{"document_id":"chicken_lawn\/howstartfoodforest4863665.txt:0","document_content":"Home & Garden Garden How to Start a Food Forest By Ilana Strauss Ilana Strauss Yale University University of Illinois at Urbana-Champaign Ilana Strauss is a journalist who began writing for the Treehugger family in 2015. Her work has been featured in The Atlantic, The Cut, New York Magazine, and other publications. Learn about our editorial process Updated July 25, 2017 Food forests are an old idea gaining traction in modern times. Ilana Strauss Home & Garden Planting Guides Indoor Gardening Urban Farms Insects Gardens and orchards may look orderly, but they don't stay that way naturally. That's why food forests --- forests made up entirely of plants that can be eated --- are becoming popular. These ecosystems take a long time to get going, but once they're in motion, they basically maintain themselves. Plus, they can provide much more food than most traditional gardens. Nimrod Hochberg, an Israeli community organizer, is building a food forest inside a Tel Aviv park. He also lives on his family's food forest in the countryside, where he helps maintains 500 acres of fruits and vegetables, all growing wildly. I sat down with Hochberg to find out how you can start one of these forests, whether you've got a huge tract of land or a small backyard. Start with the basics As with any type of gardening, know your soil before you start planting your food forest. Ilana Strauss \"The first thing you need is patience and knowledge that you are starting a long-term project,\" explained Hochberg. \"The second thing you need is a piece of land --- the bigger the better.\" It's tempting to immediately buy fruit trees and plant them, but Hochberg says the soil is the first thing you should pay attention to. \"A good farmer doesn't grow plants, he grows soil,\" Hochberg told me. In a natural environment, the dead leaves from a tree fall to the ground, slowly composting and turning into dirt. In traditional orchards, those dead leaves are frequently removed and replaced with fertilizer, but in nature, trees use thiscompost to grow. \"To create a sustainable system, you need to imitate patterns you see in nature,\" Hochberg continued. \"When we put mulch on the ground, we are imitating this natural cycle.\" So start your forest by covering your land with a heavy dose of mulch and giving it time to decompose. Remember water City planners tend to divert water into tunnels and away from towns, which can make it hard for plants to grow. So you need to figure out where your forest's water will come from. In his forest, Hochberg set up a pool to catch rainwater. The rain hits a roof first, then flows into the pool and is used to water the forest. \"It depends on where you are,\" pointed out Hochberg. If you're in Israel or California, you may need an elaborate system like this. On the other hand, if you're in Costa Rica and get too much rain, you can probably just rely on nature. Move onto the starter plants Now that your soil is composted and land watered, you're ready to start planting. But don't buy that apple tree just yet! \"First, grow plants that grow fast and easy,\" Hochberg explained. You need to start off with hardy plants, like legume trees and clovers, before you invest in more delicate trees. Let the tough plants literally grow like weeds for a few months or even a year. They'll make the area more hospitable to other plants by putting more nutrition in the soil, blocking hard winds and creating a better microclimate. \"Trees are amazing temperature moderators,\" Hochberg said. The main attraction Eventually, your food forest will yield yummy produce, like eggplants. Ilana Strauss Finally, it's time to plant those fruit trees. Pick trees that grow naturally in your area (i.e., don't try to grow oranges in New York), and plant them between your \"starter\" trees. For the first year, you'll need to pay close attention to these delicate fruit trees. Water them, add compost and just generally baby them. After a year, you'll have better soil and your trees will be stronger, so you'll be able to let them grow on their own. \"After a few years, you don't really need to maintain anything,\" Hochberg said. \"My family's forest is in its sixth year, and for about 80 percent of the trees, we don't treat anymore.\" Don't limit your forest to trees. Real forests have many different kinds of plants living in the same environment, and food forests should too. Hochberg recommends planting \"layers\" --- big trees, small trees, bushes, small plants, vines and herbs --- next to each other. You might have big pecan trees with small mulberry trees underneath them, and lettuce, broccoli, herbs and mushrooms on the ground. \"Because of the layers, you can get a lot of food,\" said Hochberg. \"You can get much more food from a food forest than from a regular orchard.\" In addition, the plants help each other. Trees give shade to vegetables, which provide mulch to trees. You might even consider getting some chickens to live in your new ecosystem so you get fresh eggs from your built-in insect eaters. \"It creates the feeling of a forest, not an orchard,\" said Hochberg. Prune out the starters Food forests can bring you closer to all the cycles of nature. Ilana Strauss After a few years, your food plants will be thriving, and you won't need the starter plants anymore. \"Take them down,\" said Hochberg. \"They've done their job.\" Building a food forest is a time-consuming process, but the results can be pretty amazing. \"You get very intimate with your land. You know every tree, you know every bush, every bug,\" said Hochberg. \"It connects you to the real world, gets you out of screens. Because nature is much more interesting.\"","parent_id":"chicken_lawn\/howstartfoodforest4863665.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"aquaponics\/Gaslift.txt:0","document_content":"A gas lift or bubble pump is a type of pump that can raise fluid between elevations by introducing gas bubbles into a vertical outlet tube; as the bubbles rise within the tube they cause a drop in the hydrostatic pressure behind them, causing the fluid to be pulled up. Gas lifts are commonly used as artificial lifts for water or oil, using compressed air or water vapor.\nGas lifts have been used for a variety of applications:\nCoffee percolators and electric drip coffeemakers use vaporized water to lift hot water\nAirlift pumps use compressed air to lift water\nPulser pumps use a subterranean air chamber to lift underground water\nSuction dredges use a variety of the gas lift called an airlift pump to vacuum mud, sand and debris\nMist lifts use vaporized water to draw seawater in ocean thermal energy conversion systems","parent_id":"aquaponics\/Gaslift.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"aquaponics\/Gaslift.txt:1","document_content":"## Petroleum industry uses\nIn the United States, gas lift is used in 10% of the oil wells that have insufficient reservoir pressure to produce the well. In the petroleum industry, the process involves injecting gas through the tubing-casing annulus. Injected gas aerates the fluid to reduce its density; the formation pressure is then able to lift the oil column and forces the fluid out of the wellbore. Gas may be injected continuously or intermittently, depending on the producing characteristics of the well and the arrangement of the gas-lift equipment.\nThe amount of gas to be injected to maximize oil production varies based on well conditions and geometries. Too much or too little injected gas will result in less than maximum production. Generally, the optimal amount of injected gas is determined by well tests, where the rate of injection is varied and liquid production (oil and perhaps water) is measured. Alternatively, mathematical models can be used to estimate the optimum gas injection rate. Such models offer significant economic benefit, since they allow one to simulate the performance of an actual or planned gas-lifted well using a digital replica of the well.\nAlthough the gas is recovered from the oil at a later separation stage, the process requires energy to drive a compressor to raise the pressure of the gas to a level where it can be re-injected.\nThe gas-lift mandrel is a device installed in the tubing string of a gas-lift well onto which or into which a gas-lift valve is fitted. There are two common types of mandrels. In a conventional gas-lift mandrel, a gas-lift valve is installed as the tubing is placed in the well. Thus, to replace or repair the valve, the tubing string must be pulled. In the side-pocket mandrel, however, the valve is installed and removed by wireline while the mandrel is still in the well, eliminating the need to pull the tubing to repair or replace the valve.\nA gas-lift valve is a device installed on (or in) a gas-lift mandrel, which in turn is put on the production tubing of a gas-lift well. Tubing and casing pressures cause the valve to open and close, thus allowing gas to be injected into the fluid in the tubing to cause the fluid to rise to the surface. In the lexicon of the industry, gas-lift mandrels are said to be \"tubing retrievable\" wherein they are deployed and retrieved attached to the production tubing. See gas-lift mandrel.\nGas lift operation can be optimized in different ways. The newest way is using risk-optimization which considers all aspects for gas lift allocation.","parent_id":"aquaponics\/Gaslift.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"neanderthals_vitamin_C_diet\/L-gulonolactone_oxidase.txt:1","document_content":"## Gulonolactone oxidase deficiency\nThe non-functional gulonolactone oxidase pseudogene (GULOP) was mapped to human chromosome 8p21, which corresponds to an evolutionarily conserved segment on either porcine chromosome 4 (SSC4) or 14 (SSC14). GULO produces the precursor to ascorbic acid, which spontaneously converts to the vitamin itself.\nThe loss of activity of the gene encoding L-gulonolactone oxidase (GULO) has occurred separately in the history of several species. GULO activity has been lost in some species of bats, but others retain it. The loss of this enzyme activity is responsible for the inability of guinea pigs to enzymatically synthesize vitamin C. Both these events happened independently of the loss in the haplorrhine suborder of primates, which includes humans.\nThe remnant of this non-functional gene with many mutations is still present in the genomes of guinea pigs and humans. It is unknown if remains of the gene exist in the bats who lack GULO activity. The function of GULO appears to have been lost several times, and possibly re-acquired, in several lines of passerine birds, where ability to make vitamin C varies from species to species.\nLoss of GULO activity in the primate order occurred about 63 million years ago, at about the time it split into the suborders Haplorhini (which lost the enzyme activity) and Strepsirrhini (which retained it). The haplorhine (\"simple-nosed\") primates, which cannot make vitamin C enzymatically, include the tarsiers and the simians (apes, monkeys and humans). The strepsirrhine (\"bent-nosed\" or \"wet-nosed\") primates, which can still make vitamin C enzymatically, include lorises, galagos, pottos, and, to some extent, lemurs.\nL-Gulonolactone oxidase deficiency has been called \"hypoascorbemia\" and is described by OMIM (Online Mendelian Inheritance in Man) as \"a public inborn error of metabolism\", as it affects all humans. There exists a wide discrepancy between the amounts of ascorbic acid other primates consume and what are recommended as \"reference intakes\" for humans. In its patently pathological form, the effects of ascorbate deficiency are manifested as scurvy.","parent_id":"neanderthals_vitamin_C_diet\/L-gulonolactone_oxidase.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"neanderthals_vitamin_C_diet\/L-gulonolactone_oxidase.txt:2","document_content":"## Consequences of loss\nIt is likely that some level of adaptation occurred after the loss of the GULO gene by primates. Erythrocyte Glut1 and associated dehydroascorbic acid uptake modulated by stomatin switch are unique traits of humans and the few other mammals that have lost the ability to synthesize ascorbic acid from glucose. As GLUT transporters and stomatin are ubiquitously distributed in different human cell types and tissues, similar interactions may occur in human cells other than erythrocytes.\nLinus Pauling observed that after the loss of endogenous ascorbate production, apo(a) and Lp(a) were greatly favored by evolution, acting as ascorbate surrogate, since the frequency of occurrence of elevated Lp(a) plasma levels in species that had lost the ability to synthesize ascorbate is great. Also, only primates share regulation of CAMP gene expression by vitamin D, which occurred after the loss of GULO gene.\nJohnson et al.\u00a0have hypothesized that the mutation of the GULOP pseudogene so that it stopped producing GULO may have been of benefit to early primates by increasing uric acid levels and enhancing fructose effects on weight gain and fat accumulation. With a shortage of food supplies this gave mutants a survival advantage.\n\n## Animal models\nStudies of human diseases have benefited from the availability of small laboratory animal models. However, the tissues of animal models with a GULO gene generally have high levels of ascorbic acid and so are often only slightly influenced by exogenous vitamin C. This is a major handicap for studies involving the endogenous redox systems of primates and other animals that lack this gene.\nGuinea pigs are a popular human model. They lost the ability to make GULO 20 million years ago.\nIn 1999, Maeda et al.\u00a0genetically engineered mice with inactivated GULO gene. The mutant mice, like humans, entirely depend on dietary vitamin C, and they show changes indicating that the integrity of their vasculature is compromised. GULO--\/-- mice have been used as a human model in multiple subsequent studies.\nThere have been successful attempts to activate lost enzymatic function in different animal species. Various GULO mutants were also identified.","parent_id":"neanderthals_vitamin_C_diet\/L-gulonolactone_oxidase.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"selection_bias\/Selectionbias.txt:0","document_content":"Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. It is sometimes referred to as the selection effect. The phrase \"selection bias\" most often refers to the distortion of a statistical analysis, resulting from the method of collecting samples. If the selection bias is not taken into account, then some conclusions of the study may be false.\n\n## Types of bias\n### Sampling bias\nSampling bias is systematic error due to a non-random sample of a population, causing some members of the population to be less likely to be included than others, resulting in a biased sample, defined as a statistical sample of a population (or non-human factors) in which all participants are not equally balanced or objectively represented. It is mostly classified as a subtype of selection bias, sometimes specifically termed sample selection bias, but some classify it as a separate type of bias.\nA distinction of sampling bias (albeit not a universally accepted one) is that it undermines the external validity of a test (the ability of its results to be generalized to the rest of the population), while selection bias mainly addresses internal validity for differences or similarities found in the sample at hand. In this sense, errors occurring in the process of gathering the sample or cohort cause sampling bias, while errors in any process thereafter cause selection bias.\nExamples of sampling bias include self-selection, pre-screening of trial participants, discounting trial subjects\/tests that did not run to completion and migration bias by excluding subjects who have recently moved into or out of the study area, length-time bias, where slowly developing disease with better prognosis is detected, and lead time bias, where disease is diagnosed earlier for participants than in comparison populations, although the average course of disease is the same.\n\n### Time interval\nEarly termination of a trial at a time when its results support the desired conclusion.\nA trial may be terminated early at an extreme value (often for ethical reasons), but the extreme value is likely to be reached by the variable with the largest variance, even if all variables have a similar mean.","parent_id":"selection_bias\/Selectionbias.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"selection_bias\/Selectionbias.txt:1","document_content":"## Types of bias\n### Exposure\nSusceptibility bias\nClinical susceptibility bias, when one disease predisposes for a second disease, and the treatment for the first disease erroneously appears to predispose to the second disease. For example, postmenopausal syndrome gives a higher likelihood of also developing endometrial cancer, so estrogens given for the postmenopausal syndrome may receive a higher than actual blame for causing endometrial cancer.\nProtopathic bias, when a treatment for the first symptoms of a disease or other outcome appear to cause the outcome. It is a potential bias when there is a lag time from the first symptoms and start of treatment before actual diagnosis. It can be mitigated by lagging, that is, exclusion of exposures that occurred in a certain time period before diagnosis.\nIndication bias, a potential mixup between cause and effect when exposure is dependent on indication, e.g.\u00a0a treatment is given to people in high risk of acquiring a disease, potentially causing a preponderance of treated people among those acquiring the disease. This may cause an erroneous appearance of the treatment being a cause of the disease.\n\n### Data\nPartitioning (dividing) data with knowledge of the contents of the partitions, and then analyzing them with tests designed for blindly chosen partitions.\nPost hoc alteration of data inclusion based on arbitrary or subjective reasons, including:\nCherry picking, which actually is not selection bias, but confirmation bias, when specific subsets of data are chosen to support a conclusion (e.g.\u00a0citing examples of plane crashes as evidence of airline flight being unsafe, while ignoring the far more common example of flights that complete safely. See: availability heuristic)\nRejection of bad data on (1) arbitrary grounds, instead of according to previously stated or generally agreed criteria or (2) discarding \"outliers\" on statistical grounds that fail to take into account important information that could be derived from \"wild\" observations.\n\n### Studies\nSelection of which studies to include in a meta-analysis (see also combinatorial meta-analysis).\nPerforming repeated experiments and reporting only the most favorable results, perhaps relabelling lab records of other experiments as \"calibration tests\", \"instrumentation errors\" or \"preliminary surveys\".\nPresenting the most significant result of a data dredge as if it were a single experiment (which is logically the same as the previous item, but is seen as much less dishonest).","parent_id":"selection_bias\/Selectionbias.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"selection_bias\/Selectionbias.txt:2","document_content":"## Types of bias\n### Attrition\nAttrition bias is a kind of selection bias caused by attrition (loss of participants), discounting trial subjects\/tests that did not run to completion. It is closely related to the survivorship bias, where only the subjects that \"survived\" a process are included in the analysis or the failure bias, where only the subjects that \"failed\" a process are included. It includes dropout, nonresponse (lower response rate), withdrawal and protocol deviators. It gives biased results where it is unequal in regard to exposure and\/or outcome. For example, in a test of a dieting program, the researcher may simply reject everyone who drops out of the trial, but most of those who drop out are those for whom it was not working. Different loss of subjects in intervention and comparison group may change the characteristics of these groups and outcomes irrespective of the studied intervention.\nLost to follow-up, is another form of Attrition bias, mainly occurring in medicinal studies over a lengthy time period. Non-Response or Retention bias can be influenced by a number of both tangible and intangible factors, such as; wealth, education, altruism, initial understanding of the study and its requirements. Researchers may also be incapable of conducting follow-up contact resulting from inadequate identifying information and contact details collected during the initial recruitment and research phase.\n\n### Observer selection\nPhilosopher Nick Bostrom has argued that data are filtered not only by study design and measurement, but by the necessary precondition that there has to be someone doing a study. In situations where the existence of the observer or the study is correlated with the data, observation selection effects occur, and anthropic reasoning is required.\nAn example is the past impact event record of Earth: if large impacts cause mass extinctions and ecological disruptions precluding the evolution of intelligent observers for long periods, no one will observe any evidence of large impacts in the recent past (since they would have prevented intelligent observers from evolving). Hence there is a potential bias in the impact record of Earth. Astronomical existential risks might similarly be underestimated due to selection bias, and an anthropic correction has to be introduced.","parent_id":"selection_bias\/Selectionbias.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"selection_bias\/Selectionbias.txt:3","document_content":"## Types of bias\n### Volunteer bias\nSelf-selection bias or a volunteer bias in studies offer further threats to the validity of a study as these participants may have intrinsically different characteristics from the target population of the study. Studies have shown that volunteers tend to come from a higher social standing than from a lower socio-economic background. Furthermore, another study shows that women are more probable to volunteer for studies than males. Volunteer bias is evident throughout the study life-cycle, from recruitment to follow-ups. More generally speaking volunteer response can be put down to individual altruism, a desire for approval, personal relation to the study topic and other reasons. As with most instances mitigation in the case of volunteer bias is an increased sample size.\n\n## Mitigation\nIn the general case, selection biases cannot be overcome with statistical analysis of existing data alone, though Heckman correction may be used in special cases. An assessment of the degree of selection bias can be made by examining correlations between exogenous (background) variables and a treatment indicator. However, in regression models, it is correlation between unobserved determinants of the outcome and unobserved determinants of selection into the sample which bias estimates, and this correlation between unobservables cannot be directly assessed by the observed determinants of treatment.\nWhen data are selected for fitting or forecast purposes, a coalitional game can be set up so that a fitting or forecast accuracy function can be defined on all subsets of the data variables.\n\n## Related issues\nSelection bias is closely related to:\npublication bias or reporting bias, the distortion produced in community perception or meta-analyses by not publishing uninteresting (usually negative) results, or results which go against the experimenter's prejudices, a sponsor's interests, or community expectations.\nconfirmation bias, the general tendency of humans to give more attention to whatever confirms our pre-existing perspective; or specifically in experimental science, the distortion produced by experiments that are designed to seek confirmatory evidence instead of trying to disprove the hypothesis.\nexclusion bias, results from applying different criteria to cases and controls in regards to participation eligibility for a study\/different variables serving as basis for exclusion.","parent_id":"selection_bias\/Selectionbias.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"odometry_trajectory\/PlotJuggler.txt:0","document_content":"Gold Sponsor: Greenzie\nPlotJuggler is a tool to visualize time series that is fast, powerful and intuitive.\nNoteworthy features:\n- Simple Drag & Drop user interface.\n- Load data from file.\n- Connect to live streaming of data.\n- Save the visualization layout and configurations to re-use them later.\n- Fast OpenGL visualization.\n- Can handle thousands of timeseries and millions of data points.\n- Transform your data using a simple editor: derivative, moving average, integral, etc...\n- PlotJuggler can be easily extended using plugins.\n<!-- -->\n- Load CSV files.\n- Load ULog (PX4).\n- Subscribe to many different streaming sources: MQTT, WebSockets, ZeroMQ, UDP, etc.\n- Understand data formats such as JSON, CBOR, BSON, Message Pack, etc.\n- Well integrated with ROS: open rosbags and\/or subscribe to ROS topics (both ROS1 and ROS2).\n- Supports the Lab Streaming Layer, that is used by many devices.\n- Easily add your custom data source and\/or formats...\nPlotJuggler makes it easy to visualize data but also to analyze it. You can manipulate your time series using a simple and extendable Transform Editor.\nAlternatively, you may use the Custom Function Editor, which allows you to create Multi-input \/ Single-output functions using a scripting language based on Lua.\nIf you are not familiar with Lua, don't be afraid, you won't need more than 5 minutes to learn it ;)\nTo learn how to use PlotJuggler, check the tutorials here:\nTutorial 1\nTutorial 2\nTutorial 3\nSome plugins can be found in a different repository. The individual README files should include all the information needed to compile and use the plugin.\nPlease submit specific issues, Pull Requests and questions on the related Github repository:\nIf you want a simple example to learn how to write your own plugins, have a look at PlotJuggler\/plotjuggler-sample-plugins\nThe snap contains a version of PlotJuggler that can work with either ROS1 or ROS2.\nTo install it in Ubuntu 22.04, with ROS2 support, run:\n          sudo snap install plotjuggler","parent_id":"odometry_trajectory\/PlotJuggler.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"odometry_trajectory\/PlotJuggler.txt:1","document_content":"If you are still using ROS1 (Ubuntu 20.04), install instead:\n          sudo snap install plotjuggler-ros\nThis installer does not include ROS plugins.\nWindows Installer: PlotJuggler-Windows-3.9.3-installer\nInstall the ROS packages with:\n          sudo apt install ros-$ROS_DISTRO-plotjuggler-ros\nTo launch PlotJuggler on ROS, use the command:\n          rosrun plotjuggler plotjuggler\nor, if are using ROS2:\n          ros2 run plotjuggler plotjuggler\nROS plugins are available in a separate repository: https:\/\/github.com\/PlotJuggler\/plotjuggler-ros-plugins\nPlease take a look at the instructions in that repository if you want to compile PJ and its ROS plugins from source.\nYou can find the detailed instructions here: COMPILE.md.\nPlotJuggler required a lot of work to develop and maintain; my goal is to build the most intuitive and powerful tool to visualize data and timeseries.\nIf you find PlotJuggler useful, consider donating PayPal or becoming a Github Sponsor.\nIf you need to extend any of the functionalities of PlotJuggler to cover a specific need or to parse your custom data formats, you can receive commercial support from the main author, Davide Faconti.\nPlotJuggler is released under the Mozilla Public License Version 2.0, which allows users to develop closed-source plugins.\nPlease note that some third-party dependencies (including Qt) use the GNU Lesser General Public License.","parent_id":"odometry_trajectory\/PlotJuggler.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"meal_kit\/comparisonlifecycleenvironmentalimpactsmealkitsand.txt:0","document_content":"## Comparison of Life Cycle Environmental Impacts from Meal Kits and Grocery Store Meals\nMeal kits contain ingredients for cooking a meal that are pre-portioned, packaged, and delivered to a consumer's residence. Life cycle environmental impacts associated with climate change, acidification, eutrophication, land use, and water use are compared for five dinner recipes sourced as meal kits and through grocery store retailing. Inventory data are obtained from direct measurement of ingredients and packaging, supplemented with literature data for supply chain and production parameters. Results indicate that, on average, grocery meal greenhouse gas emissions are 33% higher than meal kits (8.1 kg CO2e\/meal compared with 6.1 kg CO2e\/meal kit). Other impact categories follow similar trends. A Monte Carlo analysis finds higher median emissions for grocery meals than meal kits for four out of five meals, occurring in 100% of model runs for two of five meals. Results suggest that meal kits' streamlined and direct-to-consumer supply chains (-1.05 kg CO2e\/meal), reduced food waste (-0.86 kg CO2e\/meal), and lower last-mile transportation emissions (-0.45 kg CO2e\/meal), appear to be sufficient to offset observed increases in packaging (0.17 kg CO2e\/meal). Additionally, meal kit refrigeration packs present an average emissions decrease compared with retail refrigeration (-0.37 kg CO2e\/meal). Meals with the largest environmental impact either contain red meat or are associated with large amounts of wasted food. The one meal kit with higher emissions is due to food mass differences rather than supply chain logistics. Meal kits are an evolving mode for food supply, and the environmental effects of potential changes to meal kit provision and grocery retailing are discussed.","parent_id":"meal_kit\/comparisonlifecycleenvironmentalimpactsmealkitsand.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"Irreversibility\/Irreversibleprocess.txt:0","document_content":"In thermodynamics, an irreversible process is a process that cannot be undone. All complex natural processes are irreversible, although a phase transition at the coexistence temperature (e.g.\u00a0melting of ice cubes in water) is well approximated as reversible.\nA change in the thermodynamic state of a system and all of its surroundings cannot be precisely restored to its initial state by infinitesimal changes in some property of the system without expenditure of energy. A system that undergoes an irreversible process may still be capable of returning to its initial state. Because entropy is a state function, the change in entropy of the system is the same whether the process is reversible or irreversible. However, the impossibility occurs in restoring the environment to its own initial conditions. An irreversible process increases the total entropy of the system and its surroundings. The second law of thermodynamics can be used to determine whether a hypothetical process is reversible or not.\nIntuitively, a process is reversible if there is no dissipation. For example, Joule expansion is irreversible because initially the system is not uniform. Initially, there is part of the system with gas in it, and part of the system with no gas. For dissipation to occur, there needs to be such a non uniformity. This is just the same as if in a system one section of the gas was hot, and the other cold. Then dissipation would occur; the temperature distribution would become uniform with no work being done, and this would be irreversible because you couldn't add or remove heat or change the volume to return the system to its initial state. Thus, if the system is always uniform, then the process is reversible, meaning that you can return the system to its original state by either adding or removing heat, doing work on the system, or letting the system do work. As another example, to approximate the expansion in an internal combustion engine as reversible, we would be assuming that the temperature and pressure uniformly change throughout the volume after the spark. Obviously, this is not true and there is a flame front and sometimes even engine knocking. One of the reasons that Diesel engines are able to attain higher efficiency is that the combustion is much more uniform, so less energy is lost to dissipation and the process is closer to reversible.\nThe phenomenon of irreversibility results from the fact that if a thermodynamic system, which is any system of sufficient complexity, of interacting molecules is brought from one thermodynamic state to another, the configuration or arrangement of the atoms and molecules in the system will change in a way that is not easily predictable. Some \"transformation energy\" will be used as the molecules of the \"working body\" do work on each other when they change from one state to another. During this transformation, there will be some heat energy loss or dissipation due to intermolecular friction and collisions. This energy will not be recoverable if the process is reversed.\nMany biological processes that were once thought to be reversible have been found to actually be a pairing of two irreversible processes. Whereas a single enzyme was once believed to catalyze both the forward and reverse chemical changes, research has found that two separate enzymes of similar structure are typically needed to perform what results in a pair of thermodynamically irreversible processes.","parent_id":"Irreversibility\/Irreversibleprocess.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"gdp_wellbeing\/wellbeingandgdphtm.txt:0","document_content":"## Well-being and GDP: why we need them both\nBy Romina Boarini, OECD\nMeasuring well-being is about going beyond the cold numbers of GDP. But cold as it may be, GDP remains a very important indicator for measuring the economic performance of countries, which is a fundamental driver of well-being. This is not only because income means higher material standards but also because income is needed to sustain private and public spending in non-material components of well-being, such as education and health. However, there is an increasing recognition that focusing on GDP alone is not enough to achieve better lives for all.\nThe chart below demonstrates this by showing a country's s GDP per capita alongside its performance on the OECD Better Life Index. The relationship is positive -- in other words, countries with higher GDP per capita are also those where well-being is higher on average. However this relationship becomes weaker as a country's income grows, suggesting that once income reaches a certain level, increased income is less likely to generate well-being. The other interesting feature of this chart is that some countries do better at delivering wellbeing as measured by the Better Life Index than they do if gauged only on the basis of economic production per capita. This is the case for all the Nordic European countries but also for New Zealand. On the other hand, there are countries that do better in GDP per capita than on average well-being, for instance the United States and Switzerland.\nSo why in these two sets of countries do economic performance and well-being not go strictly hand in hand? One explanation is that the countries that do better in terms of well-being have made the choice of working less to achieve a better work and life balance. This translates into lower income but also increased leisure time that can be shared with friends and family, or that is used for volunteering and engaging with the community. Another reason is that these countries have better environmental quality, partly because of lower economic production and thus pollution. Well-being is a matter of democracy and societal choices, what really matters at the end of the day is whether countries are where their citizens would like them to be. It can be higher economic production or more time for life, longer healthy lives or more connected neighbourhoods. What is important is to collect the relevant set of statistics to judge whether collective objectives are met and ensure that governments are paying the righight degree of attention to these statistics.\nNote: Norway refers to mainland GDP per capita","parent_id":"gdp_wellbeing\/wellbeingandgdphtm.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"matching_price\/matchingordersasp.txt:0","document_content":"## What Are Matching Orders?\nMatching orders is the process by which a securities exchange pairs one or more unsolicited buy orders to one or more sell orders to make trades. This can be contrasted with requests for a quote (RFQ) in a security to proceed with a trade.\nIf one investor wants to buy a quantity of stock and another wants to sell the same quantity at the same price, their orders match, and a transaction is effected. The work of pairing these orders is the process of order matching whereby exchanges identify buy orders, or bids, with corresponding sell orders, or asks, to execute them. Over the past decade, this process has become almost entirely automated.\n\n### Key Takeaways\n- Matching orders is the process of identifying and effecting a trade between equal and opposite requests for a security (i.e., a buy and a sale at the same price).\n- Order matching is how many exchanges pair buyers and sellers at compatible prices for efficient and orderly trading.\n- Over the past decade, this process has become almost entirely automated.\n\n## How Matching Orders Works\nMatching the orders of buyers and sellers is the primary work of specialists and market makers in the exchanges. The matches happen when compatible buy orders and sell orders for the same security are submitted in close proximity in price and time.\nGenerally, a buy order and a sell order are compatible if the maximum price of the buy order matches or exceeds the minimum price of the sell order. From there, the computerized, order-matching systems of different exchanges use a variety of methods to prioritize orders for matching.\n\n### Fast Fact\nToday, most exchanges match orders using computer algorithms; but historically, brokers matched orders through face-to-face interactions on a trading floor in an open-outcry auction.\nQuick, accurate order matching is a critical component of an exchange. Investors, particularly active investors and day traders, will look for ways to minimize inefficiencies in trading from every possible source. A slow order-matching system may cause buyers or sellers to execute trades at less-than-ideal prices, eating into investors' profits. If some order-matching protocols tend to favor buyers, and others favor sellers, these methods become exploitable.\nThis is one of the areas where high-frequency trading (HFT) was able to improve efficiency. Exchanges aim to prioritize trades in a way that benefits buyers and sellers equally so as to maximize order volume---the lifeblood of the exchange.","parent_id":"matching_price\/matchingordersasp.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"matching_price\/matchingordersasp.txt:1","document_content":"## Popular Algorithms for Matching Orders\nAll major markets have transitioned to electronic matching. Each securities exchange uses its own specific algorithm to match orders. Broadly, they fall under two categories: first-in-first-out (FIFO) and pro-rata.\n\n### FIFO\nUnder a basic FIFO algorithm, or price-time-priority algorithm, the earliest active buy order at the highest price takes priority over any subsequent order at that price, which in turn takes priority over any active buy order at a lower price. For example, if a buy order for 200 shares of stock at \\$90 per share precedes an order for 50 shares of the same stock at the same price, the system must match the entire 200-share order to one or more sell orders before beginning to match any portion of the 50-share order.\n\n### Pro-Rata\nUnder a basic pro-rata algorithm, the system prioritizes active orders at a particular price, proportional to the relative size of each order. For example, if both a 200-share buy order and a 50-share buy order at the same price are active when a compatible 200-share sell order arrives, the system will match 160 shares to the 200-share buy order and 40 shares to the 50-share buy order.\nSince the sell order is not large enough to fulfill both buy orders, the system will partially fill both. In this case, the pro-rata matching algorithm fills 80 percent of each order.","parent_id":"matching_price\/matchingordersasp.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"electrical_shock_freeze_up_muscles\/Tetanic_contraction.txt:0","document_content":"A tetanic contraction (also called tetanized state, tetanus, or physiologic tetanus, the latter to differentiate from the disease called tetanus) is a sustained muscle contraction evoked when the motor nerve that innervates a skeletal muscle emits action potentials at a very high rate. During this state, a motor unit has been maximally stimulated by its motor neuron and remains that way for some time. This occurs when a muscle's motor unit is stimulated by multiple impulses at a sufficiently high frequency. Each stimulus causes a twitch. If stimuli are delivered slowly enough, the tension in the muscle will relax between successive twitches. If stimuli are delivered at high frequency, the twitches will overlap, resulting in tetanic contraction. A tetanic contraction can be either unfused (incomplete) or fused (complete). An unfused tetanus is when the muscle fibers do not completely relax before the next stimulus because they are being stimulated at a fast rate; however there is a partial relaxation of the muscle fibers between the twitches. Fused tetanus is when there is no relaxation of the muscle fibers between stimuli and it occurs during a high rate of stimulation. A fused tetanic contraction is the strongest single-unit twitch in contraction. When tetanized, the contracting tension in the muscle remains constant in a steady state. This is the maximal possible contraction. During tetanic contractions, muscles can shorten, lengthen or remain constant length.\nTetanic contraction is usually normal (such as when holding up a heavy box). Muscles often exhibit some level of tetanic activity, leading to muscle tone, in order to maintain posture; for example, in a crouching position, some muscles require sustained contraction to hold the position. Tetanic contraction can exist in a variety of states, including isotonic and isometric forms---for example, lifting a heavy box off the floor is isotonic, but holding it at the elevated position is isometric. Isotonic contractions place muscles in a constant tension but the muscle length changes, while isometric contractions hold a constant muscle length.\nVoluntary sustained contraction is a normal (physiologic) process (as in the crouching or box-holding examples), but involuntary sustained contraction exists on a spectrum from physiologic to disordered (pathologic). Muscle tone is a healthy form of involuntary sustained partial contraction. In comparison with tetanic contraction in an isometric state (such as holding up a heavy box for several minutes), it differs only in the percentage of motor units participating at any moment and the frequency of neural signals; but the low percentage and low frequency in healthy tone are the key factors defining it as healthy (and not tetanic). Involuntary sustained contraction of a hypertonic type, however, is a pathologic process. On the mild part of the spectrum, cramps, spasms, and even tetany are often temporary and nonsevere. On the moderate to severe parts of the spectrum are dystonia, trismus, pathologic tetanus, and other movement disorders featuring involuntary sustained strong contractions of skeletal muscle.","parent_id":"electrical_shock_freeze_up_muscles\/Tetanic_contraction.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"data_center_heat\/wasteheatenergyreusehtml.txt:0","document_content":"# High-Performance Computing Data Center Waste Heat Reuse\nAt the Energy Systems Integration Facility (ESIF), heat exchangers in the High-Performance Computing Data Center enable the reuse of energy from computing waste heat.\nWith heat exchangers, heat energy in the energy recovery water (ERW) loop becomes available to heat the facility's process hot water (PHW) loop. Once heated, the PHW loop supplies:\n- Active chilled beams to heat the office space\n- Air handlers to heat the conference and high bay spaces\n- Snow melt loop in the courtyard of the ESIF's main entrance\n- District heating loop:\n  - If additional heat is needed for the building, the PHW loop can draw heat from the campus heating loop\n  - If surplus heat is available, the PHW loop can provide heat to the campus heating loop. During transition months (April and October), excess heat from the ESIF has been sufficient to provide heat for other buildings, shortening the time boilers are needed to provide campus heat.\nShare","parent_id":"data_center_heat\/wasteheatenergyreusehtml.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"eyes_tired\/Computer_vision_syndrome.txt:0","document_content":"Computer vision syndrome (CVS) is a condition resulting from focusing the eyes on a computer or other display device for protracted, uninterrupted periods of time and the eye's muscles being unable to recover from the constant tension required to maintain focus on a close object.\n\n## Symptoms\nSome symptoms of CVS include headaches, blurred vision, neck pain, fatigue, eye strain, dry eyes, irritated eyes, double vision, vertigo\/dizziness, polyopia, and difficulty refocusing the eyes. These symptoms can be further aggravated by improper lighting conditions (i.e.\u00a0glare, strong blue-spectrum backlights, or bright overhead lighting) or air moving past the eyes (e.g.\u00a0overhead vents, or direct air from a fan).","parent_id":"eyes_tired\/Computer_vision_syndrome.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"men_women_science\/19883140.txt:0","document_content":"# Men and things, women and people: a meta-analysis of sex differences in interests\n- PMID: 19883140\n- DOI: 10.1037\/a0017364\n\n## Abstract\nThe magnitude and variability of sex differences in vocational interests were examined in the present meta-analysis for Holland's (1959, 1997) categories (Realistic, Investigative, Artistic, Social, Enterprising, and Conventional), Prediger's (1982) Things-People and Data-Ideas dimensions, and the STEM (science, technology, engineering, and mathematics) interest areas. Technical manuals for 47 interest inventories were used, yielding 503,188 respondents. Results showed that men prefer working with things and women prefer working with people, producing a large effect size (d = 0.93) on the Things-People dimension. Men showed stronger Realistic (d = 0.84) and Investigative (d = 0.26) interests, and women showed stronger Artistic (d = -0.35), Social (d = -0.68), and Conventional (d = -0.33) interests. Sex differences favoring men were also found for more specific measures of engineering (d = 1.11), science (d = 0.36), and mathematics (d = 0.34) interests. Average effect sizes varied across interest inventories, ranging from 0.08 to 0.79. The quality of interest inventories, based on professional reputation, was not differentially related to the magnitude of sex differences. Moderators of the effect sizes included interest inventory item development strategy, scoring method, theoretical framework, and sample variables of age and cohort. Application of some item development strategies can substantially reduce sex differences. The present study suggests that interests may play a critical role in gendered occupational choices and gender disparity in the STEM fields.","parent_id":"men_women_science\/19883140.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fresh_air_car\/useherbsasanallnaturalairfreshener5944860.txt:0","document_content":"If you've ever grown fresh herbs, you know that some plants just grow and grow---sometimes faster than you can eat them. Thankfully, eating them isn't the only thing you can do. Consider using fresh aromatic herbs like basil and rosemary as an all-natural air freshener for your car or another small space.\nThis tip comes to us from the folks at Stylist, which suggests using Basil to freshen your car by putting some fresh basil leaves on a piece of newspaper and just letting it dry itself out in the back of your car. The windows make it a natural greenhouse, so as the basil dries, the delicious smell will spread through your vehicle---it's much better than the gym socks in the backseat or the lingering smell of fast food from your last McDonald's stop.\nThe idea got us thinking though: why stop with basil? Rosemary, tarragon, and thyme are just as aromatic, and can work just as well. Plus, there's no reason to stop with your car: as long as you have a space that will get some light (and therefore heat), the herbs will dry nicely and smell great. Put a few leaves on some newspaper and rest them on your windowsill in your home office, and you'll have a natural air freshener that's perfect for small spaces (large spaces need not apply, obviously.) Just be careful, the smell might make you hungry.\nHow to Remove Car Odors with Basil \\| Stylist\nPhoto by Chris Pillen.","parent_id":"fresh_air_car\/useherbsasanallnaturalairfreshener5944860.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"shut_down_conciousness\/Neocortex.txt:0","document_content":"The neocortex, also called the neopallium, isocortex, or the six-layered cortex, is a set of layers of the mammalian cerebral cortex involved in higher-order brain functions such as sensory perception, cognition, generation of motor commands, spatial reasoning, and language. The neocortex is further subdivided into the true isocortex and the proisocortex.\nIn the human brain, the cerebral cortex consists of the larger neocortex and the smaller allocortex, respectively taking up 90% and 10%. The neocortex is made up of six layers, labelled from the outermost inwards, I to VI.\n\n## Etymology\nThe term is from cortex, Latin, \"bark\" or \"rind\", combined with neo-, Greek, \"new\". Neopallium is a similar hybrid, from Latin pallium, \"cloak\". Isocortex and allocortex are hybrids with Greek isos, \"same\", and allos, \"other\".\n\n## Anatomy\nThe neocortex is the most developed in its organisation and number of layers, of the cerebral tissues. The neocortex consists of the grey matter, or neuronal cell bodies and unmyelinated fibers, surrounding the deeper white matter (myelinated axons) in the cerebrum. This is a very thin layer though, about 2--4 mm thick. There are two types of cortex in the neocortex, the proisocortex and the true isocortex. The pro-isocortex is a transitional area between the true isocortex and the periallocortex (part of the allocortex). It is found in the cingulate cortex (part of the limbic system), in Brodmann's areas 24, 25, 30 and 32, the insula and the parahippocampal gyrus.\nOf all the mammals studied to date (including humans), a species of oceanic dolphin known as the long-finned pilot whale has been found to have the most neocortical neurons.","parent_id":"shut_down_conciousness\/Neocortex.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"shut_down_conciousness\/Neocortex.txt:2","document_content":"## Anatomy\n### Cortical columns\nThe neocortex is often described as being arranged in vertical structures called cortical columns, patches of neocortex with a diameter of roughly 0.5 mm (and a depth of 2 mm, i.e., spanning all six layers). These columns are often thought of as the basic repeating functional units of the neocortex, but their many definitions, in terms of anatomy, size, or function, are generally not consistent with each other, leading to a lack of consensus regarding their structure or function or even whether it makes sense to try to understand the neocortex in terms of columns.\n\n## Function\nThe neocortex is derived embryonically from the dorsal telencephalon, which is the rostral part of the forebrain. The neocortex is divided into regions demarcated by the cranial sutures in the skull above, into frontal, parietal, occipital, and temporal lobes, which perform different functions. For example, the occipital lobe contains the primary visual cortex, and the temporal lobe contains the primary auditory cortex. Further subdivisions or areas of neocortex are responsible for more specific cognitive processes. In humans, the frontal lobe contains areas devoted to abilities that are enhanced in or unique to our species, such as complex language processing localized to the ventrolateral prefrontal cortex (Broca's area). In humans and other primates, social and emotional processing is localized to the orbitofrontal cortex.\nThe neocortex has also been shown to play an influential role in sleep, memory and learning processes. Semantic memories appear to be stored in the neocortex, specifically the anterolateral temporal lobe of the neocortex. It is also involved in instrumental conditioning; responsible for transmitting sensory information and information about plans for movement to the basal ganglia. The firing rate of neurons in the neocortex also has an effect on slow-wave sleep. When the neurons are at rest and are hyperpolarizing, a period of inhibition occurs during a slow oscillation, called the down state. When the neurons of the neocortex are in the excitatory depolarizing phase and are firing briefly at a high rate, a period of excitation occurs during a slow oscillation, called the up state.","parent_id":"shut_down_conciousness\/Neocortex.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"ring_finger_not_move\/Extrinsic_extensor_muscles_of_the_hand.txt:0","document_content":"The extrinsic extensor muscles of the hand are located in the back of the forearm and have long tendons connecting them to bones in the hand, where they exert their action. Extrinsic denotes their location outside the hand. Extensor denotes their action which is to extend, or open flat, joints in the hand. They include the extensor carpi radialis longus (ECRL), extensor carpi radialis brevis (ECRB), extensor digitorum (ED), extensor digiti minimi (EDM), extensor carpi ulnaris (ECU), abductor pollicis longus (APL), extensor pollicis brevis (EPB), extensor pollicis longus (EPL), and extensor indicis (EI).","parent_id":"ring_finger_not_move\/Extrinsic_extensor_muscles_of_the_hand.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"ring_finger_not_move\/Extrinsic_extensor_muscles_of_the_hand.txt:3","document_content":"## Extensor digitorum tendons\nThe ED tendons are more complex in their course. Opposite the metacarpophalangeal joint each tendon is bound by fasciculi to the collateral ligaments and serves as the dorsal ligament of this joint; after having crossed the joint, it spreads out into a broad aponeurosis, which covers the dorsal surface of the first phalanx and is reinforced, in this situation, by the tendons of the Interossei and Lumbricalis.\nOpposite the first interphalangeal joints this aponeurosis divides into three slips; an intermediate and two collateral: the former is inserted into the base of the second phalanx; and the two collateral, which are continued onward along the sides of the second phalanx, unite by their contiguous margins, and are inserted into the dorsal surface of the last phalanx. As the tendons cross the interphalangeal joints, they furnish them with dorsal ligaments. The tendon to the index finger is accompanied by the EI, which lies on its ulnar side. On the back of the hand, the tendons to the middle, ring, and little fingers are connected by two obliquely placed bands, one from the third tendon passing downward and lateralward to the second tendon, and the other passing from the same tendon downward and medialward to the fourth.\nOccasionally the first tendon is connected to the second by a thin transverse band. Collectively, these are known as the sagittal bands; they serve to maintain the central alignment of the extensor tendons over the metacarpal head, thus increasing the available leverage. Injuries (such as by an external flexion force during active extension) may allow the tendon to dislocate into the intermetacarpal space; the extensor tendon then acts as a flexor and the finger may no longer be actively extended. This may be corrected surgically by using a slip of the extensor tendon to replace the damaged ligamentous band\n\n## Anatomical snuff box\nThe EPL tendon crosses obliquely the tendons of the ECRL and ECRB, and is separated from the EPB by a triangular interval, the anatomical snuff box, in which the radial artery is found.","parent_id":"ring_finger_not_move\/Extrinsic_extensor_muscles_of_the_hand.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"ring_finger_not_move\/Extrinsic_extensor_muscles_of_the_hand.txt:4","document_content":"## Insertion and action\nThe ECRL inserts into the dorsal surface of the base of the second metacarpal bone on its radial side to extend and abduct the wrist. The ECRB inserts into the lateral dorsal surface of the base of the third metacarpal bone, with a few fibres inserting into the medial dorsal surface of the second metacarpal bone, also to extend and abduct the wrist. The ED inserts into the middle and distal phalanges to extend the fingers and wrist. Opposite the head of the second metacarpal bone, the EI joins the ulnar side of the ED tendon to extend the index finger. The EDM has a similar role for the little finger. The ECU inserts at the base of the 5th metacarpal to extend and adduct the wrist. The APL inserts into the radial side of the base of the first metacarpal bone to abduct the thumb at the carpometacarpal joint and may continue to abduct the wrist. The EPB inserts into the base of the first phalanx of the thumb to extend and abduct the thumb at the carpometacarpal and MCP joints.\nThe EPL inserts on the base of the distal phalanx of the thumb. It uses the dorsal tubercle on the radius as fulcrum to help the EPB with its action as well as extending the distal phalanx of the thumb. Because the index finger and little finger have separate extensors, these fingers can be moved more independently than the other fingers.\n\n## Neurovascular supply\nThe ECU is supplied by the ulnar artery. The APL, EPB, EPL, EI, ED, and EDM are supplied by the Posterior interosseous artery, a branch of the ulnar artery. The ECRL and ECRB receive blood from the radial artery.\nThe ECRL is supplied by the radial nerve and the ECRB by its deep branch. The remaining extrinsic hand extensors are supplied by the posterior interosseus nerve, another branch of the radial nerve.\n\n## See also\nExtensor digitorum reflex","parent_id":"ring_finger_not_move\/Extrinsic_extensor_muscles_of_the_hand.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"treatment_difference\/180309015.txt:0","document_content":"# Economics \\> Econometrics\n\\[Submitted on 23 Mar 2018 (v1), last revised 1 Dec 2020 (this version, v4)\\]\n\n# Title:Difference-in-Differences with Multiple Time Periods\nView PDF\n> Abstract:In this article, we consider identification, estimation, and inference procedures for treatment effect parameters using Difference-in-Differences (DiD) with (i) multiple time periods, (ii) variation in treatment timing, and (iii) when the \"parallel trends assumption\" holds potentially only after conditioning on observed covariates. We show that a family of causal effect parameters are identified in staggered DiD setups, even if differences in observed characteristics create non-parallel outcome dynamics between groups. Our identification results allow one to use outcome regression, inverse probability weighting, or doubly-robust estimands. We also propose different aggregation schemes that can be used to highlight treatment effect heterogeneity across different dimensions as well as to summarize the overall effect of participating in the treatment. We establish the asymptotic properties of the proposed estimators and prove the validity of a computationally convenient bootstrap procedure to conduct asymptotically valid simultaneous (instead of pointwise) inference. Finally, we illustrate the relevance of our proposed tools by analyzing the effect of the minimum wage on teen employment from 2001--2007. Open-source software is available for implementing the proposed methods.\n\n## Submission history\nFrom: Pedro H. C. Sant'Anna \\[view email\\]\n\\[v1\\] Fri, 23 Mar 2018 23:45:05 UTC (132 KB)\n\\[v2\\] Fri, 31 Aug 2018 19:30:23 UTC (758 KB)\n\\[v3\\] Tue, 18 Aug 2020 03:32:06 UTC (65 KB)\n\\[v4\\] Tue, 1 Dec 2020 16:15:59 UTC (884 KB)\nCurrent browse context:\necon.EM\n\n# Bibliographic and Citation Tools\nBibliographic Explorer (What is the Explorer?)\nConnected Papers (What is Connected Papers?)\nLitmaps (What is Litmaps?)\nscite Smart Citations (What are Smart Citations?)\n\n# Code, Data and Media Associated with this Article\nalphaXiv (What is alphaXiv?)\nCatalyzeX Code Finder for Papers (What is CatalyzeX?)","parent_id":"treatment_difference\/180309015.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"meat_chicken\/Feedconversionrateforchickens.txt:0","document_content":"Although it sounds esoteric, the feed conversion rate is at the heart of raising a sustainable chicken.\u00a0 Also known as the feed to meat ratio, this number is simply the pounds of feed given to a chicken divided by the weight of the cleaned carcass.\\\nThe sad truth is that the feed conversion rate for chickens raised by nearly all backyard hobbyists is two, three, or even four times as high as the ratio for industrial chickens.\u00a0 Yes, you do end up with a higher quality chicken that lived a happier life if you raise it yourself, but that\\\nchicken will not only take more money out of your pocket than buying one from the store would, your homegrown chicken will also have a larger environmental footprint.\u00a0 In my mind, that's unsustainable.\nLet's look at some feed to meat conversion ratios:\n- 2 : 1 --- what the industry claims they get for factory farmed Cornish Cross.\\\n  (Hard to tell if this is true. My other numbers come from extension service websites or my own experience, both of which I trust more.)\n- 3.5 : 1 --- what you can expect to get from pastured Cornish Cross in optimum weather.\n- 5.2 : 1 --- Freedom Rangers on pasture, again optimal conditions. (Other \"slow\" broiler breeds are in the same ball park.)\n- 6.2 : 1 --- Our Dark Cornish at 12 weeks last year.\nYou'll notice that pastured chickens actually eat more feed to reach a certain weight than they would have eaten if they were confined.\u00a0 (Side by side experiments have confirmed this.)\u00a0 Although we think of\\\npastured chickens as getting a lot of their nutrition from wild food,\\\nchickens can't digest much grass, so what you're really counting is how many bugs your birds found.\u00a0 It seems to take broilers more energy to find bugs than they get from eating those bugs, thus the lower feed conversion rate on pasture.\\\nAlthough these numbers seem very disheartening, I hope they don't make you turn to supermarket chickens.\u00a0 As I'll explain in a later post, I think that homesteaders can grow heritage chickens at nearly the same feed conversion rate that you'd get from Cornish Cross on pasture (and maybe even better) if we're willing to think outside the box.","parent_id":"meat_chicken\/Feedconversionrateforchickens.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"cancer_not_communicable\/Clonally_transmissible_cancer.txt:0","document_content":"A transmissible cancer is a cancer cell or cluster of cancer cells that can be transferred between individuals without the involvement of an infectious agent such as an oncovirus. The evolution of transmissible cancer has occurred naturally in other animal species, but human cancer transmission is rare. This transfer is typically between members of the same species or closely related species.\n\n## General mechanism\nTransmissible cancers require a specific combination of related circumstances to occur. These conditions involve both the host species and the tumors being transferred. These typically include low genetic diversity among individuals, an effective physical and environmental transport system, and a high enough dose of infective material. The cancers reproduce faster in larger quantities with different means of reproduction tend to be favored for transmission if host conditions are met. Transmissible cancers follow the general pattern of cancer spread, starting with the growth of primary cancer cells at tumor sites followed by invasion of surrounding tissue and subsequent spread throughout the organism. The main hurdles for surviving cells of a successful spread to a new host are histocompatibility barriers. The cancers have to bypass the self recognition system, survive the difference in nutrients and induce the correct response in the new hosts to begin the cycle anew.\nTransmissible cancers behave as true parasites, relying primarily on transport systems like direct contact, environmental transport and vectors, rather than hematogenous and lymphatic carriers to spread between organisms. The amount of shedded cancer cells from initial host has to be high enough to increase survival probability. Direct contact transmissions through sexual or general contact such as in DFTD and CVTD ensures a higher potential for transmission. Population factors also play an important role. A dense population of available and uninfected potential hosts is ideal for the tumors given the complexity and difficulty of the overall process, hence its virulence and potency must be adequately controlled.","parent_id":"cancer_not_communicable\/Clonally_transmissible_cancer.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"reddish_adapt_to_color\/Afterimage.txt:0","document_content":"An afterimage, or after-image, is an image that continues to appear in the eyes after a period of exposure to the original image. An afterimage may be a normal phenomenon (physiological afterimage) or may be pathological (palinopsia). Illusory palinopsia may be a pathological exaggeration of physiological afterimages. Afterimages occur because photochemical activity in the retina continues even when the eyes are no longer experiencing the original stimulus.\nThe remainder of this article refers to physiological afterimages. A common physiological afterimage is the dim area that seems to float before one's eyes after briefly looking into a light source, such as a camera flash. Palinopsia is a common symptom of visual snow.","parent_id":"reddish_adapt_to_color\/Afterimage.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"reddish_adapt_to_color\/Afterimage.txt:1","document_content":"## Negative afterimages\nNegative afterimages are generated in the retina but may be modified like other retinal signals by neural adaptation of the retinal ganglion cells that carry signals from the retina of the eye to the rest of the brain.\nNormally, any image is moved over the retina by small eye movements known as microsaccades before much adaptation can occur. However, if the image is very intense and brief, or if the image is large, or if the eye remains very steady, these small movements cannot keep the image on unadapted parts of the retina.\nAfterimages can be seen when moving from a bright environment to a dim one, like walking indoors on a bright snowy day. They are accompanied by neural adaptation in the occipital lobe of the brain that function similar to color balance adjustments in photography. These adaptations attempt to keep vision consistent in dynamic lighting. Viewing a uniform background while adaptation is still occurring will allow an individual to see the afterimage because localized areas of vision are still being processed by the brain using adaptations that are no longer needed.\nThe Young-Helmholtz trichromatic theory of color vision postulated that there were three types of photoreceptors in the eye, each sensitive to a particular range of visible light: short-wavelength cones, medium-wavelength cones, and long-wavelength cones. Trichromatic theory, however, cannot explain all afterimage phenomena. Specifically, afterimages are the complementary hue of the adapting stimulus, and trichromatic theory fails to account for this fact.\nThe failure of trichromatic theory to account for afterimages indicates the need for an opponent-process theory such as that articulated by Ewald Hering (1878) and further developed by Hurvich and Jameson (1957). The opponent process theory states that the human visual system interprets color information by processing signals from cones and rods in an antagonistic manner. The opponent color theory is that there are four opponent channels: red versus cyan, green vs magenta, blue versus yellow, and black versus white. Responses to one color of an opponent channel are antagonistic to those of the other color. Therefore, a green image will produce a magenta afterimage. The green color adapts the green channel, so they produce a weaker signal. Anything resulting in less green is interpreted as its paired primary color, which is magenta (an equal mixture of red and blue).","parent_id":"reddish_adapt_to_color\/Afterimage.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"3D_vision\/Binocular_disparity.txt:0","document_content":"Binocular disparity refers to the difference in image location of an object seen by the left and right eyes, resulting from the eyes' horizontal separation (parallax). The mind uses binocular disparity to extract depth information from the two-dimensional retinal images in stereopsis. In computer vision, binocular disparity refers to the difference in coordinates of similar features within two stereo images.\nA similar disparity can be used in rangefinding by a coincidence rangefinder to determine distance and\/or altitude to a target. In astronomy, the disparity between different locations on the Earth can be used to determine various celestial parallax, and Earth's orbit can be used for stellar parallax.","parent_id":"3D_vision\/Binocular_disparity.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"3D_vision\/Binocular_disparity.txt:1","document_content":"## Definition\nHuman eyes are horizontally separated by about 50--75 mm (interpupillary distance) depending on each individual. Thus, each eye has a slightly different view of the world around. This can be easily seen when alternately closing one eye while looking at a vertical edge. The binocular disparity can be observed from apparent horizontal shift of the vertical edge between both views.\nAt any given moment, the line of sight of the two eyes meet at a point in space. This point in space projects to the same location (i.e.\u00a0the center) on the retinae of the two eyes. Because of the different viewpoints observed by the left and right eye however, many other points in space do not fall on corresponding retinal locations. Visual binocular disparity is defined as the difference between the point of projection in the two eyes and is usually expressed in degrees as the visual angle.\nThe term \"binocular disparity\" refers to geometric measurements made external to the eye. The disparity of the images on the actual retina depends on factors internal to the eye, especially the location of the nodal points, even if the cross section of the retina is a perfect circle. Disparity on retina conforms to binocular disparity when measured as degrees, while much different if measured as distance due to the complicated structure inside eye.\nFigure 1: The full black circle is the point of fixation. The blue object lies nearer to the observer. Therefore, it has a \"near\" disparity dn. Objects lying more far away (green) correspondingly have a \"far\" disparity df. Binocular disparity is the angle between two lines of projection . One of which is the real projection from the object to the actual point of projection. The other one is the imaginary projection running through the nodal point of the fixation point.\nIn computer vision, binocular disparity is calculated from stereo images taken from a set of stereo cameras. The variable distance between these cameras, called the baseline, can affect the disparity of a specific point on their respective image plane. As the baseline increases, the disparity increases due to the greater angle needed to align the sight on the point. However, in computer vision, binocular disparity is referenced as coordinate differences of the point between the right and left images instead of a visual angle. The units are usually measured in pixels.","parent_id":"3D_vision\/Binocular_disparity.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"3D_vision\/Binocular_disparity.txt:2","document_content":"## Tricking neurons with 2D images\nBrain cells (neurons) in a part of the brain responsible for processing visual information coming from the retinae (primary visual cortex) can detect the existence of disparity in their input from the eyes. Specifically, these neurons will be active, if an object with \"their\" special disparity lies within the part of the visual field to which they have access (receptive field).\nResearchers investigating precise properties of these neurons with respect to disparity present visual stimuli with different disparities to the cells and look whether they are active or not. One possibility to present stimuli with different disparities is to place objects in varying depth in front of the eyes. However, the drawback to this method may not be precise enough for objects placed further away as they possess smaller disparities while objects closer will have greater disparities. Instead, neuroscientists use an alternate method as schematised in Figure 2.\nFigure 2: The disparity of an object with different depth than the fixation point can alternatively be produced by presenting an image of the object to one eye and a laterally shifted version of the same image to the other eye. The full black circle is the point of fixation. Objects in varying depths are placed along the line of fixation of the left eye. The same disparity produced from a shift in depth of an object (filled coloured circles) can also be produced by laterally shifting the object in constant depth in the picture one eye sees (black circles with coloured margin). Note that for near disparities the lateral shift has to be larger to correspond to the same depth compared with far disparities. This is what neuroscientists usually do with random dot stimuli to study disparity selectivity of neurons since the lateral distance required to test disparities is less than the distances required using depth tests. This principle has also been applied in autostereogram illusions.","parent_id":"3D_vision\/Binocular_disparity.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"earth_warm\/geothermalenergymarketglobalindustryanalysissizesharegrowthtrendsandforecast20122018262290htm.txt:0","document_content":"Transparency Market Research Report Add \"Geothermal Energy Market - Global Industry Analysis, Size, Share, Growth, Trends And Forecast, 2012 - 2018\" to its database.\nAlbany, NY -- (SBWIRE) -- 06\/10\/2013 -- Geothermal energy is a type of heat energy that is produced in the earth's core. This energy is utilized in a wide range of applications from power stations to simple pumping systems. Geothermal energy is considered as a renewable source of energy since the water which is captured in the form of heat while extracting geothermal energy is continuously replenished by rainfall and again the heat generated from it can be used. A major concentration of geothermal energy on the planet is in the area bordering the Pacific Ocean and is called the Ring of Fire.\nBrowse Report : http:\/\/www.transparencymarketresearch.com\/geothermal-energy-market.html\nThere are two types of geothermal systems -- hydrothermal and hot rock or enhanced geothermal systems. The most important type of geothermal energy is hydrothermal energy which is most widely used for generating electricity.\nIncreasing concerns regarding energy security, economic growth in developing markets, rising costs of fossil fuels, several incentives given by European countries, new technologies like binary technology, which can use even moderate temperatures to generate a decent amount of electricity, are some of the major drivers that are significantly fuelling this market.\nThe major impediments which this industry faces include initial financing of large scale projects, resource development risks like failure of drilling wells and insufficient productivity, lack of skilled labor to work on the projects, issues related to drilling rigs and market and network issues like proximity to the market and network capital costs. Also, there are some environmental problems in producing geothermal energy like release of hydrogen sulfide and disposal of toxic geothermal fluids while extraction.\nChallenges to this industry are carrying out efficient programs for land leasing where reserves of geothermal energy are located, better drilling assistance in terms of accurate positioning of the site and its viability, and significant financial support needed to establish the plants at the desired locations.\nThe United States of America has the largest amount of installed capacity and is succeeded by Philippines, Indonesia, Mexico, and Italy. Currently there are over 150 projects under development in the U.S.. On the other hand, China is the largest direct user of geothermal energy followed by the United States, Sweden, and Turkey.","parent_id":"earth_warm\/geothermalenergymarketglobalindustryanalysissizesharegrowthtrendsandforecast20122018262290htm.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"shutdown_sleep\/indexhtm.txt:0","document_content":"Often I've wondered about my computer standby mode power consumption. How much electricity does my computer use when it is in sleep mode? Since my computer (a tower desktop with two LCD monitors) is several years old it takes a while to boot up so I like to leave it in standby mode when I can.\nTo test the standby mode power consumption of my computer I got a P3 International Kill-a-Watt meter for about \\$21 online to use as a PC power consumption monitor. The Kill-a-Watt power meter plugs into the wall and then the appliance plugs into the meter. It has a has an LCD screen to tell you how much electricity was consumed in that time period.\nHere's what I found (cost per KWH in Maryland is 10.28 cents):\nState\nTime\nPower Usage (KWH)\nKWH per hr\nKWH per day\nCost per day\nOff but plugged in\n8hrs\n0.08\n0.01\n0.24\n2.5\nSleep mode\n14hrs 23min\n0.16\n0.011\n0.27\n2.8\nRegular usage\n6hrs 40 min\n1.15\n0.173\n4.15\n42.7\n\n### In Summary ...\nThe standby mode power consumption is just a bit more than leaving the computer plugged in but off. So I can use standby mode without any significant additional cost.\nWhile I'm away for more than 8 hours it makes sense to turn the computer off at the power strip. At this point no electricity is being used by any of the devices on the power strip. I usually do this when I am done using the computer in the evening or plan to be away for a while.\nNote - if you have power supplies (the black boxes you plug into a power strip or the wall) plugged directly into the wall they will be using electricity (feel them, they'll be warm). The power strip allows you to turn them off completely. This goes for stereo systems, power tools, etc.\nSearch the Web for a Kill-A-Watt Power Meter:","parent_id":"shutdown_sleep\/indexhtm.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inefficient_driving\/rderealdrivingemissionstest.txt:0","document_content":"The Real Driving Emissions (RDE) test measures the pollutants, such as NOx, emitted by cars while driven on the road. RDE does not replace the WLTP laboratory test, but complements it. RDE ensures that cars deliver low emissions over on-road conditions. Europe is the first region in the world to introduce such on-road testing, marking a major leap in the testing of car emissions.\nUnder RDE, a car is driven on public roads and over a wide range of different conditions. Specific equipment installed on the vehicle collects data to verify that legislative caps for pollutants such as NOx are not exceeded.\nConditions include:\n- Low and high altitudes\n- Year-round temperatures\n- Additional vehicle payload\n- Up- and down-hill driving\n- Urban roads (low speed)\n- Rural roads (medium speed)\n- Motorways (high speed)\nTo measure pollutant emissions as the vehicle is being driven on the roads, cars are fitted with Portable Emission Measuring Systems (PEMS) that provide a complete real-time monitoring of the key pollutants emitted by the vehicle (ie NOx).\nThe PEMS used for regulated emissions are complex pieces of equipment that integrate advanced gas analysers, exhaust mass flow meters, weather station, Global Positioning System (GPS) and a connection to the vehicle networks.\nAll parties -- including approval authorities -- must learn the proper use of PEMS systems. There is no 'standard' PEMS equipment and equipment manufactured by different suppliers will always deliver slightly different results. The collected data is analysed to check that the RDE trip boundary conditions were achieved and that the emissions were within acceptable levels.\n- RDE step 1 (with a NOx conformity factor of 2.1) applies since 1 September 2017 for new car types. It will apply to all types as from September 2019.\n- RDE step 2 (with a NOx conformity factor of 1.0 plus an error margin of 0.5) will apply in January 2020 for new types and then from January 2021 for all types.","parent_id":"inefficient_driving\/rderealdrivingemissionstest.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"psycho_flow\/Flowpsychology.txt:0","document_content":"Flow in positive psychology, also known colloquially as being in the zone or locked in, is the mental state in which a person performing some activity is fully immersed in a feeling of energized focus, full involvement, and enjoyment in the process of the activity. In essence, flow is characterized by the complete absorption in what one does, and a resulting transformation in one's sense of time. Flow is the melting together of action and consciousness; the state of finding a balance between a skill and how challenging that task is. It requires a high level of concentration. Flow is used as a coping skill for stress and anxiety when productively pursuing a form of leisure that matches one's skill set.\nFirst presented in the 1975 book Beyond Boredom and Anxiety by the Hungarian-American psychologist Mih\u00e1ly Cs\u00edkszentmih\u00e1lyi, the concept has been widely referred to across a variety of fields (and is particularly well recognized in occupational therapy).\nThe flow state shares many characteristics with hyperfocus. However, hyperfocus is not always described in a positive light. Some examples include spending \"too much\" time playing video games or becoming pleasurably absorbed by one aspect of an assignment or task to the detriment of the overall assignment. In some cases, hyperfocus can \"capture\" a person, perhaps causing them to appear unfocused or to start several projects, but complete few. Hyperfocus is often mentioned \"in the context of autism, schizophrenia, and attention deficit hyperactivity disorder -- conditions that have consequences on attentional abilities.\"\nFlow is an individual experience and the idea behind flow originated from the sports-psychology theory about an Individual Zone of Optimal Functioning. The individuality of the concept of flow suggests that each person has their subjective area of flow, where they would function best given the situation. One is most likely to experience flow at moderate levels of psychological arousal, as one is unlikely to be overwhelmed, but not understimulated to the point of boredom.\n\n## Etymology\nFlow is so named because, during Cs\u00edkszentmih\u00e1lyi's 1975 interviews, several people described their \"flow\" experiences using the metaphor of a water current carrying them along:\nWe have called this state the flow experience, because this is the term many of the people we interviewed had used in their descriptions of how it felt to be in top form: \"It was like floating,\" \"I was carried on by the flow.\"","parent_id":"psycho_flow\/Flowpsychology.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"psycho_flow\/Flowpsychology.txt:6","document_content":"## Characteristics\n### Challenges to maintaining flow\nSome of the challenges to staying in flow include states of apathy, boredom, and anxiety. The state of apathy is characterized by easy challenges and low skill level requirements, resulting in a general lack of interest in the activity. Boredom is a slightly different state that occurs when challenges are few, but one's skill level exceeds those challenges causing one to seek higher challenges. A state of anxiety occurs when challenges are high enough to exceed perceived skill level, causing distress and uneasiness. These states in general prevent achieving the balance necessary for flow. Cs\u00edkszentmih\u00e1lyi has said, \"If challenges are too low, one gets back to flow by increasing them. If challenges are too great, one can return to the flow state by learning new skills.\"","parent_id":"psycho_flow\/Flowpsychology.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"verbal_memory\/Memoryspan.txt:0","document_content":"In psychology and neuroscience, memory span is the longest list of items that a person can repeat back in correct order immediately after presentation on 50% of all trials. Items may include words, numbers, or letters. The task is known as digit span when numbers are used. Memory span is a common measure of working memory and short-term memory. It is also a component of cognitive ability tests such as the Wechsler Adult Intelligence Scale (WAIS). Backward memory span is a more challenging variation which involves recalling items in reverse order.\n\n## As a functional aspect\nFunctionally, memory span is used to measure the number of discrete units over which the individual can successively distribute his attention and still organize them into a working unit. To generalize, it refers to the ability of an individual to reproduce immediately, after one presentation, a series of discrete stimuli in their original order.\nExperiments in memory span have found that the more familiar a person is with the type of subject matter presented to them, the more they will remember it in a novel setting. For example, a person will better remember a sequence in their first-language than their second-language; a person will also remember a sequence of words better than they would a sequence of nonsense syllables.\nAccording to a theory by Alan Baddeley and Graham Hitch, working memory is under the influence of three key mechanisms: the visuospatial sketchpad, the central executive, and the phonological loop. A mechanism called the episodic buffer was later added to the model. The phonological loop is the mechanism that facilitates learning and memory by storing information (in the articulatory loop) and refreshing or rehearsing it in memory (in the acoustic store). The phonological similarity effect is when items in a list have similar features (e.g.\u00a0similar sound), they are more difficult to remember. Likewise, the more different the items in a list are, the easier it is to recall them. Memory span tasks since the formulation of Baddeley and Hitch's theory have been helpful as support for the phonological loop as part of the working memory.","parent_id":"verbal_memory\/Memoryspan.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"tesla_free_charging\/Complementarygood.txt:0","document_content":"In economics, a complementary good is a good whose appeal increases with the popularity of its complement. Technically, it displays a negative cross elasticity of demand and that demand for it increases when the price of another good decreases. If\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0A`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0A}`\\\n`\u00a0`\\\n`is\u00a0a\u00a0complement\u00a0to\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0B`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0B}`\\\n`\u00a0`\n, an increase in the price of\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0A`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0A}`\\\n`\u00a0`\\\n`will\u00a0result\u00a0in\u00a0a\u00a0negative\u00a0movement\u00a0along\u00a0the\u00a0demand\u00a0curve\u00a0of\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0A`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0A}`\\\n`\u00a0`\\\n`and\u00a0cause\u00a0the\u00a0demand\u00a0curve\u00a0for\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0B`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0B}`\\\n`\u00a0`\\\n`to\u00a0shift\u00a0inward;\u00a0less\u00a0of\u00a0each\u00a0good\u00a0will\u00a0be\u00a0demanded.\u00a0Conversely,\u00a0a\u00a0decrease\u00a0in\u00a0the\u00a0price\u00a0of\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0A`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0A}`\\\n`\u00a0`\\\n`will\u00a0result\u00a0in\u00a0a\u00a0positive\u00a0movement\u00a0along\u00a0the\u00a0demand\u00a0curve\u00a0of\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0A`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0A}`\\\n`\u00a0`\\\n`and\u00a0cause\u00a0the\u00a0demand\u00a0curve\u00a0of\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0B`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0B}`\\\n`\u00a0`\\\n`to\u00a0shift\u00a0outward;\u00a0more\u00a0of\u00a0each\u00a0good\u00a0will\u00a0be\u00a0demanded.\u00a0This\u00a0is\u00a0in\u00a0contrast\u00a0to\u00a0a\u00a0substitute\u00a0good,\u00a0whose\u00a0demand\u00a0decreases\u00a0when\u00a0its\u00a0substitute's\u00a0price\u00a0decreases.`","parent_id":"tesla_free_charging\/Complementarygood.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"tesla_free_charging\/Complementarygood.txt:1","document_content":"When two goods are complements, they experience joint demand - the demand of one good is linked to the demand for another good. Therefore, if a higher quantity is demanded of one good, a higher quantity will also be demanded of the other, and vice versa. For example, the demand for razor blades may depend on the number of razors in use; this is why razors have sometimes been sold as loss leaders, to increase demand for the associated blades. Another example is that sometimes a toothbrush is packaged free with toothpaste. The toothbrush is a complement to the toothpaste; the cost of producing a toothbrush may be higher than toothpaste, but its sales depends on the demand of toothpaste.\nAll non-complementary goods can be considered substitutes. If\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0x`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0x}`\\\n`\u00a0`\\\n`and\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0y`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0y}`\\\n`\u00a0`\\\n`are\u00a0rough\u00a0complements\u00a0in\u00a0an\u00a0everyday\u00a0sense,\u00a0then\u00a0consumers\u00a0are\u00a0willing\u00a0to\u00a0pay\u00a0more\u00a0for\u00a0each\u00a0marginal\u00a0unit\u00a0of\u00a0good\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0x`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0x}`\\\n`\u00a0`\\\n`as\u00a0they\u00a0accumulate\u00a0more\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0y`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0y}`\\\n`\u00a0`\n. The opposite is true for substitutes: the consumer is willing to pay less for each marginal unit of good \"\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0z`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0z}`\\\n`\u00a0`\n\" as it accumulates more of good \"\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0y`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0y}`\\\n`\u00a0`\n\".\nComplementarity may be driven by psychological processes in which the consumption of one good (e.g., cola) stimulates demand for its complements (e.g., a cheeseburger). Consumption of a food or beverage activates a goal to consume its complements: foods that consumers believe would taste better together. Drinking cola increases consumers' willingness to pay for a cheeseburger. This effect appears to be contingent on consumer perceptions of these relationships rather than their sensory properties.","parent_id":"tesla_free_charging\/Complementarygood.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"tesla_free_charging\/Complementarygood.txt:2","document_content":"## Examples\nAn example of this would be the demand for cars and petrol. The supply and demand for cars is represented by the figure, with the initial demand\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0D`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a01`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0D_{1}}`\\\n`\u00a0`\n. Suppose that the initial price of cars is represented by\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0P`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a01`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0P_{1}}`\\\n`\u00a0`\\\n`with\u00a0a\u00a0quantity\u00a0demanded\u00a0of\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Q`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a01`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0Q_{1}}`\\\n`\u00a0`\n. If the price of petrol were to decrease by some amount, this would result in a higher quantity of cars demanded. This higher quantity demanded would cause the demand curve to shift rightward to a new position\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0D`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a02`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0D_{2}}`\\\n`\u00a0`\n. Assuming a constant supply curve\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0S`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0S}`\\\n`\u00a0`\\\n`of\u00a0cars,\u00a0the\u00a0new\u00a0increased\u00a0quantity\u00a0demanded\u00a0will\u00a0be\u00a0at\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Q`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a02`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0Q_{2}}`\\\n`\u00a0`\\\n`with\u00a0a\u00a0new\u00a0increased\u00a0price\u00a0`\\\n`\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0P`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a02`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0`\\\n`\u00a0\u00a0\u00a0{\\displaystyle\u00a0P_{2}}`\\\n`\u00a0`\n. Other examples include automobiles and fuel, mobile phones and cellular service, printer and cartridge, among others.","parent_id":"tesla_free_charging\/Complementarygood.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inner_insulation\/Passivesolarbuildingdesign.txt:0","document_content":"In passive solar building design, windows, walls, and floors are made to collect, store, reflect, and distribute solar energy, in the form of heat in the winter and reject solar heat in the summer. This is called passive solar design because, unlike active solar heating systems, it does not involve the use of mechanical and electrical devices.\nThe key to designing a passive solar building is to best take advantage of the local climate performing an accurate site analysis. Elements to be considered include window placement and size, and glazing type, thermal insulation, thermal mass, and shading. Passive solar design techniques can be applied most easily to new buildings, but existing buildings can be adapted or \"retrofitted\".\n\n## Passive energy gain\nPassive solar technologies use sunlight without active mechanical systems (as contrasted to active solar, which uses thermal collectors). Such technologies convert sunlight into usable heat (in water, air, and thermal mass), cause air-movement for ventilating, or future use, with little use of other energy sources. A common example is a solarium on the equator-side of a building. Passive cooling is the use of similar design principles to reduce summer cooling requirements.\nSome passive systems use a small amount of conventional energy to control dampers, shutters, night insulation, and other devices that enhance solar energy collection, storage, and use, and reduce undesirable heat transfer.\nPassive solar technologies include direct and indirect solar gain for space heating, solar water heating systems based on the thermosiphon, use of thermal mass and phase-change materials for slowing indoor air temperature swings, solar cookers, the solar chimney for enhancing natural ventilation, and earth sheltering.\nMore widely, solar technologies include the solar furnace, but this typically requires some external energy for aligning their concentrating mirrors or receivers, and historically have not proven to be practical or cost effective for widespread use. 'Low-grade' energy needs, such as space and water heating, have proven over time to be better applications for passive use of solar energy.","parent_id":"inner_insulation\/Passivesolarbuildingdesign.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inner_insulation\/Passivesolarbuildingdesign.txt:2","document_content":"## As a science\nSpecific attention is divided into: the site, location and solar orientation of the building, local sun path, the prevailing level of insolation (latitude\/sunshine\/clouds\/precipitation), design and construction quality\/materials, placement\/size\/type of windows and walls, and incorporation of solar-energy-storing thermal mass with heat capacity.While these considerations may be directed toward any building, achieving an ideal optimized cost\/performance solution requires careful, holistic, system integration engineering of these scientific principles. Modern refinements through computer modeling (such as the comprehensive U.S. Department of Energy \"Energy Plus\" building energy simulation software), and application of decades of lessons learned (since the 1970s energy crisis) can achieve significant energy savings and reduction of environmental damage, without sacrificing functionality or aesthetics. In fact, passive-solar design features such as a greenhouse\/sunroom\/solarium can greatly enhance the livability, daylight, views, and value of a home, at a low cost per unit of space.\nMuch has been learned about passive solar building design since the 1970s energy crisis. Many unscientific, intuition-based expensive construction experiments have attempted and failed to achieve zero energy -- the total elimination of heating-and-cooling energy bills.\nPassive solar building construction may not be difficult or expensive (using off-the-shelf existing materials and technology), but the scientific passive solar building design is a non-trivial engineering effort that requires significant study of previous counter-intuitive lessons learned, and time to enter, evaluate, and iteratively refine the simulation input and output.\nOne of the most useful post-construction evaluation tools has been the use of thermography using digital thermal imaging cameras for a formal quantitative scientific energy audit. Thermal imaging can be used to document areas of poor thermal performance such as the negative thermal impact of roof-angled glass or a skylight on a cold winter night or hot summer day.\nThe scientific lessons learned over the last three decades have been captured in sophisticated comprehensive building energy simulation computer software systems (like U.S. DOE Energy Plus).\nScientific passive solar building design with quantitative cost benefit product optimization is not easy for a novice. The level of complexity has resulted in ongoing bad-architecture, and many intuition-based, unscientific construction experiments that disappoint their designers and waste a significant portion of their construction budget on inappropriate ideas.\nThe economic motivation for scientific design and engineering is significant. If it had been applied comprehensively to new building construction beginning in 1980 (based on 1970s lessons learned), The United States could be saving over \\$250,000,000 per year on expensive energy and related pollution today.\nSince 1979, Passive Solar Building Design has been a critical element of achieving zero energy by educational institution experiments, and governments around the world, including the U.S. Department of Energy, and the energy research scientists that they have supported for decades. The cost effective proof of concept was established decades ago, but cultural change in architecture, the construction trades, and building-owner decision making has been very slow and difficult.\nThe new subjects such as architectural science and architectural technology are being added to some schools of architecture, with a future goal of teaching the above scientific and energy-engineering principles.","parent_id":"inner_insulation\/Passivesolarbuildingdesign.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inner_insulation\/Passivesolarbuildingdesign.txt:4","document_content":"## The solar path in passive design\nThe 47-degree difference in the altitude of the sun at solar noon between winter and summer forms the basis of passive solar design. This information is combined with local climatic data (degree day) heating and cooling requirements to determine at what time of the year solar gain will be beneficial for thermal comfort, and when it should be blocked with shading. By strategic placement of items such as glazing and shading devices, the percentage of solar gain entering a building can be controlled throughout the year.\nOne passive solar sun path design problem is that although the sun is in the same relative position six weeks before, and six weeks after, the solstice, due to \"thermal lag\" from the thermal mass of the Earth, the temperature and solar gain requirements are quite different before and after the summer or winter solstice. Movable shutters, shades, shade screens, or window quilts can accommodate day-to-day and hour-to-hour solar gain and insulation requirements.\nCareful arrangement of rooms completes the passive solar design. A common recommendation for residential dwellings is to place living areas facing solar noon and sleeping quarters on the opposite side. A heliodon is a traditional movable light device used by architects and designers to help model sun path effects. In modern times, 3D computer graphics can visually simulate this data, and calculate performance predictions.\n\n## Passive solar heat transfer principles\nPersonal thermal comfort is a function of personal health factors (medical, psychological, sociological and situational), ambient air temperature, mean radiant temperature, air movement (wind chill, turbulence) and relative humidity (affecting human evaporative cooling). Heat transfer in buildings occurs through convection, conduction, and thermal radiation through roof, walls, floor and windows.","parent_id":"inner_insulation\/Passivesolarbuildingdesign.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inner_insulation\/Passivesolarbuildingdesign.txt:5","document_content":"## Passive solar heat transfer principles\n### Convective heat transfer\nConvective heat transfer can be beneficial or detrimental. Uncontrolled air infiltration from poor weatherization \/ weatherstripping \/ draft-proofing can contribute up to 40% of heat loss during winter; however, strategic placement of operable windows or vents can enhance convection, cross-ventilation, and summer cooling when the outside air is of a comfortable temperature and relative humidity. Filtered energy recovery ventilation systems may be useful to eliminate undesirable humidity, dust, pollen, and microorganisms in unfiltered ventilation air.\nNatural convection causing rising warm air and falling cooler air can result in an uneven stratification of heat. This may cause uncomfortable variations in temperature in the upper and lower conditioned space, serve as a method of venting hot air, or be designed in as a natural-convection air-flow loop for passive solar heat distribution and temperature equalization. Natural human cooling by perspiration and evaporation may be facilitated through natural or forced convective air movement by fans, but ceiling fans can disturb the stratified insulating air layers at the top of a room, and accelerate heat transfer from a hot attic, or through nearby windows. In addition, high relative humidity inhibits evaporative cooling by humans.","parent_id":"inner_insulation\/Passivesolarbuildingdesign.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inner_insulation\/Passivesolarbuildingdesign.txt:6","document_content":"## Passive solar heat transfer principles\n### Radiative heat transfer\nThe main source of heat transfer is radiant energy, and the primary source is the sun. Solar radiation occurs predominantly through the roof and windows (but also through walls). Thermal radiation moves from a warmer surface to a cooler one. Roofs receive the majority of the solar radiation delivered to a house. A cool roof, or green roof in addition to a radiant barrier can help prevent your attic from becoming hotter than the peak summer outdoor air temperature (see albedo, absorptivity, emissivity, and reflectivity).\nWindows are a ready and predictable site for thermal radiation.\nEnergy from radiation can move into a window in the day time, and out of the same window at night. Radiation uses photons to transmit electromagnetic waves through a vacuum, or translucent medium. Solar heat gain can be significant even on cold clear days. Solar heat gain through windows can be reduced by insulated glazing, shading, and orientation. Windows are particularly difficult to insulate compared to roof and walls. Convective heat transfer through and around window coverings also degrade its insulation properties. When shading windows, external shading is more effective at reducing heat gain than internal window coverings.\nWestern and eastern sun can provide warmth and lighting, but are vulnerable to overheating in summer if not shaded. In contrast, the low midday sun readily admits light and warmth during the winter, but can be easily shaded with appropriate length overhangs or angled louvres during summer and leaf bearing summer shade trees which shed their leaves in the fall. The amount of radiant heat received is related to the location latitude, altitude, cloud cover, and seasonal \/ hourly angle of incidence (see Sun path and Lambert's cosine law).\nAnother passive solar design principle is that thermal energy can be stored in certain building materials and released again when heat gain eases to stabilize diurnal (day\/night) temperature variations. The complex interaction of thermodynamic principles can be counterintuitive for first-time designers. Precise computer modeling can help avoid costly construction experiments.\n\n## Site specific considerations during design\nLatitude, sun path, and insolation (sunshine)\nSeasonal variations in solar gain e.g.\u00a0cooling or heating degree days, solar insolation, humidity\nDiurnal variations in temperature\nMicro-climate details related to breezes, humidity, vegetation and land contour\nObstructions \/ Over-shadowing -- to solar gain or local cross-winds","parent_id":"inner_insulation\/Passivesolarbuildingdesign.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"foam\/Expandedpolyethylene.txt:0","document_content":"Expanded polyethylene (EPE foam) refers to foams made from polyethylene. Typically it is made from expanded pellets ('EPE bead') made with use of a blowing agent, followed by expansion into a mold in a steam chest - the process is similar to that used to make expanded polystyrene foam.\n\n## Properties\nEPE foams are low density, semi-rigid, closed cell foam that are generally somewhere in stiffness\/compliance between Expanded polystyrene and Polyurethane. Production of EPE foams is similar to that of expanded polystyrene, but starting with PE beads. Typical densities are 29 to 120 kg\/m3 (49 to 202 lb\/cu yd) with the lower figure being common. Densities as low as 14 kg\/m3 (24 lb\/cu yd) can be produced.\nBase polymer for EPE foams range from Low-density polyethylene (LDPE) to High-density polyethylene (HDPE).\n\n### Co-polymers\nExpanded polyethylene copolymers (EPC) are also known - such as 50:50 (weight) materials with polystyrene. Though other properties are intermediate between the two bases, toughness for the copolymer exceeds either, with good tensile and puncture resistance. It is particularly applicable for re-usable products.\n\n## Production\nEPE foams were first manufactured in the 1970s.\nProduction of the PE beads is usually by extrusion, followed by chopping, producing a 'pellet'. Autoclave expansion is the most common route the bead foam. Butane or pentane is often used as a blowing agent (before 1992 CFCs may have been used). Depending on the specific process uses the beads may be cross-linked either by electron beam irradiation (see Electron beam processing), or by the addition of a chemical agent such as dicumyl peroxide.\nAn alternate route (JSP Process) to the beads uses carbon dioxide as a blowing agent which is impregnated into the pellets in an autoclave at a temperature close to the plastic's crystalline melting point. The pellets are foamed by \"flashing\" into the (lower pressure) atmosphere to expand.\nFinally molding is done by steam chest compression molding; usually the low pressure variant of the process is used, though the high pressure variant may be used for HDPE based EPE foams.","parent_id":"foam\/Expandedpolyethylene.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"foam\/whatkindofpolyethylenematerialcanberecycledhtml.txt:0","document_content":"### What kind of polyethylene material can be recycled?\nPolyethylene (PE) or polyethylene is the most common plastic. The annual global production is around 80 million tons. Its primary use is in packaging (plastic bags, plastic films, geomembranes, containers including bottles, etc.).\nExpanded polyethylene (EPE) can often be made from polyethylene. EPE is a closed-cell, non-crosslinked polyethylene foam composed of LDPE (low-density polyethylene) resins. Due to its excellent thermal insulating qualities and water resistance, EPE foam finds extensive use in packaging. It is produced via an extrusion technique and is often offered in a variety of shapes and sizes, including sheets, rolls, pipes, rods, L, C, and U sections, each of which has a specific set of applications. The most common forms of utilization are rolls and sheets.\nEPE is a recyclable material, and many companies today can offer Polyethylene foam recycling solutions. The method of EPE recycling is relatively simple. In fact, hot melting is the easiest first step to recycle EPE. The recycled EPE can be used to granulate PE pellets.\nThe hot melt machine can be used to achieve melted EPE, and GREENMAX from INTCO, which has a decent reputation, currently offers the hot melt machine at a reasonable cost. A device that is capable of processing a variety of foam materials is the GRRENMAX foam densifier. The EPE material can be perfectly melted by it. Its technology of screw crushing can break the EPE material into fragments. Its hot melt technology can then be used to melt these EPE bits into ingots.\nThis melting approach has several advantages, such as reducing the volume, easy to transport, reduce transportation costs and so on. And the configuration and service of GREENMAX foam densifier is very good. When the foam densifier is shipped to the guests, there will be a dedicated engineer alongside to help text the operation. As long as the operation is proper, the hot melted EPE ingots will be of good quality.\nIf you also want to participate in the recycling of this recyclable EPE, GREENMAX foam densifier will be a very good choice.","parent_id":"foam\/whatkindofpolyethylenematerialcanberecycledhtml.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"yeast_dissolve_in_sugar\/Osmosis.txt:0","document_content":"Osmosis (, US also ) is the spontaneous net movement or diffusion of solvent molecules through a selectively-permeable membrane from a region of high water potential (region of lower solute concentration) to a region of low water potential (region of higher solute concentration), in the direction that tends to equalize the solute concentrations on the two sides. It may also be used to describe a physical process in which any solvent moves across a selectively permeable membrane (permeable to the solvent, but not the solute) separating two solutions of different concentrations. Osmosis can be made to do work. Osmotic pressure is defined as the external pressure required to prevent net movement of solvent across the membrane. Osmotic pressure is a colligative property, meaning that the osmotic pressure depends on the molar concentration of the solute but not on its identity.\nOsmosis is a vital process in biological systems, as biological membranes are semipermeable. In general, these membranes are impermeable to large and polar molecules, such as ions, proteins, and polysaccharides, while being permeable to non-polar or hydrophobic molecules like lipids as well as to small molecules like oxygen, carbon dioxide, nitrogen, and nitric oxide. Permeability depends on solubility, charge, or chemistry, as well as solute size. Water molecules travel through the plasma membrane, tonoplast membrane (vacuole) or organelle membranes by diffusing across the phospholipid bilayer via aquaporins (small transmembrane proteins similar to those responsible for facilitated diffusion and ion channels). Osmosis provides the primary means by which water is transported into and out of cells. The turgor pressure of a cell is largely maintained by osmosis across the cell membrane between the cell interior and its relatively hypotonic environment.","parent_id":"yeast_dissolve_in_sugar\/Osmosis.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"solar_car\/Solarcellefficiency.txt:0","document_content":"Solar-cell efficiency is the portion of energy in the form of sunlight that can be converted via photovoltaics into electricity by the solar cell.\nThe efficiency of the solar cells used in a photovoltaic system, in combination with latitude and climate, determines the annual energy output of the system. For example, a solar panel with 20% efficiency and an area of 1 m2 produces 200 kWh\/yr at Standard Test Conditions if exposed to the Standard Test Condition solar irradiance value of 1000 W\/m2 for 2.74 hours a day. Usually solar panels are exposed to sunlight for longer than this in a given day, but the solar irradiance is less than 1000 W\/m2 for most of the day. A solar panel can produce more when the Sun is high in Earth's sky and produces less in cloudy conditions, or when the Sun is low in the sky. The Sun is lower in the sky in the winter.\nTwo location dependent factors that affect solar PV yield are the dispersion and intensity of solar radiation. These two variables can vary greatly between each country. The global regions that have high radiation levels throughout the year are the middle east, Northern Chile, Australia, China, and Southwestern USA. In a high-yield solar area like central Colorado, which receives annual insolation of 2000 kWh\/m2\/year, a panel can be expected to produce 400 kWh of energy per year. However, in Michigan, which receives only 1400 kWh\/m2\/year, annual energy yield drops to 280 kWh for the same panel. At more northerly European latitudes, yields are significantly lower: 175 kWh annual energy yield in southern England under the same conditions.","parent_id":"solar_car\/Solarcellefficiency.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"solar_car\/Solarcellefficiency.txt:1","document_content":"Several factors affect a cell's conversion efficiency, including its reflectance, thermodynamic efficiency, charge carrier separation efficiency, charge carrier collection efficiency and conduction efficiency values. Because these parameters can be difficult to measure directly, other parameters are measured instead, including quantum efficiency, open-circuit voltage (VOC) ratio, and \u00a7 Fill factor. Reflectance losses are accounted for by the quantum efficiency value, as they affect external quantum efficiency. Recombination losses are accounted for by the quantum efficiency, VOC ratio, and fill factor values. Resistive losses are predominantly accounted for by the fill factor value, but also contribute to the quantum efficiency and VOC ratio values.\nAs of 2024, the world record for solar cell efficiency is 47.6%, set in May 2022 by Fraunhofer ISE, with a III-V four-junction concentrating photovoltaic (CPV) cell. This beat the previous record of 47.1%, set in 2019 by multi-junction concentrator solar cells developed at National Renewable Energy Laboratory (NREL), Golden, Colorado, USA, which was set in lab conditions, under extremely concentrated light. The record in real-world conditions is held by NREL, who developed triple junction cells with a tested efficiency of 39.5%.\n\n## Factors affecting energy conversion efficiency\nThe factors affecting energy conversion efficiency were expounded in a landmark paper by William Shockley and Hans Queisser in 1961. See Shockley--Queisser limit for more detail.","parent_id":"solar_car\/Solarcellefficiency.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"solar_car\/Solarcellefficiency.txt:4","document_content":"## Factors affecting energy conversion efficiency\n### Quantum efficiency\nWhen a photon is absorbed by a solar cell it can produce an electron-hole pair. One of the carriers may reach the p--n junction and contribute to the current produced by the solar cell; such a carrier is said to be collected. Or, the carriers recombine with no net contribution to cell current.\nQuantum efficiency refers to the percentage of photons that are converted to electric current (i.e., collected carriers) when the cell is operated under short circuit conditions. The two types of quantum that are usually referred to when talking about solar cells are external and internal. External quantum efficiency (EQE) relates to the measurable properties of the solar cell. The \"external\" quantum efficiency of a silicon solar cell includes the effect of optical losses such as transmission and reflection. Measures can be taken to reduce these losses. The reflection losses, which can account for up to 10% of the total incident energy, can be dramatically decreased using a technique called texturization, a light trapping method that modifies the average light path.\nThe internal quantum efficiency (IQE) gives insight into the internal material parameters like the absorption coefficient or internal luminescence quantum efficiency. IQE is mainly used to aid the understanding of the potential of a certain material rather than a device.\nQuantum efficiency is most usefully expressed as a spectral measurement (that is, as a function of photon wavelength or energy). Since some wavelengths are absorbed more effectively than others, spectral measurements of quantum efficiency can yield valuable information about the quality of the semiconductor bulk and surfaces.\nQuantum efficiency is not the same as overall energy conversion efficiency, as it does not convey information about the fraction of power that is converted by the solar cell.\n\n### Maximum power point\nA solar cell may operate over a wide range of voltages (V) and currents (I). By increasing the resistive load on an irradiated cell continuously from zero (a short circuit) to a very high value (an open circuit) one can determine the maximum power point, the point that maximizes V\u00d7I; that is, the load for which the cell can deliver maximum electrical power at that level of irradiation. (The output power is zero in both the short circuit and open circuit extremes).\nThe maximum power point of a solar cell is affected by its temperature. Knowing the technical data of certain solar cell, its power output at a certain temperature can be obtained by","parent_id":"solar_car\/Solarcellefficiency.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fainting_mechanism\/Reflex_syncope.txt:0","document_content":"Reflex syncope is a brief loss of consciousness due to a neurologically induced drop in blood pressure and\/or a decrease in heart rate. Before an affected person passes out, there may be sweating, a decreased ability to see, or ringing in the ears. Occasionally, the person may twitch while unconscious. Complications of reflex syncope include injury due to a fall.\nReflex syncope is divided into three types: vasovagal, situational, and carotid sinus. Vasovagal syncope is typically triggered by seeing blood, pain, emotional stress, or prolonged standing. Situational syncope is often triggered by urination, swallowing, or coughing. Carotid sinus syncope is due to pressure on the carotid sinus in the neck. The underlying mechanism involves the nervous system slowing the heart rate and dilating blood vessels, resulting in low blood pressure and thus not enough blood flow to the brain. Diagnosis is based on the symptoms after ruling out other possible causes.\nRecovery from a reflex syncope episode happens without specific treatment. Prevention of episodes involves avoiding a person's triggers. Drinking sufficient fluids, salt, and exercise may also be useful. If this is insufficient for treating vasovagal syncope, medications such as midodrine or fludrocortisone may be tried. Occasionally, an artificial cardiac pacemaker may be used as treatment. Reflex syncope affects at least 1 in 1,000 people per year. It is the most common type of syncope, making up more than 50% of all cases.","parent_id":"fainting_mechanism\/Reflex_syncope.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fainting_mechanism\/Reflex_syncope.txt:1","document_content":"## Signs and symptoms\nEpisodes of vasovagal syncope are typically recurrent and usually occur when the predisposed person is exposed to a specific trigger. Before losing consciousness, the individual frequently experiences early signs or symptoms such as lightheadedness, nausea, the feeling of being extremely hot or cold (accompanied by sweating), ringing in the ears, an uncomfortable feeling in the heart, fuzzy thoughts, confusion, a slight inability to speak or form words (sometimes combined with mild stuttering), weakness and visual disturbances such as lights seeming too bright, fuzzy or tunnel vision, black cloud-like spots in vision, and a feeling of nervousness can occur as well. The symptoms may become more intense over several seconds to several minutes before the loss of consciousness (if it is lost). Onset usually occurs when a person is sitting up or standing.\nWhen people lose consciousness, they fall down (unless prevented from doing so) and, when in this position, effective blood flow to the brain is immediately restored, allowing the person to regain consciousness. If the person does not fall into a fully flat, supine position, and the head remains elevated above the trunk, a state similar to a seizure may result from the blood's inability to return quickly to the brain, and the neurons in the body will fire off and generally cause muscles to twitch very slightly but mostly remain very tense.\nThe autonomic nervous system's physiological state (see below) leading to loss of consciousness may persist for several minutes, so\nIf patients try to sit or stand when they wake up, they may pass out again\nThe person may be nauseated, pale, and sweaty for several minutes or hours\n\n## Causes\nReflex syncope occurs in response to a trigger due to dysfunction of the heart rate and blood pressure regulating mechanism. When heart rate slows or blood pressure drops, the resulting lack of blood to the brain causes fainting.\n\n### Vasovagal\nTypical triggers include:\nProlonged standing\nEmotional stress\nPain\nThe sight of blood\nFear of needles\nTime varying magnetic field (i.e.\u00a0transcranial magnetic stimulation)\n\n### Situational\nAfter or during urination (micturition syncope)\nStraining, such as to have a bowel movement\nCoughing\nSwallowing\nLifting a heavy weight\n\n### Carotid sinus\nPressing upon a certain spot in the neck. This may happen when wearing a tight collar, shaving, or turning the head.","parent_id":"fainting_mechanism\/Reflex_syncope.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"crazy_file_add_variable\/pythonapi.txt:7","document_content":"## Logging\nThe datatype is the transferred datatype, it will be converted from internal type to transferred type before transfers:\n- float\n- uint8_t and int8_t\n- uint16_t and int16_t\n- uint32_t and int32_t\n- FP16: 16bit version of floating point, allows to pack more variables in one packet at the expense of precision.\nThe logging cannot be started until your are connected to a Crazyflie:\n              # Callback called when the connection is established to the Crazyflie\n        def connected(link_uri):\n            crazyflie.log.add_config(logconf)\n\n            if logconf.valid:\n                logconf.data_received_cb.add_callback(data_received_callback)\n                logconf.error_cb.add_callback(logging_error)\n                logconf.start()\n            else:\n                print \"One or more of the variables in the configuration was not found in log TOC. No logging will be possible.\"\n\n        def data_received_callback(timestamp, data, logconf):\n            print \"[%d][%s]: %s\" % (timestamp, logconf.name, data)\n\n        def logging_error(logconf, msg):\n            print \"Error when logging %s\" % logconf.name\nThe values of log variables are transferred from the Crazyflie using CRTP packets, where all variables belonging to one logging configuration are transferred in the same packet. A CRTP packet has a maximum data size of 30 bytes, which sets an upper limit to the number of variables that can be used in one logging configuration. If the desired log variables do not fit in one logging configuration, a second configuration may be added.\n              crazyflie.log.add_config([logconf1, logconfig2])\n\n## Synchronous API\nThe synchronous classes are wrappers around the asynchronous API, where the asynchronous calls\/callbacks are replaced with blocking calls. The synchronous API does not provide the full flexibility of the asynchronous API, but is useful when writing small scripts, for logging for instance.\nThe synchronous API uses the python Context manager concept, that is the\n    with\nkeyword.\nA resource is allocated when entering a\n    with","parent_id":"crazy_file_add_variable\/pythonapi.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"moveit_config\/setupassistanttutori.txt:0","document_content":"Documentation Version\nYou're reading the documentation for a stable version of MoveIt that is not being developed further. For information on the recommended version, please have a look at Main.\n\n# MoveIt Setup Assistant\uf0c1\n## Overview\uf0c1\nThe MoveIt Setup Assistant is a graphical user interface for configuring any robot for use with MoveIt. Its primary function is generating a Semantic Robot Description Format (SRDF) file for your robot. Additionally, it generates other necessary configuration files for use with the MoveIt pipeline. To learn more about the SRDF, you can go through the URDF\/SRDF Overview page.\n\n## Getting Started\uf0c1\nMoveIt and ROS\n- Follow the instructions for installing MoveIt first if you have not already done that.\n\n- If you haven't already done so, make sure you have the Franka description package for Noetic:\n\n  > sudo apt install ros-humble-franka-description\n\n- If you have the\n\n      panda_moveit_config\n\n  package already git-cloned from the Getting Started page, be sure to delete that now since this tutorial will teach you how to create it from scratch:\n\n  > cd \\~\/ws_moveit\/src rm -rf panda_moveit_config catkin clean panda_moveit_config\n\n## Step 1: Start\uf0c1\n- To start the MoveIt Setup Assistant:\n\n  > roslaunch moveit_setup_assistant setup_assistant.launch\n\n- This will bring up the start screen with two choices: Create New MoveIt Configuration Package or Edit Existing MoveIt Configuration Package.\n\n- Click on the Create New MoveIt Configuration Package button to bring up the following screen:\n<!-- -->\n- Click on the browse button and navigate to the panda_arm_hand.urdf.xacro file installed when you installed the Franka package above. (This file gets installed in \/opt\/ros\/noetic\/share\/franka_description\/robots\/panda_arm_hand.urdf.xacro on Ubuntu with ROS Noetic.) Choose that file and then click Load Files. The Setup Assistant will load the files (this might take a few seconds) and present you with this screen:","parent_id":"moveit_config\/setupassistanttutori.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"moveit_config\/setupassistanttutori.txt:1","document_content":"# MoveIt Setup Assistant\uf0c1\n## Step 2: Generate Self-Collision Matrix\uf0c1\nThe Default Self-Collision Matrix Generator searches for pairs of links on the robot that can safely be disabled from collision checking, decreasing motion planning processing time. These pairs of links are disabled when they are always in collision, never in collision, in collision in the robot's default position or when the links are adjacent to each other on the kinematic chain. The sampling density specifies how many random robot positions to check for self collision. Higher densities require more computation time while lower densities have a higher possibility of disabling pairs that should not be disabled. The default value is 10,000 collision checks. Collision checking is done in parallel to decrease processing time.\n- Click on the Self-Collisions pane selector on the left-hand side and click on the Generate Collision Matrix button. The Setup Assistant will work for a few second before presenting you the results of its computation in the main table.\n\n## Step 3: Add Virtual Joints\uf0c1\nVirtual joints are used primarily to attach the robot to the world. For the Panda we will define only one virtual joint attaching the panda_link0 of the Panda to the world world frame. This virtual joint represents the motion of the base of the robot in a plane.\n- Click on the Virtual Joints pane selector. Click on Add Virtual Joint\n\n- Set the joint name as \"virtual_joint\"\n\n- Set the child link as \"panda_link0\" and the parent frame name as \"world\".\n\n- Set the Joint Type as \"fixed\".\n\n- Click Save and you should see this screen:\n\n## Step 4: Add Planning Groups\uf0c1\nPlanning groups are used for semantically describing different parts of your robot, such as defining what an arm is, or an end effector.\n- Click on the Planning Groups pane selector.\n\n- Click on Add Group and you should see the following screen:\nAdd the arm\n- We will first add Panda arm as a planning group\n\n  - Enter Group Name as panda_arm\n\n  - Choose kdl_kinematics_plugin\/KDLKinematicsPlugin as the kinematics solver. Note: if you have a custom robot and would like a powerful custom IK solver, see Kinematics\/IKFast\n\n  - Let Kin. Search Resolution and Kin. Search Timeout stay at their default values.\n<!-- -->","parent_id":"moveit_config\/setupassistanttutori.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"moveit_config\/setupassistanttutori.txt:2","document_content":"# MoveIt Setup Assistant\uf0c1\n## Step 4: Add Planning Groups\uf0c1\n- Now, click on the Add Joints button. You will see a list of joints on the left hand side. You need to choose all the joints that belong to the arm and add them to the right hand side. The joints are arranged in the order that they are stored in an internal tree structure. This makes it easy to select a serial chain of joints.\n\n  - Click on virtual_joint, hold down the Shift button on your keyboard and then click on the panda_joint8. Now click on the \\> button to add these joints into the list of selected joints on the right.\n<!-- -->\n- Click Save to save the selected group.\nAdd the gripper\n- We will also add a group for the end effector. NOTE that you will do this using a different procedure than adding the arm.\n\n  - Click on the Add Group button.\n\n  - Enter Group Name as hand\n\n  - Let Kinematic Solver stay at its default value; None.\n\n  - Let Kin. Search Resolution and Kin. Search Timeout stay at their default values.\n\n  - Click on the Add Links button.\n\n  - Choose panda_hand, panda_leftfinger, and panda_rightfinger and add them to the list of Selected Links on the right hand side.\n\n  - Click Save\n\n## Step 5: Add Robot Poses\uf0c1\nThe Setup Assistant allows you to add certain fixed poses into the configuration. This helps if, for example, you want to define a certain position of the robot as a Home position.\n- Click on the Robot Poses pane.\n\n- Click Add Pose. Choose a name for the pose. The robot will be in its Default position where the joint values are set to the mid-range of the allowed joint value range. Move the individual joints around until you are happy and then Save the pose. Note how poses are associated with particular groups. You can save individual poses for each group.\n\n- IMPORTANT TIP: Try to move all the joints around. If there is something wrong with the joint limits in your URDF, you should be able to see it immediately here.\n\n## Step 6: Label End Effectors\uf0c1\nWe have already added the gripper of the Panda. Now, we will designate this group as a special group: end effectors. Designating this group as end effectors allows some special operations to happen on them internally.","parent_id":"moveit_config\/setupassistanttutori.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"moveit_config\/setupassistanttutori.txt:3","document_content":"# MoveIt Setup Assistant\uf0c1\n## Step 6: Label End Effectors\uf0c1\n- Click on the End Effectors pane.\n\n- Click Add End Effector.\n\n- Choose hand as the End Effector Name for the gripper.\n\n- Select hand as the End Effector Group.\n\n- Select panda_link8 as the Parent Link for this end-effector.\n\n- Leave Parent Group blank.\n\n## Step 7: Add Passive Joints\uf0c1\nThe passive joints tab is meant to allow specification of any passive joints that might exist in a robot. These are joints that are unactuated on a robot (e.g.\u00a0passive casters.) This tells the planners that they cannot (kinematically) plan for these joints because they can't be directly controlled. The Panda does not have any passive joints so we will skip this step.\n\n## Step 8: 3D Perception\uf0c1\nThe 3D Perception tab is meant to set the parameters of the YAML configuration file for configuring the 3D sensors sensors_3d.yaml.\ne.g.\u00a0point_cloud parameters:\nFor more details about those parameters please see perception pipeline tutorial\nIn case of sensors_3d.yaml was not needed, choose None.\n\n## Step 9: Gazebo Simulation\uf0c1\nThe Simulation tab can be used to help you simulate your robot with Gazebo by generating a new Gazebo compatible urdf if needed.\nYou can use the generated robot urdf to spawn the robot in Gazebo in the following way.\n- Use rosrun to start gazebo empty world:\n\n  > roslaunch gazebo_ros empty_world.launch paused:=true use_sim_time:=false gui:=true throttled:=false recording:=false debug:=true\n\n- Use rosrun to spawn the robot:\n\n  > rosrun gazebo_ros spawn_model -file \\<\/path_to_new_urdf\/file_name.urdf\\> -urdf -x 0 -y 0 -z 1 -model panda\n\n## Step 10: ROS Control\uf0c1\nROS Control is a set of packages that include controller interfaces, controller managers, transmissions and hardware_interfaces, for more details please look at ros_control documentation\nROS Control tab can be used to auto generate simulated controllers to actuate the joints of your robot. This will allow us to provide the correct ROS interfaces MoveIt.\n- Click on the ROS Control pane selector.\n<!-- -->","parent_id":"moveit_config\/setupassistanttutori.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"moveit_config\/setupassistanttutori.txt:4","document_content":"# MoveIt Setup Assistant\uf0c1\n## Step 10: ROS Control\uf0c1\n- Click on Add Controller and you should see the following screen:\n\n- We will first add Panda arm position controller\n\n- Enter Controller Name as arm_position_controller\n\n- Choose position_controllers\/JointPositionController as the controller type\n\n- Next you have to choose this controller joints, you can add joints individually or add all the joints in a planning group all together.\n\n- Now, click on Add Planning Group Joints.\n<!-- -->\n- Choose panda_arm planning group to add all the joints in that group to the arm controller.\n<!-- -->\n- Click Save to save the selected controller.\n\n## Step 12: Generate Configuration Files\uf0c1\nYou are almost there. One last step - generating all the configuration files that you will need to start using MoveIt\n- Click on the Configuration Files pane. Choose a location and name for the ROS package that will be generated containing your new set of configuration files. Click browse, select a good location (for example, your home directory), click Create New Folder, call it \"panda_moveit_config\", and click Choose. \"panda_moveit_config\" is the location used in the rest of the documentation on this wiki. This package does not have to be within your ROS package path. All generated files will go directly into the directory you have chosen.\n\n- Click on the Generate Package button. The Setup Assistant will now generate and write a set of launch and config files into the directory of your choosing. All the generated files will appear in the Generated Files\/Folders tab and you can click on each of them for a description of what they contain.\n<!-- -->\n- Congratulations!! - You are now done generating the configuration files you need for MoveIt\n\n## What's Next\uf0c1\nThe MoveIt RViz plugin\n- Start looking at how you can use the generated configuration files to play with MoveIt using the MoveIt RViz Plugin.\nSetup IKFast Inverse Kinematics Solver\n- A faster IK solver than the default KDL solver, but takes some additional steps to setup: Kinematics\/IKFast\n\n## Additional Reading\uf0c1\n- See the URDF and SRDF page for more details on the components of the URDF and SRDF mentioned in this tutorial.","parent_id":"moveit_config\/setupassistanttutori.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"brain_train_neural_network\/Hebbian_theory.txt:0","document_content":"Hebbian theory is a neuropsychological theory claiming that an increase in synaptic efficacy arises from a presynaptic cell\\'s repeated and persistent stimulation of a postsynaptic cell. It is an attempt to explain synaptic plasticity, the adaptation of brain neurons during the learning process. It was introduced by Donald Hebb in his 1949 book The Organization of Behavior. The theory is also called Hebb\\'s rule, Hebb\\'s postulate, and cell assembly theory. Hebb states it as follows:\nThe theory is often summarized as \\\"Cells that fire together wire together.\\\" However, Hebb emphasized that cell A needs to \\\"take part in firing\\\" cell B, and such causality can occur only if cell A fires just before, not at the same time as, cell B. This aspect of causation in Hebb\\'s work foreshadowed what is now known about spike-timing-dependent plasticity, which requires temporal precedence.\nThe theory attempts to explain associative or Hebbian learning, in which simultaneous activation of cells leads to pronounced increases in synaptic strength between those cells. It also provides a biological basis for errorless learning methods for education and memory rehabilitation. In the study of neural networks in cognitive function, it is often regarded as the neuronal basis of unsupervised learning.","parent_id":"brain_train_neural_network\/Hebbian_theory.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"brain_train_neural_network\/Hebbian_theory.txt:1","document_content":"Hebbian engrams and cell assembly theory\\[edit\\]\nHebbian theory concerns how neurons might connect themselves to become engrams. Hebb\\'s theories on the form and function of cell assemblies can be understood from the following:\nThe general idea is an old one, that any two cells or systems of cells that are repeatedly active at the same time will tend to become \\'associated\\' so that activity in one facilitates activity in the other.\nHebb also wrote:\nWhen one cell repeatedly assists in firing another, the axon of the first cell develops synaptic knobs (or enlarges them if they already exist) in contact with the soma of the second cell.\n\\[D. Alan Allport\\] posits additional ideas regarding cell assembly theory and its role in forming engrams, along the lines of the concept of auto-association, described as follows:\nIf the inputs to a system cause the same pattern of activity to occur repeatedly, the set of active elements constituting that pattern will become increasingly strongly inter-associated. That is, each element will tend to turn on every other element and (with negative weights) to turn off the elements that do not form part of the pattern. To put it another way, the pattern as a whole will become \\'auto-associated\\'. We may call a learned (auto-associated) pattern an engram.\nWork in the laboratory of Eric Kandel has provided evidence for the involvement of Hebbian learning mechanisms at synapses in the marine gastropod Aplysia californica. Experiments on Hebbian synapse modification mechanisms at the central nervous system synapses of vertebrates are much more difficult to control than are experiments with the relatively simple peripheral nervous system synapses studied in marine invertebrates. Much of the work on long-lasting synaptic changes between vertebrate neurons (such as long-term potentiation) involves the use of non-physiological experimental stimulation of brain cells. However, some of the physiologically relevant synapse modification mechanisms that have been studied in vertebrate brains do seem to be examples of Hebbian processes. One such study reviews results from experiments that indicate that long-lasting changes in synaptic strengths can be induced by physiologically relevant synaptic activity working through both Hebbian and non-Hebbian mechanisms.","parent_id":"brain_train_neural_network\/Hebbian_theory.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"bid_auction\/ci112pdf.txt:3","document_content":"Auction format. The best-known feature of a Treasury auction---the single-price format---was introduced in 1992.\nThe change from the earlier multiple-price format was part\nof a major overhaul of the auction process that followed several violations of auction rules in 1991.\nThe Treasury first adopted the multiple-price format\nwhen it initiated bill auctions in 1929 and it continued to use\nthat format when it introduced auctions of coupon-bearing\nsecurities in the early 1970s. However, when the auction\nprocess came under scrutiny in 1991, public officials became\ninterested in alternative formats that might appeal to more\ninvestors and that might lead to lower financing costs.\nSeveral academics had suggested earlier that single-price\nauctions might reduce financing costs (see Carson \\[1959\\],\nFriedman \\[1960, 1963\\], and Smith \\[1966\\]). In a single-price\nauction, a participant can bid its actual reservation yield for\na new security, that is, the minimum yield at which it is willing to buy the security. The bidder certainly has no reason to\nbid a lower yield, but if the auction stops at a higher yield it\nwill get the full benefit of buying at that higher yield. In contrast, the multiple-price format encourages a participant to\nbid higher than its reservation yield in hopes of getting the\nsecurity on more favorable terms.\nWhether the Treasury would be better off selling securities in a single-price format or a multiple-price format was a\nmatter that could only be resolved by empirical analysis.7 In\nSeptember 1992, the Treasury announced that, in an experiment, it would begin to auction two-year notes and five-year\nnotes in the single-price format. It subsequently produced\ntwo empirical studies analyzing the results of the experiment (see Box 2). Although the evidence was not unambiguous, the Treasury decided in October 1998 that it justified\nextending the single-price format to all auction offerings.\nRestrictions on auction awards to competitive bidders.\nIn the interest of fostering a liquid post-auction secondary\nmarket for a new issue, the Treasury limits the maximum\nauction award to a single bidder to 35 percent of the offering,\nless the bidder's \"reportable net long position\" in the security. A bidder's net long position is the sum, as of one-half\nhour before the close of bidding, of\n(a) when-issued, forward, and futures contracts for the\nsecurity and for principal STRIPS to be derived from the\nsecurity (STRIPS---an acronym for Separate Trading\nof Registered Interest and Principal of Securities---\nare single-payment claims for the respective interest\nand principal payments from a coupon-bearing\nsecurity) and\nwww.newyorkfed.org\/research\/current_issues 3\nOn Wednesday, August 25, 2004, the Treasury auctioned\n\\$24 billion of two-year notes that would be issued on\nAugust 31 and that would mature on August 31, 2006. It\nreceived noncompetitive bids for \\$994,798,000 of the notes,\nand competitive bids for \\$51,580,904,000.\nAfter allocating enough notes to satisfy the noncompetitive bids, the Treasury had \\$23,005,202,000 notes remaining to be sold to competitive bidders. Accepting bids in\norder of increasing yield, the Treasury stopped at a yield of\n2.494 percent. All bids specifying yields below 2.494 percent were accepted in full; a bid at 2.494 percent was allocated 32.34 percent of the amount specified. (The allocation\nat the stop is the ratio of (a) the quantity of securities that\nremain to be sold at the stop to (b) the quantity bid at the\nstop, rounded up to two digits to the right of the decimal","parent_id":"bid_auction\/ci112pdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"bid_auction\/ci112pdf.txt:5","document_content":"not materialize, they would end up owning more securities\nthan they wanted. In the interest of encouraging broad public participation in its auctions, the Treasury announced in\nJuly 1990 that it would limit the total bids by a given participant at a given yield or discount rate to 35 percent of the\namount offered to the public.\nGranularity of bidding. When the Treasury introduced bidding on notes and bonds in terms of yields in 1974, it specified\nthat bids should be expressed to a whole basis point.11When it\nintroduced bidding on bills in terms of discount rates in 1983,\nit made a similar stipulation.12 Bidding to a whole basis point\ncontinued until 1995, when Treasury officials specified that\nbids on notes and bonds should be expressed to 1\/10 of 1 basis\npoint. The greater precision was intended to \"increase participation in Treasury auctions and to conform the auctions to\nmarket practice for when-issued trading.\"13 Officials refined\nthe bidding increment to 1\/2 of 1 basis point in late 1997 for\nthirteen-, twenty-six-, and fifty-two-week bills and in April\n2002 for cash management bills, saying that they expected the\nchange \"to promote more efficient and aggressive bidding and\nlead to marginally higher revenue.\" 14\n4\nThe Treasury produced two empirical studies of the results\nof its experiment with a single-price auction format: Malvey,\nArchibald, and Flynn (1995) and Malvey and Archibald\n(1998). The studies calculated---for both single-price and\nmultiple-price auctions---the difference between the auction\nyield of a security and the yield at which the same security\nwas trading in the when-issued market at the time of the\nauction. A positive difference indicated that the securities\nhad been auctioned at a yield higher than the one at which\nthey were trading in the when-issued market. For securities\nauctioned in a multiple-price format, the average difference\nwas statistically significantly greater than zero. For securities\nauctioned in a single-price format, however, the studies were\nunable to reject the hypothesis that the average difference\nwas zero. These results suggest that moving to a single-price\nformat would lead to lower financing costs. Nevertheless,\nthe studies were also unable to reject the hypothesis that\nchanging auction formats would leave the average difference\nunchanged. The apparent inconsistency arose because the\ndifferences between auction yields and when-issued yields in\nsingle-price auctions were quite volatile. The studies could\nneither reject the hypothesis that the average difference in\nsingle-price auctions was different from zero, nor could they\nreject the hypothesis that the average difference was different from the (positive) average difference that characterized\nmultiple-price auctions.\nThe studies also examined whether single-price auctions\nreduced the concentration of auction awards. The studies\nfound that the single-price format did not materially affect\nthe distribution of awards between dealers and others but\nthat it did lead to a lower concentration of auction awards to\nthe largest dealers.\nBox 2","parent_id":"bid_auction\/ci112pdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"ceopay\/ExecutiveExcess1999pdf.txt:8","document_content":"variable. Indeed, when the stock market was weak in 1994, fewer executives exercised\ntheir options and total compensation took a dip. However, most executives still enjoy generous base pay packages and in fact in 1994 a record number earned more than \\$1 million.12\nMoreover, while CEOs might face the unhappy prospect of their stock options slipping\n\"underwater,\\\" employees have their very livelihoods at risk, since layoffs are often the first\nresponse to economic downturns.\nB. International Analysis\nDuring the 1990s, executive pay in other countries, though increasing, doesn't begin to\napproach the outrageous levels in the United States. The slight increases in foreign\ncompensation levels can be attributed to two factors:\n\u2022 Stock options are increasingly permitted as part of compensation in other countries\n\u2022 Mergers between U.S. and foreign firms have resulted in foreign executives receiving\npay hikes to lift them toward the level of their U.S. colleagues.\nStill, CEOs at many globally competitive foreign firms earn modest amounts relative to comparable U.S. firms. We requested compensation information from the more than\n90 foreign firms that had net income levels over \\$1 billion in 1997. Because most governments outside the United States do not require that corporations report such information,\nresponse to our requests was spotty. However, as the chart on page 5 reveals, none of the\ncorporations that responded pay their top executive anywhere near the average total compensation of \\$10.6 million earned in 1998 by the average U.S. CEO. These seven foreign\nfirms successfully compete in the global marketplace while paying their top executive\nbetween 4 percent and 27 percent of the amount earned by average U.S. executive.\nNo Japanese firms responded to our inquiry, but Towers Perrin, a U.S.-based consulting firm, has studied Japanese compensation levels and estimates that chief executives\nof companies with revenues between \\$250 million and \\$500 million in that country make\non average \\$420,855.13 Pay levels for Japanese executives have not risen much during the\ndecade. Towers Perrin estimated in 1990 that executives of large Japanese companies\nreceived between \\$270,000 to \\$400,000 per year.14\n6\nOlav Sabo (D-MN) points out that\"a company doesn't exist solely for the benefit of those\nrunning it. It has a relationship with shareholders, consumers, communities and workers---all of which are essential to the company's success. Those who work on the factory\nfloor should be as important as those who work in the executive suite.\"16 Likewise, William\nBennett, one of the nation's leading conservatives and a self-described ethics expert, chastised members of the American Compensation Association in May 1999, describing some\npay packages as \"ridiculous\" and posing the rhetorical question \"How much do people\nactually need?\\\"\nThese arguments are nothing new. At the turn of the century, finance magnate J.P.\nMorgan espoused the opinion that CEOs should not make more than 20 times the compensation of the average employee.17 In 1912, Theodore Roosevelt told the Ohio Constitutional\nConvention:\"I hold it to be our duty to see that the wage worker, the small producer, the\nordinary consumer, shall get their fair share of the benefit of business prosperity.\"18\nThe other camp of critics focuses on economic concerns. They include money managers and other economic analysts---including even Federal Reserve Chairman Alan\nGreenspan---who see excessive executive compensation as an obstacle to shareholder profits and U.S. corporate competitiveness. The following section lays out the five major economic arguments against excessive CEO pay.\nA. Short-termism\nExorbitant stock options grants have generated much of the explosion in executive pay\nin the past decade. Promoters of stock options bill them as a way to get managers to\nthink like owners, by linking their wealth directly to firm value. However, a study by the","parent_id":"ceopay\/ExecutiveExcess1999pdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"oil_price_cap\/businessreview20220928willanoilpricecapmanagetoreducethepdf.txt:0","document_content":"Will an oil price cap manage to reduce the flow of\nrevenue to Russia?\nIn early September 2022, the finance ministers of the G7 countries confirmed their intention to implement a price\ncap on purchases of Russian oil and related products. Their objective is to reduce Russia's ability to fund its\ninvasion of Ukraine while limiting the war's impact on global energy prices. A survey by the Initiative on Global\nMarkets asked economists for their thoughts on price caps. Romesh Vaitilingam summarises the results.\nWe invited our European and US experts to express their views on this proposal, asking both panels whether they\nagree or disagree with the following statements, and, if so, how strongly and with what degree of confidence:\na) A price cap imposed by the G7\/EU countries on purchases of Russian oil and oil-related products (and which\napplies to all importers of Russian oil using Western trade infrastructure, shipping, and insurance) would be an\neffective measure to reduce the flow of revenues to Russia.\nb) The oil price cap imposed by the G7\/EU countries will not have a substantial effect on the world oil price (such as\nthe Brent crude benchmark).\nThe price cap and Russian revenues\nOf our 43 US experts, 39 participated in this survey; of our 49 European experts, 38 participated -- for a total of 77\nexpert reactions. On the first statement, over two-thirds of the panellists agree or strongly agree with the statement\n(among whom European experts were more likely to say that they strongly agree), most of the rest are uncertain, and a few disagree. Weighted by each expert's confidence in their response, 16% of the European panel strongly agree, 57% agree, 20% are uncertain, 4% disagree, and 4% strongly disagree (totals don't always sum to 100 because of rounding). Among the US panel (again weighted by each expert's confidence in their response), 5% strongly agree, 59%\nagree, 28% are uncertain, and 8% disagree. Overall, across both panels, 11% strongly agree, 58% agree, 23% are\nuncertain, 6% disagree, and 2% strongly disagree. More details on the experts' views come in the short comments that they are able to include when they participate\nin the survey. Among those who agree or strongly agree with the statement, Maristella Botticini at Bocconi argues:\n'Price caps (and floors) typically generate distortions. True. But in extraordinary times, like during a war after a\npandemic, policy recommendations based on EC101 models should become more sophisticated. A temporary price\ncap together with other policy measures can help a lot.' Richard Portes at London Business School (LBS) points out that: 'Russia is already selling oil to India and China at\nsubstantially discounted prices. And the oil price is responding to demand, not significantly affected by speculation. Russia will have few alternative major buyers at prices above the cap, provided that is set sensibly.' Olivier\nBlanchard at the Peterson Institute also refers to the importance of where the cap is set: 'A well designed price cap,\njust such as to give Russia the incentive to sell at the cap rather than just stop selling. Want to affect revenues, not\nquantities sold. Hard to do right.' David Autor at MIT also considers implementation difficult to get right: 'It's a great idea in theory but hard to enforce\nin practice. The cap will likely depress Russian oil revenue somewhat, in part by enabling China, Iran, and North\nKorea to negotiate a greater discount (though above the price cap).' But Kenneth Judd at Stanford is optimistic:\n'Exercising monopsony power will push down revenues to Russia. They may find other buyers but the mechanics of\nmoving oil will limit that leakage. Hopefully diplomatic efforts will convince potential buyers to not increase their\npurchases.'\nLSE Business Review: Will an oil price cap manage to reduce the flow of revenue to Russia? Page 1 of 3\nDate originally posted: 2022-09-28\nPermalink: <https:\/\/blogs.lse.ac.uk\/businessreview\/2022\/09\/28\/will-an-oil-price-cap-manage-to-reduce-the-flow-of-revenue-to-russia\/>\nBlog homepage: <https:\/\/blogs.lse.ac.uk\/businessreview\/>\nSeveral experts who agree with the statement wonder how large the effect could be. Ricardo Reis at the London\nSchool of Economics (LSE) says: 'Effective to reduce the flow of revenues to Russia, but unclear how large. Depends, in the short run on response of non-G7\/EU government, and in the long run on entry into market of non- G7\/EU traders\/shippers\/financiers.' He links to a useful overview of the issues at The Economist.\nJudith Chevalier at Yale replies: 'While leakage will be large, the sanctions plus price cap should improve the\nbargaining position of non-G7 countries vis-\u00e0-vis Russia and reduce Russian revenues. There appears to be some","parent_id":"oil_price_cap\/businessreview20220928willanoilpricecapmanagetoreducethepdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inflation_interest\/neofisherismpdf.txt:3","document_content":"when inflation is low. The reasoning behind\nthis practice is that increasing interest rates\nreduces spending, \"cools\" the economy and\nreduces inflation, while reducing interest\nrates increases spending, \"heats up\" the\neconomy and increases inflation.\nNeo-Fisherism\nBut what if central banks have inflation\ncontrol wrong? A well-established empirical regularity, and a key component of\nessentially all mainstream macroeconomic\ntheories, is the Fisher effect---a positive\nrelationship between the nominal interest\nrate and inflation. The Fisher relationship,\nnamed for Irving Fisher, is readily discernible in the data. Look at Figure 1, for example, which is a scatter plot of the inflation\nrate (the four-quarter percentage change\nin the personal consumption deflator---the\nFed's chosen measure of inflation) vs.\u00a0the\nfed funds rate for the period 1954-2015. In\nFigure 1, a positively sloped line would be\nthe best fit to the points in the scatter plot,\nindicating that inflation tends to rise as the\nfed funds rate rises.\nMany macroeconomists have interpreted\nthe Fisher relation observed in Figure 1 as\ninvolving causation running from inflation to the nominal interest rate (the usual\nmarket quote for the interest rate, not\nadjusted for inflation). Market interest rates\nare determined by the behavior of borrowers and lenders in credit markets, and these\nborrowers and lenders care about real rates\nof interest. For example, if I take out a car\nloan for one year at an interest rate of 10\npercent, and I expect the inflation rate to be\n2 percent over the next year, then I expect\nthe real rate of interest that I will face on\nthe car loan will be 10 percent -- 2 percent =\n8 percent. Since borrowers and lenders care\nabout real rates of interest, we should expect\nthat as inflation rises, nominal interest\nrates will rise as well. So, for example, if the\ntypical market interest rate on car loans is","parent_id":"inflation_interest\/neofisherismpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inflation_interest\/neofisherismpdf.txt:4","document_content":"10 percent if the inflation rate is expected to\nbe 2 percent, then we might expect that the\nmarket interest rate on car loans would be\n12 percent if the inflation rate were expected\nto be 4 percent. If we apply this idea to all\nmarket interest rates, we should anticipate\nthat, generally, higher inflation will cause\nnominal market interest rates to rise.\nBut, what if we turn this idea on its head,\nand we think of the causation running\nfrom the nominal interest rate targeted by\nthe central bank to inflation? This, basically, is what Neo-Fisherism is all about.\nNeo-Fisherism says, consistent with what\nwe see in Figure 1, that if the central bank\nwants inflation to go up, it should increase\nits nominal interest rate target, rather than\ndecrease it, as conventional central banking\nwisdom would dictate. If the central bank\nwants inflation to go down, then it should\ndecrease the nominal interest rate target.\nBut how would this work? To simplify,\nthink of a world in which there is perfect\ncertainty and where everyone knows what\nfuture inflation will be. Then, the nominal\ninterest rate R can be expressed as\nR = r + \u03c0,\nwhere r is the real (inflation-adjusted) rate\nof interest and \u03c0 is future inflation. Then,\nsuppose that the central bank increases the\nnominal interest rate R by raising its nominal interest rate target by 1 percent and uses\nits tools (intervention in financial markets)\nto sustain this forever. What happens?\nTypically, we think of central bank policy as\naffecting real economic activity---employment, unemployment, gross domestic\nproduct, for example---through its effects\non the real interest rate r. But, as is widely\naccepted by macroeconomists, these effects\ndissipate in the long run. So, after a long\nperiod of time, the increase in the nominal\ninterest rate will have no effect on r and will","parent_id":"inflation_interest\/neofisherismpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inflation_interest\/neofisherismpdf.txt:5","document_content":"be reflected only in a one-for-one increase\nin the inflation rate, \u03c0. In other words, in\nthe long run, the only effect of the nominal\ninterest rate on inflation comes through the\nFisher effect; so, if the nominal interest rate\nwent up by 1 percent, so should the inflation\nrate---in the long run.\nBut, in the short run, it is widely accepted\nby macroeconomists (though there is some\ndisagreement about the exact mechanism)\nthat an increase in R will also increase r,\nwhich will have a negative effect on aggregate economic activity---unemployment will\ngo up and gross domestic product will go\ndown. This is what macroeconomists call a\nnon-neutrality of money. But note that, if\nan increase in R results in an increase in r,\nthe short-run response of inflation to the\nincrease in R must be less than one-for-one.\nNeo-Fisherism says, consistent with what we see in\nFigure 1, that if the central\nbank wants inflation to go up,\nit should increase its nominal\ninterest rate target, rather\nthan decrease it, as conventional central banking wisdom\nwould dictate. If the central\nbank wants inflation to go\ndown, then it should decrease\nthe nominal interest rate target.\nThe Regional Economist \\| www.stlouisfed.org 7\nHowever, if inflation is to go down when R\ngoes up, the real interest rate r must increase\nmore than one-for-one with an increase in\nR, that is, the non-neutrality of money in the\nshort run must be very large.\nTo assess these issues thoroughly, we need\na well-specified macroeconomic model. But\nessentially all mainstream macroeconomic\nmodels predict a response of the economy\nto an increase in the nominal interest rate\nas depicted in Figure 2. In this figure, time","parent_id":"inflation_interest\/neofisherismpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"inflation_interest\/neofisherismpdf.txt:6","document_content":"is on the horizontal axis, and the central\nbank acts to increase the nominal interest\nrate permanently, and in an unanticipated\nfashion, at time T. This results in an increase\nin the real interest rate r on impact. Inflation \u03c0 increases gradually over time, and\nthe real interest rate falls, with the inflation rate increasing by the same amount\nas the increase in R in the long run. This\ntype of response holds even in mainstream\nNew Keynesian models, which, it is widely\nbelieved, predict that a central bank wanting to increase inflation should lower its\nnominal interest rate target. However,\nas economist John Cochrane shows, the\nNew Keynesian model implies that if the\ncentral bank carries out the policy we have\ndescribed---a permanent increase of 1\npercent in the central bank's nominal interest rate target---then the inflation rate will\nincrease, even in the short run.4\nThe Low-Inflation Policy Trap\nWhat could go wrong if central bankers do not recognize the importance of\nthe Fisher effect and instead conform to\nconventional central banking wisdom?\nConventional wisdom is embodied in the\nTaylor rule, first proposed by John Taylor\nin 1993.5\nTaylor's idea is that optimal\ncentral bank behavior can be written\ndown in the form of a rule that includes\na positive response of the central bank's\nnominal interest rate target to an increase\nin inflation.\nBut the Taylor rule does not seem to\nmake sense in terms of what we see in\nFigure 2. Taylor appears to have thought,\nin line with conventional central banking wisdom, that increasing the nominal\ninterest rate will make the inflation rate go\ndown, not up. Further, Taylor advocated a\nspecific aggressive response of the nominal\ninterest rate target to the inflation rate,\nsometimes called the Taylor principle. This\nprinciple is that the nominal interest rate","parent_id":"inflation_interest\/neofisherismpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:0","document_content":"Littering in Context: Personal and Environmental\nPredictors of Littering Behavior\nP.Wesley Schultz1\n, Ren\u00e9e J. Bator3\n, Lori Brown Large2\n, Coral M.Bruni2\n, and\nJennifer J.Tabanico2\nAbstract\nThis article reports the results from a large-scale study of\nlittering behavior. Findings are reported from coded\nobservations of the littering behavior among 9,757 individuals\nat 130 outdoor public locations in the United States. The focus\nwas on littering behavior of any item, but a separate sample is\nalso reported on the littering behavior of only smokers. For\nsmokers, the observed littering rate for cigarette butts was 65%.\nResults from the general littering observations showed that of\nall the disposal behaviors observed, 17% resulted in litter.\nStatistical analyses using multilevel modeling showed that age\n(negatively) was predictive of individual littering. At the level\nof the site, the presence of existing litter (positively) and the\navailability of trash receptacles (negatively) predicted littering.\nSupplemental analyses showed that among individuals who\ndisposed of an item, distance to the receptacle was positively\npredictive of littering.Implications for litter prevention\nstrategies are discussed.\n1California State University, San Marcos, USA, 2Action Research, Inc., CA,\nUSA, 3SUNY Plattsburgh, NY, USA\nCorresponding Author:\nP. Wesley Schultz,California State University, 333 SouthTwin Oaks\nValley Road, San Marcos, CA 92096, USA, Email: <wschultz@csusm.edu>\nKeywords: Littering, field study, behavioral observation\n2\nLitter is any piece of misplaced solid waste (Geller, 1980). This\ncan range from small items, such as cigarette butts or candy\nwrappers, to abandoned automobiles, appliances, and even\nspacecraft. Most commonly, litter refers to items that are\ndiscarded by an individual, but it can include any item that is in\nan unacceptable location, regardless of the origin. This could\nnot only include the candy wrapper dropped on the ground but\nalso the newspaper that blows out of a trash can. The\ndistinction here is between litter (the item) and littering (the\nbehavior). Although the exact percentage of litter attributed to\nimproper disposal behavior by individuals is unknown, there is\nevidence to suggest that a large majority of litter is linked with\nindividual disposals (MSW Consultants, 2009). A recent\nanalysis of the sources of litter along roadsides attributed 70%\nto individuals (52% to motorists and 18% topedestrians). In\ncomparison, 21% came from unsecured loads, 5% from the\nvehicles themselves (e.g., tires and vehicle debris), and 3%\ncame fromunsecured containers in the nearby vicinity.\nSimilarly, at transition points such as bus stops, 88% of the\nsmall littered items were attributed to individuals, as was 90%\nof large items (69% to pedestrians and 21% to motorists).\nThese findings underscore the importance of the individual as a\nsource of litter.\nLitter poses a number of important environmental, social,\nand aesthetic problems. As an environmental problem, litter is\na substantial source of contamination. Misplaced plastics,\nStyrofoam, paper, glass, and many other commonly used\nconsumer materials accumulate in the environment, posing a\nnumber of harmful environmental consequences. The social\nproblems related to litter include safety hazards, fire hazards,\nhuman health hazards, and indirect health hazards from\nbacteria, rats, roaches, and mosquitoes that are attracted to\nlitter. In addition, litter is predictive of changing crime rates in\na community (Brown, Perkins, & Brown, 2004), and there is\nexperimental evidence showing that the presence of litter\nresults in an increase in othersocial transgressions like theft\n(Keizer, Lindenberg, & Steg, 2008). There are aesthetic issues\n3\nwith litter, as there is near unanimous agreement that litter is\nunsightly (Pandey, 1990). Indeed, the presence of litter in a\nresidential com- munity decreases property value, and litter in\ncommercial areas reduces sales and attracts fewer customers","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:1","document_content":"(National Association of Home Builders, 2009; Skogan, 1990).\nFinally, there are the direct costs of litter cleanup, which\nconservatively tops US\\$11 billion annually in the United States\n(MSW Consultants, 2009).\nGiven the myriad of problems that result from litter, it is not\nsurprising that a sizable amount of research has focused on\nunderstanding and preventing it. Litter was one of the first\nenvironmental problems to lend itself to systematic behavioral\nresearch, with studies going back more than 40 years. In an\nearly 1968 study, Keep America Beautiful (KAB) reported on\nthe attitudes, beliefs, and self-reported behaviors among a large\nnational sample (Public Opinion Surveys, Inc., 1968).\nSubsequently, studies throughout the 1970s were used as a\nbasis for creating litter prevention programs (Burgess, Clark, &\nHendee, 1971; Cone & Hayes, 1980; Geller, Winett, & Everett,\n1982). In the section below, the three dominant approaches to\nunderstanding litter and littering behavior are summarized.\nPrior Studies of Litter\nWho litters? One approach to understanding littering focuses\non the demo- graphic and personal qualities of the type of\nperson who litters---the \"litter bug.\" Although much of these\ndata come from surveys in which people self- report littering\nrates, a few studies have conducted observations (e.g.,\ndistributing a marked flyer or handbill under varying\nconditions and monitoring to see which accumulate as litter).\nThe widely accepted conclusions from these studies are that\nlittering is more common among males, younger adults, and\nindividuals living in rural communities more than cities.\nHowever, the research results on these characteristics of the\n\"litter bug\" are far from conclusive and many studies have\nfailed to find significant demographic predictors (Beck, 2007;\nFinnie, 1973; Geller, Witmer, & Tuso, 1977). As a result, there\n4\nis little consistent evidence for demographic characteristics of\nthe \"litter bug.\"\nHow often do people litter? Given the volume of litter that\naccumulates nationally and worldwide, it is important to\nunderstand the littering behavior of individuals. One way to\naddress this question is by watching the behavior of individuals\nin public spaces(Geller et al., 1977; Heberlein, 1971).Although\nonly a handful of studies have utilized observational methods,\nthe results are instructive. An early study by Finnie (1973)\nreported observations of individuals in four outdoor spaces in\nPhiladelphia as they ate hot dogspurchased from street\nvendors. Of the 272 observed individuals, 91 littered the\nwrapper (33%). Littering was more common in sites that were\nalready littered and in sites without trash receptacles. Similarly,\nCialdini, Kallgren, and Reno (1991) and Cialdini, Reno, and\nKallgren (1990) placed flyers on the windshields of parked cars\nand observed the percentage of individuals who littered. In one\nillustrative finding, they found that 14% of the individuals\nlittered when the environment was litter free, whereas 32%\nlittered into an already-littered environment. In an interesting\nextension of these findings, Keizer et al.\u00a0(2008) found that\nparticipants were more likely to litter into \"disordered\" settings (those with graffiti or fireworks or shopping carts left\nunreturned). These findings illustrate the importance of\nunderstanding the role of the physical context in facilitating or\ndiscouraging littering behavior, andsimilar results have been\nreported in other studies (Williams, Curnow, & Streker, 1997).\nCollected litter. By far, the most commonly used method for\nlitter research is to count and characterize the types of litter\ncollected from different locations (KAB, 2007). Litter cleanups\nhappen on a regular basis, including the KAB (2007) Great\nAmerican Cleanup, regular Adopt-a-Highway cleanups, and\nthe Ocean Conservancy's International Coastal Cleanup. In\naddition, states and local governments regularly conduct \"litter\nsurveys\" to identify the types and sources of materials found\nalong roadways throughout the country. These events remove\nmillions of pounds of litter annually from roadways, parks,\n5\nshorelines, and natural areas worldwide. In the 2007 Coastal\nCleanup, the Ocean Conservancy collected 6 million pounds of\nmaterials, including cigarette butts (1,971,551 or 27% of all\ncollected items), food wrappers (10% of collected items), caps\nand lids (9%), bags (8%), plastic beverage bottles (7%), plastic","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:2","document_content":"utensils (5%), and glass beverage bottles (5%; Ocean\nConservancy, 2007).\nThe current study involved making unobtrusive observations\nof disposal behavior of pedestrians at outdoor sites in which we\nsimultaneously examined demographic characteristics of the\nparticipants as well as contextual variables such as the\npresence, characteristics, and placement of receptacles. As an\nextension of prior littering studies, the current work examined\nboth person-level and context-level predictors of observed\nlittering behavior using a multilevel modeling framework.\nCurrent Project\nAlthough there is a long history of research on litter and\nlittering, a number of fundamental questions remain to be\nanswered. In the current article, the results from a nationwide\nstudy of littering behavior are reported. This research\ninvestigation had three goals: (a) to conduct an observational\nstudy of littering behavior across a diverse sample of sites and\nlocations; (b) to develop a set of observational methodologies\nfor observing littering (including a modified protocol for\nobserving smokers) that could be replicated over time and in\ndifferent locations; and (c) to utilize a multilevel approach in a\nway that would allow for the simultaneous analysis of\npersonal- and contextual-level determinants of littering. At the\nlevel of the individual, we examined the effects of variables\nfound to predict littering in past research: gender (males\nlittering more than females), age (younger littering more than\nolder), and distance from a receptacle (greater distance at the\ntime of disposal predicting higher littering rates). We also\nexplored new potential predictors, including time of day, and\nwhether being in a group might be associated with lower\nlittering rates because of social disapproval. At the level of the\n6\ncontext, past research led us to expect that littering would\noccur more often: in sites that were high in existing litter, in\nsites with fewer receptacles, and in sites with no existing\nsignage about littering. We also explored several less widely\nstudied variables, including rural versus urban locations,\ncleanliness, landscaping, infrastructure, and the number of\npeople within the location.\nMethod\nSites and Participants\nDuring the spring of 2008, systematic observations of\nindividuals were con- ducted in a wide range of outdoor public\nlocations across the United States. The research design was\ndeveloped as a multilevel model, with random samples of\nindividuals \"nested\" within site (see Raudenbush & Bryk,\n2002). At each location, random samples of individuals were\nselected, and their behavior was unobtrusively monitored as\nthey moved through the site. A modified protocol was\ndeveloped for monitoring the behavior of smokers, which\nincluded the various means by which smokers typically dispose\nof their butts.\nObservations were conducted in 10 states (Arkansas,\nCalifornia, Georgia, Illinois, Kentucky, Nevada, New Mexico,\nNew York, Utah, and Vermont), selected to represent a variety\nof regions across the country. Within each state, an urban,\nrural, and suburban city was selected using U.S. Census\nstatistics. Finally, within each of those cities, specific\nobservation sites were randomly selected from a list of all\npossible sites of each type: city center, fast food, recreation,\ngas station, and rest stop. Three additional site types were\nselected for observations of cigarette smokers: medical,\nbars\/restaurant, and retail.\nThe final data set included observations of 9,757 individuals\nfrom 130 locations: 86 general litter and 44 focused on\ncigarette disposal. Of these, 30 were recreational, 24 city center,\n22 fast food, 12 retail, 12 bars\/restaurants, 11 gas stations with\n7\nconvenience stores, 11 rest stops, and 8 medical facilities.\nProcedure\nSystematic observations were made by pairs of observers\nfollowing a strict protocol that was developed after\nconsiderable training. The protocol and code sheets are\navailable on request from the authors. On arrival at the research\nsite, the field team first defined the physical boundary of the","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:3","document_content":"observation area. This would be an area that the team could\nclearly observe from an unobtrusive lookout point (e.g., in a\npublic seating area or inside a parked car). This lookout point\nwas typically at the back border of the observation area. This\nenabled the research team to remain forward facing (which was\nnecessary when they were inside a parked car) and increased\ntheir ability to remain unobtrusive. These boundaries were\ntypically areas of about 2,000 square feet that allowed for\nunobstructed and unobtrusive observations of individuals. This\nobservation area always included the most heavily trafficked\npart of the site (e.g., the entrance\/exits to the nearest building).\nBefore observing any participants, the research team used a\ndetailed codebook to record a variety of characteristics related\nto the setting.\nSetting characteristics. The codebook provided a variety of\ncategorical and continuous measures for the research team to\nrecord for each setting. The research team specified the site\ntype---recreational, city center,fastfood,retail, bar\/restaurant,\ngasstation with convenience store, reststop, or medical facility\n(categorical measure); identified whether the location was\ncategorized asrural, urban, or suburban (categorical measure);\nrecorded the time of day as before noon, afternoon, or after 4:00\np.m. (categorical measure); rated the amount of existing litter in\nthe location from 0 = not at all littered to 10 = extremely littered\n(continuous measure); indicated whether or not each of 9\ndifferent types of litter (e.g., paper, food wrappers, cans, bottles,\netc.) was present or absent (categorical); rated the amount of\ncigarette butt litter present from 0 = not at all littered to 10 =\nextremely littered (continuous); counted the number of cigarette\n8\nbuttsin the observational area (continuous); rated the overall\ncleanliness of the site from 0 = not at all clean to 10 =\nextremely clean (operationalized as free from bad smells, litter,\nunkempt infrastructure, and objects that do not belong in the\nlocation; continuous); judged the landscaping (operationalized\nas the presence and care of foliage; continuousfrom 0 = not at\nall landscaped to 10 = extremely landscaped); and rated the\noverall infrastructure from 0 = low infrastructure to 10 = high\ninfrastructure (operationalized as the placement of physical\nobjects within a location as a means to increase the aesthetics,\nwalk- ability, cleanliness, and landscaping of the area). This\nincluded planters, paved walkways, benches, and trash\nreceptacles(continuous).The research team also recorded the\nnumber oftrash receptaclesfor each offive receptacle types:\ntrash can, ashtray, ash\/trash combination, dumpster, and\nrecycling (continuous). For analytic purposes, these were\nsummed to produce a single score of the total number of\navailable receptacles. The team recorded whether or not there\nwas littering signage present (dichotomous, 1 = yes, 0 = no).\nFinally, they rated the crowdedness of the location from 0 = not\nat all crowded to 10 = extremely crowded, operationalized as the\ninability to move freely. It was defined for the observational\nteam asthe combination of the number of people in the location,\ngiven the features of the location (continuous). These measures\nof the setting were made to examine the impact of contextual\nvariables on participants'littering behavior.\nParticipant characteristics. After recording the details of the\nsetting, the research team randomly selected a participant by\ntaking the Nth person to enter the space, with N determined\nusing the crowdedness of the location and ranged from 1 to 6.\nRandom selection of the individual participant at each site is a\nkey aspect of this research protocol, and it provides data that\ncan be used to calculate a littering rate for each site as well as\nthe data needed to analyze the personal and contextual-level\npredictors of littering.\nThe research team recorded each participant's gender,\napproximate age, whether the selected participant was alone or\n9\nwith one or more others, and noted one of three possible disposal\noptions: the participant did not have an item to dispose, the\nparticipant had an item to dispose but left the site carrying the\nobject, or the participant disposed of the object. No other\nobservations were made for participants who had no object to\ndispose or who left the site with the object.\nThe research team made additional recordings for only those","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:4","document_content":"participants who disposed of an object. They recorded whether\nthe object was disposed of properly or improperly. Proper\ndisposal was operationalized as any disposal that resulted in the\nobject being placed in a receptacle, including ashtray, trash can,\nor recycling bin. Items placed in the wrong receptacle (e.g.,\ntrash in a recycling container or cigarette butts in a trash can)\nwere not coded as litter. For analytic purposes, these disposals\nwere coded as \"proper.\" Also coded as proper were pocketing\nthe item or handing it to another person. Improper disposals\nincluded disposals on the ground, planters, bushes or\nshrubbery, or disposals on or around receptacles. The research\nteam also recorded the type of object disposed using a code\nsheet with 13 options, including an open- ended option for\n\"other.\"\nOf those who were observed to have littered, the researchers\nrecorded the person's intent to litter using eight categories,\ndrawing on prior work by Williams et al.\u00a0(1997): drop without\nintent, drop with intent, flick, shoot and miss, inch away,\nwedge, sweep, or 90%. All but the first coded category were\nclassified as \"with intent.\" Drop with intent was a subjective\nclassification made by the coder and required one of two\nspecific actions: the individual visually inspected the item\neither at the point of disposal or immediately fol- lowing, or\nthere was an observable hand movement indicating an\nintentional discard (e.g., flick, toss, fling, wedge, and sweep).\nThe disposal strategies of drop, flick, and shoot and miss\ninvolved the intentional placement of the item in an improper\nlocation; sweep strategies involved brushing items from a flat\nsurface unto the ground; and \"90%\" codes included instances\nwhere the individual collected other items for proper disposal\n10\nbut intentionally left one or more objects behind. More detailed\ndescriptions of these eight intentional disposal strategies can be\nfound in Williams et al.\nFinally, the research team recorded littering participants'\ndistance (in feet) from receptacles at the time they littered. Any\ndiscrepancies were resolved through discussion. Observations\nwithin each site continued until 30 participants were observed\nmaking a disposal (proper or improper) or until the conclusion\nof an 8-hour observation period.A minimum of 4 hours of\nobservations were conducted at each site.\nResults\nReliability Measures\nDuring training, the research team conducted multiple sessions\nduringwhich they practiced coding both the settings and\nindividuals. These training sessions were conducted until the\npairs of raters achieved a minimum of 80% agreement for the\ncategorical variables of the setting and r = .70 for continuous\nvariables of the setting. The reliabilities reported below are the\naverage percentage agreements and correlations across pairs of\nteam members on the final day of training:\n\u2022 Did the person have an item for disposal in his or her\nhand (dichotomous, 1 = yes or 0 = no)? Percentage of\nagreement, 93%.\n\u2022 Did the person dispose of an item while within the\nobservational boundary (dichotomous, 1 = yes or 0 = no)?\nPercentage agreement, 95%.\n\u2022 Did the disposalresult in litter(dichotomous, 1 = yes or 0 =\nno)? Percent- age of agreement, 97%. This variable served\nasthe primary outcome.\n11\n\u2022 Type of item disposed? (categorical: 13 options plus\n\"other\"). Percentage of agreement excluding \"other,\"\n97%.\n\u2022 For individuals who were observed littering, was there\nclear intent (dichotomous, 1 = yes or 0 = no)? Percentage of\nagreement, 98%.\n\u2022 For individuals who were observed littering, what was\nthe distance to the closest receptacle at the point of\nlittering, in feet (r = .94).\nDuring actual data collection, additional reliabilities were\ncomputed using data from 127 observed individuals at three\nsites obtained from three pairs of the field team. The following\npercentage agreement was found: gender(95% agreement),\napproximate age (r = .94), whether the individual was alone","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:5","document_content":"(96% agreement), and time of day (100% agreement).\nThe data were analyzed as a multilevel model, which\nallowed for both individual- and context-level predictors of\nlittering behavior (Hox, 2002; Raudenbush & Bryk, 2002). The\nsummary below begins with basic descriptive statistics from\nthe observations and then proceeds to report the results from\nthe hierarchical linear model. Results from the multilevel\nmodels are reported following convention, with \u03b2 representing\nunstandardized Level-1 coefficients (in these analyses, personlevel predictors) and \u03b3 representing unstandardized Level-2\ncoefficients (in these analyses, context-level predictors).\nMeasures of variability are also reported, with \u03c3 representing\nvariance at Level 1 (person-level) and \u03c4 for variance at Level 2.\nDescriptive Statistics\nAcross the 130 sites, 118 of them (91%) had at least one trash\nreceptacle. These included 64 sites with uncovered trash cans,\n58 sites with lidded trash cans, 43 sites with ash receptacles, 16\nsites with recycling bins, 18 sites with combined trash can\/ash\nreceptacles, and 12 sites with dumpsters. Many of the sites had\nseveral types of receptacles, so the total exceeds 130. Of the\n12\n130 sites, only 2 had no visible litter within the observation\nboundary. By count, the most frequently observed visible litter\nincluded cigarette butts and miscellaneous paper. The number\nof sites with various types of litter is shown in Table 1. \"Other\"\nitems included diapers, dog waste, fishing gear, clothing, and\nchildren's toys. These findings indicate that although trash\nreceptacles are quite common in public spaces, ash receptacles,\nand (particularly) recycling bins are less common.\nObservations of littering in general were made at 86 sites\nacross 10states. A total of 8,990 general observations were\nmade; an additional sample of 767 smokers is reported\nseparately below. The general observations were evenly\ndivided across rural (33%), suburban (34%), and urban areas\n(33%). Observations were made throughout the day, with 27%\nmade in the morning before noon, 58% in the afternoons\nbetween noon and 4:00p.m., and 16% in the evening after\n4:00p.m. Of the observations, 56% of the observed targets were\nmale, and 44% were female. Observed ages ranged from 1 to\n82 (M = 38, SD = 16), and 50% of the observed individuals\nwere alone.\nOf the 8,990 people who were observed, 2,472 left the site\nwith no object for disposal (28%), 4,534 left the site with an\nobject (50%), and 1,962 dis- posed of an object while on site\n(22%). Among these disposals, there were 342 instances of\nlittering observed. That is, of all 8,990 individuals that were\nobserved moving through a diverse range of sites, 4% littered.\nIn addition, of all the disposal behaviors that were observed (N\n= 1,962), 342 (or 17%) were improperly disposed by littering.\nThe remaining proper disposals included trash receptacle\n(60%), pocketing the item (9%), handing the item to another\nperson (6%), ashtray (6%), and recycling bin (1%).\n13\nTable 1. Percentage of Sites (out of 130) With that Litter Type\nPresent and Percent of Participants who Disposed of that Item\nImproperly\nLitter type % sites with this\ntype of litter\npresent\n% participants who\ndisposed of item\nimproperly\nCigarette butts 82 (fo = 106) 57 (n = 194)\nPaper 67 (fo = 87) 7 (n = 20)\nFood wrappers 45 (fo = 58) 14 (n = 14)\nConfections 34 (fo = 44) 0 (n = 0)\nNapkin\/tissue 34 (fo = 44) 8 (n = 9)\nMiscellaneous\nplastic\n33 (fo = 43) 0 (n = 0)\nFood remnants 24 (fo = 31) 20 (n = 16)\nBeverage cup 16 (fo = 21) 3 (n = 5)\nBeverage bottle:\nplastic\n11 (fo = 14) 5 (n = 5)\nFood containers 9 (fo = 12) 2 (n = 1)","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:6","document_content":"Plastic bags 8 (fo = 11) 5 (n = 2)\nBeverage can 6 (fo = 8) 12 (n = 8)\nBeverage bottle:\nglass\n5 (fo = 6) 0 (n = 0)\nYard waste 5 (fo = 6) 0 (n = 0)\nCombination\/mixed\ntrash\n0 (fo = 0) 4 (n = 12)\nOther 27 (fo = 35) 37 (n = 46)\nUnknown 0 (fo = 0) 8 (n = 10)\n14\nOf the 1,962 coded disposals, the most frequent were\ncigarettes (N = 340), mixed trash (N = 337), and paper (N =\n272). Table 1 also shows the types, frequencies, and littering\nrates for the disposed objects. The table shows the frequency of\nproper and improper disposals, along with the percentage of\neach type of material that was littered (computed as improper \/\nproper + improper). The \"other\" category includes a number of\nlow-frequency disposals, including pet waste, candy and other\nconfections, matches and cigarette lighters, diapers, straws,\nchewing tobacco, and miscellaneous product pack- aging like\nprice tags, foil wrappers, and twist ties.\nThe 342 acts of littering were coded into discrete disposal\nstrategies, along with coded intent. The most frequent littering\nstrategy was to drop with intent (N = 183, 54%). That is, the\nperson committed a clear and deliberate act of littering. Other\nlitter strategies included flick (N = 68, 20%) and drop without\nintent (N = 42, 12%). The behaviors were also coded into\nlittering strategies found in prior research (Williams et al.,\n1997): inch away (N = 8), shoot and miss (N = 8), wedge (N =\n4), sweep (N = 3), and 90% (N = 2). When combined, an\nestimated 81% of observed littering occurred with intent.\nThe observation team coded the distance (in feet) from the\ndisposer to the nearest receptacle (trash, recycling, or ashtray).\nAlthough there were several instances of littering that occurred\nimmediately adjacent to a receptacle, most littering occurred at\na considerable distance (mean distance to a receptacle at time\nof littering was 29 feet).\nMultilevel Modeling\nFinally, a series of statistical analyses were conducted to\nexamine the individual and contextual variables that were\npredictive of littering. The analysis was conducted using only\ndata from observations where a disposal (either proper or\nimproper) occurred (N = 1962). Multilevel modeling is a\nstatistical technique that allows for \"nested\" data structures (in\n15\nthis case, individuals nested within site). In addition, the\nmultilevel approach does not require balanced data (i.e., equal\nnumbers of observations per site) and instead utilizes all\navailable information to estimate the underlying effects. The\napproach makes it possible to simultaneously model\nindividual-level and contextual- level variables and to estimate\nthe percentage of total variance in the out- come measure that\nresults from each (quantified as the IntraClass Correlation\nCoefficient \\[ICC\\]). The analysis was conducted as a two-level\nmodel, with person at Level 1 and context at Level 2. The\nanalyses were conducted in SPSS 19 using MIXED LINEAR.\nThis analysis assumes a continuous and normal dependent\nvariable (which was violated). A parallel set of analyses were\nalso performed using the SPSS 19 GENLINMIXED procedure\nand specifying a logistic link function and binomial\ndistribution. For ease of interpretation, we have presented the\nresults in the original probability units from the continuous\nSPSS MIXED multilevel model (0 = no littering and 1\n= littering), rather than log-odds units. The conclusions are the\nsame as those obtained using a logistic link function.\nThe initial random effects model showed that the overall\nlittering rate was .17. That is, of all disposals, 17% were\nimproper, t(74.86 = 9.87, p \\< .001). Acrossthe 1,962 disposals,\n\u03c3 = .12, Z = 30.66, p \\< .01, and the 86 locations, \u03c400= .022, Z =\n5.71, p \\< .01, there was considerable variability in the littering\nrate. The ICC was .15. This statistic is directly interpretable,\nand it indicates that 15% of the variance in littering behavior\nresulted from site-level variables, whereas 85% resulted from","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:7","document_content":"individual variability. This finding shows that on a national\nlevel, the large majority (85%) of littering behavior results from\nindividual-level variables (e.g., age, gender, attitudes, and\nmotivation). This is not saying that physical context does not\nmatter, and in fact, these resultsshow that 15% of the variance in\nobserved littering behavior was due to some aspect of the\ncontext (e.g., existing litter, lack of convenient receptacles, etc.).\nThe second set of analyses focused on individual-level\npredictors of littering behavior: age, gender, time of day, and\nwhether the individual wasalone. Results showed that age, \u03b2 =\n16\n\u2212.001; df = 1943, t = \u22122.15, p \\< .05, and gender, \u03b2 = \u2212.06; df =\n1943, t = \u22123.42, p \\< .05, were the only significant predictors,\nwith older individuals littering less than younger and males\nlittering more than females. Time of day and being alone were\nnot significantly predictive of littering. For clarification, age\nwas coded into demographic categories. The highest rate of\nobserved littering occurred for younger individuals, aged 18 to\n29 years, for whom the littering rate was 26%. For adults 30\nyears and older, the littering rate remained steady at\napproximately 15%. Children and adolescents (younger than 18\nyears) had a littering rate of 13%. The gender effect in the\ngeneral littering observations showed that men (21%) littered\nmore than women (15%). No other individual-level variables\nwere predictive of littering. However, the variability in the\nLevel-1 equation remained statistically significant, indicating\nthat other variables are required tofully explain individual\nvariability in littering. Combined, age and gender explained\nless than 1% of the residual variance at Level 1.\nUsing the hierarchical structure of these data, the contextual\npredictors of littering behavior were analyzed: site type (e.g.,\ncity center and fast food), location type (rural, urban, and\nsuburban), amount of existing litter present, beautification\nefforts in the area (included ratings for cleanliness,\nlandscaping, and infrastructure), availability and number of\nreceptacles(summed number across trash, ash, and recycling),\nposted signage about littering, and crowdedness of the location.\nGiven the relatively large number of predictor variables,\nparticularly with the dummy coded categorical variables of site\ntype and location type, the multilevel model was conducted\nthrough a building process as recommended by Raudenbush\nand Bryk (2002). The analysisstarted by testing each dummycoded categorical variable, sequentially, and removing\nnonsignificant predictors. The continuous predictors were then\nexamined, again removing nonsignificant predictors. The\ncumulative results from these analyses revealed two uniquely\nand statistically significant predictors: availability of disposal\nreceptacles and amount of litter present. The first was the\n17\nnumber of disposal receptacles. As part of the site observations,\nthe team counted the number of receptacles (trash, recycling,\ncigarette, and dumpster), along with the distance from the\nperson at the time of disposal. The average was 5.8 bins per\nlocation, with a range from 0 to 19. The analysis for presence\nof receptacles revealed the expected finding that littering rates\nwere higher when no receptacle was present. But more relevant\nto the current research questions, among sites with at least one\nreceptacle, the statistical analysis showed that locations with\nmore receptacles had a lower littering rate, \u03b3 = \u2212.01, df =\n73.42; t = \u22122.52, p \\< .05. Thisstatistical coefficient can be\ninterpreted directly, such that for every added trash receptacle,\nthe littering rate decreased by 1% (from the overall rate of\n17%).\nThe second statistically significant predictor of littering\nbehavior was the presence of litter in the site. Locations with\nmore litter were associated with a higher littering rate. The\nstatistical analyses showed that the presence of existing litter\n(rated by the observers on a scale from 0-10) was predictive of\nlittering behavior, \u03b3 = .02, df = 82.01; t = 2.40, p = .018. This\nindicates that for every unit increase in the amount of existing\nlitter (from 0-10), the observed littering rate increased by 2%.\nWith both predictors in the model, the variance at Level 2\nremained statistically significant, indicating that more variables\nare needed to fully explain the variability across site. Combined,\nthe two variables explained 9% of the Level-2 variance, but the\nvariability in littering rates across the sites remained","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:8","document_content":"statistically significant, \u03c4 = .019; Z = 4.60, p \\< .001.\nSupplemental analyses were also conducted using the Level1 predictor of distance to the nearest receptacle. This analysis\nwas performed using the multilevel framework but only for\nobservations at sites with at least one receptacle (of any type).\nResults showed that distance to a receptacle at time of disposal\nwas strongly related to the likelihood of littering, \u03b2 = .007; df =\n1926, t = 17.95, p \\< .001. Distance to the receptacle\nexplained 11% of the\n18\nresidual variance at Level 1, \u03c3 = .108, Z = 30.55, p \\< .001. Note\nthat distance was coded in feet, so that for each added foot of\ndistance from a receptacle at the time of disposal, the\nprobability of littering increased by .007. For clarification, we\ncalculated littering rates for disposals at seven different\ndistances, each of 10-foot increments. For disposals that\noccurred within 0 to 9 feet of a receptacle, littering rates were\n12%. At the largest distance (60 or more feet), littering rates\nwere 30% of disposals.\nObservations of smokers. In addition to the large number of\ngeneral littering observations, the field team also conducted a\nsmaller number of observations of smokers. The separate focus\non smokers was based on two considerations. First, unlike the\ngeneral littering observations of individuals moving through a\npublic space, all smokers have something to litter---a cigarette\nbutt. Second, cigarette butts constitute the most frequently\ncollected litter worldwide.\nThe observations were made using the same protocol\ndescribed above, with a few modifications. First, only\nindividuals who were (estimated) over the age of 21 were\nutilized. This qualifier was imposed to provide consistency\nacross our observational protocol and to respond to the\npossibility of local restrictions on tobacco use for individuals\nyounger than 21 years. Second, a measure of existing litter was\nincluded at each site that focused on the number of cigarette\nbutts within the observational boundary. Third, the measure of\nexisting receptacles focused on only ashtrays (or trash\/ash\ncombinations). As with the previous study, disposals of\ncigarette butts were coded as proper if they reached any type of\nreceptacle and not necessarily an ashtray.\nIn total, observational data were obtained from 767 smokers\nfrom 44sites (11 recreational, 12 bars\/restaurants, 12 retail, 8\nmedical, and 1 city center). There were 412 males and 344\nfemales, ranging in age from 21 to 72 (M = 40, SD = 13; 11 not\ncoded). Of the 767 observed individuals, 206 (27%) left the\nobservation area still smoking, and the disposal behavior of 31\n19\nsmokers could not be clearly established. Of the remaining 530\nsmokers, 187 properly dis- posed of the butt (35%) and 343\nimproperly disposed (65%). When the butt was littered, drop\nwith intent was the most frequently used strategy (35%),\nfollowed by flick (27%), stomp (27%), and \"other\" (1%,\nincluding placing the butt on or near a receptacle). Although\nthere were several instances of littering near a receptacle, most\nlittering occurred at considerable distance from a receptacle\n(average distance at time of littering was 31 feet).\nThe data analytic strategy followed the multilevel model\napproach used above, in which the individual and contextual\npredictors of littering were examined simultaneously. The\nreported results were calculated using the MIXED command in\nSPSS version 19, and the results are reported in original\nprobability units. The analysis was performed on 530 cases\n(187 proper disposals and 343 littered). The results from the\nmultilevel model showed that across the 530 individuals, \u03c3 =\n.135, Z = 15.70, p \\< .001, and the 44 locations,\n\u03c400 = .081, Z = 4.73, p \\< .01, there was considerable variability\nin the littering rate. The ICC was .38, indicating that 38% of the\nvariance in cigarette littering resulted from contextual variables,\nwhereas 62% resulted from individual variability. This is a\nconsiderably higher clustering effect than that observed for\ngeneral littering behavior, and it suggests that cigarette butt\ndisposal is more affected by contextual-level variables than are\ngeneral disposals (see recommendations section below).\nAt the level of the individual (Level 1), only age emerged as\na statistically significant predictor, with older individuals\nlittering less than younger, \u03b2 = \u2212.004, df = 518.49; t = 2.93, p","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:9","document_content":"\\< .01. The highest littering rates occurred for smokers in their\n20s (66% littering rate) and 30s (72%), compared with smokers\nin their 40s (58%), 50s (66%), and 60s (50%). Age explained\nless than 1% of the Level-1 variance, and the variability across\nindividuals remained statistically significant, \u03c3 = .134, Z =\n15.59, p \\< .001, suggesting the need for additional predictors.\nNeither gender, time of day, nor being part of a group were\nrelated to cigarette butt littering.\nAt the level ofsite (Level 2), analyses utilized the contextual\n20\npredictors used in the analyses of general litter (with minor\nmodifications noted above). The resultsshowed three uniquely\npredictive variables:site type, existing litter, and presence of ash\nreceptacles. One ofthe strongest predictors of cigarette littering\nwasthe number of ash receptacles, \u03b3 = \u2212.09, df = 31.91, t =\n\u22122.13, p \\< .01). The parameter estimate from the analysis is\ndirectly interpretable, and it indicates thatfor every added ash\nreceptacle,the littering rate for cigarette butts decreased by 9%\n(from the initial base littering rate of 65%). The second\nsignificant predictor of cigarette litter was the amount of\nexisting litter, \u03b3 = .05, df = 39.01, t = 2.24, p = .03, with more\nlittered environments attracting more cigarette butt litter. Note\nthat the existing litter is of any type and not just cigarette butts.\nResults also showed an effect for site type, where retail locations\nwere associated with the lowest rate of littering (58%),\nfollowed by city centers (58%). Bars and restaurants were third\n(62%), whereas recreational (74%) and medical\/hospital sites\n(75%) had the highest littering rates. Combined, these three\nvariables explained 24% of the variance at Level 2, although the\nvariability in littering rates across site remained statistically\nsignificant, \u03c4 = .061, Z = 3.21, p \\< .01,suggesting the need for\nadditional predictors.\nFinally, supplemental analyses were conducted to examine\ndistance to an ash receptacle at time of disposal. Commensurate\nwith the previous analyses, this Level-1 predictor was\nexamined within the multilevel framework but only using\ndata from sites with at least one ash receptacle. Results showed\nthat distance to the nearest receptacle was strongly predictive of\nlittering, \u03b2 =\n.005, df = 292.79, t = 6.93, p \\< .001. Although a few instances\nof littering were observed immediately adjacent to an ash\nreceptacle, the average distance for litterers was 31 feet away.\nDiscussion and Conclusions\nThe results from these litter observations support a number of\nconclusions. First, the overall littering rate was 17%. That is, of\nall the disposals observed across the country, 17% were\n21\nimproper. In addition, of the individuals sampled from 86\nlocations nationwide, 4% littered as they passed through the\nsite. For cigarette butts, the littering rate obtained from the\nfocused observations was 65%. This is a strikingly high\nnumber, despite the strong norm favoring proper disposal that\nhas emerged over the past 40 years (see Bator, Bryan, &\nSchultz, 2011).\nImportantly, this littering rate was generated from a random\nsample of individuals across a range of different locations and\nnot just a few isolated observations or of one type of location.\nIn addition, the results showed that in the majority of instances\n(81%), the littering occurred with intent.\nThe results from these analyses underscore findings from\nstudies con- ducted nearly 40 years ago (Burgess et al., 1971;\nFinnie, 1973; Geller et al., 1977). Although much has been said\nabout litter and littering over the years, no study has afforded\nthe opportunity to simultaneously test the degree to which it is\naffected by personal and contextual variables. In fact, to our\nknowledge, this is the first article to examine the same behavior\nacross a large number of contexts---a procedure which allows\nfor a quantitative analysis of \"personal\" and \"environmental\"\ninfluences on behavior. The results of the current research\nindicate that 15% of general littering acts result from contextual\nvariables, and 85% result from personal qualities. This finding\nis particularly instructive because it indicates that given the\nsame infrastructure and opportunities to properly dispose,\nindividuals will vary tremendously. Note that if the trend had\nbeen reversed, such that 85% of the variance was due to the","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:10","document_content":"situation, it would indicate that while individuals vary across\nsettings, within a setting they act similarly (e.g., littering or\nnot).\nThe results from the analyses of littering behavior identified\nonly a couple of significant predictors. Interestingly, gender\nwas not a consistent predictor of littering behavior. Gender was\na significant predictor of littering in the general observations,\nwith males littering more than females. However, gen- der was\nnot a significant predictor of littering for cigarette butts. This\n22\nsecond finding runs contrary to prior data showing that men are\nmore likely to litter than women (Meeker, 1997; Torgler,\nGarc\u00eda-Vali\u00f1as, & Macintyre, 2008) but is consistent with other\nobservational studies showing no gender effects (Finnie, 1973;\nGeller et al., 1977; Williams et al., 1997).\nAt the individual level, the results did show a consistent and\nstatistically significant effect for age, with young adults (18-\n29) more likely to litterthan older adults. The negative\nrelationship between age and littering has been documented in\nseveral survey studies of littering behavior (Beck, 2007), with\nresearchers reporting that younger people tend to litter more\noften than those who are older (e.g., Durdan, Reeder, Hecht,\n1985; Finnie, 1973; Heberlein, 1971; Krauss, Freedman, &\nWhitcup, 1978). Krauss et al.\u00a0(1978) also found that younger\nparticipants were more likely to litter. They considered that\nnormative control requires both internal controls and cognitive\ninformation, both of which develop through the socialization\nprocess.\nAt the level of the location, presence and number of trash\nreceptacles, along with the amount of litter present were\nsignificant predictors oflittering behavior. These findings are\nconsistent with previous studies (Cialdini et al.1990; Meeker,\n1997), although Roales-Nieto (1988) reported results show- ing\nthat adding more receptacles did not result in reductions in\nlitter. This latter finding suggests that a raw count of\nreceptacles is probably an overly simplistic consideration.\nIndeed, the current study shows that convenience (i.e., distance\nto a receptacle) plays an important role. One well-placed\nreceptacle is likely to produce a larger reduction in littering\nthan several inconveniently placed receptacles.\nTo this end, it is tempting to ask about the \"optimal\" spacing\nbetween receptacles. Although these data do not speak directly\nto this issue, there is evidence that the lowest littering rate\noccurs when receptacles are available and close at hand. This\neffect was consistent for both general littering and disposals of\ncigarette butts. Further inspection of the data showed that\naggregated observed general littering rates were low (and\n23\nrelatively flat at 12%) for receptacles less than 20 feet away.\nThe littering rates increased linearly between 21 and 60 feet\nand then remained relatively flat at 30% for receptacles 61 feet\naway and beyond. It is also important to point out that\n\"optimal\" spacing will vary by location, and the key\nconsideration is the distance to the receptacle when the\nindividual has an item for disposal. The current results showed\nthat the lowest rate of littering occurred when a receptacle was\nfewer than 20 feet away. To deter littering, we encourage\nthoughtful placement of receptacles so they are in the most\neasily accessible location depending on where pedestrians are\nlikely to be when they are in need of making a disposal.\nThe observations ofsmokersrevealed similar findings. First,\nwith regard to cigarette butt litter, results showed an average\nnational littering rate of 65%. Thisissubstantially higher than\nthat found for littering in general and corroborates the high\nnumber of cigarette butts collected in cleanups worldwide. As\nwith general litter, younger individuals were more likely to\nlitter than older, although the overall rate of improper cigarette\ndisposal was above 50% for all age groups. With regard to the\nmultilevel analyses, resultsshowed a clustering effect of .38,\nindicating that a substantial amount of variability in littering\nbehavior results from contextual variables. Subsequent analyses\nrevealed that the lack of convenient ash receptacles, and sites\nwith high levels of existing litter (of any type, not just cigarette\nlitter), were predictive of higher litter rates. Although the\nlittering rates reported in this article are based on a large,","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:11","document_content":"national sample, it is important to acknowledge a few\nmethodological limitations. First, the sample cannot be\nconsidered representative of all individuals in the United States.\nAlthough the reported results are based on random samples of\nindividuals within each site and of randomly selected specific\nsite locations across the country, the type of sites where\nobservations were made was not randomly determined. That is,\neight specific types of sites were selected for observations\n(e.g., retail and recreational) at the outset of the study, and\nalthough diverse, these eight site types cannot be considered\n24\nrepresentative of all physical environments across the country.\nAlthough drawing a random sample of physical locations\nacross the country is methodologically desirable,\nit was not practically feasible in the current project.\nAnother limitation with the littering rate reported in this\narticle is the potential bias toward large or more readily\nobservable items. The observed littering rate of 17% is\nprobably an underestimate for the true littering rate because\nthere were certainly littered objects that went undetected by the\nfield team. Small items, in particular, are likely to be\nunderrepresented using the observational protocol by virtue of\nthe difficulty in seeing them from a distance. It is also possible\nthat the mere presence of the research team in the environments\nmuted the littering rates, although the observational protocol\nwas designed to minimize this influence.\nJust as the observational protocol is likely to underestimate\nthe littering rate, it is also likely to overestimate \"intended\"\nlittering. In coding behaviors in the field, proper disposals are\nrelatively easy to determine, as are intended littering behaviors.\nAlthough the observational teamwas meticulousin observing\nand coding behaviors, unintentional littering isinherently more\ndifficult to detect. As a result, the reported 81% of litter that is\nintentional should be interpreted with caution. This limitation is\nmore applicable to the general littering observations and less\nso for the focused smoker observations. Given that\nintentional littering has been found to be more easily deterred\nthan unintentional littering (Sibley & Liu, 2003) and that we\nrecorded substantially more unintentional littering behavior, we\nencourage tests of litter prevention techniques that promote\nawareness and individual-level motivation.\nFinally, we offer a caution on our interpretation of the ICC.\nThe ICC represents the degree to which the data \"cluster\", and\nin our study, it quantifies the proportion of variance in the\ndependent variable that is attributed to the site, rather than to\nthe individual. At one extreme, an ICC = 1.0 would indicate that\nall of the variance in littering behavior was associated with site\nsuch that all individuals observed within each site were the same\n25\n(either littering or not) but that littering occurred at some sites\nbut not others. On the other extreme, with an ICC = 0, all sites\nwould show the same littering rate, but individuals would vary\nwithin each site. At the site level, we have used contextual\nvariables like the availability of trash receptacles or the amount\nof existing litter as predictors. However, it isimportant to point\nout thatsite-level variance could also be due to shared regional\nor local norms associated with littering in different types of\nlocations or even shared norms about littering in general. To\nillustrate, consider the case of cigarette butt disposal, for which\nwe found an ICC of .38. Although some of this clustering is\ncertainly due to contextual variables like the availability of an\nashtray,some may also be due to the strong norm against\nsmoking and littering in some contexts. For instance, had we\nincluded cigarette butt disposal by staff smoking in a\ndesignated area near an elementary school, the littering rates\nwould likely have been affected more by the norm of social\nresponsibility than by the availability of ashtrays.\nImplications for Litter Prevention\nThe findings from this research point to several strategies for\nlitter prevention. These strategies include a combination of\nboth structural and motivational activities. This section of the\narticle provides a series of recommendations for litter\nprevention that are consistent with the research findings.\nImportantly, this is not an exhaustive list, and readers are\nencouraged to think creatively about ways to link the reported","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:12","document_content":"findings to litter prevention. In addition, it seems likely that\nany single prevention activity will yield only small results, and\nthe most effective approach will utilize multi-pronged\nstrategies that target both structural and personal variables.\nBeautification. The current results clearly show that litter\nbegets littering. This finding is not new, and indeed, it was\nnoted in the early studies of litter (e.g., Cialdini et al., 1990;\nKeizer et al., 2008). However, although most of the early\nstudies presented participants with an object to either litter or\ndispose of properly, the current research was completely\n26\nnonintrusive. We observed genuine behavior in a variety of\nsettings across the United States. Given this methodology, we\nwere able to learn that individuals use a variety of cues from\ntheir surrounding environment to determine what is a common\nand accepted behavior. The presence of litter communicates the\nnorm for that situation and the acceptability of littering. In\naddition, the existing litter will require cleanup, so one more\npiece may seem inconsequential.\nTo this end, a key to the success of any litter prevention\nactivity is to clean up and remove existing litter. Reducing the\namount of existing litter in a location is a surefire way to reduce\nthe rate of littering behavior (Casey &Lloyd, 1977; Huffman,\nGrossnickle, Cope, & Huffman, 1995). In addition, prior\nstudies have found that involving community residents in\ncleanup activities can promote a long-term reduction in litter\nand increase an individual's motivation not to litter (RoalesNieto, 1988).\nBehavioral opportunity. Related to the recommendation for\nbeautification efforts (above), there is also consistent evidence\nfor the importance of opportunity. That is, the context should\nprovide a convenient and accessible means for proper disposal\nof trash and recyclables. Although the current results show the\nwidespread availability of receptacles in public places, results\nalso revealed that distance to a trash can was a strong predictor\nof littering behavior. Providing easily identifiable, accessible\nreceptacles, with clear and recognizable messaging and\nprompts, can go a long way toward reducing littering rates (De\nKort, McCalley, & Midden, 2008; National Cooperative\nHighway Research program, 2009).\nThe issue of behavioral opportunity is especially important\nfor cigarette butts. The reported observational data suggest that\ndisposal of cigarette butts is more strongly clustered within\nlocations, yet less than half (47%) of the locations in the\nsample provided an ash receptacle. Indeed, Liu and Sibley\n(2004) reported a 64% drop in cigarette butt littering by adding\nashtrays on a university campus, although the change did not\naffect attitudes about litter. Similar results were reported by\n27\nGeller, Brasted, and Mann (1980) and by Sibley and Liu\n(2003). Given the increase in legislation prohibiting indoor\nsmoking, an increasing number of smokers are moving outside\nto smoke. However, the infrastructure for collecting ashes and\nlit cigarettes is woefully behind these policies, and the reported\ndata suggest that more efforts to afford smokers an opportunity\nfor proper disposal are needed.\nAwareness and motivation campaigns. In addition to the\nrecommendations for beautification and infrastructure, there is\nan important role for litter prevention strategies that target\nindividual-level motivation. The statistical analyses showed\nthat 85% of the variance in general littering and 62% of the\nvariance in cigarette butt littering resulted from individual\ndifferences. These include demographic, attitudinal, and\nmotivational differences (among others), and they speak to the\nimportance of understanding the individual-level motivations\nand barriers to littering (McKenzie-Mohr, 2002).\nOne way to promote individual-level motivations is through\noutreach and media messages (Nolan, Schultz, & Knowles,\n2009). Although prior research has shown that such campaigns\ntypically only produce small changes in behavior (if any), there\nis reason to continue utilizing media messages, and more\nimportantly branding, in litter prevention efforts. Based on the\nreported data, and background literature, messages should\nhighlight the dramatic decline in littering rates over the past 40\nyears, the generally infrequent over- all littering rate, and the\nwidespread disapproval for individuals who litter (see also","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:13","document_content":"Cialdini, 2003).\nIn a related data set collected as part of the current study,\nsurveys were con- ducted with observed individuals randomly\nsampled across the country. These surveys were conducted with\nboth litterers and nonlitters, and the findings show a near\nunanimous disapproval for littering (Bator et al., 2011). This\nfinding, coupled with other research on the role of injunctive and\npersonal norms, suggests that messages should emphasize that\nonly a few deviant individuals litter and that these individuals are\ndisapproved of by the majority (see Cialdini, 2003; Grasmick,\n28\nBursik, & Kinsey, 1991; Schultz, Tabanico, & Rend\u00f3n, 2008).\nIn closing, the data reported in this article represent the largest\nsingle study of littering behavior conducted to date. Data are\nreported from unobtrusive observations of nearly 10,000\nrandomly selected individuals across 130 diverse public locations\nacross the country. The results show that of all the disposals that\ntook place in these locations, 17% resulted in litter. For disposals\nof cigarette butts, the littering rate was even higher, at on\nobserved rate of 65%. Statistical analyses are reported that utilize\nthe multilevel framework and simultaneously examine both the\ncontextual and personal predictors of littering behavior. The\nfindingsshow that littering resultsfrom both personal and\ncontextual factors and that both are critical in understanding\nlittering behavior. This perspective is consistent with the\ntraditional approach utilized by environmental psychologists and\ncan be particularly instructive in efforts to reduce littering rates.\n29\nAuthor's Note\nSupplemental Appendix of this article is available on the\nEnvironment and Behavior's\nWeb site: Sage Publishing (<http:\/\/eab.sagepub.com\/>.)\nAcknowledgment\nThe authors want to acknowledge the excellent work and\ncommitment of their field research team: Jenna Albert, Sara\nAguilar, Michelle Cugini, Tracy Galea, Elizabeth Morales,\nBelinda Rojas, and Michael Stringham. They also thank their\ncollaborating teams in New York and Vermont: Montgomery\nBopp, Kara Carpenter, Ashley Doyle, Cassie Fortney, Jamie\nKuhn, Nicole LeFevre, Andrea Martino, Eva Richardson, and\nAshlee Rock. Finally, they want to thank the collaborating\nteam in New Mexico: Angela Bryan, Maddia Ikeda, Jenna\nKicklighter, Stefan Klimaj, Eva Padilla, Jenna Tonelli, and\nKiani Wong. The authors want to express their appreciation for\nthe sup- port and encouragement of Susanne Woods and the\nstaff at Keep America Beautiful.\nDeclaration of Conflicting Interests\nThe authors declared no potential conflicts of interest with\nrespect to the research, authorship, and\/or publication of this\narticle.\nFunding\nThe research reported in this article was conducted with\nfunding from Keep America Beautiful, using financial support\nfrom Philip Morris, An Altria Company.\n30\nReferences\nBator, R., Bryan, A., & Schultz, P. W. (2011). Who gives a\nhoot? Intercept surveys of litterers and disposers.\nEnvironment and Behavior, 43, 295-315.\nBeck R. W. (2007). Literature review---Litter: A review of litter\nstudies, attitudes surveys, and other litter related literature.\nRetrieved from Keep American Beautiful\n(<http:\/\/www.kab.org\/site\/>\nDocServer\/Litter_Literature_Review.pdf?docID=481)\nBrown, B., Perkins, D., & Brown, G. (2004). Crime, new\nhousing, and housing incivilities in a first-ring suburb:\nMultilevel relationships across time. Housing Policy Debate,\n15, 301-345.\nBurgess, R. L., Clark, R. N., & Hendee, J. C. (1971). An\nexperimental analysis of anti- littering procedures. Journal\nof Applied Behavior Analysis, 4, 71-74.\nCasey, L., & Lloyd, M. (1977). The cost effectiveness of litter\nremoval proceduresin an amusement park. Environment and\nBehavior, 9, 535-546.\nCialdini, R. B. (2003). Crafting normative messages to project","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:14","document_content":"the environment.Cur- rent Directions in Psychological\nScience, 12, 105-109.\nCialdini, R. B., Kallgren, C. A., & Reno, R. R. (1991). A focus\ntheory of normative conduct: A theoretical refinement and\nreevaluation of the role of norms in human behavior.\nAdvances in Experimental Social Psychology, 21, 201-234.\nCialdini, R. B., Reno, R. R., & Kallgren, C. A. (1990). A focus\ntheory of normative conduct: Recycling the concept of\nnorms to reduce littering in public places. Jour- nal of\nPersonality and Social Psychology, 58, 1015-1026.\nCone, J. D., & Hayes, S. C. (1980). Environmental problems:\nBehavioral solutions.\nMonterey, CA: Brooks\/Cole.\nDe Kort, Y., McCalley, L., & Midden, C. (2008). Persuasive\n31\ntrash cans:Activation of littering norms by design.\nEnvironment and Behavior, 40, 870-891.\nDurdan, C. A., Reeder, G. D., & Hecht, P. R. (1985). Litter in a\nuniversity cafeteria: Demographic data and the use of\nprompts as an intervention strategy. Environment and\nBehavior, 16, 387-404.\nFinnie, W. C. (1973). Field experiments in litter control.\nEnvironment and Behavior, 5, 123-144.\nGeller, E. S. (1980). Applications of behavioral analysis for\nlitter control. In D. Glen- wick & L. Jason (Eds.),\nBehavioral community psychology: Progress and prospects\n(pp.\u00a0254-283). New York, NY: Praeger.\nGeller, E. S., Brasted, W., & Mann, M. (1980). Waste receptacle\ndesigns and interventions for litter control. Journal of\nEnvironmental Systems, 9, 145-160.\nGeller, E. S., Winett, R. A., & Everett, P. B. (1982). Preserving\nthe environment: New strategies for behavior change.\nElmsford, NY: Pergamon.\nGeller, E. S., Witmer, J. F., & Tuso, M. E. (1977).\nEnvironmental interventions for litter control. Journal of\nApplied Psychology, 62, 344-351.\nGrasmick, H., Bursik, R., & Kinsey, K. (1991). Shame and\nembarrassment as deter- rents to noncompliance with the\nlaw: The case of an antilittering campaign.Environment and\nBehavior, 23, 233-251.\nHeberlein, T. (1971). Moral norms, threatened sanctions,\nand littering behavior\n(Unpublished doctoral dissertation). University of Wisconsin,\nMadison.\nHox, J. (2002). Multilevel analysis: Techniques and applications.\nMahwah, NJ: Erlbaum.\nHuffman, K., Grossnickle, W., Cope, J., & Huffman, K.\n(1995). Litter reduction: A review and integration of the\nliterature. Environment and Behavior, 27, 153-183.\n32\nKeep America Beautiful. (2007). KAB's seven primary sources\nof litter. Retrieved from\n<http:\/\/www.kab.org\/site\/PageServer?pagename=litter_seven>\nsources\nKeizer, K., Lindenberg, S., & Steg, L. (2008). The spreading of\ndisorder. Science, 322, 1681-1685.\nKrauss, R. M., Freedman, J. L., & Whitcup, M. (1978). Field\nand laboratory studies of littering. Journal of Experimental\nSocial Psychology, 14, 109-122.\nLiu, J., & Sibley, C. (2004). Attitudes and behavior in social\nspace: Public good inter- ventions based on shared\nrepresentations and environmental influences. Journal of\nEnvironmental Psychology, 24, 373-384.\nMcKenzie-Mohr, D. (2002). The next revolution: Sustainability.\nIn P. Schmuck & P.\nW. Schultz (Eds.), Psychology of sustainable development\n(pp.\u00a019-36). Norwell, MA: Kluwer.\nMeeker, F. L. (1997). A comparison of table-littering behavior\nin two settings: A case for a contextual research strategy.\nJournal of Environmental Psychology, 17, 59-68. MSW\nConsultants. (2009). National visible litter study. New\nMarket, MD: Author. Retrieved from Keep American\nBeautiful (www.kab.org\/research09)\nNational Association of Home Builders. (2009). House price\nestimator. Available from National Association of Home","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:15","document_content":"Builders (www.nahb.org)\n33\nNational Cooperative Highway Research Program. (2009).\nReducing litter on road- sides. Washington, DC:\nTransportation Research Board of the National Academies.\nRetrieved from National Cooperative Highway Research\nProgram\n(<http:\/\/onlinepubs.trb.org\/onlinepubs\/nchrp\/nchrp_syn_394.p>\ndf)\nNolan, J., Schultz, P. W., & Knowles, E. (2009). Using public\nservice announcements to change behavior: No more money\nand oil down the drain. Journal of Applied Social\nPsychology, 39, 1035-1056.\nOceanConservancy.(2007).Start asea change.Washington\nDC:Author.Retrieved from Ocean Conservancy\n(<http:\/\/www.oceanconservancy.org\/site\/DocServer\/ICC_AR>\n07.pdf?docID=3741) Pandey, J. (1990). The environment,\nculture, and behavior. In R. Brislin (Ed.), Applied\ncross-cultural psychology (pp.\u00a0254-277). Thousand Oaks,\nCA: SAGE.\nPublic Opinion Surveys, Inc.\u00a0(1968). Who litters and why.\nPrinceton, NJ: Keep Amer- ica Beautiful, Inc.\nRaudenbush, S., & Bryk, A. (2002). Hierarchical linear\nmodels: Applications and data analysis methods. (2nd ed.).\nThousand Oaks, CA: SAGE.\nRoales-Nieto, J. G. (1988). A behavioral community programme\nfor litter control.\nJournal of Community Psychology, 16, 107-118.\nSchultz, P.W., Tabanico, J., & Rend\u00f3n, T. (2008). Normative\nbeliefs as agents of influ- ence: Basic processes and realworld applications. In R. Prislin & W.Crano (Eds.), Attitudes\nand attitude change (pp.\u00a0385-409). New York, NY:\nPsychology Press.\nSibley, C., & Liu, J. (2003). Differentiating between active and\npassive littering: A two-stage process model of littering\n34\nbehavior in public spaces. Environment and Behavior, 35,\n415-433.\nSkogan, W. (1990). Decline and disorder: Crime and the spiral\nof decay inAmerican neighborhoods. New York, NY: Free\nPress.\nTorgler, B., Garc\u00eda-Vali\u00f1as, M., & Macintyre, A. (2008).\nJustifiability of littering:An empirical investigation\n(Working Paper No.\u00a02008-8). Basil, Switzerland: Center for\nResearch in Economics, Management, and the Arts.\nRetrieved from http:\/\/ Center for Research in Economics,\nManagement and the Arts (www.cremaresearch.ch\/papers\/2008-08.pdf)\nWilliams, E., Curnow, R., & Streker, P. (1997). Understanding\nlittering behaviour in Australia: A report for the Industry\nEnvironment Council. Retrieved from http:\/\/ Australian\nFood & Grocery Council\n(www.afgc.org.au\/cmsDocuments\/LBS%20I.pdf)\n35\nBios\nP. Wesley Schultz is professor of psychology at California\nState University, San Marcos. He earned his bachelor's degree\nfrom the University of California, Irvine and his doctoral degree\nfrom the Claremont Graduate University. His research interests\nare in applied social psychology, particularly in the area of\nsustainable behavior. His cur- rent work focuses on social\nnorms and the importance of social norms in promoting\nconservation. He has worked on projects for a variety of\norganizations, including the\nU.S. Environmental Protection Agency, National Institute of\nGeneral Medical Science, National Institute of Justice, and the\nCalifornia Integrated Waste Management Board.\nRen\u00e9e J. Bator is professor and cochairperson in the\npsychology department at the State University of New York,\nPlattsburgh. She completed her bachelor's degree in\npsychology at the University of California at Santa Cruz. She\nearned her MA and PhD from the Social Psychology Program\nat Arizona State University. Her research inter- ests focus on\nthe application of persuasion theory to prosocial outcomes,\nespecially those with environmental or health benefits.\nLori Brown Large is project director at Action Research. She\nearned her BA and MA degrees in sociology from California","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"vengeance\/p8418n91jpdf.txt:16","document_content":"State University, Fullerton. She has extensive experience in the\narea of applied social science with an emphasis in survey\nresearch design and implementation. Her particular interests are\nin the area of waste reduction, energy conservation, and\npollution prevention. At Action Research she works with a\nvariety of organizations to develop, implement, and evaluate\noutreach campaigns aimed at changing behavior.\n36\nCoral M. Bruni is a doctoral student at the Claremont\nGraduate University. She completed her bachelor's and\nmaster's degrees in psychology at California State University,\nSan Marcos. Her research interests include connectedness with\nnature, self\/identity, and implicit social cognition. Her recent\nstudies have focused on the role of implicit connectedness with\nnature across a variety of ages and places.\nJennifer J. Tabanico is principal at Action Research. She\nearned her BA degree in psychology and MA degree in\nexperimental psychology both from California State\nUniversity, San Marcos. Her research interests are in applied\nsocial psychology with particular emphasis on the applications\nof psychological theory to the development of public policy\nand behavior change programs. In both academic and\nprofessional appointments, she has completed numerous\nstudies of environmental attitudes, haz- ardous waste\nmanagement, energy conservation, and pollution prevention.\nAt Action Research, she works with a variety of organizations\nto develop, implement, and evaluate outreach campaigns aimed\nat changing behavior.","parent_id":"vengeance\/p8418n91jpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"verbal_memory\/02687030701803788.txt:0","document_content":"Skip to Main Content\nTaylor and Francis Online homepage\nLog in \\| Register\nCart\nHome All Journals Aphasiology List of Issues Volume 22, Issue 7-8 Instruction processing in young and olde ....\nEnter keywords, authors, DOI, etc\nSearch in:\nThis Journal\nAdvanced search\nPublication Cover\nAphasiology\nVolume 22, 2008 - Issue 7-8\nSubmit an article Journal homepage\n311\nViews\n10\nCrossRef citations to date\n0\nAltmetric\nPapers\nInstruction processing in young and older adults: Contributions of memory span\nEsther S. Kim PhD,Kathryn A. Bayles &P\u00e9lagie M. Beeson\nPages 753-762 \\| Received 19 Jul 2007, Accepted 12 Nov 2007, Published online: 18 Jun 2008\nCite this article <https:\/\/doi.org\/10.1080\/02687030701803788>\nFull Article Figures & data References Citations Metrics Reprints & Permissions Read this article\nAbstract\nBackground: Age\u2010related changes in cognition and in particular, working memory, can impact older adults\\' abilities to comprehend linguistic information. Many investigators have undertaken the study of age effects on language comprehension, but confounding variables, such as vocabulary level, general knowledge, and episodic memory ability limit what can be inferred about linguistic processing in ageing.\nAims: The purpose of this study was to investigate young and older adults\\' performance on a language\u2010processing task that assessed ability to follow instructions. Despite having ecological validity, little attention has been paid to age effects on the processing of procedural information. The use of the instruction task allowed for an investigation of age effects on language comprehension while mitigating the effects of thematic knowledge, vocabulary and episodic memory.\nMethods & Procedures: A total of 37 older adults (M = 72.1 years) and 41 young adults (M = 22.5 years) received three measures of verbal memory: digit span, word span, and listening span. In addition, they were administered an experimental instruction task requiring participants to sort coloured pills into pill containers in response to spoken instructions. Information load of the instructions was manipulated by varying the number of actions per instruction and the number of components to be remembered per action. For example, the instruction \"Take three pills on Monday and two on Tuesday\" has two actions, and each action has two components to remember (number of pills and day). The dependent variable was participants\\' performance accuracy in following the instructions.","parent_id":"verbal_memory\/02687030701803788.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"verbal_memory\/02687030701803788.txt:1","document_content":"Outcomes & Results: Significant age effects were observed on the experimental instruction task, as well as on word and listening span measures. As the information load of the instructions increased, accuracy decreased for both groups, although this effect was greater for the older adults. When comparing instructions that had the same number of total components to be remembered, but differed in how these components were structured, participants performed more accurately when the instruction contained fewer actions, even if each action had more components to remember. Digit span was a significant predictor of performance on the instruction task, together with age accounting for more than half of the variance.\nConclusions: The results of this study demonstrate the expected age effects on working memory span capacity, and illustrate the effect of span capacity on following verbal instructions. From a practical perspective, these findings suggest that when a procedural instruction loaded with content is presented to an older adult, processing will be enhanced when it requires fewer actions.\nKeywords: AgeingMemory spanWorking memoryInstructions.\nPrevious article\nView issue table of contents\nNext article\nThis project was supported in part by National Multipurpose Research and Training Center Grant DC\u201001409 from the National Institute on Deafness and other Communication Disorders, and a Fellowship from the Cognitive Science Program at the University of Arizona.\nNotes\n1.  Values are reported using the Greenhouse\u2010Geisser correction for the variable \"actions\" as the homogeneity of variance assumption was violated.\nShare iconShare","parent_id":"verbal_memory\/02687030701803788.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:0","document_content":"Skip to Main Content\nOxford Academic\nJournals\nBooks\nInformation\nAccount\nNutrition Reviews International Life Sciences Institute\nIssuesMore Content Submit PurchaseAlertsAbout\nNavbar Search Filter\nNutrition Reviews\nEnter search term\nSearchAdvanced Search\nIssue Cover\nVolume 79Issue 6\nJune 2021\nArticle Contents\nAbstract\nINTRODUCTION\nCONCLUSION\nAcknowledgments\nReferences\nNext \\>\npdfPDF Split View Cite\nPermissions Icon Permissions\nShare Icon Share\nNavbar Search Filter\nNutrition Reviews\nEnter search term\nSearch\nJOURNAL ARTICLE\nNutritional status and eating habits of people who use drugs and\/or are undergoing treatment for recovery: a narrative review\nNadine Mahboub, Rana Rizk, Mirey Karavetian, Nanne de Vries\nNutrition Reviews, Volume 79, Issue 6, June 2021, Pages 627--635, <https:\/\/doi.org\/10.1093\/nutrit\/nuaa095>\nPublished: 25 September 2020\npdfPDF\nSplit View\nCite\nPermissions Icon Permissions\nShare Icon Share\nAbstract\nA comprehensive overview is presented of the nutritional issues faced by people who use drugs or are undergoing treatment for recovery. Chronic substance use affects a person's nutritional status and body composition through decreased intake, nutrient absorption, and dysregulation of hormones that alter the mechanisms of satiety and food intake. Anthropometrics alone is not the best indicator of nutritional status, because this population has hidden deficiencies and disturbed metabolic parameters. Socioeconomic factors (eg, higher education, higher income, presence of a partner, living at home) positively affect nutritional status. Scarce available data on users undergoing treatment indicate improvement in anthropometric and metabolic parameters but with micronutrient intake remaining suboptimal. Weight gain is noted especially among women who use drugs and potentially increases their risk of relapse. Finally, specific amino acids and omega-3 fatty acids are promising in decreasing relapse and improving mental health during treatment; however, additional high-quality studies are needed. Nutrition intervention for people who use drugs or are undergoing treatment for recovery is underused; comprehensive programs addressing this population's unique needs are necessary. Future research will identify which components are needed.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:1","document_content":"drug users, health promotion, nutritional status, substance abuse treatment centers, substance-related disorders\nTopic: dietbody compositionhabitsmicronutrientsweight gaineatingscience of nutritionnutritional statusdrug usagesubstance use disordersnarrative review\nIssue Section: Lead Article\nINTRODUCTION\nNearly 5% of the world population is currently estimated to use drugs once daily, and almost 0.6% suffer from severe drug use disorder.1 To date, opioids are the most harmful type of used drugs, and cannabis remains the world's most widely used drug.1\nThere are various types of treatments for drug addiction, including detoxification (complete abstinence) or opioid substitution treatment (OST).2 Drug detoxification mostly takes place initially in hospitals, followed by psychotherapy and behavioral modification in a therapeutic community or a rehabilitation center.3 By contrast, OST is a medication-assisted program during which the patient receives a long-term opioid agonist (methadone or buprenorphine) to reduce the withdrawal symptoms and decrease the cravings for street opioids.4 OST is suggested to be the more efficient method for reducing blood-borne illnesses like infection with the human immunodeficiency virus (HIV) and hepatitis.5\nDrug use poses a cluster of harmful consequences to a person's well-being on psychological, emotional, and social levels.6 It leads to increased risk of infectious illnesses7 and medical issues, including mental disorders, cancer, stroke, and liver, lung, and cardiovascular diseases.8\nAdditionally, substance use can compromise the user's nutrition2 and greatly affects their dietary habits. In general, this population has a disrupted and chaotic lifestyle, and money is usually spent on drugs rather than on food. This severely affects the user's food intake, which eventually leads to undernutrition.9 Other factors affecting the nutritional status of drug users include the type, frequency, and duration of the drug used and the presence of infectious diseases.10 Furthermore, the type of treatment drug users might be receiving, such as being enrolled in a detoxification program and living in a rehabilitation center vs receiving OST and living in the community, might also influence their nutritional status.11","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:2","document_content":"In this article, the literature on the nutritional issues faced by people who use drugs (PWUD) or those undergoing treatment for recovery is reviewed, as is the effect of drug use on dietary intake and dietary habits. The effect of drugs on anthropometric indices, body composition, nutrient deficiencies, and metabolic parameters are exposed, and the effect of nutrition on substance use and the changes that occur during treatment and recovery are discussed. The term malnutrition describes a state of imbalance---excess or deficiency---that leads to alteration in body composition and negatively affects the health status of the individual. In this article, the term malnutrition is used synonymously with undernutrition.\nWe chose to conduct a narrative review because there are many different topics in this field with few studies on each and statistical combination is impossible. These data will be compiled to have a comprehensive overview and provide new insights on drug users' eating patterns for future nutritional interventions in the promotion of good health among this population.\nVarious databases were searched for relevant literature (namely, PubMed, Google Scholar, Science Direct, and Medline), using the following terms: \"nutrition\" OR \"nutritional status\" OR \"malnutrition\" OR \"dietary habits\" AND \"illicit drug use\" OR \"substance abuse\" OR \"drug use\\*\" OR \"drug treatment.\" The keywords were modified according to the searched database. In addition, references of included articles were reviewed for inclusion when we thought they were relevant. Searches were restricted to English-language journals and a date range of 1990 until the present. A total of 83 studies initially were included in the review. Eight additional studies were suggested by key scholars; accordingly, the total number of studies included was 91.\nEffect of drug use on dietary habits: food preferences, eating behaviors, and appetite regulation\nLittle research has been done to tackle the issues of food preferences and dietary habits of active drug users or those undergoing different treatment modalities. Cocaine drug users have irregular eating patterns and rely mainly on 1 meal taken late at night. Typically, this meal is high in refined carbohydrates and fat and low in fruits and vegetables.12--14 People addicted to opiates replace protein and fats with meals high in sugar and alcohol, which are low in essential nutrients and, therefore, are sources of empty calories.9 Substantial evidence supports the increased preferences for sweet taste among PWUD.15--20","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:3","document_content":"During the early phase of detoxification, when patients are still receiving pharmacotherapy, they report a period of low food intake, and eating becomes their last priority as they experience nausea, anorexia, and gastrointestinal disturbances, all of which make eating difficult.12,19 Between the first and sixth month of detoxification, a high preference and craving for table sugar and sweet foods, such as cakes and confectionary foods, often takes place as a replacement for the drug. However, in the later recovery phase, after 6 months, sugar cravings seem to level off with more structural food intake and improved appetite.17,19,21\nStudies of persons receiving OST also show higher preference and intake of sugary foods15,22--24 (eg, high consumption of tablesugar, yogurt, and soft drinks), with very little intake of fruits and vegetables.25,26 Sugary foods appear to be the preferred foods for PWUD or those undergoing treatment. This preference may be an indication of addictive tendencies, because some studies show that heroin users have these cravings prior to using heroin more than after using it.27\nThe poor dietary habits decreasing food intake, the preference for sugary foods contributing to empty calories, the compromised liver storage and\/or increased excretion of nutrients with accompanying diseases like HIV and hepatitis are major risk factors for malnutrition and hazardous health among PWUD.28\nNutrition knowledge seems to affect dietary choices in this population. For instance, when nutrition knowledge was offered as part of an OST program, sugary food craving was still observed but healthier foods and more meals were consumed by the participants.18","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:4","document_content":"Effect of drug use on dietary intake: macro- and micronutrients\nIn the short term, opiates cause anorexia, decreased food consumption, and reduced gastrointestinal motility, all leading to malnutrition and increased risk of infections in the long term.29 Socioeconomic factors like education and income are positively associated with nutritional indices like body mass index (BMI), hemoglobin level, and serum protein levels among PWUD. This association is in agreement with the well-documented fact that socioeconomic factors are related to the nutritional status of the individual, in addition to the high prevalence of self-reported homelessness among PWUD.20,30 Similarly, people who use heroin and cocaine have lower energy and protein intake than nonusers.16,31 This intake seems to decline more with higher intensity and duration of drug use.10 The presence of disease also appears to affect food intake. HIV-positive PWUD have more energy, protein, and fat-deficient diets compared with PWUD who are HIV negative.28 The high levels of food insecurity among this population are mainly due to the limited funds, which are usually allocated to the support of their habits rather than food; this leads to serious decrease in intake levels.\nConsistent with the lower intakes of nutrient-dense foods in this population, the intake of the majority of vitamins and minerals, like thiamin, riboflavin, pyridoxine, folate, vitamin\u2009D, vitamin\u2009C, magnesium, iron, calcium, zinc, copper, and selenium is below the recommended intake.32 The nutritional imbalance (a higher ratio of macronutrients to micronutrients) indicating higher intakes of empty calories is strongly associated with drug use.33\nEffect of drug use on plasma nutrient deficiencies\nThe malnutrition of PWUD, assessed by anthropometric measurements, is not usually very severe; thus, measuring the plasma levels of macronutrients and micronutrients might reveal hidden deficiencies that reflect the decrease in the intake of these nutrients.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:5","document_content":"Essential nutrients are depleted among PWUD in general.15 This population exhibits low selenium and potassium levels due to lower muscle mass attributed to malnutrition.34 Iron deficiency and iron-deficiency anemia are widespread, mostly among female PWUD,35--37 as are low plasma levels of vitamins\u2009A, C, D, and E. The latter is inversely correlated with the dose and period of addiction.16,30,35 These deficiencies are mainly caused by restricted access to foods, in addition to the food choices previously discussed.16,30,35 Thus, the issue of vitamin and mineral supplementation among PWUD and during treatment requires additional consideration.\nOn the other hand, the plasma levels of some minerals are reported to be higher in this group compared with healthy individuals. This is not due to proper nutrition but rather is attributed to factors unique to PWUD. Higher serum levels of phosphorus, sodium, and magnesium are tentatively attributed to partial dehydration.15 Similarly, increased serum levels of copper and zinc are due to inflammation, acute fasting, and smoking.15,34,36\nEffect of drug use on anthropometric indices and body composition\nAlthough scarce, the majority of the literature assessing the nutritional status of PWUD mostly points toward malnutrition.11 The relation among drug use, body weight, and BMI has been addressed in many epidemiological studies, and most of the evidence shows an inverse correlation among these variables.28,38 On admission for detoxification, up to 70% of PWUD have BMI values below the normal range or weight values below the population mean.10 Similarly, Ross et al35 showed that 24% of PWUD, within a short period of admission for detoxification, exhibited mild to moderate malnutrition, based on the Subjective Global Assessment.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:6","document_content":"In general, the BMI of PWUD is lower than that of nonusers. HIV-positive persons who use cocaine have the lowest BMI, as compared with users of other drugs or with nonusers.39 It is believed that cocaine suppresses appetite and decreases food intake, and subsequently body weight, by inhibiting dopamine transporters, decreasing reuptake of serotonin, upregulating the glucocorticoid production, and increasing the cocaine- and amphetamine-regulated transcript expression.40,41 Cowan et al21 supported this finding when reporting that weight was gained with the cessation of cocaine use. Ersche et al13 challenged the assumption that cocaine leads to weight loss through appetite suppression; rather, they suggested that metabolic alteration is the cause. Their findings showed that cocaine users had lower body weight and fat mass as compared with nonusers, despite reporting higher dietary fat and carbohydrate intake.\nPeople who smoke heroin appear to have a lower BMI and body weight than nonusers. This inverse correlation is modulated by the high frequency (\\>3 times\/d) and the route of administration of the drug.38 The significant negative contribution of smoked heroin to body weight and BMI may be due to faster rate of brain delivery of the drug as compared with injection, snorting, or oral ingestion, leading to greater reinforcing effects. Substances like heroin may compete with food in the brain activating reward pathways and increasing dopamine receptor' availability, thus suppressing the appetite and leading to lower body weight. This is particularly noted among heroin smokers.38,42--45\nMcIlwraith et al46 showed that heroin users are more prone to being underweight as compared with morphine and amphetamine users, whereas people who use amphetamines were at higher risk of being obese as compared with morphine users. This finding is contradictory to the appetite-suppressing effect of amphetamine, and its relevance to the general population will need to be investigated by future studies, because this increase in obesity was found only in comparison with morphine users and not with a nondrug-using control group.46,47","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:7","document_content":"Methylamphetamine (MA), a relatively new psychostimulant (the second most widely used drug now after heroin, marijuana, and others) is associated with cardiac and hepatic pathology, neurological impairment, mood disorders, and malnutrition.48 People dependent on MA have a lower BMI as compared with that of healthy individuals. This might be due to cognitive deficits, abnormal metabolic activity, duration of MA use, and improper oral health that affects food chewing and, thus, intake.48,49 More frequent use of other types of drugs such as marijuana or sedatives showed a weak association with a lower BMI, although this association is statistically not significant.39,50\nIn addition, sex might influence the BMI, weight, and body composition of PWUD. Women who are heavy drug users (ie, using methadone or injection of drugs \\>16 times\/wk) have less body fat and lower BMI as compared with PWUD moderately or infrequently, and nonusers. This difference among different levels of drug use is not present in men.51 This study by \\\"Cofrancesco et al.51\\\" confirms the results of studies that showed a negative relation between drug use and BMI solely among women and not men.10,52,53\nFurthermore, factors like decreased frequency of food consumption are negatively associated with body weight and BMI. Also, poverty resulting from unemployment, common among PWUD, leads to an inability to purchase nutritious foods and is associated with a low BMI. In addition, multiple drug use can lead to poorer nutritional status due to the appetite-suppressing effect of the drug.20,28,30\nInterestingly, Richardson et al54 showed that BMI alone may not be the best indicator to assess PWUD because there was no association between BMI and the nutritional risk level of PWUD when screened. Using other tools to assess appetite, diet quality, and biochemical parameters better identified nutritional deficiencies to be addressed.35","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:8","document_content":"Throughout treatment processes, whether by OST or detoxification, PWUD start to consume healthier foods and more structured meals.19,21,26 Better dietary habits are seen among those in residential homes where meals are provided, or later in recovery when food preparation becomes a more sociable and satisfying activity as compared with PWUD who have severe addiction and for whom eating is given little consideration.19Table\u20091 summarizes the factors contributing to changes in anthropometric indices and body composition among PWUD.\nTable 1Factors contributing to lower body weight, BMI, and body composition among drug users\nFactor Finding\nSex Underweight is more frequent among women than men.\nType of drug\nHeroin: highest percentage of drug users in underweight category\nCocaine: decrease in weight specific to fat mass with no significant changes in BMI\nAmphetamines: higher risk of obesity in users as compared with morphine users\nMethylamphetamines: lower BMI as compared with nonusers\nFrequency and route of administration\nMultiple drug use for a long duration is negatively associated with the nutritional status.\nSmoking has faster delivery of the drug to the brain, resulting in a lower BMI as compared with snorting or injection.\nFood insecurity and poverty Negative effect on the nutritional status by decreasing body weight, body fat, and BMI\nPathological diseases Add to the severity of malnutrition among drug users\nTreatment Healthier dietary habits seen in detoxification and OST\nAbbreviations: BMI, body mass index; OST, opioid substitution treatment.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:9","document_content":"Open in new tab\nEffect of drug use on plasma metabolic parameters\nThe effect of drug use on plasma parameters has also been studied with emphasis on lipid profile, glucose and hemoglobin levels, and hematocrit. In general, plasma total cholesterol has an inverse relation with drug use. Persons addicted to opium, heroin, and MA have a significant decrease in serum cholesterol level as compared with nonusers but with no change in triglyceride levels.49,55--58 By contrast, comparing HIV-positive and HIV-negative injecting drug users with a control group, total cholesterol levels were lower and triglyceride levels were significantly higher in the HIV-positive drug users, indicating the possible effect of the disease itself and not the drug use.28 These findings were supported by Maccari et al,59 who found that heroin users had significantly lower serum cholesterol and high-density lipoprotein levels, and higher triglyceride levels than nonusers. The aforementioned decrease in serum lipid levels could be mainly attributed to malnutrition and weight loss, specifically the loss of abdominal fat, in addition to the presence of liver diseases or HIV that are common among heroin users.\nDecreased plasma cholesterol levels have been associated with many negative psychological behaviors, including aggression, depression, and suicide60; however, this remains controversial. Low plasma cholesterol levels can alter tissue concentration of polyunsaturated fatty acids, the depletion of which has important consequences on modulating the serotonergic and dopaminergic functions that play key roles in the aforementioned behaviors. Yet, to date, a causal relationship has not been shown.58,61--63 Persons addicted to cocaine who relapsed after detoxification had lower plasma cholesterol values (\\<160\u2009mg\/dL) than those who did not, suggesting an increased vulnerability to the development of behavioral and psychological disorders with low cholesterol levels.55 Whether these diminished levels are associated with drug craving still needs to be investigated.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:10","document_content":"Glucose is another parameter that was studied in PWUD and remains not well understood. In a study by Zhang et al,48 the fasting blood glucose levels of persons addicted to MA were lower than those of control participants. This finding runs in parallel with studies done on animals that reported a direct effect of MA on the pancreas, leading to insulin secretion and induced hypoglycemia.64 On the other hand, non-insulin dependent persons with diabetes who used opium had higher glycosylated hemoglobin values than did nonusers, thereby indicating elevated blood glucose levels in the former for the previous 3 months.65 The effect of morphine on glucose has been demonstrated in animals, with several mechanisms suggested, like an increase in hormone levels including adrenalin, noradrenalin, corticosterone, and glucagon; these, in turn, increase blood glucose levels.66,67 Among the very few studies on humans, Carey et al68 showed that morphine can induce a reduction in the plasma counterregulatory epinephrine response, thus causing hypoglycemia symptoms in healthy individuals without diabetes. More studies are needed to confirm if behavioral factors play a role in the effect of drugs on plasma glucose levels.\nHemoglobin and hematocrit levels are lower in PWUD than in nonusers, with the lowest levels seen among multiple-drug users and those with longer duration of addiction.30 This finding was related to malnutrition and decreased micronutrient intakes, especially iron.69 The decrease in hemoglobin levels and hematocrit among PWUD is specifically noted among women. This might be because men are institutionalized for a longer period than women and that, in turn, correlates with better nutritional status.32,35","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:11","document_content":"Nutritional changes during recovery (detoxification or OST)\nIn addition to being an effective method for reducing harm, OST or methadone maintenance treatment (MMT) also improves the nutritional status of PWUD, whereby the BMI and weight of users starting treatment significantly increase.70,71 The increased weight and BMI are mostly seen in patients with higher education and income, suggesting a positive role of social factors on the nutritional status of PWUD.20,30,70,72 From the patients' point of view, MMT has a positive impact on their physical health, sleep, and weight gain.73 They report better appetite, change in taste, and more desire to eat.\nPWUD starting MMT show a decreased intake in the majority of the nutrients (ie, fats, cholesterol, fibers, and some minerals and vitamins) 2 months after beginning treatment, followed by an increase after 9 months.74 Sex might modulate the effect of MMT on weight gain. W hereas studies show an increase in dietary intake, body weight, BMI, and skin fat folds among men, as compared with a modest weight loss in women,74 other studies show the opposite, with women having a much greater increase in BMI and weight than men.75 The reason underlying this significant difference between sexes does not seem to be related to the duration of the treatment and needs additional investigation. The increase in weight and BMI may not be due to the shift toward a healthier eating pattern but might be related to the pharmacological aspect of the treatment itself.23,75,76 Detoxification also results in increased weight and food intake,77--79 which vary at different recovery stages. In the early stages, binge eating is observed as a result of the replacement of drugs with food. Binging may be related to changes in the eating behaviors of PWUD after periods of food restriction caused by drugs. In later stages of their recovery, PWUD developed more structured and less frequent overeating habits.21","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:12","document_content":"The studies regarding the effect of MMT on some metabolic parameters are limited. After 6 months of MMT, persons addicted to opioids show an increase in serum levels of leptin, total cholesterol, high-density lipoprotein , and low-density lipoprotein, compared with serum levels before initiation of the treatment.70,80 A positive correlation has been shown between leptin, BMI, and serum lipid levels, with greater effect among women; this is attributed to the difference in percent body fat mass.\nAs for micro- and macronutrient intake during MMT or detoxification, an increase in the overall intake of energy, proteins, and carbohydrates occurs with both modalities after initiation of the treatment. Yet, this is followed by a decrease in later stages of recovery, when the food intake starts to become more structured. Interestingly, intake of the majority of the minerals remains below the recommended levels, especially in patients with HIV; this could be related to the increased intake of energy-dense foods rather than nutrient-dense ones.24,81\nPersonal and environmental factors like decreased physical activity and the purchase of high-fat, less-expensive foods play a role in the weight gain seen among patients in recovery from drug use, thereby highlighting the need to incorporate exercise and nutrition information as part of the treatment.82 Exercise reduces stress, anxiety, depression, and drug use in individuals recovering from substance use.83\nBetter nutrition knowledge and healthier eating habits are seen among PWUD in MMT after receiving nutrition lectures as part of the treatment program, although no effect on BMI and weight gain is seen. This could be because the intervention program emphasized the healthier eating habits and did not specifically target weight reduction.84","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:13","document_content":"Concerns about weight gain among women drug users in recovery is a potential risk factor for relapse. In a study of 297 women of different ethnicities who were recruited from 7 different treatment facilities, Warren et al79 reported that 70% were concerned about weight gain during recovery, and 45% were concerned about relapse because of this gain. One-third of the sample indicated that weight loss was a reason to initiate drug use to start with. Similarly, drug use was positively associated with overweight among female adolescents.85 Data revealing drug users' perceptions about the kind of intervention programs for tackling the weight gain they face during treatment are scarce. Most of the research suggests similarities between women and men in terms of drug-use behaviors; however, significant differences exist that may indicate a need for more sex-specific research on prevention and treatment strategies.85 On the basis of these findings, giving individualized behavioral recommendations must be considered, because all intervention research shows its efficiency. Table\u20092 summarizes the effect of drug use and treatment on different aspects of the nutritional status of PWUD.\nTable 2Effect of drug use and treatment methods on the nutritional status\nDrug use OST Detoxification\nFood preferences Consumption of 1 meal\/d with higher preference for sugars and fats and lower intakes of fruits and vegetables\nBetter appetite and increased number of meals\nHigh consumption of sugars, yogurt, and soft drinks with low intakes of fruits and vegetables\nBinging on sweets in early phases of treatment with more structured food intakes in later recovery stages\nMacro- and micronutrient intake\nDeficits in energy and protein\nMajority of vitamins and minerals below RI\nHigher energy, proteins, and carbohydrates after initiation of treatments, with a decrease in later stages Higher energy, proteins, and carbohydrates after initiation of treatments, with a decrease in later stages.\nPlasma nutrients\nLow levels of Se, K, Fe, vitamins A, D, C, and E\nHigh levels of Mg, Na, and Ph attributed to dehydration","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:14","document_content":"Majority of micronutrient levels stayed below the recommended levels. Majority of micronutrient levels stayed below the recommended levels.\nAnthropometrics Decrease in BMI and weight with variations based on the type of drug Significant increase in BMI and weight, with more significance in women, placing them in the overweight category. Increase in weight and food intake in early stages of recovery\nMetabolic parameters Low levels of total and HDL-cholesterol, leptin, FBS, Hct, and Hb Increase in total and HDL-cholesterol and leptin levels\nAbbreviations: BMI, body mass index; FBS, fasting blood sugar; Fe, iron; Hb, hemoglobin; Hct, hematocrit; HDL, high-density lipoprotein; K, potassium; Mg, magnesium; Na, sodium; OST, opioid substitution treatment; Ph, phosphorus; RI, recommended intake; Se, selenium.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:15","document_content":"Open in new tab\nEffect of nutrition on substance use\nThe high prevalence of PWUD with mood disorders like depression and anxiety has been confirmed by numerous, large epidemiological studies86--88 and these disorders, in turn, may have a negative impact on users' recovery, which will lead to relapse.15,89 Essential micronutrients play an important role in mood regulation by the brain,33 and deficiencies or insufficient intakes of these nutrients, in addition to food deprivation, correlate with poor mental health, especially depression.90,91 Serotonin plays a role in the modulation of many behaviors, including violence, aggression, mood, sleep, and appetite.92,93 The synthesis of serotonin starts with the amino acid tryptophan. Increasing dietary intake of tryptophan can increase serotonin levels, thus modulating the aforementioned behaviors. Data in the literature concerning the positive effect of tryptophan supplementation on depression are inconsistent; consensus has not yet been reached regarding the effectiveness in the treatment of drug use.93--95 Tyrosine and phenylalanine are also involved in the synthesis of dopamine and catecholamines that influence behavioral performance, with limited and inconsistent evidence that their supplementation is beneficial in the treatment of PWUD.15,95,96 When patients dependent on heroin or opiates are given a combination of amino acids (namely, phenylalanine, tryptophan, tyrosine, and glutamine) while undergoing detoxification, they show a significant reduction in the craving for opiates.97 This might be an important tool in the treatment of drug use that warrants additional study.\nThe provision of micronutrients is required as a cofactor for the synthesis of serotonin, dopamine, and catecholamines.98,99 Deficiencies of copper, selenium, manganese, magnesium, folate, and B-complex vitamins are linked to depression,98,100--102 which might hinder the treatment process of drug users. Vitamin and mineral supplementation should be considered, not only for the management of malnutrition but also as a preventive measure of relapse.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"fasting_workout\/5911317.txt:16","document_content":"Furthermore, fatty acids are also involved in regulating the aforementioned behaviors.103,104 Elevated levels of corticotropin-releasing hormone, which is associated with defensive and violent behaviors, decrease with supplementation of a combination of omega-3 fatty acid docosahexaenoic and eicosapentaenoic acids.105 Patients undergoing detoxification from drug use have a decrease in anger score upon supplementation with docosahexaenoic acid, whereas lower anxiety scores are associated with supplementation with eicosapentaenoic acid.106\nSupplementation could have a positive effect on the psychological behaviors that might prevent relapse. The intake of specific nutrients like amino acids and omega-3 fatty acids are promising in decreasing relapse and improving mental health during treatment, but additional high-quality studies are needed to provide evidence that such supplementation can increase the efficacy of the treatment of PWUD.\nCONCLUSION\nPWUD are a vulnerable population, and most of the research exploring their nutritional status points to malnutrition. Substance use affects the nutritional status and body composition through decreased food intake and nutrient absorption, altered metabolism, and use of multiple drugs, in addition to the dysregulation of hormones altering the mechanism of satiety and food intake. Anthropometric measurements alone are not the best indicators of assessment in this patient population, because active users and those seeking treatment have many hidden deficiencies and disturbed metabolic parameters. Socioeconomic factors like education, income, presence of a partner, and living in a residential home where meals are provided have a positive impact and should be considered.\nScarce available data indicate improvements in the anthropometric and metabolic parameters of PWUD when they initiate treatment, but micronutrient levels remain below recommended intake values. Yet, an increase in weight is noted, which might pose negative health implications.\nAll of these factors draw attention to the importance of proper, comprehensive nutrition care being provided for drug users and in treatment centers. Simple nutrition education about healthy eating habits improves the quality of the nutritional intake of PWUD but does not seem to be solely effective in treating the problems faced by users and those undergoing treatment and improving their outcomes. This indicates the need for an individualized and comprehensive nutritional intervention. The components of this intervention still need to be determined by future studies.","parent_id":"fasting_workout\/5911317.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"gz_sim\/edit.txt:6","document_content":"\\$ gz sim \\--help\nEnvironment variables:\nGZ_SIM_RESOURCE_PATH Colon separated paths used to locate resources such as worlds and models.\nGZ_SIM_SYSTEM_PLUGIN_PATH Colon separated paths used to locate system plugins.\nGZ_SIM_SERVER_CONFIG_PATH Path to server configuration file.\nGZ_GUI_PLUGIN_PATH Colon separated paths used to locate GUI plugins.\nGZ_GUI_RESOURCE_PATH Colon separated paths used to locate GUI resources such as configuration files.\n37\nTutorial:\nDynamic level-of-detail loading\n38\n\\$ gz sim levels.sdf \\--levels\n39\nFor Ubuntu binary installs, more example worlds are in \/usr\/share\/gz\/gz-sim7\/worlds\/\nlevels.sdf\n40\nLevel of detail (LOD) concept:\nFor large worlds, set up SDF to dynamically load models based on distance from robot\nUsed in DARPA SubT\nFollow tutorial (see next slide) gazebosim.org\/api\/sim\/7\/levels.html\nTODO(nice to have) replace with video after running commands on next page\n\\$ gz topic -t \\\"\/model\/vehicle_blue\/cmd_vel\\\" -m gz.msgs.Twist -p \\\"linear: {x: 4.0}\\\"\n\\$ gz topic -t \\\"\/model\/vehicle_red\/cmd_vel\\\" -m gz.msgs.Twist -p \\\"linear: {x: 2.0}\\\"\n41\nlevels.sdf\n42\nDynamic load\/unload in vicinity of moving blue vehicle\nlevels.sdf\n43\nlevels.sdf\n44\nTutorial:\nUsing sensors\n45\nUsing sensors\nTutorial detailed walkthrough: gazebosim.org\/docs\/garden\/sensors\nQuick try: Download code files into a directory called sensors github.com\/gazebosim\/docs\/tree\/master\/garden\/tutorials\/sensors\nFiles you need: CMakeLists.txt lidar_node.cc sensor_launch.gzlaunch sensor_tutorial.sdf\n46\nCompile:\n\\$ cd sensors\n\\$ mkdir build && cd build\n\\$ cmake ..\n\\$ make\n47\nRun:","parent_id":"gz_sim\/edit.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"renewable_energy\/241RaugeiEROIEPrevisedII201203VMFpdf.txt:7","document_content":"modules with performance ratios derived from extensive experimental field data is\narguably the most valid approach to assessing the level of energy performance that\ncan be expected of a PV system today. Conversely, defaulting to measured\n11\nelectricity generation records from existing installations only returns an aggregated\nmeasure of the performance of a long chain of system components, some of which\nare likely to be no longer representative of the current state of technological\nadvancement, and is therefore not a viable alternative if one wishes to faithfully\nportray a technology that is still in such a state of flux.\nWe herein present the results of our new EROI calculations for a range of modern\nPV systems (mono-crystalline Si, multi-crystalline Si, ribbon Si and CdTe thin film),\nbased on the most recent published LCA studies by ourselves and other colleagues\n(Fthenakis et al., 2009; Held and Ilg, 2011; Fthenakis and Kim, 2011).\nData were normalized to assume conservative performance ratios (PR) of 75% for\nrooftop mounted systems and 80% for ground mounted optimal latitude installations,\nwhich also implicitly account for module degradation (Fthenakis et al., 2011). In all\ncases, the complete PV system was addressed, including all balance of system\n(BOS) components, and the analysis was extended to the full life cycle, including\ntake back and recycling, and assuming an industry-standard PV system lifetime (T)\nof 30 years (Fthenakis et al., 2011). We also adopted the average southern\nEuropean ground-level insolation, i.e.\u00a01,700 kWh\/(m2\n\u00b7yr), which incidentally\ncoincides with the mean global insolation (horizontal surface) in between the Arctic\nand Antarctic circles (NASA, 2008). Finally, the EU-27 electric grid efficiency (\u03b7grid =\n0.31) was used, when called for, to convert the electricity generated by PV into its\n'Primary Energy equivalent', in accordance with the common practice for EPBT\ncalculations.\nOur full EROI calculations for PV are illustrated in Table 1.\nFor comparative purposes, we also calculated the EROI of oil- and coal-fired\nthermal electricity. We took the primary energies required for the respective power\nplants (EPP) and the total direct inputs of feedstock energies over their 30-year\nlifetimes (EFeed) from the reputable LCA database Ecoinvent v.2 (Jungbluth, 2007;\n12\nDones et al., 2007; Ecoinvent, 2011); we then back-calculated EED for each as\nEFeed\/EROIF.\nOur full EROI calculations for oil- and coal-fired thermal electricity are illustrated in\nTables 2 and 3.\n13\nTable 1 EROI calculations for PV. LCI data from (Fthenakis et al., 2009; Held and Ilg, 2011; Fthenakis and Kim, 2011)\nRef. Eqn. Mono-c Si (rooftop) Multi-c Si (rooftop) Ribbon Si (rooftop) CdTe (ground)\nInsolation \\[kWh\/(m2\n\u00b7yr)\\] 1,700 1,700 1,700 1,700\nPerformance Ratio 0.75 0.75 0.75 0.8\nModule efficiency 14% (a) 13% 13% 11% (a)\nEOUT,yr \\[kWhel\/(m2\n\u00b7yr)\\] 179 166 166 150\nT \\[yr\\] 30 30 30 30\nEOUT \\[kWhel\/(m2\n)\\] 5,355 4,973 4,973 4,488\nEPP \\[MJPE\/m2","parent_id":"renewable_energy\/241RaugeiEROIEPrevisedII201203VMFpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"renewable_energy\/241RaugeiEROIEPrevisedII201203VMFpdf.txt:8","document_content":"\\] 3,257 3,057 1,907 1,375\nEqn. 2 EROIel = EOUT\/EPP 5.9 5.9 9.4 11.8\n\u03b7grid 0.31 0.31 0.31 0.31\nEOUT-eq,yr = EOUT,yr \/ \u03b7grid\n\\[MJPE-eq\/(m2\n\u00b7yr)\\] 2,073 1,925 1,925 1,737\nEPBT = EPP\/EOUT-eq,yr \\[yr\\] 1.6 1.6 1.0 0.8\nEqn. 4 EROIPE-eq = T\/EPBT 19 19 30 38\n(a) It is noted that current efficiencies of mono-c Si and CdTe PV are slightly higher than those stated here; correspondingly, their EROIs are\nalso higher.\nSubscripts to energy units stand for: el = electricity; PE = Primary Energy; PE-eq = 'Primary energy equivalent' (based on \u03b7grid).\n14\nTable 2 EROI calculations for oil-fired thermal electricity. LCI data from\n(Ecoinvent, 2011; Jungbluth, 2007)\nRef. Eqn. minimum maximum\nEROIF 10 30\nEPP \\[MJPE\/(plant unit)\\] 1.90\u00b7109 1.90E\u00b7109\nPP units per kWhel output\n\\[(plant units)\/kWhel\\]\n1.18\u00b710-11 1.18\u00b710-11\nEPP \\[MJPE\/kWhel\\] 2.24\u00b710-2 2.24\u00b710-2\nEOUT \\[kWhel\\] 1 1\nEFeed \\[MJPE\/kWhel\\] (a) 9.5 9.5\nEED = EFeed\/EROIF\n\\[MJPE\/kWhel\\]\n0.95 0.32\nEqn. 2 EROIel = EOUT\/(EPP+EED) 3.7 10.6\n(a) Weighted average for European (UCTE) oil-fired electricity.\nSubscripts to energy units stand for: el = electricity; PE = Primary Energy.\nTable 3 EROI calculations for coal-fired thermal electricity (without Carbon\nCapture and Storage). LCI data from (Ecoinvent, 2011; Dones et al., 2007)\nRef. Eqn. minimum maximum\nEROIF 40 80\nEPP \\[MJp\/(plant unit)\\] 2.68E\u00b7109 1.60E\u00b7109\nPP units per kWhel output\n\\[(plant units)\/kWhel\\]\n1.04\u00b710-11 1.31\u00b710-11\nEPP \\[MJPE\/kWhel\\] 2.79\u00b710-2 2.09\u00b710-2\nEOUT \\[kWhel\\] 1 1\nEFeed \\[MJPE\/kWhel\\] (a) 10.7 10.1\n15\nEED = EFeed\/EROIF\n\\[MJPE\/kWhel\\]\n0.27 0.13\nEqn. 2 EROIel = EOUT\/(EPP+EED) 12.2 24.6\n(a) Weighted averages respectively for European (UCTE) lignite-fired electricity\n('minimum' column) and hard coal-fired electricity ('maximum' column).\nSubscripts stand for: el = electricity; PE = Primary Energy.\n4. Discussion\nStarting with the most straightforward approach, i.e.\u00a0adopting the system boundaries","parent_id":"renewable_energy\/241RaugeiEROIEPrevisedII201203VMFpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"renewable_energy\/241RaugeiEROIEPrevisedII201203VMFpdf.txt:9","document_content":"illustrated in Figure 1 and applying Eqn. 2, we may compare the ensuing EROIel of\nPV electricity to the EROIel ranges for oil-and coal-fired thermal electricity (Figure 2).\n0\n2\n4\n6\n8\n10\n12\n14\n16\n18\n20\n22\n24\n26\nmono-c Si\nPV\nelectricity\nmulti-c Si\nPV\nelectricity\nribbon Si\nPV\nelectricity\nCdTe PV\nelectricity\nOil-fired\nelectricity\n(min.)\nOil-fired\nelectricity\n(max.)\nCoal-fired\nelectricity\n(min.)\nCoal-fired\nelectricity\n(max.)\nEROI\nFigure 2 EROIel of PV electricity, compared to the EROIel of oil- and coal-fired\nthermal electricity (Eqn. 2)\n16\nThese results show that, when accounting for the 'energy return' as a straight\nEnergy Carrier (i.e.\u00a0electricity as such), the resulting EROIel of PV spans\napproximately the same range (EROIel \u2248 6 -- 12) as the EROIel of conventional oilfired electricity systems (EROIel \u2248 4 -- 11), while the EROIel of coal-fired electricity\nsystems come out approximately double of that of PV (EROIel \u2248 12 -- 24). However,\nit should not be forgotten that thermal electricity production, and coal-fired systems\nin particular, suffer from much higher life-cycle greenhouse gas emissions than PV\n(Fthenakis and Kim, 2011), which would be energy-intensive to reduce by means of","parent_id":"renewable_energy\/241RaugeiEROIEPrevisedII201203VMFpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"wood_CO2\/stationaryemissions32016pdf.txt:31","document_content":"## and N2 O by the respective global warming potential (GWP) to calculate CO2\nNatural Gasoline 66.88 3.0 0.60\nOther Oil (\\>401 deg F) 76.22 3.0 0.60\nAppendix A: Default Emission Factors\nU.S. EPA Center for Corporate Climate Leadership -- GHG Inventory Guidance 21\nDirect Emissions from Stationary Combustion Sources\nFuel Emission\nFactors\nPetroleum Products (continued) (kg CO2\n\/mmBtu) (g CH4\n\/mmBtu) (g N2\nO\/mmBtu)\nPentanes Plus 70.02 3.0 0.60\nPetrochemical Feedstocks 71.02 3.0 0.60\nPetroleum Coke 102.41 3.0 0.60\nPropane 62.87 3.0 0.60\nPropylene 67.77 3.0 0.60\nResidual Fuel Oil No.\u00a05 72.93 3.0 0.60\nResidual Fuel Oil No.\u00a06 75.10 3.0 0.60\nSpecial Naphtha 72.34 3.0 0.60\nUnfinished Oils 74.54 3.0 0.60\nUsed Oil 74.00 3.0 0.60\nTable A-4: Emission Factors for Equation 2 (EF2\n) - Emissions per Energy Unit for Biomass Fuel Combustion\nFuel Emission\nFactors\nBiomass Fuels (Solid) (kg CO2\n\/mmBtu) (g CH4\n\/mmBtu) (g N2\nO\/mmBtu)\nAgricultural Byproducts 118.17 32 4.2\nPeat 111.84 32 4.2\nSolid Byproducts 105.51 32 4.2\nWood and Wood Residuals 93.80 7.2 3.6\nBiomass Fuels (Gaseous)\nLandfill Gas 52.07 3.2 0.63\nOther Biomass Gases 52.07 3.2 0.63\nBiomass Fuels (Liquid)\nBiodiesel (100%) 73.84 1.1 0.11\nEthanol (100%) 68.44 1.1 0.11\nRendered Animal Fat 71.06 1.1 0.11","parent_id":"wood_CO2\/stationaryemissions32016pdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"wood_CO2\/stationaryemissions32016pdf.txt:32","document_content":"## and N2 O by the respective global warming potential (GWP) to calculate CO2\nVegetable Oil 81.55 1.1 0.11\nBiomass Fuels (Kraft Pulping Liquor, by Wood Furnish)\nNorth American Softwood 94.4 1.9 0.42\nNorth American Hardwood 93.7 1.9 0.42\nBagasse 95.5 1.9 0.42\nBamboo 93.7 1.9 0.42\nStraw 95.1 1.9 0.42\nSource for the emission factors in this appendix: Solid, gaseous, liquid, and biomass fuels: Federal Register (2009) EPA; 40 Source for the\nemission factors in this appendix: Federal Register (2013) EPA; 40 CFR Part 98; 2013 Revisions to the Greenhouse Gas Reporting Rule and Final\nConfidentiality Determinations for New or Substantially Revised Data Elements; Final Rule. November 29, 2013. Table C-1, Table C-2, Table AA-1.\n<http:\/\/www.gpo.gov\/fdsys\/pkg\/FR-2013-11-29\/pdf\/2013-27996.pdf>.\nAppendix A: Default Emission Factors","parent_id":"wood_CO2\/stationaryemissions32016pdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"certificate\/2562pdf.txt:15","document_content":"are the followings:\n\u2022 The contents and the visual presentation of the EPCs.\nThe usability and therefore the credibility of the certificate\nis highly influenced by the level of information shown on\nit as well as by the way this information is accessible to a\nwide range of users, from professionals to building owners.\n\u2022 The assessment method. The EPC quality depends\nstrongly on the assessment methodology of the EPC\nscheme. For instance the preference for a rating system and the corresponding energy classes as well as the\namount and the accuracy of the default values influence\nsignificantly the quality of the EPC.\n\u2022 The public awareness on EPCs. The level of public awareness and the quality of the promotional campaigns are important factors in increasing the usability of the EPCs. The\nmarket campaigns for promoting the EPCs are especially\ninfluential for the building owners and users, but should\nproperly address all the users' categories in order to be\neffective.\n\u2022 The level of enforcement. The non-compliance and the\npoor quality of the certifiers' assessment may create serious doubts on the real value of the EPC. Therefore, the\nlevel of enforcement and the related penalties for noncompliance and bad execution are determinant for the usability of the EPC scheme.\nTable 2: Main characteristics of the EPCs in selected countries.\nAT BE CZ DK FR\nRes Non-res\nDE HU IE NL PL PT ES\nLabel classes A++ A+ No A A A A No A+ A1A2A3 A++ A+ A No A+ A A\nA sliding\nscale B B B B sliding\nscale A B1B2B3 B sliding\nscale B, B- B\nB C C C C B C1C2C3 C C C\nC D D D D C D1D2 D D D\nD E E E E D E1E2 E E E\nE F F F F E F F F F\nF G G G G F G G G G\nG H G\nI\nPerformance\nindicator kWh\/m2a kWh\/m2a GJ\/year\nNo\nspecific\ninfo\nNo specific info kWh\/m2a No specific\ninfo\nkWh\/m2a\nand CO2-\nemission\nEnergy\nindex\nNo\nspecific\ninfo\nkWh\/m2a\nNo\nspecific\ninfo\nLabel\npresent situation\nof the building\nYes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes\nLabel after\nimplementing the","parent_id":"certificate\/2562pdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"spring_store_energy\/S187661021502576Xpdf.txt:6","document_content":"Table 1. Energy data on spring-based energy storage systems.\nReference Power density Gravimetric energy density Volumetric energy density\nSteel coiled spring \\[26\\] - 0.14 kJ\/kg 1080 kJ\/m3\nCNT yarn spring \\[21\\] - 4.20 kJ\/kg 4900 kJ\/m3\nCNT yarn spring-driven\nelectromagnetic generator \\[14\\]\n2500 W\/kg 0.88kJ\/kg 1770kJ\/m3\nTwisted CNT \\[22\\] - 8.30 kJ\/kg -\nBatteries \\[5\\] 100-2000 W\/kg 20-576 kJ\/kg 54000-1.6\u00b7106 kJ\/m3\nCompressed Air Energy Storage \\[5\\] - 12.60 kJ\/kg 18000 kJ\/m3\nFlywheel Energy Storage \\[5\\] 12000 W\/kg 18-360 kJ\/kg -\nSupercapacitors \\[5\\] 800-20000 W\/kg 7-100 kJ\/kg 36000 kJ\/m3\nComparing CNT springs performances with those of other technologies, they lag behind the energy\ndensities of rechargeable batteries.\nThe order of magnitude of CNT springs' energy densities is comparable with that of CAES, flywheels\nand supercapacitors. Even if at an early stage, CNT springs have a power density that is comparable to\nbatteries.\n3. Conclusion\nConventional mechanical springs coupled with electromechanical devices for energy storage and","parent_id":"spring_store_energy\/S187661021502576Xpdf.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"water_plant\/SolubleSalts.txt:0","document_content":"SKIP TO CONTENT SITE MAP\nEnter Search Terms\nSearch GIVE\nlogo\nUniversity of California Agriculture and Natural Resources\nThe California Garden Web\nThe California Garden Web\nUC Master Gardener Program\nUC ANR Home\nSHARE PRINT\nSoluble Salts\nSoluble salts may accumulate on the top of the soil, forming a yellow or white crust. A ring of salt deposits may form around the pot at the soil line or around the drainage hole. Salts may also build up on the outside of clay pots. In house plants, signs of excess soluble salts include reduced growth, brown leaf tips, dropping of lower leaves, small new growth, dead root tips, and wilting.\nSoluble salts are minerals dissolved in water. Fertilizer dissolved in water becomes a soluble salt. When water evaporates from the soil, the minerals or salts stay behind. As the salts in the soil become more and more concentrated, it becomes more difficult for plants to take up water. If salts build up to an extremely high level, water can be taken out of the root tips, causing them to die. High levels of soluble salts damage the roots directly, weakening the plant and making it more susceptible to attack from insects and diseases. One of the most common problems associated with high salt levels is root rot.\nThe best way to prevent soluble salt injury is to stop the salts from building up. When watering, allow some water to drain through the container and then empty the saucer. Do not allow the pot to sit in water. If the drained water is absorbed by the soil, the salts that were washed out are reabsorbed through the drainage hole or directly through a clay pot.\nHouse plants should be leached at least every 4 to 6 months. To leach plants, pour excess water on the soil and let it drain completely. The amount of water used for leaching should equal twice the volume of the pot. Keep the water running through the soil to wash out the salts. If a layer of salts has formed a crust at the soil surface, remove the salt crust before leaching. Do not remove more than 1\/4 inch (6 mm) of soil. It is best not to add soil to the top of the pot. If the soluble salt level appears to be extremely high, repot the plant.","parent_id":"water_plant\/SolubleSalts.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"water_plant\/SolubleSalts.txt:1","document_content":"The level of salts that causes injury varies with the species of plant and how it is grown. A house plant may be injured by salts at a very low concentration, but the same plant growing in a greenhouse where watering is well managed may tolerate salts at high levels. Some nurseries and retail plant outlets leach plants to remove excess salts before the plant is sold. If you are not sure that a newly purchased plant has been leached, leach it the first time you water.\nHome\nDrought\nFlowers\nGardening Basics\nGardening Classes & Events\nGlossary: A - M\nGlossary: N-Z\nGrowing Berries in Your Backyard\nGrowing Grapes (table, wine, raisins) in Your Backyard\nIndoor Plants\nWhat does my plant need?\nFertilization\nSoluble Salts\npH\nGrowing Media\nLandscape Trees, Shrubs, & Vines\nLawns\nLinks\nNut & Fruit Trees & Vines\nPoisonous Plants\nVegetables\nWhat is my climate zone?\nDivision of Agriculture and Natural Resources, University of California\n\u00a9 2024 Regents of the University of California Division of Agriculture and Natural Resources Nondiscrimination Statement\nAccessibility Get PDF Reader Site Information","parent_id":"water_plant\/SolubleSalts.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"ceremics\/pageid56.txt:0","document_content":"`\\Home`{=tex}\\\n\n# Home\nSearch\nPrimary Menu Skip to content\n- MUSIC\n- FAQs\n- BIBLIOGRAPHY\n- Getting to ZW -The Book\n- PROJECTS\n- PRINCIPLES\n- The Thermodynamic Argument Dismantled\n- Your Personal Efforts and Zero Waste\n- A Quick Walk Through Thermodynamics\n- ARCHIVE\n- GREENWASHING\n- CONTACT US\n- ABOUT US\n- Can you help?\n- Your Stories\n- STUDIES\nSearch for:\n\n# Ceramics\nCeramics are a confusing issue. Are they like glass? Actually they aren't,\nbecause they don't melt. Are they organic, so they can be composted? No again!\nSo they end up in garbage where their sharp corners are a danger, then in\ndumps, which is a waste and a shame.\nA ceramic is most often made from clay that has been heated to where the\nparticles partially melt together (sinter) and stick together into a rigid\nmass. The way to reuse a broken ceramic mass is thus obvious. Break the\nparticles apart and return them to the clay that they were made from. This is\nbest done by grinding the pieces in a mill, but second best would be simply\nbreaking the large pieces into powder with a large hammer or a flat tamping\ntool. The powder may not be valuable, since it is just ordinary clay, but at\nleast it can be distributed onto soil with no ill effect and it is not filling\nup dumps. Some excessively sandy soils may benefit from the addition of clay\npowder.\nSome ceramics, known as refractories, usually found in high tech or research\nceramics, may be made from valuable or rare oxides, or even highly refined\naluminum oxides (claylike) rather than simple clay. Recapturing the powder may\nbe economically worthwhile.\nUsing a personal hammer for smashing broken teapots or flowerpots is\nsatisfying but is not a large scale solution for society. What we need is a\ndedicated grinding mill that takes in all of a population's broken ceramics\nand puts them through a power mill. Then the amount of powder would be\nsignificant and could be reused for new ceramics. More research would be\nuseful, since not all ceramics are the same and they often have glazes.\nOne ceramic that is common and a bit valuable is porcelain which is made from\na fine, white clay. There is a ton of this available from unwanted toilets and\nsinks. One tile maker in San Jose California makes a good living by milling\nbathroom fixtures back into clay and then remaking them as exquisite tiles.\nRead more.","parent_id":"ceremics\/pageid56.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt:0","document_content":"Are banana peels higher in potassium and magnesium than the fruit itself?\nSort\nProfile photo for Assistant\nAssistant\n\u00b7\nBot\nBanana peels do contain higher amounts of potassium and magnesium compared to the fruit itself. While the peel is not typically consumed, it does have nutritional benefits. However, it\\'s important to note that the peel also contains more fiber and other compounds that may not be as palatable as the fruit.\nProfile photo for Dan Hauenstein\nDan Hauenstein\nStudied Biology at College of Lake County\n\u00b7\n4y\nBananas contain a plethora of nutrients, including Vitamin B6, Manganese, Vitamin C, Magnesium and a huge amount of potassium. The peel is edible and consumed in many cultures. The peel has a lot of the nutrients the rest of the fruit has, but the inside of the fruit still contains more potassium than the peel. The average banana contains a whopping 422mg of potassium and the peel contains about 78mg.","parent_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt:1","document_content":"Sponsored by ATP Personal Training Hong Kong\nWhat is metabolic health, and why does it matter?\nTry these 5 simple tips to become healthier metabolically without having to be a fitness fanatic.\nRelated questions\nHow many bananas can I eat to get full magnesium?\nDo bananas contain magnesium?\nWhich food contains a higher amount of magnesium, banana or avocado?\nWhich fruit has the most potassium and magnesium?\nAre banana peels good for plants?\nProfile photo for Shilpa Sadhaa\nShilpa Sadhaa\nStudied Nutrition & YogaAuthor has 370 answers and 230K answer views\n\u00b7\n1y\nRelated\nWhat minerals and vitamines does a banana\/peel have the most of?\nThe banana peels themselves offer additional nutrients, including:\nVitamin B6.\nVitamin B12.\nMagnesium.\nPotassium.\nFiber.\nProtein.\nBanana peels are rich in polyphenols, carotenoids, and other antioxidants that protect your body from cancer-causing free radicals. Consuming more banana peels can boost your antioxidant levels and lower your chance of developing cancer.\nBanana peel also contains vitamins C, E, and B6. Vitamin C can act as an antioxidant, while serotonin is thought to play an anti-depressant so as to increase feed intake and body weight on heat stress conditions.\nThe banana peel is rich in protein, dietary fiber, vitamin C, vitamin A, calcium, iron, essential amino acids, polyunsaturated fatty acids, antioxidants and potassium.\nIf you\\'ve been wondering if you can eat raw, cooked or even frozen banana peels, the answer is yes! If you are going to eat your banana peel, know that---just like the fruit itself---the riper the peel, the sweeter it will taste.\nWhile this is not much of a concern if you\\'re only eating the fruit, it may be something to consider when consuming the peel. Pesticide exposure has been linked to several adverse effects on health and may increase the risk of conditions like autism, cancer, high blood pressure, diabetes, and dementia.","parent_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt:2","document_content":"Profile photo for Boris Zakharin\nBoris Zakharin\nloves scienceAuthor has 3.8K answers and 2.4M answer views\n\u00b7\n4y\nThere are plenty of articles claiming that banana peels are full of nutrients, and that people all over the world eat banana peels together with the flesh. While the peels really do contain nutrients, there have been no studies about how efficiently these nutrients are absorbed by the body, if at all. There have also been no legitimately documented cultures where banana peel eating is widespread. In fact, even monkeys peel bananas before eating them.\nThat said, aside for potential pesticides sprayed on them, banana peels are not harmful to eat, just bitter and unpleasant, so those who want to t\nProfile photo for Dr.\u00a0Gennifer Herley\nDr.\u00a0Gennifer Herley\nMD Student at Yale School of Medicine (2021--present)Author has 497 answers and 351.2K answer views\n\u00b7\n6mo\nRelated\nIs banana content magnesium?\nIn the world of health and nutrition, one question that often arises is, \\\"Is banana content magnesium?\\\" Bananas are a beloved fruit enjoyed by people all around the globe, and their nutritional value is a topic of interest for many. In this comprehensive article, we will delve into the composition of bananas, exploring whether they contain magnesium and what implications this has for your health.\nThe Nutritional Powerhouse: Bananas\nBananas are not only delicious but also pack a powerful nutritional punch. They are rich in essential vitamins and minerals that contribute to overall health and well","parent_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt:3","document_content":"Sponsored by JetBrains\nNew code quality platform by JetBrains. Connect to any CI tool.\nBrings JetBrains IDE-native inspections to your CI\/CD pipeline. Support for 60+ technologies.\nRelated questions\nAre bananas a good source of magnesium?\nHow might I measure the amount of potassium in a banana?\nThe US RDA of potassium is 4700 mg. However it is a lot work to get this. What is the difference between eating 15 bananas as opposed to taking a couple of teaspoons of potassium citrate daily?\nIs coconut water a better source of potassium and magnesium than bananas?\nHow many bananas do you have to eat to get your daily potassium?\nProfile photo for Mary\nMary\nBachelor\\'s degree in history, Master\\'s degree in cultural stAuthor has 1.5K answers and 4.5M answer views\n\u00b7\n10mo\nRelated\nHas there been any extensive research about the nutritional content of cavendish banana peels?\nWhile bananas are a widely consumed fruit, the focus of nutritional research has primarily been on the edible portion---the flesh of the banana---rather than the peel. As a result, there is limited and extensive research specifically on the nutritional content of Cavendish banana peels.\nHowever, it is known that banana peels contain certain nutrients and compounds. They are a source of dietary fiber, including both soluble and insoluble fiber, which can support digestive health. Additionally, banana peels contain various vitamins and minerals, such as vitamin C, vitamin B6, potassium, magnesium, and manganese, although the exact quantities may vary.\nSome preliminary studies have explored the potential health benefits of consuming banana peels. These studies suggest that the peels may have antioxidant properties due to their content of phenolic compounds. Banana peels also contain compounds like dopamine and serotonin, which are associated with mood regulation and may have positive effects on mental well-being.","parent_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt:4","document_content":"Profile photo for Lucy Thompson\nLucy Thompson\nLives in Jefferson City, MissouriAuthor has 2.3K answers and 1.7M answer views\n\u00b7\n2y\nRelated\nHow many milligrams of potassium are in each gram of banana peel?\nThe banana peel does have potassium as well as the banana fruit. There are wildly varying reports of the potassium content of banana peels, and some \"organic gardeners\" extoll the virtues of the high level of potassium in peels and use them for fertilizer championing the added potassium to their precious dirt. A couple of websites actually claim the banana peel is 42% potassium.\nA \"pretty good\" average value for the amount of potassium in banana:\nFruit - 3.58 mg K per gm of banana fruit\nPeel - 0.78 mg K per gm of banana peel\nSponsored by Aspose\nAspose.BarCode for Java - Barcode Generation & Recognition API.\nCreate, & recognize barcodes of linear, 2D and postal types within any Java application and much more!\nProfile photo for Shipra K B\nShipra K B\nInsurance Advisor at Turtle Mintpro (2022--present)\n\u00b7","parent_id":"banana_peel\/Arebananapeelshigherinpotassiumandmagnesiumthanthefruititself.txt","metadata":null,"task_split":"stack_exchange"}
{"document_id":"non_organic\/section205203.txt:1","document_content":"\u00a7 205.203 Soil fertility and crop nutrient management practice standard.\n(a) The producer must select and implement tillage and cultivation practices that maintain or improve the physical, chemical, and biological condition of soil and minimize soil erosion.\n(b) The producer must manage crop nutrients and soil fertility through rotations, cover crops, and the application of plant and animal materials.\n(c) The producer must manage plant and animal materials to maintain or improve soil organic matter content in a manner that does not contribute to contamination of crops, soil, or water by plant nutrients, pathogenic organisms, heavy metals, or residues of prohibited substances. Animal and plant materials include:\n(1) Raw animal manure, which must be composted unless it is:\n(i) Applied to land used for a crop not intended for human consumption;\n(ii) Incorporated into the soil not less than 120 days prior to the harvest of a product whose edible portion has direct contact with the soil surface or soil particles; or\n(iii) Incorporated into the soil not less than 90 days prior to the harvest of a product whose edible portion does not have direct contact with the soil surface or soil particles;\n(2) Composted plant and animal materials produced through a process that:\n(i) Established an initial C:N ratio of between 25:1 and 40:1; and\n(ii) Maintained a temperature of between 131 \u00b0F and 170 \u00b0F for 3 days using an in-vessel or static aerated pile system; or\n(iii) Maintained a temperature of between 131 \u00b0F and 170 \u00b0F for 15 days using a windrow composting system, during which period, the materials must be turned a minimum of five times.\n(3) Uncomposted plant materials.\n(d) A producer may manage crop nutrients and soil fertility to maintain or improve soil organic matter content in a manner that does not contribute to contamination of crops, soil, or water by plant nutrients, pathogenic organisms, heavy metals, or residues of prohibited substances by applying:\n(1) A crop nutrient or soil amendment included on the National List of synthetic substances allowed for use in organic crop production;\n(2) A mined substance of low solubility;\n(3) A mined substance of high solubility: Provided, That, the substance is used in compliance with the conditions established on the National List of nonsynthetic materials prohibited for crop production;\n(4) Ash obtained from the burning of a plant or animal material, except as prohibited in paragraph (e) of this section: Provided, That, the material burned has not been treated or combined with a prohibited substance or the ash is not included on the National List of nonsynthetic substances prohibited for use in organic crop production; and\n(5) A plant or animal material that has been chemically altered by a manufacturing process: Provided, That, the material is included on the National List of synthetic substances allowed for use in organic crop production established in \u00a7 205.601.\n(e) The producer must not use:\n(1) Any fertilizer or composted plant and animal material that contains a synthetic substance not included on the National List of synthetic substances allowed for use in organic crop production;\n(2) Sewage sludge (biosolids) as defined in 40 CFR part 503; and\n(3) Burning as a means of disposal for crop residues produced on the operation: Except, That, burning may be used to suppress the spread of disease or to stimulate seed germination.","parent_id":"non_organic\/section205203.txt","metadata":null,"task_split":"stack_exchange"}