888 resultados para spend hen


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A comprehensive analysis of precompetition dietary beliefs and behaviors of competitive bodybuilders has yet to be documented in the literature. The purposes of this study were (a) to quantify and document types of supplements competitive male and female bodybuilders consume, (b) to document how much money they spend on them each month, (c) to describe what dietary modifications and behaviors they follow in preparation for a contest and (d) to describe their nutrition beliefs associated with these habits. Three hundred and nine competitive male and female bodybuilders completed questionnaires regarding their precompetition dietary practices. It was found that bodybuilders consume a wide variety of supplements and use a multitude of dietary training practices which vary depending on the training phase. A large percentage of bodybuilders agreed with statements on supplement use and training practices that are unsubstantiated by scientific research.

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This project will create a blueprint for an eco-settlement in the South Florida area that will house a total of ten people on a five acre plot of land. Using a combination of permaculture design principles and simple tech solutions, this settlement will be capable of supporting its inhabitants “off the grid”, or with no reliance on outside public utilities. More specifically, the settlement will be capable of supporting its inhabitants by producing a minimum of 80% of its resources on site using only all natural farming techniques, proper water management, companion planting and various other techniques. Instead of using modern agricultural practices that damage the land in the long term, all of the principles that will be used in this design will allow the land to heal over time while still producing most of what is needed for any inhabitants. This project is significant because all of the principles used are time-tested and capable of adapting to any type of environment. The principles used do not have a steep learning curve. In fact, anyone ranging from a kindergartener to a 90-year-old will be able to learn and teach the required skill sets in as little as one week. By contrast, in order to fully utilize GMO crops, first a scientist must spend a minimum of eight years getting degrees in various fields of study to even reach a textbook understanding of the exact science. In addition, several years must be spent in sterile lab environments to see the results of complex experiments that may not even be used, thus wasting time, money, and resources. I am certain that this will be successful because similar goals have already been reached by people around the world without access to modern utilities. The only major difference is that my approach will be documented scientifically, and show that not only is this way of life healthy, but also easy and practical. Because of this, my project will bring permaculture design into the spotlight, and will hopefully see widespread adoption. This will result in cities designed with the intent to live with nature instead of conquering it, and will hopefully aid the earth in healing for future generations.

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This work was developed with the objective of proposing a simple, fast and versatile methodological routine using near-infrared spectroscopy (NIR) combined with multivariate analysis for the determination of ash content, moisture, protein and total lipids present in the gray shrimp (Litopenaeus vannamei ) which is conventionally performed gravimetrically after ashing at 550 ° C gravimetrically after drying at 105 ° C for the determination of moisture gravimetrically after a Soxhlet extraction using volumetric and after digestion and distillation Kjedhal respectively. Was first collected the spectra of 63 samples processed boiled shrimp Litopenaeus vannamei species. Then, the determinations by conventional standard methods were carried out. The spectra centered average underwent multiplicative scattering correction of light, smoothing Saviztky-Golay 15 points and first derivative, eliminated the noisy region, the working range was from 1100,36 to 2502,37 nm. Thus, the PLS models for predicting ash showed R 0,9471; 0,1017 and RMSEP RMSEC 0,1548; Moisture R was 0,9241; 2,5483 and RMSEP RMSEC 4,1979; R protein to 0,9201; 1,9391 and RMSEP RMSEC 2,7066; for lipids R 0,8801; 0,2827 and RMSEP RMSEC 0,2329 So that the results showed that the relative errors found between the reference method and the NIR were small and satisfactory. These results are an excellent indication that you can use the NIR to these analyzes, which is quite advantageous, since conventional techniques are time consuming, they spend a lot of reagents and involve a number of professionals, which requires a reasonable runtime while after the validation of the methodology execution using NIR reduces all this time to a few minutes, saving reagents, time and without waste generation, and that this is a non-destructive technique.

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Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.

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Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.

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Recent technological developments in the field of experimental quantum annealing have made prototypical annealing optimizers with hundreds of qubits commercially available. The experimental demonstration of a quantum speedup for optimization problems has since then become a coveted, albeit elusive goal. Recent studies have shown that the so far inconclusive results, regarding a quantum enhancement, may have been partly due to the benchmark problems used being unsuitable. In particular, these problems had inherently too simple a structure, allowing for both traditional resources and quantum annealers to solve them with no special efforts. The need therefore has arisen for the generation of harder benchmarks which would hopefully possess the discriminative power to separate classical scaling of performance with size from quantum. We introduce here a practical technique for the engineering of extremely hard spin-glass Ising-type problem instances that does not require "cherry picking" from large ensembles of randomly generated instances. We accomplish this by treating the generation of hard optimization problems itself as an optimization problem, for which we offer a heuristic algorithm that solves it. We demonstrate the genuine thermal hardness of our generated instances by examining them thermodynamically and analyzing their energy landscapes, as well as by testing the performance of various state-of-the-art algorithms on them. We argue that a proper characterization of the generated instances offers a practical, efficient way to properly benchmark experimental quantum annealers, as well as any other optimization algorithm.

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Long-distance migratory birds are declining globally and migration has been identified as the primary source of mortality in this group. Despite this, our lack of knowledge of habitat use and quality at stopovers, i.e., sites where the energy for migration is accumulated, remains a barrier to designing appropriate conservation measures, especially in tropical regions. There is therefore an urgent need to assess stopover habitat quality and concurrently identify efficient and cost-effective methods for doing so. Given that fuel deposition rates directly influence stopover duration, departure fuel load, and subsequent speed of migration, they are expected to provide a direct measure of habitat quality and have the advantage of being measurable through body-mass changes. Here, we examined seven potential indicators of quality, including body-mass change, for two ecologically distinct Neotropical migratory landbirds on stopover in shade-coffee plantations and tropical humid premontane forest during spring migration in Colombia: (1) rate of body-mass change; (2) foraging rate; (3) recapture rate; (4) density; (5) flock size; (6) age and sex ratios; and (7) body-mass distribution. We found higher rates of mass change in premontane forest than in shade-coffee in Tennessee Warbler Oreothlypis peregrina, a difference that was mirrored in higher densities and body masses in forest. In Gray-cheeked Thrush Catharus minimus, a lack of recaptures in shade-coffee and higher densities in forest, also suggested that forest provided superior fueling conditions. For a reliable assessment of habitat quality, we therefore recommend using a suite of indicators, taking into account each species’ ecology and methodological considerations. Our results also imply that birds stopping over in lower quality habitats may spend a longer time migrating and require more stopovers, potentially leading to important carryover effects on reproductive fitness. Evaluating habitat quality is therefore imperative prior to defining the conservation value of newly identified stopover regions.

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This paper will explore a data-driven approach called Sales Resource Management (SRM) that can provide real insight into sales management. The DSMT (Diagnosis, Strategy, Metrics and Tools) framework can be used to solve field sales management challenges. This paper focus on the 6P's strategy of SRM and illustrates how to use them to solve the CAPS (Concentration, Attrition, Performance and Spend) challenges. © 2010 IEEE.

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Objective. This study aims to provide a better understanding of the amounts spent on different malaria prevention products and the determinants of these expenditures. Methods. 1,601 households were interviewed about their expenditure on malaria mosquito nets in the past five years, net re-treatments in the past six months and other expenditures prevention in the past two weeks. Simple random sampling was used to select villages and streets while convenience sampling was used to select households. Expenditure was compared across bed nets, aerosols, coils, indoor spraying, using smoke, drinking herbs and cleaning outside environment. Findings. 68% of households owned at least one bed net and 27% had treated their nets in the past six months. 29% were unable to afford a net. Every fortnight, households spent an average of US $0.18 on nets and their treatment, constituting about 47% of total prevention expenditure. Sprays, repellents and coils made up 50% of total fortnightly expenditure (US$0.21). Factors positively related to expenditure were household wealth, years of education of household head, household head being married and rainy season. Poor quality roads and living in a rural area had a negative impact on expenditure. Conclusion. Expenditure on bed nets and on alternative malaria prevention products was comparable. Poor households living in rural areas spend significantly less on all forms of malaria prevention compared to their richer counterparts. Breaking the cycle between malaria and poverty is one of the biggest challenges facing malaria control programmes in Africa.

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At least since the seminal works of Jacob Mincer, labor economists have sought to understand how students make higher education investment decisions. Mincer’s original work seeks to understand how students decide how much education to accrue; subsequent work by various authors seeks to understand how students choose where to attend college, what field to major in, and whether to drop out of college.

Broadly speaking, this rich sub-field of literature contributes to society in two ways: First, it provides a better understanding of important social behaviors. Second, it helps policymakers anticipate the responses of students when evaluating various policy reforms.

While research on the higher education investment decisions of students has had an enormous impact on our understanding of society and has shaped countless education policies, students are only one interested party in the higher education landscape. In the jargon of economists, students represent only the `demand side’ of higher education---customers who are choosing options from a set of available alternatives. Opposite students are instructors and administrators who represent the `supply side’ of higher education---those who decide which options are available to students.

For similar reasons, it is also important to understand how individuals on the supply side of education make decisions: First, this provides a deeper understanding of the behaviors of important social institutions. Second, it helps policymakers anticipate the responses of instructors and administrators when evaluating various reforms. However, while there is substantial literature understanding decisions made on the demand side of education, there is far less attention paid to decisions on the supply side of education.

This dissertation uses empirical evidence to better understand how instructors and administrators make decisions and the implications of these decisions for students.

In the first chapter, I use data from Duke University and a Bayesian model of correlated learning to measure the signal quality of grades across academic fields. The correlated feature of the model allows grades in one academic field to signal ability in all other fields allowing me to measure both ‘own category' signal quality and ‘spillover' signal quality. Estimates reveal a clear division between information rich Science, Engineering, and Economics grades and less informative Humanities and Social Science grades. In many specifications, information spillovers are so powerful that precise Science, Engineering, and Economics grades are more informative about Humanities and Social Science abilities than Humanities and Social Science grades. This suggests students who take engineering courses during their Freshman year make more informed specialization decisions later in college.

In the second chapter, I use data from the University of Central Arkansas to understand how universities decide which courses to offer and how much to spend on instructors for these courses. Course offerings and instructor characteristics directly affect the courses students choose and the value they receive from these choices. This chapter reveals the university preferences over these student outcomes which best explain observed course offerings and instructors. This allows me to assess whether university incentives are aligned with students, to determine what alternative university choices would be preferred by students, and to illustrate how a revenue neutral tax/subsidy policy can induce a university to make these student-best decisions.

In the third chapter, co-authored with Thomas Ahn, Peter Arcidiacono, and Amy Hopson, we use data from the University of Kentucky to understand how instructors choose grading policies. In this chapter, we estimate an equilibrium model in which instructors choose grading policies and students choose courses and study effort given grading policies. In this model, instructors set both a grading intercept and a return on ability and effort. This builds a rich link between the grading policy decisions of instructors and the course choices of students. We use estimates of this model to infer what preference parameters best explain why instructors chose estimated grading policies. To illustrate the importance of these supply side decisions, we show changing grading policies can substantially reduce the gender gap in STEM enrollment.

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Surveys can collect important data that inform policy decisions and drive social science research. Large government surveys collect information from the U.S. population on a wide range of topics, including demographics, education, employment, and lifestyle. Analysis of survey data presents unique challenges. In particular, one needs to account for missing data, for complex sampling designs, and for measurement error. Conceptually, a survey organization could spend lots of resources getting high-quality responses from a simple random sample, resulting in survey data that are easy to analyze. However, this scenario often is not realistic. To address these practical issues, survey organizations can leverage the information available from other sources of data. For example, in longitudinal studies that suffer from attrition, they can use the information from refreshment samples to correct for potential attrition bias. They can use information from known marginal distributions or survey design to improve inferences. They can use information from gold standard sources to correct for measurement error.

This thesis presents novel approaches to combining information from multiple sources that address the three problems described above.

The first method addresses nonignorable unit nonresponse and attrition in a panel survey with a refreshment sample. Panel surveys typically suffer from attrition, which can lead to biased inference when basing analysis only on cases that complete all waves of the panel. Unfortunately, the panel data alone cannot inform the extent of the bias due to attrition, so analysts must make strong and untestable assumptions about the missing data mechanism. Many panel studies also include refreshment samples, which are data collected from a random sample of new

individuals during some later wave of the panel. Refreshment samples offer information that can be utilized to correct for biases induced by nonignorable attrition while reducing reliance on strong assumptions about the attrition process. To date, these bias correction methods have not dealt with two key practical issues in panel studies: unit nonresponse in the initial wave of the panel and in the

refreshment sample itself. As we illustrate, nonignorable unit nonresponse

can significantly compromise the analyst's ability to use the refreshment samples for attrition bias correction. Thus, it is crucial for analysts to assess how sensitive their inferences---corrected for panel attrition---are to different assumptions about the nature of the unit nonresponse. We present an approach that facilitates such sensitivity analyses, both for suspected nonignorable unit nonresponse

in the initial wave and in the refreshment sample. We illustrate the approach using simulation studies and an analysis of data from the 2007-2008 Associated Press/Yahoo News election panel study.

The second method incorporates informative prior beliefs about

marginal probabilities into Bayesian latent class models for categorical data.

The basic idea is to append synthetic observations to the original data such that

(i) the empirical distributions of the desired margins match those of the prior beliefs, and (ii) the values of the remaining variables are left missing. The degree of prior uncertainty is controlled by the number of augmented records. Posterior inferences can be obtained via typical MCMC algorithms for latent class models, tailored to deal efficiently with the missing values in the concatenated data.

We illustrate the approach using a variety of simulations based on data from the American Community Survey, including an example of how augmented records can be used to fit latent class models to data from stratified samples.

The third method leverages the information from a gold standard survey to model reporting error. Survey data are subject to reporting error when respondents misunderstand the question or accidentally select the wrong response. Sometimes survey respondents knowingly select the wrong response, for example, by reporting a higher level of education than they actually have attained. We present an approach that allows an analyst to model reporting error by incorporating information from a gold standard survey. The analyst can specify various reporting error models and assess how sensitive their conclusions are to different assumptions about the reporting error process. We illustrate the approach using simulations based on data from the 1993 National Survey of College Graduates. We use the method to impute error-corrected educational attainments in the 2010 American Community Survey using the 2010 National Survey of College Graduates as the gold standard survey.

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Grey seal, Halichoerus grypus, pups in the breeding colony at Froan, Norway, have a bimodal pattern of early aquatic behaviour. About 40% of the pups spend their time ashore to save energy, which can be allocated to growth or deposition of energy-rich adipose tissue. The other 60% of the pups enter the sea during suckling and the early postweaning period, and disperse to other locations within the breeding colony. Pups may swim distances up to 12 km. Neonatal aquatic dispersal behaviour may lead to increased energy expenditure for thermoregulation and swimming, and thus lead to a low rate of body mass gain during suckling and a high rate of body mass loss after weaning. Thus, we examined relationships between natal aquatic dispersal behaviour and change in body mass (DeltaBM) in suckling and weaned pups. Suckling pups that had dispersed >2000 m had a significantly lower DBM than suckling pups that dispersed <2000 m or that did not disperse. In weaned pups, there were no effects of aquatic dispersal behaviour on DBM. We suggest that the bimodal natal aquatic dispersal behaviour in grey seals at the study site reflects two different strategies for postweaning survival: to stay ashore and get fat, or to take a swim and acquire diving and feeding skills.

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The behaviors of youth ice hockey coaches during games are examined using the Coaches Observation System for Games. This tool identifies 16 types of coach behaviors and eight targets of such behaviors. Findings reveal that coaches spend 51.2% of their time simply observing the game. Other common coach behaviors are organizing (15%), directing the game (8.1%) and giving information (6.1%). Targets of these behaviors include players in action (40.9%), on the bench (30.4%) and in transition (22.3%).

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Background: Chronic fatigue syndrome, also known as myalgic encephalomyelitis (CFS/ME), is characterized by chronic disabling fatigue and other symptoms, which are not explained by an alternative diagnosis. Previous trials have suggested that graded exercise therapy (GET) is an effective and safe treatment. GET itself is therapist-intensive with limited availability. Objective: While guided self-help based on cognitive behavior therapy appears helpful to patients, Guided graded Exercise Self-help (GES) is yet to be tested. Methods: This pragmatic randomized controlled trial is set within 2 specialist CFS/ME services in the South of England. Adults attending secondary care clinics with National Institute for Health and Clinical Excellence (NICE)-defined CFS/ME (N=218) will be randomly allocated to specialist medical care (SMC) or SMC plus GES while on a waiting list for therapist-delivered rehabilitation. GES will consist of a structured booklet describing a 6-step graded exercise program, supported by up to 4 face-to-face/telephone/Skype™ consultations with a GES-trained physiotherapist (no more than 90 minutes in total) over 8 weeks. The primary outcomes at 12-weeks after randomization will be physical function (SF-36 physical functioning subscale) and fatigue (Chalder Fatigue Questionnaire). Secondary outcomes will include healthcare costs, adverse outcomes, and self-rated global impression change scores. We will follow up all participants until 1 year after randomization. We will also undertake qualitative interviews of a sample of participants who received GES, looking at perceptions and experiences of those who improved and worsened. Results: The project was funded in 2011 and enrolment was completed in December 2014, with follow-up completed in March 2016. Data analysis is currently underway and the first results are expected to be submitted soon. Conclusions: This study will indicate whether adding GES to SMC will benefit patients who often spend many months waiting for rehabilitative therapy with little or no improvement being made during that time. The study will indicate whether this type of guided self-management is cost-effective and safe. If this trial shows GES to be acceptable, safe, and comparatively effective, the GES booklet could be made available on the Internet as a practitioner and therapist resource for clinics to recommend, with the caveat that patients also be supported with guidance from a trained physiotherapist. The pragmatic approach in this trial means that GES findings will be generalizable to usual National Health Service (NHS) practice.

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The strained relationship between pedagogy and self-cultivation is often overlooked in favour of more pressing and profitable concerns within educational institutions. However, the end of education is not a well-paying job. It is often thought that education will produce a certain type of learned individual. Students are entered into educational institutions from a very young age and spend most of their youth within them, subsequently forming a part of themselves, their self-identify and agency, through these institutions. A significant amount of trust is placed in the hands of educators not only to impart information about various subject matters but to teach students how to think. This, however, is a difficult task which cannot be completely accomplished; thinking is a skill which an educator can promote but only the individual can cultivate. If self-cultivation is not the end of pedagogical practice and education, there is something deeply contradictory between the theoretical and practical values and aims of educational institutions.This thesis will address the problems caused by the neglect of self-cultivation within the pedagogical practices of contemporary educational institutions. I argue that self-cultivation, existential learning and flourishing should be the focus of these institutions. Educational institutions can make alternative efforts not only to improve the learning environment for these students but to prepare them to cope with existential questions. By acknowledging and focusing on the significance of self-cultivation, educational institutions can and should make efforts not only to teach useful, marketable skills and information but to also nurture the agency and mental well-being of the student him- or herself. My hope is that this thesis will be the first step towards answering a larger concern: How can educational institutions alleviate the struggles of students, particularly the seemingly growing number who are suffering from depression, by appealing to notions of self-cultivation?