893 resultados para computational materials science and simulation
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Land systems are the result of human interactions with the natural environment. Understanding the drivers, state, trends and impacts of different land systems on social and natural processes helps to reveal how changes in the land system affect the functioning of the socio-ecological system as a whole and the tradeoff these changes may represent. The Global Land Project has led advances by synthesizing land systems research across different scales and providing concepts to further understand the feedbacks between social-and environmental systems, between urban and rural environments and between distant world regions. Land system science has moved from a focus on observation of change and understanding the drivers of these changes to a focus on using this understanding to design sustainable transformations through stakeholder engagement and through the concept of land governance. As land use can be seen as the largest geo-engineering project in which mankind has engaged, land system science can act as a platform for integration of insights from different disciplines and for translation of knowledge into action.
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Calving of ice is a relatively new area of research in the still young field of glaciology. In the short time that calving has been studied, it has been mainly treated as an afterthought, with the predominant mode of thinking being that it will happen so to concern oneself with why is not important. Many studies dealt with observations of calving front positions over time vs. ice velocity in an attempt to quantify the calving rate as the difference between the two, while others have attempted to deduce some empirical relationship between calving rate and variables such as water depth or temperature. This study instead addresses the question of why, where, and when ice will first become crevassed, which is an obviously necessary condition for a later calving event to occur. Previous work examining the causes of calving used ideas put forth from a variety of fields, including civil engineering, materials science, and results from basic physics and mechanics. These theories are re-examined here and presented as part of a larger whole. Important results from the field of fracture mechanics are utilized frequently, and these results can be used as a predictor of ice behavior and intrinsic properties of ice, as well as properties like back stresses induced by local pinning points and resistive shears along glacial ice boundaries. A theory of fracture for a material experiencing creep is also presented with applications to ice shelves and crevasse penetration. Finally, a speculative theory regarding large scale iceberg formation is presented. It is meant mainly as an impetus to further discussion on the topic, with the hope that a model relating crevasse geometries to flow parameters can result in crevasse spacings that could produce the tabular icebergs which are so newsworthy. The primary focus of this thesis is to move away from the "after the fact" studies that are so common in calving research, and instead devote energy to determining what creates the conditions that drive the calving of ice in the first place.
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by Morris Lichtenstein
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Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^
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Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^
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The software PanXML is a tool to create XML files needed for DOI registration at the German National Library of Science and Technology (TIB). PanXML is distributed as freeware for the operating systems Microsoft Windows, Apple OS X and Linux. An XML file created by PanXML is based on the XSD file article-doi_v3.2.xsd. Further schemas may be added on request.