5,716 research outputs found
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Methodology for Analyzing the Technical Potential for Energy Performance in the U.S. Commercial Buildings Sector with Detailed Energy Modeling: Preprint
This paper summarizes a methodology for developing quantitative answers to the question, ''How low can energy use go within the commercial buildings sector''? The basic process is to take each building in the 1999 CBECS public use data files and create a baseline building energy model for it as if it were being built new in 2005 with code-minimum energy performance
Light particle spectra from 35 MeV/nucleon 12C-induced reactions on 197Au
Energy spectra for p, d, t, 3He, 4He, and 6He from the reaction 12C+197Au at 35 MeV/nucleon are presented. A common intermediate rapidity source is identified using a moving source fit to the spectra that yields cross sections which are compared to analogous data at other bombarding energies and to several different models. The excitation function of the composite to proton ratios is compared with quantum statistical, hydrodynamic, and thermal models
Evidence that high von Willebrand factor and low ADAMTS-13 levels independently increase the risk of a non-fatal heart attack
Background: A disintegrin and metalloproteinase with a thrombospondin type 1 motif, member 13 (ADAMTS-13) may influence von Willebrand factor (VWF) levels and consequently the risk of myocardial infarction (MI). Moreover, ADAMTS-13 influences hemostatic plug formation in mouse models. We therefore studied their associations in the Glasgow MI Study (GLAMIS). Methods and results: We measured ADAMTS-13 and VWF antigen levels by ELISAs in stored plasma from a case–control study of 466 MI cases and 484 age- and sex-matched controls from the same north Glasgow population. There was no correlation between ADAMTS-13 and VWF levels in cases or controls. ADAMTS-13 levels correlated positively with serum cholesterol and triglycerides and body mass index, and negatively with high-density lipoprotein-cholesterol. VWF levels correlated with age, fibrinogen and C-reactive protein. In multivariable analyses including risk factors, VWF correlated positively with risk of MI, and ADAMTS-13 correlated negatively with risk of MI. These associations were independent of each other. The association of ADAMTS-13 with risk of MI was observed only in multivariable analysis. Conclusions: VWF and ADAMTS-13 levels were not associated in this study, and showed associations with MI risk in opposite directions but of similar strength. The association of ADAMTS-13 with MI is influenced by lipid levels, and consequently requires further investigation
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Does it matter which weather data you use in energy simulations?
Users of energy simulation programs often have a variety of weather data from which to choose--from locally recorded, measured weather data to preselected typical years--a bewildering range of options. In the last two years, several organizations have developed several new typical weather data sets including WYEC2, TMY2, CWEC, and CTZ2. Unfortunately, neither how these new data influence energy simulation results nor how they compare to existing typical data sets or actual weather data is well documented. In this paper, the authors present results from the DOE-2.1E hourly energy simulation program for a prototype office building as influenced by local measured weather data for multiple years and several weather data sets for a set of North American locations. They compare the influence of the various weather data sets on simulated annual energy use and energy costs. Statistics for temperature, solar radiation, and heating and cooling degree days for the different locations and data sets are also presented. Where possible, they explain the variation relative to the different designs used in developing each data set. They also show the variation inherent in actual weather data and how it influences simulation results. Finally, based on these results, they answer the question--does it really matter which weather data you use
Highly-Parallel, Highly-Compact Computing Structures Implemented in Nanotechnology
In this paper, we describe work in which we are evaluating how the evolving properties of nano-electronic devices could best be utilized in highly parallel computing structures. Because of their combination of high performance, low power, and extreme compactness, such structures would have obvious applications in spaceborne environments, both for general mission control and for on-board data analysis. However, the anticipated properties of nano-devices mean that the optimum architecture for such systems is by no means certain. Candidates include single instruction multiple datastream (SIMD) arrays, neural networks, and multiple instruction multiple datastream (MIMD) assemblies
Deep Hole States in Two Particle Transfer Reactions
This work was supported by National Science Foundation Grants PHY 76-84033A01, PHY 78-22774, and Indiana Universit
Alexithymia in autism: cross-sectional and longitudinal associations with social-communication difficulties, anxiety and depression symptoms
Background: Alexithymia (difficulties identifying and describing emotion) is a transdiagnostic trait implicated in social-emotional and mental health problems in the general population. Many autistic individuals experience significant social-communication difficulties and elevated anxiety/ depression and alexithymia. Nevertheless, the role of alexithymia in explaining individual variability in the quality/ severity of social-communication difficulties and/ or anxiety and depression symptoms in autism remains poorly understood.
Methods: 337 adolescents and adults (autism N=179) were assessed for alexithymia on the Toronto Alexithymia Scale and for social-communication difficulties, anxiety and depression symptoms. 135 individuals (autism N=76) were followed up 12-24-months later. We used regression models to establish cross-sectional and longitudinal associations between alexithymia, social-communication difficulties, anxiety and depression symptoms.
Results: Autistic individuals reported significantly higher alexithymia than comparison individuals (p<0.001, r effect size=0.48), with 47.3% of autistic females and 21.0% of autistic males meeting cut-off for clinically relevant alexithymia (score ≥61). Difficulties describing feelings were particularly associated with current self-reported social-communication difficulties (p<0.001, β=0.57, 95% CI [0.44, 0.67]) and predicted later social-communication difficulties (p=0.02, β=0.43, 95% CI [0.07, 0.82]). Difficulties identifying feelings were particularly associated with current anxiety symptom severity (p<0.001, β=0.54, 95% CI [0.41, 0.77]) and predicted later anxiety (p=0.01; β=0.31, 95% CI [0.08, 0.62]).
Conclusions: Our findings suggest that difficulties identifying vs. describing emotion are associated with differential clinical outcomes in autism. Psychological therapies targeting emotional awareness may improve social-communication and anxiety symptoms in autism, potentially conferring long-term benefits
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Energy Design Plugin: An EnergyPlus Plugin for SketchUp; Preprint
This paper describes the Energy Design Plugin, a new software plugin that aims to integrate simulation as a tool during the earliest phases of the design process. The plugin couples the EnergyPlus whole-building simulation engine to the Google SketchUp drawing program
Estimating the functional form for the density dependence from life history data
Two contrasting approaches to the analysis of population dynamics are currently popular: demographic approaches where the associations between demographic rates and statistics summarizing the population dynamics are identified; and time series approaches where the associations between population dynamics, population density, and environmental covariates are investigated. In this paper, we develop an approach to combine these methods and apply it to detailed data from Soay sheep (Ovis aries). We examine how density dependence and climate contribute to fluctuations in population size via age- and sex-specific demographic rates, and how fluctuations in demographic structure influence population dynamics. Density dependence contributes most, followed by climatic variation, age structure fluctuations and interactions between density and climate. We then simplify the density-dependent, stochastic, age-structured demographic model and derive a new phenomenological time series which captures the dynamics better than previously selected functions. The simple method we develop has potential to provide substantial insight into the relative contributions of population and individual-level processes to the dynamics of populations in stochastic environments
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