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858 results for “Energy Data”
Data from: Geographic origins and population genetics of bats killed at wind-energy facilities
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Data from: Global energy sector methane emissions estimated by using facility-level satellite observations
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Energy consumption and greenhouse gas emissions data of activated carbon production using different biomass
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Data from: Do the high energy lifestyles of shorebirds result in high maximal metabolic rates? - Basal and maximal metabolic rates in least and pectoral sandpipers during migration
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Data from: Resting and daily energy expenditures during reproduction are adjusted in opposite directions in free-living birds
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Data from: Is biodiversity energy-limited or unbounded? A test in fossil and modern bivalves
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Data for: Hunting behavior of a solitary sailfish Istiophorus platypterus and estimated energy gain after prey capture
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Data from: Individual variation in energy-saving heterothermy affects survival and reproductive success
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Data for: Low predictability of energy balance traits and leaf temperature metrics in desert, montane, and alpine plant communities
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Code and data used in "Health co-benefits of sub-national renewable energy policy in the US"
<p>Archive of modeling, inputs, and results.</p>
Data: The effects of general fatigue induced by incremental exercise test and active recovery modes on energy cost, gait variability and stability in male soccer players
<p>Data, code, and movies for Mahaki et al. (2020); The effects of general fatigue induced by incremental exercise test and active recovery modes on energy cost, gait variability and stability in male soccer players. Published in The Journal of Biomechanics (<a href="https://doi.org/10.1016/j.jbiomech.2020.109823">https://doi.org/10.1016/j.jbiomech.2020.109823</a>).</p> <p><strong>Gas data</strong> - contains all Oxygen data plus a script to run the data.</p> <p> - Subjectxx - folder with oxygen data.</p> <p> - GasdataMohammad [type of file: MATLAB code (.m)] - script to analyze the oxygen data. The outcomes have been saved as RestECnet, PWSECnet, and IVTECnet [type of files: MATLAB data (.mat)].</p> <p> - EC_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of energetic cost, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery) and to show the outcome in boxplot together with individual data points (The results have been presented in <strong>Fig 2.</strong>)</p> <p> </p> <p><strong>Kinematic Data</strong> - contains all Kinematic data plus scripts to run the data:</p> <p> - Subjectxx - folder with kinematics data.</p> <p> - Rest_VAR [type of file: MATLAB code (.m)] - script to analyze the kinematics data in the Rest recovery session. The outcomes have been saved as RestVAR [type of file: MATLAB data (.mat)]. The corresponding plots, per subject & per trial, have been saved in the Plots folder.</p> <p> - PWS_VAR [type of file: MATLAB code (.m)] - script to analyze the kinematics data in the PWS recovery session. The outcomes have been saved as PWSVAR [type of file: MATLAB data (.mat)]. The corresponding plots, per subject & per trial, have been saved in the Plots folder.</p> <p> - IVT_VAR [type of file: MATLAB code (.m)] - script to analyze the kinematics data in the IVT recovery session. The outcomes have been saved as IVTVAR [type of file: MATLAB data (.mat)]. The corresponding plots, per subject & per trial, have been saved in the Plots folder.</p> <p> - VAR_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability (VAR sagittal, frontal, and horizontal) and to show the outcome in boxplot together with individual data points (The results have been presented in <strong>Fig 3.</strong>).</p> <p> - VAR_Sagittal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability in sagittal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - VAR_Frontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability in frontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - VAR_Horizontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait variability in horizontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - normalizetimebase [type of file: MATLAB code (.m)] – function to normalize VAR from 0 to 100% of the gait cycle.</p> <p> - VAR_Sagittal [type of file: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait variability in sagittal plane. Imported data have been saved as VAR_Sagittal [type of file: Excell file (.csv)].</p> <p> - VAR_Frontal [type of file: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait variability in frontal plane. Imported data have been saved as VAR_Frontal [type of file: Excell files (.csv)].</p> <p> - VAR_Horizontal [type of file: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait variability in horizontal plane. Imported data have been saved as VAR_Horizontal [type of file: Excell file (.csv)].</p> <p> + Trunk Stability - folder includes all outcomes and codes in terms of gait stability:</p> <p> -Thoracic [type of file: Excell file (.xlsx)] - general file includes all outcomes in terms of gait stability.</p> <p> - LDS_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait stability (λ sagittal, λ frontal, and λ horizontal) and to show the outcome in boxplot together with individual data points (The results have been presented in <strong>Fig 5.</strong>).</p> <p> - LDS_Sagittal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses inn terms of gait stability in sagittal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - LDS_Frontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait stability in frontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - LDS_Horizontal_Stat_boxplot [type of file: MATLAB code (.m)] - script to statistically test the hypotheses in terms of gait stability in horizontal plane, to calculate the effect sizes of main effects of Time, Recovery and Interaction effect (Time vs Recovery), and to show the outcome in boxplot together with individual data points.</p> <p> - Rest_LDS_Sagittal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the Rest recovery session and in the sagittal plane.</p> <p> - Rest_LDS_Frontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the Rest recovery session and in the frontal plane.</p> <p> - Rest_LDS_Horizontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the Rest recovery session and in the horizontal plane.</p> <p> - PWS_LDS_Sagittal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the PWS recovery session and in the sagittal plane.</p> <p> - PWS_LDS_Frontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the PWS recovery session and in the frontal plane.</p> <p> - PWS_LDS_Horizontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the PWS recovery session and in the horizontal plane.</p> <p> - IVT_LDS_Sagittal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the IVT recovery session and in the sagittal plane.</p> <p> - IVT_LDS_Frontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the IVT recovery session and in the frontal plane.</p> <p> - IVT_LDS_Horizontal [type of file: Excell file (.xlsx)] - file includes LDS outcomes in the IVT recovery session and in the horizontal plane.</p> <p> - LDS_sagittal [type of files: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait stability in sagittal plane. Imported data have been saved as LDS_sagittal [type of file: Excell file (.csv)].</p> <p> - LDS_frontal [type of files: JASP/Jamovie files (.jasp/.omv)] - file to statistically test gait stability in frontal plane. Imported data have been saved as LDS_frontal [type of file: Excell file (.csv)].</p> <p> - LDS_horizontal [type of files: JASP/Jamovie file (.jasp/.omv)] - file to statistically test gait stability in horizontal plane. Imported data have been saved as LDS_horizontal [type of file: Excell file (.csv)].</p> <p> </p> <p><strong>Movies</strong> –contains some movies [type of files: .mp4] to show the Noraxon calibration, IMUs placement on body segments, fatigue protocol, walking at PWS, and resting metabolic cost measurement.</p> <p> </p> <p><strong>The characteristics of participants</strong> [type of file: Excell file (.xlsx)] – file includes 4 sheets:</p> <p> - Sheet 1 includes height (cm), weight (kg), age (year), BMI, and body fat percentage of each participant.</p> <p> - Sheets 2-4 include the physiological parameters of each participant during IVT, PWS, and Rest recovery modes. The physiological parameters such as Vo2, Vo2max, HR, and RER of each participant have been reported during rest (i.e. sitting position) and incremental exercise test.</p> <p> </p>
Data archive for paper "WRF‐TEB: Implementation and Evaluation of the Coupled Weather Research and Forecasting (WRF) and Town Energy Balance (TEB) Model"
<p><strong>WRF-TEB data archive</strong></p> <p>This archive contains data and tools to reproduce results as included in <a href="https://doi.org/10.1029/2019ms001961">Meyer et al. (2020)</a>.</p> <p><strong>Prerequisites</strong></p> <ul> <li><a href="https://sylabs.io/">Singularity</a> version >= 3.</li> </ul> <p><strong>Usage</strong></p> <p>To run all models and plotting scripts included in integration test and meteorological evaluation, run the following command from your command-line interface.</p> <pre><code>NPROC=8 TYPE=evaluate tools/singularity/run.sh</code></pre> <p>where <code>NPROC=8</code> is the maximum number of processes to use. The output can be found in the <code>work/</code> folder.</p> <p><strong>HPC</strong></p> <p>If you want to use this in an HPC environment, use <code>tools/hpc</code> as a template. As an example, to run the evaluation on Imperial HPC using PBS (Portable Batch System), use:</p> <pre><code>qsub -v REPO_ROOT=$(pwd),TYPE=evaluate tools/hpc/job_imperial.sh</code></pre> <p><strong>Copyright and License</strong></p> <p>Copyright and licensing information are included at the top of source files or as separate files in folders.</p> <p><strong>References</strong></p> <p>Meyer, D., Schoetter, R., Riechert, M., Verrelle, A., Tewari, M., Dudhia, J., Masson, V., Reeuwijk, M., & Grimmond, S. (2020). WRF‐TEB: implementation and evaluation of the coupled Weather Research and Forecasting (WRF) and Town Energy Balance (TEB) model. Journal of Advances in Modeling Earth Systems. <a href="https://doi.org/10.1029/2019ms001961">https://doi.org/10.1029/2019ms001961</a></p>
Data sets used in the manuscript titled "Ecosystem-level energy and water budgets are resilient to canopy mortality in sparse semi-arid biomes"
<p><span>This data set reports water and energy fluxes, soil water content and sap fluxes measured at two adjacent pinon-juniper woodlands in central New Mexico from January 2009 to December 2016. This data set was used for the analysis in the manuscript titled "Ecosystem-level energy and water budgets are resilient to canopy mortality in sparse semi-arid biomes" submitted to JGR-Biogeosciences. </span></p>
Supporting model data for paper: Measuring the impact of a new snow model using surface energy budget process relationships
<p>Supporting model data for paper: Measuring the impact of a new snow model using surface energy budget process relationships which has been submitted to the Journal of Advances in Modelling Earth Systems: https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020MS002144</p> <p>The experiment id h3hh corresponds to simulations with the ECMWF IFS with a single layer snow model. h3eg corresponds to the experimental 5-layer snow model.</p> <p>The timeseries are made by concatenating hourly data from day2 of forecasts initialised at 00UTC each day between Dec 1st 2013 and 1 June 2014.</p>
Data for Assessing the renewable energy policy paradox: a scenario analysis for the Italian electricity market
<p>This page contains the datasets and codes used to generate the figures for the article Assessing the renewable energy policy paradox: a scenario analysis for the Italian electricity market.</p> <p>Below you will find two datasets (.dta) and four codes (.do) files. Please note that the .do files contain the original paths to where the datasets were saved, you should change them to where they are saved in your computer. </p> <ol> <li>The file <em>clustering_prer_ok.do</em> uses dataset <em>yearlyvars_raw.dta</em> to generate three additional datasets <em>clusters.dta</em>, <em>yearly_scenarios.dta</em> and <em>xwalk.dta</em> <ul> <li><em>clusters.dta</em> is used in <em>Figs_2-5-6_ok.do</em></li> <li><em>yearly_scenarios.dta</em> is used in <em>Figs_3_ok.do</em></li> </ul> </li> <li>Dataset <em>hprice_raw.dta</em> is used together with the generated <em>xwalk.dta</em> in <em>Fig_4_ok.do</em>.</li> </ol>
Spatially anonymized data from: Novel step selection analyses on energy landscapes reveal how linear features alter migrations of soaring birds
<p>This dataset consists of spatially anonymized movement data as well as environmental covariate data to estimate energy landscape step selection selections for migratory golden eagles that summer in Alaska.</p> <ol> <li>Human modification of landscapes includes extensive addition of linear features, such as roads and transmission lines. These can alter animal movement and space use and affect the intensity of interactions among species, including predation and competition. Effects of linear features on animal movement have seen relatively little research in avian systems, despite ample evidence of their effects in mammalian systems and that some types of linear features, including both roads and transmission lines, are substantial sources of mortality.</li> <li>Here, we used satellite telemetry combined with step selection functions designed to explicitly incorporate the energy landscape (el‐SSFs) to investigate the effects of linear features and habitat on movements and space use of a large soaring bird, the golden eagle <em>Aquila chrysaetos</em>, during migration. Our sample consisted of 32 adult eagles tracked for 45 spring and 39 fall migrations from 2014 to 2017.</li> <li>Fitted el‐SSFs indicated eagles had a strong general preference for south‐facing slopes, where thermal uplift develops predictably, and that these areas are likely important aspects of migratory pathways. el‐SSFs also provided evidence that roads and railroads affected movement during both spring and fall migrations, but eagles selected areas near roads to a greater degree in spring compared to fall and at higher latitudes compared to lower latitudes. During spring, time spent near linear features often occurred during slower‐paced or stopover movements, perhaps in part to access carrion produced by vehicle collisions.</li> <li>Regardless of the behavioural mechanism of selection, use of these features could expose eagles and other soaring species to elevated risk via collision with vehicles and/or transmission lines. Linear features have previously been documented to affect the ecology of terrestrial species (e.g. large mammals) by modifying individuals' movement patterns; our work shows that these effects on movement extend to avian taxa.</li> </ol>
Metabolic rates and growth data for: Do small precocial birds enter torpor to conserve energy during development?
<p>Precocial birds hatch feathered and mobile, but when they become fully endothermic soon after hatching, their heat loss is high and they may become energy-depleted. These chicks could benefit from using energy-conserving torpor, which is characterised by controlled reductions of metabolism and body temperature (T<sub>b</sub>). We investigated at what age the precocial king quail <i>Cortunix chinensis</i> can defend a high T<sub>b</sub> under a mild thermal challenge and whether they can express torpor soon after achieving endothermy to overcome energetic and thermal challenges. Measurements of surface temperature (T<sub>s</sub>) using an infrared thermometer showed that king quail chicks are partially endothermic at 2-10 days, but can defend high T<sub>b</sub> at a body mass of ~13 g. Two chicks expressed shallow nocturnal torpor at 14 and 17 days for 4 to 5 hours with a reduction of metabolism by > 40% and another approached torpor threshold. Although chicks were able to rewarm endogenously from the first torpor bout, metabolism and T<sub>s</sub> decreased again by the end of the night, but they rewarmed passively when removed from the chamber. The total metabolic rate increased with body mass. All chicks measured showed a greater reduction of nocturnal metabolism than previously reported in quails. Our data show that shallow torpor can be expressed during the early postnatal phase of quails, when thermoregulatory efficiency is still developing, but heat loss is high. We suggest that torpor may be a common strategy for overcoming challenging conditions during the development in small precocial and not only altricial birds.</p>
Raw data on computational analysis the relationships of energy and mechanical properties with sensitivity for 1, 1-diamino-2, 2-dinitroethene based polymer bonded explosives
<p>The dataset provides raw data on key properties in the text as well as raw data on the temperature and energy balances of the P, P1, P2, P3 and P4 systems at room temperature. These data allow the results obtained in the article to be reproduced, while the reader can obtain the raw data for the plots not labeled with data in the article and thus quantify the exact magnitude of the changes shown in the plots. The main work of the article is: Molecular dynamics (MD) simulations have been applied to investigate 1, 1-diamino-2, 2-dinitroethene (FOX-7) crystal and FOX-7(011)-based polymer-bonded explosives (PBXs) with four typical polymers, polyethylene glycol (PEG), fluorine-polymer (F<sub>2603</sub>), ethylene-vinyl acetate copolymer (EVA) and ester urethane (ESTANE5703) under COMPASS force field. Binding energy (E<sub>bind</sub>), cohesive energy density (CED), initiation bond length distribution, radial distribution function, and isotropic mechanical properties of FOX-7 and its PBXs at different temperatures were reported for the first time, and the relationship between them and sensitivity. Using quantum chemistry, FOX-7 was optimized with the four polymers at the B3LYP/6-311++G(d,p) level, and the structure and RDG of the optimized composite system were analyzed.</p>
Data from: PCB126 inhibits the activation of AMPK-CREB signal transduction required for energy sensing in liver
3,3',4,4',5-pentachlorobiphenyl (PCB126), a dioxin-like PCB, elicits toxicity through a wide array of non-carcinogenic effects, including metabolic syndrome, wasting, and non-alcoholic fatty-liver disease (NAFLD). Previously, we reported decreases in the transcription of several enzymes involved in gluconeogenesis, before the early onset of lipid accumulation. Hence, this study was aimed at understanding the impact of resultant decreases gluconeogenic enzymes on growth, weight and metabolism in the liver, upon extended exposure. Male Sprague-Dawley rats (75-100 g), fed a defined AIN-93G diet, were injected (ip) with single dose of soy oil (5 ml/kg body weight; n=14) or PCB126 (5 µmol/kg; n=15), 28 d, prior euthanasia. A subset of rats from each group were fasted for 12h (vehicle (n=6) and PCB126 (n=4)). Rats only showed significant weight loss between days 14 and 28 (P<0.05) and some mortality (P=0.0413). As in our previous studies, the expression levels of enzymes involved in gluconeogenesis (Pepck-c, G6Pase, Sds, Pc and Ldh-A) and glycogenolysis (Pygl) were strongly downregulated. The decreased expression of these enzymes in PCB126 treated rats after a 12 h fast decreased hepatic glucose production from glycogen and gluconeogenic substrates, exacerbating the hypoglycemia. Additionally, PCB126 caused hepatic steatosis and decreased the expression of the transcription factor Pparα and its targets, necessary for fatty-acid oxidation. The observed metabolic disruption across multiple branches of fasting metabolism resulted from inhibition in the activation of enzyme AMPK and transcription factor CREB signaling, necessary for "sensing" energy-deprivation and the induction of enzymes that respond to the PCB126 triggered fuel crisis in liver.
Data from: Flexibility, variability and constraint in energy management strategies across vertebrate taxa revealed by long-term heart rate measurements
1) Animals are expected to be judicious in the use of the energy they gain due to the costs and limits associated with its intake. The management of energy expenditure (EE) exhibited by animals has previously been considered in terms of three patterns: the constrained, independent and performance patterns of energy management. These patterns can be interpreted by regressing daily EE against maintenance EE measured over extended periods. From the multiple studies on this topic, there is equivocal evidence about the existence of universal patterns in certain aspects of energy management. 2) The implicit assumption that animals exhibit specifically one of three discrete energy management patterns, and without variation, seems simplistic. We suggest that animals can exhibit gradations of different energy management patterns and that the exact pattern will fluctuate as their environmental context changes. 3) To investigate these ideas, and for possible large-scale patterns in energy management pattern, we analysed long-term heart rate data – a strong proxy for EE – across and within individuals in 16 species of birds, mammals, and fish. 4) Our analyses of 292 individuals representing 46 539 observation-days suggest that vertebrates typically exhibit predominantly the independent or performance energy patterns at the across-individual level, and that the pattern does not associate with taxonomic group. Within individuals, however, animals generally exhibit some degree of energy constraint. Together, these findings indicate that across diverse species, some individuals supply more energy to all aspects of their life than do others, however all individuals must trade-off deployment of their available energy between competing functions. This demonstrates that within-individual analyses are essential for interpretation of energy management patterns. 5) We also found that species do not necessarily exhibit a fixed energy management pattern but rather temporal variation in their energy management over the year. Animals' energy management exhibited stronger energy constraint during periods of higher EE, which typically coincided with clear and key life cycle events such as reproduction, suggesting an adaptive plasticity to respond to fluctuating energy demands.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.