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858 results for “Energy Data”
NARSTO EPA Supersite (SS) Houston, Texas Air Quality Study 2000 (TexAQS2000) Department of Energy (DOE) G-1 Air Chemistry, Aerosol, and Met Data
NARSTO_EPA_SS_HOUSTON_TEXAQS2000_DOE_G-1_DATA is North American Research Strategy for Tropospheric Ozone (NARSTO) Environmental Protection Agency (EPA) Supersite (SS) Houston, Texas Air Quality Study 2000 (TexAQS2000) Department of Energy (DOE) G-1 Air Chemistry, Aerosol, and Met Data. Twenty research flights were made from August 18 to September 12, 2000.The Houston Supersite is one of several Supersites that was established in urban areas within the United States by the U.S. Environmental Protection Agency (EPA) to better understand the measurement, sources, and health effects of suspended particulate matter (PM). The overall goals were to characterize the composition and identify the sources of particulate matter in Southeastern Texas, to develop and test new methods for characterizing fine particulate matter, and to collect data on the physical and chemical characterization of fine particulate matter that can be used to support exposure and health effects studies.NARSTO, which has since disbanded, was a public/private partnership, whose membership spanned across government, utilities, industry, and academe throughout Mexico, the United States, and Canada. The primary mission was to coordinate and enhance policy-relevant scientific research and assessment of tropospheric pollution behavior; activities provide input for science-based decision-making and determination of workable, efficient, and effective strategies for local and regional air-pollution management. Data products from local, regional, and international monitoring and research programs are still available.
CERES Energy Balanced and Filled (EBAF) TOA and Surface Monthly means data in netCDF Edition 4.1
CERES_EBAF_Edition4.1 is the Clouds and the Earth's Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) and surface monthly means data in netCDF format Edition 4.1 data product. Data was collected using the CERES Scanner instruments on both the Terra and Aqua platforms. Data collection for this product is ongoing.CERES_EBAF_Edition4.1 data are monthly and climatological averages of TOA clear-sky (spatially complete) fluxes and all-sky fluxes, where the TOA net flux is constrained to the ocean heat storage. It also provides computed monthly mean surface radiative fluxes consistent with the CERES EBAF-TOA product and some basic cloud properties derived from MODIS. Cloud Radiative Effects are provided at both the TOA and surface as determined using a cloud-free profile in the Fu-Liou Radiative Transfer Model (RTM). Observed fluxes are obtained using cloud properties derived from narrow-band imagers onboard both EOS Terra and Aqua satellites, as well as geostationary satellites, to fully model the diurnal cycle of clouds. The computations are also based on meteorological assimilation data from the Goddard Earth Observing System (GEOS) Versions 5.4.1 models. Unlike other CERES Level 3 clear-sky regional data sets that contain clear-sky data gaps, the clear-sky fluxes in the EBAF-TOA product are regionally complete. The EBAF-TOA product is the CERES project's best estimate of the fluxes based on all available satellite platforms and input data. CERES is a key Earth Observing System (EOS) program component. The CERES instruments provide radiometric measurements of the Earth's atmosphere from three broadband channels. The CERES missions follow the successful Earth Radiation Budget Experiment (ERBE) mission. The first CERES instrument, the proto flight model (PFM), was launched on November 27, 1997, as part of the Tropical Rainfall Measuring Mission (TRMM). Two CERES instruments (FM1 and FM2) were launched into polar orbit on board the Earth Observing System (EOS) flagship Terra on December 18, 1999. Two additional CERES instruments (FM3 and FM4) were launched on board Earth Observing System (EOS) Aqua on May 4, 2002. The CERES FM5 instrument was launched on board the Suomi National Polar-orbiting Partnership (NPP) satellite on October 28, 2011. The newest CERES instrument (FM6) was launched on board the Joint Polar-Orbiting Satellite System 1 (JPSS-1) satellite, now called NOAA-20, on November 18, 2017.
Data for "Reducing operational costs of offshore HVDC energy export systems through optimized maintenance"
<p>The files in this record contain the scripts, input data and results for the maintenance model described in the above publication (will be added later).</p> <p>To use the scripts, you need the software MATLAB (min. version 2016b).</p> <p>Steps to run the model:</p> <p>1. run "ini.m"</p> <p>2. run "szenarien_~"</p> <p>3. save the results in the directory "Ergebnisse"</p> <p>4. run scripts located in the directory "Auswertungen"</p>
Supplementary data to 'Do beach profiles under non-breaking waves minimize energy dissipation?'
<p>This repository contains the following files:</p> <p>1. 'data_for_tables.xlsx' summarises the results of using the codes in doi:10.5281/zenodo.3725621 for all profiles considered in this associated paper. These data feed into the tables of the paper. Additional notes can be found in the spreadsheet.</p> <p>2. Three files with extension *.sfit are sessions for the 'cftool' toolbox of Matlab (version 2017b) that give the results of the best-fits to the measured profiles.</p>
Data set for "Determining the minimum energy requirement of an LNG process: New insights into the impact of the vapour liquid equilibrium"
<p>Accompanying information for Xuan et al, 2020, "Determining the minimum energy requirement of an LNG process: New insights into the impact of the vapour liquid equilibrium", Energy, Paper number 117785, <a href="https://doi.org/10.1016/j.energy.2020.117785">https://doi.org/10.1016/j.energy.2020.117785</a></p>
Data from: Transcutaneous ultrasound energy harvesting using capacitive triboelectric technology
A major challenge for implantable medical systems is the inclusion or reliable delivery of electrical power. We use ultrasound to deliver mechanical energy through skin and liquids, and demonstrate a thin implantable vibrating triboelectric generator able to effectively harvest it. The ultrasound can induce the micrometer scale displacement of a polymer thin membrane to generate electrical energy through contact electrification. We recharge a Li-ion battery at a rate of 166 μC/s in water. The voltage and current generated ex-vivo by ultrasound-energy transfer reached 2.4 V and 156 µA under porcine tissue. It shows that capacitive triboelectric electret is the first technology able to compete with piezoelectricity to harvest ultrasound in-vivo and power medical implants.
Resource and Load Compatibility Assessment of Wind Energy Offshore of Humboldt County, California: Data and Software
<p>These files contain the raw data and code used to analyzed wind resource and local load compatibility of offshore wind in Humboldt, California.</p>
Supplementary data: "Early decarbonisation of the European energy system pays off"
<p>This repository includes input data to run the model <a href="https://github.com/martavp/pypsa-eur-sec-30-path">PyPSA-Eur-Sec-30-paths</a> and the results discussed in the paper "<a href="https://arxiv.org/abs/2004.11009">Early decarbonisation of the European energy system pays off</a>"</p> <p>The code to run the model can be found in the Github repository <a href="https://github.com/martavp/pypsa-eur-sec-30-path">PyPSA-Eur-Sec-30-paths</a> and the permanent repository <a href="https://zenodo.org/record/4014807#.X1IKRYtS-Uk">10.5281/zenodo.4014807</a></p> <p>The directory 'data/' includes all the datasets needed to run the model.</p> <p>The directories 'version-*/' include the network objects obtained as an outcome of the optimization in the different scenarios.</p> <p>The directory 'summaries/' includes summaries with the most relevant aggregated results.</p> <p>All input data (in the directory 'data/') and results (in the directories 'version-*/' and 'summaries/') are released under the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International Licence</a> (CC BY 4.0), except those where explicit sources and licences are mentioned in the data folders.</p> <p> </p>
Data of "Accuracy of predicting chemical body composition of growing pigs by dual-energy X-ray absorptiometry"
<p>Data set for article "Accuracy of predicting chemical body composition of growing pigs by dual-energy X-ray absorptiometry" (DOI). Data set of Swiss Large White entire male pigs for nutrient composition (water, lipid, N, ash, Ca and P) determined by wet-chemistry and body composition (lean mass, body mineral content and fat tissue mass) by dual-energy X-ray absorptiometry (DXA) in the empty body of live pigs and (N=61) in pig carcasses (N=68) within a body weight range from 20 to 100 kg.</p> <p><strong>metadata.xlsx</strong>: description of variables in the data sets</p> <p><strong>emptybody.txt</strong>: corresponds to contents of the empty body at slaughter (three days after DXA live scans) and DXA live scans</p> <p><strong>Carcass.txt</strong>: corresponds to carcass contents and DXA carcass scans on the day of slaughter</p> <p> </p>
Data from: Energy landscape for the insertion of amphiphilic nanoparticles into lipid membranes: a computational study
Amphiphilic, monolayer-protected gold nanoparticles (NPs) have been shown to enter cells via a non-endocytic, non-disruptive pathway that could be valuable for biomedical applications. The same NPs were also found to insert into a series of model cell membranes as a precursor to cellular uptake, but the insertion mechanism remains unclear. Previous simulations have demonstrated that an amphiphilic NP can insert into a single leaflet of a planar lipid bilayer, but in this configuration all charged end groups are localized to one side of the bilayer and it is unknown if further insertion is thermodynamically favorable. Here, we use atomistic molecular dynamics simulations to show that an amphiphilic NP can reach the bilayer midplane non-disruptively if charged ligands iteratively ``flip'' across the bilayer. Ligand flipping is a favorable process that relaxes bilayer curvature, decreases the nonpolar solvent-accessible surface area of the NP monolayer, and increases attractive ligand-lipid electrostatic interactions. Analysis of end group hydration further indicates that iterative ligand flipping can occur on experimentally relevant timescales. Supported by these results, we present a complete energy landscape for the non-disruptive insertion of amphiphilic NPs into lipid bilayers. These findings will help guide the design of NPs to enhance bilayer insertion and non-endocytic cellular uptake, and also provide physical insight into a possible pathway for the translocation of charged biomacromolecules.
Data from: Re-assessing causality between energy consumption and economic growth
The energy consumption-growth nexus has been widely studied in the empirical literature, though results have been inconclusive regarding the direction, or even the existence, of causality. These inconsistent results can be explained by two important limitations of the literature. First, the use of bivariate models, which fail to detect more complex causal relations, or the ad hoc approach to selecting variables in a multivariate framework; and, second, the use of linear causal models, which are unable to capture more complex nonlinear causal relationships. In this paper, we aim to overcome both limitations by analysing the energy consumption-growth nexus using a Flexible Fourier form due to [1] The analysis focuses on the US over the period 1949 to 2014. From our results we can conclude that, where the linear methodology supports the neutrality hypothesis (no causality between energy consumption and growth), the Flexible Fourier form points to the existence of causality from energy consumption to growth. This is contrary to the linear analysis, suggesting that lowering energy consumption would adversely affect US economic growth. Thus, by employing the Flexible Fourier form we find the conclusions can be quite different.
Measured wave, eddy-covariance and energy budget data
<p>Measurement data of wave, eddy-covariance and energy budget in Lake Balaton, Hungary</p> <p>May - Oct 2019</p>
Data for "Microphysics of early dark energy"
<p>Data to reproduce figures in "Microphysics of early dark energy" (arXiv: 2202.08291). For questions please contact Vivian I. Sabla. </p>
Data for "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" (Subset 3)
<p>This is dataset of ocean wave simulations used in the paper "The 20-year highest tropical cyclone-generated waves associated with the maximum energy of seismic noises" by Shimura et al. (submitted).</p> <p>The dataset contains </p> <ul> <li>significant wave height (Subset 1),</li> <li>wave induced surface pressure (Subset 2)</li> <li>long-period componet of wave heights (Subset 3)</li> <li>long-period component of surface pressure (Subset 4)</li> </ul> <p>during 2004 from 2023 summer. </p>
Data and software for "Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument"
<p>Supplementary material to the DESI publication "Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument".</p> <p>The main "turbfigures.py" script generates the figures in the paper from the included data files.</p> <p>Contents:</p> <p><strong>Software files</strong></p> <ul> <li>turbfigures.py: Turbulence plotting and analysis plotting routines.</li> <li>turbulence.py: Analysis routines called by turbfigures.py. The live version of this code in production for desi is in the desimeter package (https://github.com/desihub/desimeter/blob/main/py/desimeter/turbulence.py)</li> </ul> <p><strong>Data files</strong></p> <ul> <li>coord-summary-20240124-pm.fits <ul> <li>Measured centroids of fibers in for 400 consecutive images of the focal plane while at zenith. File contains the following columns: <ul> <li>expid - exposure ID</li> <li>location - "location" of fiber in focal plane; ranges from 0 - 10000. Fibers on petal 0 have numbers between 0 and 1000, etc. There are only 500 positioners per petal, so most locations are not populated.</li> <li>move - in real data, this indexes over the moves in a DESI positioning loop; garbage information here.</li> <li>fpa_{x,y} - measured position of the fiber in this exposure</li> <li>req_{x,y} - requested position of the fiber in this exposure; not used for this data set where positioners are fixed in location</li> <li>{x,y}turb - empty in this file; gets filled in by turbfigures.py with measured turbulence</li> <li>flags_cor - flags indicating that a positioner or fiber may be problematic</li> <li>postype - flags indicating that a location corresponds to a real positioner vs. a fiducial</li> <li>expected_{x,y} - empty in this file; gets filled in by turbfigures.py with "expected" positions of each fiber, so that fpa_{x,y} - expected_{x,y} is a noisy estimate of the turbulence seen by the fiber.</li> </ul> </li> <li>Note that this file has an awkward structure. It has 10000 rows, one for each possible location. Most fields are then 400 element arrays that gives the corresponding values, corresponding to the 400 exposures present in the file.</li> </ul> </li> <li>coordinates-stats.ecsv <ul> <li>statistics of positioning accuracy and turbulence amplitude in DESI positioning loops. Measured RMSes are the 5-sigma clipped root-mean-square positioning offset in 2D: sqrt(mean(dx^2 + dy^2)). Measured medians are median(sqrt(dx^2 + dy^2)).</li> <li>Contents: <ul> <li>coord_filename - file name of DESI coordinates file statistics were drawn from</li> <li>rms_turbulence - RMS for the turbulent contribution to the positioning error</li> <li>rms_positioning - RMS for positioning after removing turbulence</li> <li>rms_total - Total RMS</li> <li>med_turbulence - median turbulence in exposure</li> <li>med_positioning - median positioning error in exposure</li> <li>med_total - median total turbulence + positioning error in exposure</li> <li>expid - exposure id number</li> </ul> </li> </ul> </li> </ul> <p>Dependencies: The included software uses the DESI software stack and otherwise the usual python astronomy packages: numpy scipy matplotlib astropy. Alternatively, people with access to NERSC can load the default DESI environment and pull in all needed dependencies.</p>
(re)Use Indications of High Energy Physics related Research Data and Software in HEPData
<p>This dataset contains High Energy Physics related research data and software (re)use indications (formal citations, informal mentions) in scholarly works. All research data and software resources were identified and extracted from HEPData. The (re)use indications were identified by a mix of approaches: use of citation discovery services and multiple search approaches in Google Scholar. All identified research data and software (re)use indications were classified according to their purpose, location, and elements.</p> <p>The data was collected in 2018 for a PhD thesis on research data and software (re)use indications in scholarly works.</p>
Preliminary Assessment of Added Diagnostic Value of Dual Energy CT Images Using Data Acquired on a Spectral Detector CT
ClinicalTrials.gov study NCT02760706. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Dual Energy Cardiac CT Data Collection and Evaluation
ClinicalTrials.gov study NCT05171764. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Data from: Energy landscape for the insertion of amphiphilic nanoparticles into lipid membranes: a computational study
Open the record for dataset details and reuse information.
Data from: Re-assessing causality between energy consumption and economic growth
Open the record for dataset details and reuse information.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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