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3,186 results for “efficiency”
Dataset for: Modelling the filtration efficiency of a woven fabric: The role of multiple lengthscales
<p>This is data for: "Modelling the filtration efficiency of a woven fabric: The role of multiple lengthscales", on <a href="https://arxiv.org/abs/2110.02856">arXiv</a></p> <p>Files are (this is also in README file):</p> <p>1) FinalFused.tif : stack of slices taken with confocal at Bristol by Ioatzin Rios de Anda. This is the imaging data of the fabric used</p> <p>2) processDataTo3D_PAPER.py : Python code to analyse 1) to produce mask of fibre voxels needed for LB simulation, by Jake Wilkins</p> <p>3) LBregionstack.tiff : image stack for region in LB simulations</p> <p>4) masknx330ny280nz462_t10.txt : mask in right format to be read in to Palabos LB code to specify which voxels are fibre and so need bounce-back</p> <p>5) Ioatzin3D.cpp : C++ code for Palabos LB. NB need Palabos LB code: https://palabos.unige.ch/, should go in directory "~/palabos-v2.2.0/examples/Ioatzin/3D<br> ". Needs 4)</p> <p>6) make_pkl.py : converts output of LB code into Python pickled format for .py codes below.</p> <p>7) IoatzinDarcy_pkl.py : takes pickled output of LB code and computes Darcy k etc</p> <p>8) traj2_pkledge.py : computes trajectories of particles and so filtration efficiency, needs pickled output of LBC code and 9)</p> <p>9) lattice_params.yaml : parameter values for 7) and 8)</p> <p>10) eff_filter_edges.txt : filtration efficiencies computed by 8) WITH inertia</p> <p>11) eff_filter0Stokes.txt : filtration efficiencies computed by 8) WITHOUT inertia</p> <p>12) plot_filtration.py : plots 10) and 11)</p> <p>13) Final_render.mp4 : rotating animation showing region simulated by LB code, by Jake Wilkins</p> <p>14) alpha_ofz.txt : alpha - fraction of fibres voxels as function of z</p> <p>15) plot_justalpha.py : plots 14)</p> <p>16) vtk01.vti : flow field velocity field in vti format - as used by Paraview</p> <p>17) vel3D.pkl : flow field velocity field in Python's pkl format</p> <p>18) slice_heatmap.py : produces heatmap of velocities in xy slice through the flow field</p> <p>19) plot_sigma_streamlines.py : plots Sigma (curvature lengthscale) from 20), 21), 22), 23)</p> <p>20) stream4.txt: streamline for flow field</p> <p>21) stream5.txt: streamline for flow field</p> <p>22) stream6.txt: streamline for flow field</p> <p>23) stream7.txt: streamline for flow field</p> <p>24) plot_Stokes.py : plots Stokes number as function of particle diameter</p> <p>25) 0traj20.0_47.xyz : trajectory in format that Paraview can read</p> <p>26) intraj20.0_47.xyz : another trajectory</p> <p>27) streamlines_pkl.py : calculates streamlines, eg 20), 21), 22) and 23) </p> <p>28) this README file</p> <p>Abstract of that work:</p> <p>During the COVID-19 pandemic, many millions have worn masks made of woven fabric, to reduce the risk of transmission of COVID-19. Masks are essentially air filters worn on the face, that should filter out as many of the dangerous particles as possible. Here the dangerous particles are the droplets containing virus that are exhaled by an infected person. Woven fabric is unlike the material used in standard air filters. Woven fabric consists of fibres twisted together into yarns that are then woven into fabric. There are therefore two lengthscales: the diameters of: (i) the fibre and (ii) the yarn. Standard air filters have only (i). To understand how woven fabrics filter, we have used confocal microscopy to take three dimensional images of woven fabric. We then used the image to perform Lattice Boltzmann simulations of the air flow through fabric. With this flow field we calculated the filtration efficiency for particles around a micrometre in diameter. We find that for particles in this size range, filtration efficiency is low ($\sim 10\%$) but increases with increasing particle size. These efficiencies are comparable to measurements made for fabrics. The low efficiency is due to most of the air flow being channeled through relatively large (tens of micrometres across) inter-yarn pores. So we conclude that our sampled fabric is expected to filter poorly due to the hierarchical structure of woven fabrics.</p>
Environmental efficiency estimates for 127 Swiss acute care hospitals
<p>These are the estimates from our enviromental efficiency estimates using frontier analysis (Stochastic Frontier Analysis and Data Envelopment Analysis) for 127 Swiss acute care hospital in 2018.</p> <p>For further details please see our working paper: <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3939627">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3939627</a></p>
Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials
<p>Archive with data supporting the paper "Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials" and the related PhD thesis by B. Pampel</p>
Dataset for Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur)
<p>This file contains the R and C++ code used for simulating experiments, simulated fluctuation data, and the results of estimations used in the paper "Efficient, robust, and versatile fluctuation data analysis using MLE MUtation Rate calculator (mlemur)".</p>
Accurate and Efficient Estimation of Local Heritability using Summary Statistics and LD Matrix -- Demo datasets for the HEELS tutorials
<p>We introduced a new estimator for local heritability, "HEELS", which attains comparable statistical efficiency as the REML estimator (such as those produced by GCTA and BOLT-REML) but only requires summary-level statistics – Z-scores from marginal association tests and the empirical LD. Our method has been implemented into an open-source Python-based command line tool. </p> <p>The datasets released here can be downloaded to test the two main functions of our software package: 1) estimating local heritability; 2) computing the low-dimensional representation of the LD matrix. They are meant to accompany the HEELS tutorials we have posted onto the wiki pages of our github repository: https://github.com/huilisabrina/HEELS/wiki.</p> <p> </p>
Dataset for Charge collection efficiency, underlying recombination mechanisms, and the role of electrode distance of vented ionization chambers under ultra-high dose-per-pulse conditions
<p>Dataset for paper: Kranzer et al., <a href="https://www.sciencedirect.com/journal/physica-medica">Physica Medica</a> <a href="https://www.sciencedirect.com/journal/physica-medica/vol/104/suppl/C">Volume 104</a>, December 2022, Pages 10-17</p> <p><a href="https://doi.org/10.1016/j.ejmp.2022.10.021">https://doi.org/10.1016/j.ejmp.2022.10.021</a></p>
A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR: accompanying dataset
<p>Dataset containing surface temperature and surface mass balance datasets generated from the MAR regional climate model over Greenland over two test areas using statistical downscaling tools from 6 km to 100m. The abstract of the accompanying submitted paper follows: </p> <p> </p> <p>The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise and this contribution is projected to accelerate over next decades. A crucial tool for studying the evolution surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs) which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. The results obtained in the case of the SMB, assessed through the comparison of the modeled outputs with in-situ SMB measurements, show a considerable improvement in the case of the downscaled product with respect to the original, coarse output. In the case of the downscaled MAR product, the coefficient of determination (R<sup>2</sup>) increases from 0.868 for the original MAR output to 0.935 for the downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the intercept and from the value -235mm (original) to -57 mm (downscaled) in the case of the slope, considerably improving upon results previously published in the literature.</p>
Regulation of mature mRNA levels by RNA processing efficiency
<p>Data from the research paper "Regulation of mature mRNA levels by RNA processing efficiency" by Henfrey, C., Murphy, S., and Tellier, M.:</p> <p>-Highest expressed transcript annotation for protein-coding genes, gencode v38.</p> <p>-15 txt (BED) files for chromatin vs nucleoplasm enrichment gene sets: HeLa full gene sets, canonical protein only sets, chromatin RNA seq subsamples, mNET seq subsamples, Raji gene sets.</p> <p>-Proteomics data table</p> <p>-mRNA half-life table</p> <p>-Splicing efficiency for POINT-seq, ChrRNA-seq, NucRNA-seq table</p> <p>-Ser2-P mNET-seq readthrough index data table</p> <p>-Splicing efficiency for siLuc/siEX3 table (ChrRNA-seq, NucRNA-seq)</p> <p>-RMATs output tables for alternative splicing results (siEX3 vs siLuc)</p> <p>-Tables for TSS:TES quantifications (mNET-seq(CTD) vs log2FoldChange, chr/nuc/mnet siEX3 vs siLuc)</p>
Efficiency of the formation of acid-resistant Calcium-oxalate layers on limestone
<p><strong>Scientific background:</strong></p> <p>Carbonate-based stone monuments and buildings are susceptible to weathering in acidic environments. To combat surface corrosion and slow down material deterioration, protective coatings that inhibit calcite dissolution have been proposed. The efficiency and integrity of the coatings was studied by measuring sulfur distribution along the treated surface. Such experiment cannot be efficiently performed with standard SSD PIXE detectors due to high overlap between the strong Ca K x-ray escape peaks and S Kα. For that purpose, a new parallel-beam wavelength dispersive (PB-WDS) X-ray emission spectrometer at JSI have been used which achieves high energy resolution in the eV range and is able to measure S distribution on the surface of treated marble samples.</p> <p><strong>Measurements performed within TNA project:</strong></p> <p>The new PB-WDS X-ray emission spectrometer at J. Stefan Institute (Ljubljana, Slovenia) was used to map the presence of Sulphur on the surface of 13 marble samples treated with different coatings and after exposure to 2% sulfuric acid. Ge(111) crystal analyzer was used in the spectrometer to record the S Ka signal, the overall scan size was 5 × 5 mm<sup>2</sup>.</p> <p><strong>Data files:</strong></p> <p>We are sharing the files produced during measurements. The signal from the detector preamplifier was processed with the XIA DXP-XMAP digital pulse processor. The files are two main formats:</p> <ol> <li>Files containing mapping data. The spectrometer was set to the Bragg angle corresponding to the energy of the S Ka emission line. In a .zip folder, with 4 .mca files for every measured point (extension: _0-Si(Li) detector, _2- PB-WDS spectrometer)</li> <li>High energy resolution spectra recorded at selected points on the sample surface.</li> </ol> <p> </p> <p> </p> <table> <thead> <tr> <th> <p>#</p> </th> <th> <p>Filename</p> </th> <th> <p> </p> </th> </tr> </thead> <tbody> <tr> <td> <p>1</p> </td> <td> <p>VES_A1_5.zip</p> </td> <td> <p>Map of S on VES_A1_5 sample. Ge 111, 100X100 points, 50μm step, 4s/point</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>S_X80_Y85.zip</p> </td> <td> <p>Scan over S Ka and Kb peak on the surface of VES_A1_5 sample. Point position x = 80px, y = 85px</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>VES_A3_5.zip</p> </td> <td> <p>Map of S on VES_A3_5 sample. Ge 111, 100X100 points, 50μm step, 4s/point</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>S_X95_Y33.zip</p> </td> <td> <p>Scan over S Ka and Kb peak on the surface of VES_A3_5 sample. Point position x = 95px, y = 33px</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>VES_A1_12.zip</p> </td> <td> <p>Map of S on VES_A1_12 sample. Ge 111, 40x40 points, 125μm step, 5s/point</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>S_X3_Y3.zip</p> </td> <td> <p>Scan over S Ka and Kb peak on the surface of VES_A1_12 sample. Point position x = 3px, y = 3px. Z position optimized to maximum at this point</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>S_X20_Y20.zip</p> </td> <td> <p>Scan over S Ka and Kb peak on the surface of VES_A1_12 sample. Point position x = 20px, y = 20px. Z position optimized to maximum at this point</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>S_X35_Y20.zip</p> </td> <td> <p>Scan over S Ka and Kb peak on the surface of VES_A1_12 sample. Point position x = 35px, y = 20px. Z position optimized to maximum at this point</p> </td> </tr> <tr> <td> <p>9</p> </td> <td> <p>CAR_A1_12.zip</p> </td> <td> <p>Map of S on VES_A1_12 sample. Ge 111, 80x80 points, 65μm step, 4s/point</p> </td> </tr> <tr> <td> <p>10</p> </td> <td> <p>CAR_A1_12_back_side.txt</p> </td> <td> <p>Scan over S Ka and Kb peak on the back surface of CAR_A1_12 sample.</p> </td> </tr> <tr> <td> <p>11</p> </td> <td> <p>VES_A1_12_Washed.zip</p> </td> <td> <p>Sample washed under running water. 2250 eV - 2350 eV; stepsize = 1.00eV; 6s/point or 10s/point for back</p> </td> </tr> <tr> <td> <p>12</p> </td> <td> <p>VES_A2_12.zip</p> </td> <td> <p>Line map of S on VES_A2_12. 10x1 points, 1mm stepsize, 10s/point</p> </td> </tr> <tr> <td> <p>13</p> </td> <td> <p>CAR_A3_5.zip</p> </td> <td> <p>Line map of S on CAR_A3_5. 10x1 points, 1mm stepsize, 10s/point</p> </td> </tr> <tr> <td> <p>14</p> </td> <td> <p>CAR_A1_5.zip</p> </td> <td> <p>Line map of S on CAR_A1_5. 10x1 points, 1mm stepsize, 10s/point1</p> </td> </tr> <tr> <td> <p>15</p> </td> <td> <p>VES_A3_12.zip</p> </td> <td> <p>Line map of S on VES_A3_12. 10x1 points, 1mm stepsize, 10s/point + Map of S on VES_A3_12 sample. Ge 111, 50x25 points, 200μm step, 3s/point</p> </td> </tr> <tr> <td> <p>16</p> </td> <td> <p>VES_A2_5.zip</p> </td> <td> <p>Line map of S on VES_A2_5. 5x1 points, 1mm stepsize, 10s/point</p> </td> </tr> <tr> <td> <p>17</p> </td> <td> <p>CAR_A2_5.zip</p> </td> <td> <p>Line map of S on CAR_A2_5. 5x1 points, 1mm stepsize, 10s/point</p> </td> </tr> <tr> <td> <p>18</p> </td> <td> <p>CAR_A2_12.zip</p> </td> <td> <p>Line map of S on CAR_A2_12. 5x1 points, 1mm stepsize, 10s/point</p> </td> </tr> <tr> <td> <p>19</p> </td> <td> <p>CAR_A3_12.zip</p> </td> <td> <p>Line map of S on CAR_A3_12. 5x1 points, 1mm stepsize, 10s/point</p> </td> </tr> </tbody> </table> <p> </p>
Accompanying Dataset migr_asyappctzm for Efficient Analytical Queries on Semantic Web Data Cubes
<p>This dataset shows how the Eurostat data cube in the orginal publicatin is modelled in QB4OLAP.</p> <p>This data is based on statistical data about asylum applications to the European Union, provided by Eurostat on</p> <p><a href="http://ec.europa.eu/eurostat/web/products-datasets/-/migr_asyappctzm">http://ec.europa.eu/eurostat/web/products-datasets/-/migr_asyappctzm</a></p> <p>Further data has been integrated from: https://github.com/lorenae/qb4olap/tree/master/examples</p>
Dataset of scientific article "Variability in Arsenic Methylation Efficiency across Aerobic and Anaerobic Microorganisms"
<p>Dataset for journal paper entitled "Variability in Arsenic Methylation Efficiency across Aerobic and Anaerobic Microorganisms" (DOI: 10.1021/acs.est.0c03908).</p> <p><strong>Partial publication's abstract:</strong> "Microbially-mediated methylation of arsenic (As) plays an important role in the As biogeochemical cycle, particularly in rice paddy soils where methylated As, generated microbially, is translocated into rice grains. The presence of the arsenite (As(III)) methyltransferase gene (<em>arsM</em>) in soil microbes has been used as an indication of their capacity for As methylation. Here, we evaluate the ability of seven microorganisms encoding active ArsM enzymes to methylate As. Amongst those, only the aerobic species were efficient methylators. The anaerobic microorganisms presented high resistance to As exposure, presumably through their efficient As(III) efflux, but methylated As poorly. The only exception were methanogens, for which efficient As methylation was seemingly an artifact of membrane disruption."</p> <p>The files deposited include: the flow cytometry data and fluorescence microscopy pictures used to assess membrane disruption of the methanogen <em>Methanosarcina mazei</em>, for experimental details please refer to publication, and the supporting information of the publication. Files:</p> <ol> <li><strong>Figure 3_flowcytometry files.zip:</strong> flow cytometry measurements reported in Figure 3 of publication. Measurements were performed with a 5-laser LSRII SORP flow cytometer. SYBR Green I (SG) (Invitrogen) was excited by the Blue laser (488 nm) and detected using a 530/30 band pass filter. propidium iodide (PI) (Sigma) was excited by the YG laser (561 nm) and detected using a 610/20 band pass filter. 30’000 events per sample were analyzed into four populations (no fluorescence, SG, SG/PI, or PI). Cells could be assigned to the membrane-compromised population, based on the gating of double-stained and single-stained controls of glutaraldehyde- fixed and ethanol-permeabilized cells. Cytometric data were acquired and analyzed using BD TM FACSDiva software v. 8.0.1 (BD Biosciences, CA, USA). The files consist of the reports generated by BD TM FACSDiva software in .jpg format.</li> <li><strong>Figure S14_fluorescence microscopy files.zip:</strong> Fluorescence microscopy pictures in .lsm format of single-stained SG control (SG), single-stained PI control (PI), double-stained control (SG/PI), 16-days sample (16 days) and 20-day sample (20 days) of a <em>Methanosarcina mazei</em> culture grown with 10 μM As(III) as initial concentration. The pictures are published as Figure S14 of the publication. The pictures were taken using Zeiss LSM 700 in the upright configuration equipped with a Plan-Apochromat 63x/1.40 oil immersion objective. For more details please refer to supplementary information in publicaiton. Recommended software for .lsm format included in .zip file.</li> <li><strong>SI_tables_Viacava_et_al_for_publication:</strong> file in .xlsx format including the tables: Accession numbers for As(III)-efflux and ArsM proteins and genes; primers used in preparing mutants of <em>C. pasteurianum</em>; growth curves and growth rates values for all sampled cultures; relative abundance of flow-cytometry populations; ICP-MS settings for As analysis; primers for <em>arsM</em> gene amplifications; primers for RT-qPCR of <em>C. pasteurianum</em>; HPLC-ICP-MS spectrum values ; values of <em>arsM</em> and <em>acr3</em> expression in <em>C. pasteurianum</em> WT and <em>Δacr3</em>; and concentration of total soluble arsenic and soluble arsenic species in filtered medium from all sampled cultures.</li> <li><strong>SI_Viacava_et_al_for_publication:</strong> file in .pdf format including: <ol> <li>Materials and methods: total arsenic and arsenic speciation analysis; cloning the arsM genes and gene expression in <em>E. coli </em>AW3110 (DE3); growth conditions of <em>C. pasteurianum</em> H0D0R4, strain used for genetic modification; isolation of the <em>Δacr3</em> and <em>ΔpyrE::Δacr3</em> mutants; arsenic methylation by <em>C. pasteurianum Δacr3</em>; transcription of arsM in <em>C. pasteurianum</em> WT and <em>Δacr3</em>; and membrane-integrity assessment of <em>M. mazei</em> cells using flow cytometry.</li> <li>Figures: growth rate of each individual species; abiotic control growth curves; total soluble anaerobic bacterium culture; soluble arsenic species in filtered medium from anaerobic bacterial cultures grown with 50 μM As(III); soluble arsenic species in filtered medium and volatile arsenic species from an A. rosenii culture; soluble arsenic in filtered medium from <em>S. vietnamensis, M. mazei and M. acetivorans</em> cultures; soluble arsenic species in abiotic controls; spiked HPLC-ICP-MS spectra; growth and concentration of soluble arsenic species in ArsM-expressing <em>E. coli </em>AW3110 (DE3); fluorescence microscopy pictures of flow cytometry controls from the membrane-integrity assessment from a <em>M. mazei </em>culture grown with 50 μM As(III); expression of <em>arsM</em> and <em>acr3</em> in <em>C. pasteurianum</em> WT and <em>Δacr3</em> mutant; and alignment of ArsM proteins.</li> </ol> </li> <li><strong>README.txt:</strong> .txt file with this description text.</li> </ol>
Dataset for "Droplet collection efficiencies inferred from satellite retrievals constrain effective radiative forcing of aerosol-cloud interactions"
<p>This dataset in includes MODIS-CloudSat CFODD reference data, the updated Warm Rain Diagnostics implemented in COSPv2.0, RANSAC regression analysis, and figure production scripts associated with the manuscript “Droplet collection efficiencies estimated from satellite retrievals constrain effective radiative forcing of aerosol-cloud interactions”<br> Authors: Beall, Charlotte, M.; Ma, Po-Lun; Christensen, Matthew W.; Mülmenstädt, Johannes; Varble, Adam; Suzuki, Kentaroh; Michibata, Takuro<br> Journal: Atmospheric Chemistry & Physics (submitted, 2023)</p>
Buried Interface Engineering Enables Efficient and 1,960-hour Isos-L-2i Stable Inverted Perovskite Solar Cells
<p>High-performance perovskite solar cells (PSCs) typically require interfacial passivation, yet this is challenging for the buried interface, owing to the dissolution of passivation agents during the deposition of perovskites. Here, we overcome this limitation with in-situ buried interface passivation – achieved via directly adding a cyanoacrylic acid-based molecular additive, namely BT-T, into the perovskite precursor solution. Classical and ab-initio molecular dynamics simulations reveal that BT-T spontaneously may self-assemble at the buried interface during the formation of the perovskite layer on a nickel oxide hole transporting layer. The preferential buried interface passivation results in facilitated hole transfer and suppressed charge recombination. In addition, residual BT-T molecules in the perovskite layer enhance its stability and homogeneity. We report a power-conversion efficiency (PCE) of 23.48% for 1.0 cm2 inverted-structure PSCs. The encapsulated PSC retains 95.4% of its initial PCE following 1,960-hour maximum power point tracking under continuous light illumination at 65°C (i.e., ISOS-L-2I protocol). Our demonstration of operating-stable PSCs under accelerated ageing conditions represents a step closer to the commercialization of this emerging technology.</p>
Cytomulate: accurate and efficient simulation of cytof data
<p>All six datasets and analysis code for reproducing the findings of "Cytomulate: accurate and efficient simulation of cytof data". The analysis code is also available at <a href="https://github.com/kevin931/cytomulate/releases/tag/benchmark.rev.1">https://github.com/kevin931/cytomulate/releases/tag/benchmark.rev.1</a>. The Cytomulate Python software can be found at <a href="https://github.com/kevin931/cytomulate">https://github.com/kevin931/cytomulate</a>. </p>
Systematic Multi-Trait AAV Capsid Engineering for Efficient Gene Delivery
<p>Datasets for "Systematic Multi-Trait AAV Capsid Engineering for Efficient Gene Delivery", Eid et al., <em>Nature Communications. </em></p>
Experimental evaluation of louver guidance efficiency for green sturgeon (Acipenser medirostris), Primary Datasets, 2016-2017
Throughout the world, louver-bypass systems are a common method for fish protection at water diversion sites. This study used controlled laboratory experiments to quantify louver efficiency for juvenile green sturgeon under a range of conditions. Green sturgeon juveniles used in the study were spawned from the University of California, Davis (hereafter UC Davis) captive broodstock program. Experimental trials were conducted within an indoor flume at the J. Amorocho Hydraulics Laboratory (JAHL) at UC Davis. The flume had a zero degree bed slop, and was equipped with a louver placed at a 15-degree angle to the streamwise flow. Louver slats had 25-mm clear spacing. The louver terminated at a bypass channel 0.3 m wide, and was operated to maintain water velocity in the bypass that was 1.2 times greater than the velocity in the flume. Full factorial experimental treatments were designed to address the influence of sturgeon size, water velocity, diel period, and water temperature on louver performance and behavior. Sturgeon were tested within three predefined size classes (range: 6 – 34 cm TL). At each size class, fish were tested under combinations of water velocity, water temperature, and photophase. During each experimental trial, 60 (+/-2) juvenile sturgeon were released from an acclimation chamber to enter the test area at the bottom of the flume. Fish were allowed to freely navigate throughout the test area until they were transported through the louver slats or bypass channel, at which point they were removed and the time was recorded. Trials ended when all fish were collected at a downstream endpoint, or after 90 minutes of exposure time, and remaining fish were removed from the flume. Trials were completed across two study years within seven months after hatch, following the same protocols with a few minor adjustments in year two. During daytime trials in both study years the louver face was monitored with video recordings to observe contact between fish and the
Instrinsic water use efficiency of Ponderosa Pine of the southwestern U.S.
Tree rings were collected from 17 populations of ponderosa pine forests across the southwestern U.S. Carbon isotope of early wood and latewood were then analyzed for each annual ring, from 1960-2017. Intrinsic water-use efficiency (A/gs) chronologies were calculated with adjusted latewood chronologies as used in Strange et al. (2023) Global Change Biology. Details regarding the process of calculating adjusted latewood chronologies can be found in the methods section of Strange et al. (2023) Global Change Biology.
The North American Monsoon Climate System and its influence on Ponderosa pine water use and water use efficiency
All data in this package are presented as used in Strange et al. (2023). Earlywood (EW) and Latewood (LW) isotope chronologies are presented in the delta (d) notation relative to Vienna Peedee Belemnite (VPDB) standards. Further details regarding data collection, processing, α-cellulose extraction, etc. can be found in the Global Change Biology manuscript associated with these data.
(POST) Socio-economic and cultural dataset in relation to Persuasive Strategies to boost Energy Efficiency and in the UK, Spain, Greece and Austria
<p>The dataset has been created from obtaining post-pilot answers from 106 participants of four different countries in the EU (the questionnaire can be studied in <strong>GreenSoul_Validation_Questionnaire-POST.pdf</strong>). It is composed by several factors which are explained in<strong> POST-coding.ods </strong>file. All these factors are contained in: "<strong>POST-results-socio-economic-model.ods</strong>" and "<strong>POST-results-treatments-evaluation.ods</strong>" along with their answers by participants.</p> <p>Finally, we provided a cleaned version of the dataset to study how can a researcher is able to forecast the ranking that a user will give to different persuasion strategies according to user profiles: "<strong>POST-results-ranking-model.ods</strong>"</p>
20% of US electricity from wind will have limited impacts on system efficiency and regional climate
<p>Simulations of wind turbine wakes conducted with WRF for current and possible future installed capacities upto 20% US electricity from wind.</p>
ScienceDex guides
Understand access before you commit
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.