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3-D synthetic near surface data set with frequency-domain electromagnetic induction data
<p>Realistic three-dimensional exhaustive data set that mimics a near surface mining landfill deposit of waste fine-shaly sands. The data set is composed by petrophysical properties and frequency domain electromagnetic induction (FDEM) data and was created with the purpose of testing algorithms for near-surface modeling and characterization using electromagnetic data.</p> <p>The set of petrophysical properties include porosity, water saturation, particle density and density. Each property corresponds to a single geostatistical realization. The three-dimensional model has a dimension of 150 by 200 by 4 meters (i.e., length, width, depth) with a cell size of 0.5 m by 0.5 m by 0.1 m, respectively (grid size of 300 x 400 x 40). The model grid has 4.8 million cells.<br> Porosity and particle density were modelled based on samples of fine-shaly sands collected at a mine tailing in Portugal for which we investigated porosity, specific weight and particle density. The results of these investigations were used to generate three-dimensional models of subsurface rock properties with unconditional stochastic sequential simulation (Deutsch & Journel, 1998).<br> Porosity was modelled with an omnidirectional spherical variogram model in the horizontal direction. The variogram model has a horizontal range of 10 m, a vertical range of 1 m and a nugget effect of 0.2 % of the total variance of the data. This variogram model describes the expected spatial distribution of this property in the mine tailing.</p> <p>To ensure plausibility between rock properties, particle density and water saturation models were generated with stochastic sequential co-simulation (Deutsch & Journel, 1998) conditioned to the porosity model. For particle density we imposed an omnidirectional spherical variogram model in the horizontal direction with a range of 10 m, a vertical range of 1 m and a nugget effect of 0.2 % of the total variance of the data, and the correlation between porosity and particle density from the lab measurements. For water saturation we imposed an omnidirectional spherical variogram model in the horizontal direction with a range of 16 m, a vertical range of 2 m and a nugget effect of 0.1 (%). For the co-simulation we imposed a correlation between porosity and water content, borrowed from Bhanbhro et al. (2013) and Dumont et al. (2016).</p> <p>The pore fluid was defined as consisting in 80% of water and 20% of leachate, having a density of 0.99114 g/cm3 at a temperature of 30ºC (Souza et al., 2014). The density was mathematically calculated from porosity and particle density models and the density of the pore fluid by using a simple volumetric average of the geological material densities and its relationship to porosity (Mavko et al., 2009), <em>d</em><sub><em>b</em> </sub>= (1 - Ø) <em>d<sub>0</sub></em> Ø <em>d<sub>fl</sub></em> , where <em>d<sub>0</sub></em> is the density of the mineral grains, <em>d<sub>fl</sub></em> is the density of the pore fluids, and Ø is porosity.</p> <p>The electrical conductivity (EC) was created based on the well-known empirical relationship of Archie’s law (Archie, 1942). We first calculate electrical conductivity using the following equation, <em>R<sub>t</sub></em> = <em>a</em> <em>S<sub>w</sub><sup>-n</sup></em> Ø<sup><em>-m</em></sup> <em>R<sub>w</sub></em> , where <em>a</em> is the tortuosity constant, assumed as 0.88, <em>S<sub>w</sub></em> is the water saturation, <em>n</em> is the saturation exponent, assumed as 2, Ø is the porosity, <em>m</em> is the cementation exponent, assumed as 1.37, and <em>R<sub>w</sub></em> is the electrical resistivity of the pore fluid, assumed as 0.25. From the lithology and range of porosity values of the mining landfill model, the values of <em>a</em>, <em>n</em> and <em>m</em> were defined from Keller (1987). The electrical resistivity of the pore fluid was defined based on its composition and density (Keller, 1987). The EC was calculated based on Archie´s second law (Archie, 1942), where conductivity of the partially saturated rock (<em>c<sub>t</sub></em>) is the inverse of its resistivity (<em>R<sub>t</sub></em>), <em>c<sub>t</sub></em> = 1 / <em>R<sub>t </sub></em> (Mavko et al., 2009).</p> <p>Since the relationship between magnetic minerals and the magnetic properties of the rocks depends primarily of the composition and grain size of them (Butler, 2005), the magnetic susceptibility (MS) was modelled using the common range of magnetic susceptibility for unconsolidated sediments (Hudson et al., 1999) with unconditional stochastic sequential simulation (Deutsch & Journel, 1998), imposing an omnidirectional spherical variogram model in the horizontal direction with a range of 20 m, a vertical range of 4 m and a nugget effect of 0.1 % of the total variance.</p> <p>From the resulting three-dimensional models of EC and MS, we retrieved nine equally spaced boreholes along the same yz profile. These borehole data might be used as experimental data for modelling workflows, including geophysical inversion.</p> <p>FDEM data, both the in-phase (IP) and quadrature-phase (QP), were calculated using a 1-D forward model (Hanssens et al., 2019). The acquisition configuration replicates one of the most common sensors for FDEM near-surface surveys, namely the DUALEM-421S (DUALEM Inc., Milton, Canada). It considers two loop-loop coil orientations, a horizontal coplanar (HCP) and a perpendicular one (PRP), with the normal 3 offsets per coil orientation for this equipment, 1, 2 and 4 meters for HCP, and 1.1, 2.1 and 4.1 meters for PRP, plus an extra offset per coil orientation, 10 meters for HCP and 10.1 meters for PRP, ensuring a theoretical larger depth of investigation. The FDEM data were calculated defining the operating frequency of the sensor as 9000 Hz, with an elevation to the surface of 0.15 m.</p>
Accompanying data set for the manuscript "REverSe TRanscrIptase Chain Termination (RESTRICT) for Selective Measurement of Nucleotide Analogs Used in HIV Care and Prevention"
<p>This data set contains all experimental and theoretical data included in the manuscript " REverSe TRanscrIptase Chain Termination (RESTRICT) for Selective Measurement of Nucleotide Analogs Used in HIV Care and Prevention", namely:</p> <p>RESTRICT_model: MATLAB script for completing calculations in the RESTRICT theoretical model.</p> <p>Figure 2:</p> <ul> <li>Raw data from theoretical model showing contributions of individual model components, Kaff = 0.3</li> <li>Normalized data from theoretical model showing contributions of individual model components, Kaff = 0.3</li> <li>Experimental NRTI Drug Screen 180 nt TTCA 500 nM dNTP</li> </ul> <p>Figure 3:</p> <ul> <li>Experiment-dNTP-Concentration-Screen</li> <li>Theory-dNTP-Concentration-Screen</li> <li>Experiment-Template-Length-Screen</li> <li>Theory-Template-Length-Screen</li> <li>Experiment-Sequence-Screen</li> <li>Theory-Sequence-Screen</li> </ul> <p>Figure 4:</p> <ul> <li>Experimental-NRTI-Drug-Screen-90nt-TCAA-only</li> <li>Theory-TCAA90-Kaff=0point2</li> <li>Experimental-NRTI-Drug-Screen-GGCA-only</li> <li>Theory-GGCA180-Kaff=0point2</li> </ul> <p>Figure 5:</p> <ul> <li>GGCA-vs-TTCA-Specificity-Analysis</li> </ul>
Daily water quality data sets of the nine U.S. watersheds
<p>US_daily_WQ_datasets_2.xlsx contains daily water quality (WQ) and discharge data from the nine watersheds in the United States. The data value of -999 means missing observation. The names (USGS station numbers) of nine WQ monitoring sites are Blanchard River (04189000), Cuyahoga River (0428000), Great Miami River (03271500), Honey Creek (04197100), Maumee River (04193500), Muskingum River (03150000), Portage River (04195500), Rock Creek (04197170), and Tiffin River (04185000). Daily WQ data were composed by following the procedure described in the Appendix S1 in Hirsch (2014). The all WQ data river were retrieved from the Heidelberg University's National Center for Water Quality Research site (https://ncwqr.org/monitoring/data) and discharge data were downloaded from the USGS National Water Information System (<a href="http://waterdata.usgs.gov/nwis/">http://waterdata.usgs.gov/nwis/</a> or https://doi.org/10.5066/F7P55KJN) in 2020. All the daily discharge data were acquired via the USGS National Water Information System.</p> <p>These data were used to evaluate the performance of the unbiased load estimates and confidence intervals of river loads based on the rating curve method using rejection sampling in the listed article below. To maintain the traceability of the proposed load estimation method and replicability of the results in the article, the authors of the article upload the data used in this repository.</p>
Phenomenological EOS Data Set
<p>The MATLAB workspace file eos_data_set.mat contains the parameters and physical properties of 1,966,225 phenomenological neutron star (NS) equations of state (EOS).</p>
Quantum coherent spin-electric control in a molecular nanomagnet at clock transitions. Open data set
<p>Data supporting the related publication.</p>
Code and data sets for "DeepLC can predict retention times for peptides that carry as-yet unseen modifications"
<p>Code used to prepare the data sets, calibrate retention times, generate DeepLC models, make predictions, and generate the figures. See README.md for more information on how to use these files and reproduce the results reported in the manuscript titled "DeepLC can predict retention times for peptides that carry as-yet unseen modifications".</p>
data set for 10.1109/TMAG.2021.3084866
<p>Data set and python files for Fig.2, 3, 5 and 6 of 10.1109/TMAG.2021.3084866</p>
Data from: Wild Goffin's cockatoos flexibly manufacture and use tool sets
<p>The use of different tools to achieve a single goal is considered unique to human and primate technology. To unravel the origins of such complex behaviors, it is crucial to investigate tool use that does not occur species wide. These cases can be assumed to have emerged innovatively and be applied flexibly, thus emphasizing creativity and intelligence. However, it is intrinsically challenging to record tool innovations in natural settings that do not occur species-wide. Here we report the discovery of two distinct tool manufacture methods and the use of tool sets in wild Goffin's cockatoos (<i>Cacatua goffiniana</i>). Up to three types of wooden tools, differing in their physical properties and each serving a different function, were manufactured and employed to extract embedded seed matter of <i>Cerbera manghas</i>. While Goffin's cockatoos do not depend on tool-obtained resources, repeated observations of two temporarily kept wild birds and indications from free-ranging individuals suggest this behavior occurs in the wild, albeit not species-wide. The use of a tool set in a non-primate implies convergent evolution of advanced tool use. Furthermore, these observations demonstrate how a species without hands can achieve dexterity in a high-precision task. This finding of flexible use and manufacture of tool sets in animals distantly related to humans significantly diversifies the phylogenetic landscape of technology.</p>
data set regarding to project- Malnutrition, sarcopenia and malnutrition-sarcopenia syndrome in Older Adults with COPD
<p><strong>data set regarding to project- Malnutrition, sarcopenia and malnutrition-sarcopenia syndrome in Older Adults with COPD</strong></p>
Shared motivations, goals and values in the practice of personal science - Qualitative data set
<p>269 transcribed excerpts coded from 22 interviews to self-researchers for the study "Shared motivations, goals and values in the practice of personal science - A community perspective on self-tracking for empirical knowledge". Interviews with participants were conducted via video conferencing and were based on a list of open-ended questions, separated into key sections around participation and collaboration in personal science. Participants who agreed to be interviewed, gave informed consent in like with the ethics approval by the Inserm Institutional Review Board (IRB) for this study, and regarding this data set, previous agreement in compliance with privacy and anonymity requirements. Academic article based on this dataset: Senabre Hidalgo, E., Ball, M. P., Opoix, M., & Greshake Tzovaras, B. (2022). Shared motivations, goals and values in the practice of personal science: a community perspective on self-tracking for empirical knowledge. <em>Humanities and Social Sciences Communications</em>, <em>9</em>(1), 1-12. <a href="https://doi.org/10.1057/s41599-022-01199-0">https://doi.org/10.1057/s41599-022-01199-0</a></p>
Data set related to the manuscript "Carbon-carbon supercapacitors: Beyond the average pore size or how electrolyte confinement and inaccessible pores affect the capacitance"
<p>Graphical files in the agr format and xyz files for the figures in the manuscript entitled "Carbon-carbon supercapacitors: Beyond the average pore size or how electrolyte confinement and inaccessible pores affect the capacitance". Examples of input files for the two systems simulated.</p>
Data Set: Hyperspectral image unmixing with LiDAR data-aided spatial regularization
<p>Data set and matlab codes used for the experimental section of "Hyperspectral Image Unmixing With LiDAR Data-Aided Spatial Regularization"</p> <p>T. Uezato, M. Fauvel and N. Dobigeon, "Hyperspectral Image Unmixing With LiDAR Data-Aided Spatial Regularization," in <em>IEEE Transactions on Geoscience and Remote Sensing</em>, vol. 56, no. 7, pp. 4098-4108, July 2018.<br> doi: 10.1109/TGRS.2018.2823419<br> URL: <a href="http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8347066&isnumber=8393475">http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8347066&isnumber=8393475</a><br> </p>
Data set for bionic simulation of double clap-and-fling wing mechanism with SPH FSI method
<p>Data set containing the rigid-body based flapping wing models coupled with smoothed particle hydrodynamics (SPH), by means of <a href="https://github.com/DualSPHysics/DualSPHysics/wiki/9.-New-in-DualSPHysics#new-in-dualsphysics-v50">DualSPHysics version 5.0 </a>and <a href="https://projectchrono.org/download/">Project Chrono</a>.</p><p>These models are part of the paper:</p><blockquote><p>Yanwei Zhang, Zhonglai Wang, Saullo G. P. Castro. Bionic simulation of double clap-and-fling wing mechanism with SPH FSI method. EngXriv Preprint, 2022. <a href="https://doi.org/10.31224/2652">DOI: 10.31224/2652</a></p></blockquote><p>File "simulations.zip" contains the simulation files.</p><p>File "DualSPHysics_v5.0.zip" contains the compiled DualSPHysics software.</p><p>Procedure to run the simulations on a Windows machine:</p><ul><li>Working directory: .\simulations\flappingwing\case01</li><li>Step 1: Obtain rigid bodies by modeling of SOLIDWORKS and Macro command of FreeCAD (e.g. external_wing111.stl)</li><li>Step 2: Run ".bat" file (e.g. flapping01.bat) to start simulation and force acquisition</li><li>Step 3: Revise ".bat" and ".xml" (e.g. flapping01.bat and flapping01_Def.xml)to adapt to the next case. If required, change the model and Macro command of step 1. Common modification items:</li></ul><p><geometry>-<definition> <floatings>- <floating><angularvel> <floatings>- <floating><property> <properties>-<propertyfile> <initials> <execution>-<special>-<chrono> <execution>-<special>-<inout> <parameters> </p><ul><li>Step 4: Run "Filter.m" to handle force data by filters. Step 5: Compare forces of all cases. PS: Other files are revised function files derived from DualSPHysics 5.0.</li></ul><p> </p><p>Abstract: Three-dimensional numerical simulations of flexible flapping wings based<br>on the fluid-structure interaction in biological and bioinspired flow have become a<br>vibrant and challenging research topic. The present paper focuses on a parametric<br>study of the aerodynamic performance of a bionic flexible clapping wing. The proposed<br>model deforms the wing in spanwise and chordwise directions based on the six rigid<br>bodies connected along the wing veins using ball links and springs. Unsteady effects of<br>flapping wing micro air vehicles with a double clap-fling configuration are investigated<br>using an air-solid interaction model based on smoothed particle hydrodynamics and<br>rigid multi-body dynamics. A validation experiment determined the convergence<br>conditions and computational model accuracy. The proposed numerical model is<br>evaluated in terms of flexible variation law and aerodynamic performance. The results<br>indicate that the flapping frequency, angle of attack, and wind velocity significantly<br>influence the lift. Furthermore, increasing the frequency will monotonically expand<br>the maximum and time-averaged lift curve values. When the angle of attack is less<br>than 30 ◦, the influence on the time-averaged and maximum lift is proportional to the<br>angle of attack. When the angle of attack is larger than 45 ◦, a stall-like condition<br>is detected. To broaden the applicability of the present findings, a dimensionless<br>parameter, reduced frequency, is defined, and its influence on the maximum and time-<br>averaged lift is investigated. This parametric study shows that as the reduced frequency<br>increases, the maximum and time-averaged lift increases and then decreases. The<br>present study could reach a modeling framework that better explains the clapping<br>wing aerodynamics.<br> </p>
Cryptocurrency Fraud and Code Sharing Data Set and Analysis Code
<p>This release covers the state of the data and associated analysis code for determining code sharing between cryptocurrency codebases funded through the end of the original NSF CRII award. This material is based on work supported by the National Science Foundation under Grant CNS-1849729.</p>
Data set for design for bird strike crashworthiness using a building block approach applied to the Flying-V aircraft
<p>Data set for the manuscript:</p> <p>Chen SY, van de Waerdt W, Castro SGP (2022). Design for bird strike crashworthiness using a building block approach applied to the Flying-V aircraft. Preprint. DOI: <a href="https://doi.org/10.31224/2559">https://doi.org/10.31224/2559</a></p>
Psychological adjustment in Third Culture Kids living in Switzerland: Data Set
<p>demographic variables:</p> <p>parent's assignment length, child's agreeableness with the relocation, child's age (7–12 years and 13–17 years), school type (international or other), and history of psychological treatment </p> <p>Labels:</p> <p>parent variables (P1) parent filled child well being and mental health (CC1), child filled variables (C1)</p> <p>variables:</p> <p>Well-being using the 10-item KIDSCREEN-10 Index (The KIDSCREEN Group Europe, 2006). </p> <p>Mental health problems using the 25-item SDQ (R. Goodman, 1997). </p> <p>Emotion regulation strategies using the Emotion Regulation Questionnaire for Children and Adults (Gullone & Taffe, 2012), a 10-item self-report scale that measures expressive EES and CCS. </p> <p>Perceived stress using the 13-item Perceived Stress Scale for Children (White, 2014). </p> <p>Resilience using the 12-item Child and Youth Resilience Measure (CYRM-12; Liebenberg et al., 2013). </p> <p>Negative social cognitions using the 10-item Social Threat Subscale of the Children's Automatic Thoughts Scale (Schniering & Lyneham, 2007; Schniering & Rapee, 2002),</p> <p> </p>
Data Set: Renewable hydrogen fuels versus fossil fuels for trucking, shipping and aviation: A holistic cost model
<p>Data Set: Renewable hydrogen fuels versus fossil fuels for trucking, shipping and aviation: A holistic cost model</p>
Image data set based on the age of giant pandas
<p>The conservation of the giant panda (<em>Ailuropoda melanoleuca</em>), as an iconic vulnerable species, has received great attention in the past few decades. As an important part of the giant panda population survey, the age distribution of giant pandas can not only provide useful instruction but also verify the effectiveness of conservation measures. The current methods for determining the age groups of giant pandas are mainly based on the size and length of giant panda feces and the bite value of intact bamboo in the feces, or in the case of a skeleton, through the wear of molars and the growth line of teeth. These methods have certain flaws that limit their applications. In this study, we developed a deep learning method to study age group classification based on facial images of captive giant pandas and achieved an accuracy of 85.99% on EfficientNet. The experimental results show that the faces of giant pandas contain some age information which is mainly concentrated between the eyes of giant pandas. In addition, the results also indicate that it is feasible to identify the age groups of giant pandas through the analysis of facial images.</p>
Data set for sperm storage in female squid, Todarodes pacificus
<p><span>Female eumetazoans often develop sperm storage organs (SSOs). Although the processes of sperm storage may influence post-copulatory sexual selection in polyandrous species, the significance of multiple SSOs is not understood. In contrast to coastal squids (which develop no more than two SSOs), the female <em>Todarodes pacificus</em>, a more oceanic species, develops more than 20 SSOs, which take the form of specialized pockets, called seminal receptacles (SRs), near the mouth. We investigated the sperm storage pattern of SRs by paternity analysis of hatchlings obtained after artificial insemination using sperm retrieved from 6 arbitrarily selected SRs. The results showed that </span><span>females</span><span> were capable of storing sperm contributed by 9 to 23 males, indicating that females are broadly </span><span>promiscuous</span><span>. In the pattern of sperm storage, the number of males and proportion of their sperm present in the SRs varied among SRs, and sperm storage was biased towards particular males at the individual SR level. However, when calculated as a proportion of all the SRs within a female, the number of sires increased and the paternity bias towards any particular male weakened. These results suggest that one function of having multiple SRs in <em>T. pacificus</em> may be to ensure genetic diversity of the offspring.</span></p>
Saskatchewan seismic data set 2
<p>Seismic data from Saskatchewan glacier. Includes the waveform data, the log files, and the instrument response file.</p>
ScienceDex guides
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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.