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3,481 results for “data set”
Spontaneous reversal of spin chirality and competing phases in the topological magnet EuAl4 - Data set
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Data set: Comparison of the predictive capacity of the erotophobia-erotophilia and the attitudes toward sexual behaviors in the sexual experience of young adults
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Data set in EDI format for the manuscript titled "2D Broadband Magnetotelluric Study of the Axial Fault Region of the New Madrid Seismic Zone"
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Data Set For Projection-Based Density Matrix Renormalization Group in Density Functional Theory Embedding
<p><span>Funded by the National Science Center grant no 2021/43/I/ST4/02250 </span></p>
Data Set For Variational Quantum Eigensolver Boosted by Adiabatic Connection
<p><span>Funded by the National Science Center grant no 2021/43/I/ST4/02250 </span></p>
Data Set For Toward more accurate adiabatic connection approach for multireference wavefunctions
<p><span>Funded by National Science Center grant no. 2021/43/I/ST4/02250 <br></span></p>
Data Sets for "Efficient Solution of the Number Partitioning Problem on a Quantum Annealer: A Hybrid Quantum-Classical Decomposition Approach"
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TAMU - ARPA-E SMARTFARM Grain Sorghum 2022 Texas site comprehensive sensor modalities data set.
<p>Comprehensive Year 2 data of ARPA-E SMARTFARM Grain Sorghum project titled "Establishing Validation Sites for Field-Level Emissions Quantification from Grain Sorghum in Southern Great Plains". Data sets includes Eddy Caovariance measurements of GHGs (CO2, CH4 and N2O) along with sub acre level soil moisture, soil temperarature, soil N and carbon, plant biomass and yield. This data is from the Texas site of the project. </p>
UF/OSU - ARPA-E SMARTFARM Grain Sorghum 2022 Oklahoma site comprehensive sensor modalities data set.
<p>Comprehensive Year 2 data of ARPA-E SMARTFARM Grain Sorghum project titled "Establishing Validation Sites for Field-Level Emissions Quantification from Grain Sorghum in Southern Great Plains". Data sets includes Eddy Caovariance measurements of GHGs (CO2, CH4 and N2O) along with sub acre level soil moisture, soil temperarature, soil N and carbon, plant biomass and yield. This data is from the Oklahoma site of the project. </p>
TAMU - ARPA-E SMARTFARM Grain Sorghum 2021 Texas site comprehensive sensor modalities data set.
<p>Comprehensive Year 1 data of ARPA-E SMARTFARM Grain Sorghum project titled "Establishing Validation Sites for Field-Level Emissions Quantification from Grain Sorghum in Southern Great Plains". Data sets includes Eddy Caovariance measurements of GHGs (CO2, CH4 and N2O) along with sub acre level soil moisture, soil temperarature, soil N and carbon, plant biomass and yield. This data is from the Texas site of the project. </p>
TAMU - ARPA-E SMARTFARM Grain Sorghum 2023 Texas site comprehensive sensor modalities data set.
<p>Comprehensive Year 3 data of ARPA-E SMARTFARM Grain Sorghum project titled "Establishing Validation Sites for Field-Level Emissions Quantification from Grain Sorghum in Southern Great Plains". Data sets includes Eddy Caovariance measurements of GHGs (CO2, CH4 and N2O) along with sub acre level soil moisture, soil temperarature, soil N and carbon, plant biomass and yield. This data is from the Texas site of the project. </p>
UF/OSU - ARPA-E SMARTFARM Grain Sorghum 2021 Oklahoma site comprehensive sensor modalities data set
<p>Comprehensive Year 1 data of ARPA-E SMARTFARM Grain Sorghum project titled "Establishing Validation Sites for Field-Level Emissions Quantification from Grain Sorghum in Southern Great Plains". Data sets includes Eddy Caovariance measurements of GHGs (CO2, CH4 and N2O) along with sub acre level soil moisture, soil temperarature, soil N and carbon, plant biomass and yield. This data is from the Oklahoma site of the project.</p>
Data set for the paper "How is perceived social pressure associated with attributions of academic achievement? A case study of Czech Universities Applicants"
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Data set and control code for "Force-Sensor-Free Implementation of a Hybrid Position–Force Control for Overconstrained Cable-Driven Parallel Robots"
<p>See the attached readme file</p>
Data set and control code for "Force and time-optimal trajectory planning for dual-arm unilateral cooperative grasping"
<p>See the attached readme file</p>
Data set for "Pose-estimation methods for underactuated cable-driven parallel robots"
<p>See the attached readme file</p>
Data set for "Influences on Reliable Capacity Measurements of Hard Carbon in Highly Loaded Electrodes"
<p>C. Müller, Z. Wang, A. Hofmann, P. Stüble, X. Liu-Théato, J. Klemens, A. Smith, Batteries & Supercaps 2023, 6, e202300322. https://chemistry-europe.onlinelibrary.wiley.com/doi/10.1002/batt.202300322</p> <h1>Abstract</h1> <p><code>For the development of a full-cell battery system, typically appropriate cathodes and anodes are characterized within a half-cell setup where a metal counter electrode is installed to gather data about the employed electrodes. Ultimately, the individual capacity loadings allow for suitable balancing of the anode to cathode capacity in the full-cell. This approach seems rather unproblematic for lithium-ion batteries. For sodium-ion batteries, however, we show that the high reactivity of sodium metal strongly influences hard carbon-based electrode measurements within sodium-ion half-cells. As hard carbon is considered state-of-the-art anode material, the presented results have high impact on the development of sodium ion batteries. Specifically, we show that the type of electrolyte, as well as cell- and measurement-setup are key factors for reliable sodium half-cell measurements of hard carbon. The investigated hard carbon electrodes have a high active material loading of 7.2 mg/cm2 (with 93 % active material content) resulting in an areal capacity of 2.4 mAh/cm2, which represent application-relevant conditions.</code></p> <h1>Funding</h1> <p>This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy - EXC 2154 - Project number 390874152 (POLiS Cluster of Excellence), and contributes to the research performed at Center for Electrochemical Energy Storage Ulm Karlsruhe (CELEST). We would like to thank Dr.-Ing. Philip Scharfer and Prof. Dr.-Ing. Wilhelm Schabel from Thin Film Technology at KIT for coating and drying electrodes in their TFT Coating and Printing Lab within the scope of the joint research in the DFG Cluster of Excellence POLiS. Open Access funding enabled and organized by Projekt DEAL.</p>
Data from: Variable mesophyll conductance among soybean cultivars sets a tradeoff between photosynthesis and water-use-efficiency
Photosynthetic efficiency is a critical determinant of crop yield potential, though it remains below the theoretical optimum in modern crop varieties. Enhancing mesophyll conductance, i.e. the rate of carbon dioxide diffusion from substomatal cavities to the sites of carboxylation, may increase photosynthetic and water use efficiencies. To improve water-use-efficiency mesophyll conductance should be increased without concomitantly increasing stomatal conductance. Here we partition variance in mesophyll conductance to within and among cultivar components across soybeans grown under both controlled and field conditions, and examine the covariation of mesophyll conductance with photosynthetic rate, stomatal conductance, water-use-efficiency and leaf mass per area. We demonstrate that mesophyll conductance varies more than 2-fold and that 38% of this variation is due to cultivar identity. As expected mesophyll conductance is positively correlated with photosynthetic rates. However, a strong positive correlation between mesophyll and stomatal conductance among cultivars apparently impedes positive scaling between mesophyll conductance and water-use-efficiency in soybean. Contrary to expectations, photosynthetic rates and mesophyll conductance both increased with increasing leaf mass per area. The presence of genetic variation for mesophyll conductance suggests there is potential to increase photosynthesis and mesophyll conductance by selecting for greater leaf mass per area. Increasing water-use-efficiency though, is unlikely unless there is simultaneous stabilizing selection on stomatal conductance.
Data from: Multiple data sets, congruence, and hypothesis testing for the phylogeny of basal groups of the lizard genus Sceloporus (Squamata, Phrynosomatidae)
Several data partitions, including nuclear and mitochondrial gene sequences, chromosomes, isozymes, and morphological characters, were used to propose a new phylogeny and to test previously published hypotheses about the phylogenetic positions of basal clades of the lizard genus Sceloporus and the relationship of Sceloporus to the former genus "Sator". In accord with earlier studies, our results grouped "Sator" internal to Sceloporus, and both support a hypothesis of transgulfian vicariance for the origin of the former genus "Sator" on islands in the Sea of Cortez. Robustness of support for internal nodes in our best tree was established though widely used indices (bootstrap proportions, decay values) but also through congruence among independent data partitions. Several deep nodes in the tree recovered by a number of methods, including equally weighted and differentially weighted parsimony, and maximum likelihood models, are only weakly supported by the traditional indices, and this methodological concordance is taken as evidence for insensitivity of the deep structure of the topology to alternate assumptions.
Data from: Ultraconserved element (UCE) probe set design: base genome and initial design parameters critical for optimization
Targeted capture and enrichment approaches have proven effective for phylogenetic study. Ultraconserved elements (UCEs) in particular have exhibited great utility for phylogenomic analyses, with the software package phyluce being among the most utilized pipelines for UCE phylogenomics, including probe design. Despite the success of UCEs, it is becoming increasing apparent that diverse lineages require probe sets tailored to focal taxa in order to improve locus recovery. However, factors affecting probe design and methods for optimizing probe sets to focal taxa remain underexplored. Here, we use newly available beetle (Coleoptera) genomic resources to investigate factors affecting UCE probe set design using phyluce. In particular, we explore the effects of stringency during initial design steps, as well as base genome choice on resulting probe sets and locus recovery. We found that both base genome choice and initial bait design stringency parameters greatly alter the number of resultant probes included in final probe sets and strongly affect the number of loci detected and recovered during in silico testing of these probe sets. In addition, we identify attributes of base genomes that correlated with high performance in probe design. Ultimately, we provide a recommended workflow for using Phyluce to design an optimized UCE probe set that will work across a targeted lineage, and use our findings to develop a new, open‐source UCE probe set for beetles of the suborder Adephaga.
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.