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10,767 results for “Contribution”
CNRM-ARPEGE v6.2.4 contribution to Antarctic Cordex
<p>This data set is a contribution to Antarctic Polar Cordex using the stretched grid capacity of CNRM-ARPEGE atmospheric GCM. Model outputs have been interpolated from the native ARPEGE grid, with horizontal resolution varying between 35kms (near the stretching pole) to 45 kms on the Antarctic continent, to the ANTi-44 domain (actual lon/lat). The data and metadata format respect almost all of Cordex/CMIP conventions (variables names, units, file names...). The data set consists in six simulations of 30 years time slots : 1981-2010 for "historical" simulations and 2071-2100 for future projections using radiative forcing from RCP8.5 scenario :</p> <p>- ARP-AMIP : amip-style control run driven by observed SST and sea-ice (1981-2100)</p> <p>- ARP-NOR-OC : Future projection driven by NorESM1-M RCP8.5 climate change signal on SST and sea-ice (2071-2100)</p> <p>- ARP-MIR-OC : Future projection driven by MIROC-ESM RCP8.5 climate change signal on SST and sea-ice (2071-2100)</p> <p>More details on these three simulations are given in Beaumet et al., 2019 (<strong><a href="https://dx.doi.org/10.5194/tc-13-3023-2019">10.5194/tc-13-3023-2019) </a></strong></p> <p>- ARP-AMIP-AC : Driven by observed SST and sea-ice + run-time flux bias correction*</p> <p>- ARP-NOR-AOC : Driven by same SST and sea-ice as NOR-OC + run-time flux bias correction*</p> <p>- ARP-MIR-AOC : Driven by same SST and sea-ice as MIR-OC + run-time flux bias correction*</p> <p>Empirical run-time bias correction uses correction terms derived from the climatological mean of tendency errors of a simulation nudged towards climate reanalysis (here ERA-Interim). The method is presented first in Guldberg et al., 2005 (10.1111/j.1600-0870.2005.00120.x) and Krinner et al., 2019 (10.1029/2018MS001438). The method applied with ARPEGE over Antarctica and the evalution of the simulation are presented in this paper : https://doi.org/10.5194/tc-2020-307 (In review)</p> <p>Outputs are available at daily time scale for near-surface atmospherique mean (tas), min (tasmin) and max (tasmax) temperature, total precipitation (pr), snowfall (prsn), snowmelt(snm), surface snow sublimation (sbl_i) and surface runoff (mrros).</p> <p>If you consider using these data, please email me (Julien.Beaumet@univ-grenoble-alpes.fr) to see how I can help and/or be involved.</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Gender Differences in Public Code Contributions: a 50-year Perspective - Replication Package
<p>This page details the steps needed to replicate the findings of the paper: <a href="https://upsilon.cc/~zack/">Stefano Zacchiroli</a>, <em>Gender Differences in Public Code Contributions: a 50-year Perspective</em>, <a href="https://www.computer.org/csdl/magazine/so">IEEE Software</a>, 2021.</p> <p>After retrieving the replication package, follow the instruction described in the README.html file.</p>
Transcriptome analysis of the effect of over-expressing H2A.J mutants in proliferating WI38 fibroblasts for the paper entitled: The H2A.J histone variant contributes to Interferon-Stimulated Gene expression in senescence by its weak interaction with H1 and the derepression of repeated DNA sequences
<p>Abstract for overall study:</p> <p>The histone variant H2A.J was previously shown to accumulate in senescent human fibroblasts with persistent DNA damage to promote inflammatory gene expression, but its mechanism of action was unknown. We show that H2A.J accumulation contributes to weakening the association of histone H1 to chromatin and increasing its turnover. Decreased H1 in senescence is correlated with increased expression of some repeated DNA sequences, increased expression of STAT/IRF transcription factors, and transcriptional activation of Interferon-Stimulated Genes (ISGs). The H2A.J-specific Val-11 moderates the transcriptional activity of H2A.J, and H2A.J-specific Ser-123 can be phosphorylated in response to DNA damage with potentiation of its transcriptional activity by the phospho-mimetic S123E mutation. Our work demonstrates the functional importance of H2A.J-specific residues and potential mechanisms for its function in promoting inflammatory gene expression in senescence.</p> <p>Specific description for this dataset:</p> <p>H2A.J differs from canonical H2A only by a valine at position 11 instead of alanine, and the 7 C-terminal amino acids containing a potential minimal phosphorylation site SQ for DNA-damage response kinases. To test the functional importance of these H2A.J-specific sequences, we mutated Val-11 to Ala as is found in all canonical H2A sequences, and we mutated Ser-123 to either Glu to mimic a phospho-serine residue or to Ala to prevent phosphorylation. We also substituted the C-terminus of H2A.J with the C-terminus of H2A. These mutants, WT-H2A.J and canonical H2A-type1 were ectopically expressed in proliferating fibroblasts, and their microarray transcriptomes were compared to that of proliferating and senescent fibroblasts without ectopic histone expression. Genome-wide transcriptome analysis indicated that senescent fibroblasts clustered distinctly from proliferating fibroblasts, and proliferating fibroblasts expressing the H2A.J-V11A and H2A.J-S123E mutants clustered distinctly from fibroblasts expressing the other H2A.J mutants, WT-H2A.J, and H2A. Hallmark gene set enrichment analysis of the transcriptomes of fibroblasts expressing H2A.J-V11A or H2A.J-S123E versus control proliferating fibroblasts indicated that they showed the same highly significant enrichment for the Epithelial-Mesenchyme Transition, TNF-Alpha Signaling Via NF-kB, and Inflammatory Response gene sets. Notable inflammatory genes including IL1A, IL1B, IL6, CXCL8, and CCL2 are contained in these gene sets and are often induced in senescence as part of the senescence-associated secretory phenotype. Heat maps showed that the H2A.J-V11A and H2A.J-S123E mutants were particularly apt at activating the expression of these inflammatory genes in proliferating fibroblasts</p>
Supporting data to M. Cavallaro, et al., 3'-5' crosstalk contributes to transcriptional bursting, 2019
<p>This repository contains supporting data to reference [1]. Please cite [1] if you find this repository useful. The data include:</p> <ul> <li>Flow cytometry data of HBB and HIV transgenes' expression in `.fcs` format.</li> <li>NanoString data for HIV expression.</li> <li>smFISH data for HBB and Akt1 gene expression.</li> </ul> <p>[1] M. Cavallaro, <em>et al.</em>, 3'-5' interactions contribute to transcriptional bursting, bioR$\chi$iv 514174. <a href="https://doi.org/10.1101/514174">https://doi.org/10.1101/514174</a></p>
UWSCatCH: Urban Water Supply Catchment Contributions and Hydrological Statistics for large cities of the conterminous United States.
<p>UWSCatCH extends and enhances the Urban Water Blueprint (McDonald et al., 2014) for a selection of 116 cities (population > 150,000) and their associated surface water supply catchments in the conterminous United States. The two major enhancements to the Urban Water Blueprint are: [1] estimates of the relative contributions of each surface water catchment to each city's average water supply (as well as updated estimates of any contributions from groundwater); [2] NHDplusV2 reach codes for each water supply intake stream location and associated average flow estimates (regulated and unregulated) (local upstream USGS gage IDs are also provided). UWSCatCH also features a raster file with spatially distributed (1/24° grid) runoff (average of 1980 - 2012 reanalysis simulation) which is masked to watershed polygons (included as a shapefile) to explore spatial distribution of average runoff generation affecting each city. UWSCatCH is designed for use in the R package "gamut" (https://github.com/IMMM-SFA/gamut), and may be applied in a variety of regional and national scale research studies concerning drinking water supply to major US cities.</p>
Dataset: Brain negativity as an indicator of predictive error processing: The contribution of visual action effect monitoring
<p>There are two files for each subject:</p> <p>1. sub##_error.dat -> Contains EEG Segments, that were recorded while the subject executed a clear target miss (minimal distance between the center of the ball and target > 12 cm) in the task (segment and electrode information can be found below).</p> <p>2. sub##_hit.dat -> Contains EEG Segments, that were recorded while the subject executed a clear target hit (minimal distance between the center of the ball and the target < 7 cm) in the task (segment and electrode information can be found below).</p> <p><br> The data in the *.dat-files are stored in a two dimensional matrix: n*1400 datapoints x 15 electrodes</p> <p>n represents the number of segments. 1400 datapoints per segment translate to a segment length of 2800 ms (from 600 ms before to 2200 ms after ball release). The ball´s release is located at the 301st datapoint and the feedback was presented at datapoint 726 (850 ms after ball release) in every segment.</p> <p>datapoints: The first dimension (rows) includes the measured neural activations in microvolts. The data is stored vectorized,<br> i.e. hit/error #1 -> row 1 to 1400, hit/error #2 -> row 1401 to 2800, ..., hit/error #n -> (n-1) * 1400 + 1 to n * 1400</p> <p>electrodes: The second dimension (columns) consists of the 15 different electrodes that were used during data recording in this exact order: [F3 Fz F4 C4 Cz C3 P3 Pz P4 VEOGu VEOGo HEOGre HEOGli FCz Mastre]</p>
Code and data to "Climate change contribution to the 2023 autumn temperature records in Vienna"
<p>The dataset consists of the code and data used for the preprint "Climate change contribution to the 2023 autumn temperature records in Vienna". </p> <p>It contains two objects:</p> <ul> <li>The station data of mean monthly temperature for Vienna Hohe-Warte from 1750 to 2023 (vienna_hohe-warte.csv), which also can be downloaded here: http://www.zamg.ac.at/histalp/dataset/station/csv.php. </li> <li>The code for modeling and producing the figures of the preprint (autumn_temperature.R).</li> </ul>
Supplementary micro-X-ray Fluorescence data for: "On the possible contribution of meteoritic metal to some Ni-rich Indonesian kris daggers: Comparing original daggers and newly forged analogue objects"
<p>This repository contains the micro X-Ray Fluorescence (microXRF) results described within the manuscript titled “On the possible contribution of meteoritic metal to Ni-rich Indonesian kris daggers: Comparing original daggers and newly forged analog objects” submitted to the Meteoritics and Plantetary Science (MAPS) journal by Brandstätter et al. The manuscript describes two types of microXRF results: Semi-quantitative maps and quantified line scan results. The README file contains a detailed overview of which files contain which data.</p>
Sample of Developer Contributions by Gender
<p>Two sets of 100k anonymized software developers from World of Code after applying the name-to-gender inference tool Wiki-Gendersort and quantifying each developer's number of contributions by commit, project, files; files are classified into 116 sub-categories according to language or development file type (e.g., programming, scripting, or markdown languages such as C, C++, Python, JavaScript, Assembly, HTML; build files such as Dockerfiles, CMake, etc; configuration files; documentation files such as README and Markdown; and libraries. One sample is stratified (50/50 split between male and female developers), and one sample is representative of the population. Wiki-Gendersort outputs M (male), F (female), UNK (unknown), INI (initialis), or UNI (unisex). The scripts used to generate the data set can be found on GitHub. </p>
MeanDRS River Width Sampling: Data products corresponding to "Intrinsic spatial scales of river stores and fluxes and their relative contributions to the global water cycle"
<p><strong>Corresponding peer-reviewed publication</strong></p> <p>This dataset corresponds to all input and output files that were used in the study reported in:</p> <ul> <li>Wade, J., David, C.H., Collins, E.L., Denbina, M., Cerbelaud, A., Tom, M., Reager, J.T., Frasson, R.P.M., Famiglietti, J.S., Lee, T., Gierach, M.M. (In Review), Intrinsic spatial scales of river stores and fluxes and their relative contributions to the global water cycle.</li> </ul> <p>When making use of any of the files in this dataset, please cite both the aforementioned article and the dataset herein.</p> <p><strong>Summary</strong></p> <p>The Earth’s rivers vary in size across several orders of magnitude. Yet, the relative significance of small upstream reaches compared to large downstream rivers in the global water cycle remains unclear, challenging the determination of adequate spatial resolution for observations. Using monthly simulations of river stores and fluxes from the MeanDRS river routing dataset, we sample global rivers by a range of estimated river width thresholds to investigate the intrinsic spatial scales of the global river water cycle. We frame these scale-dependent river dynamics in terms of observational capabilities, assessing how the size of rivers that can be resolved influences our ability to capture key global hydrologic stores and fluxes.</p> <p>We aim to answer two questions:</p> <p>1. What is the intrinsic spatial resolution of global river dynamics?</p> <p>2. How can the spatial scale of river processes be used to inform efficient monitoring and modeling strategies of global river stores and fluxes?</p> <p><strong>Data sources</strong></p> <p>The following sources were used to produce files in this dataset:</p> <ul> <li>Mean Discharge Runoff and Storage (MeanDRS) dataset (version v0.4) available under a CC BY-NC-SA 4.0 license. <a href="../records/10013744">https://zenodo.org/records/10013744</a>. DOI: 10.5281/zenodo.10013744; 10.1038/s41561-024-01421-5</li> <li>MERIT-Basins (version 1.0) derived from MERIT-Hydro (version 0.7) available under a CC BY-NC-SA 4.0 license. <a href="https://www.reachhydro.org/home/params/merit-basins">https://www.reachhydro.org/home/params/merit-basins</a></li> </ul> <p><strong>Software</strong></p> <p>The software that was used to produce files in this dataset are available at https://github.com/jswade/meandrs-width-sampling.</p> <p><strong>Data Products</strong></p> <p>The following files represent the primary outputs of the analysis. Each file class generally has 61 files, corresponding to the 61 global hydrologic regions (region ii).</p> <p><strong>Riv_coast.zip</strong> contains shapefiles of corrected and uncorrected MeanDRS river reaches that intersect with the global coast and are inferred to drain to the ocean.</p> <p><strong>· </strong><strong>riv_coast.zip</strong></p> <p><strong> o </strong><strong>cor:</strong> riv_coast_pfaf_ii_COR.shp</p> <p><strong> o </strong><strong>uncor: </strong>riv_coast_pfaf_ii_UNCOR.shp</p> <p><strong> </strong></p> <p><strong>Qout_rivwidth.zip </strong>contains csv files of the aggregate river discharge to the ocean (km<sup>3</sup>/yr) of under each tested river width sampling scenario for each of the 61 global hydrologic regions.</p> <p><strong>· </strong><strong>Qout_rivwidth.zip: </strong>Qout_pfaf_ii_rivwidth.csv</p> <p><strong> </strong></p> <p><strong>V_rivwidth_low.zip</strong> contains csv files of the aggregate river storage (km<sup>3</sup>) for the low residence time scenario under each tested river width sampling scenario for each of the 61 global hydrologic regions.</p> <p><strong>· </strong><strong>V_rivwidth_low.zip:</strong> V_pfaf_ii_rivwidth_low.csv</p> <p><strong> </strong></p> <p><strong>V_rivwidth_nrm.zip </strong>contains csv files of the aggregate river storage (km<sup>3</sup>) for the normal (medium) residence time scenario under each tested river width sampling scenario for each of the 61 global hydrologic regions.</p> <p><strong>· </strong><strong>V_rivwidth_nrm.zip: </strong>V_pfaf_ii_rivwidth_nrm.csv</p> <p><strong> </strong></p> <p><strong>V_rivwidth_hig.zip </strong>contains csv files of the aggregate river storage (km<sup>3</sup>) for the high residence time scenario under each tested river width sampling scenario for each of the 61 global hydrologic regions.</p> <p><strong>· </strong><strong>V_rivwidth_hig.zip: </strong>V_pfaf_ii_rivwidth_hig.csv</p> <p><strong> </strong></p> <p><strong>Largest_rivs.zip </strong>contains files related to our analysis of the relative contributions of discharge to the ocean from the 10 largest global river basins.</p> <p><strong>· </strong><strong>largest_rivs.zip</strong></p> <p><strong> o </strong><strong>cat: </strong>cat_dis_top10_nxx.shp – dissolved catchments of reaches draining from the 10 largest basins</p> <p><strong> o </strong><strong>csv:</strong> Q_df_top10.csv – total discharge contributed by each basin</p> <p><strong> o </strong><strong>riv:</strong> riv_top10_nxx.shp – river reaches that drain the 10 largest basins</p> <p><strong> </strong></p> <p><strong>Smallest_rivs.zip </strong>contains files related to our analysis of the relative contributions of discharge to the ocean from global rivers narrower than 100 m.</p> <p><strong>· </strong><strong>smallest_rivs.zip</strong></p> <p><strong> o </strong><strong>cat: </strong>cat_pfaf_pfaf_ii_small_100m.shp – dissolved catchments of narrow reaches draining to the ocean for each region ii</p> <p><strong> o </strong><strong>csv:</strong> Q_df_top10.csv – total discharge to the ocean from each narrow river reach</p> <p><strong> o </strong><strong>riv: </strong>riv_pfaf_ii_small_100m.shp – river reaches narrower than 100 m that drain to the ocean for each region ii</p> <p><strong> </strong></p> <p><strong>Global_summary.zip </strong>contains files related to the global aggregation of our region-specific river width sampling estimates for discharge to the ocean and river storage.</p> <p><strong>· </strong><strong>global_summary.zip</strong></p> <p><strong> o </strong><strong>Qout_rivwidth: </strong>global summary files for discharge to the ocean (km<sup>3</sup>/yr) under river width sampling</p> <p><strong> o </strong><strong>V_rivwidth_low:</strong> global summary files for total river storage (km<sup>3</sup>) for the low residence time scenario under river width sampling</p> <p><strong> o </strong><strong>V_rivwidth_nrm:</strong> global summary files for total river storage (km<sup>3</sup>) for the normal (medium) residence time scenario under river width sampling</p> <p><strong> o </strong><strong>V_rivwidth_hig: </strong>global summary files for total river storage (km<sup>3</sup>) for the hig residence time scenario under river width sampling</p> <p><strong> o </strong><strong>cat_small_gl: </strong>cat_dis_global_small_100m.shp – global dissolved catchments contributing to all rivers narrower than 100 m that drain to the ocean</p> <p><strong> </strong></p> <p><strong>Rivwidth_sens.zip </strong>contains files related to our supplemental analysis of the sensitivity of our width estimation approach to choice of input discharge dataset. Here, we compute estimated river widths using 3 versions of MeanDRS discharge outputs (VIC, CLSM, NOAH) and compare the results of river width sampling from those runs to that of the primary analysis. The file formats and explanations follow those presented above, with added information for the land surface model used to generate those discharge simulations.</p> <p><strong>· </strong><strong>Rivwidth_sens.zip</strong></p> <p><strong> o </strong><strong>riv_coast</strong></p> <p><strong> o </strong><strong>Qout_rivwidth_VIC</strong></p> <p><strong> o </strong><strong>Qout_rivwidth_CLSM</strong></p> <p><strong> o </strong><strong>Qout_rivwidth_NOAH</strong></p> <p><strong> o </strong><strong>V_rivwidth_low_VIC</strong></p> <p><strong> o </strong><strong>V_rivwidth_nrm_VIC</strong></p> <p><strong> o </strong><strong>V_rivwidth_hig_VIC</strong></p> <p><strong> o </strong><strong>V_rivwidth_low_CLSM</strong></p> <p><strong> o </strong><strong>V_rivwidth_nrm_CLSM</strong></p> <p><strong> o </strong><strong>V_rivwidth_hig_CLSM</strong></p> <p><strong> o </strong><strong>V_rivwidth_low_NOAH</strong></p> <p><strong> o </strong><strong>V_rivwidth_nrm_NOAH</strong></p> <p><strong> o </strong><strong>V_rivwidth_hig_NOAH</strong></p> <p><strong> o </strong><strong>global_summary_VIC</strong></p> <p><strong> o </strong><strong>global_summary_CLSM</strong></p> <p><strong> o </strong><strong>global_summary_NOAH</strong></p> <p><strong> </strong></p> <p><strong>Cor_sens.zip </strong>contains files related to our supplemental analysis of the sensitivity use of corrected ensemble MeanDRS discharge and volume simulations as opposed to uncorrected ensemble simulations. Here, we repeat our primary analysis using only uncorrected simulations throughout, rather than performing river width sampling using corrected simulations. The file formats and explanations follow those presented above, with the files using uncorrected ensemble (ENS) discharge and storage values in contrast to the primary analysis.</p> <p><strong>· </strong><strong>Cor_sens.zip</strong></p> <p><strong> o </strong><strong>Qout_rivwidth_ENS</strong></p> <p><strong> o </strong><strong>V_rivwidth_low_ENS</strong></p> <p><strong> o </strong><strong>V_rivwidth_nrm_ENS</strong></p> <p><strong> o </strong><strong>V_rivwidth_hig_ENS</strong></p> <p><strong> o </strong><strong>global_summary_ENS</strong></p> <p><strong> </strong></p> <p><strong>Width_val.zip </strong>contains files related to our supplemental validation of river widths estimated from MeanDRS discharge simulations through comparison with optical measurements of widths from the Global River Widths from Landsat (GRWL) Databse (Allen & Pavelsky, 2018).</p> <p><strong>· Width_val.zip: </strong>width_validation_pfaf_ii.csv</p> <p> </p> <p><strong>Known bugs in this dataset or the associated manuscript</strong></p> <p>No bugs have been identified at this time.</p> <p> </p> <p><strong>References</strong></p> <p>Allen, G. H., & Pavelsky, T. M. (2018). Global extent of rivers and streams. <em>Science</em>, <em>361</em>(6402), 585-588. https://doi.org/10.1126/science.aat0636</p> <p>Collins, E. L., David, C. H., Riggs, R., Allen, G. H., Pavelsky, T. M., Lin, P., Pan, M., Yamazaki, D., Meentemeyer, R. K., & Sanchez, G. M. (2024). Global patterns in river water storage dependent on residence time. <em>Nature Geoscience</em>, 1–7. https://doi.org/10.1038/s41561-024-01421-5</p> <p>Lin, P., Pan, M., Beck, H. E., Yang, Y., Yamazaki, D., Frasson, R., David, C. H., Durand, M., Pavelsky, T. M., Allen, G. H., Gleason, C. J., & Wood, E. F. (2019). Global Reconstruction of Naturalized River Flows at 2.94 Million Reaches. <em>Water Resources Research</em>, <em>55</em>(8), 6499–6516. https://doi.org/10.1029/2019WR025287</p> <p>Yang, Y., Pan, M., Lin, P., Beck, H. E., Zeng, Z., Yamazaki, D., David, C. H., Lu, H., Yang, K., Hong, Y., & Wood, E. F. (2021). Global Reach-Level 3-Hourly River Flood Reanalysis (1980–2019). <em>Bulletin of the American Meteorological Society</em>, <em>102</em>(11), E2086–E2105. https://doi.org/10.1175/BAMS-D-20-0057.1</p>
'Subglacial Water Amplifies Antarctic Contributions to Sea-Level Rise' by Chen Zhao et al.
<p>Code and data used to produce figures in "Subglacial Water Amplifies Antarctic Contributions to Sea-Level Rise" by Chen Zhao et al.</p> <p>We are happy to help with anybody with any problems with this code, please get in touch (chen.zhao@utas.edu.au) or raise an issue.</p>
Supplemental Data for "Eyewall Asymmetries and Their Contributions to the Intensification of an Idealized Tropical Cyclone Translating in Uniform Flow"
<p>The repository contains a set of files required to reproduce the idealized tropical cyclone simulation analyzed in the manuscript entitled "Eyewall asymmetries and their contributions to the intensification of an idealized tropical cyclone translating in uniform flow", submitted to the Journal of the Atmospheric Sciences. See the README file for brief descriptions about the content of each file within this repository.</p> <p>The simulation was produced with the Cloud Model 1 (CM1) version 19.7, and CM1 can be downloaded at https://www2.mmm.ucar.edu/people/bryan/cm1/. </p>
PhasAGE Expert Seminar- Dissecting the contribution of motor-cargo adaptors to microtubule-based transport in neurons
<p>The PhasAGE Expert Seminars consist of a series of talks with speakers from PhasAGE partner’s institutions to promote a successful transfer of knowledge about PhasAGE topics – biomolecular phase separation, aging and age-related diseases.</p>
The contribution of genetic and environmental effects to Bergmann's rule and Allen's rule in house mice
<p>Data associated with the manuscript, "The contribution of genetic and environmental effects to Bergmann's rule and Allen's rule in house mice".</p> <p><strong>Abstract</strong>: Distinguishing between genetic, environmental, and genotype-by-environment effects is central to understanding geographic variation in phenotypic clines. Two of the best-documented phenotypic clines are Bergmann's rule and Allen's rule, which describe larger body sizes and shortened extremities in colder climates, respectively. Although numerous studies have found inter- and intraspecific evidence for both ecogeographic patterns, we still have a poor understanding of the extent to which these patterns are driven by genetics, environment, or both. Here, we measured the genetic and environmental contributions to Bergmann's rule and Allen's rule across introduced populations of house mice (<em>Mus musculus domesticus</em>) in the Americas. First, we documented clines for body mass, tail length, and ear length in natural populations, and found that these conform to both Bergmann's rule and Allen's rule. We then raised descendants of wild-caught mice in the lab and showed that these differences persisted in a common environment and are heritable, indicating that they have a genetic basis. Finally, using a full-sib design, we reared mice under warm and cold conditions. We found very little plasticity associated with body size, suggesting that Bergmann's rule has been shaped by strong directional selection in house mice. However, extremities showed considerable plasticity, as both tails and ears grew shorter in cold environments. These results indicate that adaptive phenotypic plasticity as well as genetic changes underlie major patterns of clinal variation in house mice and likely facilitated their rapid expansion into new environments across the Americas.</p> <p>Supplemental data files are provided below.</p> <p>Code associated with the analysis of these data can be found on GitHub at <a href="https://github.com/malballinger/Ballinger_allenbergmann_AmNat_2021">https://github.com/malballinger/Ballinger_allenbergmann_AmNat_2021</a>.</p>
SciKGTeX Scientific Contribution Metadata LaTeX Package User Evaluation Results & Analysis
<p>The responses and measured variables from 26 participants of the first user test of the SciKGTeX package.</p> <p><a href="https://github.com/Christof93/SciKGTeX">https://github.com/Christof93/SciKGTeX</a></p> <p>Also the raw text source for the evaluation tasks and the result analysis notebook with the results saved as tsv file.</p>
Evaluation Set - Contributions Similarity in the Open Research Knowledge Graph
<p>This evaluation set has been created for evaluating a content-based recommender system in the context of the Open Research Knowledge Graph (ORKG). The recommender system accepts structured ORKG contribution as input and recommends existing contributions in the ORKG semantically relevant to the given one.</p> <p> </p> <p>The evaluation set is manually annotated based on the <a href="https://www.orkg.org/orkg/featured-comparisons">featured comparisons</a> in the ORKG. In the course of this, it has been distinguished between homogeneous (those who are dissimilar in 2-3 properties) and heterogeneous (otherwise) instances. Multiple annotations have been obtained for the former and exactly one for the latter.</p> <p> </p> <p>It has been also distinguished between "with_response" and "without_response" instances (50 instances for each). The former are those contributions for them the initial version of the contributions similarity service has found similarities and the latter are the opposite case.</p> <p> </p> <p>This evaluation set has been created and applied on a modified version of the contributions similarity service in the context of <a href="https://doi.org/10.15488/11834">this master's thesis</a>. The modified version of the service has simplified the document representation of contributions that are stored in an ElasticSearch index by omitting redundant terms.</p> <p>The evaluation set has the following schema:</p> <pre><code class="language-json">{ "with_response": [ { "contribution_id": "some_id", "comparison_id": "some_id", "comparison_label": "some_label", "contribution_label": "some_label", "paper": "some_id", "research_field": "some_id", "research_problems": [ "some_id" ], "annotations": [ "some_id of a similar contribution", ... ] }, ... ], "without_response": [ ... ] }</code></pre> <p> </p>
Increments for Group Contribution Models (SUB-2017)
<p>Increments values and correction factors values for Group Contribution Models for Molar Refractivity, Heat of formation and LogP (n-octanol/water partition coefficient).</p>
First-principles prediction of the Co-Al phase diagram including configurational, vibrational and magnetic contributions
<p>Documentation for the Dataset used in the publication entitled "First-principles prediction of the Co–Al phase diagram including configurational, vibrational and magnetic contributions" <br>** These datasets comprise all configurations used in Co-Al system and their formation enthalpies at different temperatures, where configurational, vibrational and magnetic contributions were considered. Hcp Co and fcc Al were used as reference states. **<br>** More details about the methodology can be found in the paper "First-principles prediction of the Co-Al phase diagram including configurational, vibrational and magnetic contributions, Journal of Materials Research and Technology, 2024" **</p> <p>1. bcc-Co-Al.zip<br>- Description: bcc-Co-Al.zip is a compressed folder. It contains Al1-xCox configurations with bcc lattice used to fit the cluster expansion (CE). Each folder contains a POSCAR file that correspons to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p>2. fcc-Co-Al.zip<br>- Description: fcc-Co-Al.zip is a compressed folder. It contains Al1-xCox configurations with fcc lattice used to fit the CE. Each folder contains a POSCAR file that correspons to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p>3. hcp-Co-Al.zip<br>- Description: hcp-Co-Al.zip is a compressed folder. It contains Al1-xCox configurations with hcp lattice used to fit the CE. Each folder contains a POSCAR file that correspons to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p><br>4. Formation enthalpies of bcc-Co-Al.xlsx<br>- Description: Formation enthalpies of bcc lattice in Co-Al system at different temperatures, which includes the effect of lattice vibration and magnetic excitation. Fcc Al and hcp Co were used as reference states.</p> <p>- Variable description by columns:<br> 1-(Folder name) - type: numerical (integer)<br> Description: Each folder name in the bcc-Co-Al.zip corresponds to a configuration.<br> 2- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 3- (H_f^(conf)(DFT) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K calculated by density functional theory (DFT) following eq.(18) in the paper.<br> 4- (H_f^(conf)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K fitted by CE. <br> 6- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 7- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 400 K calculated by DFT, the bond length vs. bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 8- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 400 K fitted by CE. <br> 10- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 11- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 800 K calculated by DFT, the bond length vs. bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 12- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 800 K fitted by CE. <br> 14- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 15- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K calculated by DFT, the bond length vs.bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 16- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K fitted by CE.<br> 18- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 19- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1600 K calculated by DFT, the bond length vs.bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 20- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1600 K fitted by CE.</p> <p><br>5. Formation enthalpies of fcc Co-Al.xlsx<br>- Description: Formation enthalpies of fcc lattice in Co-Al system at different temperatures, which includes the effect of lattice vibration and magnetic excitation. Fcc Al and hcp Co were used as reference states.</p> <p>- Variable descriptions by columns are the same as those of Formation enthalpies of bcc-Co-Al.xlsx.</p> <p><br>6. Formation enthalpies of hcp-Co-Al.xlsx<br>- Description: Formation enthalpies of hcp lattice in Co-Al system at different temperatures, which includes the effect of lattice vibration and magnetic excitation. Fcc Al and hcp Co were used as reference states.</p> <p>- Variable descriptions by columns are the same as those of Formation energies of bcc-Co-Al.xlsx.</p> <p><br>7. ECIs of bcc-Co-Al at different temperatures.txt<br>- Description: ECIs of bcc lattice in Co-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that configurational, vibrational and magnetic contributions were considered.</p> <p><br>8. ECIs of fcc-Co-Al at different temperatures.txt<br>- Description: ECIs of fcc lattice in Co-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that configurational, vibrational and magnetic contributions were considered.</p> <p><br>9. ECIs of hcp-Co-Al at different temperatures.txt<br>- Description: ECIs of hcp lattice in Co-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that configurational, vibrational and magnetic contributions were considered.</p> <p><br>10. Clusters of bcc-Co-Al.txt<br>- Description: Cluster information of bcc lattice in Co-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p> <p><br>11. Clusters of fcc-Co-Al.txt<br>- Description: Cluster information of fcc lattice in Co-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p> <p><br>12. Clusters of hcp-Co-Al.txt<br>- Description: Cluster information of hcp lattice in Co-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p>
First principles prediction of the Al-Li phase diagram including configurational and vibrational entropic contributions
<p>Documentation for the Dataset used in the publication entitled "First principles prediction of the Al-Li phase diagram including configurational and vibrational entropic contributions" <br>** These datasets comprise all configurations used in Al-Li system and their formation enthalpies at different temperatures, where both configurational and vibrational contribution were considered. Bcc Li and fcc Al were used as reference state. **<br>** More details about the methodology can be found in the paper "Wei Shao, Sha Liu, Javier LLorca, First principles prediction of the Al-Li phase diagram including configurational and vibrational entropic contributions, Computational Materials Science, 2023"**</p> <p>1. bcc-Al-Li.zip<br>- Description: bcc-Al-Li.zip is a compressed folder. It contains Al1-xLix configurations with bcc lattice used to fit the cluster expansion (CE). Each folder contains a POSCAR file that corresponds to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p><br>2. fcc-Al-Li.zip<br>- Description: fcc-Al-Li.zip is a compressed folder. It contains Al1-xLix configurations with fcc lattice used to fit the CE. Each folder contains a POSCAR file that corresponds to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p>3. Formation enthalpies of bcc-Al-Li.xlsx<br>- Description: Formation enthalpy of each configuration in bcc Al-Li system at different temperatures, which includes the effect of lattice vibration. Bcc Li and fcc Al were used as reference state.</p> <p>- Variable descriptions by columns:<br> 1-(Folder nam) - type: numerical (integer)<br> Description: Each folder name in the bcc-Al-Li.zip corresponds to a configuration.<br> 2- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 3- (H_f^(conf)(DFT) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K calculated by density functional theory (DFT).<br> 4- (H_f^(conf)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration fitted by CE at 0 K. <br> 6- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 7- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 100 K calculated by DFT and bond length vs. bond stiffness relationship (L-S).<br> 8- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 100 K fitted by CE. <br> 10- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 11- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 200 K calculated by DFT and L-S.<br> 12- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 200 K fitted by CE. <br> 14- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 15- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 300 K calculated by DFT and L-S.<br> 16- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 300 K fitted by CE.<br> 18- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 19- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 400 K calculated by DFT and L-S.<br> 20- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 400 K fitted by CE.<br> 22- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 23- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 500 K calculated by DFT and L-S.<br> 24- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 500 K fitted by CE. <br> 26- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 27- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 600 K calculated by DFT and L-S.<br> 28- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 600 K fitted by CE.<br> 30- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 31- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 700 K calculated by DFT and L-S.<br> 32- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 700 K fitted by CE.<br> 34- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 35- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 800 K calculated by DFT and L-S.<br> 36- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 800 K fitted by CE. <br> 38- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 39- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 900 K calculated by DFT and L-S.<br> 40- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 900 K fitted by CE.<br> 42- (at. fraction of Li (%)) - type: numerical (float)<br> Description: The atomic fraction of Li in each configuration.<br> 43- (H_f^(conf+vib)(DFT+L-S) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1000 K calculated by DFT and L-S.<br> 44- (H_f^(conf+vib)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1000 K fitted by CE.</p> <p>4. Formation enthalpies fcc-Al-Li.xlsx<br>- Description: Formation enthalpy of each configuration in fcc Al-Li system at different temperatures, which includes the effect of lattice vibration. Bcc Li and fcc Al were used as reference state.</p> <p>- Variable descriptions by columns are the same as those of Formation enthalpies of bcc-Al-Li.xlsx.</p> <p><br>5. ECIs of bcc-Al-Li at different temperatures.txt<br>- Description: ECIs of bcc lattice in Al-Li system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that both configurational and vibrational contributions were considered.</p> <p><br>6. ECIs of fcc-Al-Li at different temperatures.txt<br>- Description: ECIs of fcc lattice in Al-Li system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that both configurational and vibrational contributions were considered.</p> <p><br>7. Clusters of bcc-Al-Li.txt<br>- Description: Cluster information of bcc lattice in Al-Li system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p> <p><br>8. Clusters of fcc-Al-Li.txt<br>- Description: Cluster information of fcc lattice in Al-Li system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p>
Data: Projecting the Response of Greenland's Peripheral Glaciers to Future Climate Change: Glacier Losses, Sea Level Impact, Freshwater Contributions, and Peak Water Timing
<p>The dataset contains supporting data for the paper submitted to The Cryosphere "Projecting the Response of Greenland's Peripheral Glaciers to Future Climate Change: Glacier Losses, Sea Level Impact, Freshwater Contributions, and Peak Water Timing".<br><br>OGGM_area_projections.nc contains data for Figure 3.<br>OGGM_volume_projections contains data for Figure 4.</p> <p>OGGM_MassLoss_SLR_projections_regions.nc contains data for Figure 5.</p> <p>OGGM_solid_ice_discharge_regions.nc contains data for Figure 6.</p> <p>OGGM_freshwater_runoff_magnitude_composition_timings_projections.nc & OGGM_freshwater_runoff_projections_regions.nc contain data for Figure 7.</p> <p>OGGM_PeakWaterYear_projections_regions.nc contains data for Figure 8.</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.