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1,855 results for “Framework”
Data for contrastive learning framework
<p>Data for contrastive learning framework, containing data for training and evaluation in two settings: detection of functionally equivalent programs on the <br> POJ-104 dataset, and the plagiarism detection task on the dataset of solutions to competitive programming contests held on the Codeforces platform. In both tasks, the datasets contain pairs of programs, labeled whether they are clones or not.</p>
Probing Heterodimer and Multi-adsorbate Hydrocarbon Adsorption Trends in the MFI Framework
<p>Ground-state geometries for all adsorbates heterodimer pairs and multiple adsorbate hydrocarbon sets as part of the Supplementary Information document for the manuscript titled 'Probing Heterodimer and Multi-adsorbate Hydrocarbon Adsorption Trends in the MFI Framework'. </p>
SiEUGreen_Dataset_for_Monitoring_the_contribution_of_urban_agriculture_to_urban_sustainability:_an_indicator-based_framework
<p>The data was collected for scientific publication: Tapia, C., Randall, L., Wang, S.; Borges, L. A. (2021): Monitoring the contribution of urban agriculture to urban sustainability: an indicator-based framework. <em>Sustainable Cities and Society</em>. In press, <a href="https://doi.org/10.1016/j.scs.2021.103130">https://doi.org/10.1016/j.scs.2021.103130</a></p> <p>This dataset includes the data from the survey in Brabrand Fallaesgartneriet, which is the study case reported in the article.</p>
Data from: Towards a better ecological understanding of metacommunity stability: A multiscale framework to disentangle population variability and synchrony effects
<p>1. Despite great progress in our understanding of the mechanisms governing ecosystem stability in local communities, we still lack knowledge at a larger spatial scale. Studying the stability of metacommunities requires assessing the temporal stability and synchrony of populations across space and organizational levels. Previous attempts to disentangle these effects have provided limited ecological interpretations, and conceptual improvements are needed to identify the underlying ecological processes.</p> <p>2. We propose an extended framework aiming at disentangling simultaneously the relative effects of population stability and different types of synchronies on metacommunity stability. We adapted previous methods of decomposing stability into a new set of indices associated with clearer ecological hypotheses. Particularly, we provide synchrony indices that are not affected by statistical properties of the metacommunity but focus on species responses to environment, demography, and interactions. We applied this framework to a unique dataset describing the sorted biomass of individual plant populations, across 12 communities of a species-rich meadow, and for 16 years. The communities were sampled in different treatments of fertilization and dominant removal to evaluate the effect of environmental heterogeneity on stability.</p> <p>3. We found higher stability at a larger spatial scale, mainly due to statistical averaging (portfolio effect). The variability of individual populations was an important determinant of the stability of the whole metacommunity. Consistent with the hypothesis of a common response to environmental conditions, we found that the fluctuations of populations were mostly synchronized (within and between species) at a large spatial scale and tended to destabilize the metacommunity. On the other hand, opposite fluctuations (anti-synchrony) between populations occurred at the local scale, probably due to local species interactions.</p> <p>4. Synthesis Our framework appears as a powerful tool to test how ecological processes occurring simultaneously at different spatial and organizational scales affect the stability of metacommunities. This study advances our ecological understanding of the processes underlying the stability of species-rich environments. --</p>
Effect of Guest Molecules on the Stacking Configuration of Covalent Organic Frameworks: A Periodic Energy Decomposition Analysis
<p>Illustrative videos that provide an in-depth understanding of the methodology and the result obtained from our recent study. A full description of the method is found in the paper. The potential energy surface was plotted using imshow Matplotlib and the 3d structures were rendered using povray. The videos are all free to use for educational purposes but please remember to cite the paper at anytime you use the videos. </p> <p> </p>
A Semi-Empirical Framework for Ice Sheet Response Analysis under Oceanic Forcing in Antarctica and Greenland
<p>Supplementary material for</p> <p>Luo, X. & Lin, T. (2022). “A Semi-Empirical Framework for Ice Sheet Response Analysis under Oceanic Forcing in Antarctica and Greenland.” Climate Dynamics, in press. <a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1007%2Fs00382-022-06317-x&data=05%7C01%7CXiao.Luo%40ttu.edu%7C2a6949c147dd4aa9880f08da345e55ae%7C178a51bf8b2049ffb65556245d5c173c%7C0%7C0%7C637879877007681605%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=2G3mD6n0ZOogcEFQcuCCElFmgKE0%2B%2F5KPTtzBeq8kM4%3D&reserved=0">https://doi.org/10.1007/s00382-022-06317-x</a></p> <p>This repository contains data and scripts that are used to facilitate the analysis of Greenland and Antarctica ice sheet melting induced by ocean warming.</p> <p>The GCM directory contains ocean potential temperature time series for both Antarctica ice shelves near open sea retrieved from FGOALS-s2 under RCP 6.0 and Greenland store glacier retrieved from MIROC5 under RPC8.5 and HadGEM3-GC31-MM projections under update of RCP8.5 based on SSP5. The raw data are accessed from CMIP5 (https://esgf-node.llnl.gov/search/cmip5/) and CMIP6 (https://esgf-node.llnl.gov/search/cmip6/) projects respectively and the processed data deposited here are stored in Excel format.</p> <p>The WOD directory contains the NetCDF files of Present-Day ocean conditions including temperature, salinity, depth, and other variables retrieved from World Ocean Database (WOD). The data are deposited as NetCDF format.</p> <p>The Analysis directory contains 3 subdirectories that illustrates the analysis workflow for both Greenland and Antarctica.</p> <p> The Antarctica subdirectory contains the analysis codes to reproduce Antarctica ice shelf melting response and future projection. Antarctica_analysis.m is the main routine for computation and plotting, and the other files are input files including PISM/PICO simulations outputs and ocean temperature time series retrieved from CMIP5 project that can be found on the previous GCM directory.</p> <p> The Greenland subdirectory contains the main routine store_analysis.m for Greenland Store glacier computation and plotting, the response time series (store.mat), perturbed response time series (store_pert.mat), ocean temperature projection (store_temp.mat) generated by MIROC5, and subglacial runoff time series (store_runoff.mat) estimated from annual basin surface runoff using MAR data forced by MIROC5 under RCP8.5.</p> <p> The Historical subdirectory contains the data and scripts used for the historical analyses in the main text. AIS_melt_historical.m is the main script of the analysis, along with two other plotting functional scripts including plot_melt_rate.m and plot_ocean_temp.m. The input files include the PISM/PICO simulations outputs, which are the same files in Antarctica subdirectory, and other 2 input files that contain the temperature time series from 6 CMIP5 GCMs.</p>
Raw data files for "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" manuscript
<p>Raw data files for a manuscript "3D vs. turbostratic: controlling metal-organic framework dimensionality via N-heterocyclic carbene chemistry" published in Chemical Science. <a href="https://doi.org/10.1039/D2SC01041K">https://doi.org/10.1039/D2SC01041K</a></p> <p>The files are organized by manuscript figure names and are in a simple text or CSV format. The headers contain the necessary information such as column designations, units, etc.</p> <p> </p> <p> </p> <p> </p>
REIP: a Reconfigurable Environmental Intelligence Platform and Software Framework for Fast Sensor Network Prototyping - use case dataset
<p>Sensor networks have dynamically expanded our ability to monitor and study the world. Their presence and need keep increasing, and new hardware configurations expand the range of physical stimuli that can be accurately recorded. Sensors are also no longer simply recording the data, they process it and transform into something useful before uploading to the cloud. However, building sensor networks is costly and very time consuming. It is difficult to build upon other people’s work and there are only a few open-source solutions for integrating different devices and sensing modalities. We introduce REIP, a Reconfigurable Environmental Intelligence Platform for fast sensor network prototyping. REIP’s first and most central tool, implemented in this work, is an open-source software framework, an SDK, with a flexible modular API for data collection and analysis using multiple sensing modalities. REIP is developed with the aim of being user-friendly, device-agnostic, and easily extensible, allowing for fast prototyping of heterogeneous sensor networks. Furthermore, our software framework is implemented in Python to reduce the entrance barrier for future contributions. We show the potential and versatility of REIP in real world applications, along with performance studies and benchmark REIP SDK against similar systems.</p> <p>This dataset was created for the case study in Section 5 of the paper.</p>
KUALA: A Machine Learning-driven framework for kinase inhibitors repositioning
<p>The complete list of all predicted compounds for each kinase accompanied by RT thresholds.</p>
Supplementary information for: A continuous-score occupancy modeling framework for incorporating uncertain machine learning output in autonomous biodiversity surveys
<p><span>Ecologists often study biodiversity by evaluating species occupancy and the relationship between occupancy and other covariates. Occupancy models are now widely used to account for false absences in field surveys and to reduce bias in estimates of covariate relationships. Existing occupancy models take as inputs binary detection/non-detection observations of species at each visit to each site. However, autonomous sensing devices and machine learning models are increasingly used to survey biodiversity, generating a new type of observation record (i.e., continuous-score data) that reflects the model's confidence a species is present in each autonomously sensed file, instead of binary detection/non-detection data. These data are not directly compatible with traditional binary occupancy modeling methods.</span></p> <p><span>Here, we develop a new occupancy model that models continuous scores on a visit level as a Gaussian mixture, combining a distribution of scores for files that do contain the species of interest and a distribution of scores for files that do not. The model takes as input continuous scores for each autonomously sensed and classified file, along with an optional small number of binary, manually verified detection and non-detection annotations.</span></p> <p><span>We present a simulation study that shows that over a range of empirically realistic parameters, our model outperforms traditional occupancy models that are based on binary annotation alone. We also apply this new model to an empirical case study using data generated from five machine learning classifiers applied to autonomous acoustic recordings gathered in the eastern United States.</span></p> <p><span>Because our occupancy model generalizes allowable input data beyond binary observations, it is particularly well-suited to the increasing volume of machine learning classified data in ecology and conservation.</span></p>
Framework for the development of employability competencies at Campus FP
<p>Framework for the development of employability competencies at Campus FP </p>
Documentation and code for reproducing analyses presented in: vcferr: Development, Validation, and Application of a SNP Genotyping Error Simulation Framework
<p>Documentation and code for reproducing analyses presented in: vcferr: Development, Validation, and Application of a SNP Genotyping Error Simulation Framework. Please see the <strong>README.pdf</strong> for step-by-step instructions for reproducing the entire analysis described in the paper.</p>
Dataset for the paper: Computational framework for radionuclide migration assessment in clay rocks
<p>This dataset contains OpenGeoSys-6 simulations results and scripts in Jupyter-notebook format for reproducing and visualizing the results of the paper:</p> <p>Garibay-Rodriguez J, Chen C, Shao H, Bilke L, Kolditz O, Montoya V and Lu R (2022) Computational Framework for Radionuclide Migration Assessment in Clay Rocks. Front. Nucl. Eng. 1:919541. doi: 10.3389/fnuen.2022.919541</p> <p>Details about the usage of the scripts can be found in the OpenGeoSys-6 user guide: https://www.opengeosys.org/</p>
Assessing population structure and genetic diversity in U.S. Suffolk sheep to define a framework for genomic selection
<p>Long-term sustainability of breeds depends on having sufficient genetic diversity for adaptability to change, whether driven by climatic conditions or by priorities in breeding programs. Genetic diversity in Suffolk sheep in the U.S. was evaluated in four ways: 1) using genetic relationships from pedigree data [(n=64,310 animals recorded in the U.S. National Sheep Improvement Program (NSIP)]; 2) using molecular data (n=304 Suffolk genotyped with the OvineHD BeadChip); 3) comparing Australian (n=109) and Irish (n=55) Suffolk sheep to those in the U.S. using molecular data; and 4) assessing genetic relationships (connectedness) among active Suffolk flocks (n=18) in NSIP. By characterizing genetic diversity, a goal was to define the structure of a reference population for use for genomic selection strategies in this breed. Pedigree-based mean inbreeding level for the most recent year of available data was 5.5%. Ten animals defined 22.8% of the current gene pool. The effective population size (N<sub>e</sub>) ranged from 27.5 to 244.2 based on pedigree and was 79.5 based on molecular data. Expected (H<sub>E</sub>) and observed (H<sub>O</sub>) heterozygosity were 0.317 and 0.306, respectively. Model-based population structure included 7 subpopulations. From Principal Component Analysis, countries separated into distinct populations. Within the U.S. population, flocks formed genetically disconnected clusters. A decline in genetic diversity over time was observed from both pedigree and genomic-based derived measures with evidence of population substructure as measured by F<sub>ST</sub>. Using these measures of genetic diversity, a framework for establishing a genomic reference population in U.S. Suffolk sheep engaged in NSIP was proposed.</p>
An analytical framework to measure social return of community-supported agriculture
<p>Figures of the case studies (original data from CSA websites and staff interviews)</p>
Data for "Physically Based Deep Learning Framework to Model Intense Precipitation Events at Engineering Scales"
<p>The dataset consists of high resolution (250 m) and low resolution (0.025 degree) climate model outputs in netCDF format. Each file contains data for one variable and one month.</p> <p>Low resolution files follow the naming scheme: montrealC_0025deg_200x200_ERA5_1m_YYYYMM_VAR.nc</p> <p>High resolution files follow the naming scheme: montrealC_250m_324x324_ERA5_TEB_100_noconv_YYYYMM_VAR.nc</p> <p>YYYYMM stands for the year (first 4 digits) and month (last 2 digits).</p> <p>_VAR indicates the variable contained in the file:</p> <ul> <li>_UU700 stands for the east-west component of wind at a pressure level of 700 hPa (hourly frequency)</li> <li>_VV700 stands for the north-south component of wind at a pressure level of 700 hPa (hourly frequency)</li> <li>When _VAR is omitted, the variable is precipitation at 1-minute temporal resolution</li> </ul>
A new tree-based methodological framework to infer the evolutionary history of Mesopolyploid lineages: An application to the Brassiceae tribe (Brassicaceae)
<p>Whole genome duplication events are notably widespread in plants and this poses particular challenges for phylogenetic inference in allopolyploid lineages, i.e. lineages that result from the merging of two or more diverged genomes after interspecific hybridization. The nuclear genomes resulting from allopolyploidization contain homologous gene copies from different evolutionary origins called homoeologs, whose orthologs must be sorted out in order to reconstruct the evolutionary history of polyploid clades. In this study, we propose a methodological approach to resolve the phylogeny of allopolyploid clades focusing on mesopolyploid genomes, which experienced some level of genome reshuffling and gene fractionation across their subgenomes. To illustrate our methodological framework, we applied it to a clade belonging to the model Brassicaceae plant family, the Brassiceae tribe, that experienced a mesohexaploidy event. The dataset analysed consists of both publically available genomic sequences and new transcriptomic data according to taxa. The present methodology requires a well-annotated reference genome, for which the identification of the parental subgenome fragments has been performed (e.g. Brassica rapa and Brassica oleracea). Focusing on fully retained genes (i.e., genes for which all homoeologous gene copies inherited from the parental lineages are still present in the reference genome), the method constructs multilabelled gene trees that allow subsequent assignment of each gene copy to its diploid parental lineage. Once the orthologous copies are identified, genes from the same parental origin are concatenated and tree-building methods are used to reconstruct the species tree. This method allows resolving the phylogenetic relationships (i) among extant species within a mesopolyploid clade, (ii) among the parental lineages of a mesopolyploid lineage, and (iii) between the parental lineages and closely related extant species. We report here the first well-resolved nuclear-based phylogeny of the Brassiceae tribe.</p>
Multiscale light-sheet organoid imaging framework
<p>These two files correspond to the data associated with the light-sheet recordings and time-course recordings utilized for the manuscript entitled "Multiscale light-sheet organoid imaging framework".<br> If access to the imaging data is needed, (which in total comprises of ~700 GB), please contact Prisca Liberali (prisca.liberali@fmi.ch) for more information.</p>
Data for Functional Group Pair Distance Based Descriptor for Isomerisation in Porous Molecular Framework Materials
<p>This is a dataset of isomer structure files for pore topology: Tri2Di3, Tri4Di6, Tri4-2Di6,Tri6Di9, Tet2Di4, Tet3Di3, Tet4-4Di8, Tet5Di10, and Tet6Di12. </p> <p>All.tar.bz2 contains all pore topologies, the total disk space after unzipping the bundle is 1.8 Gb. The total disk space for pore Tet6Di12 alone is 1.5Gb.</p> <p>The base structure of all pore topologies are constructed using a metal node of radius ~5 (represented by a Zirconium atom) and a benzene linker, while the functional group is represented by a Nitrogen atom.</p>
Data for COLLAPSE: A representation learning framework for identification and characterization of protein structural sites
<p>Data for methods described in the paper "COLLAPSE: A representation learning framework for identification and characterization of protein structural sites" by Alexander Derry and Russ B. Altman (BioRxiv, 2022). https://www.biorxiv.org/content/10.1101/2022.07.20.500713v1</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.