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2,326 results for “clusters”

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zenodo40/100

Applicability and limiations of Cluster Perturbation Theory for Hubbard models

<p>These are the Cluster Greensfunctions that were used in the paper &quot;Applicability and limiations of Cluster<br> Perturbation Theory for Hubbard models&quot; published as part of the special edition &ldquo;S.I.: Non-Equilibrium Quantum<br> Physics, Many Body Systems, and Foundations of Quantum Mechanics&rdquo; in the European Journal of Phyiscs in 2023.<br> The Greensfunctions were generated via a Chebyshev expansion and are currently in a real space representation.<br> You may use python and import them via numpy as follows:</p> <p>```console<br> import numpy as np</p> <p>MC = &lt;number_of_sites&gt; # Here you have to add the number of cluster sites (e.g. 16 for a 4x4 cluster)</p> <p>greensfunctions = np.genfromtxt(&quot;&lt;file_name&gt;&quot;)<br> greensfunctions = greensfunctions.reshape(greensfunctions.shape[0], MC, MC)<br> ```</p> <p>This way you obtain a tensor where the first dimension corresponds to the frequency and the other two<br> to the real space indices.</p> <p>For further questions please contact the corresponding author Nicklas Enenkel via E-mail<br> (nicklas.enenkel@quantumsimulations.de)</p>

opencc-by-4.0Jun 2023View details →
zenodo40/100

Database and Syntax for Analysis of the Paper: "Effects of introducing the WHO Labour Care Guide on Caesarean section: a pragmatic, stepped-wedge, cluster randomized trial in India"

<p>The following files contains the information used to analyze the trial &ldquo;Implementing the WHO Labour Care Guide to reduce the use of Caesarean section in four hospitals in India: a pragmatic, stepped wedge, cluster randomized pilot trial&rdquo; in which it was hypothesized that the intervention would promote correct LCG use by these providers, changing their labour monitoring and management practices to align with WHO&rsquo;s intrapartum recommendations. In turn, this could reduce overuse of Caesarean section, improve maternal and newborn outcomes, and enhance women&rsquo;s care experiences. &nbsp;</p> <p>Two datafiles with extension &ldquo;csv&rdquo; are uploaded. The databased named &ldquo;LCG Trial Women Database (transition period included).csv&rdquo; is the database which contains the data of the recruited women in the trial. There is one row per women. The databased named &ldquo;LCG Trial Neonates Database (transition period included).csv&rdquo; is the database which contains the data of the neonates born from the recruited women. There is one row per neonate.</p> <p>The excel file &ldquo;Data Dictionary LCG to Share.xlsx&rdquo; is the data dictionary of the two databases. In the sheet named &ldquo;Maternal Variables&rdquo; a list and description of the variables included in the maternal database is included and, in the sheet, named &ldquo;Neonatal Variables&rdquo; a list and description of the variables included in the neonatal database is included.</p> <p>Three files of &ldquo;R&rdquo; extension and one &ldquo;rmd&rdquo; are included. The file named &ldquo;RunningModelsFunctions.R&rdquo; is the one use to run the models that are included in the analyses, the file named &ldquo;2. Final Analysis LCG Trial.R&rdquo; is the one in which the tables are prepared, and the file named &ldquo;3. LCG Results Output Final.rmd&rdquo; is used to export the tables with results. The R file named &ldquo;funciones.tablas.R&rdquo; is used in the analyses.</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

STGMVA: clustering, imputation, and integration for spatial resolved transcriptomics using spatiotemporal gaussian mixture variational autoencoder

<p>&nbsp;In this study, we present STGMVA, a comprehensive analysis toolkit employs a spatiotemporal gaussian mixture variational autoencoder to tackle these tasks effectively. STGMVA consists of two stages: pretraining the gene expression and spatial location using a gaussian mixture model, and learning the embedding vectors through a variational graph autoencoder. Results demonstrate STGMVA surpasses state-of-the-art approaches on various spatial transcriptomics datasets, exhibiting superior performance across different scales and resolutions. Notably, STGMVA achieves the highest clustering accuracy in human brain, mouse hippocampus, and mouse olfactory bulb tissues. Furthermore, STGMVA enhances and denoises gene expression patterns for gene imputation task. Additionally, STGMVA has the capability to correct batch effects and achieve joint analysis when integrating multiple tissue slices.</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

Рис. 2. Ширина трофической ниши паукообразных в биотопах трех типов: I – поΛупустынная равнина; II – каменистые скΛоны пΛато; III – ΔоΛина со скопΛениями скаΛьных останцев. Fig. 2. The width of the trophic niche of arachnids in biotopes of three types: I – semidesert plain; II – stony slopes of the plateau; III – valley with clusters of rocks. in Comparison of trophic spectra and hunting strategies of some large arachnids (Arachnida: Scorpiones, Solifugae, Aranei) in semi-desert biocenoses of Gobustan (Eastern Azerbaijan)

Рис. 2. Ширина трофической ниши паукообразных в биотопах трех типов: I – поΛупустынная равнина; II – каменистые скΛоны пΛато; III – ΔоΛина со скопΛениями скаΛьных останцев. Fig. 2. The width of the trophic niche of arachnids in biotopes of three types: I – semidesert plain; II – stony slopes of the plateau; III – valley with clusters of rocks.

opencc-by-4.0Dec 2017View details →
zenodo40/100

Materials for the "Unsupervised classification (clustering) of satellite images" workshop

<p>Dataset for the &quot;<strong>Unsupervised classification (clustering) of satellite images</strong>&quot; workshop on <a href="https://opengeohub.org/summer-school/opengeohub-summer-school-poznan-2023/">OpenGeoHub Summer School 2023</a>. The repository with the code can be found on GitHub: <a href="https://github.com/kadyb/OGH2023">https://github.com/kadyb/OGH2023</a>.</p> <p>In the .zip archive there are two catalogs: &quot;<em>data</em>&quot; and &quot;<em>task</em>&quot;, which include:</p> <ul> <li>Landsat 8 scene (7 spectral bands) + metadata;</li> <li>polygons with coverage of Poznań and Szamotuły counties.</li> </ul> <p>The satellite data was downloaded from <a href="https://earthexplorer.usgs.gov/">EarthExplorer</a>.</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

Dataset: Formulation and Implementation of Frequency-Dependent Linear Response Properties with Relativistic Coupled Cluster Theory for GPU-accelerated Computer Architectures

<p>This dataset collects the data (outputs, coordinate files) for the calculations presented in the manuscript &quot;Formulation and Implementation of Frequency-Dependent Linear Response Properties with Relativistic Coupled<br> &nbsp; Cluster Theory for GPU-accelerated Computer Architectures&quot;.</p>

opencc-by-4.0Jul 2023View details →
zenodo40/100

16S rRNA phylogeny and clustering is not a reliable proxy for genome-based taxonomy in Streptomyces

<p>This file is intended&nbsp;as supplementary information for a forthcoming publication:&nbsp;16S rRNA phylogeny and clustering is not a reliable proxy for genome-based taxonomy in <em>Streptomyces</em>.&nbsp;</p>

opencc-by-4.0Aug 2023View details →
zenodo40/100

Artifact Description/Artifact Evaluation/Computational Artifact for "SPEChpc 2021 Benchmarks on Ice Lake and Sapphire Rapids Infiniband Clusters: A Performance and Energy Case Study"

<p>We provide reproducibility initiative dependencies (Artifact Description or Artifact Evaluation or Computational Results Analysis) appendix at https://github.com/RRZE-HPC/PMBS23-AD. To allow a third party to duplicate the findings, this article provides our extensive performance data artifact and describes further details regarding the software environments, experimental design, and methodology employed for the results shown in the paper, entitled &quot;SPEChpc 2021 Benchmarks on Ice Lake and Sapphire Rapids Infiniband Clusters: A Performance and Energy Case Study&quot;. The computational artifacts will enable experienced performance engineers to reproduce and interpret the data shown in the paper in the appropriate way and to follow the conclusions we draw from it.</p>

opengpl-2.0Aug 2023View details →
zenodo40/100

Dataset: Frequency-Dependent Quadratic Response Properties and Two-photon Absorption from Relativistic Equation-of-Motion Coupled Cluster Theory

<p>This dataset comprises outputs and post-processing results related to the paper &quot;Frequency-Dependent Quadratic Response Properties and Two-photon Absorption from Relativistic Equation-of-Motion Coupled Cluster Theory&quot;, by Xiang Yuan, Loic Halbert, Lucas Visscher and Andre Severo Pereira Gomes.</p>

opencc-by-4.0Sep 2023View details →
zenodo40/100

Multi-method gene clusters at species-level resolution for 125 prokaryotic pangenomes

<p>This dataset contains 9 sets of species-level gene clusters and high-resolution species trees for 125 representative bacterial and archaeal species, encompassing a total of 6,851 nearly complete genomes. Each set represents a different approach to homology-, orthology-, and synteny-based gene clustering as implemented by 6 popular tools for comparative genomics and pangenome analysis (Roary, panX, OrthoFinder, MMseqs2/PanACoTa, CD-HIT, and eggNOG-mapper).</p> <p>For <em>Escherichia coli</em>, <em>Cutibacterium acnes</em>, <em>Bacteroides uniformis</em>, and <em>Staphylococcus epidermidis</em>, we provide additional sets that combine high-quality genomes with different proportions of medium- and low-quality metagenome-assembled genomes (MAGs).</p> <p>This dataset is a helpful resource for benchmarking gene clustering tools and pangenome analysis workflows, as well as for testing their robustness with respect to the presence of incomplete or contaminated genomic assemblies.</p> <p><strong>Reference:</strong> Manzano-Morales S, Liu Y, Gonz&aacute;lez-Bod&iacute; S, Huerta-Cepas J, Iranzo J. 2022. Comparison of gene clustering criteria reveals intrinsic uncertainty in pangenome analyses. <em>bioRxiv</em> doi: <a href="https://doi.org/10.1101/2022.09.25.509376">10.1101/2022.09.25.509376</a></p>

opencc-by-4.0Oct 2023View details →
zenodo40/100

A Toroidal Zr70 Oxysulfate Cluster and Its Diverse Packing Structures

<p>Supplementary material: &nbsp;Syntheses, XRD, TGA, SEM, PXRD</p>

opencc-by-4.0Oct 2023View details →
ClinicalTrials.gov40/100

Tailoring Maintenance Therapy to Cluster of Differentiation 5 Positive (CD5+) Regulatory B Cell Recovery in ANCA Vasculitis

ClinicalTrials.gov study NCT03906227. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →
dryad40/100

Data from: A novel approach to quantifying mammal locomotor repertoires using scoring and cluster analysis

Open the record for dataset details and reuse information.

publicDec 2025View details →
dryad40/100

Solid-state-like high harmonic generation from cluster molecules with rotational periodicities

Open the record for dataset details and reuse information.

publicJan 2023View details →
dryad40/100

A role for myosin II cluster and membrane energy in cortex rupture for Dictyostelium discoideum cells

Open the record for dataset details and reuse information.

publicMar 2022View details →
dryad40/100

Directional hydrophone clusters reveal evasive responses of small cetaceans to disturbance at offshore windfarms

Open the record for dataset details and reuse information.

publicDec 2022View details →
dryad40/100

Extended data tables to Haering and Habermann, F1000Res, RNfuzzyApp: an R shiny RNA-seq data analysis app for visualisation, differential expression analysis, time-series clustering and enrichment analysis

Open the record for dataset details and reuse information.

publicJul 2021View details →
dryad40/100

Generalising an outbreak cluster detection method for two groups: An application to rabies

Open the record for dataset details and reuse information.

publicOct 2025View details →
dryad40/100

Optimal sequence similarity thresholds for clustering of molecular operational taxonomic units in DNA metabarcoding studies

Open the record for dataset details and reuse information.

publicMar 2022View details →
dryad40/100

Subtyping of common complex diseases and disorders by integrating heterogeneous data. Identifying clusters among women with lower urinary tract symptoms in the LURN study

Open the record for dataset details and reuse information.

publicJul 2022View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record