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2,326 results for “clusters”
Duhumbi Phonology - Onset clusters
<p>This set presents the overview of the Duhumbi onset clusters and their origins, including the decision made for the phonological description of the language, supplementing the information in section 2.5.2 of the Duhumbi grammar and including several sound files.</p> <p>This material is made freely available to everyone for informative or scientific purposes as long as the source (this DOI) / the collectors are properly credited. Please note that use of the material for commercial purposes <em><strong>of any kind</strong>, which includes conversion into commercial audio-visual media (documentaries etc.), storage and dissemination through sites that require registration & payment for access, or sites that rely on advertisement (including YouTube) </em>is <strong>not</strong> permitted without <strong>specific written consent</strong> from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions.</p> <p>This data set falls under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. This license lets you remix, tweak, and build upon this work non-commercially, as long as you credit us and license your new creations under the identical terms. License Deed on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">https://creativecommons.org/licenses/by-nc-sa/4.0/</a>. Legal Code on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode</a>.</p> <p>Tim Bodt: bodttim (at) gmail (dot) com</p>
DAPI stained nuclei more or less clustered
<p>DAPI stained nuclei more or less clustered and the corresponding cells stained with TexasRed.</p>
Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states: Dataset
<p>This dataset collects the unprocessed (= outputs from calculations) and processed (= outputs from fits for obtaining spectroscopic constants) results discussed in the paper titled "Equation-of-Motion Coupled-Cluster Theory based on the 4-component Dirac--Coulomb(--Gaunt) Hamiltonian. Energies for single electron detachment, attachment and electronically excited states", by Avijit Shee, Trond Saue, Lucas Visscher and Andre Severo Pereira Gomes.</p>
bin3C - Cluster report and CheckM result for bin3C solution of the real human gut microbiome
<p>Supplementary data table S3 from the manuscript</p> <p>bin3C : Exploiting Hi-C sequencing data to accurately resolve metagenome-assembled genomes (MAGs)</p> <p>A real human gut microbiome was deconvoluted using bin3C. Subsequently, bin3C produced a report detailing per-cluster statistics for the entire solution. The largest 296 clusters were then analyzed with CheckM and joined to the report.</p>
Data for "The role of H2SO4-NH3 anion clusters in ion-induced aerosol nucleation mechanisms in the boreal forest"
<p>This is the dataset that has been analyzed for "The role of H2SO4-NH3 anion clusters in ion-induced aerosol nucleation mechanisms in the boreal forest". Please contact the author (chao.yan@helsinki.fi) for more details. </p>
Predictive simulations of ionization energies of solvated halide ions with relativistic embedded Equation of Motion Coupled-Cluster Theory: Dataset
<p>This dataset collects the unprocessed (= outputs from calculations) and processed (= plots, average values for ionization energies) results discussed in the paper titled "Predictive simulations of ionization energies of solvated halide ions with relativistic embedded Equation of Motion Coupled-Cluster Theory", by Yassine Bouchafra, Avijit Shee, Florent Réal, Valérie Vallet and André Severo Pereira Gomes.</p> <p>In each archive file there is a README explaining how to use the bundled scripts to process the data.</p>
Data set for "Columnar clusters in the human motion complex reflect consciously perceived motion axis"
<p>Accompanying data for manuscript “Columnar clusters in the human motion complex reflect consciously perceived motion axis” written by Marian Schneider, Valentin Kemper, Thomas Emmerling, Federico De Martino, Rainer Goebel, submitted, November 2018.</p> <p>Imaging files<br> -------------<br> * T1w and PDw images, only acquired in session 1<br> * 2 runs task-MotLoc, only acquired in session 2<br> * 5-6 runs task-ambiguous (called "Experiment 1" in accompanying manuscript, divided across 2 scanning sessions)<br> * 5-6 runs task-unambiguous (called "Experiment 2" in accompanying manuscript, divided across 2 scanning sessions)</p> <p><br> Acquisition details<br> -------------------<br> For visualization of the functional results, we acquired scans with structural information in the first scanning session. At high magnetic fields, MR images exhibit high signal intensity variations that result from heterogeneous RF coil profiles. We therefore acquired both T1w images and PDw images using a magnetization-prepared 3D rapid gradient-echo (3D MPRAGE) sequence (TR: 3100 ms (T1w) or 1440 ms (PDw), voxel size = 0.6 mm isotropic, FOV = 230 x 230 mm2, matrix = 384 x 384, slices = 256, TE = 2.52 ms, FA = 5°). Acquisition time was reduced by using 3× GRAPPA parallel imaging and 6/8 Partial Fourier in phase encoding direction (acquisition time (TA): 8 min 49 s (T1w) and 4 min 6 s (PDw)).</p> <p>To determine our region of interest, we acquired two hMT+ localiser runs. We used a 2D gradient echo (GE) echo planar imaging (EPI) sequence (1.6 mm isotropic nominal resolution; TE/TR = 18/2000 ms; in-plane field of view (FoV) 150×150 mm; matrix size 94 x 94; 28 slices; nominal flip angle (FA) = 69°; echo spacing = 0.71 ms; GRAPPA factor = 2, partial Fourier = 7/8; phase encoding direction head - foot; 240 volumes). We ensured that the area of acquisition had bilateral coverage of the posterior inferior temporal sulci, where we expected the hMT+ areas. Before acquisition of the first functional run, we collected 10 volumes for distortion correction - 5 volumes with the settings specified here and 5 more volumes with identical settings but opposite phase encoding (foot - head), here called "phase1" and "phase2".</p> <p>For the sub-millimetre measurements (Experiments 1: here called "task-ambiguous" and Experiments 2: here called "task-unambiguous"), we used a 2D GE EPI sequence (TE/TR = 25.6/2000 ms; in-plane FoV 148×148 mm; matrix size 186 x 186; slices = 28; nominal FA = 69°; echo spacing = 1.05 ms; GRAPPA factor = 3, partial Fourier = 6/8; phase encoding direction head - foot; 300 volumes), yielding a nominal resolution of 0.8 mm isotropic. Placement of the small functional slab was guided by online analysis of the hMT+ localizer data recorded immediately at the beginning of the first session. This allowed us to ensure bilateral coverage of area hMT+ for every subject. In the second scanning session, the slab was placed using Siemens auto-align functionality and manual corrections. Before acquisition of the first functional run, we collected 10 volumes for distortion correction (5 volumes with opposite phase encoding: foot - head). During acquisition, runs for the ambiguous and unambiguous motion experiments were interleaved.</p>
Giant vortex clusters in a two-dimensional quantum fluid: Data sets
<p>This data set collates the experimental and simulation data for the paper "Giant vortex clusters in a two-dimensional quantum fluid."</p> <p><strong>Database S1: Data_Excel_Sheet.xlsx </strong>contains the data shown in Figs. 1, 3, and 4 of the paper.</p> <p><strong>Database S2: Exp_Vortex_Location_Data.zip</strong> contains the experimental vortex positions.</p> <p><strong>Database S3: 2DGPE.zip</strong> contains the outputs of the 2D GPE simulations, along with the generating scripts.</p> <p><strong>Database S4: MonteCarlo_raw.zip</strong> contains the Monte Carlo outputs used to generate the shown in Fig. 1. </p> <p>Additional scripts to reproduce the MC data, GPE data, and reproduce the figures may be found at <a href="https://github.com/UQBEC/GiantVortices">https://github.com/UQBEC/GiantVortices</a>.</p> <p> </p>
A labeled Ecore metamodel dataset for domain clustering
<p>Manually labeled 555 metamodels mined from GitHub in April 2017. </p> <p>Domains: (1) bibliography, (2) conference management, (3) bug/issue tracker, (4) build systems, (5) document/office products, (6) requirement/use case, (7) database/sql, (8) state machines, (9) petri nets</p> <p>Procedure for constructing the dataset: fully manual, by searching for certain keywords and regexes (e.g. "state" and "transition" for state machines) in the metamodels and inspecting the results for inclusion. </p> <p>Format for the file names: ABSINDEX_CLUSTER_ITEMINDEX_name_hash.ecore</p>
A Multi-Challenge Clustering Benchmark Dataset Embedding Large Differences in Spatial Extent
<p>This artificial clustering benchmark dataset was designed manually and draws its inspiration from structural aspects that can be seen in principal component plots of hyperspectral image data. Distance-separated, density-separated, gradient-separated as well as connected clusters have been placed into the dataset. Following the notion that clusters may vary significantly with respect to their spatial extent the respective separability problems are scaled at different levels and only become visible by magnifying certain parts of the dataset. Another special aspect of this dataset is that cluster borders have been kept rather ambiguous which, in our opinion, better resembles the situation in spectroscopic data.</p>
Dataset related to article "Pentraxin 3 regulates synaptic function by inducing AMPA receptor clustering via ECM remodeling and β1-integrin"
<p>This record contains raw data related to article "Pentraxin 3 regulates synaptic function by inducing AMPA receptor clustering via ECM remodeling and β1-integrin"</p> <p>Abstract</p> <p>Control of synapse number and function in the developing central nervous system is critical to the formation of neural circuits. Astrocytes play a key role in this process by releasing factors that promote the formation of excitatory synapses. Astrocyte-secreted thrombospondins (TSPs) induce the formation of structural synapses, which however remain post-synaptically silent, suggesting that completion of early synaptogenesis may require a two-step mechanism. Here, we show that the humoral innate immune molecule Pentraxin 3 (PTX3) is expressed in the developing rodent brain. PTX3 plays a key role in promoting functionally-active CNS synapses, by increasing the surface levels and synaptic clustering of AMPA glutamate receptors. This process involves tumor necrosis factor-induced protein 6 (TSG6), remodeling of the perineuronal network, and a β1-integrin/ERK pathway. Furthermore, PTX3 activity is regulated by TSP1, which directly interacts with the N-terminal region of PTX3. These data unveil a fundamental role of PTX3 in promoting the first wave of synaptogenesis, and show that interplay of TSP1 and PTX3 sets the proper balance between synaptic growth and synapse function in the developing brain.</p> <p> </p>
Fig. 4 – Cluster analysis results for the distance from which ants mobilize from the nest. 4 in Mobilization Strategies in Ants (Hymenoptera: Formicidae)
Fig. 4 – Cluster analysis results for the distance from which ants mobilize from the nest. 4th cluster: F cin – Formica cinerea; 3rd cluster: F. fus – F. fusca; M. rub – Myrmica rubra; M. mut – Messor muticus; M. rug – Myrmica ruginodis; L. bru – Lasius brunneus; D. qua – Dolichoderus quadripunctatus; L. nig – Lasius niger; L. pla – L. platythorax; L. neg U – L. neglectus; T. cae – Tetramorium caespitum; T. err – Tapinoma erraticum; Temn – Temnothorax sp.; P. pal – Plagiolepis pallescens; L. ace – Leptothorax acervorum; S. fug – Solenopsis fugax; P. tau – Plagiolepis tauricus; T. arm – Tetramorium armatum; M. sal – Myrmica salina; M. spe – M. specioides; F. cun – Formica cunicularia; L. ema – Lasius emarginatus; F. ruf – Formica rufibarbis; F. cla – F. clara; C. aet – Camponotus aethiops; 2nd cluster: F. tru – Formica truncorum; L. ful – Lasius fuliginosus; C. vag – Camponotus vagus; F. pra – Formica pratensis; 1st cluster: F. rufa – Formica rufa; F. pol – F. polyctena; C. sub U – Crematogaster subdentata.
Fig. 2 in Juvenile-only clusters and behaviour of the Early Cretaceous dinosaur Psittacosaurus
Fig. 2. Cluster of six juvenile ceratopsian dinosaurs Psittacosaurus (IVPP V14341) from the Early Cretaceous of Lujiatun, Liaoning Province, China. The specimen, illustrated as a photograph (A) and interpretive drawing (B), shows six aligned juvenile specimens, of which specimens 2–6 are estimated to have been two years old at death, and specimen 1 was three years old, based on bone histological analysis.
Fig. 1 in Juvenile-only clusters and behaviour of the Early Cretaceous dinosaur Psittacosaurus
Fig. 1. Isometric growth in Psittacosaurus lujiatunensis. Skull length (y-axis) increases linearly with estimated age, in years (x-axis). The plot is based on measurements of 13 specimens (see SOM).
Fig. 3 in Juvenile-only clusters and behaviour of the Early Cretaceous dinosaur Psittacosaurus
Fig. 3. Bone histological evidence for growth and age in ceratopsian dinosaur Psittacosaurus lujiatunensis Zhou, Gao, Fox, and Chen, 2006 from the Early Cretaceous of Lujiatun, Liaoning Province, China. Mid-diaphyseal transverse sections of fibulae: IVPP V14341.1 (A), IVPP V14341.2 (B), IVPP V14341.3 (C), IVPP V14341.4 (D), and IVPP V14341.5 (E); radius: IVPP V14341.6 (F). White arrows indicate lines of arrested growth (LAGs).
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5. Dendrogram of hierarchical standardized clustering based on the SØrensen similarity index of the studied fragments. The cophenetic correlation coefficient of the cluster is 0.89. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF. Fig. 6. Linkage tree analysis (LINKTREE) showing divisive clustering of fragments (F1–F5) from species compositions constrained by inequalities on one or more environmental variables. Only binary partitions of uncorrelated environmental variables are shown in the cluster. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF.
Curation of Vibrio biofilm matrix cluster and associated proteins
<p>The supplementary data and other supporting materials for the paper titled "Comprehensive Genomic and Evolutionary Analysis of Biofilm Matrix Clusters and Proteins in the <em>Vibrio </em>Genus".</p>
The central role of oxo clusters in zirconium-based esterification catalysis
<p>Data of the figures in the publication "<strong>The central role of oxo clusters in zirconium-based esterification catalysis</strong>".<br>DOI: <a href="https://doi.org/10.1002/smsc.202400369">https://doi.org/10.1002/smsc.202400369</a></p> <p>The <em>.pxp</em> documents contain the experimental data of the figures in the manuscript and SI and they can be opened/edited with the software IGOR Pro 6.3 or higher.</p> <p> </p> <p><strong>Figure 1:</strong> Structural representation of catalysts used in this article. A) Nanocrystal (ZrO2 ), B) Metal-organic framework (UiO-66), (C) Zr6 oxo cluster (Zr6-acetate) and D) Zr12 oxo cluster (Zr12-acetate)</p> <p><strong>Figure 2:</strong> Catalytic esterification of oleic acid with ethanol in ortho-dichlorobenzene (o-DCB). The catalyst is either Zr12-oleate, ZrO2 nanocrystals or the MOF UiO-66. The reactions were performed in triplicate.</p> <p><strong>Figure 3:</strong> Catalytic esterification, comparing Zr12 oxo clusters and UiO-66, for different carboxylic acid substrates. The conditions are identical to Figure 1: 120 °C, 12 mol% zirconium, 0.2 M carboxylic acid, molecular sieves, and four equivalents of ethanol.</p> <p><strong>Figure 4:</strong> Catalytic esterification of oleic acid with hexanol. The reaction is either done in mesitylene (using four equivalents hexanol), without mesitylene (using four equivalents hexanol), or without mesitylene and a reduced 1.2 equivalents of hexanol. In the latter case, we recovered the catalyst and used this for a second catalytic reaction. The dotted line corresponds to the maximum yield that can be obtained when excluding the oleate ligands on the catalyst surface.</p> <p><strong>Figure 5: </strong>PDF refinement for A) Zr12-oleate cluster before catalysis, and after the first and second round of catalysis, B) and for catalyst recovered after 30 min with and without molecular sieves using Zr(OR)4 as the catalyst. The values in square brackets correspond to the ratio of monomer to dimer-cluster in the fit. The refinement is performed using both Zr6- and Zr12-propionate structures obtained from the single crystal structure (CCDC 604529).</p> <p><strong>Figure S1 - S24:</strong> Figures from Supporting Information.</p>
Dataset for "On the potential of the Cluster Ion Counter (CIC) to observe local new particle formation, condensation sink and growth rate of newly formed particles"
<p>Data for Kulmala et al. (2024 )"On the potential of the Cluster Ion Counter (CIC) to observe local new particle formation, condensation sink and growth rate of newly formed particles" (https://doi.org/10.5194/ar-2024-14).</p> <p>Included in the file are number concentrations of sub-2 nm ions and 2-2.3 nm ions measured with Cluster Ion Counter (CIC) and Neutral cluster and Air Ion Spectrometer (NAIS) at SMEAR II station in Hyytiälä, Finland. Concentrations of 1-2 nm ions measured with the NAIS are also included. Sub-2 nm (2-2.3 nm) ion concentrations measured with CIC are refered as Channel 1 (Channel 2-Channel 3) in the .csv file.</p> <p>Contact Santeri Tuovinen (santeri.tuovinen@helsinki.fi) for more details.</p>
Nonlinear methods for dimensionality reduction and clustering of bacterial single-cell sequencing data - intermediate data and figures (MSc thesis)
<p>Data, intermediate results and figures for analyses of my master's thesis in biostatistics at LMU Munich. I took a look on how to use Nonlinear Matrix Decomposition (NMD) (<a href="https://doi.org/10.1137/21M1405769">Saul, L., 2022</a>) in the context of bacterial scRNA-seq analysis (Heumos, L., et. al. 2023), replacing Principal Component Analysis in the optimized workflow, as outlined in Ostner, J. (2024).</p> <p>My thesis was structured along the following objectives:</p> <ul> <li>implement the algorithms from <a href="https://arxiv.org/abs/2305.08687">Seraghiti, G., et. al. (2023)</a> in the Python module <a href="https://github.com/flatironinstitute/nomad/">nomad</a> in cooperation with <a href="https://www.simonsfoundation.org/flatiron/" rel="nofollow">Flatiron Institute</a></li> <li>code for the simulation study of the algorithms in <a href="https://arxiv.org/abs/2305.08687">Seraghiti, G., et. al. (2023)</a> with varying sparsity can be found in <code>/simulation</code></li> <li>apply NMD in the context of the BacSC workflow (<a href="https://www.biorxiv.org/content/10.1101/2024.06.22.600071v1">Ostner, J., et. al. (2024)</a>) on raw and normalized counts (found in <code>/application/analysis</code>), also for manually set number of latent dimensions</li> <li>explore NMD's potential for imputation of <a href="https://www.nature.com/articles/s41467-021-27729-z" rel="nofollow">sampling zeros</a> (check <code>/application/NMD_zero_imputation /</code>)</li> <li>potential of Poisson-Hurdle model-based clustering (<a href="https://academic.oup.com/bioinformatics/article/39/1/btac782/6873739">Qiao, Z., et. al. (2023)</a>) for scRNA-seq (<code>/application/poisson_hurdle</code>).</li> </ul>
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.