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3,339 results for “heterogeneities”
Supplementary material 1 from: El-Barougy RF, Cadotte MW, Khedr A-HA, Nada RM, Maclvor SJ (2017) Heterogeneity in patterns of survival of the invasive species Ipomoea carnea in urban habitats along the Egyptian Nile Delta. NeoBiota 33: 1-17. https://doi.org/10.3897/neobiota.33.9968
Table 1S. Comparison of stratified multivariable generalized linear models : Explanation note: Comparison of stratified multivariable generalized linear models that model the relationship between survival probability and different variables. The best model, selected by AIC, p-value of chi square, deviance explained (DE) and (AW). AW is the Akaikes weight which is the probability of the model being the best model explaining the relationship between survival probability and different variables. DE is the percentage of deviance explained (DE) as a measure of the model's goodness-of-fit.
Asymmetric Collaborative Bar Stabilization Tethered to Two Heterogeneous Aerial Vehicles
<p>We consider a system composed of a bar tethered to two unmanned aerial vehicles (UAVs), where the cables behave as rigid links under tensile forces, and with the control objective of stabilizing the bar's pose around a desired pose. Each UAV is equipped with a PID control law, and we verify that the bar's motion is decomposable into three decoupled motions, namely a longitudinal, a lateral and a vertical. We then provide relations between the UAVs' gains, which, if satisfied, allows us to decompose each of those motions into two cascaded motions; the latter relations between the UAVs' gains are found so as to counteract the system asymmetries, such as the different cable lengths and the different UAVs' weights. Finally, we provide conditions, based on the system's physical parameters, that describe good and bad types of asymmetries. We present experiments that demonstrate the stabilization of the bar's pose.</p>
Replication data for Chen and Khanna. (Global Environmental Change Advances, 2024), "Heterogeneous and Long-Term Effects of a Changing Climate on Bird Biodiversity"
<p>This dataset contains code and data to replicate the results for "Heterogeneous and Long-Term Effects of a Changing Climate on Bird Biodiversity" by Luoye Chen and Madhu Khanna.</p>
Evaluation of the role of environmental, habitat and landscape heterogeneity for lizard communities along the island of Cyprus' riverbanks
<p><span>The raw data of the recorded species’ occurrence and abundance, as well as all the other variables examined for the PhD research "Evaluation of the role of environmental, habitat, and landscape heterogeneity for lizard communities along the island of Cyprus’ riverbanks,".</span></p>
Gene expression profile at both bulk and single cell level for heterogeneous cell type mixtures of A375, HAP1, THP1, HEK239FT, K562, and A549
<p>We used poly-A bulk RNA sequencing and single-cell RNA sequencing using mixtures of well-characterized purified cell lines to better understand measurement noise between technologies. A375, HAP1, THP1, HEK239FT, K562, and A549 cells were mixed in various proportions to generate four in vivo cell mixtures that mimic tissues. Mixtures of 6, 4, 2, and 1 of the cell types are respectively denoted 6ct, 4ct, 2ct, and 1ct. In the included zip, directories are labeled using this notation, followed by a list of cell types in the mixture after an underscore. In each directory, bulk and single cell count data is included.</p>
Food production and biodiversity are not incompatible in temperate heterogeneous agricultural landscapes
<p>We need landscape-scale approaches to design and manage agro-ecosystems that can sustain both agricultural production and biodiversity conservation. In this study, yield figures provided by 299 farmers served to quantify the energy-equivalents of food production across different crops in 49 1-km<sup>2</sup> landscapes. Our results show that the relationship between bird diversity and food energy production depends on the proportion of farmland within the landscape, with a negative correlation observed in agriculture dominated landscapes (≥ 64–74% farmland). In contrast, neither typical farmland birds nor butterflies showed any significant relationship with total food energy production. We conclude that in European temperate regions consisting of small-scale, mixed farming systems (arable and livestock production), productivity and biodiversity conservation may not be purely antagonistic, particularly when (semi-)natural habitats make up a large fraction of the landscape (≥ 20%).</p>
Data from: Unravelling the complexities of temporal biotic homogenisation and heterogenization: Avian assemblage dynamics in Britain
<p>Biotic homogenization is a process whereby species assemblages become more similar through time. The standard way of identifying the process of biotic homogenization is to look for decreases in spatial beta-diversity. However, using a single assemblage-level metric to assess homogenization can mask important changes in the occupancy patterns of individual species. Here, we analysed changes in the spatial beta-diversity patterns (i.e., biotic heterogenization or homogenization) of British bird assemblages within 30km x 30km regions between two periods (1988-1991 and 2008-2011). We partitioned the change in spatial beta-diversity into extirpation and colonisation resultant change (i.e., change in spatial beta-diversity within each region resulting from both extirpation and colonisation). We used measures of abiotic change in combination with Bayesian modelling to disentangle the drivers of biotic heterogenization and homogenization. We detected both heterogenization and homogenization across the two time periods and three measures of diversity (taxonomic, phylogenetic, and functional). In addition, both extirpation and colonisation contributed to the observed changes, with heterogenization mainly driven by extirpation and homogenization by colonisation. These assemblage-level changes were primarily due to shifting occupancy patterns of generalist species. Compared to habitat generalists, habitat specialists had significantly (i) higher average contributions to colonisation resultant change (indicating heterogenization within a region due to colonisation) and (ii) lower average contributions to extirpation resultant change (indicating homogenization from extirpation). Generalists showed the opposite pattern. Increased extirpation resultant homogenization within regions was associated with increased urban land cover and decreased habitat diversity, precipitation, and temperature. Changes in extirpation resultant heterogenization and colonisation resultant heterogenization were associated with differences in elevation between regions and changes in temperature and land cover. Many of the 'winners' (i.e., species that increased in occupancy) were species that had benefitted from conservation action (e.g., buzzard (<em>Buteo buteo</em>)). The 'losers' (i.e., those that decreased in occupancy) consisted primarily of previously common species, such as cuckoo (<em>Cuculus canorus</em>). Our results show that focusing purely on changes in spatial beta-diversity over time may obscure important information about how changes in the occupancy patterns of individual species contribute to homogenization and heterogenization.</p>
Data from: Tree diversity across multiple scales and environmental heterogeneity promote ecosystem multifunctionality in a large temperate forest region
<p><strong>Aim</strong>: Biodiversity across different scales provides multidimensional insurance for ecosystem functioning. Although the effects of biodiversity on ecosystem multifunctionality are well recorded in local communities, they remain poorly understood across scales (from local to larger spatial scales). This study evaluates how multiple attributes of biodiversity maintain ecosystem multifunctionality from local to regional scales, across diverse environmental gradients.</p> <p><strong>Location</strong>: North-eastern China.</p> <p><strong>Time period</strong>: 2017.</p> <p><strong>Major taxa studied</strong>: Woody plants.</p> <p><strong>Methods</strong>: We define multifunctionality using both averaged and modified multiple threshold approaches. Multiple dimensions of biodiversity across varying spatial scales were measured within the framework of Hill‒Chao numbers. Using variance decomposition, linear mixed models, and structural equation modeling, we explored how multiple attributes of tree diversity at varying spatial scales affect multifunctionality, and how these relationships are modulated by environmental drivers.<br>Results: We found that both α- and β-diversity are critical for regional community multifunctionality, while the relationships between species, functional, and phylogenetic diversity and multifunctionality decoupled across spatial scales and thresholds of ecosystem functioning. Phylogenetic β-diversity and species α-diversity are respectively more important for promoting high and moderate threshold multifunctionality (e.g., EMFT90 and EMFT50) in regional communities. Environmental drivers typically have stronger effects than biodiversity on multifunctionality. Soil and climatic conditions had either direct effects on multifunctionality, or indirect ones mediated by species α-diversity. Environmental heterogeneity is important for high threshold multifunctionality, exerting directly and indirectly through phylogenetic β-diversity. Latitude not only directly influences multifunctionality but also modulates it through species α-diversity and phylogenetic β-diversity.</p> <p><strong>Main conclusions</strong>: This study underscores the positive effects of biodiversity on multifunctionality across multiple dimensions. Based on our findings, we conclude that any design of a forested landscape that is aimed at maximizing multifunctionality should consider maintaining high local diversity as well as forest community heterogeneity at varying scales.</p>
Pan-cancer networks for TREE, including six homogeneous and two heterogeneous networks
Open the record for dataset details and reuse information.
The impact of top management team tenure heterogeneity on declining firm's innovation efficiency
<p>A firm maybe experiences a flourishing or declining period, and it also probably survives or even dies in future. Most firms have experienced decline in their development process. The impact of demand contraction and COVID-19 has caused more firms to face decline. Under the dilemma of resources reduction and recovery, the declining firm pays more and more attention to the efficient utilization of limited resources. It attempts to achieve turnaround through CEO substitution, adjustment of ownership concentration, innovation-oriented and other strategies. Based on Upper echelons theory and resource-based view, using the data of A-share listed manufacturing firms in Shanghai and Shenzhen from 2015 to 2019, the impacts of TMT tenure heterogeneity and ownership concentration on the innovation efficiency were investigated. The results show that the TMT tenure heterogeneity promotes the innovation efficiency of declining firms, while the relatively centralized ownership structure negatively moderates this effect. The robustness analysis of variable replacement and the solving of endogenous problem also further support this conclusion. This study not only enriches the application areas of Upper echelons theory, but also provides practical guideline for declining firms to replace top management members and to dilute equity in order to achieve recovery.</p>
The dataset for the paper "Ambient noise tomography reveals asymmetric impact damage zone beneath Lonar crater, India: Implications for oblique impact cratering in heterogeneous basalt with planetary applications"
<p>These datasets are used to produce the results and generate figures and tables in the manuscript titled as "Ambient Noise Tomography Reveals Asymmetric Impact Damage Zone Beneath Lonar Crater, India: Implications for Oblique Impact Cratering in Heterogeneous Basalt with Planetary Applications" submitted to JGR-Planets.</p>
Exploring doxorubicin transport in 2D and 3D models of MDA-MB-231 sublines: impact of hypoxia and cellular heterogeneity on doxorubicin accumulation in cells
<p><span>This data set includes raw data supporting the paper "</span><strong><span>Exploring doxorubicin transport in 2D and 3D models of MDA-MB-231 sublines: impact of hypoxia and cellular heterogeneity on doxorubicin accumulation in cells</span></strong><span>".</span></p> <p><strong><span>The files include the following data</span></strong><span>:</span></p> <p><span>1. MTT assay results used for calculation of <strong>cell viability</strong> / <em><strong><span>EC</span></strong></em></span><strong><sub><span>50</span></sub></strong><strong><span> values</span></strong><span> for doxorubicin in MDA-MB-231 cell line and its sublines;</span></p> <p><span>2. The raw data used for calculating <strong><span>doxorubicin </span></strong></span><strong><span>transport</span></strong><strong><span> </span></strong><span>in <strong><span>2D</span></strong> cells under <strong>normoxia</strong>;</span></p> <p><span>3. The raw data used for calculating <strong><span>doxorubicin </span></strong></span><strong><span>transport</span></strong><strong><span> </span></strong><span>in <strong><span>2D</span></strong> cells under <strong>hypoxia</strong>;</span></p> <p><span>4. The raw data used for calculating <strong><span>doxorubicin </span></strong></span><strong><span>transport</span></strong><strong><span> </span></strong><span>in cancer spheroids (<strong><span>3D</span></strong> cultures).</span></p>
Dataset: Phytoplankton Cell-States: multiparameter lifetime flow monitoring reveals cellular heterogeneity: additional repeats
<p>Additional datasets of repeated experiments for Dataset: Phytoplankton Cell-States: multiparameter lifetime flow monitoring reveals cellular heterogeneity</p>
Flux of density-driven convective dissolution in heterogeneous porous media
<div> <p>Dissolution of CO2 in to brine can increase the density of CO2 rich brine and can cause density driven convection, which can enhance the dissolution of CO2 into brine. Permeability heterogeneity in natural saline aquifers cuases uncertaintis in dissolutio rates, which is measured with mass flux at the CO2-brine interface. Both laboratory experiments and numerical simiulations were conducted to investigate the impact of permeability heterogeneity on convective dissolution. This dataset includes the flux at the CO2-brine interface against time of 48 experiments and 2000 numerical simulations.</p> <p> </p> <p> </p> </div>
Heterogeneous orientation tuning in primary visual cortex of mice diverges from Gabor-like receptive fields in primates
<div> <h2>Data for the Fu et al. (2024) article: 'Heterogeneous orientation tuning in primary visual cortex of mice diverges from Gabor-like receptive fields in primates'</h2> <p> </p> </div> <div> <h3>Summary</h3> </div> <p>Here we provide the complete data for the article Fu et al., 2024 'Heterogeneous orientation tuning in primary visual cortex of mice diverges from Gabor-like receptive fields in primates': include link.</p> <p>The mouse datasets consists of X individual datasets (i.e. recording scans) of calcium activity of L2/3 and L4 neurons in mouse V1. All datasets were acquired using two-photon imaging of awake, head-fixed mice.</p> <p>The monkey dataset has already been published <a href="https://figshare.com/collections/Monkey_V1_and_V4_single-cell_responses_to_natural_images_ephys_Data_from_Cadena_et_al_2024_/6658331/2">here</a>.</p> <div> <h3>Repository structure</h3> </div> <p>The datasets are divided into different experimental paradigms.</p> <p><strong>Imagenet scans</strong> (starting with "static*.zip": contain the neuronal activity in response to grayscale naturalistic images. We used these scans for training deep convolutional neural networks to learn an <em>in-silico</em> model of the recorded neuronal population and to optimize MEIs as well as optimal Gabors. The file "ImageNet_Data_Structure.md" contains detailed information about the content of the files.</p> <p><strong>Dotmap and orientation scans </strong>("dataset_*.pkl"): These scans include two types of stimuli: 1) A sparse noise paradigm for mapping receptive fields of visual neurons. 2) Small patches of drifting gratings to study the orientation tuning selectivity at sub receptive field scale of mouse V1 neurons. The file "RFMapping_Orientation_Data_Structure.md" contains information about the content of the files.</p> <div> <h3>Related Repositories</h3> </div> <p>We used the following Github repositories for analysis, which are all publicly available:</p> <ul> <li>Processing of the calcium data: <a href="https://github.com/cajal/pipeline">https://github.com/cajal/pipeline</a></li> <li>Model training of mouse datasets: <a href="https://github.com/sinzlab/nnidentify">https://github.com/sinzlab/nnidentify</a></li> <li>MEI optimization: <a href="https://github.com/sinzlab/mei/tree/inception_loop">https://github.com/sinzlab/mei/tree/inception_loop</a></li> <li>Gabor optimization: <a href="https://github.com/mohammadbashiri/fitgabor">https://github.com/mohammadbashiri/fitgabor</a></li> </ul>
"A Comprehensive Global Modelling Assessment of Nitrate Heterogeneous Formation on Desert Dust": Column loads monthly means per species.
<p>Column load monthly means of the different species traced with the MONARCH model. <br>The period is 201707 - 201712 (spin-up) and 201801 - 201812 (study period). <br><br>Files are distributed by type of mechanism (fTEQ, HYB and DBCLL) and species in the structure: <br><br><mechanism>_outputs/<methodology>/monthly_means/<species>/<species>_<YYYYMM>.nc</p>
Cumulative arrival time distribution data for "Upscaling transport in heterogeneous media featuring local-scale dispersion: flow channeling, macro-retardation and parameter prediction"
<div> <div>This archive contains arrival time CDF data for a variety of transport simulations in heterogeneous Darcy flow fields, alongside metadata describing the flow fields. The flow fields were spatially periodic, intersected by uniformly-spaced imaginary planes. Arrival times represent length of time from particle departure from one plane until arrival at the next.</div> <div> </div> <div>Consult the README.md file at the top level of the archive for more information. The file format used to store the CDF data is documented in the Python script at the top level of the archive.</div> </div>
Tools for prediction of tumor heterogeneity by a machine learning approach
<p>The package includes R codes and datasets. We applied three classification algorithms: Support Vector Machine, Random Forest, and Naïve Bayes. Datasets include tab-delimited files of mutation and gene expression profile for stomach cancer. </p>
qFit-ligand reveals widespread conformational heterogeneity of drug-like molecules in X-ray electron density maps
<p>Benchmark dataset and prospective cases tested for the development of <em>qFit-ligand</em>. Files included: refined single conformer models, un-refined qFit-ligand multiconformer models, and refined qFit-ligand multiconformer models. </p>
Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability
<p>"Pan-cancer inference of intra-tumor heterogeneity reveals associations with different forms of genomic instability", F. Raynaud, M. Mina, D. Tavernari and G. Ciriello</p> <p>These files are necessary to generate the supplementary table containing:</p> <p>#Sample_name #Cancer_type #Cancer_subtype #Mean_reads_per_mutations #Number_of_mutations #Number_of_altered_segments #Number_of_clones #TreeScore #Number_of_mutations_first_clone #Number_of_mutations_other_clones</p> <p>REQUIREMENTS</p> <p>Phylogenies generated by PhyloWGS (PhyloWGS: Reconstructing subclonal composition and evolution from whole-genome sequencing of tumors](<a href="http://genomebiology.com/2015/16/1/35">http://genomebiology.com/2015/16/1/35</a>), Deshwar et al.)</p> <p>Output files from PhyloWGS for each sample:</p> <ul> <li> <p>top_k_trees which contains the best phylogenies (50 by default) with the label of each clone, the population frequency of each clone, the number of children of each clone, number of mutations in the clone, the labels of the mutations</p> </li> <li> <p>top_k_trees1, top_k_trees2, ... , top_k_treesN output file for the best k trees (50 by default)</p> </li> </ul> <p>FILES</p> <p>*Molecular data for the tumor types: CESC, UCEC, UVM, THCA, KICH, BRCA, SKCM, ACC, CRC, STAD, BLCA, LUAD, KIRP, PRAD, LIHC; has been collected in July 2015 *Molecular data for the tumor types: SARC, PAAD, MESO, LGG, GBM, DLBC, UCS, THYM, TGCT, PCPG, OV, LUSC, LAML, KIRC, HNSC, ESCA, CHOL; has been collected in 2018</p> <p>from the FireHose (<a href="https://gdac.broadinstitute.org/">https://gdac.broadinstitute.org/</a>) and cBioPortal (Cerami et al., 2012) (<a href="http://www.cbioportal.org/">http://www.cbioportal.org/</a>) data repositories for The Cancer Genome Atlas (TCGA). Only TCGA datasets publicly available at that time were used in our study.</p> <p>-Mutation files (MAF format): combined_2015_2018_MAF.maf.bz2</p> <p>-Copy number segmentation files: combined_seg_2015_2018.seg.bz2</p> <p>-analyze_public.py: Python file to generate the Supplementary Table run: python2.7 analyze_public.py</p> <p>- All input data and results from PhyloWGS: PhyloWGS_input_output.tar.bz2 </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.