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1,454 results for “large scale”
Supplemental data for "Large-scale quantum machine learning"
<p>This data supports "Large-scale quantum machine learning" by Tobias Haug, Chris N. Self, M. S. Kim (arxiv:2108.01039) https://arxiv.org/abs/2108.01039</p> <p>Related code can be found in the GitHub repository: (https://github.com/chris-n-self/large-scale-qml). The 'studies' folder here can be dropped inside the code repository in order to run the analysis scripts.</p> <p>Both 'processed' and 'unprocessed' data is provided. Unprocessed data is the qiskit measurement results for each case study, executed on the IBM Quantum device <em>ibmq_guadalupe</em> and <em>ibmq_toronto</em>. Processed is the Gram matrix evaluated from the measurements and the data vectors needed to fit support vector machine classifiers.</p>
Large-scale drivers of relationships between soil microbial properties and organic carbon across Europe
<p>The aim of this study was to quantify direct and indirect relationships between soil microbial community properties (potential basal respiration, microbial biomass) and abiotic factors (soil, climate) in three major land-cover types.</p> <p>Location: Europe</p> <p>Time period: 2018</p> <p>Major taxa studied: Microbial community (fungi and bacteria)</p> <p>We collected 881 soil samples from across Europe in the framework of the Land Use/Land Cover Area Frame Survey (LUCAS). We measured potential soil basal respiration at 20ºC and microbial biomass (substrate-induced respiration) using an O2-microcompensation apparatus. Climate and soil data were obtained from previous LUCAS surveys and online databases. Structural equation modeling (SEM) was used to quantify relationships between variables, and equations extracted from SEMs were used to create predictive maps. Fatty acid methyl esters were measured in a subset of samples to distinguish fungal from bacterial biomass. Soil microbial properties in croplands were more heavily affected by climate variables than those in forests. Potential soil basal respiration and microbial biomass were correlated in forests but decoupled in grasslands and croplands, where microbial biomass depended on soil carbon. Forests had a higher ratio of fungi to bacteria than grasslands or croplands. Soil microbial communities in grasslands and croplands are likely carbon-limited in comparison with those in forests, and forests have a higher dominance of fungi indicating differences in microbial community composition. Notably, the often already-degraded soils of croplands could be more vulnerable to climate change than more natural soils. The provided maps show potentially vulnerable areas that should be explicitly accounted for in coming management plans to protect soil carbon and slow the increasing vulnerability of European soils to climate change.</p>
A novel big data mining framework for reconstructing large-scale daily MAIAC AOD across China from 2000 to 2020
<p>This dataset contains the mean reconstructed MAIAC AOD and mean percentage of coverage of reconstructed MAIAC AOD across China from 2000 to 2020. </p>
Large-scale supplemental feeding alters lay date and nest survival in Eastern Bluebirds but not in two species of chickadees
<p>Wild bird feeding is a popular and growing activity, with approximately half of households participating in nations including the United States, Canada, the United Kingdom, New Zealand, and Australia. Supplemental feeding can increase survival and reproductive success of birds (which is often a goal of supplemental feeding efforts), but it raises concerns about phenological mismatch, reduced clutch size, or increased risk of nest predation. Our objectives were to test whether access to supplemental food during the breeding season was correlated with (1) advanced egg-laying phenology, (2) increased clutch size, or (3) improved nest survival of 3 cavity-nesting species (Carolina Chickadee, <i>Poecile carolinensis</i>; Black-capped Chickadee, <i>P. atricapillus</i>; and<i> </i>Eastern Bluebird, <i>Sialia</i> <i>sialis</i>) at a large spatial scale (United States and Canada; 22 degrees latitude difference and 55 degrees longitude difference). We examined data from 24,528 nest attempts submitted to NestWatch from 2014–2019. For Eastern Bluebirds, birds with access to supplemental insects initiated clutches 5.83 (± 0.89 SE) days earlier than birds without access to food subsidies, while predicted nest survival was 5% greater for birds with access to supplemental insects (probability of nest success = 0.79, 95% CI = 0.77–0.81) when compared to birds without (0.74, 95% CI = 0.72–0.75). Clutch size of Eastern Bluebirds did not differ between birds with and without access to supplemental insects. For chickadees, supplemental feeding (of seeds, suet, insects, or fruit) was not correlated with phenology, clutch size, or nest survival. <span>Our results suggest that supplemental feeding of insects can be an effective tool for increasing nest survival in Eastern Bluebirds and potentially other food-limited insectivores. However, the efficacy of supplemental feeding for improving reproductive success varies across <a>taxa</a></span><span>. </span>Our results can help elucidate how wild bird feeding contributes to global phenomena such as earlier nesting, nest survival, and population <a>change</a>.</p>
High-Throughput-Methyl-Reading (HTMR) assay: A solution based on nucleotide methyl-binding proteins enables large-scale screening for DNA/RNA methyltransferases and demethylases
<p>Epigenetic therapy has significant potential for cancer treatment. However, few small potent molecules have been identified against DNA or RNA modification regulatory proteins. Current approaches for activity detection of DNA/RNA methyltransferases and demethylases are time-consuming and labor-intensive, making it difficult to subject them to high-throughput screening. Here, we developed a fluorescence polarization-based "High-Throughput Methyl Reading" (HTMR) assay to implement large-scale compound screening for DNA/RNA methyltransferases and demethylases-DNMTs, TETs, ALKBH5, and METTL3/METTL14. This assay is simple to perform in a mix-and-read manner by adding the methyl-binding proteins MBD1 or YTHDF1. The proteins can be used to distinguish FAM-labelled substrates or product oligonucleotides with different methylation statuses catalyzed by enzymes. Therefore, the extent of the enzymatic reactions can be coupled with the variation of FP binding signals. Furthermore, this assay can be effectively used to conduct a cofactor competition study. Based on the assay, we identified two natural products as candidate compounds for DNMT1 and ALKBH5. In summary, this study outlines a powerful homogeneous approach for high-throughput screening and evaluating enzymatic activity for DNA/RNA methyltransferases and demethylases that is cheap, easy, quick, and highly sensitive.</p>
Large-scale integration of single-cell transcriptomic data captures transitional progenitor states in mouse skeletal muscle regeneration
<p>Skeletal muscle repair is driven by the coordinated self-renewal and fusion of myogenic stem and progenitor cells. Single-cell gene expression analyses of myogenesis have been hampered by the poor sampling of rare and transient cell states that are critical for muscle repair, and do not inform the spatial context that is important for myogenic differentiation. Here, we demonstrate how large-scale integration of single-cell and spatial transcriptomic data can overcome these limitations. We created a single-cell transcriptomic dataset of mouse skeletal muscle by integration, consensus annotation, and analysis of 23 newly collected scRNAseq datasets and 88 publicly available single-cell (scRNAseq) and single-nucleus (snRNAseq) RNA-sequencing datasets. The resulting dataset includes more than 365,000 cells and spans a wide range of ages, injury, and repair conditions. Together, these data enabled identification of the predominant cell types in skeletal muscle, and resolved cell subtypes, including endothelial subtypes distinguished by vessel-type of origin, fibro/adipogenic progenitors defined by functional roles, and many distinct immune populations. The representation of different experimental conditions and the depth of transcriptome coverage enabled robust profiling of sparsely expressed genes. We built a densely sampled transcriptomic model of myogenesis, from stem cell quiescence to myofiber maturation and identified rare, transitional states of progenitor commitment and fusion that are poorly represented in individual datasets. We performed spatial RNA sequencing of mouse muscle at three time points after injury and used the integrated dataset as a reference to achieve a high-resolution, local deconvolution of cell subtypes. We also used the integrated dataset to explore ligand-receptor co-expression patterns and identify dynamic cell-cell interactions in muscle injury response. We provide a public web tool to enable interactive exploration and visualization of the data. Our work supports the utility of large-scale integration of single-cell transcriptomic data as a tool for biological discovery.</p>
A Large-scale Benchmark for Technical Debt Assessment
<p>This repository hosts the supplementary material of the paper entitled "A Large-scale Benchmark for Technical Debt Assessment". It comprises a very large-scale study on the Technical Debt of more than 55 million open-source Java files.</p>
An Exploratory Study on Faults in Web API Integration in a Large-Scale Payment Company: Appendix
<p>Appendix of our "An Exploratory Study on Faults in Web API Integration in a Large-Scale Payment Company: Appendix" paper.</p>
Dataset 2 for Large‐ and small‐scale geographic structures affecting genetic patterns across populations of an Alpine butterfly
<p>Understanding factors influencing patterns of genetic diversity and the population genetic structure of species is of particular importance in the current era of global climate change and habitat loss. These factors include the evolutionary history of a species as well as heterogeneity in the environment it occupies, which in turn can change across time. Most studies investigating spatio-temporal genetic patterns have focused on patterns across wide geographical areas rather than local variation, but the latter can nevertheless be important particularly in topographically complex areas. Here we consider these issues in the Sooty Copper butterfly (<i>Lycaena tityrus</i>) from the European Alps, using genome-wide SNPs identified through RADseq. We found strong genetic differentiation within the Alps with four genetic clusters, indicating western, central, and eastern refuges, and a strong reduction of genetic diversity from west to east. This reduction in diversity may suggest that the southwestern refuge was the largest one in comparison to other refuges. Also, the high genetic diversity in the West may result from (1) admixture of different western refuges, (2) more recent demographic changes, or (3) introgression of lowland <i>L. tityrus</i> populations. At small spatial scales, populations were structured by several landscape features and especially by high mountain ridges and large river valleys. We detected 36 outlier loci likely under altitudinal selection, including several loci related to membranes and cellular processes. We suggest that efforts to preserve alpine <i>L. tityrus </i>should focus on the genetically diverse populations in the western Alps, and that the dolomite populations should be treated as genetically distinct management units, since they appear to be currently more threatened than others. This study demonstrates the usefulness of SNP-based approaches for understanding patterns of genetic diversity, gene flow and selection in a region that is expected to be particularly vulnerable to climate change.</p>
Limited seed dispersal shapes fine-scale spatial genetic structure in a Neotropical dioecious large-seeded palm
<p><span>Seed and pollen dispersal contribute to gene flow and shape the genetic patterns of plants over fine spatial scales. We inferred fine-scale spatial genetic structure (FSGS) and estimated realized dispersal distances in Phytelephas aequatorialis, a Neotropical dioecious large-seeded palm. We aimed to explore how seed and pollen dispersal shape this genetic pattern in a focal population. For this purpose, we genotyped 138 seedlings and 99 adults with 20 newly developed microsatellite markers. We tested if rodent-mediated seed dispersal has a stronger influence than insect-mediated pollen dispersal in shaping FSGS. We also tested if pollen dispersal was influenced by the density of male palms around mother palms in order to further explore this ecological process in large-seeded plants. Rodent-mediated dispersal of these large seeds occurred mostly over short distances (mean 34.76 ± 34.06 m) while pollen dispersal distances were two times higher (mean 67.91 ± 38.29 m). The spatial extent of FSGS up to 35 m and the fact that seed dispersal did not increase the distance at which male alleles disperse suggest that spatially limited seed dispersal is the main factor shaping FSGS and contributes only marginally to gene flow within the population. Pollen dispersal distances depended on the density of male palms, decreasing when individuals show a clumped distribution and increasing when they are scattered. Our results show that limited seed dispersal mediated by rodents shapes FSGS in P. aequatorialis, while more extensive pollen dispersal accounts for a larger contribution to gene flow and may maintain high genetic diversity.</span></p>
Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation (Unlabeled Data Part I)
<p>Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampered by the lack of a large-scale benchmark from diverse clinical scenarios. Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods. To mitigate the limitations, we present AMOS, a large-scale, diverse, clinical dataset for abdominal organ segmentation. AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs, providing challenging examples and test-bed for studying robust segmentation algorithms under diverse targets and scenarios. We further benchmark several state-of-the-art medical segmentation models to evaluate the status of the existing methods on this new challenging dataset. We have made our datasets, benchmark servers, and baselines publicly available, and hope to inspire future research. The paper can be found at https://arxiv.org/pdf/2206.08023.pdf</p> <p>In addition to providing the labeled 600 CT and MRI scans, we expect to provide 2000 CT and 1200 MRI scans without labels to support more learning tasks (semi-supervised, un-supervised, domain adaption, ...). The link can be found in:</p> <ul> <li><a href="https://zenodo.org/deposit/7262581">labeled data (500CT+100MRI)</a></li> <li><a href="https://zenodo.org/record/7262757#.Y2iSQ9JBwYs">unlabeled data Part I (900CT)</a></li> <li><a href="https://zenodo.org/record/7295661#.Y2iR_9JBwYs">unlabeled data Part II (1100CT)</a> (Now there are 1000CT, we will replenish to 1100CT)</li> <li><a href="https://zenodo.org/record/7295816">unlabeled data Part III (1200MRI)</a></li> </ul> <p>if you found this dataset useful for your research, please cite:</p> <blockquote> <pre>@article{ji2022amos, title={AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation}, author={Ji, Yuanfeng and Bai, Haotian and Yang, Jie and Ge, Chongjian and Zhu, Ye and Zhang, Ruimao and Li, Zhen and Zhang, Lingyan and Ma, Wanling and Wan, Xiang and others}, journal={arXiv preprint arXiv:2206.08023}, year={2022} }</pre> </blockquote>
Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation (Unlabeled Data Part II)
<p>Despite the considerable progress in automatic abdominal multi-organ segmentation from CT/MRI scans in recent years, a comprehensive evaluation of the models' capabilities is hampered by the lack of a large-scale benchmark from diverse clinical scenarios. Constraint by the high cost of collecting and labeling 3D medical data, most of the deep learning models to date are driven by datasets with a limited number of organs of interest or samples, which still limits the power of modern deep models and makes it difficult to provide a fully comprehensive and fair estimate of various methods. To mitigate the limitations, we present AMOS, a large-scale, diverse, clinical dataset for abdominal organ segmentation. AMOS provides 500 CT and 100 MRI scans collected from multi-center, multi-vendor, multi-modality, multi-phase, multi-disease patients, each with voxel-level annotations of 15 abdominal organs, providing challenging examples and test-bed for studying robust segmentation algorithms under diverse targets and scenarios. We further benchmark several state-of-the-art medical segmentation models to evaluate the status of the existing methods on this new challenging dataset. We have made our datasets, benchmark servers, and baselines publicly available, and hope to inspire future research. The paper can be found at https://arxiv.org/pdf/2206.08023.pdf</p> <p>In addition to providing the labeled 600 CT and MRI scans, we expect to provide 2000 CT and 1200 MRI scans without labels to support more learning tasks (semi-supervised, un-supervised, domain adaption, ...). The link can be found in:</p> <ul> <li><a href="https://zenodo.org/deposit/7262581">labeled data (500CT+100MRI)</a></li> <li><a href="https://zenodo.org/record/7262757#.Y2iSQ9JBwYs">unlabeled data Part I (900CT)</a></li> <li><a href="https://zenodo.org/record/7295661#.Y2iR_9JBwYs">unlabeled data Part II (1100CT)</a> (Now there are 1000CT, we will replenish to 1100CT)</li> <li><a href="https://zenodo.org/record/7295816">unlabeled data Part III (1200MRI)</a></li> </ul> <p>if you found this dataset useful for your research, please cite:</p> <blockquote> <pre>@article{ji2022amos, title={AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation}, author={Ji, Yuanfeng and Bai, Haotian and Yang, Jie and Ge, Chongjian and Zhu, Ye and Zhang, Ruimao and Li, Zhen and Zhang, Lingyan and Ma, Wanling and Wan, Xiang and others}, journal={arXiv preprint arXiv:2206.08023}, year={2022} </pre> </blockquote>
Quantitative monitoring of diverse fish communities on a large scale combining eDNA metabarcoding and qPCR
<p>eDNA metabarcoding is an effective method for studying fish communities but allows only an estimation of relative species abundance (density / biomass). Here, we combine metabarcoding with an estimation of the total abundance of eDNA amplified by our universal marker (teleo) using a qPCR approach to infer the absolute abundance of fish species. We carried out a 2,850 km eDNA survey within the Danube catchment using a spatial integrative sampling protocol coupled with traditional electrofishing for fish biomass and density estimation. Total fish eDNA concentrations and total fish abundance were highly correlated. The correlation between eDNA concentrations per taxon and absolute specific abundance was of comparable strength when all sites were pooled and remained significant when the sites were considered separately. Furthermore, a non-linear mixed model showed that species richness was underestimated when the amount of teleo-DNA extracted from a sample was below a threshold of 0.65.106 copies of eDNA. This result, combined with the decrease in teleo-DNA concentration by several orders of magnitude with river size, highlights the need to increase sampling effort in large rivers. Our results show a comprehensive description of longitudinal changes in fish communities and underline our combined metabarcoding/qPCR approach for biomonitoring and bioassessment surveys when a rough estimate of absolute species abundance is sufficient.</p>
Incorporating the effect of large-scale vertical motion on convection through convective mass flux adjustment in E3SMv2
<p>Simulation data for the manuscript entitled of "Incorporating the effect of large-scale vertical motion on convection through convective mass flux adjustment in E3SMv2". </p>
Supporting data for "The time scale of shallow convective self-aggregation in large-eddy simulations is sensitive to numerics"
<p>Numerical settings, routines and post-processed data used to generate the figures presented in "The time scale of shallow convective self-aggregation in large-eddy simulations is sensitive to numerics", manuscript submitted to Journal of Advances in Modeling Earth Systems. This version is an update after accounting for comments of three reviewers to the submitted manuscript.</p>
Behavioral responses of a large, heat-sensitive mammal to climatic variation at multiple spatial scales
<p>1. Climate warming creates energetic challenges for endothermic species by increasing metabolic and hydric costs of thermoregulation. Although endotherms can invoke an array of behavioral and physiological strategies for maintaining homeostasis, the relative effectiveness of those strategies in a climate that is becoming both warmer and drier is not well understood.</p> <p>2. In accordance with the heat dissipation limit theory, which suggests that allocation of energy to growth and reproduction by endotherms is constrained by the ability to dissipate heat, we expected that patterns of habitat use by large, heat-sensitive mammals across multiple scales are critical for behavioral thermoregulation during periods of potential heat stress and that they must invest a large portion of time to maintain heat balance.</p> <p>3. To test our predictions, we evaluated mechanisms underpinning the effectiveness of bed sites for ameliorating daytime heat loads and potential heat stress across the landscape while accounting for other factors known to affect behavior. We integrated detailed data on microclimate and animal attributes of moose <em>Alces</em> <em>alces</em>, into a biophysical model to quantify costs of thermoregulation at fine and coarse spatial scales.</p> <p>4. During summer, moose spent an average of 67.8% of daylight hours bedded, and selected bed sites and home ranges that reduced risk of experiencing heat stress. For most of the day, shade could effectively mitigate the risk of experiencing heat stress up to 10°C, but at warmer temperatures (up to 20℃) wet soil was necessary to maintain homeostasis via conductive heat loss. Consistent selection across spatial scales for locations that reduced heat load underscores the importance of the thermal environment as a driver of behavior in this heat-sensitive mammal.</p> <p>5. Moose in North America have long been characterized as riparian-obligate species because of their dependence on woody plant species for food. Nevertheless, the importance of dissipating endogenous heat loads conductively through wet soil suggests riparian habitats also are critical thermal refuges for moose. Such refuges may be especially important in the face of a warming climate in which both high environmental temperatures and drier conditions will likely exacerbate limits to heat dissipation, especially for large, heat-sensitive animals.</p>
Data from "Molecular Mapping of DR Tau's Protoplanetary Disk, Envelope, Outflow, and Large-Scale Spiral Arm"
<p>Data associated with Huang et al., 2023, "Molecular Mapping of DR Tau's Protoplanetary Disk, Envelope, Outflow, and Large-Scale Spiral Arm," ApJ, 943, 107</p> <p>The raw data can be obtained by requesting data from program W20BE (PI: J. Huang) from the NOEMA archive. </p> <p><strong>Images</strong></p> <p>images.tar: FITS files of image cubes and moment maps as shown in Figs. 2, 3, 5, 9, and 10 (see also finalimagingscript.py)</p> <p><strong>Spectra</strong></p> <p>spectra.tar: ASCII files of spectra shown in Figs. 1 and 9 (see also finalimagingscript.py) </p> <p><strong>Measurement sets (CASA format)</strong></p> <p>drtau_LINENAME_corrected.ms.tar: Measurement set for a given line, corresponding to drtau_LINENAME_selfcal-contsub.uvt in lines_contsub_uvt.tar </p> <p>drtau_ui_cont_corrected.ms.tar: Continuum measurement set corresponding to the UI baseband, generated from w20be-ui-cont-selfcal.uvt in continuum_uvt.tar </p> <p><strong>UV tables (GILDAS format)</strong></p> <p>LR_uvt.tar: Pipeline-calibrated UV tables of low-resolution data (see w20be-tables-LR.clic)</p> <p>HR_uvt.tar: Pipeline-calibrated UV tables of high-resolution data (see w20be-tables-HR.clic)</p> <p>continuum_uvt.tar: Self-calibrated, spectrally averaged continuum UV tables generated from LR_uvt.tar</p> <p>lines_contsub_uvt.tar: Self-calibrated, continuum-subtracted line UV tables generated from the UV tables in HR_uvt.tar</p> <p><strong>Scripts</strong></p> <p>w20be-tables-LR.clic: CLIC script used to output UV tables of low-resolution data from the pipeline-calibrated data (output contained in LR_uvt.tar)</p> <p>w20be-tables-HR.clic: CLIC script used to output UV tables of high-resolution data from the pipeline-calibrated data (output contained in HR_uvt.tar)</p> <p>uvfitstoms.py: Script to export uvfits files to measurement sets and to correct the metadata in the measurement sets </p> <p>finalimagingscript.py: CASA script used to generate imaging products in images.tar and spectra in spectra.tar </p> <p><strong>Other:</strong></p> <p>calib.tar: Files output by NOEMA pipeline </p> <p> </p>
Large-scale survey of excitatory synapses reveals sublamina-specific and asymmetric synapse disassembly patterns in a neurodegenerative circuit
<p>Dataset associated with the manuscript titled "<strong>Large-scale survey of excitatory synapses reveals sublamina-specific and asymmetric synapse disassembly patterns in a neurodegenerative circuit"</strong></p>
Appendix of Large-Scale Evaluation of Method-Level Bug Localization with FinerBench4BL
<p>Appendix of "Large-Scale Evaluation of Method-Level Bug Localization with FinerBench4BL"</p> <p> </p> <p>FinerBench4BL is available at the following URL</p> <p><a href="https://github.com/salab/FinerBench4BL">https://github.com/salab/FinerBench4BL</a></p>
Long-term responses to large-scale disturbances: Spatiotemporal variation in gastropod populations and communities
<p>The Anthropocene is characterized by complex, primarily human-generated, disturbance regimes that include combinations of long-term press (e.g. climate change, pollution) and episodic pulse (e.g. cyclonic storms, floods, wildfires, land use change) disturbances. Within any regime, disturbances occur at multiple spatial and temporal scales, creating complex and varied interactions that influence spatiotemporal dynamics in the abundance, distribution, and biodiversity of organisms. Moreover, responses to disturbance are context-dependent, with the legacies of previous disturbances affecting responses to ensuing perturbations. We use three decades of annual data to evaluate the effects of repeated pulse disturbances and global warming on gastropod populations and communities in Puerto Rico at multiple spatial scales. More specifically, we quantify (1) the relative importance of large-scale and small-scale aspects of disturbance on variation in abundance, biodiversity, and species composition; and (2) the spatial scales at which populations and communities integrate information in the spatially heterogenous environments created by disturbances. Gastropods do not exhibit consistent decreases in abundance or biodiversity in association with global warming: abundance for many species has increased over time and species richness does not evince a temporal trend. Nonetheless, gastropods are sensitive to hurricane severity, spatial environmental variation, and successional trajectories of the flora. In addition, they exhibit context-dependent (i.e. legacy effects) responses that are scale-dependent. The Puerto Rican biota has evolved in a disturbance-mediated system. This historical exposure to repeated, severe hurricane-induced disturbances has imbued the biota with high resistance and resilience to the current disturbance regime, resulting in an ability to persist or thrive under current environmental conditions. Nonetheless, these ecosystems may yet be threatened by worsening direct and indirect effects of climate change. In particular, more frequent and severe hurricanes may prevent the establishment of closed-canopy forests, negatively impacting populations and communities that rely on these habitats.</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.