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2,015 results for “context”
Fig. 6 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive
Fig. 6: Scatterplot matrices for Large (A) and Linear (B) FM functions.
Fig. 8 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive
Fig. 8: High values of the FP c index as estimated by Local Moran's I test.
Fig. 5 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive
Fig. 5: Spatial representation of coastal vessels activity indexes (Ac).
Fig. 4 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive
Fig. 4: Spatial representation of the Coastal fishery suitability index (Sc).
Fig. 3 in Multi-Criteria Decision Analysis as a tool to extract fishing footprints: application to small scale fisheries and implications for management in the context of the Maritime Spatial Planning Directive
Fig. 3: Spatial representation of the criteria ranking taken into account in MCDA.
Scaling up video: from ePLANET region to national context
<p><span>The ePLANET scaling-up videos have been designed as a key material to highlight the added value of using ePLANET platform and governance strategies within the pilot territories, and so attract other local and regional authorities at national level on the adoption of ePLANET outcomes.</span></p> <p><span>In total, 3 scaling-up videos have been produced, each of them tailored to the specific states of pilot regions. In particular:</span></p> <ul> <li><span>Czech Republic (Zlín region pilot)</span></li> <li>Catalonia (Girona region pilot)</li> <li>Greece (Crete island pilot)</li> </ul> <p><span>The 3 videos have a common initial section, combining motion graphics together with a voice-over presentation (in the national language of each pilot region), followed by a tailored section with two short testimonials from the addressed pilot region.</span></p> <p><span>The common initial section has the format of a storytelling animated by motion-graphics. The storytelling highlights the added value of collaboration amongst local authorities to improve the capacities, decision-making and investment opportunities related to the deployment of Energy Action plans.</span></p> <p> </p>
Linking individual and species-level leaf traits with ontogenetic development stage to explain tree performance under competition and environmental contexts
<p><span>To verify how species traits and individual traits link ontogenetic size, external biotic and abiotic factors to influence tree performance. In a temperate natural forest in northeastern China, we measured dynamic performance, size, as well as competition, topography, and soil variables as biotic and abiotic variables for all 1320 trees of 17 species in 62 monitoring plots from 2010-2020. For each individual tree, we also measured five typical functional traits representing leaf size and elemental content: leaf area, specific leaf area, leaf dry matter content, leaf nitrogen content, and leaf carbon : nitrogen ratios. These traits are not only strongly associated with performance, but trade-offs between traits have previously been shown to express plant acquisitive-conservative strategy characteristics. Reconceptualized based on previous understanding of trait-based approach (Fig. 1). We first tested the direct explanatory effects of species traits and individual traits on performance in multifactorial contexts.</span> <span>We first tested the direct explanatory effects of species traits and individual traits on performance in multifactorial contexts. Subsequently, we analyzed the moderating and mediating effects of these two levels of traits in explaining ontogenetic size, external competition, and environmental influences on performance. The following three questions were posed in response to the results:</span></p> <p><em><span>QI: Do species and individual traits differ in directly explaining performance in a multifactor context that includes ontogenetic size, external biotic and abiotic factors?</span></em></p> <p><em><span>QII: How species and individual traits explain the effect of ontogenetic size on performance</span> </em><em><span>by moderating and mediating effects.</span></em></p> <p><em><span>QIII: Can traits at the species and individual level influence competition- and environment-performance relationships</span> </em><em><span>through trait-based approaches? Does ontogenetic size work jointly with traits at different levels in this process?</span></em></p>
Data from: Native plant traits and invasibility of restored communities: Importance of environmental context and trait hierarchies
<p>During community assembly, theory predicts trait convergence among species due to environmental filtering, and trait divergence due to biotic filtering. Learning how traits of non-native species enable them to overcome these filters informs the process of invasion.<strong> </strong>We manipulated mixtures of native plants in a large restoration project in Southern California that was initially dominated by non-native annual grasses and forbs but was restored to a mixture of native shrubs, grasses, and forbs. We measured subsequent establishment and performance by three non-native species (<em>Brassica nigra</em>, <em>Salsola tragus,</em> and <em>Sonchus oleraceus</em>) on N- and S-facing slopes to investigate relationships between the abiotic environment, native community composition, and invasibility in the context of trait-driven ecological filters. We then evaluated which community metrics influenced invader performance and tested whether relationships between invader performance and community-weighted traits varied depending on slope aspect. Plots with slow-growing native shrubs contained less of the fast-growing invasive, <em>Brassica nigra</em>. Invasibility was greatest in native communities restored with native grass and on N-facing slopes. Traits of individual species indicated relatively greater biotic as compared to environmental filtering. For example, abundance of <em>Phacelia cicutaria</em>, a native annual with traits most like invasive <em>Brassica nigra</em>, was negatively correlated with abundance of that invasive. Several community-weighted trait metrics were also significantly related to invasibility, but the direction of the relationship varied depending on the specific functional trait, community-weighted trait measure (mean or dispersion), invader, and slope aspect. The native functional group that was more likely to prevent invasion by non-native annual species (native shrubs) was different from the single species that most prevented invasion (a native forb). In restoration planning, functional groups and trait values of individual species may point to different mixtures of native species that prevent invasion by specific non-natives, depending on priority effects. Understanding the priority effects and trait hierarchies that underly biotic filtering appears critical to interpreting community-weighted traits and their complexity of responses to environmental variation in space and time. </p>
CATCH-EyoU: Representation of the EU and Youth Active Citizenship in Educational Contexts: Cross-national Textbook Analysis
<p>The data set contains the results of the quantitative and qualitative content analysis of local textbooks from different subjects (e.g. ESL, EFL, History, Social Sciences, Civic Education) at ISCED 3 level (upper secondary schools as well as vocational schools). Data collection was carried out using a specifically designed analytical grid (Ribeiro; Ferreira & Menezes, 2016). The grid was tested and applied by national research teams (Portugal, Czechia, Estonia, Germany, Italy and Sweden) participating to Catch-EyoU project – each textbook analysis implied filling one grid. In total, 34 textbooks were analysed across the participating countries. All grids include excerpts of the textbooks (text or images, whenever legally possible). Quantitative analysis data and bibliographical metadata are also included.</p> <p>Data collection and analysis was aimed at getting an overall picture of school texts, including the analysis of number of paragraphs, pages and exercises about topics such as the EU, active citizenship, intercultural awareness, political involvement.</p> <p>Although textbook analysis is relatively common and there are other European projects that include it, the data analysis grid is original (and relatively innovative in the area) as it directly relates to the project topics.</p> <p>The potential users can be other researchers who might be interested not only in the grid but also in the analysis itself, either to use it with other textbooks or compare it with existing research or with similar data collected in different countries; teachers might also find it useful to explore the analysis as a basis for their practice. Also other stakeholders may be interested in reanalyzing our data for comparative aims.</p>
Replication Package: Developer Reading Behavior while Summarizing Java Methods: Size and Context Matters
<p>A replication package for the study presented in the ICSE 2019 paper titled "Developer Reading Behavior while Summarizing Java Methods: Size and Context Matters" by Abid, Sharif, Dragan, Alrasheed, and Maletic</p>
Data from: Are drivers of microbial diatom distributions context dependent in human impacted and pristine environments? in Ecological Applicatios (2019)
<p>Species occurrence (0/1) and environmental data from research article "Are drivers of microbial diatom distributions context dependent in human impacted and pristine environments?" in Ecological Applications (2019). </p> <p>Please see more details in the readme-file and the original article. </p>
Replication Package for "How Developers Engage with Static Analysis Tools in Different Contexts"
<p>This is the replication package for the paper "How Developers Engage with Static Analysis Tools in Different Contexts".</p> <p>We include all the artifacts necessary to replicate the results obtained in our paper. Specifically, we provide (i) the survey questions together with all the valid answers we received including the demographics of our respondents, (ii) the most relevant statements that we extracted from the interviews including the demographics of our interviewees, (iii) the results of the card sorting performed on the development activities where our participants adopt Static Analysis Tools, (iv) all the data related to Krippendorff’s Alpha calculation for the performed card sorting, and (v) mapping of ASATs to the "rules" categories defined by Novak et al. (2010) and script for calculating occurrence, definition, and enforcement of the different ASAT types together with input and output data. Furthermore, we include the list of links to Reddit posts and inspected open-source projects together with their inspection data and the scripts for computing the inter-rater agreement during the inspection. Finally, we provide the Github features computed for each project and script for generating the sets of projects.</p>
BackFlow: Backward Context-sensitive Flow Reconstruction of Taint Analysis Results
<p>This archive contains the details of the experimental results reported in the VMCAI 2020 paper, and instruction on how to reproduce these results.</p>
Text-fig. 2. Date calibration of skull from Moča (Komárno district, southern Slovakia). in A Late Upper Palaeolithic Skull From Moča (The Slovak Republic) In The Context Of Central Europe
Text-fig. 2. Date calibration of skull from Moča (Komárno district, southern Slovakia).
Fig. 1 in New evidence on the taphonomic context of the Ediacaran Pteridinium
Fig. 1. Location of the Kuibis and Schwarzrand Subgroups in Namibia.
Dataset 1. Functional genomic profiling of O-GlcNAc reveals its context-specific interplay with RNA polymerase II.
<p>This dataset is used in the bioformatic methods of the article <strong>Functional genomic profiling of O-GlcNAc reveals its context-specific interplay with RNA polymerase II </strong>(doi: 10.1186/s13059-025-03537-2). The corresponding code can be found in the repository https://github.com/descostesn/chromglycomethods.git</p>
Data Analysis for Context- and sex-dependent links between sire sexual success and offspring pathogen resistance
<p>Data Analysis for "Context- and sex-dependent links between sire sexual success and offspring pathogen resistance"</p> <p>By Aijuan Liao and Tadeusz J. Kawecki</p>
Specifying cellular context of transcription factor regulons for exploring context-specific gene regulation programs
<p>This repository contains the raw and processed files used in Minaeva et al. 2024.</p> <p>In this version, we have revised the regulon construction pipeline and expanded the dataset to cover 40 common cell lines.</p> <p>The code used to generate these files is available at <a href="https://github.com/LappalainenLab/chip_seq_regulons" target="_new" rel="noreferrer">GitHub - LappalainenLab/chip_seq_regulons</a>.</p> <p>The descriptions of the files contained within each subdirectory are as follows:</p> <h3>1-dataset_stats</h3> <ul> <li><code>per_gene_stats_{approach}_{cell_line}.tsv</code>: Number of TFs regulating a gene according to the respective approach (S2Mb, M2Kb, or S2Kb) in a given cell line.</li> <li><code>per_tf_stats_{approach}_{cell_line}.tsv</code>: Number of target genes regulated by a TF according to the respective approach (S2Mb, M2Kb, or S2Kb) in a given cell line.</li> </ul> <h3>1-network_enrichment</h3> <ul> <li><code>enrich_scores_remap_all_tfs_K562.tsv</code>: Results of fitting logistic regression for testing the enrichment of the K562 regulon in other biological networks (PPI, coexpression, experimental trans-networks).</li> </ul> <h3>2-plot_decoupler_comparison_benchmark_across_cells</h3> <ul> <li><code>{cell_line}_comparison_benchmark.tsv</code>: Results of benchmarking S2Mb, M2Kb, CollecTri, Dorothea, ChIP-Atlas, RegNet, and TRRUST regulons using the decoupler package and the KnockTF database. Cell lines considered are K562, HepG2, and MCF7 (see Methods for benchmarking pipeline details).</li> </ul> <h3>2-plot_decoupler_filter_benchmark_across_methods</h3> <ul> <li><code>{cell_line}_filtering_benchmark.tsv</code>: Results of benchmarking S2Mb, M2Kb, and S2Kb regulons with different filters applied using the decoupler package and the KnockTF database. Cell lines considered are K562, HepG2, and MCF7 (see Methods for benchmarking pipeline details).</li> </ul> <h3>3-tf_activity</h3> <ul> <li><code>aml_k562_activity_{regulon}_sc.tsv</code>: Results of TF activity analysis based on a respective regulon between healthy hematopoietic stem cells (HSCs) and abnormal AML progenitor cells following the decoupler pipeline. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>aml_activity_estimates_hsc_sc.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between healthy HSCs and abnormal AML progenitor cells across regulons.</li> <li><code>aml_dhsc_ahsc_activity_{regulon}_sc.tsv</code>: Results of TF activity analysis based on a respective regulon between leukemic activated and dormant HSCs following the decoupler pipeline. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>aml_activity_estimates_dhsc_ahsc_sc.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between leukemic activated and dormant HSCs across regulons.</li> <li><code>bc_bas_activity_{regulon}.tsv</code>: Results of TF activity analysis based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from basal breast cancer following the decoupler pipeline. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_activity_estimates_bas.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between healthy epithelial breast cells and malignant epithelial cells from basal breast cancer across regulons.</li> <li><code>bc_lum_activity_{regulon}.tsv</code>: Results of TF activity analysis based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from luminal type A breast cancer following the decoupler pipeline. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_activity_estimates_lum.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between healthy epithelial breast cells and malignant epithelial cells from luminal type A breast cancer across regulons.</li> <li><code>hep_activity_{regulon}.tsv</code>: Results of TF activity analysis based on a respective regulon between neoplastic and healthy liver cells following the decoupler pipeline. Regulons considered are HepG2-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>hep_activity_estimates.tsv</code>: Summary of the TF activity analysis for statistically significantly dysregulated TFs between neoplastic and healthy liver cells across regulons.</li> </ul> <h3>3-tf_disease_enrichment</h3> <ul> <li><code>aml_{database}_enrich_{regulon}_hsc_sc.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between healthy HSCs and abnormal AML progenitor cells following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, OMIM, and KEGG. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>aml_{database}_enrich_{regulon}_dhsc_ahsc_sc.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between leukemic activated and dormant HSCs following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, OMIM, and KEGG. Regulons considered are K562-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_{database}_enrich_{regulon}_bas.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from basal breast cancer following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, and OMIM. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>bc_{database}_enrich_{regulon}_lum.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between healthy epithelial breast cells and malignant epithelial cells from luminal type A breast cancer following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, and OMIM. Regulons considered are MCF7-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> <li><code>hep_{database}_enrich_{regulon}.tsv</code>: Results of enrichment analysis of dysregulated TFs identified based on a respective regulon between neoplastic and healthy liver cells following the decoupler pipeline. Databases considered are COSMIC, DisGeNet, OMIM, and KEGG. Regulons considered are HepG2-specific ChIP-Atlas and M2Kb regulons, and generalized CollecTri regulon.</li> </ul> <h3>regulons</h3> <ul> <li><code>{cell_line}_regulon.tsv</code>: S2Mb, M2Kb, and S2Kb regulons generated in this study with all acquired annotations (see Methods for details).</li> </ul> <p>External regulons used for comparison. Cell lines considered are K562, HepG2, MCF7, and GM12878:</p> <ul> <li><code>ChIP-Atlas_target_genes_{cell_line}.tsv</code>: Customized ChIP-Atlas regulons (see Methods for details).</li> <li><code>Revised_Supplemental_Table_S3_Normal.csv</code>: Dorothea regulon collected from supplementary materials of Garcia-Alonso et al. (2019).</li> </ul> <h3>s3-network_enrichment</h3> <ul> <li><code>enrich_scores_remap_all_tfs_{cell_line}.tsv</code>: Results of fitting logistic regression for testing the enrichment of cell-line-specific regulons in PPI networks (see Methods and corresponding GitHub repository for details). Cell lines considered are K562, HepG2, MCF7, and GM12878.</li> </ul> <p> </p>
Definition of the terms verification, validation, evaluation and benchmarking for use in the climate model context
<p>Schematic definition of the terms Verification, Validation, Evaluation and Benchmarking for use in the climate model context. Note that although through benchmarking some kind of ranking can be performed based on the chosen metric and selected observations, this is by far not a generally applicable ranking valid for all metrics, all realms and all possible observational references.</p>
Data from: Underlying mechanisms and ecological context of variation in exploratory behavior of the Argentine ant, Linepithema humile
Uncovering how and why animals explore their environment is fundamental for understanding population dynamics, the spread of invasive species, species interactions, etc. In social animals, individuals within a group can vary in their exploratory behavior, and the behavioral composition of the group can determine its collective success. Workers of the invasive Argentine ant (Linepithema humile) exhibit individual variation in exploratory behavior, which affects the colony's collective nest selection behavior. Here, we examine the mechanisms underlying this behavioral variation in exploratory behavior and determine its implications for the ecology of this species. We first establish that individual variation in exploratory behavior is repeatable and consistent across situations. We then show a relationship between exploratory behavior and the expression of genes that have been previously linked with other behaviors in social insects. Specifically, we found a negative relationship between exploratory behavior and the expression of the foraging (Lhfor) gene. Finally, we determine how colonies allocate exploratory individuals in natural conditions. We found that ants from inside the nest are the least exploratory individuals, whereas workers on newly formed foraging trails are the most exploratory individuals. Furthermore, we found temporal differences throughout the year: in early-mid spring, when new resources emerge, workers are more exploratory than at the end of winter, potentially allowing the colony to find and exploit new resources. These findings reveal the importance of individual variation in behavior for the ecology of social animals.
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.