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3,101 results for “Table”
The relative influence of catchment and site variables on fish and macroinvertebrate richness in Cerrado biome streams. Supplemental Materials Table SM1
<p>Table SM 1. Correlation among all environmental varibles</p>
Table S1. Differentially expressed genes during apical shoot development in Pinus canariensis
<p>Differentially Expressed Genes after time-course analysis during apical shoot development and transition from primary to secondary growth in the Canary Island pine (<em>Pinus canariensis</em>). This table includes information about the clusters in which transcripts were included according to their expression profiles, the name of the transcripts, the functional description of transcripts after BLASTx search against the Viridiplantae section of the NCBI RefSeq, the p-value adjusted by FDR of the gene expression analysis using MaSigPro, and the length of transcripts.</p>
Supplementary Figures and Tables - Diop et al. 2020
<p>This is supplementary Figures and Tables of <strong>:</strong> Diop, M. M, Chandre, F., Rossignol, M., Porciani, A., Château, M., Moiroux, N. and Pennetier, C. (2020). Sub-lethal insecticide exposure affects host biting efficiency of Kdr-resistant <em>Anopheles gambiae</em>. bioRxiv 653980, ver 4 peer-reviewed and recommended by PCI Zoology. doi: 10.1101/653980</p>
Nativ and Turowski. raw data Table 2
<p>Raw data used in the submitted paper Nativ and Turowski. See Table 2 therein. </p>
Cluster-based Table Detection Dataset
<p>This data set contains PDF segments and document features, combined with a label whether a segment is part of a table or not.</p> <p>The contained features are:</p> <ul> <li>file: Corresponding PDF file name</li> <li>page: Page where the cluster is located, starting with 0</li> <li>bbox: Bounding box of the cluster, stored as (x_0,x_1,y_0,y_1)</li> <li>text: This information had to be removed because it can be confidential.</li> <li>n_nodes: Number of layout elements in the cluster</li> <li>approx_size: Approximate number of cells when assuming a tabular cluster structure</li> <li>tabular_fill_score: Percentage of filled cells. This is calculated by building an artificial grid over the cluster and set the cells which would be filled relative to the maximal possible number, namely the approx_size.</li> <li>loop_score: Percentage of loops present in a cluster, relative to the maximal possible number.</li> <li>rectangle_score: Percentage of unique rectangles in a cluster, relative to the maximal possible number (which would be one rectangle per element)</li> <li>x_sparsity_abs: Average length of horizontal edges in a cluster</li> <li>x_sparsity_rel: Average length of horizontal edges in a cluster (i.e. x_sparsity_abs), relative to the horizontal sparsity the same page</li> <li>font_size_entropy: Shannon entropy of the font sizes in a cluster</li> <li>font_name_entropy: Shannon entropy of the font names in a cluster</li> <li>bold_pct: Percentage of bold texts in a cluster</li> <li>italic_pct: Percentage of italic texts in a cluster</li> <li>font_size_entropy_doc: Shannon entropy of the font sizes in a document</li> <li>font_name_entropy_doc: Shannon entropy of the font names in a document</li> <li>bold_pct_doc: Percentage of bold texts in a document</li> <li>italic_pct_doc: Percentage of italic texts in a document</li> <li>font_size_entropy_diff: Deviation of the font size entropy of a cluster (i.e. font_size_entropy) compared to the corresponding measurement on document-level (i.e. font_size_entropy_doc)</li> <li>font_name_entropy_diff: Deviation of the font name entropy of a cluster (i.e. font_name_entropy) compared to the corresponding measurement on document-level (i.e. font_name_entropy_doc)</li> <li>bold_pct_diff: Deviation of the percentage of bold texts in a cluster (i.e. bold_pct) compared to the corresponding measurement on document-level (i.e. bold_pct_doc)</li> <li>italic_pct_doc_diff: Deviation of the percentage of italic texts in a cluster (i.e. italic_pct) compared to the corresponding measurement on document-level (i.e. italic_pct_doc)</li> <li>is_table: Label indicating with 1 that a cluster contains pure table content and 0 otherwise</li> </ul>
Table S1. Unique set of pncA alleles among MDR+PZA-R isolates reported by Mansjö et al
<p>The unique set of pncA alleles among MDR PZA-R isolates reported by Mansjö & colleagues https://pubmed.ncbi.nlm.nih.gov/28559517/</p>
Spectral Upsampling Coefficient Tables - Jakob and Hanika. (2019)
<p><strong>Source URL</strong>: <a href="https://www.rit.edu/cos/colorscience/re_AsanoObserverFunctions.php">https://rgl.epfl.ch/publications/Jakob2019Spectral</a><br> <strong>Source DOI</strong>: <a href="https://www.researchgate.net/deref/http%3A%2F%2Fdx.doi.org%2F10.1111%2Fcgf.13626">10.1111/cgf.13626</a></p> <p><strong>Abstract</strong></p> <p>We present a versatile technique to convert textures with tristimulus colors into the spectral domain, allowing such content to be used in modern rendering systems. Our method is based on the observation that suitable reflectance spectra can be represented using a low-dimensional parametric model that is intrinsically smooth and energy-conserving, which leads to significant simplifications compared to prior work. The resulting spectral textures are compact and efficient: storage requirements are identical to standard RGB textures, and as few as six floating point instructions are required to evaluate them at any wavelength. Our model is the first spectral upsampling method to achieve zero error on the full sRGB gamut. The technique also supports large-gamut color spaces, and can be vectorized effectively for use in rendering systems that handle many wavelengths at once.</p>
Giant panda metagenomic sequencing analysis table
<p>Giant panda metagenomic sequencing function analysis table</p>
Table 1 : Norms for clinical use of CXM, a real-time marker of height velocity
<p>Table 1 data set</p>
How do table shape, group size, and gender affect on-task actions in collaborative learning activities? - Qualitative data
<p>Qualitative data set for the ijCSCL journal paper " <strong>How do table shape, group size, and gender affect on-task actions in collaborative learning activities?</strong> "</p>
Suppelementary Table S1. List of heat-affected proteins in buds, open flowers, wilted flowers, and donor leaves of common buckwheat accessions 'Panda' and PA15. Comparison of protein abundance between heat-treated plants and those growing in optimal conditions.
<p>Suppelementary Table S1. List of heat-affected proteins in buds, open flowers, wilted flowers, and donor leaves of common buckwheat accessions ‘Panda’ and PA15. Comparison of protein abundance between heat-treated plants and those growing in optimal conditions. </p>
Table 7: Pairwise comparison matrix – motorcyclist perceptions
<p>Pairwise comparison matrix for motorcyclist perceptions</p>
Supplementary Table S3.3
<p>Allelic diversity of genes putatively involved in S. agalactiae virulence among ST17 and ST19 strains.</p>
Supplementary Table S3.4
<p>Allelic diversity of genes putatively involved in S. agalactiae virulence among ST17 and ST19 strains.</p>
Data from: Drought legacies are dependent on water table depth, wood anatomy, and drought timing across the eastern U.S.
Severe droughts can impart long-lasting legacies on forest ecosystems through lagged effects that hinder tree recovery and suppress whole-forest carbon uptake. However, the local climatic and edaphic factors that interact to affect drought legacies in temperate forests remain unknown. Here, we pair a dataset of 143 tree ring chronologies across the mesic forests of the eastern U.S. with historical climate and local soil properties. We found legacy effects to be widespread, the magnitude of which increased markedly in diffuse porous species, sites with deep water tables, and in response to late-season droughts (August – September). Using an ensemble of downscaled climate projections, we additionally show that our sites are projected to drastically increase in water deficit and drought frequency by the end of the century, potentially increasing the size of legacy effects by up to 65% and acting as a significant process shaping forest composition, carbon uptake, and mortality.
Multi-regional Input–output Table for the Global Emerging Economies (EMERGING V2.5)
<p><strong>EMERGING V2.5</strong>: This version removes the 27th sector, totaling 133 sectors, compared to EMERGING1.0. It has been optimized and calibrated to improve the intermediate input matrix (Z matrix), trade volumes (imports and exports), and total output for the electricity, transportation, and energy sectors across 245 economies, with a particular focus on small and medium-sized emerging economies.</p> <p><strong>EMERGING CO<sub>2</sub> Inventory</strong>: CO<sub>2</sub> emissions (Mt CO<sub>2</sub>eq) from fossil fuel combustion and energy consumption at the sectoral level in each region are available from the IEA database and CEADs emission inventory data. The EMERGING CO<sub>2</sub> Inventory includes a total of 7 energy types: 1. Coal; 2. Natural gas; 3. Oil products; 4. Crude, NGL, Ref Feeds.; 5. Other; 6. Oil shale & oil sands; 7. Peat & Peat products.</p> <p><strong>Announcements</strong></p> <p>These data are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific insights. The availability of these data does not constitute publication of the data. The data providers rely on the ethics and integrity of the user to ensure that they receive fair credit for their work. If the data are obtained for potential use in a publication or presentation, we kindly ask you to cite them properly according to the instructions on the website.</p> <p>Queries about the EMERGING database and further collaboration can be addressed to: huojw20@hotmail.com</p>
Full versions of the Tables from the PhD Thesis
<p>Full versions of the Tables from the AASS PHD Thesis by <strong>Alessandro Coletta</strong>:<br>- Main properties of the ALMAGAL clumps sample<br>- ALMAGAL compact source catalog and photometric properties<br>- Estimated physical parameters of the extracted cores</p>
S Table 1. Characteristics of all sorghum cultivars assessed for drought and salinity.
<p>The data is presented in a table (S Table 1. Characteristics of all sorghum cultivars assessed for drought and salinity) as a supplement of a manuscript in MDPI <i>Agronomy | </i>Special Issue<i> "Novel Insights into Abiotic Stress Tolerance of Crops" </i>journal. </p>
A comparison of model-based and model-free agents in solving semi-automatically generated PPDDL problems - Agent classification table
<p>This table classifies the agents used in the work to those which use models in their decision-making, which are model-based (MB), and those which do not, which are model-free (MF).</p>
Table S1: Complete list of identified IVD-related studies.
<p> Columns B-AB correspond to the original dataset obtained as described in the materials and methods section. Columns AC-AR result from the manual analysis of the selected studies.</p>
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.