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3,101 results for “tables”
Kinematics characteristics of rockfalls during earthquakes: Insights from shaking table tests
<p>This dataset contains the experimental results of runout distance and lateral displacement from all over 3000 tests, categorized and labeled based on different influencing factors, including Triangular prism, Quadrangular prism, Pentagonal prism, Hexagonal prism, Initial velocity, Slope type, Slenderness ratio.</p>
Colosseum Marble Table (Piazza del Colosseo)
www.havadanharita.com Source: Objaverse 1.0 / Sketchfab
Arabic Table
A round Arabic Table Source: Objaverse 1.0 / Sketchfab
LowPoly medieval round table
This is a lowpoly medieval round table. Source: Objaverse 1.0 / Sketchfab
ENTRANT: A Large Financial Dataset for Table Understanding
<p>Tabular data is a way to structure, organize and present information conveniently and effectively. Real-world tables present data in two dimensions by arranging cells in matrices that summarize information and facilitate side-by-side comparisons. Recent research efforts aim to train large models with machine learning methods to understand structured tables, a process that enables knowledge transfer in various downstream tasks. Model pre-training, though, requires large tabular datasets, conveniently formatted to reflect cell and table properties and characteristics. This paper presents a financial dataset, called ENTRANT that comprises millions of tables. The tables are transformed to reflect cell attributes, as well as positional and hierarchical information. Hence, they facilitate, among other things, pre-training tasks for table understanding with deep learning methods. The dataset provides table and cell information along with the corresponding metadata in a machine-readable JSON format. Furthermore, we have automated all data processing and curation in a free and open-access project. Moreover, we have technically validated the dataset, through unit testing of high code coverage. Finally, we demonstrate the use of the dataset in a pre-training task of a state-of-the-art model, which is also used for downstream cell classification.</p>
IPBES Invasive Alien Species Assessment: Chapter 4. Figures, tables and captions
<p>Figures, tables and captions from Chapter 4: Impacts of biological invasions on nature, nature’s contributions to people, and good quality of life. In: Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
IPBES Invasive Alien Species Assessment: Chapter 5. Figures, tables and captions
<p>Figures, tables and caption from Chapter 5: Management; challenges, opportunities and lessons learned. In: Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
IPBES Invasive Alien Species Assessment: Chapter 3. Figures, tables and captions
<p>Figures, tables and captions from Chapter 3: Drivers of biodiversity change affecting biological invasions. In: Thematic Assessment Report on Invasive Alien Species and their Control of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.</p>
Differential gene expression table of the transcriptional response of Colorado potato beetle to aegerolysin-based complex
<p>The file in Excel format (xlsx) contains the results of differential gene expression analysis of a study with Colorado potato beetle larvae that explores the potential adaptive response of CPB larvae to feeding with feed complemented by the aegerolysin-based complex PlyA2/PlyB.</p> <p>Experimental design: Leptinotarsa decemlineata larvae fed on potato leaf disks supplemented with PlyA2/PlyB/buffer solution vs control larvae fed on leaves soaked in buffer. Whole larvae were sampled at 1 and 5 days post-treatment, and RNA was isolated and sequenced on an Illumina sequencing platform.</p>
Tables Supplementary S1 and S2
<p><strong><span>Table Supplementary S1 </span></strong><span>Assessment of assumptions regarding normal distribution performed using the Shapiro-Wilk test and homogeneity of variances using the Brown-Forsyth test for the studied leukocyte subpopulations in three groups.</span></p> <p> </p> <p><strong><span>Table Supplementary S2 </span></strong><span>Assessment of assumptions regarding normal distribution performed using the Shapiro-Wilk test and homogeneity of variances using the Brown-Forsyth test for the studied lymphocytes T subpopulations in three groups.</span></p>
DOES OBESITY DRIVE THE DEVELOPMENT OF POLYCYSTIC OVARY SYNDROME? AN EPIDEMIOLOGIC STUDY (SUPPLEMENTARY TABLES)
<p>These are the Supplementary tables for manuscript entitled 'Does Obesity Drive the Development of Polycystic Ovary Syndrome? An Epidemiologic Study', denoting: Table 1: the search strategy for the systematic review; Table 2: the NOS quality scoring of included studies; and Table 3: the association between mean BMI or obesity prevalence and PCOS prevalence by PCOS diagnostic criteria. </p>
Uncoupling of Behavioral and Metabolic Twenty-Four-Hour Rhythms in Reindeer (Current Biology, Meier et al. 2024): Metabolomics analysis tables: Annotation list, pathway analysis outputs, target list for targeted peak exstraction and MS/MS spectra of annotated features
<p><span>Metabolomics analysis tables: Annotation list, pathway analysis outputs, target list for targeted peak exstraction and MS/MS spectra of annotated features</span></p>
Supplementary Tables S1-S5 for an article "Square Antiprismatic Chelation Is a Key Determinant for Potassium Ion Selectivity"
<p>This file contain tables S1-S5 for the supporting information from the original paper. These tables describe potassium binding sites indentifieid in potassium channels, other membrane proteins and randomly chosen non-membrane proteins. (See the article text for details)</p> <p> </p>
Supplementary Tables 1 to 7
<p>This dataset combines the supplementary tables generated in the context of our manuscript (Mozin <em>et al.</em>).</p> <p><strong>Table S1:</strong> cell_data file obtained after the initial sciRNA-Seq experiment. The genotype, time point, number of expressed genes and cluster of origin are indicated for each individual cell.</p> <p><strong>Table S2:</strong> Differentially expressed genes (p-adj < 0.0001) obtained after branch expression analysis modeling (BEAM) and the cluster to which they belong on the heatmap shown in Figure 1F.</p> <p><strong>Table S3:</strong> Differentially expressed genes (p-adj < 0.01) detected at Day 10 after sciRNA-Seq.</p> <p><strong>Table S4:</strong> Details of the differentiation experiments performed to obtain Figures 1 to 4.</p> <p><strong>Table S5:</strong> Differentially expressed genes (p-adj < 0.01) detected at Day 10 after split-pool barcoding RNA-Seq.</p> <p><strong>Table S6:</strong> Differentially expressed genes (abs(log2(fold-change)) > 1 & p-adj < 0.01) detected at Day 10 after bulk RNA-Seq in the study previously published by our group.</p> <p><strong>Table S7:</strong> List of barcoded primers used in the RT reaction and in the illumine library preparation of the sciRNA-Seq experiment.</p>
Supplementary Table 1: Search terms used for each database.
Open the record for dataset details and reuse information.
Supplementary material-Figure S1、Figure S2、Table S1 and Table S2
Open the record for dataset details and reuse information.
Supplementary Table Chapter 5 - Coco Duizer
<p><strong>Supplementary Table Chapter 5 - Coco Duizer</strong></p> <p><strong>Table S2: <strong><span>Results of the microarray analysis of HeLa 57A cells stimulated with <em>C</em>. <em>jejuni-</em>released ADP-heptose.</span></strong><span> <br></span></strong><span><span>Shown are all genes that are either up- or downregulated with a statistical significance of p <em>< </em>0.05.</span></span></p>
Multi-regional Input–output Table for the Global Emerging Economies (EMERGING)
<p><strong>EMERGING</strong>: Up-to-date and full-scale MRIO tables covering 135 sector code (the actual number of sectors is 134) in 245 economies. The EMERGING database is also designed to incorporate more official and publicly available data from national statistical institutes to ensure a high level of data quality, especially for these economies. </p> <p>Please see the steps in the development of the database and reconciliation and validation of bilateral trade data and national statistics in: <strong>Huo, J., Chen, P., Hubacek, K., Zheng, H., Meng, J., & Guan, D. (2022). Full-scale, near real-time multi-regional input–output table for the global emerging economies (EMERGING). Journal of Industrial Ecology, 1– 15. </strong><a href="https://doi.org/10.1111/jiec.13264"><strong>https://doi.org/10.1111/jiec.13264</strong></a></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> <div><strong>End year: </strong>The current version of the time series for EMERGING MRIO data is from 2010, 2015 to 2019. We have completed a full update for the period of 2020 to 2022 and the relevant new MRIO table is currently in the testing phase. It will be publicly shared online soon.</div> <div> </div> <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: jing.j.meng@ucl.ac.uk or huojw20@mails.tsinghua.edu.cn </p>
Leveraging basecaller's move table to generate a lightweight k-mer model
<p>The ONT RNA004 dataset that is used to create a 5-mer model using the basecaller's movetable.</p> <p>The dataset is a sub-sample extracted from a dataset that sequenced Universal Human Reference RNA.</p> <p>The specification of the bio sample is here</p> <p>https://www.agilent.com/cs/library/usermanuals/public/740000.pdf</p>
Appendix 3 Frequency tables
<p>Appendix 3 of the paper "<span>Between source language constructions and target language expectations. </span>An analysis of passive constructions in translated and non-translated Spanish", published in <em>Review of Cognitive Linguistics.</em></p> <p>It contains the frequency tables for all passive constructions in the three languages. </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.