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3,101 results for “tables”
Outcome of Childhood Adrenocortical Carcinoma in Developing Countries. Supplementary Table 3: Pathological details
<p>The outcome of Childhood Adrenocortical Carcinoma in Developing Countries; a scene for surgeons or a chance for medicines</p> <p>Supplementary Table 3: Pathological details</p>
The outcome of Childhood Adrenocortical Carcinoma in Developing Countries; Supplementary Table 2: Metastatic sites
<p>The outcome of Childhood Adrenocortical Carcinoma in Developing Countries; a scene for surgeons or a chance for medicines.</p> <p>Supplementary Table 2: Metastatic sites</p>
Outcome of Childhood Adrenocortical Carcinoma in Developing Countries. Supplementary Table 1: Patients' characteristics and endocrinal manifestations
<p>Outcome of Childhood Adrenocortical Carcinoma in Developing Countries. Supplementary Table 1: Patients’ characteristics and endocrinal manifestations</p>
Table S3 - Mass Spec Data
<p>Mass Spec Data: Plasmodium falciparum proteins PF3D7_0201600, PF3D7_0500800, PF3D7_0830600, and PF3D7_1476200 were used as bait in BioID immunoprecipitations. The column labels describe the type of data found in each column. The tab names correspond to the bait protein gene ID numbers.</p>
Tables and Figures complementing the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2017
<p>All tables, figures and maps produced for the European Union Summary Report on Antimicrobial Resistance in Zoonotic and Indicator Bacteria from Humans, Animals and Food in 2017 are provided.</p>
Characterizing Novel Olfactory Receptors Expressed in the Murine Renal Cortex: Supplemental Table S2
<p><strong>Olfactory receptors selected for study. </strong>Olfactory receptors (ORs) selected for study based on mapped reads in at least 7 out of 8 murine renal cortex samples. Murine samples are listed as A - M. Samples A - G were fed high fat diet, while samples I - M were fed control diet. (mm10) FPKM counts for ORs selected for study based on the GRCm30/mm10 genome build using previously published OR coordinates. ORs are listed using the "Olfr" gene names, as well as the "CUFFOR" names as determined by Ibarra-Soria X et al. (mm9) FPKM counts for ORs selected for study based on the NCBI37/mm9 genome build using established coordinates. ORs listed in green were identified and cloned from kidney RNA previously.</p> <p> </p> <p>Data accessible at NCBI GEO database, accession number GSE117249<br> https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE117249</p>
MAJA look-up tables for Venµs satellite
<p>This archive contains the look-up tables used by MAJA atmospheric correction software, used to process Venµs satellite data. These look-up tables correspond to a continental model.</p> <p>V1.1 corrects for a bug in VE_TEST_GIP_L2DIRT_L_ALLSITES_00010_20000101_99991231.HDR, (Direct Transmission file) which contained references to Diffuse transmission files for bands 7 to 12.</p> <p>V1.2 corrects a typo in VE_TEST_GIP_L2ALBD_L_ALLSITES_00010_20000101_99991231.HDR</p> <p>V1.3 adds LUT for Copernicus Atmosphere aerosol types </p>
MAJA look-up tables for Sentinel-2 A&B sensors, for Copernicus Atmosphere Monitoring Service aerosol types
<p>The archive contains the Look-up tables used by MAJA atmospheric correction software, used to process Sentinel-2 A&B sensors. These look-up tables correspond to the aerosol types used by Copernicus Atmosphere Monitoring Service (CAMS). However, the default continental model is also provided.</p> <p>Version 1.1 has new LUT for water vapour estimates, which corrects for a bias observed for large water vapour contents (above 2.5 g/cm2)</p> <p>Version 1.2 just changed the Folder name for a better integration with Start_maja.</p> <p>Version 1.3 added the Header files</p>
HDF5 Table for Machine Learning on Difference image analysis
<p>A table with the features.</p> <p>There exists several tables within this file.</p> <p>Each table is a set of transient candidates, with the column IS_REAL stating their status of real or bogus.</p>
Table S1 for "Lowermost mantle anisotropy beneath Africa from differential SKS-SKKS shear-wave splitting"
<p>SKS-SKKS measurements per station and per event. We provide details in the following order: station, network, station latitude, station longitude, event date, event time, event latitude, event longitude, event depth, event magnitude, distance, backazimuth, misalignment correction value, phi, dt, min. phi error, max. phi error, min. dt error, max. dt error, splitting intensity, min. splitting intensity error, max. splitting intensity error, category (SplitRacer), individual category, category for pair. Values for field ‘category(SplitRacer)’ are based on SplitRacer’s quality criteria: good, average, null-measurement, with our addition of the category ‘fair null-measurement’ for nulls which are slightly noisy. In general, these categories are selected by the user on the basis of the noise level of the traces, the amount of energy reduction, splitting intensity value (and errors), visual comparison of the time derivative radial component to the transverse component, scatter in the histogram over the used time windows and the size of 95% confidence level The selection of final usable events was then based on the width of the 95% confidence level. The field ‘Individual category’ has the following values: 0=null-measurement; 1=very good (phi error < 30°; dt error 0.75 s); 2= good (phi error >30°; < 60°, dt error > 0.75 s; <1.55 s), 3= fair (error bars larger than category 2 but clear splitting and the other phase of the same event is a category 1). Categories for pairs are: 0 = both phases are null-measurements; 1= both phases have an individual category of 1, individual categories of 1 & 2, or one phase is null while the other is an individual category 1; 2= both phases have an individual category of 2 or one phase is null while the other is an individual category 2 measurement or one phase is an individual category 1 measurement while the other is an individual category 3 measurement (the latter only applies to 30 pairs in total).</p>
Summary Table of AHG Parameters, Hydraulics, Morphological and geophysical variables, and Suspending Sediment Concentration Derived at 1246 USGS River Monitoring Stations
<p>This table contains information about:</p> <p>1) At-A-Station Hydraulic Geometry Parameters,</p> <p>2) Hydraulics Variables,</p> <p>3) Morphological and Geophysical Variables, and</p> <p>4) Suspending Sediment Concentration and Fraction of Sand, Silt, and Clay,</p> <p>derived at 1246 USGS river monitoring stations across the conterminous United States. </p>
Cutting through the Jungle: Disambiguating Model-based Traceability Terminology — Terminology Mapping Table
<p>This dataset contains the mapping of model-based traceability terminology developed in Holtmann et al. to the secondary sources that have been used as part of the validation of the terminology.</p>
Urban-rural life tables for Scotland, 1861-1910
<p>This data set contains the life tables the were computed for the study presented in: Torres, C., V. Canudas-Romo, and J. Oeppen (2019) 'The contribution of urbanization to changes in life expectancy in Scotland, 1861–1910', <em>Population Studies</em>, 73:3, 387-404, DOI: 10.1080/00324728.2018.1549746</p> <p>The life tables are by sex and urban-rural category. For reasons explained in the paper, the tables cover periods of different lengths, from 1861 to 1910.</p> <p><strong>Example of how to load the data in R:</strong></p> <p>LT <- read.table("Urban-Rural-LifeTables-Scotland-1861-1910.txt", header = T, sep = ";")</p> <p><strong>Description of each column:</strong><br> Period: time-interval, including the first and excluding the last indicated years (e.g., [1861,1866) corresponds to the years from 1861 to 1865). Available periods: 1861-1865, 1866-1870, 1871-1874, 1875-1877, 1878-1880, 1881-1885, 1886-1890, 1891-1892, 1893-1896, 1897-1900, 1901-1905, 1906-1910.<br> Population: Rural, Semi-Urban, Urban, or Total population (see definitions in Torres et al. 2019)<br> Sex: Female or Male<br> x : Age (from 0 to 110+, by single ages)<br> nmx: Death rate in the age interval [x, x+n)<br> nax: average number of person-years lived in the age interval [x, x+n) by those who die in that interval<br> nqx: Probability of dying in the age interval [x, x+n)<br> lx: number of survivors at exact age x, or probability of surviving until exact age x<br> ndx: Life-table deaths in the age interval [x, x+n)<br> nLx: Person-years lived in the age interval [x, x+n)<br> Tx: Person-years lived above age x<br> ex: Remaining life expectancy at age x</p> <p>For more information about life tables in general, see: Preston, S., Heuveline, P., and Guillot, M. (2001). <em>Demography: Measuring and Modeling Population Processes</em>. Wiley-Blackwell</p>
Supplementary Table S5
<p><strong>Rywal biological evidence filtering results</strong>.</p> <p>Output of 1<sup><em>st</em></sup> filtering step by biological evidence for cv. Rywal.</p> <p>Layer _p_stRT/_I_STRT/_S_03_stCuSTr/ _A_03.1_filtering, DOI: 10.15490/fairdomhub.1.datafile.3112.1</p>
Supplementary Table S2
<p><strong>Detailed <em>de novo</em> assemblies information table</strong>.</p> <p>Primary potato transcriptome assemblies summary listing parameters used for short reads <em>de novo</em> assembly generation.</p> <p>Layer _p_stRT/_I_STRT/_S_02_denovo, DOI: 10.15490/fairdomhub.1.datafile.3091.1</p>
Supplementary Table S3
<p><strong>Désirée biological evidence filtering results</strong>.</p> <p>Output of 1<sup><em>st</em></sup> filtering step by biological evidence for cv. Désirée.</p> <p>Layer _p_stRT/_I_STRT/_S_03_stCuSTr/ _A_03.1_filtering, DOI: 10.15490/fairdomhub.1.datafile.3110.1</p>
Part of FPKM and htseqcount tables from GSE129424
<p>Part of FPKM and htseqcount tables from GSE129424 that can be used to test https://github.com/lldelisle/rnaseq_rscripts</p>
Text-fig. 2. Map showing the distribution of localities included in the treatment of Brown (1962), based on the coordinates presented in Appendix Table 1. Localities are distributed across New Mexico (NM), Colorado (CO), Wyoming (WY), Montana (MT), South Dakota (SD) and North Dakota (ND). Also plotted are cited Canadian localities: Joffre Bridge, in Alberta (AB), and Ravenscrag, in Saskatchewan (SK). Map generated with Map-It (2014) website. in Revisions To Roland Brown'S North American Paleocene Flora
Text-fig. 2. Map showing the distribution of localities included in the treatment of Brown (1962), based on the coordinates presented in Appendix Table 1. Localities are distributed across New Mexico (NM), Colorado (CO), Wyoming (WY), Montana (MT), South Dakota (SD) and North Dakota (ND). Also plotted are cited Canadian localities: Joffre Bridge, in Alberta (AB), and Ravenscrag, in Saskatchewan (SK). Map generated with Map-It (2014) website.
Figure 3 in Morphology of immature stages, biological parameters and life table of Microtechnites bractatus (Hemiptera: Miridae) on different host plants
Figure 3 Average survival of Microtechnites bractatus nymphs fed with alfalfa, white clover, potato, wheat, and beans under laboratory conditions (25 ± 2°C, photoperiod 12L:12D). *Lines followed by different letters differ from each other by the paired Mentex-Cox test (Log Rank) (df=1, p<0.05).
Figure 2 in Morphology of immature stages, biological parameters and life table of Microtechnites bractatus (Hemiptera: Miridae) on different host plants
Figure 2 Five nymphal instars of Microtechnites bractatus: (A) first instar; (B) second instar; (C) third instar; (D) fourth instar; (E) fifth instar reduced wing pads for adult brachypterous (female); (F) elongated fifth-instar wing pads for adult macropterous (male).
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.