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3,101 results for “tables”
Life tables and graphs for Bahry (2022) - Equilibrium conditions in the evolution of senescence [MSc thesis, Carleton Univeristy]
<p>Life table data, and derived quantities, for <em>Equilibrium Conditions in the Evolution of Senescence</em> (Bahry, 2022, MSc thesis); adapted from the supplementary data of (Jones et al., 2014). Life table data for human (Japan 2009), human (Aché hunter-gatherer), fruit fly, Soay sheep, freshwater hydra, and desert tortoise.</p> <p>Basic life table quantities: age interval <span class="math-tex">\((X)\)</span>; survival function <span class="math-tex">\((l_X)\)</span>; and age-specific interval fecundity <span class="math-tex">\((m_X)\)</span>. Derived quantities include interval average force of mortality; reproductive value; residual reproductive value; Hamilton's indicators of the age-specific forces of selection; and actual age-specific mortality vs. predicted age-specific mortality based on models treated in (Bahry, 2022).</p> <p>In the original life tables of Jones et al. (2014), desert tortoises negatively senesce over the range of observed ages, but had a final observed cut-off age of 74; this causes reproductive value to artifactually fall to 0 as age-approached the cutoff. To get around this, I also used an extrapolated desert tortoise life table, assuming the age-74 mortality and fecundity rates remained constant until age 1000, then using the extrapolated life table to calculate reproductive value (and Hamilton's indicators) up to the cutoff age 74.</p> <p><strong>References</strong></p> <p>Bahry, D. (2022). <em>Equilibrium Conditions in the Evolution of Senescence</em> [Master's thesis, Carleton University].</p> <p>Jones, O. R. et al. (2014). Diversity of ageing across the tree of life. <em>Nature</em> 505: 169–174. https://doi.org/10.1038/nature12789</p>
Stowaways Supplement Table S4: Ma'agan Mikhael B Rattus rattus Bone Surface Modifications and Taphonomic Analysis Datasheet
<p>Bone surface modifications and taphonomic analysis dataset. Data includes catalogue number, fragmentation, Munsell color code, color notes, cut marks, burning, sand abrasion stage, and marine corrosion degree. For a detailed description of the methods and references, please refer to 'Supplement S1: Methods' in the manuscript.</p> <p>***Version 2 added two new specimens from the September 2022 excavation season.</p>
Datasets-A globally robust relationship between water table decline, subsidence rate and carbon release from peatlands
<p>Supplementary Data A shows meta-data for in-situ and laboratory measurements of soil respiration or its components soil heterotrophic respiration and autotrophic respiration, as well as associated environmental variables from global pristine peatlands and water table decline peatlands, respectively.</p> <p> </p> <p>Supplementary Data B shows the relationships between peatland subsidence rates and drainage years for different land uses in different climate zones, relationships between proportion of peatland subsidence rates due to oxidation and drainage years for different land uses in different climate zones, the estimated peat subsidence rates and peat subsidence rates due to oxidation, the synthesized soil organic carbon content and soil bulk density at the layer of 0-30 cm from pristine peatlands, and the in-situ measured annual soil heterotrophic respiration rates for validating the robustness of the developed emipirical models of this study. </p>
Figure 1 in Biology and life table parameters of Proprioseiopsis lindquisti on three eriophyid mites (Acari: Phytoseiidae: Eriophyidae)
Figure 1. Age-specific survival rate (lx), age-stage specific fecundity of female (fxj) and age-specific fecundity rate (mx) of Propriopseiosis lindquisti on three eriophyid mites.
Fine-root biomass production, sedge root, sedge leaf, and moss shoot decomposition, soil water-table level, and temperature data from two sedge fens in Finland
<p>Dataset including fine-root biomass production, mass loss of sedge (<em>Carex rostrata</em>) roots and leaves, and moss (<em>Sphagnum</em> <em>fallax</em>) shoots, along with environmental data (soil water-table level, air temperature, soil temperature at 5 cm, and soil temperature at 15 cm) from two sedge fens located in southern Finland (Lakkasuo, Orivesi, 61°48' N 24°19'E) and northern Finland (Lompolojänkkä, Kittilä, 68°N 24°12'E). Data are from a climate change experiment, where warming was induced with open top chambers (OTCs) and drying with shallow ditching. Data are from years 2011-2013.</p>
The Relationship between LRP5 (rs556442 and rs638051) Polymorphisms and Mutation with Bone Metabolism in Xinjiang women with Type 2 Diabetes after Menopause(Table 1 and Table 2 Statistical Values of Analysis Process)
<p>The Relationship between LRP5 (rs556442 and rs638051) Polymorphisms and Mutation with Bone Metabolism in Xinjiang women with Type 2 Diabetes after Menopause(Table 1 and Table 2 Statistical Values of Analysis Process)</p>
Supplemental Tables for Wheat et al 2022 submitted to Geochemistry, Geophysics, Geosystems
<p>Data are from multiple expeditions to the eastern flank of the Juan de Fuca Ridge off the coast of Washington, USA. Most of the data are from the RetroFlux Expedition. These data were coupled with other published data to assess chemical conditions of the basaltic aquifer below the seafloor within the norther portion of the Juan de Fuca Plate. This work will be published in Geochemistry Geophysics Geosystems in 2022.</p>
rDNA 18S V9 metabarcoding tables (Swarm) for Tara Oceans Expedition (2009-2013), including Tara Polar Circle Expedition (2013)
<p>Reads were grouped into OTUs using the following swarm-based pipeline: paired-end reads were merged with vsearch’s --fastq_mergepairs command (version 2.15.1, allowing for staggered reads; Rognes et al., 2016), and trimmed with cutadapt (version 3.0; Martin, 2011), keeping only reads containing both forward and reverse primers. After trimming, the expected error per read was estimated with vsearch’s command --fastq_filter and the option --eeout. Each sample was then de-replicated, i.e. strictly identical reads were merged, using vsearch’s command --derep_fulllength, and converted into fasta format. Clustering was performed at the sample level with swarm 3.0 using default parameters (Mahé et al., 2015). Prior to global clustering, individual fasta files (one per sample) were pooled and further dereplicated with vsearch. Files containing per-read expected error values were also dereplicated to retain only the lowest expected error for each unique sequence. Global clustering was performed with swarm (using the fastidious option). Cluster representative sequences were then searched for chimeras with vsearch’s command --uchime_denovo using default parameters (Edgar et al., 2011).</p> <p>Clustering results, expected error values, taxonomic assignments, and chimera detection results were used to build a “raw” occurrence table. Reads without primers, reads shorter than 32 nucleotides and reads with uncalled bases (“N”) were discarded. For a “filtered” occurrence table, non-chimeric sequences, sequences with an expected error per nucleotide below 0.0002, and clusters containing at least 2 reads were retained. Since primer trimming is not perfect, some sequences can still contain primer fragments or be excessively trimmed. These sub- or super-sequences were identified using vsearch and merged with their closest, most abundant perfectly trimmed sequence. Finally, occurrence patterns throughout our sample collection were used to further refine the occurrence table. Clusters that contain sub-clusters with only a single-nucleotide difference but with different ecological patterns (defined here as uncorrelated abundance values in at least 5% of the samples) were turned into distinct clusters (https://github.com/frederic-mahe/fred-metabarcoding-pipeline). On the other hand, clusters with similar sequences that had correlated abundance values in at least 95% of the samples, were merged using a re-implementation of lulu's method (Frøslev et al. 2017; https://github.com/frederic-mahe/mumu).</p> <p> </p>
Supplementary Tables for "Immune cell-specific smoking-related expression characteristics are revealed by re-analysis of transcriptomes from the CEDAR cohort"
<p>Supplementary Tables from "Immune cell-specific smoking-related expression characteristics are revealed by re-analysis of transcriptomes from the CEDAR cohort".</p>
Supporting data sets for "Estimating Carbon Fixation of Plant Organs for Afforestation Monitoring using a Process-based Ecosystem Model and Ecophysiological Parameter Optimization". (the survey of tree breast diameter and tree height in 11-year old Eucommia ulmoides plantation, values of simulation results used in figures and tables.)
<p>Supporting data sets for Miyauchi et al., Ecology and Evolution, 2019 (accepted).</p> <p>The files store: </p> <p>(1) The survey of tree breast diameter and tree height in <em>Eucommia ulmoides</em> plantation<em>.</em> The ring and stem analysis and dry weight of seven harvested sample trees in the plantation.</p> <p>(2) Values of optimization result used fig.7.</p> <p>(3) Values of prediction result used fig.8. and table 4.</p> <p>(4) Values of optimized parameters by optimization methods, parameter range and constrain.</p>
Table: Critical assessment of charge mobility extraction in field-effect transistors.
<p>This TABLE lists the measurement reliability factor, <em>r</em>, the maximum power density, <em>P</em><sub>max</sub>, dissipated in the transistor<br> channel, as well as the maximum current density, <em>j</em><sub>SD</sub><sup>max</sup>, in the channel of (organic) field-effect transistors (FETs) calculated from the data shown in recent literature reports. For the exact definitions of these parameters see Nature Mater. DOI: 10.1038/nmat5035.</p>
Figure 2. The structures of the two tables from the Dex Online database-ADX – Agent for Morphologic Analysis of Lexical Entries in a Dictionary
<p>Dex Online is a project initiated and coordinated by Catalin Francu [3]. He intended to<br> realise an online database for all the words in the Romanian language, using the main explanatory<br> dictionaries, dictionaries of synonyms, neologisms, published by the Romanian Academy and other<br> scientific forums.<br> The database was completed by volunteers, similarly to the Wikipedia system. They actually<br> transcribed the information from different important dictionaries, but many words have been<br> electronically entered by two companies (Siveco and Litera International Publishing House).</p>
Table 1. The declination of feminine nouns (after [4])-ADX — Agent for Morphologic Analysis of Lexical Entries in a Dictionary
<p>An example of such searching trees for nouns of all genders (masculine, feminine, neuter)<br> together with the entire analysis made by the ADX agent for the word “cepelor” is presented in<br> figure 2. The pairs of numbers in brackets form lists of lines and columns from the inflections’<br> charts where endings from the top of the list are found. We have noted the zero ending with – (that<br> is always the root of the tree) and the void list with * (Null/Nil).</p>
Annotation table - Whole body transcriptomes of the tick Ixodes ricinus at different stage and feeding conditions
<p>Annotation table for a <em>de novo</em> assembled transcriptome of<em> Ixodes ricinus</em> in different stages and conditions.</p> <p>Description of the fields of each column (Trinotate results, and additionnal statistics):</p> <p>1. Contig_name: name of the contig (Trinity assembly)</p> <p>2. sprot_Top_BLASTX_hit: first hit of the blastx search against SwissProt (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>3. TrEMBL_Top_BLASTX_hit: first hit of the blastx search against Uniref90 (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>4. RNAMMER: identification of non-coding RNAs</p> <p>5. prot_id: identifier of the predicted protein (TransDecoder)</p> <p>6. prot_coords: coordinates (start, end and strand) of the predicted protein on the contig</p> <p>7. sprot_Top_BLASTP_hit: first hit of the blastp search between the predicted protein and SwissProt (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>8. TrEMBL_Top_BLASTP_hit: first hit of the blastp search between the predicted protein and Uniref90 (https://data.broadinstitute.org/Trinity/Trinotate v2.0 RESOURCES/)</p> <p>9. Pfam: result of the search against PfamA database</p> <p>10. SignalP: prediction of a signal peptide with SignalP</p> <p>11. TmHMM: prediction of a transmembrane domain with THMM</p> <p>12. eggnog: eggNOG database of orthologous genes (v3.0) assignation</p> <p>13. gene_ontology_blast: GO assignation based on blast results</p> <p>14. gene_ontology_pfam: GO assignation based on pfam results</p> <p>15. Contig_length: length of the contig in bp</p> <p>16. Busco_Id: name of the BUSCO (v1)</p> <p>17. Busco_status: status of the BUSCO (complete/fragmented/duplicated)</p> <p>18-32: Kallisto read counts for the 15 libraries</p> <p>A, B, C: unfed nymphs (replicates 1, 2, 3)</p> <p>D, E, F: partially fed nymphs (replicates 1, 2, 3)</p> <p>G, H, I: males (unfed) (replicates 1, 2, 3)</p> <p>J, K, L: unfed adult females (replicates 1, 2, 3)</p> <p>M, N, O: partially fed adult females (replicates 1, 2, 3)</p> <p>33. log2FoldChange_UnfedVsPartiallyFed: log fold change in base 2 of expression (comparison between "unfed" -including males- and "fed" ticks)</p> <p>34. pvalue_UnfedVsPartiallyFed: p-value of the comparison between "unfed" -including males- and "fed" ticks</p> <p>35. log2FoldChange_MaleVsFemale: log fold change in base 2 of expression (comparison between "males" and "females")</p> <p>36. pvalue_MaleVsFemale: p-value of the comparison between "males" and "females"</p> <p>37. log2FoldChange_NymphsVsAdults: log fold change in base 2 of expression (comparison between "nymphs" and "adults" -males and females-)</p> <p>38. pvalue_NymphsVsAdults: p-value of the comparison between "nymphs" and "adults" -males and females-)</p> <p> </p> <p> </p>
Table 4: The means of the items comprising the test anxiety questionnaire
<p>The purpose of the study was twin: to investigate the test-taking anxiety of ESP students of<br> Engineering taking a course in general English and to shed light on the relationship between the<br> students' test-taking anxiety and their performance on a general English test. To this end, the first<br> phase of the study was devoted to the reliability of the two instruments employed to address the<br> research question: (a) the anxiety questionnaire (TAS), and (b) the general English test. The second<br> or main phase of the study was concerned with the four research question. In this section, the results<br> of analyses related to the two phases are presented.</p> <p>Table 4 also shows the mean of each of 37 items comprising the TAS.</p>
Table 5: Overall correlation between test anxiety and test performance
<p>The second research question in this study addressed the relationship between test-taking<br> anxiety and learners' performance on the general English test. To investigate the relationship, the<br> Pearson product-moment correction was employed. First, the correction between total anxiety and<br> test performance was calculated. As shown in Table 5, the index was -.011.</p> <p> </p>
Table 3: Descriptive statistics for the test anxiety questionnaire
<p>The first research question was concerned with the degree of the general test-taking anxiety<br> of ESP students learning general English. Table 3 presents the students' mean anxiety (x=2.16, sd. =<br> .34).</p>
Table 2: Reliability of the general English test
<p>The purpose of the study was twin: to investigate the test-taking anxiety of ESP students of<br> Engineering taking a course in general English and to shed light on the relationship between the<br> students' test-taking anxiety and their performance on a general English test. To this end, the first<br> phase of the study was devoted to the reliability of the two instruments employed to address the<br> research question: (a) the anxiety questionnaire (TAS), and (b) the general English test. The second<br> or main phase of the study was concerned with the four research question. In this section, the results<br> of analyses related to the two phases are presented.</p> <p>The General English Test: The formula KR21 was used to determine the reliability of the general<br> English test. As shown in Table 2, the reliability of the test was .82</p> <p> </p>
Table 1: Reliability of the test anxiety questionnaire
<p>The purpose of the study was twin: to investigate the test-taking anxiety of ESP students of<br> Engineering taking a course in general English and to shed light on the relationship between the<br> students' test-taking anxiety and their performance on a general English test. To this end, the first<br> phase of the study was devoted to the reliability of the two instruments employed to address the<br> research question: (a) the anxiety questionnaire (TAS), and (b) the general English test. The second<br> or main phase of the study was concerned with the four research question. In this section, the results<br> of analyses related to the two phases are presented.</p> <p>The TAS: The present study used the TAS (Sarason, 1975) [27] to determine the students'<br> test-taking anxiety. The use of Cronbach’s alpha showed the internal consistency of .876.</p> <p> </p>
Table 5: Model Fit Summary (b) for Grade Three
<p>The model summary in Table 5 reports the strength of the relationship between the model and the<br> dependent variable, i.e., ECA exam. The multiple correlation coefficient, R, which is the linear<br> correlation between the observed and the model-predicted values of the dependent variable is .551.<br> R Square, which is also called the coefficient of determination, is .303 showing that approximately<br> 30 percent of the variation in ECA exam is explained by the model. Its interpretation is that 30<br> percent of the variation in the ECA test scores is common with the vocabulary scores. The Standard<br> Error of the Estimate of the model is approximately 3.16 out of a total of 30, meaning that the<br> prediction model produces an error range between ± [3.16]. Therefore, the prediction formula must<br> be rewritten as (AVERAGE VOCAB × 0.713) + 2.871± [3.16].</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.