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136 results for “trend analysis”
Accelerated change in the glaciated environments of western Canada revealed through trend analysis of optical satellite imagery (Polygons)
<p>Automatically generated dataset of glacier outlines from the journal article: "Accelerated change in the glaciated environments of western Canada revealed through trend analysis of optical satellite imagery"</p> <p>Research paper: https://www.sciencedirect.com/science/article/pii/S0034425721005824</p> <p>More information can be found here: https://github.com/bevingtona/glacier_change_western_canada</p>
Healthcare Expenditure and Demographic Trends: A Comparative Analysis of Selected Countries (2000-2024)
<p><strong><em><span>This research journal investigates the interplay between healthcare expenditure, life expectancy, and demographic characteristics across selected countries from 2000 to 2024. Utilizing quantitative analysis, the study examines healthcare spending as a percentage of GDP, average life expectancy, and the age distribution of populations. For instance, the USA's healthcare expenditure is projected to reach 19.2% of GDP by 2024, with an average life expectancy of 81.9 years. In contrast, Bangladesh's healthcare expenditure is anticipated to be 7.0% of GDP, with a life expectancy of 70.0 years. The findings reveal critical insights regarding the effectiveness and sustainability of healthcare systems, emphasizing the need for policy interventions that prioritize healthcare funding, especially in aging populations where the percentage of individuals aged 65 and older is expected to rise significantly—projected at 16.0% for the USA and 7.0% for Bangladesh in 2024</span></em></strong><strong><span>.</span></strong><strong><span> </span></strong></p>
Raw and aggregated data for the study introduced in the article "An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors"
<p>This dataset contains all the raw data and aggregated data subject of the study introduced in the article "An analysis of citing and referencing habits across all scholarly disciplines: approaches and trends in bibliographic metadata errors". The study is based on the bibliographic and citation data contained in 729 articles published in 147 journals in 27 subject areas. The articles contained a total amount of 34,140 bibliographic references and 55,100 mentions and quotations overall.</p> <p>The dataset is composed of a series of files:</p> <ul> <li>the files "subject_area_<discipline-name>.csv" contain the raw data of the articles published in the journals of all the disciplines considered in the study;</li> <li>the file "article_data_summary.csv" contains the aggregated data created considering the raw data in the previous files, which have been used to creating all the tables and figures in the article;</li> <li>the file "starred_metadata_set.csv" contains information about the most used subset of bibliographic metadata;</li> <li>the file "journals_selection.csv" contains information about all the journals selected for the study.</li> </ul>
Model agreement and trend analysis data associated to the publication: "Impact of climate change on site characteristics of eight major astronomical observatories using high-resolution global climate projections until 2050"
<p>This dataset is associated with the following publication:</p> <p>Haslebacher, C., Demory, M.-E., Demory, B.-O., Sarazin, M., and Vidale, P. L., “Impact of climate change on site characteristics of eight major astronomical observatories using high-resolution global climate projections until 2050. Projected increase in temperature and humidity leads to poorer astronomical observing conditions”, <em>Astronomy and Astrophysics</em>, vol. 665, 2022. doi:10.1051/0004-6361/202142493.</p> <p>In the folder 'model_agreement', there are pickle files from which a python dictionary can be extracted with:</p> <pre><code>with open('mypklfile.pkl', 'rb') as myfile: dload = pickle.load(myfile)</code></pre> <p>Pickle files ending with '_d_obs_ERA5.pkl' contain in situ data and ERA5 data. Pickle files ending with 'd_model.pkl' contain PRIMAVERA model data. A few explanations:<br> - 'ds_sel': contains monthly timeseries of selected intersecting data<br> - 'ds_taylor': contains data used for the Taylor diagram (Figs. 4-10)<br> - 'ds_mean_month': contains seasonal cycle for plotting (Figs. 4-10)<br> - 'ds_mean_year': contains yearly timeseries for plotting (Figs. 4-10) </p> <p>The subfolder 'median_nc_u_v_t' contains NETCDF files with the median and interquartile range of the wind speed in u and v direction, the temperature and geopotential height. This was used for Figs. G1-G8 and to calculate the refractive index structure constant Cn2.</p> <p>The subfolder 'skill_score_classification' contains csv files with the sorted skill score classifications. The column headers are: model_name, skill score, correlation coefficient, standard deviation, centred root mean square error.</p> <p>The folder 'trend_analysis' contains for each variable csv files of ERA5 and PRIMAVERA monthly time series used for trend analysis, pdf files of analysis summaries, csv files of Bayesian analysis results and png files of longitude-latitude maps of trends (analysed with linear regression). Additionally, there is a csv file of averaged in situ pressures.</p> <p>Code that generated and used this data is available on github: <a href="https://github.com/CarolineHaslebacher/Astroclimate-future-project">https://github.com/CarolineHaslebacher/Astroclimate-future-project</a> </p> <p> </p>
Analysis of the P. lividus sea urchin genome highlights contrasting trends of genomic and regulatory evolution in deuterostomes
<p><br> Supplementary datasets accompanying paper: </p> <p>stage_peaks_anc_sel.xlsx : ATAC peaks with classification, conservation and binding sites<br> Pliv.mfuzz.enrichGO.txt : GO enrichment in MFuzz cluster<br> Pliv_genes_master_filt.xlsx : Gene models with corresponding information<br> bindetect_results_anf.txt : results of TOBIAS<br> hits_pprx_cl0_ord3vrr+Et_red.fa : alignment of homeobox sequences<br> Pliv_aH2p.gn.gtf.gz : annotation in GTF format<br> Pliv_PqN3S_sm.fa.gz : genome of P. livius <br> ansr_*_network.tsv.gz : Stage specific networks from ANANSE analysis<br> ATAC_pks_normcov.tsv : Coverage of unified peaks for ATAC-seq<br> Cttg_pks_normcov.tsv : Coverage of unified peaks for Cut-and-tag H3K27Ac data<br> lncRNA_stgSpe_fpkm.tsv : Expression levels (FPKM) for predicted lncRNAs for available RNA-seq samples <br> Split_Urchin_FPKMs.clean.txt.gz : Expression levels for unified ATAc-seq peaks following direct and reverse orientation</p> <p> </p> <p> </p> <p> </p> <p> </p>
Seasonal trends in leaf level physiological parameters, obtained through gas exchange, reflectance spectroscopy and, functional trait analysis
This data package contains leaf level gas exchange, reflectance spectroscopy, and functional trait measurements collected in six common deciduous tree species across the full 2021 growth season (May -October) at the Black Rock Forest in Cornwall, New York, USA. Branches were sampled predawn using the shotgun method of branch retrieval, and re-cut under water to preserve hydraulic function before transport to the lab. Gas exchange data included in this package are stomatal response curves (irradiance response) which can be used to estimate stomatal slope and intercept. Spectroscopic data are full-range (350 – 2500 nm) leaf reflectance spectra collected on all leaves sampled for gas exchange and traits. Leaf level trait measurements include leaf mass per area (LMA), leaf dry matter content (LDMC), elemental nitrogen and carbon expressed on a per mass basis, and fitted values of Asat, Vcmax, and Rdark scaled to a reference temperature of 25C. Data from these three data tables (stomatal responce, spectra, leaf traits) can be cross referenced using the unique SampleID. Additional data tables include stomatal anatomy (stomatal density, length, and width of the guard cells), hydraulic properties estimated from pressure volume curves (relative water deficit at the turgor loss point), and predawn water potential for all sampled branches. Site level data includes the dGPS location of each sampled tree, its species, and DBH. Each tabular data file (*.csv) is accompanied by a data description (*_dd.csv) which includes relevant metadata (unit, definition, data type). Copies of all raw instrument output (spectroradiometer, LICOR, pressure chamber) and included as .zip files.
Research4Life Landscape and Situation Analysis - Trends in Scholarly Communication PEST Analysis
<p>A PEST infographic summarising the key trends in scholarly communication, as identified in the report 'Research4Life Landscape and Situation Analysis' prepared by Research Consulting for the Research4Life partnership.</p>
Research4Life Landscape and Situation Analysis - Trends in the funding of research in and for LMICs PEST Analysis
<p>A PEST infographic summarising the key trends in the funding of research in and for low and middle-income countries, as identified in the report 'Research4Life Landscape and Situation Analysis' prepared by Research Consulting for the Research4Life partnership.</p>
Figure 17. A–G in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 17. A–G, Operculinoides soldadensis Vaughan & Cole; A, Loma El Santo, CA-215-871; B, Loma Candelaria, 98LC-1-669; C– F, Norona; C, NOR-UN 24; D–F, NOR-UN 15/14; G, holotype, Trinidad. H, I, Palaeonummulites trinitatensis (Nutall); H, Loma Candelaria, 98LC-1ICT3; I, holotype of Operculinoides kugleri Vaughan & Cole, Trinidad. J, Operculinoides ocalanus (Cushman), Loma Jabaco, CA-4-724. A–D, G–J, A forms in equatorial section; E, A form in axial section; F, external view.
Figure 18. A, B, D–H in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 18. A, B, D–H, Heterostegina ocalana Cushman; A, Loma Viǵıa, CA-216-D1a; B, Norona, NOR-UN 15/14; D, Loma Viǵıa, CA-216-79; E, F, Loma Jabaco; E, LM-52-756; F, LM-52-752; G, H, Norona, NOR-UN 24. C, Heterostegina cubana Cizancourt, Loma candelaria, 98LC-1H-809. I, Heterostegina sp. indet., Loma Candelaria, 98LC-1H-808. A, B, A forms in axial section; C–G, I, A forms in equatorial section; H, external view.
Figure 14 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 14. Distribution of larger benthic foraminifera (LBF) in the Loma Viǵıa section, central Cuba.
Figure 12 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 12. Distribution of larger benthic foraminifera (LBF) in the Loma El Santo section, central Cuba.
Figure 11 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 11. Distribution of larger benthic foraminifera (LBF) in the Loma Candelaria section, western Cuba (modified from Torres-Silva et al. 2017).
Figure 15. Nummulites striatoreticulatus Rutten. A–C in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 15. Nummulites striatoreticulatus Rutten. A–C, Entronque de Herradura; A, 98LC-2-686; B, 98LC-2-687; C, 98LC-2-1a. D–F, Loma Candelaria; D, 98LC-1-660; E, 98LC-1-630; F, 98LC-1-806. G–K, La Esperanza; G, E-126-474; H, E-126-466; I, E-126-458; J, E-126-470, gaps in the septa between adjacent alar prolongations of the chambers; K, E-126-459; L, M, Loma El Santo; L, CA-215- 865; M, CA-215- 65. A, B, E, F, H, I, L and M are A forms in equatorial section; C, D, G and J are A forms in axial section.
Figure 13 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 13. Distribution of larger benthic foraminifera (LBF) in the Norona section, western Cuba (modified from Torres-Silva et al. 2017).
Figure 10 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 10. Distribution of larger benthic foraminifera (LBF) in the Entronque de Herradura section, western Cuba.
Figure 8 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 8. Palaeogeographical distribution of the Eocene nummulitid species found at the Cuban localities. Map adapted from Pindell (2009).
Figure 19 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 19. Discriminant analysis of nummulitid species, where the important discriminators are ranked along the discriminant functions. Orange arrows indicate possible source of morphological changes. A, discriminant analysis within Nummulites striatoreticulatus at localities 98LC-2, 98LC-2 and E-126. B, discriminant analysis within Operculinoides floridensis at localities 98 LC-1, CA-215 and CA-216. C, discriminant analysis within O. soldadensis at localities 98LC-1, CA-125 and NOR-UN.
Figure 7. A in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 7. A, schematic diagram showing the Eocene depositional environments in sections from western and central Cuba (modified from Cotton 2012). B, schematic diagram showing depth zonation of nummulitid species and larger benthic foraminifera (LBF) present in the Eocene section across the depositional gradient (modified from Beavington-Penney & Racey 2004).
Figure 4 in Morphometric analysis of Eocene nummulitids in western and central Cuba: taxonomy, biostratigraphy and evolutionary trends
Figure 4. Discriminant analysis of nummulitid species, where the important discriminators are ranked along the discriminant functions. A, discriminant analysis between Operculinoides and Palaeonummulites species; B, discriminant analysis within Nummulites striatoreticulatus from different localities; C, discriminant analysis within O. floridensis from different localities; D, discriminant analysis within O. soldadensis from different localities.
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.