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12,237 results for “2019”
Community-level survey of coronavirus disease 2019 (COVID-19) preventive measures in Kwara State.
<p>Raw dataset </p>
FIGURES 1–6 in The male of Estigena wallacei Spitsyn et al., 2019 (Lepidoptera: Lasiocampidae)
FIGURES 1–6. Estigena wallacei Spitsyn, Bolotov, Kondakov & Tomilova, 2019, Flores Island, Indonesia: 1) Male specimen RMBH Sph0828, Flores Island, Labuan Bajo, Mbeliling Mountain Ecolodge; 2) Male specimen RMBH Sph0829, Flores Island, Bajawa, Wolokoro Ecolodge; 3) Holotype female RMBH Sph0571, Flores Island, Labuan Bajo, 4) Female specimen RMBH Sph0922, Flores Island, Bajawa, Wolokoro Ecolodge. Scale bar = 10 mm. 5–6) Genital capsule (left) and aedeagus (right): 5) RMBH Sph0828, 6) RMBH Sph0829. Scale bar = 1 mm. (Photos: Elizaveta Spitsyna).
PM2.5 data for "Contribution of fire emissions to PM2.5 and its transport mechanism over the Yungui Plateau, China during 2015–2019"
<p>PM2.5 data for "Contribution of fire emissions to PM2.5 and its transport mechanism over the Yungui Plateau, China during 2015–2019"</p>
SuperDARN data in netCDF format (2019-Nov)
<p>2019-Nov SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here: https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>
FIGURES 8–12. Cylindroeme vietnamica Vives, 2019 & C in A new species, Cylindroeme yunnanensis sp. nov. from China (Coleoptera, Cerambycidae, Cerambycinae)
FIGURES 8–12. Cylindroeme vietnamica Vives, 2019 & C. yunnanensis sp. nov. 8–10. Cylindroeme vietnamica; a. dorsal view; b. lateral view; c. ventral view; d. head, pronotum and scutellum, dorsal view; 11–12. C. yunnanensis sp. nov. 9. & 12. Head and prothorax, ventral view; 10 & 11. Head and apical part of pronotum, showing the differences. 8a-8c, Scale bar = 2 mm. others, not to scale.
snow samples from Svalbard 2019
<p>snow samples from the upper snow layer, sediment deposition and basic litophile elements content</p>
FIGURES 9–13 in Larval description of Limnephilus barbagaensis Malicky, Sekhi & Lounaci 2019 (Trichoptera: Limnephilidae), a micro-endemic of Algeria, with notes on its ecology
FIGURES 9–13. Limnephilus barbagaensis Malicky, Sekhi & Lounaci 2019. 9, pro-, meso-, and metanota (sa1–sa3 = setal areas 1–3, with sclerites and setae). 10, abdominal segments I–IV, right ventrolateral (dotted circles refer to sa1–3 = setal areas 1–3 on abdominal segment I; lp = lateral protuberance; lf = lateral fringe). 11, abdominal segments VIII–X, dorsal (pds = posterodorsal setae on abdominal tergum VIII; pls = posterolateral seta [paired] of abdominal segment IX; red arrow = unpaired seta on midline of tergite IX, ls = lateral sclerite of anal proleg [paired]). 12, abdominal segments VIII–X, ventral (dotted circle = ventral setae on abdominal sternum IX [paired]; ac = anal claw [paired]). 13, larval case, right lateral.
FIGURES 3–8 in Larval description of Limnephilus barbagaensis Malicky, Sekhi & Lounaci 2019 (Trichoptera: Limnephilidae), a micro-endemic of Algeria, with notes on its ecology
FIGURES 3–8. Limnephilus barbagaensis Malicky, Sekhi & Lounaci 2019, 5th instar larva. 3, head and frontoclypeal apotome, frontal. 4, head, dorsal, scale bar: 0.5 mm. 5, antennal base and antenna (white arrow), mandible and mandibular teeth (red arrow). 6, head, ventral (white arrow = cardo; va = ventral apotome), scale bar: 0.5 mm. 7, head and pronotum, lateral view (black arrow = transverse rim; red arrow = semicircular groove). 8, thorax, ventral (ph = prosternal horn; cp = central prosternite; lp = lateral prosternite).
Earthquake Archaeological Effects documented in the Cusco area in 2019 (RISC project)
<p>In 2019, the RISC project led to the implementation of an unprecedented archaeoseismological survey in the Cusco area, Peru. The main objective was to identify and map the earthquake-induced damage on the stone architecture of famous Inca archaeological sites. This spreadsheet summarizes all the observations. Each row corresponds to an Earthquake Archaeological Effect (EAE). For each strain structure, the columns contain information relative to the geographical and architectural contexts, the measurements and the level of confidence. The data were extracted from the RISC database, which supported the fieldwork. For more details about the design and structure of the RISC database please read:</p> <p>Combey et al. (2021) Monumental Inca remains and past seismic disasters: A relational database to support archaeoseismological investigations and cultural heritage preservation in the Andes, Journal of South American Earth Sciences, Volume 111, 103447,<br>https://doi.org/10.1016/j.jsames.2021.103447.</p> <p>The file is in support of the paper published in Quaternary International in 2022: <span><span><a href="https://doi.org/10.1016/j.quaint.2022.07.003"><span>https://doi.org/10.1016/j.quaint.2022.07.003</span></a></span></span></p>
Chesapeake Bay Vertical Land Motions 2019
<p>Global Positioning System (GPS) data from 2019 campaign in the Chesapeake Bay region </p>
Figure 86. Shaanxinus mingchihensis Lin, 2019. A, male left spinnerets. B, female spinnerets. Scale bar 0.1 in Evolution of nuptial-gift-related male prosomal structures: taxonomic revision and cladistic analysis of the genus Oedothorax (Araneae: Linyphiidae: Erigoninae)
Figure 86. Shaanxinus mingchihensis Lin, 2019. A, male left spinnerets. B, female spinnerets. Scale bar 0.1 mm.
The role of tropical cyclone on Changjiang River subaqueous delta geomorphology: a numerical investigation of Tropical Cyclone Danas (2019)
<p>ecs_mesh: Model domain used for numerical simulation in Matlab data format.</p> <p>Variable description of ecs_mesh.mat:</p> <p>nodex/nodey: Longitude/Latitude of the vertices of the triangles</p> <p>cellx/celly: Longitude/Latitude of the faces of the triangles</p> <p>nodeh: Bathymetry of the vertices</p> <p>nv: Vertices composition of the triangles</p> <p> </p> <p>model_result_baroclinic: Used FVCOM model output from 2019-07-01 to 2019-08-01 in Matlab data format.</p> <p>Variable description of model_result_baroclinic.mat:</p> <p>SSC: Total suspended sediment concentration of all sediment classes, units: g/L</p> <p>deposition_flux: Deposition flux of suspended sediment, units: kg/m^2/h</p> <p>divergence_sed_flux: depth-integrated divergence of sediment flux, units: kg/m^2/h</p> <p>erosion_flux: Erosion flux of sea-bed surface sediment, units: kg/m^2/h</p> <p>salinity: sea water salinity, units: psu</p> <p>taub: Total bed stress, units: Pa</p> <p>time_model: Time of the results, time zone: LST</p> <p>u: Eastward water velocity, units: m/s</p> <p>v: Northward water velocity, units: m/s</p> <p>zeta: Water surface elevation</p> <p> </p> <p>model_verify: Bed elevation data from ADV, wave parameters from buoy, and bottom suspended sediment concentration from OBS in Matlab data format.</p> <p>Variable description of model_verify.mat:</p> <p>ADV_BEC_xx: Bed Elevation measurement from ADV at Station xx, units: mm</p> <p>ADV_time_xx: Measurement time of bed elevation of ADV at Station xx, time zone: LST</p> <p>Buoy_hs_S1: Significant wave height measurement from Buoy at Station S1, units: m</p> <p>Buoy_time_S1: Measurement time of Buoy at Station S1, time zone: LST</p> <p>Buoy_tpeak_S1: Peak wave period measurement from Buoy at Station S1, units: s</p> <p>OBS_SSC_S1: Suspended sediment concentration measurement from OBS at Station S1, units: g/L</p> <p>OBS_time_S1: Measurement time of OBS at Station S1, time zone: LST</p> <p>tauc_mtke_S1: In-situ bottom shear stress calculated from turbulence kinetic energy method, units: Pa</p> <p>time_mtke_S1: Time of calculated bottom shear stress, time zone: LST</p> <p>time_wind: Time of surface wind at S1 from CFSv2 model from 2019-06-01 to 2019-08-01 time zone: LST</p> <p>u_wind: Eastward velocity of surface wind at S1 from CFSv2 model, units: m/s</p> <p>v_wind: Northward velocity of surface wind at S1 from CFSv2 model, units: m/s</p>
Quality-controlled geomagnetic hourly mean values datasets of Sheshan observatory from 1933 to 2019
<p>The Sheshan geomagnetic observatory (IAGA code SSH) is one of the earliest geomagnetic observatories in China and one of the geomagnetic observatories with the longest history in the world. The datasets include the absolute hourly mean values files of declination components D, horizontal components H and vertical components Z at SSH for 1933-2019, and the metadata files about the datasets. The datasets can be applied to the study of geomagnetic daily variation, construction of geomagnetic field model and secular variation of geomagnetic field.</p>
Dataset for a cross-sectional study collated from June 2019 to July 2022 among patients visiting Kalkaal Hospital, Mogadishu, Somalia
<p>This is a dataset for a cross-sectional study collated from June 2019 to July 2022 among patients visiting Kalkaal Hospital, Mogadishu, Somalia. All individuals were evaluated for the presence of Hepatitis B surface antigen (HBsAg) within one hour of sample collection using fast chromatographic immunoassays. Using ELISA equipment for quantitative testing, positive individuals were confirmed. Similarly, a Hepatitis C blood test was performed using a rapid and a PCR test to validate the result. The Statistical Package for Social Science (SPSS) version 20 was used as the analysis tool.</p>
CLEF EMED 2019 Dataset
<p>This is the dataset used in our work for our SALt method (code is available at <a href="https://github.com/levnikmyskin/salt">https://github.com/levnikmyskin/salt</a>). We make here available the tf-idf vectors used in our experiments for the CLEF EMED 2019 dataset and their respective labels.</p> <p>The file is a zip compressed archive. In order to use it, simply uncompress it. Every topic has a "data" and a "labels" file, saved in npz format. For the "data" objects, use <em>scipy.sparse.load_npz</em>; for the "labels" objects, use <em>numpy.load</em> instead.</p>
Habitat heterogeneity affects the thermal ecology of the federally endangered blunt-nosed leopard lizard 2019 data
<p>Global climate change is already contributing to the extirpation of numerous species worldwide, and sensitive species will continue to face challenges associated with rising temperatures throughout this century and beyond. It is especially important to evaluate the thermal ecology of endangered ectotherm species now so that mitigation measures can be taken as early as possible. A recent study of the thermal ecology of the federally endangered Blunt-Nosed Leopard Lizard (Gambelia sila) suggested that they face major activity restrictions due to thermal constraints in their desert habitat, but that large shade-providing shrubs act as thermal buffers to allow them to maintain surface activity without overheating. We replicated this study and also included a population of G. sila with no access to large shrubs to facilitate comparison of the thermal ecology of G. sila in shrubless and shrubbed populations. We found that G. sila without access to shrubs spent more time sheltering inside rodent burrows than lizards with access to shrubs, especially during the hot summer months. Lizards from a shrubbed population had higher midday body temperatures and therefore poorer thermoregulatory accuracy than G. sila from a shrubless population, suggesting that greater surface activity may represent a thermoregulatory tradeoff for G. sila. Lizards at both sites are currently constrained from using open, sunny microhabitats for much of the day during their short active seasons, and our projections suggest that climate change will exacerbate these restrictions and force G. sila to use rodent burrows for shelter even more than they do now, especially at sites without access to shrubs. The continued management of shrubs and of burrowing rodents at G. sila sites is therefore essential to the survival of this endangered species.</p>
Aggregate TB diagnosis and treatment data, Uganda 2017 and 2019
<p>To accelerate tuberculosis (TB) control and elimination, reliable data is needed to improve the quality of TB care. We assessed agreement between a surveillance dataset routinely collected for Uganda's national TB program and a high-fidelity dataset collected from the same source documents for a research study from 32 health facilities in 2017 and 2019 for six measurements: 1) Smear-positive and 2) GeneXpert-positive diagnoses, 3) bacteriologically confirmed and 4) clinically diagnosed treatment initiations, and the number of people initiating TB treatment who were also 5) living with HIV or 6) taking antiretroviral therapy. We measured agreement as the average difference between the two methods, expressed as the average ratio of the surveillance counts to the research data counts, its 95% limits of agreement (LOA), and the concordance correlation coefficient. We used linear mixed models to investigate whether agreement changed over time or was associated with facility characteristics. We found good overall agreement with some variation in the expected facility-level agreement for the number of smear-positive diagnoses (average ratio [95% LOA]: 1.04 [0.38-2.82]; CCC: 0.78), bacteriologically confirmed treatment initiations (1.07 [0.67-1.70]; 0.82), and people living with HIV (1.11 [0.51-2.41]; 0.82). The agreement was poor for Xpert positives, with surveillance data undercounting relative to research data (0.45 [0.099-2.07]; 0.36). Although surveillance data overcounted relative to research data for clinically diagnosed treatment initiations (1.52 [0.71-3.26]) and the number of people taking antiretroviral therapy (1.71 [0.71-4.12]), their agreement as assessed by CCC was not poor (0.82 and 0.62, respectively). The average agreement was similar across study years for all six measurements, but facility-level agreement varied yearly and was not explained by facility characteristics. In conclusion, the agreement of TB surveillance data with high-fidelity research data was highly variable across measurements and facilities. To advance the use of routine TB data as a quality improvement tool, future research should elucidate and address reasons for variability in its quality.</p>
TARP 2019: SU 1105
Photogrammetric capture of stratigraphic units 1105 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2088
Photogrammetric capture of stratigraphic unit 2088 Source: Objaverse 1.0 / Sketchfab
TARP 2019: SU 2072
Photogrammetric capture of stratigraphic unit 2072. Source: Objaverse 1.0 / Sketchfab
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)
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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.