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12,237 results for “2019”
Figure 12 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 12 Collection labels. A.Pachylabra angelica Annandale, 1920; NZSI M.11649/2. B.Ampullaria erronea Nevill, 1877; NZSI M.2404. C.Ampullaria conica var. expansa Nevill, 1877; NZSI M.2426.
Supplementary material 1 from: Miyazaki Y, Murase A (2019) Fish rubbings, 'gyotaku', as a source of historical biodiversity data. ZooKeys 904: 89-101. https://doi.org/10.3897/zookeys.904.47721
: Data type: species data
Figure 2 from: Miyazaki Y, Murase A (2019) Fish rubbings, 'gyotaku', as a source of historical biodiversity data. ZooKeys 904: 89-101. https://doi.org/10.3897/zookeys.904.47721
Figure 2 Three species targeted in leisure fishing and listed as threatened species in the Japanese national Red List. AHucho perryi (Brevoort, 1856) from a shop in Hokkaido BSillago parvisquamis Gill, 1861 from a shop facing Tokyo Bay CLates japonicus Katayama & Taki, 1984 from a shop in Miyazaki Prefecture.
Figure 3 from: Miyazaki Y, Murase A (2019) Fish rubbings, 'gyotaku', as a source of historical biodiversity data. ZooKeys 904: 89-101. https://doi.org/10.3897/zookeys.904.47721
Figure 3 The number of 'gyotaku' rubbings stocked at the 16 fishing shops targeted by the present study based on the year of creation. The bold and dotted lines indicate the estimation and the 95% CI (upper and lower limits) based on the statistical analysis using a state space model.
Figures 4-7 from: Yin A, Zhi Y, Cai Y (2019) Three new species of Meleonoma Meyrick from Yunnan, China (Lepidoptera, Gelechioidea, Xyloryctidae). ZooKeys 904: 23-33. https://doi.org/10.3897/zookeys.904.47189
Figures 4-7 Meleonoma species, morphology 4 male genitalia of M. plicata sp. nov., holotype, phallus illustrated separately (gen. slide no. YAH19068) 5 male genitalia of M. scalprata sp. nov., holotype, phallus illustrated separately (gen. slide no. YAH19069) 6 female genitalia of M. scalprata sp. nov., paratype (gen. slide no. YAH19070) 7 male genitalia of M. taeniata sp. nov., holotype, phallus illustrated separately (gen. slide no. YAH19071). Scale bars: 0.25 mm.
Figures 1-3 from: Yin A, Zhi Y, Cai Y (2019) Three new species of Meleonoma Meyrick from Yunnan, China (Lepidoptera, Gelechioidea, Xyloryctidae). ZooKeys 904: 23-33. https://doi.org/10.3897/zookeys.904.47189
Figures 1-3 Meleonoma species, morphology 1 adult of M. plicata sp. nov., holotype, male (gen. slide no. YAH19068) 2 adult of M. taeniata sp. nov., holotype, male (gen. slide no. YAH19071) 3 adult of M. scalprata sp. nov., paratype, female (gen. slide no. YAH19070). Scale bars: 2.50 mm.
Figure 1 from: Miyazaki Y, Murase A (2019) Fish rubbings, 'gyotaku', as a source of historical biodiversity data. ZooKeys 904: 89-101. https://doi.org/10.3897/zookeys.904.47721
Figure 1 An explanation of fish rubbing ('gyotaku', in Japanese). A 1st step – the fish specimen is painted using ink B 2nd step – the specimen is covered with a sheet of paper C the finished image of the fish specimen on the paper. This is known as the direct method of 'gyotaku'; there is also an indirect method whereby a sheet of paper is placed on the fish specimen, then the sheet is painted by hand using ink. See also Hiyama (1964a, b) and Shimizu (1972, 1975).
Figure 1 from: Hardy H, Knapp S, Allan EL, Berger F, Dixey K, Döme B, Gagnier P-Y, Frank J, Haston EM, Holstein J, Kiel S, Marschler M, Mergen P, Phillips S, Rabinovich R, Sanchez Chillón B, Sorensen MV, Thines M, Trekels M, Vogt R, Wilson S, Wiltschke-Schrotta K (2020) SYNTHESYS+ Virtual Access - Report on the Ideas Call (October to November 2019). Research Ideas and Outcomes 6: e50354. https://doi.org/10.3897/rio.6.e50354
Figure 1 Indicative proposal flow for SYNTHESYS+ Virtual Access proposals. Blue boxes indicated proposer(s) actions/responsibilities; violet boxes VA coordinator actions/responsibilities; green boxes indicate where communication and discussion between proposers and VA coordinators will be paramount; white (no fill) boxes indicate post-proposal actions. Double-ended arrows indicate where back-and-forth will occur between proposer(s) and VA coordinator(s).
Berkeley Earth Combined Land and Ocean Temperature Field, Jan 1850-Nov 2019
<p>These files contain a copy of the Dec 2019 version of the Berkeley Earth Land and Ocean gridded temperature dataset.</p> <p>The files present monthly temperature anomalies across the globe from January 1850 until November 2019. This is created by merging the Berkeley Earth land surface temperature dataset with a reinterpolated version of the HadSST ocean surface dataset. Two versions are available, one that extrapolates land air temperature over sea ice regions, and an alternative construction that extrapolates sea surface temperatures in sea ice regions. The version based on air temperature is recommended for most applications.</p> <p>Gridded NetCDF files are presented on either a 1 degree by 1 degree latitude-longitude grid or a 15984 element equal-area grid. The equal-area grid is used in the construction of the dataset, whereas the 1 degree grid is created at the end of the analysis for convenience.</p> <p>In additional, text files are provided containing global average time series and uncertainties for convenience.</p> <p>A new version of this dataset is created every month. Future updates can be accessed at <a href="http://berkeleyearth.org/data/">http://berkeleyearth.org/data/</a></p>
Crab spectrum 2018-03-15 2019-03-15
<p><a href="https://www.astro.unige.ch/cdci/astrooda_?src_name=Crab&RA=83.633080&DEC=22.014500&E1_keV=20&E2_keV=40&T1=2018-03-15T00:00:00.0&T2=2019-03-15T00:00:00.0&T_format=isot&catalog_selected_objects=1,2,3,4&detection_threshold=7.5&instrument=isgri&osa_version=OSA11.0&product_type=isgri_spectrum&query_status=ready&query_type=Real&radius=15&use_scws=no&selected_catalog=%7B%22cat_column_descr%22:%5B%5B%22meta_ID%22,%22%3Ci8%22%5D,%5B%22src_names%22,%22%7CS18%22%5D,%5B%22significance%22,%22%3Ef4%22%5D,%5B%22ra%22,%22%3Ef4%22%5D,%5B%22dec%22,%22%3Ef4%22%5D,%5B%22NEW_SOURCE%22,%22%3Ei2%22%5D,%5B%22ISGRI_FLAG%22,%22%3Ci8%22%5D,%5B%22FLAG%22,%22%3Ci8%22%5D,%5B%22ERR_RAD%22,%22%3Cf8%22%5D%5D,%22cat_column_list%22:%5B%5B1,2,3,4%5D,%5B%221A+0535%2B262%22,%224U+0517%2B17%22,%22Crab%22,%22H+0614%2B091%22%5D,%5B116.7,7.9,1232.6,8.1%5D,%5B84.726,77.667,83.631,94.254%5D,%5B26.314,16.487,22.015,9.165%5D,%5B-32768,-32768,-32768,-32768%5D,%5B2,2,2,2%5D,%5B0,0,0,0%5D,%5B0.0002,0.0002,0.0002,0.0002%5D%5D,%22cat_column_names%22:%5B%22meta_ID%22,%22src_names%22,%22significance%22,%22ra%22,%22dec%22,%22NEW_SOURCE%22,%22ISGRI_FLAG%22,%22FLAG%22,%22ERR_RAD%22%5D,%22cat_coord_units%22:%22deg%22,%22cat_frame%22:%22fk5%22,%22cat_lat_name%22:%22dec%22,%22cat_lon_name%22:%22ra%22%7D">www.astro.unige.ch/cdci/astrooda_?src_name=Crab&RA=83.633080&DEC=22.014500&E1_keV=20&E2_keV=40&T1=2018-03-15T00:00:00.0&T2=2019-03-15T00:00:00.0&T_format=isot&catalog_selected_objects=1,2,3,4&detection_threshold=7.5&instrument=isgri&osa_version=OSA11.0&product_type=isgri_spectrum&query_status=ready&query_type=Real&radius=15&use_scws=no&selected_catalog=%7B%22cat_column_descr%22:%5B%5B%22meta_ID%22,%22%3Ci8%22%5D,%5B%22src_names%22,%22%7CS18%22%5D,%5B%22significance%22,%22%3Ef4%22%5D,%5B%22ra%22,%22%3Ef4%22%5D,%5B%22dec%22,%22%3Ef4%22%5D,%5B%22NEW_SOURCE%22,%22%3Ei2%22%5D,%5B%22ISGRI_FLAG%22,%22%3Ci8%22%5D,%5B%22FLAG%22,%22%3Ci8%22%5D,%5B%22ERR_RAD%22,%22%3Cf8%22%5D%5D,%22cat_column_list%22:%5B%5B1,2,3,4%5D,%5B%221A+0535%2B262%22,%224U+0517%2B17%22,%22Crab%22,%22H+0614%2B091%22%5D,%5B116.7,7.9,1232.6,8.1%5D,%5B84.726,77.667,83.631,94.254%5D,%5B26.314,16.487,22.015,9.165%5D,%5B-32768,-32768,-32768,-32768%5D,%5B2,2,2,2%5D,%5B0,0,0,0%5D,%5B0.0002,0.0002,0.0002,0.0002%5D%5D,%22cat_column_names%22:%5B%22meta_ID%22,%22src_names%22,%22significance%22,%22ra%22,%22dec%22,%22NEW_SOURCE%22,%22ISGRI_FLAG%22,%22FLAG%22,%22ERR_RAD%22%5D,%22cat_coord_units%22:%22deg%22,%22cat_frame%22:%22fk5%22,%22cat_lat_name%22:%22dec%22,%22cat_lon_name%22:%22ra%22%7D</a></p>
TBFY RDF data from 2019
<p>TheyBuyForYou RDF data from 2019. The file containes the RDF data month by month.</p>
2019_Winter_Gucheng_ACSMData
<p>Data used in the paper "Chemical Differences between PM<sub>1</sub> and PM<sub>2.5</sub> in Highly Polluted Environment and Implications in Air Pollution Studies"</p>
Catalogues for 2019 zoonoses data reporting
<p>The EFSA catalogues applied for the 2019 zoonoses data reporting are made available in Excel format for easier use and reference.</p>
Carbon action MULTA Finnish carbon sequestration experimental field dataset 2019
<p>This dataset includes the first year observations of the Finnish Carbon Action carbon sequestration experiment. In the experiment c.a. 100 farms test carbon farming methods on a test field and an adjacent control plot. 26 of the farms were sampled during 2019 combining field observations and soil sampling. This data will be coupled with satellite imagery, field sensors and carbon cycle modeling to forecast carbon sequestration. Subsequent sampling will track changes in soil carbon stock and soil productivity.</p> <p>The dataset will be updated annually. New datasets will be published in https://zenodo.org/communities/carbonaction/ . Includes data on:</p> <ul> <li>soil properties (CEC, pH, OM)</li> <li>nutrients: P, K, S, Ca, Mg, Cu, Zn, B, Mn (Fe, Al, P-saturation)</li> <li>physical quality: soil structure (VESS), bulk density, porosity, water holding capacity, infiltration rate</li> <li>biological properties: earthworm counts, above ground biomass, plant cover (%)</li> </ul> <p> </p> <p> </p>
In silico identification of vaccine targets for 2019-nCoV (Data tables)
<p><strong>Background</strong> The newly identified coronavirus known as 2019-nCoV has posed a serious global health threat. According to the latest report (<a href="https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200218-sitrep-29-covid-19.pdf?sfvrsn=6262de9e_2">18-February-2020</a>), it has infected more than 72,000 people globally and led to deaths of more than 1,016 people in China.</p> <p><strong>Methods</strong> The 2019 novel coronavirus proteome was aligned to a curated database of viral immunogenic peptides. The immunogenicity of detected peptides and their binding potential to HLA alleles was predicted by immunogenicity predictive models and NetMHCpan 4.0.</p> <p><strong>Results</strong> We report <em>in silico</em> identification of a comprehensive list of immunogenic peptides that can be used as potential targets for 2019 novel coronavirus (2019-nCoV) vaccine development. First, we found 28 nCoV peptides identical to Severe acute respiratory syndrome-related coronavirus (SARS CoV) that have previously been characterized immunogenic by T cell assays. Second, we identified 48 nCoV peptides having a high degree of similarity with immunogenic peptides deposited in The Immune Epitope Database (IEDB). Lastly, we conducted a <em>de novo</em> search of 2019-nCoV 9-mer peptides that i) bind to common HLA alleles in Chinese and European population and ii) have T Cell Receptor (TCR) recognition potential by positional weight matrices and a recently developed immunogenicity algorithm, iPred, and identified in total 63 peptides with a high immunogenicity potential.</p> <p><strong>Conclusions</strong> Given the limited time and resources to develop vaccine and treatments for 2019-nCoV, our work provides a shortlist of candidates for experimental validation and thus can accelerate development pipeline.</p>
Dataset accompanying Nikita et al. 2019, AJPA 169, 704-713.
<p>This Excel file provides the raw data for the 29 male individuals from the Athens Collection used in Nikita E, Xanthopoulou P, Bertsatos A, Chovalopoulou ME, Hafez I (2019). <em>A three‐dimensional digital microscopic investigation of entheseal changes as skeletal activity markers</em>. Am J Phys Anthropol 169(4), 704-713. In particular, the data provided includes information on age-at-death, stature, body mass, entheseal porosity and entheseal roughness. For details on how these variables have been estimated, please see the associated AJPA publication.</p> <p> </p>
Hull Springs Farm Weather Data 2019-11-11 to 2019-12-11
<p>General Metadata for Hull Springs Farm Atmospheric Sampling Station</p> <p> </p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>HSF_weather_YYYY-MM-DD_metadata.txt </code></pre> <p>Where YYYY-MM-DD is the date that the sampling period ended.</p> <p> </p> <p>File Created</p> <ul> <li>2019-10-27 by KF</li> </ul> <p> </p> <p>File Modified</p> <p> </p> <p>Description</p> <p>These data are from a weather station installed at Hull Springs Farm near the "Yellow House" (38.121683, -76.666781) as part of the Longwood Environmental Observatory.</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p> </p> <p>Station Specifics</p> <p>The specific at each site are:</p> <pre><code>* Barometric Pressure (mmHg) - Campbell Scientific CS100 Barometric Pressure Sensor * Light Flux Density (kW/m^2) - Campbell Scientific Pyranometer CS300 * Light Total Flux (kJ/m^2) - Campbell Scientific Pyranometer CS300 * Rainfall (mm) - Texas Electronics TE525 Tipping Bucket * Temperature (dC) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Relative Humidity (%) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Wind Speed (m/s) - RM Young 05103 Wind Speed and Direction Sensor * Wind Direction (degrees from true N) - RM Young 05103 Wind Speed and Direction Sensor * Data Collection - Campbell Scientific CR200 Data Logger * The sensors are sampled every 15 minutes </code></pre> <p> </p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* DATE - the date that the record was collected (YYYY-MM-DD) * TIMESTAMP - the date and time that the record was collected (YYYY-MM-DD HH:MM:SS) * RECORD.x - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Avg - The average battery voltage (Volts) * BattV - The battery voltage at the time of the sampling (Volts) * BP_mmHg_Avg - The average barometric pressure over the sampling interval (mmHg) * BP_mmHg_Std - The standard deviation of the average barometric pressure (mmHg) * BP_mmHg - The barometric pressure at the time of the sampling (mmHg) * Rain_mm_Tot - The total rainfall during the sampling interval (mm) * AirTC_Avg - The average air temperature during the sampling interval (dC) * AirTC_Std - The standard deviation of the average air temperature (dC) * AirTC - the air temperature at the time of the sampling (dC) * RH - the relative humidity at the time of the sampling (%) * RH_Min - the minimum relative humidity recorded (%) * RH_TMn - the time that the minimum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RH_Max - the maximum relative humidity recorded (%) * RH_TMx - the time that the maximum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RECORD.y - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Min - the minimum battery voltage (Volts) * SlrkW_Avg - the average light flux density during the sampling interval (kW/m^2) * SlrkW_Std - the standard deviation of the average light flux density (kW/m^2) * SlrkW - the light flux density at the time of the sampling (kW/m^2) * SlrMJ_Tot - the total light flux (MJ/m^2) * WS_ms_Avg - the average wind speed during the sampling interval (m/s) * WS_ms_Std - the standard deviation of the average wind speed (m/s) * WS_ms - the wind speed at the time of the sampling event (m/s) * WindDir - the wind direction at the time of the sampling event (degrees from true N) * WS_ms_S_WVT - the average wind speed over the previous 15 minutes (m/s) * WindDir_D1_WVT - the average wind direction over the previous 15 minutes (degrees from true N) * WindDir_SD1_WVT - the standard deviation of the average wind direction over the previous 15 minutes (degrees from true N) </code></pre>
Hull Springs Farm Weather Data 2019-12-27 to 2020-01-31
<p>General Metadata for Hull Springs Farm Atmospheric Sampling Station</p> <p> </p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>HSF_weather_YYYY-MM-DD_metadata.txt </code></pre> <p>Where YYYY-MM-DD is the date that the sampling period ended.</p> <p> </p> <p>File Created</p> <ul> <li>2019-10-27 by KF</li> </ul> <p> </p> <p>File Modified</p> <p> </p> <p>Description</p> <p>These data are from a weather station installed at Hull Springs Farm near the "Yellow House" (38.121683, -76.666781) as part of the Longwood Environmental Observatory.</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p> </p> <p>Station Specifics</p> <p>The specific at each site are:</p> <pre><code>* Barometric Pressure (mmHg) - Campbell Scientific CS100 Barometric Pressure Sensor * Light Flux Density (kW/m^2) - Campbell Scientific Pyranometer CS300 * Light Total Flux (kJ/m^2) - Campbell Scientific Pyranometer CS300 * Rainfall (mm) - Texas Electronics TE525 Tipping Bucket * Temperature (dC) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Relative Humidity (%) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Wind Speed (m/s) - RM Young 05103 Wind Speed and Direction Sensor * Wind Direction (degrees from true N) - RM Young 05103 Wind Speed and Direction Sensor * Data Collection - Campbell Scientific CR200 Data Logger * The sensors are sampled every 15 minutes </code></pre> <p> </p> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* DATE - the date that the record was collected (YYYY-MM-DD) * TIMESTAMP - the date and time that the record was collected (YYYY-MM-DD HH:MM:SS) * RECORD.x - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Avg - The average battery voltage (Volts) * BattV - The battery voltage at the time of the sampling (Volts) * BP_mmHg_Avg - The average barometric pressure over the sampling interval (mmHg) * BP_mmHg_Std - The standard deviation of the average barometric pressure (mmHg) * BP_mmHg - The barometric pressure at the time of the sampling (mmHg) * Rain_mm_Tot - The total rainfall during the sampling interval (mm) * AirTC_Avg - The average air temperature during the sampling interval (dC) * AirTC_Std - The standard deviation of the average air temperature (dC) * AirTC - the air temperature at the time of the sampling (dC) * RH - the relative humidity at the time of the sampling (%) * RH_Min - the minimum relative humidity recorded (%) * RH_TMn - the time that the minimum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RH_Max - the maximum relative humidity recorded (%) * RH_TMx - the time that the maximum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RECORD.y - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Min - the minimum battery voltage (Volts) * SlrkW_Avg - the average light flux density during the sampling interval (kW/m^2) * SlrkW_Std - the standard deviation of the average light flux density (kW/m^2) * SlrkW - the light flux density at the time of the sampling (kW/m^2) * SlrMJ_Tot - the total light flux (MJ/m^2) * WS_ms_Avg - the average wind speed during the sampling interval (m/s) * WS_ms_Std - the standard deviation of the average wind speed (m/s) * WS_ms - the wind speed at the time of the sampling event (m/s) * WindDir - the wind direction at the time of the sampling event (degrees from true N) * WS_ms_S_WVT - the average wind speed over the previous 15 minutes (m/s) * WindDir_D1_WVT - the average wind direction over the previous 15 minutes (degrees from true N) * WindDir_SD1_WVT - the standard deviation of the average wind direction over the previous 15 minutes (degrees from true N) </code></pre>
Weather Data from Env. Education Center at Lancer Park 2019-11-01 to 2019-12-05
<p>General Metadata for Lancer Park Environmental Education Center Atmospheric Sampling Station</p> <p>Files</p> <p>Specific metadata for each deployment can be found as text files with the file format of:</p> <pre><code>LP_weather_YYYY-MM-DD_metadata.txt </code></pre> <p>Where YYYY-MM-DD is the date that the sampling period ended.</p> <p>Metadata File Created</p> <ul> <li>2019-10-27 by KF</li> </ul> <p>File Modified</p> <p>Description</p> <p>These data are from a weather station installed at the Longwood University Environmental Education Center at Lancer Park (37.308189, -78.402768) as part of the Longwood Environmental Observatory.</p> <p>All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a></p> <p>Station Specifics</p> <p>The specific at each site are:</p> <pre><code>* Barometric Pressure (mmHg) - Campbell Scientific CS100 Barometric Pressure Sensor * Light Flux Density (kW/m^2) - Campbell Scientific Pyranometer CS300 * Light Total Flux (kJ/m^2) - Campbell Scientific Pyranometer CS300 * Rainfall (mm) - Texas Electronics TE525 Tipping Bucket * Temperature (dC) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Relative Humidity (%) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Wind Speed (m/s) - RM Young 05103 Wind Speed and Direction Sensor * Wind Direction (degrees from true N) - RM Young 05103 Wind Speed and Direction Sensor * Data Collection - Campbell Scientific CR200 Data Logger * The sensors are sampled every 15 minutes </code></pre> <p>Measurement Parameters, units, and Variable Names</p> <pre><code>* DATE - the date that the record was collected (YYYY-MM-DD) * TIMESTAMP - the date and time that the record was collected (YYYY-MM-DD HH:MM:SS) * RECORD.x - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Avg - The average battery voltage (Volts) * BattV - The battery voltage at the time of the sampling (Volts) * BP_mmHg_Avg - The average barometric pressure over the sampling interval (mmHg) * BP_mmHg_Std - The standard deviation of the average barometric pressure (mmHg) * BP_mmHg - The barometric pressure at the time of the sampling (mmHg) * Rain_mm_Tot - The total rainfall during the sampling interval (mm) * AirTC_Avg - The average air temperature during the sampling interval (dC) * AirTC_Std - The standard deviation of the average air temperature (dC) * AirTC - the air temperature at the time of the sampling (dC) * RH - the relative humidity at the time of the sampling (%) * RH_Min - the minimum relative humidity recorded (%) * RH_TMn - the time that the minimum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RH_Max - the maximum relative humidity recorded (%) * RH_TMx - the time that the maximum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RECORD.y - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Min - the minimum battery voltage (Volts) * SlrkW_Avg - the average light flux density during the sampling interval (kW/m^2) * SlrkW_Std - the standard deviation of the average light flux density (kW/m^2) * SlrkW - the light flux density at the time of the sampling (kW/m^2) * SlrMJ_Tot - the total light flux (MJ/m^2) * WS_ms_Avg - the average wind speed during the sampling interval (m/s) * WS_ms_Std - the standard deviation of the average wind speed (m/s) * WS_ms - the wind speed at the time of the sampling event (m/s) * WindDir - the wind direction at the time of the sampling event (degrees from true N) * WS_ms_S_WVT - the average wind speed over the previous 15 minutes (m/s) * WindDir_D1_WVT - the average wind direction over the previous 15 minutes (degrees from true N) * WindDir_SD1_WVT - the standard deviation of the average wind direction over the previous 15 minutes (degrees from true N)</code></pre>
Datasets of UV irradiance, visible and photosynthetically active radiation in Marambio, Antarctica from March 2017 to May 2019
<p>GUV radiometer data from Marambio station for the period March 2017 - May 2019. UV-B and UV-A daily maximum irradiances and dailydoses. Daily noon UV index and total column ozone. Daily maximum irradiances at 555 nm (VIS) and daily maximum of photosynthetically active radiation.</p> <p>If you use the data, please contact Kaisa Lakkala, Finnish Meteorological Institute.</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.