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12,237 results for “2019”

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zenodo40/100

Figs 11–19. Sabaha spp., adults. 11, 12 – S in New species of gelechiid moths of the genus Sabaha M. Omelko et N. Omelko, 2019 (Lepidoptera: Gelechiidae) from Borneo Island

Figs 11–19. Sabaha spp., adults. 11, 12 – S. parda sp. n.: 11 – male, holotype; 12 – female, paratype. 13 – S. insolita sp. n., female, holotype. 14–16 – S. cheemai sp. n.: 14 – male, holotype; 15 – female, paratype; 16 – male, paratype. 17, 18 – S. gemella sp. n.: 17 – male, holotype; 18 – male, paratype. 19 – S. semiatrata sp. n., male, holotype. Scale bar on holotype photos 1 mm.

opencc-by-4.0Oct 2023View details →
zenodo40/100

Figs 32–35. Sabaha spp., male genitalia. 32, 33 – S in New species of gelechiid moths of the genus Sabaha M. Omelko et N. Omelko, 2019 (Lepidoptera: Gelechiidae) from Borneo Island

Figs 32–35. Sabaha spp., male genitalia. 32, 33 – S. gemella sp. n., holotype: 32 – ventral view; 33 – aedeagus, lateral view. 34, 35 – S. pilosa sp. n., holotype: 34 – ventral view; 35 – aedeagus, lateral view. Scale bar 0.5 mm.

opencc-by-4.0Oct 2023View details →
zenodo40/100

Figure 3 in First record of Sphaerotheca magadha Prasad et al., 2019 (Amphibia: Anura: Dicroglossidae) From West Bengal, India

Figure 3. Typical habitat of Sphaerotheca magadha from Durgapur, Paschim Bardhaman district, West Bengal.

opencc-by-4.0Mar 2021View details →
zenodo40/100

Figure 2 in First record of Sphaerotheca magadha Prasad et al., 2019 (Amphibia: Anura: Dicroglossidae) From West Bengal, India

Figure 2. (A) Specimen of Sphaerotheca magadha in life collected from Durgapur, Paschim Bardhaman; (B) Male showing the two external vocal sacs; (C) Ventral view of the specimen (ZSI A14500) collected from Durgapur; (D) Ventral view of the foot with the arrow showing the inner metatarsal tubercle; (E) Ventral view of the hand.

opencc-by-4.0Mar 2021View details →
zenodo40/100

Figure 1 – Mylothris beni A in Mylothris citius Oremans, 2019 and Mylothris beni Warren-Gash, 2020 (Papilionoidea: Pieridae: Pierinae)

Figure 1 – Mylothris beni A: Male type, dorsal surface (Kenge, N. Kivu, v.2015, ABRI collection); B: Male type, ventral surface (Kenge, N. Kivu, v.2015, ABRI collection; C: Female form dorsal surface (Mamove, N. Kivu, ii.2011, author collection; D: Female form dorsal surface (Muleke, N. Kivu, viii.2012, author collection). Both female identities confirmed through DNA sequencing.

opencc-by-4.0Jul 2021View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Nov)

<p>2019-Nov AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-May)

<p>2019-May AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Jun)

<p>2019-Jun AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Jul)

<p>2019-Jul AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Dec)

<p>2019-Dec AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Sep)

<p>2019-Sep AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Mar)

<p>2019-Mar AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Oct)

<p>2019-Oct AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Aug)

<p>2019-Aug AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

AMPERE GRD & IRD Data (2019-Apr)

<p>2019-Apr AMPERE GRD and IRD data.</p><p>AMPERE IRD files contain hemispheric delta-B observations in global coordinates (geographic and AACGM). Data are blocked into 10-minute 'chunks' at 2-minute resolution for use in the fitting algorithm. Measurements flagged 'bad' in the earlier processing are removed prior to entry in IRD.</p><p>AMPERE GRD files contain hemispheric delta-B and Birkeland current fits at 2-minute resolution.</p>

opencc-zeroDec 2024View details →
zenodo40/100

NortheastChinaSoybeanYield20m: an annual soybean yield dataset at 20 m in Northeast China from 2019 to 2023

<p>Accurate monitoring of crop yield is important for ensuring food security. Current yield estimation methods, such as machine learning models or the assimilation of remotely sensed biophysical variables into crop growth models, depend heavily on ground observations and involve significant computational costs. To solve these problems, a hybrid framework coupling the World Food Studies Simulation Model (WOFOST) and the Gated Recurrent Unit model (GRU) was proposed for soybean yield estimation in Northeast China from 2019 to 2023.</p> <p>This dataset provides 20 m annual soybena yield in Northeast China from 2019 to 2023.</p> <p>*** The data file is in &ldquo;.tif" format</p> <p>*** Temporal Resolution: annually</p> <p>*** Temporal coverage: 2019-2023</p> <p>*** Pixel size: 20 m</p> <p>*** Projection information: EPSG: 4326</p>

opencc-by-4.0Dec 2024View details →
zenodo40/100

Data for: Long-term body size change in multiple landbird species, long-term change in temperature and precipitation as well as associations between temperature, precipitation, and morphological change in multiple landbird species, 2004 – 2019, 2021 - 2022.

<p>Six data sets used to look for long-term change in precipitation and temperature, body size change and possible environmental drivers of morphological change in birds captured during spring or fall migration in and around Lackawanna State Park, northeastern Pennsylvania, USA.</p> <p>The file labeled daily_temp_precip.csv contains daily precipitation and average daily temperature data from the Scranton/Wilkes Barre Airport (Avoca, Pennsylvania, USA) and the file called daily_temp_precip_1400 contains daily precipitation and daily temperature data from weather stations within 1,400 km of our study site location (41.6<sup>o</sup>N, 75.7<sup>o</sup>W), bounded by 80<sup>o</sup> W and 70<sup>o</sup>W longitude.</p> <p>The file called band_data_final.csv contains data collected from the first capture of individuals of multiple species during spring or fall migration, the file called all_hy_env_morph.csv contains temperature and precipitation anomaly data from Scranton/Wilkes Barre Airport (Avoca, Pennsylvania, USA), as well as morphological data from the first capture of all fall migrating young of the year.</p> <p>The file called all_hy_env_morph_1400.csv contains temperature and precipitation anomaly data from weather stations within 1,400 km of our study site location (41.6<sup>o</sup>N, 75.7<sup>o</sup>W), bounded by 80<sup>o</sup> W and 70<sup>o</sup>W longitude as well as morphological data from the first capture of all fall migrating young of the year while the file called local_hy_env_morph.csv contains temperature and precipitation anomaly data as well as first capture of local young of the year.</p>

opencc-by-4.0Apr 2024View details →
zenodo40/100

Solar and meteorological data collected from the Antsiranana station (Madagascar) by the ENERGY-Lab at the University of La Reunion between November 2019 and December 2024

<p>Scientific data provided by ENERGY-Lab located at the University of La Reunion. These data come from solar and meteorological stations present in the following territories: La Reunion, Comoros, Madagascar, Mauritius, Seychelles and South Africa. A THREDDS Data Server was created as part of the IOS-net (Indian Ocean Solar Network, https://galilee.univ-reunion.fr) project which aims to study the solar field and the optimisation of intelligent solar energy systems in the countries of the IOC (Indian Ocean Commission). These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats.</p>&nbsp;<p>Dataset is available from the THREDDS Data Server to this url: <a href="https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html"> https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html</a>.</p>&nbsp;<p>Data are also viewable and exploitable on the mobile application of the IOS-net project. The SolarIO app is downloadable in all stores.</p>&nbsp;<p><strong><em>ENERGY-Lab data may be reused, provided that related metadata explaining the data has been reviewed by the user, and that the data are appropriately acknowledged.</em></strong></p>

opencc-by-4.0Feb 2024View details →
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Solar and meteorological data collected from the Ouani station (Comores) by the ENERGY-Lab at the University of La Reunion between December 2019 and December 2024

<p>Scientific data provided by ENERGY-Lab located at the University of La Reunion. These data come from solar and meteorological stations present in the following territories: La Reunion, Comoros, Madagascar, Mauritius, Seychelles and South Africa. A THREDDS Data Server was created as part of the IOS-net (Indian Ocean Solar Network, https://galilee.univ-reunion.fr) project which aims to study the solar field and the optimisation of intelligent solar energy systems in the countries of the IOC (Indian Ocean Commission). These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats.</p>&nbsp;<p>Dataset is available from the THREDDS Data Server to this url: <a href="https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html"> https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html</a>.</p>&nbsp;<p>Data are also viewable and exploitable on the mobile application of the IOS-net project. The SolarIO app is downloadable in all stores.</p>&nbsp;<p><strong><em>ENERGY-Lab data may be reused, provided that related metadata explaining the data has been reviewed by the user, and that the data are appropriately acknowledged.</em></strong></p>

opencc-by-4.0Feb 2024View details →
zenodo40/100

Solar and meteorological data collected from the Antananarivo station (Madagascar) by the ENERGY-Lab at the University of La Reunion between November 2019 and December 2024

<p>Scientific data provided by ENERGY-Lab located at the University of La Reunion. These data come from solar and meteorological stations present in the following territories: La Reunion, Comoros, Madagascar, Mauritius, Seychelles and South Africa. A THREDDS Data Server was created as part of the IOS-net (Indian Ocean Solar Network, https://galilee.univ-reunion.fr) project which aims to study the solar field and the optimisation of intelligent solar energy systems in the countries of the IOC (Indian Ocean Commission). These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats.</p>&nbsp;<p>Dataset is available from the THREDDS Data Server to this url: <a href="https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html"> https://galilee.univ-reunion.fr/thredds/catalog/dataStations/catalog.html</a>.</p>&nbsp;<p>Data are also viewable and exploitable on the mobile application of the IOS-net project. The SolarIO app is downloadable in all stores.</p>&nbsp;<p><strong><em>ENERGY-Lab data may be reused, provided that related metadata explaining the data has been reviewed by the user, and that the data are appropriately acknowledged.</em></strong></p>

opencc-by-4.0Feb 2024View details →

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