Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
736
datasets available to search
ShareScore release 0.9.0
Dataset results
736 results for “East China”
Remote Sensing based Sea Surface partial pressure of CO2 (pCO2) and air-sea CO2 flux (FCO2) in the East China Sea (2003-2019)
<p>Based on <em>in situ</em> seawater <em>p</em>CO<sub>2</sub> data collected on 51 cruises/legs over the past two decades, a satellite retrieval algorithm for seawater <em>p</em>CO<sub>2</sub> was developed by combining the semi-mechanistic algorithm and machine learning method (MeSAA-ML). MeSAA-ML introduces semi-analytical parameters, including the temperature-dependent seawater <em>p</em>CO<sub>2</sub> (<em>p</em>CO<sub>2,therm</sub> ) and upwelling index (<em>UI<sub>SST</sub></em>), to characterise the combined effect of atmospheric CO<sub>2</sub> forcing, thermodynamic effects, and multiple mixing processes on seawater <em>p</em>CO<sub>2</sub>. Additionally, considering the biological effects and various sub-regional features, multiple ocean colour parameters were also used as inputs in XGBoost, the best-selected machine learning algorithm. Independent cruise-based data were used to validate the satellite-derived <em>p</em>CO<sub>2</sub>, which achieved excellent performance in this complicated marginal sea, with low root mean square error (RMSE=19.6 μatm) and mean absolute percentage deviation (APD=4.12%). Air-sea CO2 fluxes are calculated based on retrieved seawater <em>p</em>CO<sub>2</sub>. </p>
Remote Sensing based Sea Surface partial pressure of CO2 (pCO2) and air-sea CO2 flux (FCO2) in the East China Sea (2003-2019)
<p>Based on <em>in situ</em> seawater <em>p</em>CO<sub>2</sub> data collected on 51 cruises/legs over the past two decades, a satellite retrieval algorithm for seawater <em>p</em>CO<sub>2</sub> was developed by combining the semi-mechanistic algorithm and machine learning method (MeSAA-ML). MeSAA-ML introduces semi-analytical parameters, including the temperature-dependent seawater <em>p</em>CO<sub>2</sub> (<em>p</em>CO<sub>2,therm</sub> ) and upwelling index (<em>UI<sub>SST</sub></em>), to characterise the combined effect of atmospheric CO<sub>2</sub> forcing, thermodynamic effects, and multiple mixing processes on seawater <em>p</em>CO<sub>2</sub>. Additionally, considering the biological effects and various sub-regional features, multiple ocean colour parameters were also used as inputs in XGBoost, the best-selected machine learning algorithm. Independent cruise-based data were used to validate the satellite-derived <em>p</em>CO<sub>2</sub>, which achieved excellent performance in this complicated marginal sea, with low root mean square error (RMSE=19.6 μatm) and mean absolute percentage deviation (APD=4.12%). Air-sea CO2 fluxes are calculated based on retrieved seawater <em>p</em>CO<sub>2</sub>. </p>
High-throughput in-situ plankton imaging from the East China Sea: raw images and acantharian ROIs
<p>Vertical imaging profiles were performed at four stations (3, 10, 15, 17; closed circles on the map) during the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) MR17-03C cruise from May 29 to June 13, 2017 with an ISIIS small-imager (<a href="https://www.planktonimaging.com/smaller-imagers">https://www.planktonimaging.com/smaller-imagers</a>) attached to the JAMSTEC DEEP TOW 6KCTD (<a href="https://www.jamstec.go.jp/e/about/equipment/ships/deeptow.html">https://www.jamstec.go.jp/e/about/equipment/ships/deeptow.html</a>). The ISIIS camera was programmed to take 1 photo per second coinciding with an LED flash. Each photo imaged 0.39 L (st. 3 and 10) or 0.35 L (st. 15 and 17) parcels of water in 2448 x 2050 pixel resolution, with each pixel being 22.5 µm. A Sea-Bird SBE 9 CTD was deployed with the DEEP TOW and the ISIIS internal clock was calibrated to match the CTD’s so that CTD data could be used to determine the depth at which each image was taken. Raw images are labeled with the time stamp. Acantharian ROIs are labeled with the timestamp for the raw image from which they were cropped. If more than one acantharian ROI was found in a single raw image, a letter was appended to the ROI file name. </p> <p>Accompanying data (CTD, sequencing) and analyses are available from the GitHub repository: <a href="https://github.com/maggimars/Acanth_ImageSeq">https://github.com/maggimars/Acanth_ImageSeq</a>.</p> <p> </p>
Fig. 2 in The Psilotreta Banks, 1899 of the Dabie Mountains, east central China, with descriptions of two new species (Insecta: Trichoptera: Odontoceridae)
Fig. 2. Psilotreta furcata sp.nov. A. Head, anterior view. B. Head, dorsal view. C. Maxillary palp. D. Wing veins. E. Male genitalia, left lateral view. F. Male genitalia, dorsal view. G. Male genitalia, ventral view. H. Phallus, left lateral view. I. Segment X, left lateral view. J. Parameres, posterior view. K. Aedeagus, dorsal view. Scale bars: A–C = 200 µm; D = 1 mm; E–K = 250 µm.
Fig. 1. Psilotreta daidalos Malicky 2000. A. Head, anterior view. B. Head, dorsal view. C. Maxillary palp. D. Wing veins. E. Male genitalia, left lateral view. F. Male genitalia, dorsal view. G. Male genitalia, ventral view. H. Phallus, left lateral view. I. Segment X, left lateral view. J. Parameres, ventral view. K in The Psilotreta Banks, 1899 of the Dabie Mountains, east central China, with descriptions of two new species (Insecta: Trichoptera: Odontoceridae)
Fig. 1. Psilotreta daidalos Malicky 2000. A. Head, anterior view. B. Head, dorsal view. C. Maxillary palp. D. Wing veins. E. Male genitalia, left lateral view. F. Male genitalia, dorsal view. G. Male genitalia, ventral view. H. Phallus, left lateral view. I. Segment X, left lateral view. J. Parameres, ventral view. K. Aedeagus, ventral view. Scale bars: A–C = 200 µm; D = 1 mm; E–K = 250 µm.
FIG. 7 in A new species of Tungurictis Colbert, 1939 (Carnivora, Hyaenidae) from the middle Miocene of Junggar Basin, northwestern China and the early divergence of basal hyaenids in East Asia
FIG. 7. — Tungurictis small sp., IVPP V 11497, left dentary fragment with m1 and m2 alveolus. A, stereo photos of occlusal view; B, lingual view; C, buccal view. Scale bars: 10 mm.
FIG. 5 in A new species of Tungurictis Colbert, 1939 (Carnivora, Hyaenidae) from the middle Miocene of Junggar Basin, northwestern China and the early divergence of basal hyaenids in East Asia
FIG. 5. — Tungurictis peignei, n. sp., IVPP V 25222, holotype, right dentary with p2-m2 (A, stereo photos, occlusal view, C, lingual, and D, buccal views) and IVPP V 11493, left dentary with p2-m1 (B, stereo photos, occlusal view; E, lingual view; F, buccal views). Scale bars: 10 mm.
FIG. 4 in A new species of Tungurictis Colbert, 1939 (Carnivora, Hyaenidae) from the middle Miocene of Junggar Basin, northwestern China and the early divergence of basal hyaenids in East Asia
FIG. 4. — Tungurictis peignei, n. sp., IVPP V 25222, holotype, isolated right I3, mesial view (A), right upper canine, buccal view (B), left P1, and left maxilla with P3-4 (C, stereo photos of occlusal view; D, buccal view). Scale bar: 10 mm.
Figure 4 in Two new free-living nematode species of Setosabatieria (Comesomatidea) from the East China Sea and the Chukchi Sea
Figure 4. Setosabatieria major sp. nov. (A) lateral view of male head end, showing cervical setae; (B) lateral view of female head end, showing female amphidial fovea; (C) lateral view of female vulva region, showing vulva and eggs; (D) lateral view of male tail region. Scale bars: A = 25 µm; B = 10 µm; C, D = 50 µm.
Figure 2 in Two new species of Lauratonema (Nematoda: Lauratonematidae) from the intertidal zone of the East China Sea
Figure 2. Lauratonema macrostoma sp. nov. (A) lateral view of male head end, showing amphids and bacteria; (B) lateral view of male body part, showing spicule; (C) lateral view of female body part, showing eggs; (D) lateral view of female head end, showing buccal cavity; (E) lateral view of female tail. Scale bar: A–D = 10 µm; E = 25 µm.
Figure 3 in Two new species of Lauratonema (Nematoda: Lauratonematidae) from the intertidal zone of the East China Sea
Figure 3. Lauratonema dongshanense sp. nov. (A) lateral view of male head end, showing amphid and cephalic setae; (B) lateral view of female head end, showing buccal cavity; (C) lateral view of female head end, showing amphid and bacteria; (D) lateral view of female body part, showing eggs; (E, F) lateral view of male body part, showing spicules; (G) lateral view of male tail. Scale bar: A–F = 10 µm; G = 25 µm.
Figure 1 in Two new species of Lauratonema (Nematoda: Lauratonematidae) from the intertidal zone of the East China Sea
Figure 1. Lauratonema macrostoma sp. nov. (A) lateral view of male anterior part; (B) lateral view of female tail; (C) lateral view of male tail; (D) lateral view of female posterior part, showing reproductive system; (E) lateral view of female anterior part. Scale bar: A, B, C, E = 20 µm; D = 50 µm.
Fig. 6. Physatocheila spp. A, C in Descriptions of three new species and one subspecies of Physatocheila (Heteroptera: Tingidae) from China and the Russian Far East, with an identification key to the species of the Russian fauna
Fig. 6. Physatocheila spp. A, C, Ph. dumetorum (Herrich-Schaeffer, 1838), female, 60 km SSW of Voronezh, Russia; B, D, Ph. confinis Horváth, 1905, male, environs of Teberda, 1700 m a.s.l., North Caucasus, Russia. General appearance, dorsal view (A, B); head and pronotum, dorsolateral view (C, D). Paranotum shown by arrow. Scale bars: 1 mm.
Fig. 5. Physatocheila spp. A, C in Descriptions of three new species and one subspecies of Physatocheila (Heteroptera: Tingidae) from China and the Russian Far East, with an identification key to the species of the Russian fauna
Fig. 5. Physatocheila spp. A, C, Ph. smreczynskii China, 1952, male, southern Primorskiy Territory, Russia; B, D, Ph. orientis Drake, 1942, female, Yuzhno-Sakhalinsk, Sakhalin Island, Russia. General appearance, dorsal view (A, B); head and pronotum, dorsolateral view (C, D). Paranotum shown by arrow. Scale bars: 1 mm.
Fig. 2. Physatocheila spp. A, C, E in Descriptions of three new species and one subspecies of Physatocheila (Heteroptera: Tingidae) from China and the Russian Far East, with an identification key to the species of the Russian fauna
Fig. 2. Physatocheila spp. A, C, E, Ph. potanini sp. nov., holotype, female; B, D, F, G, Ph. miyatakei latiuscula subsp. nov., holotype, male. General appearance, dorsal view (A, B); head and pronotum, dorsolateral view (C, D); labels of holotype (E, F) and paratype (G). Paranotum shown by arrow. Scale bars: 1 mm.
Fig. 3. Physatocheila spp. A, C in Descriptions of three new species and one subspecies of Physatocheila (Heteroptera: Tingidae) from China and the Russian Far East, with an identification key to the species of the Russian fauna
Fig. 3. Physatocheila spp. A, C, Ph. distinguenda (Jakovlev, 1880), female, southern Primorskiy Territory, Russia; B, D, Ph. costata (Fabricius, 1794), male, environs of St Petersburg, Russia. General appearance, dorsal view (A, B); head and pronotum, dorsolateral view (C, D). Paranotum shown by arrow. Scale bars: 1 mm.
Fig. 1. Physatocheila spp. A, C, E, F in Descriptions of three new species and one subspecies of Physatocheila (Heteroptera: Tingidae) from China and the Russian Far East, with an identification key to the species of the Russian fauna
Fig. 1. Physatocheila spp. A, C, E, F, Ph. explanata sp. nov., holotype, male; B, D, Ph. angusta sp. nov. (B, G, holotype, male; D, paratype, female). General appearance, dorsal view (A, B); head and pronotum, dorsolateral view (C, D); labels of holotype (E, G) and paratype (F). Paranotum shown by arrow. Scale bars: 1 mm.
Fig. 4. Physatocheila spp. A, C in Descriptions of three new species and one subspecies of Physatocheila (Heteroptera: Tingidae) from China and the Russian Far East, with an identification key to the species of the Russian fauna
Fig. 4. Physatocheila spp. A, C, Ph. putshkovi Golub, 1976, paratype, female, foothills of Saur Ridge, Kazakhstan; B, D, Ph. marginulata Golub, 1976, female, holotype, southern Primorskiy Territory, Russia. General appearance, dorsal view (A, B); head and pronotum, dorsolateral view (C, D). Paranotum shown by arrow. Scale bars: 1 mm.
Data of "Aerosol-cloud interactions near cloud base deteriorating the haze pollution in East China"
<p><span>The attached data is observations from ground to 1200 m a.g.l. using a tethered airship in Yangtze Rive Delta of China. The data is for analysis and figures in the study of "Aerosol-cloud interactions near cloud base deteriorating the haze pollution in East China".</span></p>
Figure 2 in First record of the East Asian fourfinger threadfin, Eleutheronema rhadinum (Jordan & Evermann, 1902), from Zhenjiang, China
Figure 2. – Lateral view of the first recorded specimen of Eleutheronema rhadinum, JSFFRI-18010, 219.6 mm SL.
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.