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FIG. 4 in Morphological identification and molecular validation of anchovies (Engraulidae) in the Persian Gulf and Oman Sea
FIG. 4. Morphological characteristics of Thryssa hamiltonii, collected from Bandar Abbas)a(snout tip above level of eye cent- er.)b(maxilla short or moderate, projects slightly beyond gill opening.)c(two supra-maxilla on upper jaw.)d(first supramaxilla small, oval.)e(the first gill arch.)f(serrae on the gillrakers not clumped.
Fig. 7 in Morphological identification and molecular validation of anchovies (Engraulidae) in the Persian Gulf and Oman Sea
Fig. 7. Morphological characteristics of Encrasicholina pseudoheteroloba, collected from Qeshm,)a(isthmus muscle)1(; reaching to hind border of gill membrane)2(; there is urohyal bony plate (3).)b (belly with needle-like scutes before pelvic fin base.)c, d(maxilla pointed posteriorly, projecting well beyond 2nd supramaxilla, reaching the margin of sub-operculum.)e(3nd anal fin ray branched.)f(3nd dorsal fin ray branched.
FIG. 5 in Morphological identification and molecular validation of anchovies (Engraulidae) in the Persian Gulf and Oman Sea
FIG. 5. Morphological characteristics of Thryssa whiteheadi, collected from Tiab)a(snout tip above level of eye centre.) b(maxilla moderate, its tip projecting just a little beyond edge of gill cover.)c) one supra-maxilla on upper jaw, jaw teeth slightly enlarged compared with other species.)d(first supra-maxilla absent.)e (the first gill arch. (f) serrae on the gillrakers not clumped.
FIG. 10 in Morphological identification and molecular validation of anchovies (Engraulidae) in the Persian Gulf and Oman Sea
FIG. 10. Morphological characteristics of larvae collected from Bandar Aftab)a) isthmus muscle (Uncertain existence urohyal bony plate(.)b(very fragile dorsal and anal fin rays and uncertain counts of unbranched and branched.)c, d(maxilla tip pointed, reaching to anterior border of pre-operculum.
FIG. 3 in Morphological identification and molecular validation of anchovies (Engraulidae) in the Persian Gulf and Oman Sea
FIG. 3. Morphological characteristics of Thryssa setirostris, collected from Bandar Abbas)a(snout tip at about level of eye center. (b(maxilla very long (the longest in Engraulidae), usually reaching at the pelvic fin base, or to the anal fin origin.)c) two supra-maxilla on upper jaw.)d(first supramaxilla great, oval.)e (the first gill arch. (f) serrae on the gillrakers not clumped.
CodiEsp codes: list of valid CIE10 codes for the CodiEsp task
<p><strong>Please cite if you use this dataset:</strong></p> <p>Antonio Miranda-Escalada, Aitor Gonzalez-Agirre, Jordi Armengol-Estapé and Martin Krallinger. Overview of automatic clinical coding: annotations, guidelines, and solutions for non-English clinical cases at CodiEsp track of CLEF eHealth 2020. In CLEF (Working Notes). 2020</p> <pre><code>@inproceedings{miranda2020overview, title={Overview of automatic clinical coding: annotations, guidelines, and solutions for non-english clinical cases at codiesp track of CLEF eHealth 2020}, author={Miranda-Escalada, Antonio and Gonzalez-Agirre, Aitor and Armengol-Estap{\'e}, Jordi and Krallinger, Martin}, booktitle={Working Notes of Conference and Labs of the Evaluation (CLEF) Forum. CEUR Workshop Proceedings}, year={2020} }</code></pre> <p> </p> <p>This compressed folder contains two files:</p> <p> + codiesp-D_codes.tsv: list of CIE10-Diagnósticos terms (2018 version) with their description in Spanish and in English.<br> + codiesp-P_codes.tsv: list of CIE10-Procedimiento terms (2018 version) with their description in Spanish and in English. In addition, the list also contains the codes until the 4th axis, which are also used in the CodiEsp-P track due to annotation reasons.</p> <p>A limited number of codes do not have an English description because they were removed from the English version but maintained in the Spanish version of the terminology.</p> <p> </p> <p>Format: <br> Tab-separated files with 3 columns<br> code es-description en-description</p> <p> </p> <p>Spanish to English description mapping:<br> For CodiEsp-D, the mapping to the English description was done through the files in the National Center for Health Statistics webpage: https://www.cdc.gov/nchs/icd/icd10cm.htm<br> Specifically, the file used was: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Publications/ICD10CM/2018/2018-ICD-10-CM-Codes-File.zip/icd10cm_codes_2018.txt</p> <p>For CodiEsp-P, the mapping to the English description was done through the files in the Centers for Medicare Services webpage: https://www.cms.gov/Medicare/Coding/ICD10/2018-ICD-10-PCS-and-GEMs<br> Specifically, the file used was: 2018_icd10pcs_codes_file.zip/icd10pcs_codes_2018.txt</p>
CNR global observation-based OMEGA3D quasi-geostrophic vertical and horizontal ocean currents (1993-2018): validation subset.
<p>A subset of the Global Ocean Multi Observations OMEGA3D product is provided here for comparison with independent in situ observations and model data. OMEGA3D product has been developed by the Consiglio Nazionale delle Ricerche in the framework of the Copernicus Monitoring Environment Marine Service (https://doi.org/10.25423/cmcc/multiobs_glo_phy_w_rep_015_007). It consists of 26 year of 3D quasi-geostrophic vertical and horizontal ocean currents (January 1993-December 2018) provided over a regular grid at 1/4° horizontal resolution, with 75 non-uniformly spaced vertical levels between the surface and 1500 m depth. The subset provided here includes horizontal velocities at 15 m and 1000 m depths (that can be used for validation with independent velocity estimates from SVP drifters and Argo floats displacements, respectively) and vertical velocities at 100 m depth (for comparison with model re-analyses). OMEGA3D product is delivered with a weekly sampling (representative of each Wednesday). The velocities are obtained by solving a Q-vector formulation of the Omega equation that explicitly considers the effect of both geostrophic advection and upper layer turbulent mixing as described by KPP parameterization. Omega forcings are estimated from the CMEMS observation-based ARMOR3D temperature and salinity multi-year data and ERA-Interim surface fluxes. </p>
Wi-Fi RSSI fingerprint dataset from two malls with validation routes in a shop-level for indoor positioning
<p><strong>Th</strong>e dataset is composed of the RSSI fingerprinting calibration of two malls employing four different smartphones with the random walking survey method. Moreover, the dataset includes validation routes performed with ten smartphones from various brands and labeled with the code of the shops where they were registered. For evaluation purposes, together with the samples, information related to the shopping center like the Euclidean distance between shops is provided. The files are described as follows:</p> <ul> <li> <p>building.csv’: two rows with the id of mall 1 and mall 2.</p> </li> <li> <p>‘floor.csv’: there is a row for each of the floors of the two malls. Three floors for mall 1 and two floors for mall 2 </p> </li> <li> <p>‘zones.csv’: for each zone is indicated the id of the mall and the id floor. There are 69 zones from mall 1 and 124 for mall 2 </p> </li> <li> <p>‘training.csv’: in this file are registered the ids and the description of the five different calibrations performed (one per smartphone) in each of the malls. </p> </li> <li> <p>‘training_sample.csv’: each row of the file has the RSSI in dBm recorded during the off-line calibration phase together with the timestamp, channel, and MAC of the AP.</p> </li> <li> <p>‘route.csv’: the id’s and the description of each of the validation routes are recorded in this file. </p> </li> <li> <p>‘route_sample.csv’: with a similar structure than the training_sample.csv, the RSSI, timestamp, channel, and MAC acquired during the validation routes are stored in this file.</p> </li> <li> <p>‘euclidea_distance.csv”: to evaluate the error of the different algorithms, this file recorded the euclidean distance from the center of a shop to each other in meters.</p> </li> </ul> <p>The dataset is to be cited as follows:<br> J. A. López-Pastor, A.J. Ruiz-Ruiz, A.J. García-Sánchez, J.L. Gómez-Tornero. Wi-Fi RSSI fingerprint dataset from two malls with validation routes in a shop-level for indoor positioning. Zenodo repository. DOI: 10.5281/zenodo.3698238</p>
Dataset from UNIBO for the deliverables 7.1 and 7.2, and SydILUC model setup, calibration and validation
<p>STAR-ProBio_ILUCLiteratureReview_v1.0 _Spreadsheet: Inventory of existing key drivers and parameters for ILUC quantification and future strategies to reduce ILUC risks, and collection of standardisation work related to the sustainability of biofuels and biomaterials.</p> <p>STAR-ProBio_ModelParameters_v13.0 _Spreadsheet: Inventory of parameters and relationships used in the SydILUC model, with related metadata, i.e. source (literature), units, suggested update period, etc... </p> <p>STAR-ProBio_CalibrationGlobalFAOSTAT_v3.0_Spreadsheet: SydILUC model historical dataset of Maize market and production data to feed, calibrate, validate and run the model</p> <p>STAR-ProBio_MaizeNationalFAOSTAT_v1.0 _Spreadsheet: SydILUC model historical dataset of Maize market and production data to feed, calibrate, validate and run the model – for the regional version of the model</p> <p>STAR-ProBio_BioplasticProductionSydILUC_v1.0 _Spreadsheet: Collection of all the yields for different bioplastics from different sources (sugar, starch, oil) – from the documents by “Biopolymers facts and statistics” by IfBB</p>
Social Value items validation through stakeholder consultation
<p>Stakeholder validation and integration of the list of social impact categories, subcategories and indicators identified in the D6.1</p> <p>This dataset has been used for these two publications:</p> <p>Imbert, E., & Falcone, P. M. (2020). Social Assessment. Transition Towards a Sustainable Biobased Economy, 64, 166</p> <p>Falcone, P. M., González García, S., Imbert, E., Lijó, L., Moreira, M. T., Tani, A., ... & Morone, P. (2019). Transitioning towards the bio‐economy: Assessing the social dimension through a stakeholder lens. Corporate Social Responsibility and Environmental Management, 26(5), 1135-1153.</p>
FIGURE 1 in Maladera rugosa (Blanchard, 1850) new combination-a valid species and senior synonym of Maladera graeca Petrovitz, 1969 (Coleoptera: Scarabaeidae Melolonthinae: Sericini)
FIGURE 1. Lectotype of Maladera rugosa (Blanchard, 1850), new combination. A, aedeagus, left side in lateral view; B, parameres, dorsal view; C, aedeagus, right side in lateral view (scale = 0.5 mm); D, habitus, dorsal view (not to scale); E, associated labels; F, head.
FIGURE5 in Description of Ptilohyale corinne sp. nov. (Amphipoda: Hyalidae) from the Bahía Blanca estuary, Argentina, including a key to all valid Ptilohyale species
FIGURE5 Ptilohyale corinne sp. nov., male holotype: a uropod 1; b uropod 2; c uropod 3; d telson. Scale bars: 200 µm.
FIGURE6 in Description of Ptilohyale corinne sp. nov. (Amphipoda: Hyalidae) from the Bahía Blanca estuary, Argentina, including a key to all valid Ptilohyale species
FIGURE6 Ptilohyale corinne sp. nov., female allotype: a antenna 2; b gnathopod 2; c coxa 3; d peraeon segments 1–3, preamplexing notch indicated by an arrow. Scale bars: 200 µm (a–c), 0.5 mm (d).
Stimuli and Results for "Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription"
<p>This contains the stimuli and the participants data for the listening tests presented in the paper:</p> <p>Adrien Ycart, Lele Liu, Emmanouil Benetos, Marcus T. Pearce. "Investigating the Perceptual Validity of Evaluation Metrics for Automatic Piano Music Transcription". <em>Transactions of the International Society for Music Information Retrieval</em>, 3(1):68-81, 2020 .</p> <p>More precisely, it contains:</p> <ul> <li>MAPS_midi_cut.zip: The MIDI files used to create the stimuli </li> <li>cut_points_seconds.zip: The points in seconds at which the MAPS music pieces were cut to make the stimuli. These correspond to manually-selected 5 to 10 seconds chunks, roughly corresponding to musical phrases.</li> <li>listening_test_results.zip: The data gathered during the listening test: <ul> <li>user_data.csv contains data about participants</li> <li>answers_data.csv contains the answers given by all participants</li> <li>comments.txt contains the comments left by the participants.</li> </ul> </li> </ul> <p>For any enquiries, please contact Adrien Ycart (a.ycart@qmul.ac.uk) or Emmanouil Benetos (emmanouil.benetos@qmul.ac.uk).</p> <p> </p>
Distribution. SE Africa from SE Zambia, S Malawi, W Mozambique, Zimbabwe, and N Botswana to Swaziland and C & E South Africa, and isolated records from Uganda and Tanzania; there are also apparently records from Togo, Benin, C Nigeria, NE Egypt, and Lesotho, but they need validation and are not mapped here. in Rhinolophidae
Distribution. SE Africa from SE Zambia, S Malawi, W Mozambique, Zimbabwe, and N Botswana to Swaziland and C & E South Africa, and isolated records from Uganda and Tanzania; there are also apparently records from Togo, Benin, C Nigeria, NE Egypt, and Lesotho, but they need validation and are not mapped here.
FIGURE 22 in Description of Pallisentis thapari n. sp. and a re-description of Acanthosentis seenghalae (Acanthocephala, Quadrigyridae, Pallisentinae) using morphological and molecular data, with analysis on the validity of the sub-genera of Pallisentis
FIGURE 22. Phylogenetic tree generated by Chaudhary et al. (2019) using maximum likelihood (ML) analysis of 18s rDNA sequence data of Pallisentis indica and related species. Tree modified from Chaudhary et al. (2019) to remove distance values and different branch lengths but retaining hypothesized phylogenetic relationships and to include the names of species associated with the sequences identified in the present work. Putative sub-genera (sensu Amin et al. 2000) indicated in color.
FIGURES 9–14 in Description of Pallisentis thapari n. sp. and a re-description of Acanthosentis seenghalae (Acanthocephala, Quadrigyridae, Pallisentinae) using morphological and molecular data, with analysis on the validity of the sub-genera of Pallisentis
FIGURES 9–14. Drawing of specimens of Acanthosentis seenghalae Chowhan, Gupta, Khera, 1988: 9. Male worm; 10. Proboscis; 11. Hooks of the proboscis; 12. Female worm; 13. Posterior end and gonopore; 14. Eggs. Scale bars: 9 = 1 mm; 10 and 12 = 500 µm; 11 = 20 µm; 13 = 200 µm; 14 = 100 µm.
FIGURE 28 in A review of the flying fish genus Cypselurus (Beloniformes: Exocoetidae). Part 1. Revision of the subgenus Zonocypselurus Parin and Bogorodsky, 2011 with descriptions of one new subgenus, four new species and two new subspecies and reinstatement of one species as valid
FIGURE 28. Flying fish Cypselurus olpar. (A)—4.3 mm SL, ~19°S ~147°E; (B)—8.6 mm SL, same place; (C)—9.4 mm SL, same place; (D)—16.0 mm SL, same place; (E)—19.8 mm SL, same place; (F)—32.0 mm SL, FRSKU 114538, 20°00'S 117°04'E; (G)—145 mm SL, IORAS 03436 (holotype), 20°00'S 117°04'E (A–E—after Belyanina, 1993; F, G—drawings by T.N. Steyker).
FIGURE 25 in A review of the flying fish genus Cypselurus (Beloniformes: Exocoetidae). Part 1. Revision of the subgenus Zonocypselurus Parin and Bogorodsky, 2011 with descriptions of one new subgenus, four new species and two new subspecies and reinstatement of one species as valid
FIGURE 25. Size variation of morphometric characters in flying fishes Cypselurus bosha (□—northern Vietnam and China, Δ—Indonesia, Philippines, Thailand, Malaysia; ◊—Kenya and Madagascar; ○—Red Sea) and C. olpar (x—western and northern Australia; +—eastern Australia). (A)—pectoral fin length (lP), (B)—pelvic fin length (lV), (C)—length of pectoral fin divided by length of pelvic fin (index lP/lV), (D)—width of interorbital space (io), (E)—lowest depth of caudal peduncle (h).
FIGURE 26 in A review of the flying fish genus Cypselurus (Beloniformes: Exocoetidae). Part 1. Revision of the subgenus Zonocypselurus Parin and Bogorodsky, 2011 with descriptions of one new subgenus, four new species and two new subspecies and reinstatement of one species as valid
FIGURE 26. Juveniles of flying fishes Cypselurus bosha (A–E) and C. olpar (F–G). (A)—25 mm SL, ZMUC uncat., Galathea Sta. 373, 4°30'N 103°28'E; (B)—28 mm SL, ZMUC uncat., same place; (C)—33 mm SL, ZMUC uncat., same place; (D)—37 mm SL, ZMUC uncat., same place; (E)—47.5 mm SL, USNM 294589, Kenya, Formosa Bay; (F)—34.5 mm SL, FRSKU 114538, 20°00'S 117°04'E; (G)—50 mm SL, IORAS 03112 (paratype), 12°28'S 128°05'E.
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.