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495 results for “Serbia”
Fig. 3 in A new amphibious species of the subterranean genus Bureschia Verhoeff, 1926 (Isopoda: Oniscidea: Trichoniscidae) from Serbia
Fig. 3. Bureschia serbica sp. nov., paratype, ♀ (7.2 mm) from Suva dupka Cave (ZZDBE 1143/2). A. Left mandible. B. Right mandible.
FIG. 2 in Food worthy of kings and saints: fish consumption in the medieval monastery Studenica (Serbia)
FIG. 2. — Aerial photo of Studenica Monastery (courtesy of the BLAGO Fund).
Figure 1 from: Mudri-Stojnić S, Andrić A, Markov-Ristić Z, Đukić A, Vujić A (2021) Contribution to the knowledge of the bee fauna (Hymenoptera, Apoidea, Anthophila) in Serbia. ZooKeys 1053: 43-105. https://doi.org/10.3897/zookeys.1053.67288
Figure 1 Map of Serbia showing the locations where specimens were collected.
Figure 1 in First results of a faunistic survey on the Orthoptera of Jadovnik Mountain, southwestern Serbia, with data on the calling songs of some bush cricket species
Figure 1. Isophya clara (male).
Figure 4 in New records and faunistic data of mosquitoes (Diptera, Culicidae) from Albania, Hungary, Macedonia, Montenegro, and Serbia
Figure 4. Aedes (Ochlerotatus) punctor (Kirby, 1837) female, lateral view.
Figure 6 in Paracossulus thrips (Hübner, 1818) (Cossidae) and Lignyoptera fumidaria (Hübner, 1825) (Geometridae) - two Lepidoptera genera new for Serbia with a review of the distribution of these two Habitats Directive species in the Balkan Peninsula
Figure 6. Paracossulus thrips male at Vidlič Mt., above Gulenovci Village, 967 m.
Comprehensive dataset from high resolution UAV land cover mapping of diverse natural environments in Serbia
<p>This dataset comprises processed outputs from an unmanned aerial vehicle (UAV) image acquisition campaign conducted across 27 study sites in Serbia. Each site is organized in a separate folder, labeled by study site name, and includes the following output data for both Object-Based Image Analysis (OBIA) and Convolutional Neural Network (CNN) approaches.</p> <table> <tbody> <tr> <td> <p><span>S.No</span></p> </td> <td> <p><span>Data Alias</span></p> </td> <td> <p><span>File Type</span></p> </td> <td> <p><span>Description</span></p> </td> </tr> <tr> <td> <p><span>1</span></p> </td> <td> <p><span>name_of_the_study site_multiband (OBIA)</span></p> </td> <td> <p><span>.tif</span></p> </td> <td> <p><span>Five band raster orthomosaic containing RGB, DSM and NDVI layers rescaled from (0-255).</span></p> </td> </tr> <tr> <td> <p><span>2</span></p> </td> <td> <p><span>Vectorized_r3 (OBIA+LSMS)</span></p> </td> <td> <p><span>.shp</span></p> </td> <td> <p><span>The output from the segmentation process and is a basis of preparation for data labeling.</span></p> </td> </tr> <tr> <td> <p><span>3</span></p> </td> <td> <p><span>train_val_set (OBIA+RF)</span></p> </td> <td> <p><span>.shp</span></p> </td> <td> <p><span>Contain labeled samples of land use classes for training and validation sets for respective study site.</span></p> </td> </tr> <tr> <td> <p><span>4</span></p> </td> <td> <p><span>ClassifiedVector (OBIA+RF)</span></p> </td> <td> <p><span>.shp</span></p> </td> <td> <p><span>Classified vectorized output in rectangle shape.</span></p> </td> </tr> <tr> <td> <p><span>5</span></p> </td> <td> <p><span>ClassifiedVector_fixed (OBIA+RF)</span></p> </td> <td> <p><span>.shp</span></p> </td> <td> <p><span>Final output of the classified orthomosaic in a vector file containing all the classes in the attribute table.</span></p> </td> </tr> <tr> <td> <p><span>6</span></p> </td> <td> <p><span>RandomForest (OBIA)</span></p> </td> <td> <p><span>.txt</span></p> </td> <td> <p><span>Represents trained model.</span></p> </td> </tr> <tr> <td> <p><span>7</span></p> </td> <td> <p><span>confusion_matrix (OBIA+RF)</span></p> </td> <td> <p><span>.csv</span></p> </td> <td> <p><span>Confusion matrix for each study site</span></p> </td> </tr> <tr> <td> <p><span>8</span></p> </td> <td> <p><span>number_of_polygons (OBIA+RF)</span></p> </td> <td> <p><span>.csv</span></p> </td> <td> <p><span>Contains the number of polygons marked for training and validation.</span></p> </td> </tr> <tr> <td> <p><span>9</span></p> </td> <td> <p><span>class_area_percentage (OBIA+RF)</span></p> </td> <td> <p><span>.csv</span></p> </td> <td> <p><span>Refers to percentage coverage of each class for a given study site.</span></p> </td> </tr> <tr> <td> <p><span>10</span></p> </td> <td> <p><span>name_of_the_study_site_result (OBIA)</span></p> </td> <td> <p><span>.png</span></p> </td> <td> <p><span>Image showing the evaluation metric values for each site.</span></p> </td> </tr> <tr> <td> <p><span>11</span></p> </td> <td> <p><span>train_val_set_CNN</span></p> </td> <td> <p><span>.geojson</span></p> </td> <td> <p><span>Bounding box labeling dataset used for CNN model training for each site.</span></p> </td> </tr> <tr> <td> <p><span>12</span></p> </td> <td> <p><span>train_parameter (CNN)</span></p> </td> <td> <p><span>.csv</span></p> </td> <td> <p><span>Hyperparameters used for training the CNN model.</span></p> </td> </tr> <tr> <td> <p><span>13</span></p> </td> <td> <p><span>CNN_models</span></p> </td> <td> <p><span>.h5</span></p> </td> <td> <p><span>CNN models for each site trained with defined hyperparameters.</span></p> </td> </tr> <tr> <td> <p><span>14</span></p> </td> <td> <p><span>CNN_confusion_matrix</span></p> </td> <td> <p><span>.png</span></p> </td> <td> <p><span>Confusion matrix for each study site.</span></p> </td> </tr> <tr> <td> <p><span>15</span></p> </td> <td> <p><span>Classified_rasters_CNN</span></p> </td> <td> <p><span>.tif</span></p> </td> <td> <p><span>Classified rasters through CNN model, both reclassified and colormapped.</span></p> </td> </tr> </tbody> </table>
Figure 6 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 6 - Vector pressure index for PLRV and most important vector per locality.
Figure 5 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 5 - Vector pressure index for PVY and most important vector per locality.
Figure 3 from: Petrović-Obradović O (2013) Monitoring of aphid flight activities in seed potato crops in Serbia. ZooKeys 319: 333-346. https://doi.org/10.3897/zookeys.319.4315
Figure 3 - Total Shannon–Weaver index diversity per locality.
PRemature Acute Myocardial Infarction Register of Serbia
ClinicalTrials.gov study NCT06753591. IPD Sharing: YES. Countries: 1. Publications: 0.
FIGURE 4 in Rediscovery of Southern Barbed-wire Bush-cricket, Onconotus servillei Fischer von Waldheim (Orthoptera: Tettigoniidae: Tettigoniinae: Onconotini) in Serbia, with notes on species' calling song at the westernmost border of its distribution area
FIGURE 4. Oscillograms (A–D) and frequency spectrum (E) of calling song of Onconotus servillei: A, C—male fromVajuga (Serbia) 18 VII 2019, air temperature 24°C; B, D—male from Pâclele muddy volcanoes (Romania) 23 VI 2014, air temperature 25°C; E—male from from Vajuga (Serbia). Blue—one group of sylalbles (echeme); red—opening hemisyllable; green—closing hemisyllable.
FIGURE 1. A in Rediscovery of Southern Barbed-wire Bush-cricket, Onconotus servillei Fischer von Waldheim (Orthoptera: Tettigoniidae: Tettigoniinae: Onconotini) in Serbia, with notes on species' calling song at the westernmost border of its distribution area
FIGURE 1. A—Distribution of Onconotus servillei in Europe; B—Geographic distribution of O. servillei in Serbia: red circles—old literature data; green circle—new locality; red triangle—Moravica river, near Sokobanja; C—Pannonic steppe grassland where the O. servillei was found.
FIGURE 3 in Rediscovery of Southern Barbed-wire Bush-cricket, Onconotus servillei Fischer von Waldheim (Orthoptera: Tettigoniidae: Tettigoniinae: Onconotini) in Serbia, with notes on species' calling song at the westernmost border of its distribution area
FIGURE 3. SEM of Onconotus servillei male taxonomically structures of: A—Cercus (Romania); B—Titillator (Romania); C—Stridulatory file (Serbia). Scale bar 300 µm.
FIGURE 2. A in Rediscovery of Southern Barbed-wire Bush-cricket, Onconotus servillei Fischer von Waldheim (Orthoptera: Tettigoniidae: Tettigoniinae: Onconotini) in Serbia, with notes on species' calling song at the westernmost border of its distribution area
FIGURE 2. A—Habitus of Onconotus servillei (male); B—Dorsal view of pronotum; C—Lateral view of pronotum; D—Male 10th tergum. Scale bar 1 mm.
FIGURE 42 in Haasea Verhoeff, 1895-a genus of tumultuous history and chaotic recordsredefinition, revision of taxonomy and geographic distributions, with descriptions of two new species from Austria and Serbia (Diplopoda, Chordeumatida, Haaseidae)
FIGURE 42. Distribution of H. intermedia Mršić, 1985, H. lacusnigri (Gulička, 1968), H. makarovi sp. nov., H. microcorna (Strasser, 1971), H. plasana (Verhoeff, 1899) and H. vidinensis (Strasser, 1973a).
FIGURE 41 in Haasea Verhoeff, 1895-a genus of tumultuous history and chaotic recordsredefinition, revision of taxonomy and geographic distributions, with descriptions of two new species from Austria and Serbia (Diplopoda, Chordeumatida, Haaseidae)
FIGURE 41. Distribution of H. cyanopida (Attems, 1903), H. faucium (Verhoeff, 1931a), H. filicis (Verhoeff, 1929), H. gruberi sp. nov., H. musimontium (Strasser, 1937) and H. pretneri (Strasser, 1966).
FIGURE 32 in Haasea Verhoeff, 1895-a genus of tumultuous history and chaotic recordsredefinition, revision of taxonomy and geographic distributions, with descriptions of two new species from Austria and Serbia (Diplopoda, Chordeumatida, Haaseidae)
FIGURE 32. Haasea makarovi sp. nov., paratype male (NHMW9473). A. Left leg 1, posterior view. B. Left leg 2, posterior view. C. Left leg 3, anterior view. D. Right leg 4, anterior view. E. Left leg 5, posterior view. F. Right leg 6, anterior view. G. Left leg 7, anterior view. H. Right leg 10, posterior view. I. Leg-pair 11, posterior view. Scale bars: 0.1 mm.
FIGURE 29 in Haasea Verhoeff, 1895-a genus of tumultuous history and chaotic recordsredefinition, revision of taxonomy and geographic distributions, with descriptions of two new species from Austria and Serbia (Diplopoda, Chordeumatida, Haaseidae)
FIGURE 29. Haasea gruberi sp. nov., A. Holotype male (NHMW9470), left anterior gonopod, lateral view. B. Holotype male (NHMW9470), right anterior gonopod, mesal view. C. Holotype male (NHMW9470), posterior gonopods, anterior view. D. Male from Admonter Kogel, Austria, left anterior gonopod, lateral view. E. Male from Admonter Kogel, Austria, left anterior gonopod, mesal view. F. Male from Admonter Kogel, Austria, right posterior gonopod, posterior view. Abbreviations: ab—anterior branch; cp—coxal process; mb—medial branch; mdl—mesodistal lobe; mp—mesal process; pb—posterior branch; pl1, pl2—posterior lamellae; t—telopodite. Scale bars: 0.1 mm.
FIGURE 31 in Haasea Verhoeff, 1895-a genus of tumultuous history and chaotic recordsredefinition, revision of taxonomy and geographic distributions, with descriptions of two new species from Austria and Serbia (Diplopoda, Chordeumatida, Haaseidae)
FIGURE 31. Haasea makarovi sp. nov. A. Holotype male (NHMW9472), habitus, lateral view. B. Paratype male (NHMW9473), labrum, anterior view. C. Paratype male (NHMW9473), gnathochilarium, ventral view. D. Paratype female (IZB), gnathochilarium, ventral view. Scale bars: 1 mm (A), 0.1 mm (B–D).
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.