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797 results for “GR”
Outdoor mesocosm study evaluating how mass, NaCl tolerance, and pesticide tolerance affect oxidative stress biomarkers (CAT, SOD, GR, GPx, TBARS) in larval wood frogs (Rana sylvatica) exposed to baseline and NaCl-contaminated conditions, 2019
Biomarkers of oxidative stress can aid in wildlife monitoring by allowing conservationists to detect sublethal environmental shifts. However, interpretation of stress responses can be complicated by multiple interacting factors (e.g., individual development, evolved physiological tolerance to stressors) which alter biomarker expression. Here, we investigated how individual ontogenetic traits and population-level tolerance traits influence oxidative stress responses under baseline and contaminated environmental conditions. For our model contaminant, we used NaCl (common freshwater contaminant due to factors such as coastal flooding, irrigation, airborne salt circulation, drought, runoff from road deicing salts). For our model wildlife populations, we used larval wood frogs (Rana sylvatica) from six noninteracting populations known to vary in two population-level tolerance traits: NaCl tolerance (calculated as average time to death from lethal NaCl exposure) and pesticide tolerance (determined by proxy of distance to agriculture - a consistent and highly repeatable relationship). At an outdoor research facility, R. sylvatica tadpoles were exposed to either baseline conditions (0 g/L NaCl added) or NaCl-contaminated conditions (1 g/L NaCl added for 21 days, then reduced to 0.5 g/L NaCl). Exposures were conducted in individual units with 40 replicates per population for each treatment. The experiment was terminated per individual to capture the full term of larval development (Developmental stage: Gosner stage 36), lasting between 33-48 days. For each individual, we measured mass, Snout-Vent-Length, and developmental stage before processing for biomarker expression. Individual homogenates were assayed for oxidative stress biomarkers superoxide dismutase (SOD; responsible for Reactive Oxygen Species capture and peroxide production), glutathione peroxidase (GPx; responsible for high-affinity peroxide reduction), catalase (CAT; responsible for low-affinity peroxide reducti
Rockfall PE GR-FL gpkg
<p>Geopackage with stopping points and volumes of past rockfall events in Liechtenstein and the canton of Grisons (CH).</p> <p>This dataset belongs to the publication "Automated delimitation of rockfall hazard indication zones<br> using high resolution trajectory modelling at regional scale", by L. Dorren et al. (2023). Geosciences.</p>
Fr. Gr. Rau (r2375)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Fr. Gr. Rau<br><u>musiXplora-ID</u>: r2375<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/r2375">https://musixplora.de/mxp/r2375</a><br><u>Gender</u>: m<br><u>First Mentioned</u>: 1886<br><u>Sectors</u>: Instrumentenbau<br><u>Professions (Historical)</u>: Saiteninstrumentenmacher<br><u>Professions (Musical)</u>: Zupfinstrumentenbauer<br><u>Other Places of Activity</u>: Nürnberg<br><br><br><u>Titel/Medien:</u><br><table><tbody><tr><th>Role</th><th>Sigel</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>Henkel 2013</td><td>Zitherbauer und -händler nach den Weltadreßbüchern von Paul de Wit. Unveröffentliches Ms.</td><td><a href="https://musixplora.de/mxp/5001813">5001813</a></td></tr></tbody></table><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Implementation of GR hydrological models in 95 near-natural catchments across Chile
<p>All the files included here contain the data and calibration results produced for the paper "Exploring parameter (dis)agreement due to calibration metric selection in conceptual rainfall-runoff models" accepted for publication in Hydrological Sciences Journal (HSJ). This database summarizes the calibrated parameter sets for the GR4J, GR5J and GR6J conceptual rainfall-runoff models, all coupled to the CemaNeige snow module (i.e., GRXJ + CemaNeige = GRXJCN), using 12 objective functions. The models are configured for 95 near-natural catchments located in Continental Chile. Each basin is identified by a unique code registered in the National Water Bank (BNA by its acronym in Spanish) by the Chilean Water Bureau (DGA; https://dga.mop.gob.cl/). Meteorological forcings and hypsometric curves for each basin studied are also included.</p> <p>The information is organized as follows:</p> <p>- "01 Forcings" : It includes a "Comma-separated value" file (".csv") per basin (according to the notation "BNA code.csv") which contains daily time series of precipitation (P; mm/d), temperature (°C) and potential evapotranspiration (E; mm/d) for the period 1980-01-01 to 2017-12-31. The daily runoff observations (Q; mm/d) and snow water equivalent (SWE; mm) from Cortés et al. (2017) are included. P and T are estimated from the basin-scale average of the CR2Met v2.0 gridded product, while E was calculated using Oudin's formula.<br> - "02 Hypsometry" : It includes a "Comma-separated value" file (".csv") per basin with elevation (in m a.s.l.) vs. area below elevation (in percentage) in the format required by GR models ("BNA code.csv" notation), and the full hypsometric curve ("BNA code_original.csv" notation) retrieved from the SRTM DEM clipped to the basin of interest.<br> - "03 Calibrated parameters": It includes one sub-directory per basin, containing a summary of the calibrated parameters for each combination of model structure (GR4JCN, GR5JCN and GR6JCN) and objective function.</p> <p>Additionally, we include the following "Comma-separated value" (i.e., ".csv") files:</p> <p>- "BNA_select.csv": list of case study basins (BNA code and name).<br> - "Catchment_attributes_CAMELS-CL.csv": catchments attributes directly obtained from CAMELS-CL.<br> - "Catchment_attributes.csv": catchments attributes used for this study. Note that this file contains re-calculated values for climatic attributes. </p>
DC & GR instances
<p>Sets of instances for the P||Cmax problem. </p><p>They are formatted in JSON. In each instance entry, n is the number of jobs, m the number of machines, P is the list of processing times. </p><p>DCU and DCNU instances are generated according to [1]. </p><p>GR1, GR2 and GR3 instances are generated according to [2]. GR2 instance set uses m = 5 as an extra value which is not used in [2]. </p><p>[1] Della Croce, F. & Scatamacchia, R. (2020). The longest processing time rule for identical parallel machines revisited. Journal of Scheduling, 23(2), 163–176. </p><p>[2] Gupta, J. N. & Ruiz-Torres, A. J. (2001). A listfit heuristic for minimizing makespan on identical parallel machines. Production Planning & Control, 12(1), 28–36.</p><p> </p>
Morphing libraries, QSAR models, and compounds predicted to be active on the Glucocorticoid receptor (GR)
<p>This repository contains datasets and files related to the computational drug discovery project of the chemical space exploration of the Glucocorticoid receptor. The accompanying Python code is freely available in the GitHub repository (<a title="https://github.com/Iagea/GRML_analyses" href="https://github.com/Iagea/GRML_analyses" target="_blank" rel="noreferrer noopener">https://github.com/Iagea/GRML_analyses</a>).</p> <p><strong>Morphing Libraries:</strong></p> <ul> <li><strong>GRML_library.csv:</strong> The GRML library is the collection of 999,015 virtual compounds generated by Molpher [1-2] starting from GR ligands with unique Bemis-Murcko scaffolds collected from the ChEMBL17 and IMG libraries.</li> <li><strong>RML_library.csv:</strong> The RML library is the collection of 1,346,310 virtual compounds generated by Molpher starting from compounds with unique Bemis-Murcko scaffolds randomly selected from the ZINC database.</li> </ul> <p><strong>IMG library:</strong></p> <ul> <li><strong>IMG_non_proprietary.csv</strong>: The non-proprietary IMG library subset containing 12,956 compounds and their corresponding B-scores from the primary screen.</li> </ul> <p><strong>Molpher inputs:</strong></p> <ul> <li><strong>GR_inputs.csv</strong>: The GR inputs are the ligands used to create the GRML library, 204 compounds from ChEMBL17 (95 compounds) and the non-proprietary dataset from IMG (109 compounds).</li> <li><strong>Random_inputs.csv</strong>: The random inputs are 249 random ZINC compounds used to create the Random library.</li> </ul> <p><strong>Model's training sets:</strong></p> <ul> <li><strong>Model33_training_set.csv</strong>: Random forest classification model training set, it includes 865 compounds; known GR actives and inactives from ChEMBL33 (738 compounds) and non-proprietary active ligands from the IMG library (127 compounds).</li> <li><strong>Model17_training_set.csv</strong>: Random forest classification model training set, it includes 601 compounds; known GR actives and inactives from ChEMBL17 (474 compounds) and non-proprietary active ligands from the IMG library (127 compounds).</li> <li><strong>RFR_training_set.csv</strong>: Random forest regression model training set, it includes 89 compounds; known GR actives and inactives from ChEMBL33 that fit into the GR pharmacophore with the four features we describe in our paper.</li> </ul> <p><strong>Models:</strong></p> <ul> <li><strong>Model33.pkl:</strong> Python pickle file containing the trained Random forest classification models used along with Mondrian cross-conformal prediction to classify GR actives/inactives. This model was trained with ChEMBL33 and IMG libraries.</li> <li><strong>Model17.pkl</strong>: Python pickle file containing the trained Random forest classification models used along with Mondrian cross-conformal prediction to classify GR actives/inactives. This model was trained with ChEMBL17 and IMG libraries.</li> <li><strong>RFR_models.pkl</strong><em>: </em>Python pickle file containing the 100 trained random forest regression models used to rank the proposed active morphs. These models were trained with the RFR_training_set.csv.</li> </ul> <p><strong>Active predicted morphs:</strong></p> <ul> <li><strong>all_morphs_actives</strong><em><strong>_</strong></em><strong>predicted.xlsx:</strong> An Excel spreadsheet containing two sheets. 1) All 22,524 GRML active predicted morphs. 2) All 4,341 RML active predicted morphs. The QED, NIBR Severity Score, and Molskill Score are given for each morph.</li> </ul> <p><strong>Proposed GR active ligands:</strong></p> <ul> <li><strong>designed_ligands.xlsx</strong>: An Excel spreadsheet containing two sheets. 1) All 54 designed GR ligands with their QED, NIBR severity score, MolSkill score, consensus ranking from the 100 RFR models, and the result of the manual annotation and remarks, if available. 2) The structure of the 54 ligands based on their manual annotation and presence or not in ChEMBL33 database.</li> </ul> <p>Researchers and professionals in the field of drug discovery and cheminformatics may find these resources useful for further analysis and investigations.</p> <p><strong>Bibliography</strong></p> <p>[1] Hoksza, D., Škoda, P., Voršilák, M. <em>et al.</em> Molpher: a software framework for systematic chemical space exploration. <em>J Cheminform</em> <strong>6</strong>, 7 (2014). https://doi.org/10.1186/1758-2946-6-7</p> <p>[2] <a href="https://github.com/lich-uct/molpher-lib">https://github.com/lich-uct/molpher-lib</a></p>
NYMPHE Horizon 2020 project Falasarna (GR) Test Sites preliminary data
<p>The dataset is a preliminary vision on the Falasarna (GR) test site for bioremediation action in the EU funded Horizon 2020 project. The data set iwill be used to futher refine the datasets structure and to define the hyerachical data dependences. The distribution of the typical species for phrigana habitat was investigated. The data were obtain prior application of the bioremediation measures. The data collection mission took place in October 2024. The valuee were obtaiing by direct measurement on site, </p>
GR_PIOP_1219X519_Tsouchlis_Epilegmena_Dimosieumata_Xiakoy_Typou_09/29/22
Documentation material from the Mastic pilot of the Mingei project
Animal and pasture data of AGROMIX WP3 pilot site trial at Tenuta di Paganico (GR) Italy (Spring 2021)
<p>Dataset of collected data on herbage, production , animal intake, and animal welfare in spring 2021 at Tenuta di Paganico (GR) Italy</p>
Text-fig. 10. Typical elements of the flora of Sjurkum. 1 – Myrica vyvenkensis AKHMETIEV, leaf, × 0.7; 2 – Rhododendron lancifolium AKHMETIEV, leaf, × 0.7; 3, 4 – cf. Vaccinium sp., leaves, × 0.8 and 1; 5 – Salix sp. (ex gr. S. glauca L.), leaf, × 0.7; 6 – Carpinus sp., involucre, × 1 (coll. Geol. Inst. RAS Moscow). in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 10. Typical elements of the flora of Sjurkum. 1 – Myrica vyvenkensis AKHMETIEV, leaf, × 0.7; 2 – Rhododendron lancifolium AKHMETIEV, leaf, × 0.7; 3, 4 – cf. Vaccinium sp., leaves, × 0.8 and 1; 5 – Salix sp. (ex gr. S. glauca L.), leaf, × 0.7; 6 – Carpinus sp., involucre, × 1 (coll. Geol. Inst. RAS Moscow).
Text-fig. 13. Typical elements of the flora of Velikaya Kema (coll. Geol. Inst. RAS Moscow). 1 – Abies sp. 1, twig, × 0.7; 2 – Larix sp., seed cone, × 0.7; 3 – Calocedrus sp., twig, × 0.7; 4 – Picea sp., seed, × 0.8; 5 – Abies sp. 2, seed, × 0.7; 6 – Metasequoia occidentalis (NEWBERRY) CHANEY, leafy shoot, × 0.7; 7 – Ostrya sp., involucre, × 0.7; 8 – Carpinus sp. (ex gr. C. cordata BLUME), involucre, × 0.7; 9 – Carpinus sp. 2 (ex gr. C. tschonoskii MAXIMOVITCH), involucre, × 0.7; 10 – Ulmus sp., leaf, × 0.7; 11 – Acer miocaudatum HU et CHANEY, leaf, × 0.8; 12 – Engelhardia (Alfaropsis) koreanica OISHI, ×; 13 – Comptonia naumannii NATHORST, leaf, × 0.7; 14 – Craigia oregonensis (ARNOLD) KVAČEK, BŮžEK et MANCHESTER, capsule valve, × 0.6; 15 – Cercidiphyllum crenatum (UNGER) R. BROWN, leaf, × 0.7; 16 – Sassafras subtriloba (KONNO) TANAI, leaf, × 0.7; 17 – Dicotylophyllum sp., leaf, × 0.7; 18 – Quercus kodairae HUZIOKA, leaf, × 1; 19 – Carpinus subcordata NATHORST, leaf, × 0.7; 20 – Ailanthus sp., fruit, × 1; 21 – Diospyros miokeaki HU et CHANEY, leaf, × 0.5. in Mid-Latitude Palaeogene Floras Of Eurasia Bound To Volcanic Settings And Palaeoclimatic Events - Experience Obtained From The Far East Of Russia (Sikhote-Alin') And Central Europe (Bohemian Massif)
Text-fig. 13. Typical elements of the flora of Velikaya Kema (coll. Geol. Inst. RAS Moscow). 1 – Abies sp. 1, twig, × 0.7; 2 – Larix sp., seed cone, × 0.7; 3 – Calocedrus sp., twig, × 0.7; 4 – Picea sp., seed, × 0.8; 5 – Abies sp. 2, seed, × 0.7; 6 – Metasequoia occidentalis (NEWBERRY) CHANEY, leafy shoot, × 0.7; 7 – Ostrya sp., involucre, × 0.7; 8 – Carpinus sp. (ex gr. C. cordata BLUME), involucre, × 0.7; 9 – Carpinus sp. 2 (ex gr. C. tschonoskii MAXIMOVITCH), involucre, × 0.7; 10 – Ulmus sp., leaf, × 0.7; 11 – Acer miocaudatum HU et CHANEY, leaf, × 0.8; 12 – Engelhardia (Alfaropsis) koreanica OISHI, ×; 13 – Comptonia naumannii NATHORST, leaf, × 0.7; 14 – Craigia oregonensis (ARNOLD) KVAČEK, BŮžEK et MANCHESTER, capsule valve, × 0.6; 15 – Cercidiphyllum crenatum (UNGER) R. BROWN, leaf, × 0.7; 16 – Sassafras subtriloba (KONNO) TANAI, leaf, × 0.7; 17 – Dicotylophyllum sp., leaf, × 0.7; 18 – Quercus kodairae HUZIOKA, leaf, × 1; 19 – Carpinus subcordata NATHORST, leaf, × 0.7; 20 – Ailanthus sp., fruit, × 1; 21 – Diospyros miokeaki HU et CHANEY, leaf, × 0.5.
Animal and microclimate data of AGROMIX WP3 pilot site trial at Tenuta di Paganico (GR) Italy - (2021 and 2022)
<p>Datasets of collected data on (i) animal weight and average daily gain, (ii) hair cortisol, (iii) blood glucose (iv) and black globe humidity index during the trial conducted in Spring and summer 2021 and 2022 at the AGROMIX trial site of Tenuta di Paganico (GR), Italy.</p>
Text-fig. 4. Small mammals from Middle Pleistocene site of Yenişarbademli (Central Turkey). a–e – Microtus ex gr. arvalis-socialis: a – m1 and fragmentary m2 sin., EUNHM PV-13210; b – fragmentary m3 sin., EUNHM PV-13211; c – M3 dex., EUNHM PV- 13212a; d, e – fragmentary M3 dex., EUNHM PV-13212b, EUNHM PV-13212c; f – cf. Chionomys nivalis, M3 dex., EUNHM PV-13213; g–j – Lagurus transiens: g, h – fragmentary m1 sin., EUNHM PV-13214-13215; i – m2 sin., EUNHM PV-13216; j – fragmentary M2 dex., EUNHM PV-13217; k – Clethrionomys cf. acrorhiza, fragmentary m3 sin., EUNHM PV-13218 in labial (k2) and lingual (k3) views; l – Ochotona sp., non-pussiloid form, p3 dex., EUNHM PV-13219; m–o – Microtus cf. guentheri: m – fragmentary m1 sin., EUNHM PV-13220; n – m3 sin., EUNHM PV-13221; o – M3 dex., EUNHM PV-13222. Scales for occlusal (larger), and lateral (smaller) views equal 1 mm. in Plio-Pleistocene Amphibians And Reptiles From Central Turkey: New Faunas And Faunal Records With Comments On Their Biochronological Position Based On Small Mammals
Text-fig. 4. Small mammals from Middle Pleistocene site of Yenişarbademli (Central Turkey). a–e – Microtus ex gr. arvalis-socialis: a – m1 and fragmentary m2 sin., EUNHM PV-13210; b – fragmentary m3 sin., EUNHM PV-13211; c – M3 dex., EUNHM PV- 13212a; d, e – fragmentary M3 dex., EUNHM PV-13212b, EUNHM PV-13212c; f – cf. Chionomys nivalis, M3 dex., EUNHM PV-13213; g–j – Lagurus transiens: g, h – fragmentary m1 sin., EUNHM PV-13214-13215; i – m2 sin., EUNHM PV-13216; j – fragmentary M2 dex., EUNHM PV-13217; k – Clethrionomys cf. acrorhiza, fragmentary m3 sin., EUNHM PV-13218 in labial (k2) and lingual (k3) views; l – Ochotona sp., non-pussiloid form, p3 dex., EUNHM PV-13219; m–o – Microtus cf. guentheri: m – fragmentary m1 sin., EUNHM PV-13220; n – m3 sin., EUNHM PV-13221; o – M3 dex., EUNHM PV-13222. Scales for occlusal (larger), and lateral (smaller) views equal 1 mm.
Text-fig. 3. Arvicolids from Plio-Pleistocene sites of Eskişehir-Sivrihisar region (Central Turkey). a–c – Promimomys cf. insuliferus from Nasrettinhoca 2: a – M3 dex., EUNHM PV-13200; b – fragmentary M2 sin., EUNHM PV-13201; c – M1 sin., EUNHM PV-13202; d – Promimomys sp. from Hamamkarahisar B, M1 sin., EUNHM PV-13203; e–i – Mimomys cf. hajnackensis: e, f – Hoyhoytepe 2, m1–m2 from the same mandibular tooth row: e – m1 sin., EUNHM PV-13204; f – m2 sin., EUNHM PV-13205; g, h – Mercan 1: g – M1 dex., EUNHM PV-13206; h – M3 sin., EUNHM PV-13207; i – Hoyhoytepe 3, M3 sin., EUNHM PV-13208; j – Mimomys ex gr. stehlini-hintoni from Mercan 2, M1 dex., EUNHM PV-13209 in lingual view (j2) and labial (j3) views. Scales for occlusal (larger), and lateral (smaller) views equal 1 mm. in Plio-Pleistocene Amphibians And Reptiles From Central Turkey: New Faunas And Faunal Records With Comments On Their Biochronological Position Based On Small Mammals
Text-fig. 3. Arvicolids from Plio-Pleistocene sites of Eskişehir-Sivrihisar region (Central Turkey). a–c – Promimomys cf. insuliferus from Nasrettinhoca 2: a – M3 dex., EUNHM PV-13200; b – fragmentary M2 sin., EUNHM PV-13201; c – M1 sin., EUNHM PV-13202; d – Promimomys sp. from Hamamkarahisar B, M1 sin., EUNHM PV-13203; e–i – Mimomys cf. hajnackensis: e, f – Hoyhoytepe 2, m1–m2 from the same mandibular tooth row: e – m1 sin., EUNHM PV-13204; f – m2 sin., EUNHM PV-13205; g, h – Mercan 1: g – M1 dex., EUNHM PV-13206; h – M3 sin., EUNHM PV-13207; i – Hoyhoytepe 3, M3 sin., EUNHM PV-13208; j – Mimomys ex gr. stehlini-hintoni from Mercan 2, M1 dex., EUNHM PV-13209 in lingual view (j2) and labial (j3) views. Scales for occlusal (larger), and lateral (smaller) views equal 1 mm.
Text-fig. 13. Scatter diagram of m1 length vs SDQ for pre-Eemian (time slice 5) Arvicola samples from different geographical provenances compared with M. savini-A. mosbachensis and Arvicola sapidus. Empty dotted ovals indicate the range of extant Arvicola ex gr. amphibius samples from Italy (cyan) and from the other European locations (green) Abbreviations: FR – France, GE – Germany, IT – Italy, SP – Spain. in Independent Water Vole (Mimomys Savini, Arvicola: Rodentia, Mammalia) Lineages In Italy And Central Europe
Text-fig. 13. Scatter diagram of m1 length vs SDQ for pre-Eemian (time slice 5) Arvicola samples from different geographical provenances compared with M. savini-A. mosbachensis and Arvicola sapidus. Empty dotted ovals indicate the range of extant Arvicola ex gr. amphibius samples from Italy (cyan) and from the other European locations (green) Abbreviations: FR – France, GE – Germany, IT – Italy, SP – Spain.
Text-fig. 11. Scatter diagram of m1 length vs SDQ for Würmian/Weichselian (time slice 3) Arvicola samples from different geographical provenances compared with M. savini-A. mosbachensis and extant Arvicola sapidus. Empty dotted ovals indicate the range of extant Arvicola ex gr. amphibius samples from Italy (cyan) and from the other European locations (green) Abbreviations: FR – France, GE – Germany, IT – Italy, SP – Spain. in Independent Water Vole (Mimomys Savini, Arvicola: Rodentia, Mammalia) Lineages In Italy And Central Europe
Text-fig. 11. Scatter diagram of m1 length vs SDQ for Würmian/Weichselian (time slice 3) Arvicola samples from different geographical provenances compared with M. savini-A. mosbachensis and extant Arvicola sapidus. Empty dotted ovals indicate the range of extant Arvicola ex gr. amphibius samples from Italy (cyan) and from the other European locations (green) Abbreviations: FR – France, GE – Germany, IT – Italy, SP – Spain.
Text-fig. 12. Scatter diagram of m1 length vs SDQ for Eemian (time slice 4) Arvicola samples from different geographical provenances compared with M. savini-A. mosbachensis and Arvicola sapidus. Empty dotted ovals indicate the range of extant Arvicola ex gr. amphibius samples from Italy (cyan) and from the other European locations (green) Abbreviations: FR – France, GE – Germany, IT – Italy, SP – Spain. in Independent Water Vole (Mimomys Savini, Arvicola: Rodentia, Mammalia) Lineages In Italy And Central Europe
Text-fig. 12. Scatter diagram of m1 length vs SDQ for Eemian (time slice 4) Arvicola samples from different geographical provenances compared with M. savini-A. mosbachensis and Arvicola sapidus. Empty dotted ovals indicate the range of extant Arvicola ex gr. amphibius samples from Italy (cyan) and from the other European locations (green) Abbreviations: FR – France, GE – Germany, IT – Italy, SP – Spain.
Text-fig. 6. Molars of Microtus from Mikhailovka-5. Microtus ex gr. agrestis LINNAEUS, 1761: a–l: M2, m–s: M3; Microtus (Terricola) ex gr. subterraneus (SELYS-LONGCHAMPS, 1836): t–z: m1, aa–ab: m2, ac–ag: M3. in Late Pleistocene (Eemian) Mollusk And Small Mammal Fauna From Mikhailovka-5 (Kursk Oblast, Central Russia)
Text-fig. 6. Molars of Microtus from Mikhailovka-5. Microtus ex gr. agrestis LINNAEUS, 1761: a–l: M2, m–s: M3; Microtus (Terricola) ex gr. subterraneus (SELYS-LONGCHAMPS, 1836): t–z: m1, aa–ab: m2, ac–ag: M3.
Text-fig. 5. Molars of Microtus ex gr. agrestis LINNAEUS, 1761 from Mikhailovka-5. a–l: m1, m–r: M1. in Late Pleistocene (Eemian) Mollusk And Small Mammal Fauna From Mikhailovka-5 (Kursk Oblast, Central Russia)
Text-fig. 5. Molars of Microtus ex gr. agrestis LINNAEUS, 1761 from Mikhailovka-5. a–l: m1, m–r: M1.
Text-fig. 8. Upper molars of Arvicola ex gr. sapidus MILLER, 1908 from Mikhailovka-5. a–d: M1, e–h: M2, i–q: M3. in Late Pleistocene (Eemian) Mollusk And Small Mammal Fauna From Mikhailovka-5 (Kursk Oblast, Central Russia)
Text-fig. 8. Upper molars of Arvicola ex gr. sapidus MILLER, 1908 from Mikhailovka-5. a–d: M1, e–h: M2, i–q: M3.
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.