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Рис. 8–13. ΔанΑшафты Южного УраΛа (8–11) и Русской равнины (12–13). 8 – разнотравная степь у поΑножия горы ВербΛюжка, местообитание Cionus rossicus; 9 – ксерофитные Λуга в пойме реки УраΛ вбΛизи горы ВербΛюжка, местообитание Cionus rossicus; 10 – южные степи в районе КзыΛаΑырского карстового поΛя, местообитание Cionus gebleri; 11 – степи низкогорий Южного УраΛа бΛиз с. КиΑрясово, местообитание Smicronyx albopictus; 12 – КаменноброΑские меΛовые горы на юго-запаΑе ПривоΛжской возвышенности, местообитание Mecinus janthiniformis, Smicronyx robustus и S. albopictus; 13 – меΛовой останец КобыΛья ГоΛова в прироΑном парке «Àонской», местообитание Mecinus janthiniformis. Figs 8–13. Landscapes of the Southern Urals (8–11) and the Russian Plain (12–13). 8 – forb steppe at the down of Verblyuzhka Mt., habitat of Cionus rossicus; 9 – xerophytic meadows in the floodplain of the Ural River near Verblyuzhka Mt., habitat of Cionus rossicus; 10 – southern steppes in the Kzyladyr karst area, habitat of Cionus gebleri; 11 – steppes of the low mountains of the Southern Urals near Kidryasovo village, habitat of Smicronyx albopictus; 12 – Kamennobrodsky chalk mountains in the southwest of the Volga Upland, habitat of Mecinus janthiniformis, Smicronyx robustus, and S. albopictus; 13 – Cretaceous outlier Kobyl'ya Golova in the Donskoy Nature Park, habitat of Mecinus janthiniformis. in Interesting records of weevils (Coleoptera: Curculionidae: Curculioninae) in the steppe zone of the European part of Russia and the Urals
Рис. 8–13. ΔанΑшафты Южного УраΛа (8–11) и Русской равнины (12–13). 8 – разнотравная степь у поΑножия горы ВербΛюжка, местообитание Cionus rossicus; 9 – ксерофитные Λуга в пойме реки УраΛ вбΛизи горы ВербΛюжка, местообитание Cionus rossicus; 10 – южные степи в районе КзыΛаΑырского карстового поΛя, местообитание Cionus gebleri; 11 – степи низкогорий Южного УраΛа бΛиз с. КиΑрясово, местообитание Smicronyx albopictus; 12 – КаменноброΑские меΛовые горы на юго-запаΑе ПривоΛжской возвышенности, местообитание Mecinus janthiniformis, Smicronyx robustus и S. albopictus; 13 – меΛовой останец КобыΛья ГоΛова в прироΑном парке «Àонской», местообитание Mecinus janthiniformis. Figs 8–13. Landscapes of the Southern Urals (8–11) and the Russian Plain (12–13). 8 – forb steppe at the down of Verblyuzhka Mt., habitat of Cionus rossicus; 9 – xerophytic meadows in the floodplain of the Ural River near Verblyuzhka Mt., habitat of Cionus rossicus; 10 – southern steppes in the Kzyladyr karst area, habitat of Cionus gebleri; 11 – steppes of the low mountains of the Southern Urals near Kidryasovo village, habitat of Smicronyx albopictus; 12 – Kamennobrodsky chalk mountains in the southwest of the Volga Upland, habitat of Mecinus janthiniformis, Smicronyx robustus, and S. albopictus; 13 – Cretaceous outlier Kobyl'ya Golova in the Donskoy Nature Park, habitat of Mecinus janthiniformis.
Рис. 1–7. Новые ΑΛя фауны России и маΛоизвестные виΑы жуков-ΑоΛгоносиков. 1–3 – Cionus rossicus: 1 – самец, 2 – эΑеагус, 3 – самка; 4 – Cionus gebleri; 5 – Mecinus janthiniformis; 6 – Smicronyx robustus; 7 – Smicronyx albopictus. Figs 1–7. New to the fauna of Russia and little known species of weevils. 1–3 – Cionus rossicus: 1 – male, 2 – aedeagus, 3 – female; 4 – Cionus gebleri; 5 – Mecinus janthiniformis; 6 – Smicronyx robustus; 7 – Smicronyx albopictus. in Interesting records of weevils (Coleoptera: Curculionidae: Curculioninae) in the steppe zone of the European part of Russia and the Urals
Рис. 1–7. Новые ΑΛя фауны России и маΛоизвестные виΑы жуков-ΑоΛгоносиков. 1–3 – Cionus rossicus: 1 – самец, 2 – эΑеагус, 3 – самка; 4 – Cionus gebleri; 5 – Mecinus janthiniformis; 6 – Smicronyx robustus; 7 – Smicronyx albopictus. Figs 1–7. New to the fauna of Russia and little known species of weevils. 1–3 – Cionus rossicus: 1 – male, 2 – aedeagus, 3 – female; 4 – Cionus gebleri; 5 – Mecinus janthiniformis; 6 – Smicronyx robustus; 7 – Smicronyx albopictus.
Figure 3. A European Robin, Erithacus rubecula. A in Capturing migratory birds and examining for ticks (Acari: Ixodida)
Figure 3. A European Robin, Erithacus rubecula. A. Examination of tick presence, B. Collection of immature ticks by a tweezer.
Dataset for "EuroMod: Modelling European power markets with improved price granularity"
<p>Raw and derived results to support the paper "EuroMod: Modelling European power markets with improved price granularity".</p> <p>Description and readme at <a href="https://github.com/carlamtmendes/EuroMod">https://github.com/carlamtmendes/EuroMod</a>.</p>
The second data release from the European Pulsar Timing Array III. Search for gravitational wave signals
<p>We present the results of the search for an isotropic stochastic gravitational wave background (GWB) at nanohertz frequencies using the second data release of the European Pulsar Timing Array (EPTA) for 25 millisecond pulsars and a combination with the first data release of the Indian Pulsar Timing Array (InPTA). A robust GWB detection is conditioned upon resolving the Hellings-Downs angular pattern in the pairwise cross-correlation of the pulsar timing residuals. Additionally, the GWB is expected to yield the same (common) spectrum of temporal correlations across pulsars, which is used as a null hypothesis in the GWB search. Such a common-spectrum process has already been observed in pulsar timing data. We analysed (i) the full 24.7-year EPTA data set, (ii) its 10.3-year subset based on modern observing systems, (iii) the combination of the full data set with the first data release of the InPTA for ten commonly timed millisecond pulsars, and (iv) the combination of the 10.3-year subset with the InPTA data. These combinations allowed us to probe the contributions of instrumental noise and interstellar propagation effects. With the full data set, we find marginal evidence for a GWB, with a Bayes factor of four and a false alarm probability of 4%. With the 10.3-year subset, we report evidence for a GWB, with a Bayes factor of 60 and a false alarm probability of about 0.1% (≳ 3σ significance). The addition of the InPTA data yields results that are broadly consistent with the EPTA-only data sets, with the benefit of better noise modelling. Analyses were performed with different data processing pipelines to test the consistency of the results from independent software packages. The latest EPTA data from new generation observing systems show non-negligible evidence for the GWB. At the same time, the inferred spectrum is rather uncertain and in mild tension with the common signal measured in the full data set. However, if the spectral index is fixed at 13/3, the two data sets give a similar amplitude of (2.5 ± 0.7) × 10−15 at a reference frequency of 1 yr−1 . Further investigation of these issues is required for reliable astrophysical interpretations of this signal. By continuing our detection efforts as part of the International Pulsar Timing Array (IPTA), we expect to be able to improve the measurement of spatial correlations and better characterise this signal in the coming years.</p>
Data and codes from "How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach"
<p>Codes and data used for "Savary et al. How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach".</p> <p> </p>
Attributing European forest disturbances to storm and fire
<p>This repository contains maps attributing each disturbance patch of the <a href="https://zenodo.org/record/4570157#.YFB27i337OQ">European Forest Disturbance Map</a> (version 1.1.4) to bark beetle/wind, fire or other disturbances (mostly harvest). The dataset is based on methods described in following paper, but have been updated with new reference data covering now also bark beetle disturbances: </p> <p>Senf, C. and Seidl, R. (2021) Storm and fire disturbance in Europe: Distribution and trends. <strong>Global Change Biology</strong>. <a href="https://doi.org/10.1111/gcb.15679">https://doi.org/10.1111/gcb.15679</a></p> <p>To get the year of disturbance, please see the underlaying disturbance maps (version 1.1.4.; link given above).</p> <p><strong>Map classes:</strong></p> <p>NA = no disturbance<br> 1 = bark beetle or wind disturbances (both classes had to be grouped due to technical reasons)<br> 2 = fire disturbances<br> 3 = other disturbances, mostly harvest but might include salvage logging go small-scale natural disturbances and infrequent other natural agents (e.g., defoliation, avalanches, etc.)</p> <p><strong>Reference system:</strong></p> <p>The spatial reference system is EPSG 3035 (ETRS89 / LAEA Europe).</p> <p><strong>Word of caution:</strong></p> <p>Remote sensing-based maps, while fascinating to look at, contain errors. If you intent to use the map for your research, please carefully read the discussion on limitations in the paper accompanying the dataset. There will be many instances where the attribution (or even disturbance detection) is wrong. The maps are intended to give a broad, continental-scale overview on the distribution of disturbance agents.</p>
Supplementary Material to "Overview of XBRL Taxonomy Usage for Structured Sustainability Reporting in European Filings"
<p>Hereby we provide supplementary material to the submitted paper "Overview of XBRL Taxonomy Usage for Structured Sustainability Reporting in European Filings". Two Excel spreadsheets have been provided containing the ESRS PoC XBRL taxonomy representation and a sample report of a tagged integrated annual report.</p> <p>The research is expected to be presented at the 1st Conference on Sustainability at Széchenyi István University, Hungary, October 10-12, 2023. This framework leverages an examination of the existing taxonomy of ESRS to provide readers with insight into the essential glossary of disclosures and metrics considered critical by official regulatory sources. During the analysis, all XBRL data was retrieved from public sources and processed in the programming environment currently under development by the Széchenyi István University research team.</p>
DOES - Dataset of European scrap classes
<p><strong>DOES </strong>- Dataset of European scrap classes</p>
Fig. 9 in Sex-ratio and body size plasticity in two cold-adapted ground beetles co-occurring in a periglacial area of the European Alps (Coleoptera: Carabidae)
Fig. 9 – Polynomial regression graph between elytra width of Nebria castanea females and the springtail abundance.
Fig. 7 in Sex-ratio and body size plasticity in two cold-adapted ground beetles co-occurring in a periglacial area of the European Alps (Coleoptera: Carabidae)
Fig. 7 – Boxplots of elytra width of Nebria castanea females as a function of landform. p-value of N. castanea morphometric analysis with Kruskal-Wallis test, that evaluate the presence of significant differences in body size between landforms with ice (active rock glacier) and without ice (fossil rock glacier and scree slope). Asterisk highlights significant values.
Fig. 3 in Sex-ratio and body size plasticity in two cold-adapted ground beetles co-occurring in a periglacial area of the European Alps (Coleoptera: Carabidae)
Fig. 3 – Boxplot of Nebria germarii body parameters as a function of sex (F=female; M=male). p-value of the Kruskal-Wallis tests for N. germarii body size as a function of sex. Asterisk highlights significant values.
Fig. 5 in Sex-ratio and body size plasticity in two cold-adapted ground beetles co-occurring in a periglacial area of the European Alps (Coleoptera: Carabidae)
Fig. 5 – PCA analysis graphs. Blue stars=active rock glacier specimens; Gold squares=fossil rock glacier specimens; Green dot=scree slope specimens.
Fig. 6 in Sex-ratio and body size plasticity in two cold-adapted ground beetles co-occurring in a periglacial area of the European Alps (Coleoptera: Carabidae)
Fig. 6 – Boxplot of head width of Nebria germarii females as a function of landform. p-value of N. germarii morphometric analysis with Kruskal-Wallis test, that evaluate the presence of significant differences in body size between landforms with ice (active rock glacier) and without ice (fossil rock glacier and scree slope). Asterisk highlights significant values.
Fig. 2 in Sex-ratio and body size plasticity in two cold-adapted ground beetles co-occurring in a periglacial area of the European Alps (Coleoptera: Carabidae)
Fig. 2 – Dorsal view of Nebria germarii and representation of the measured body parameters. For the meaning of the letters see the text (Photo by A. Carlin).
Fig. 4 in Sex-ratio and body size plasticity in two cold-adapted ground beetles co-occurring in a periglacial area of the European Alps (Coleoptera: Carabidae)
Fig. 4 – Boxplot of Nebria castanea body parameters as a function of sex (F=female; M=male). p-value of the Kruskal-Wallis tests for N. castanea body size as a function of sex. Asterisk highlights significant values.
Fig. 3 in European net-winged beetles of the Pyropterus clade, with the description of Gomezzuritus gen. nov. (Coleoptera: Lycidae)
Fig. 3. Gomezzuritus alternatus (Fairmaire, 1856), larva 3rd instar (LMBC), Asturias, 25 km SW of Oviedo, Caranga de Abajo. A. General appearance, lateral view. B. Head, pro- and mesothorax, ventral view. C. General appearance, lateral view after the treatment by KOH. D–F. Head, ventral, lateral, and dorsal view. G, H. Terminal abdominal segments, dorsal and ventral view. I, J. Head, thorax, and abdominal segment 1, dorsal, ventral view. K. Abdominal spiracle in segment 1. Scale bars: A–J = 0.5 mm.
Fig. 4 in European net-winged beetles of the Pyropterus clade, with the description of Gomezzuritus gen. nov. (Coleoptera: Lycidae)
Fig. 4. Gomezzuritus alternatus (Fairmaire, 1856). A, D. Adults in nature, Spain, Asturias, Las Agüeras, 35 km SW of Oviedo. B. Adults in nature, Spain, Las Agüeras. C, E. Larva 3rd instar in nature, Caranga de Abajo. F. Spain, Caranga de Abajo, habitat with common occurrence of G. alternatus (Fairmaire, 1856) comb. nov. Photographs: M. Motyke (A, D); L. Bocak (B–C, E–F).
Fig. 2 in European net-winged beetles of the Pyropterus clade, with the description of Gomezzuritus gen. nov. (Coleoptera: Lycidae)
Fig. 2. Gomezzuritus alternatus (Fairmaire, 1856) comb. nov., ♂, dissected (LMBC), from Asturias, Las Agüeras, 35 km SW of Oviedo. A. Head, frontal view. B. Head, ventral view. C. Metathoracic leg. D. Elytron. E. Meso- and metathorax, ventral view. F. Ditto, dorsal view. G. Pronotum. H. Hind wing. I–K. Male genitalia. Scale bars = 0.5 mm.
Fig. 1 in European net-winged beetles of the Pyropterus clade, with the description of Gomezzuritus gen. nov. (Coleoptera: Lycidae)
Fig. 1. Phylogenetic relationships of pyropterine genera and their closest relatives (modified from Motyka et al. in press). B–E. The general appearance of Western Palaearctic Dictyopterini Houlbert, 1922. B–C. Benibotarus alternatus (Fairmaire, 1856), ♂. D. B. longicornis (Reiche, 1878), ♂. E. B. rubripes (Pic, 1897), ♂. F. Distribution of Benibotarus Kôno, 1932 in the Western Palaearctic region. Nomenclature follows the placement of species before taxonomic changes discussed in the present study. The northern part of the range of B. taygetanus (Pic, 1905) is not shown (see Bocakova & Bocak 1987; Kazantsev 2012a).
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.