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4,182 results for “universities”
FIGURES 30–35. 30. Colobothea meleagrina Erichson, 1847 in An annotated and illustrated catalog of the Peruvian specimens of Cerambycidae (Coleoptera) housed in the Biological Museum at Lund University, Sweden
FIGURES 30–35. 30. Colobothea meleagrina Erichson, 1847: 30a) dorsal habitus; b) labels. 31. Colobothea plebeja Aurivillius, 1902: 31a) dorsal habitus; b) labels. 32. Taeniotes affinis Breuning, 1935: 32a) dorsal habitus; b) labels. 33. Taeniotes naevius Bates, 1872: 33a) dorsal habitus; b) labels. 34. Taeniotes orbignyi Guérin-Méneville, 1844: 34a) dorsal habitus; b) labels. 35. Jamesia globifera (Fabricius, 1801): 35a) dorsal habitus; b) labels. Scales = 5 mm, Figure 30; Scales = 10 mm, Figures 31–35.
FIGURES 1–6. 1 in An annotated and illustrated catalog of the Peruvian specimens of Cerambycidae (Coleoptera) housed in the Biological Museum at Lund University, Sweden
FIGURES 1–6. 1. Achryson surinamum (Linnaeus, 1767): 1a) dorsal habitus; b) labels. 2. Chlorida festiva (Linnaeus, 1758): 2a) dorsal habitus; b) labels. 3. Callichroma auricomum (Linnaeus, 1767): 3a) dorsal habitus; b) labels. 4. Callichroma iris trilineatum Bates, 1879: 4a) dorsal habitus; b) labels. 5. Mionochroma sp: 5a) dorsal habitus; b) labels. 6. Chrysoprasis hypocrita Erichson, 1847: 6a) dorsal habitus; b) labels. Scales = 5 mm, Figures 2, 6; Scales = 10 mm, Figures 1, 3, 4–5.
Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics
<p>This dataset provides python implementation of the paper: Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics, which is available on arXiv https://arxiv.org/abs/2308.13835.</p>
Evaluating the Impact of Education on Sustainability Knowledge, Attitudes, and Intentions Among University Students
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Thermal evolution of dark matter in the early universe from a symplectic glueball model---Data release
<p>This is the data release to reproduce the plots shown in "Thermal evolution of dark matter in the early universe from a symplectic glueball model".</p>
Teachers' perception of their assessment skills and its relationship with their assessment practices in public universities of Ethiopia
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AI at University: raising the attention
<h1>Youtube video "<a href="https://www.youtube.com/watch?v=jLCf3naieFI">Impatto dell’AI su insegnare ed imparare</a>"</h1> <p>Trying to aknowlege the impatc of the so called "Generative Artificial Intelligence" tools on many human activities, particularly on the work environment of graduated students, a short meeting was orgnized pooling some students and professors in Nuoro forestry degree courses on the 15th of October 2024.<br>The video is produced aligning the audio recording with the slide presentation avaliable also as pdf.<br>Video URL: https://www.youtube.com/watch?v=jLCf3naieFI</p>
Measurement-free, scalable and fault-tolerant universal quantum computing
<p>The repository is supporting the publication "Measurement-free, scalable and fault-tolerant universal quantum computing". </p> <p>It includes the data shown in the manuscript as well as the simulation code and circuits that were used to obtain this data. </p>
Data from: Between geometry and biology: the problem of universality of the species-area relationship
The species-area relationship (SAR) is considered to be one of a few generalities in ecology, yet a universal model of its shape and slope has remained elusive. Recently Harte et al. (2009) argued that the slope of the SAR for a given area is driven by a single parameter, the ratio between total number of individuals and number of species (i.e. the mean population size across species at a given scale). We provide a geometric interpretation of this dependence. At the same time, however, we show that this dependence cannot be universal across taxa: if it holds for a taxon composed from two subsets of species and also for one of its subsets, it cannot simultaneously hold for the other subset. Using three datasets, we show that the slope of the SAR considerably varies around the prediction. We estimate the limits of this variation using geometric considerations, providing a theory based on species spatial turnover at different scales. We argue that the SAR cannot be strictly universal, but its slope at each particular scale varies within the constraints given by species' spatial turnover at finer spatial scales, and this variation is biologically informative.
FIGURE 52 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 52. Salmo fahrettini, from top: holotype, FFR 3231, 232 mm SL; paratype, FFR 3233, 194 mm SL.
FIGURE 45 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 45. Seminemacheilus attalicus, from top: holotype, FFR 15566, 69.5 mm SL; paratype, FFR 15555, 86 mm SL.
FIGURE 43 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 43. Oxynoemacheilus sarus, from top: holotype, FFR 15584, 52.5 mm SL; paratype, FFR 15522, 53 mm SL.
FIGURE 42 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 42. Oxynoemacheilus nasreddini, from top: holotype, FFR 15588, 54 mm SL; paratype, FFR 15589, 53 mm SL.
FIGURE 41 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 41. Oxynoemacheilus muefiti, from top: holotype, FFR 15532, 70 mm SL; paratype, FFR 15522, 56 mm SL.
FIGURE 37 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 37. Oxynoemacheilus arsaniasus, from top: holotype, FFR 15530, 57 mm SL; paratype, FFR 15531, 54 mm SL.
FIGURE 39 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 39. Oxynoemacheilus cilicicus, from top: holotype, FFR 15579, 54 mm SL; paratype, FFR 15560, 53 mm SL.
FIGURE 50 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 50. Salmo coruhensis, from top: holotype, FFR 3036, 291 mm SL; paratype, FFR 3037, 270 mm SL.
FIGURE 21 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 21. Alburnoides kosswigi, from top: holotype, FFR 1064, 80 mm SL; paratype, FFR 1107, 76 mm SL.
FIGURE 20 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 20. Alburnoides freyhofi, from top: holotype, FFR 1065, 85 mm SL; paratype, FFR 7004, 76 mm SL.
FIGURE 19 in Illustrated type specimens catalogue of Recep Tayyip Erdogan University Zoology Museum of the Faculty of Fisheries
FIGURE 19. Alburnoides emineae, from top: holotype, FFR 1026, male, 69 mm SL; paratype, FFR 1073, 68 mm SL.
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.