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2,395 results for “Contrast”
"Contrast based circular approximation for accurate and robust optic disc segmentation in retinal images" - Code
<p>A new method for automatic optic disc localization and segmentation is presented. The localization procedure combines vascular and brightness information to provide the best estimate of the optic disc center which is the starting point for the segmentation algorithm. A detection rate of 99.58% and 100% was achieved for the Messidor and ONHSD databases, respectively. A simple circular approximation to the optic disc boundary is proposed based on the maximum average contrast between the inner and outer ring of a circle centered on the estimated location. An average overlap coefficient of 0.890 and 0.865 was achieved for the same datasets, outperforming other state of the art methods. The results obtained confirm the advantages of using a simple circular model under non ideal conditions as opposed to more complex deformable models.</p>
Large-scale semantic indexing of Spanish biomedical literature using contrastive transfer learning
Open the record for dataset details and reuse information.
Global monthly climatologies of thermal contrast
<p>Thermal contrast (TC) is a key parameter for the sensitivity of (nadir-viewing) infrared sounders. This global dataset includes a 18/01/2021 to 18/01/2022 climatology of TC with respect to three different altitudes (the standard meteorological height of 2 meters, half the height of the boundary layer (HBL), and the height corresponding to the maximum temperature of the lower troposphere (within a maximum of 3 km)): <br>- A gridded dataset as a function of latitude (641 bins), longitude (1280 bins), month (monthly) and local mean solar time (hourly)<br>- A gridded dataset as a function of land cover type (7 classes), latitudinal zone (3 zones), month (monthly) and local mean solar time (hourly)</p><p>This dataset is based on land surface temperature from the Copernicus Global Land Services dataset with air temperatures from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis. A detailed description can be found in T. Di Gioacchino et al. (submitted).</p>
FIG. 2 in Contrasting marine larval settlement patterns imply habitat-seeking behaviours in a fouling and a cryptic species (phylum Bryozoa)
FIG. 2. Inferred laboratory behaviours and stylized ®eld distributions of (A) Schizoporella errata and (B) Plagioecia patina. Schizoporella errata colonies are indicated by striped areas and are shown attached to undersides of a boat and to shallow parts of a vertical man-made structure such as a piling or wall. Plagioecia patina colonies are indicated by cross-hatched areas and are shown attached to deep objects, including the underside of a shell resting on its concave surface. Larval swimming paths in the laboratory experiment are indicated by sequentially numbered arrows, the widths of which are roughly proportioned to the proportion of larvae following the path. Black rectangles represent dark conditions. Inferred stimuli are indicated by letters: p+, photopositive; p±, photonegative; g +, geopositive; g±, geonegative; go, possible neutral or counterbalancing responses that result in, on average, sustained horizontal swimming.
FIG. 1 in Contrasting marine larval settlement patterns imply habitat-seeking behaviours in a fouling and a cryptic species (phylum Bryozoa)
FIG. 1. Pattern of the panel that forms the back of the array of contiguous settlement chambers in the experiment. Cross-sectional pro®les of the 24 3-cm highÖ3-cm wideÖ15.5-cm long chambers are seen. Chambers on the left were dark and those on the right were lighted. Within each of the three levels (high, middle, low), each chamber in the lighted side had a unique ¯ow velocity through it determined by the size of the downstream opening (symbolized by the size of the circle within each square). Four elongate bounding surfaces de®ned each elongate chamber: a downward-facing ceiling, two lateral walls and an upward-facing ¯oor. Distance within the chambers is not portrayed in the ®gure, but each of the four elongate walls of chambers was examined and scored as three equal segments: the portion closest to the entrance (upstream end), the middle portion and the portion closest to the back panel (downstream end).
Fig. 7 in Morphology-based phylogenetic analysis of South American Sericini chafers (Coleoptera, Scarabaeidae) contrasts patterns of morphological disparity and current classification
Fig. 7. Patterns of disparity derived from discrete morphological data: plots of axis 1 and 2 from principal coordinate analysis.
Fig. 6 in Morphology-based phylogenetic analysis of South American Sericini chafers (Coleoptera, Scarabaeidae) contrasts patterns of morphological disparity and current classification
Fig. 6. Single most parsimonious tree from implied weighting (K = 71.62) on the reduced data set (run 9), part 2. Support values (bootstrap/symmetric resampling) below 50 not shown.
Fig. 5 in Morphology-based phylogenetic analysis of South American Sericini chafers (Coleoptera, Scarabaeidae) contrasts patterns of morphological disparity and current classification
Fig. 5. Single most parsimonious tree from implied weighting (K = 71.62) on the reduced data set (run 9), part 1. Support values (bootstrap/symmetric resampling) below 50 not shown.
Fig. 4 in Morphology-based phylogenetic analysis of South American Sericini chafers (Coleoptera, Scarabaeidae) contrasts patterns of morphological disparity and current classification
Fig. 4. Characters illustrated: male genitalia. A-H) Aedeagus, dorsal view. A) Symmela beskei; B) S. varians; C) Astaena exquisita; D) A. leechi; E) A. longicornis; F) A. schnebli; G) A. sparsetosa; H) S. capixaba. Scale bars: A H) 0.5 mm.
Fig. 2 in Morphology-based phylogenetic analysis of South American Sericini chafers (Coleoptera, Scarabaeidae) contrasts patterns of morphological disparity and current classification
Fig. 2. Characters illustrated: pronotum and elytra. A-I) Pronotum, dorsal view; J-L) Elytra, dorsal view; M O) Elytra, lateral view. A) Astaena baroni; B) A. explaniceps; C, M) A. fuscipennis; D) A. peruana; E) A. producta; F) A. pygidiallis; G) A. ruficollis; H) A. suturalis; I) Symmela flavimana; J) A. longula; K) A. pilosa; L) A. pinguins; N) A. marginicollis; O) A. tarsalis. Scale bars: A-O) 1 mm.
Fig. 3 in Morphology-based phylogenetic analysis of South American Sericini chafers (Coleoptera, Scarabaeidae) contrasts patterns of morphological disparity and current classification
Fig. 3. Characters illustrated: Abdomen and legs. A) Abdomen, lateral view; B, C) Abdomen, ventral view; D F) Prolegs, dorsal view; G, H) Protarsi, lateral view; I,J) Metacoxa, lateral view; K,L) Metatibia, lateral face; M) Metatibia, interior face; N) Metatibia, dorsal view; O,P) Metatarsi, dorsal view; Q) Metatarsi, ventral view. A) Astaena fuscipennis; B) A. tarsalis; C) Symmela opaca; D) A. montivaga; E) S. jatahyensis; F) S. mutabilis; G) Raysymmela boliviensis; H) Parasymmela amazonica; I, L, O) A. aequatorialis; J) A. rosettae; K) Astaena heterophylla; M) A. andina; N) A. semiopaca; P) A. longicornis; Q) A. boliviana. Scale bars: A-F, I-Q) 1 mm; G, H) 0.3 mm.
Fig. 8. A in Morphology-based phylogenetic analysis of South American Sericini chafers (Coleoptera, Scarabaeidae) contrasts patterns of morphological disparity and current classification
Fig. 8. A - Unrooted single most parsimonious tree from implied weighting (K = 71.62) on the reduced data set (run 9); B - Unrooted single tree from distancebased clustering.
spatiAlign: An Unsupervised Contrastive Learning Model for Data Integration of Spatially Resolved Transcriptomics
<p>Integrative analysis of spatially resolved transcriptomics datasets empowers a deeper understanding of complex biological systems. However, integrating multiple tissue sections presents challenges for batch effect removal, particularly when the sections are measured by various technologies or collected at different times. Here, we propose spatiAlign, an unsupervised contrastive learning model that employs the expression of all measured genes and the spatial location of cells, to integrate multiple tissue sections. It enables the joint downstream analysis of multiple datasets not only in low-dimensional embeddings but also in the reconstructed full expression space. In benchmarking analysis, spatiAlign outperforms state-of-the-art methods in learning joint and discriminative representations for tissue sections, each potentially characterized by complex batch effects or distinct biological characteristics. Furthermore, we demonstrate the benefits of spatiAlign for the integrative analysis of time-series brain sections, including spatial clustering, differential expression analysis, and particularly trajectory inference that requires a corrected gene expression matrix.</p>
Demographic mechanisms and anthropogenic drivers of contrasting population dynamics of hummingbirds
<p>Conserving species requires knowledge of demographic rates (survival, recruitment) that govern population dynamics to allow the allocation of limited resources to the most vulnerable stages of target species' life cycles. Additionally, quantifying drivers of demographic change facilitates the enactment of specific remediation strategies. However, knowledge gaps persist in how similar environmental changes lead to contrasting population dynamics through demographic rates. For sympatric hummingbird species, the population of urban-associated partial-migrant Anna's hummigbird (<em>Calypte anna</em>) has increased, yet the populations of Neotropical migrants including rufous, calliope, and black-chinned hummingbirds have decreased. Here, we developed an integrated population model to jointly analyze 25 years of mark-recapture data and population survey data for these four species. We examined the contributions of demographic rates on population growth and evaluated the effects of anthropogenic stressors including human population density and crop cover on demographic change in relation to species' life histories. While recruitment appeared to drive the population increase of urban-associated Anna's hummingbirds, decreases in juvenile survival contributed most strongly to population declines of Neotropical migrants and highlight a potentially vulnerable phase in their life-history. Moreover, rufous hummingbird adult and juvenile survival rates were negatively impacted by human population density. Mitigating threats associated with intensively modified anthropogenic environments is a promising avenue for slowing further hummingbird population loss. Overall, our model grants critical insight into how anthropogenic modification of habitat affects the population dynamics of species of conservation concern.</p>
Figure 1 in Seed predation of Araucaria angustifolia (Araucariaceae) by small rodents in two areas with contrasting seed densities in the Brazilian Araucaria forest
Figure 1. Survivorship curves for mean number of seeds placed at two areas (27 experimental stations per area) and monitored for 30 days in two periods. These periods corresponded to the time of Araucaria angustifolia seed production (indicated by filled symbols and solid lines) and outside this period (open symbols and broken lines). The area with high density of seeds during time of seed production (planted stand of A. angustifolia) is indicated by circles and the area with low density of seeds throughout the year (planted stand of P. elliottii) is indicated by triangles. Error bars indicate standard errors of the means. Significant differences (p <0.05, log-rank survival tests with sequential Bonferroni correction) are shown by different letters. Statistical comparisons were made only between areas for each season and between seasons for each area.
Contrasting responses of forest phenological guilds to complex floodplain change
<p>Understanding the seasonal dynamics of the forest herb layer and the factors that influence it is essential for predicting how the forest ecosystem, including mutualistic interactions, will respond to global change. However, to date, no research has investigated how understorey phenological guilds respond to major environmental threats and forest interventions. We showed the marked changes in the phenological structure of floodplain forest plant communities over half a century at a multi-regional scale in Central Europe. Unlike previous studies focusing on individual species' responses to climate change, we examined shifts in species richness, frequency, and abundance between phenological guilds within the plant community. We examined the effects of temporal variation in climate, hydrology, soil conditions, and canopy structure, and assessed the effects of no-intervention and intervention management on phenological guild responses. Our results show a significant loss of local species richness and a decline in species frequency in the forest understorey vegetation, associated with species exhibiting summer phenology. In contrast, an increase in abundance and richness of spring flowering species was observed, attributed to high nutrient loads and reduced flooding, respectively. The abundance of spring species increased only in stands where canopy cover increased over time, probably due to the suppression of summer flowering species, allowing spring flowering species to spread on open bare ground. The community experienced a shift in maximum flowering plant richness from June to May. Despite management interventions such as clear-cutting and tree planting, our data show similar temporal trajectories in intervention and non-intervention forests, indicating that changes in phenological structure are largely independent of recent management activities.</p> <p><em>Synthesis.</em> We propose that a complex interplay of environmental factors, rather than climate change alone, is shaping shifts towards earlier phenological guilds in floodplain forests. This study highlights the importance of considering a comprehensive view of phenological guild dynamics and the impact of environmental factors on forest plant community structure in the face of global change.</p>
Change-Aware Sampling and Contrastive Learning for Satellite Images
<p><strong>Instructions</strong></p> <div>Change-Aware Sampling and Contrastive Learning for Satellite Images</div> <div>The 1 million sized dataset in compressed format.</div> <div>This dataset is split in 4 parts due to Zenodo's size restictions.</div> <div>Each part can be downloaded using the following link.</div> <p><strong>Part 1: </strong><a href="../records/10913216">https://zenodo.org/records/10913216</a></p> <p><strong>Part 2: </strong><a href="../records/10914902">https://zenodo.org/records/10914902</a></p> <p><strong>Part 3: </strong><a href="10915715">https://zenodo.org/uploads/10915715</a></p> <p><strong>Part 4: </strong><a href="../records/10916979">https://zenodo.org/records/10916979</a></p> <p> </p> <div>Use the following commands to combine and extract the compressed file.</div> <blockquote> <div>cat clean_1m_geography_part* > clean_1m_geography.tar.gz</div> <div>tar -xvf clean_1m_geography.tar.gz</div> </blockquote> <p> </p> <p><strong>Paper Abstract</strong></p> <p>Automatic remote sensing tools can help inform many large-scale challenges such as disaster management, climate change, etc. While a vast amount of spatio-temporal satellite image data is readily available, most of it remains unlabelled. Without labels, this data is not very useful for supervised learning algorithms. Self-supervised learning instead provides a way to learn effective representations for various downstream tasks without labels. In this work, we leverage characteristics unique to satellite images to learn better self-supervised features. Specifically, we use the temporal signal to contrast images with long-term and short-term differences, and we leverage the fact that satellite images do not change frequently. Using these characteristics, we formulate a new loss contrastive loss called Change-Aware Contrastive (CACo) Loss. Further, we also present a novel method of sampling different geographical regions. We show that leveraging these properties leads to better performance on diverse downstream tasks. For example, we see a 6.5% relative improvement for semantic segmentation and an 8.5% relative improvement for change detection over the best-performing baseline with our method.<br><br><br></p> <div> <div> </div> </div>
FIGURE 3 in Contrasting feeding and agonistic behaviour of two blenny species on a small and remote island in the equatorial Atlantic Ocean
FIGURE 3 Diet composition of (a) Entomacrodus vomerinus and (b) Ophioblennius trinitatis in the St Peter and St Paul's Archipelago: (o) Individual observation; (), mean ± 95% CI. (c) Nonmetric multidimensional scaling based on gut content of E. vomerinus () and O. trinitatis (). O, Individual observation; convex hulls were drawn to emphasise the difference between the two species
FIGURE 2 in Contrasting feeding and agonistic behaviour of two blenny species on a small and remote island in the equatorial Atlantic Ocean
FIGURE 2 Comparison of (a) feeding rate and (b) agonistic behaviour of Entomacrodus vomerinus and Ophioblennius trinitatis in the St Peter and St Paul's Archipelago. O, Individual observation; (), mean ± 95% CI
FIGURE 4 in Contrasting feeding and agonistic behaviour of two blenny species on a small and remote island in the equatorial Atlantic Ocean
FIGURE 4 Comparison (mean ± 95% CI) of: (a), (c), (e) feeding rate and (b), (d), (f) agonistic behaviour (a), (b) in the morning (O) and afternoon () and the corresponding effect of (c), (d) total length (LT) and (e), (f) group size of Entomacrodus vomerinus () and Ophioblennius trinitatis ()in tide pools of the St Peter and St Paul's Archipelago
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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.