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34 results for “feature scaling”
Data from: A national-scale model of linear features improves predictions of farmland biodiversity
1. Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically-relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies. 2. We assessed whether a novel spatial dataset mapping linear and woody linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites respectively. 3. Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. 4. Synthesis and applications. This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems, and also can potentially be used to assess habitat connectivity. 10-Mar-2017
Data from: Quantifying pursuit-diving seabirds' associations with fine-scale physical features in tidal stream environments
The rapid increase in the number of tidal stream turbine arrays will create novel and unprecedented levels of anthropogenic activity within habitats characterized by horizontal current speeds exceeding 2 ms−1. However, the potential impacts on pursuit-diving seabirds exploiting these tidal stream environments remain largely unknown. Identifying similarities between the fine-scale physical features (100s of metres) suitable for array installations, and those associated with foraging pursuit-diving seabirds, could identify which species are most vulnerable to either collisions with moving components, or displacement from these installations. A combination of vessel-based observational surveys, Finite Volume Community Ocean Model outputs and hydroacoustic seabed surveys provided concurrent measures of foraging distributions and physical characteristics at a fine temporal (15 min) and spatial (500 m) resolution across a tidal stream environment suitable for array installations, during both breeding and non-breeding seasons. These data sets were then used to test for associations between foraging pursuit-diving seabirds (Atlantic puffins Fratercula arctica, black guillemots Cepphus grylle, common guillemots Uria aalge, European shags Phalacrocorax aristotelis) and physical features. These species were associated with areas of fast horizontal currents, slow horizontal currents, high turbulence, downward vertical currents and also hard–rough seabeds. The identity and strength of associations differed among species, and also within species between seasons, indicative of interspecific and intraspecific variations in habitat use. However, Atlantic puffins were associated particularly strongly with areas of fast horizontal currents during breeding seasons, and European shags with areas of rough–hard seabeds and downward vertical currents during non-breeding seasons. Synthesis and applications. Atlantic puffins' strong association with fast horizontal current speeds indicates that they are particularly likely to interact with installations during breeding seasons. Any post-installation monitoring and mitigation measures should therefore focus on this species and season. The multi-species associations with high turbulence and downward vertical currents, which often coincide with fast horizontal current speeds, also highlight useful pre-installation mitigation measures via the omission of devices from these areas, reducing the overall likelihood of interactions. Environmental impact assessments (EIA) generally involve once-a-month surveys across 2-year periods. However, the approaches used in this study show that more focussed surveys can greatly benefit management strategies aiming to reduce the likelihood of negative impacts by facilitating the development of targeted mitigation measures. It is therefore recommended that these approaches contribute towards EIA within development sites.
Data from: Quantifying pursuit-diving seabirds' associations with fine-scale physical features in tidal stream environments
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Data from: A national-scale model of linear features improves predictions of farmland biodiversity
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Spatial-Mux-seq: Multiplexed spatial mapping of chromatin features, transcriptome, and proteins at tissue scale
GEO Series GSE263333. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing; Other; Genome binding/occupancy profiling by high throughput sequencing.
Genome-scale transcription–translation mapping reveals novel features of Zymomonas mobilis promoters and transcription units
GEO Series GSE139939. Zymomonas mobilis subsp. mobilis ZM4 = ATCC 31821. 94 samples. Type: Expression profiling by high throughput sequencing; Other.
Genome-scale Analysis of E. coli FNR Reveals Complex Features of Transcription Factor Binding
GEO Series GSE41195. Escherichia coli str. K-12 substr. MG1655; Escherichia coli str. K-12 substr. MG1655star; Escherichia coli K-12. 48 samples. Type: Genome binding/occupancy profiling by genome tiling array; Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by array; Expression profiling by high throughput sequencing; Expression profiling by genome tiling array.
Data from: Variation in three community features across habitat types and scales within a 15-ha subtropical evergreen-deciduous broadleaved mixed forest dynamics plot in China
The evergreen and deciduous broadleaved mixed forests (EDBMFs) belong to one of the ecosystems most sensitive to environmental change, however, little is known about the environmental determinants for their plant diversity and forest structure at different habitat types and spatial scales. Here, we used data from a 15-ha (300×500 m) forest dynamic plot (FDP) of an old-growth EDBMF to examine the patterns and determinants of the three community features (stem abundance, rarefied species richness and basal area) in three habitat types (ridge, hillside and foothill) and at three spatial scales (20×20 m, 50×50 m and 100×100 m). We found that the three community features significantly changed with habitat type, but only one of them (rarefied richness) changed with scale. Among spatial scales, the principle environmental factors that widely affected community features were pH, SOM and TP, while these effects only taken place at certain habitat. Variations in the three community features explained by soil conditions were generally greater than those explained by topographical conditions. With changes in habitat type, the proportion of variations explained by environmental conditions was 31-53%, 8-25%, and 18-26% for abundance, rarefied richness and basal area (BA), respectively. With increasing spatial scale, the variations explained by environmental conditions were 44-75% for abundance, 28-95% for rarefied richness, and 18-86% for BA. Our study demonstrated that environmental factors had great impacts on the plant diversity and forest structure in the EDBMFs, especially the soil factors such as pH. In addition, the importance of the environmental determinants on these community features was highly related to the spatial scale.
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models
<p>Data and checkpoints for 'Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models'</p>
Artificial Intelligence-enabled Large-scale Electrocardiogram Feature Extraction and Exploring Association Between the Extracted Features and Mortality, Stroke or Various Health Outcome of Interest
ClinicalTrials.gov study NCT06179849. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Variation in three community features across habitat types and scales within a 15-ha subtropical evergreen-deciduous broadleaved mixed forest dynamics plot in China
Open the record for dataset details and reuse information.
Genome-scale analysis of metazoan replication origins reveals their organization in specific but flexible sites defined by conserved features.
GEO Series GSE29183. Mus musculus; Drosophila melanogaster. 5 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Detection of Pol IV-dependent transcripts at the genomic scale in Arabidopsis reveals features and regulation of siRNA biogenesis
GEO Series GSE57215. Arabidopsis thaliana. 36 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
FIGURE. Phenological features of Ephedra aurea. A. San Vito lo Capo (locus classicus), natural habitat. B. Habit in natural places. C–D. Detail of ripe female cones. E. Twigs with male cones. F. Twigs with female cones. G. Internodes with scale-leaf. (Photos A, C, D, G by V. Ilardi, B, E, F by S. Cambria). in Ephedra aurea (Ephedraceae), a new species from Sicily
FIGURE. Phenological features of Ephedra aurea. A. San Vito lo Capo (locus classicus), natural habitat. B. Habit in natural places. C–D. Detail of ripe female cones. E. Twigs with male cones. F. Twigs with female cones. G. Internodes with scale-leaf. (Photos A, C, D, G by V. Ilardi, B, E, F by S. Cambria).
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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.