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2,516 results for “Seri”
Data from: What explains rare and conspicuous colours in a snail? A test of time-series data against models of drift, migration or selection
It is intriguing that conspicuous colour morphs of a prey species may be maintained at low frequencies alongside cryptic morphs. Negative frequency-dependent selection by predators using search images ('apostatic selection') is often suggested without rejecting alternative explanations. Using a maximum likelihood approach we fitted predictions from models of genetic drift, migration, constant selection, heterozygote advantage or negative frequency-dependent selection to time-series data of colour frequencies in isolated populations of a marine snail (Littorina saxatilis), re-established with perturbed colour morph frequencies and followed for >20 generations. Snails of conspicuous colours (white, red, banded) are naturally rare in the study area (usually <10%) but frequencies were manipulated to levels of ~50% (one colour per population) in 8 populations at the start of the experiment in 1992. In 2013, frequencies had declined to ~15–45%. Drift alone could not explain these changes. Migration could not be rejected in any population, but required rates much higher than those recorded. Directional selection was rejected in three populations in favour of balancing selection. Heterozygote advantage and negative frequency-dependent selection could not be distinguished statistically, although overall the results favoured the latter. Populations varied idiosyncratically as mild or variable colour selection (3–11%) interacted with demographic stochasticity, and the overall conclusion was that multiple mechanisms may contribute to maintaining the polymorphisms.
Forecasting hourly emergency department arrival using time series analysis
<p></p> Background/aims <p>The stochastic arrival of patients at hospital emergency departments complicates their management. More than 50% of a hospital's emergency department tends to operate beyond its normal capacity and eventually fails to deliver high-quality care. To address this concern, much research has been carried out using yearly, monthly and weekly time-series forecasting. This article discusses the use of hourly time-series forecasting to help improve emergency department management by predicting the arrival of future patients.</p> Methods <p>Emergency department admission data from January 2014 to August 2017 was retrieved from a hospital in Iowa. The auto-regressive integrated moving average (ARIMA), Holt–Winters, TBATS, and neural network methods were implemented and compared as forecasters of hourly patient arrivals.</p> Results <p>The auto-regressive integrated moving average (3,0,0) (2,1,0) was selected as the best fit model, with minimum Akaike information criterion and Schwartz Bayesian criterion. The model was stationary and qualified under the Box–Ljung correlation test and the Jarque–Bera test for normality. The mean error and root mean square error were selected as performance measures. A mean error of 1.001 and a root mean square error of 1.55 were obtained.</p> Conclusions <p>The auto-regressive integrated moving average can be used to provide hourly forecasts for emergency department arrivals and can be implemented as a decision support system to aid staff when scheduling and adjusting emergency department arrivals.</p> <p></p><p></p><p></p>
Data sets of MMP-cliffs, SAR transfer series and RECAP-MMPs
<p>A new and up-to-date version of three MMP-based data sets derived from compounds included in the latest release of ChEMBL is presented. These data sets include activity cliffs, structure-activity relationship (SAR) transfer series, and second generation MMPs based upon retrosynthetic rules. The structural data and information are provided in eight different files comprising the three data sets of MMP-cliffs (two files), SAR transfer series (four files), and RECAP-MMPs (two files). All MMP-cliffs, SAR transfer series with approximate or regular potency progression, and RECAP-MMPs are provided in canonical SMILES representation on a per-target basis separately for the Ki and IC50 subsets. The corresponding files are clearly designated.</p>
Data Sets of Matching Molecular Series
<p>A total of 30,452 and 45,607 target-based MMS are provided for the Ki- and IC50-based data sets from ChEMBL release 17. For each MMS in a target set, the corresponding compounds are given and ordered by increasing potency. The structures of MMS, value fragments and individual compounds are provided in canonical SMILES representation.</p>
FIGURE 7 in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 7. Double-claw photos from one Macrobiotus hystricogenitus specimen: (A) double-claws from the first pair of leg, typical Macrobiotus hystricogenitus claw morphology, and (B) double-claws from the second pair of legs with an additional spur (arrows). Scale bar = 10 μm.
FIGURE 5B in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 5B. Morphological variability found in Echiniscus merokensis. Percentages are provided for each morphotype. Arrows indicate missing appendages. (B) Echiniscus merokensis suecica.
FIGURE 6 in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 6. Morphological variability found in Echiniscus trisetosus. Percentages are provided for each morphotype. Arrows indicate missing appendages. *Morphotype found also in juvenile specimens.
FIGURE 5A in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 5A. Morphological variability found in Echiniscus merokensis. Percentages are provided for each morphotype. Arrows indicate missing appendages. (A) Echiniscus merokensis merokensis.
FIGURE 2 in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 2. Morphological variability found in Echiniscus blumi. Percentages are provided for each morphotype. Arrows indicate missing appendages.
FIGURE 3 in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 3. Morphological variability found in Echiniscus canadensis. Percentages are provided for each morphotype. Arrows indicate missing appendages. *Morphotype found also in juveniles. **Morphotype found only in juvenile specimens.
FIGURE 4 in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 4. Morphological variability found in Echiniscus mediantus. Percentages are provided for each morphotype. Arrows indicate missing appendages.
FIGURE 1 in New records and within-species variability of Iberian tardigrades (Tardigrada), with comments on the species from the Echiniscus blumi-canadensis series
FIGURE 1. (A) Map of the Iberian Peninsula indicating with a box the study area in Madrid Province. (B) Larger-scale map of the study area indicating sampling sites and altitude lines. The bold line constitutes the northern administrative border of the Comunidad de Madrid. Thin lines are equidistant altitude curves and grey areas are ecological reservoirs.
FIGURE 3 in Lerista karlschmidti (Marx and Hosmer, 1959) (Sauria: Scincidae): re-examination of the type series, reassignment of a paratype and distribution notes
FIGURE 3. Head drawings of the holotype of Rhodona karlschmidti, FMNH 97957. (A) Lateral view, (B) dorsal view, (C) ventral view.
FIGURE 1 in Lerista karlschmidti (Marx and Hosmer, 1959) (Sauria: Scincidae): re-examination of the type series, reassignment of a paratype and distribution notes
FIGURE 1. Map showing the disjunct distribution of L. karlschmidti. * = Queensland L. karlschmidti records and marks the location of the town of Woodstock, = Northern Territory L. karlschmidti records (based on Horner, 1992), ˔ = towns.
FIGURE 8. A–D in Bees of the Lasioglossum series (Hymenoptera: Halictidae) in South Korea, with an illustrated keys to species
FIGURE 8. A–D: hair tufts on S6. A: Lasioglossum nipponicola Sakagami & Tadauchi. B: L. occidens (Smith). C: Lasioglossum subopacum (Smith). D: L. upinense (Morawitz). A–D: ♂.
FIGURE 5. A, B in Bees of the Lasioglossum series (Hymenoptera: Halictidae) in South Korea, with an illustrated keys to species
FIGURE 5. A, B: basal area of T1. C, D: mesoscutum. A: Lasioglossum nipponicola Sakagami & Tadauchi. B: L. kansuense (Blüthgen). C: L. denticolle (Morawitz). D: L. occidens (Smith). A–D: ♀.
FIGURE 7. A–D in Bees of the Lasioglossum series (Hymenoptera: Halictidae) in South Korea, with an illustrated keys to species
FIGURE 7. A–D: hair tufts on S6. A: Lasioglossum circularum Fan & Ebmer. B: L. denticolle (Morawitz). C: L. formosae (Strand). D: L. kansuense (Blüthgen). A–D: ♂.
FIGURE 4. A, B, E, F in Bees of the Lasioglossum series (Hymenoptera: Halictidae) in South Korea, with an illustrated keys to species
FIGURE 4. A, B, E, F: T1. C, D: posterior surface of propodeum. A: Lasioglossum primavera Sakagami & Maeta. B: L. sutshanicum Pesenko. C, F: L. kansuense (Blüthgen). D: L. occidens (Smith). E: L. upinense (Morawitz). A–F: ♀.
FIGURE 3. A, B in Bees of the Lasioglossum series (Hymenoptera: Halictidae) in South Korea, with an illustrated keys to species
FIGURE 3. A, B: metapostnotum of propodeum. C, D: propodeum. E, F: supraclypeus. A: Lasioglossum exiliceps (Vachal). B, E: L. primavera Sakagami & Maeta. C: L. proximatum (Smith). D, F: L. sutshanicum Pesenko. A–F: ♀.
FIGURE 6. A, B in Bees of the Lasioglossum series (Hymenoptera: Halictidae) in South Korea, with an illustrated keys to species
FIGURE 6. A, B: propodeum. C, D: submedial patch of T1 encircled. A, C: Lasioglossum occidens (Smith). B, D: L. formosae (Strand). A, B: ♀. C, D: ♂.
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.