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13,864 results for “staging”
Figure 10 in First zoeal stages of grapsoid crabs (Crustacea: Brachyura) from the East African coast
Figure 10. Pachygrapsus minutus Crosnier. First zoeal stage: (f) maxillule; (g) maxilla; (h) first maxilliped; (i) second maxilliped. Scale bars as in Figure 2.
Figure 2 in First zoeal stages of grapsoid crabs (Crustacea: Brachyura) from the East African coast
Figure 2. Grapsus fourmanoiri Crosnier. First zoeal stage: (f) maxillule; (g) maxilla; (h) first maxilliped; (i) second maxilliped. Scale bars represent 0.05 mm.
Figure 18 in First zoeal stages of grapsoid crabs (Crustacea: Brachyura) from the East African coast
Figure 18. Cardisoma carnifex (Herbst). First zoeal stage: (f) maxillule; (g) maxilla; (h) first maxilliped; (i) second maxilliped. Scale bars as in Figure 2.
Figure 15 in First zoeal stages of grapsoid crabs (Crustacea: Brachyura) from the East African coast
Figure 15. Sesarma leptosoma Hilgendorf. First zoeal stage: (a) lateral view; (b) antennule; (c) antenna; (d) dorsal view of abdomen; (e) detail of telson. Scale bars as in Figure 1.
Figure 14 in First zoeal stages of grapsoid crabs (Crustacea: Brachyura) from the East African coast
Figure 14. Sarmatium crassum Dana. First zoeal stage: (f) maxillule; (g) maxilla; (h) first maxilliped; (i) second maxilliped. Scale bars as in Figure 2.
Figure 7 in Phylogeny and classification of Aedini (Diptera: Culicidae), based on morphological characters of all life stages
Figure 7. Strict consensus of the 97 MPCs obtained under equal weights and the eight MPCs obtained under implied weights based on analysis of the combined data. The monophyletic groups that survive this process are those that are weighting independent.
Figure 6 in Phylogeny and classification of Aedini (Diptera: Culicidae), based on morphological characters of all life stages
Figure 6. One of the eight MPCs obtained from analysis of the total data under implied weights. This cladogram includes the alternate topologies from each of three sets of two conflicting topologies. See Figure 5 for the other three sets of conflicting topologies and text for details.
Figure 5 in Phylogeny and classification of Aedini (Diptera: Culicidae), based on morphological characters of all life stages
Figure 5. One of the eight MPCs obtained from analysis of the total data under implied weights. This cladogram includes one of each of the three sets of two conflicting topologies. The other three sets of conflicting topologies obtained in the analysis are shown in Figure 6. See text for details.
Figure 4 in Phylogeny and classification of Aedini (Diptera: Culicidae), based on morphological characters of all life stages
Figure 4. Strict consensus of eight MPCs (Fit = 596.4) obtained from the analysis of combined adult and immature stages data under implied weights. Bremer support and relative Bremer support values of each clade are indicated above and below the branches, respectively. The clade comprising Ve. indica and Ve. pseudomediofaciata has zero Bremer support and should have been shown as collapsed.
Figure 1 in Phylogeny and classification of Aedini (Diptera: Culicidae), based on morphological characters of all life stages
Figure 1. Strict consensus of 4537 MPCs of 871 steps (CI = 0.14, RI = 0.69) obtained from analysis of adult data under equal weights. Groups in polytomies in this and subsequent consensus trees (Figs 2, 3, 4, 7) are arranged in order of increasing size, such that single taxa are listed at the top of the tree and the largest groups at the bottom. No significance should be read into this aspect of the sequence.
Fig. 2 in First record of the Vietnam Flying Frog, Rhacophorus calcaneus Smith, 1924, from Khanh Hoa Province, including the first molecular identification and morphological description of larval stages
Fig. 2. Drawings of the preserved tadpole (VNMN 6318) of Rhacophorus calcaneus from Hon Ba Nature Reserve in Gosner Stage 32: lateral view (A), dorsal view (B) (scale bar = 1 cm); oral apparatus (C) (scale bar = 0.5 mm).
Fig. 3 in First record of the Vietnam Flying Frog, Rhacophorus calcaneus Smith, 1924, from Khanh Hoa Province, including the first molecular identification and morphological description of larval stages
Fig. 3. Drawings of the preserved tadpoles of Rhacophorus calcaneus from Hon Ba Nature Reserve in advanced Gosner stages. (A) Stage 36. (B) Stage 37. (C) Stage 41 and (D) Stage 42 (scale bar = 1 cm).
Fig. 1 in First record of the Vietnam Flying Frog, Rhacophorus calcaneus Smith, 1924, from Khanh Hoa Province, including the first molecular identification and morphological description of larval stages
Fig. 1. Maximum-likelihood (ML) and Bayesian inference (BI) tree based on the partial 16S rRNA mitochondrial gene. Numbers above and under branches are ML bootstrap values and Bayesian posterior probabilities.
Can predators stabilize host-parasite interactions? Changes in aquatic predator identity alters amphibian responses and parasite abundance across life stages
<p><span><span>The role of parasites can change depending on the food web community. Predators, for instance, can amplify or dilute parasite </span><span>effects on their hosts. Likewise, exposure to parasites or predators at one life stage can have long-term consequences on individual performance and survival, which can influence population and disease dynamics. To understand how predators affect amphibian parasite infections across life stages, we manipulated exposure of northern leopard frog (<em>Rana pipiens</em>) tadpoles to three predators (crayfish [<em>Orconectes rusticus</em>], bluegill [<em>Lepomis macrochirus</em>], or mosquitofish [<em>Gambusia affinis</em>]) and to trematode parasites (<em>Echinostoma</em> spp.) in mesocosms and followed juveniles in outdoor terrestrial enclosures through overwintering. Parasites and predators both had strong impacts on metamorphosis with bluegill and parasites individually reducing metamorph survival. However, when fish were present, the negative effects of parasites on survival were not apparent, likely because fish altered community composition via increased algal food resources. Bluegill also reduced snail abundance, which could explain the reduced abundance of parasites in surviving metamorphs. Bluegill and parasite exposure increased mass at metamorphosis, which increased metamorph jumping, swimming, and feeding performance, suggesting larger frogs would experience better terrestrial survival. Effects on size at metamorphosis persisted in the terrestrial environment but did not influence overwintering survival. Based on our results, we constructed stage-structured population models to evaluate the lethal and sublethal effects of bluegill and parasites on population dynamics. Our models suggested that the positive effects of bluegill and parasites on body size may have greater effects on population growth than the direct effects of mortality.</span> <span>This study illustrates how predators can alter the outcome of parasitic infections and highlights the need for long-term experiments that investigate how changes in host-parasite systems alter population dynamics. We show some predators reduce parasite effects and have indirect positive effects on surviving individuals potentially increasing host population persistence. </span></span></p>
Figs 7–9 in Notes on the preimaginal stages and the type locality of Cissatsuma berezowskii Krupitsky, 2018 (Lepidoptera: Lycaenidae)
Figs 7–9. Host plant and habitat of Cissatsuma berezowskii Krupitsky, 2018. 7, 8 – Spiraea lasiocarpa, host plant; 9 – a valley east Chuanzhusi town (Songpan County, Sichuan Province).
COVID-19 Pandemic Stages Identification Using Machine Learning
<p>Here, we used python programming language as the Machine Learning process for identifying COVID-19 stages where we used the K-Means Clustering algorithm, Decision Tree, Naive Bayes Classifier, Random Forest, and AdaBoost algorithms. This repository also contains the dataset.</p> <p>GitHub Link:</p> <p>https://github.com/rayhanhemel/COVID-19-Pandemic-Stages-Identification-Using-Machine-Learning.git</p>
Ups!... I did it again: unveiling the hidden companion in Upsilon Sagittarii, a unique binary system at a second mass transfer stage
<p>Input files and simulation results for stellar evolution tracks computed for the paper "Ups!... I did it again: unveiling the hidden companion in Upsilon Sagittarii, a unique binary system at a second mass transfer stage". Version 15140 of MESA was used for the simulations. More details in the README.txt file and in the paper.</p>
Supporting information for: Age-specific sensitivity analysis of stable, stochastic and transient growth for stage-classified populations
<p>The study associated with this dataset proposes a way of performing age-specific sensitivity analysis of stable, stochastic and transient growth for stage-classified populations. Here, you find simulation code in R to produce figures in the manuscript and matrices reporting demographic data upon which code computations are performed.</p>
Cowpea GWAS drought stress in early vegetative stage
<p>The GWAS outputs for Cowpea (<em>Vigna unguiculata</em>) responses to drought stress at early vegetative stress. The cowpea seedlings (miniCore population) were exposed to drought stress at 17 days after germination using the weight of the pot and AAWEsmo device, developed in Julkowska Lab, Boyce Thompson Institute. The seedlings were kept at 60 and 10% of soil water holding capacity for 2 weeks and the data on cowpea shoot size, evapotranspiration and photosystem II efficiency was collected. The data was assembled and curated (https://rpubs.com/mjulkowska/Cowpea2022alltraits), and subsequently used for GWAS. The GWAS data was analyzed, and the most interesting associations were selected (https://rpubs.com/mjulkowska/Cowpea2022Gwas). </p> <p>The raw data was collected by Hayley Sussman, with help of Olga Khmelnitsky, while GWAS was performed by Magdalena Julkowska, using ASReml script developed by Arthur Korte (https://github.com/arthurkorte/GWAS), adapted for cowpea. </p>
Data for: Off-host survival of blacklegged ticks in eastern North America: A multi-stage, multi-year, and multi-site study
<p>Climatic conditions are widely thought to govern the distribution and abundance of ectoparasites, such as the blacklegged tick (<em>Ixodes scapularis</em>), vector of the agents of Lyme disease and other emerging human pathogens. However, translating physiological tolerances to distributional limits or mortality is challenging. Ticks may be able to avoid or tolerate unsuitable conditions, and what is lethal to one life history stage may not extend to others. Thus, even after decades of research there are clear gaps in our knowledge about how climatic conditions determine tick distributions or patterns of abundance. We present the results of a comprehensive, three-year study of the influence of local temperatures and vapor pressure deficits on the survival of each free-living, off-host stage of <em>I. scapularis</em> in semi-natural enclosures across three locations that span their current distribution in eastern North America. We found that only larvae are clearly sensitive to direct mortality from climatic conditions, specifically desiccating conditions, whereas mortality of nymphs and adults appears to stem from exhausted energy reserves. We also found strong evidence that key developmental transitions in the tick's life cycle—fed larvae molting into to nymphs, fed nymphs molting into adults, and fed females producing larvae (via egg masses)—were all strongly temperature-dependent, though temperatures were not limiting in any of our sites. Collectively, our results suggest that climate is likely to impact <em>I. scapularis</em> largely through its impact on the larval stage.</p>
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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.