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14,867 results for “determination”
Stable isotopes of Mya arenaria during 2010 and 2011 to determine food sources
Several sites in Plum Island Sound, the mainstem of the Parker River and Rowley River were selected and sampled during 2010 and 2011 for 2 and 4 inch intertidal clams on a monthly basis. The tissue of these clams were analyzed for stable isotopes to determine the food source of these clams. Water samples were also filtered and plants were collected to determine their isotopic composition as well.
FIG. 5 in The equids represented in cave art and current horses: a proposal to determine morphological differences and similarities
FIG. 5. — Representation of the Magdelian horse figures studied: A-D, "Altamira"; E, F, "Niaux"; G, "Font de Gaume"; H-M, "Lascaux". Designed by Francisco Salado (IAPH), using dashed lines in some recreated parts of the figures.
FIG. 7 in The equids represented in cave art and current horses: a proposal to determine morphological differences and similarities
FIG. 7. — In current breeds of horses, the mane is long and hangs by the neck. In this picture, the "Retuertas" horse could be one of the most ancient breeds. Photo Esteban García-Viñas.
FIG. 6 in The equids represented in cave art and current horses: a proposal to determine morphological differences and similarities
FIG. 6. — Discriminant body proportion analysis of three species of modern horses show three separate groups using: A, absolute variables and B, indexes.
Fig. 2 in Discrimination of habitat use between two sympatric species of mullets, Mugil curema and Mugil liza (Mugiliformes: Mugilidae) in the rio Tramandaí Estuary, determined by otolith chemistry
Fig. 2. Means and standard deviations (SD) of (a) Sr86:Ca43 (mmol.mol-1); and (b) Ba137:Ca43 ratio (µmol.mol-1) in otoliths of the inner 20 measurements (core) and the outer 20 measurements (edge) of Mugil curema and M. liza caught in the Tramandaí River Estuary, Brazil. Different letters within a spruce stand denote significant differences between species (Mann-Whitney U test, p<0.05).
Fig. 4 in Discrimination of habitat use between two sympatric species of mullets, Mugil curema and Mugil liza (Mugiliformes: Mugilidae) in the rio Tramandaí Estuary, determined by otolith chemistry
Fig. 4. Otolith transects of Mugil liza measured by LA-ICP-MS from the core to the edge. Ba137:Ca43 (line) and Sr86:Ca43 (dashed line). The identification code and total length (mm) of each fish are indicated on the graph.
Fig. 3 in Discrimination of habitat use between two sympatric species of mullets, Mugil curema and Mugil liza (Mugiliformes: Mugilidae) in the rio Tramandaí Estuary, determined by otolith chemistry
Fig. 3. Otolithtransectsof Mugilcurema measuredbyLA-ICP-MSfromthecoretotheedge. 43 (line) 86 43 (dashedline). Theidentificationcodeand totallength (mm) ofeachfishareindicatedonthegraph.
Genomic determinants of pathogenicity in SARS-CoV-2 and other human coronaviruses
<p><strong>Dataset S1.</strong>Complete nucleotide sequence alignment of all human CoV used for region identification. </p> <p><strong>Dataset S2.</strong>Complete nucleotide sequence alignment of all CoV (of human and non-human hosts).</p> <p><strong>Dataset S3.</strong>Distances between leaves (each CoV strain in Dataset S2 was considered), from every reference genome of each of the seven human CoV.</p> <p><strong>Dataset S4.</strong>Alignment of strains used for zoonotic jump analysis.</p>
Habitat features and performance interact to determine the outcomes of terrestrial predator-prey pursuits
<p>1. Animals are responsive to predation risk, often seeking safer habitats at the cost of foraging rewards. Although previous research has examined how habitat features affect detection by predators, little is known about how the interaction of habitat features, sensory cues, and physical performance capabilities affect prey escape performance once detected.</p> <p>2. To investigate how specific habitat features affect predation risk, we developed an individual-based model of terrestrial predator–prey pursuits in habitats with programmable features.</p> <p>3. We ran simulations varying the relative performance capabilities of predator and prey as well as the availability and abundance of refuges and obstacles in the habitat.</p> <p>4. Prey were more likely to avoid detection in complex habitats containing a higher abundance of obstacles; however, if detected, prey escape probability was dependent on both the abundance of refuges and obstacles and the predator's relative performance capabilities. Our model accurately predicted the relative escape success for impala escaping from cheetah in open savanna versus acacia thicket habitat, though escape success was consistently underestimated.</p> <p>5. Our model provides a mechanistic explanation for the differential effects of habitat on survival for different predator–prey pairs. Its flexible nature means that our model can be refined to simulate specific systems and could have applications toward management programs for species threatened by habitat loss and predation.</p>
Dataset for the paper "Slavic morphosyntax is primarily determined by its geographic location and contact configuration", Scando-Slavica Journal
<p>This is the raw dataset for the paper "Slavic morphosyntax is primarily determined by its geographic location and contact configuration", Scando-Slavica</p>
Population genomics reveals molecular determinants of specialization to tomato in the polyphagous fungal pathogen Botrytis cinerea
<p>Single nucleotide polymorphisms detected in Illumina-sequenced isolates of B. cinerea collected from tomato, grape, hydrangea and bramble in France.</p>
Data from: Fungal communities are important determinants of bacterial community composition in deadwood
<p>Fungal-bacterial interactions play a key role in the functioning of many ecosystems. Thus, understanding their interactive dynamics is of central importance for gaining predictive knowledge on ecosystem functioning. However, it is challenging to disentangle the mechanisms behind species associations from observed co-occurrence patterns and little is known about the directionality of such interactions. Here we apply joint species distribution modelling to high-throughput sequencing data on co-occurring fungal and bacterial communities in deadwood to ask whether fungal and bacterial co-occurrences result from shared habitat use (i.e. dead wood's properties), or whether there are fungal-bacterial interactive associations after habitat characteristics are taken into account. Moreover, we test the hypothesis that the interactions are mainly modulated through fungal communities influencing bacterial communities. For that, we quantified how much the predictive power of the joint species distribution models for bacterial and fungal community improved when accounting for the other community. Our results show that fungi and bacteria form tight association networks (i.e. some species pairs co-occur more frequently and other species pairs co-occur less frequently than expected by chance) in deadwood that include common (or opposite) responses to the environment, as well as (potentially) biotic interactions. Additionally, we show that information about the fungal occurrences and abundances increased the power to predict the bacterial abundances substantially, whereas information about the bacterial occurrences and abundances increased the power to predict the fungal abundances much less. Our results suggest that fungal communities may mainly affect bacteria in deadwood.</p> <p><b>Importance</b></p> <p>Understanding the interactive dynamics between fungal and bacterial communities is important to gain predictive knowledge on ecosystem functioning. However little is known about the mechanisms behind fungal-bacterial associations and the directionality of species interactions. Applying joint species distribution modelling to high throughput sequencing data on co-occurring fungal-bacterial communities in deadwood, we found evidence that non-random fungal-bacterial associations derive from shared habitat use, as well as (potentially) biotic interactions. Importantly,<i> </i>the combination of cross-validations and conditional cross-validations helped us to answer the question about the directionality of the biotic interactions, providing evidence that suggests that fungal communities may mainly affect bacteria in deadwood. Our modelling approach may help gaining insight into the directionality of interactions between different components of the microbiome in other environments.</p>
Social determinants of Covid-19 infection and death in a rural Indonesia: A rapid healthcare assessment
<p>Understanding the social determinants of Covid-19 infection and death is vital for effective Covid-19 early detection and mitigation strategies. This study aims to examine social determinants of Covid-19 infection and death in the context of rural Indonesia. We used Malang district government Covid-19 contact tracing data from 14,264 individuals, spanning the period from March 1, 2020 to July 29, 2020. The contact tracing data was merged with administrative data from 390 villages to determine whether village characteristics (i.e., the number of health workers, number of community-based healthcare interventions, access to Covid-19 referred hospitals, number of indigenous socio-cultural activities, poverty level and distance to a Covid-19 epicentre city) are associated with Covid-19 infection and death. We used multilevel logistic regression to take advantage of the nested structure of data at the village level. We found among the 14,264 samples, 551 individuals were confirmed infected with Covid-19, and 62 died of Covid-19. Individuals aged 18 and older, civil servants (non-health workers), and those having close contact with people with confirmed cases had a higher likelihood of infection with Covid-19. Greater numbers of community-based healthcare interventions and a lesser distance to a pandemic epicentre reduced the likelihood of infection with the virus. Males, older people, individuals with hypertension, individuals diagnosed with pneumonia, and those diagnosed with respiratory failure had a higher likelihood of death due to Covid-19. A greater number of community-based healthcare interventions seems to reduce the likelihood of Covid-19 infection, while better access to a Covid-19 referred hospital seems to reduce the risk of death among Covid-19 patients. The findings suggest the government to prioritise strategies to control the pandemic in rural area through empowering rural community in health education to prevent Covid-19 and in monitoring people mobility, while providing Covid-19 emergency services for rural areas for reducing mortality.</p>
Research data supporting for Application of electron tomography of dislocations in beam-sensitive quartz to the determination of strain components
<p>This archives contains all the raw data (micrographs) supporting the publication</p>
A dataset used to determine a semantic similarity metric based on UMLS for PMC-OA
<p>We have performed a series of in-silico experiments in order to determine a semantic similarity metric based on UMLS annotations for PubMed Central Open Access. Here we have stored the data used for and obtained from such experiments. We have worked with relevant and partially relevant articles from the TREC-2005 Genomics Track Collection, from now referred as the initial collection, including a total of 4240 unique PubMed articles. From those 4240 articles, only 62 had publicly available; those 62 articles correspond to the full-text collection.</p> <p>Our data comprises flat files using tabs as separators and one Excel sheet. Tab separated values always include a first row with headings:</p> <ul> <li>Stems extracted from title and abstract for articles in the initial collection. Each row contains a stem with its inverse-document-frequency (IDF) within the initial collection. Stems were calculated following the Porter algorithm (available at http://tartarus.org/martin/PorterStemmer/java.txt) <ul> <li>stems.TA.tsv</li> </ul> </li> <li>Article profiles, i.e., terms (either word stems or UMLS concepts) found in the articles with term frequency (TF) and IDF. The first two columns correspond to PubMed Identifier (PMID) and PubMed Central identifier (PMC). PMC identifier was set to 0 whenever full-text was not available. <ul> <li>profiles.TA.tsv: Profiles according word stems in title and abstract for the initial collection</li> <li>profiles.PMID.tsv: Profiles according to UMLS concpets in title and abstract for the initial collection</li> <li>profiles.PMC_TA.tsv: Profiles according to UMLS concepts in title and abstract for the full-text collection</li> <li>profiles.PMC.tsv: Profiles according to UMLS concepts in the full-text for the full-text collection</li> </ul> </li> <li>Similarity matrixes calculated on the article profiles with PubMed Related Article metric (PMRA), BM25, and Cosine. There are matrixes for terms found in title-and-abstract as well as full-text. In a similarity matrix, a reference article (an interest has been already expressed for it) correspond to a row, while the columns correspond to all the other articles for which the similarity was calculated. <ul> <li>Matrixes for our initial collection <ul> <li>similarity.PMRA.TA.profiles.TA.tsv: Similarity matrix for profiles.TA.tsv following the algorithm PMRA. This matrix is considered the baseline for further analyses</li> <li>similarity.PMRA.profiles.PMID.tsv: Similarity matrix for profiles.PMID.tsv following the algorithm PMRA</li> <li>similarity.BM25_1.2_0.75.profiles.PMID.tsv: Similarity matrix for profiles.PMID.tsv following the algorithm BM25 with k=1.2 and b=0.75</li> <li>similarity.COSINE.profiles.PMID.tsv: Similarity matrix for profiles.PMID.tsv following the algorithm Cosine</li> </ul> </li> <li>Matrixes for our full-text collection <ul> <li>similarity.PMRA.profiles.PMC_TA.tsv: Similarity matrix for profiles.PMC_TA.tsv following the algorithm PMRA</li> <li>similarity.PMRA.profiles.PMC.tsv: Similarity matrix for profiles.PMC.tsv following the algorithm PMRA</li> <li>similarity.BM25.profiles.PMC_TA.tsv: Similarity matrix for profiles.PMC_TA.tsv following the algorithm BM25 with k=1.2 and b=0.75</li> <li>similarity.BM25.profiles.PMC.tsv: Similarity matrix for profiles.PMC.tsv following the algorithm BM25 with k= 1.2 and b= 0.75</li> <li>similarity.COSINE.profiles.PMC_TA.tsv: Similarity matrix for profiles.PMC_TA.tsv following the algorithm Cosine</li> <li>similarity.COSINE.profiles.PMC.tsv: Similarity matrix for profiles.PMC.tsv following the algorithm Cosine</li> </ul> </li> </ul> </li> <li>Correlation matrixes for similarities calculated for title-and-abstract taking as reference the similarity values obtained with PMRA for word stems on title-and-abstract. <ul> <li>pearsonCorrelation.PMRA.tsv: Correlation for similarity.PMRA.profiles.PMID.tsv</li> <li>pearsonCorrelationTopic.PMRA.tsv: Correlation for similarity.PMRA.profiles.PMID.tsv discriminated by TREC topics</li> <li>pearsonCorrelation.BM25_1.2_0.75.tsv: Correlation for similarity.BM25_1.2_0.75.profiles.PMID.tsv</li> <li>pearsonCorrelationTopic.BM25_1.2_0.75.tsv: Correlation for similarity.BM25_1.2_0.75.profiles.PMID.tsv discriminated by TREC topics</li> <li>pearsonCorrelation.COSINE.tsv: Correlation for similarity.COSINE.profiles.PMID.tsv</li> <li>pearsonCorrelationTopic.COSINE.tsv: Correlation for similarity.COSINE.profiles.PMID.tsv discriminated by TREC topics</li> </ul> </li> <li>Precision and recall summaries for the similarities calculated based on title-and-abstract. <ul> <li>StatsAllSummary.xlsx: Precision and recall at a global level, i.e., without considering TREC topics. This file includes information for BM25 with multiples values for constants k and b</li> </ul> </li> </ul> <p>Visualization for correlation matrixes as well as scattered plots for full-text based similarity is available at http://ljgarcia.github.io/semsim.benchmark</p>
The Quadratic Zeeman effect used for state-radius determination in neutral donors and donor bound excitons in Si:P.
<p>Raw experimental data of Photoluminescence as a function of magnetic field for phosphorus impurity in silicon at 4.2K. First column is energy in meV, the other columns are the photo-luminescence intensities in arbitrary units measured at different magnetic fields. The first row indicates the values of the magnetic fields presented in each column. The photo-luminescence measured at 10T (and presented in this dataset as column 11) is shown in the paper as Fig.2. </p>
Raw Genotyping data from: Variation in recombination rate and its genetic determinism in sheep populations from combining multiple genomewide datasets
<p>Data supporting :</p> <p><strong>Variation in recombination rate and its genetic determinism in sheep populations from combining multiple genomewide datasets</strong></p> <p>Morgane Petit, Jean-Michel Astruc, Julien Sarry, Laurence Drouilhet, Stephane Fabre, Carole Moreno, Bertrand Servin</p> <p>http://doi.org/10.1534/genetics.117.300123</p> <p><strong>Abstract</strong></p> <p>Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and datasets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified about 50,000 crossover hotspots on the genome and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting inter-individual variation in recombination rate in Lacaune, including the <em>RNF212</em> and<em> HEI10</em> genes and possibly 2 other loci of smaller effects including the <em>KCNJ15</em> and <em>FSHR</em> genes. Finally, we compared our results to those obtained previously in a distantly related population of domestic sheep, the Soay. This comparison revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome and that the two datasets can be combined to create more precise male meiotic recombination maps in sheep. Despite their similar recombination maps, we show that Soay and Lacaune males exhibit different heritabilities and QTL effects for inter-individual variation in genome-wide recombination rates.</p> <p> </p> <p>Data files are provided in Plink format ( https://www.cog-genomics.org/plink2 ).</p> <p> </p>
Determinants of Thermal Refuges
<p>This repository contains the database presented in "What environmental features give rise to thermal refuges? A systematic review," as well as the necessary code to recreate the figures from that manuscript.</p>
Figure 22. A in Functional morphology of neck musculature in the Tyrannosauridae (Dinosauria, Theropoda) as determined via a hierarchical inferential approach
Figure 22. A, origins and insertions of mm. intercristales (top, light-fill shapes), mm. intertransversarii (dark-fill shapes) and an interpretation of dorsal, rib head origins (large light-filled shapes) of m. iliocostalis capitis, of Tyrannosaurus rex (AMNH 5027). B, moment arms for lateroflexion by mm. intertransversarii on C6–C8 of Tyrannosaurus rex (BHI 3033, ventral view).
Figure 23. A in Functional morphology of neck musculature in the Tyrannosauridae (Dinosauria, Theropoda) as determined via a hierarchical inferential approach
Figure 23. A, topological appearance of m. rectus capitis ventralis (anterior muscles) and m. iliocostalis cervicis (posteroventrally originating muscles) on anterior axial skeleton of Tyrannosaurus rex (BHI 3033), ventral view. The moment arm for lateral flexion by m. iliocostalis cervicis is superimposed. B, m. r.c.v.: origins of m. rectus capitis ventralis from ventral spinous processes of Tyrannosaurus rex (BHI 3033) with arrow showing course of the muscle. m. il. cerv.: origin from ventral centra and insertions onto ventral fascia of cervical ribs of m. iliocostalis cervicis, with arrow showing course of the muscle. C, insertion of m. rectus capitis ventralis onto basioccipital of Daspletosaurus torosus (CMN 8506; the specimen is incomplete and the image partly mirrored), showing moment arms. Because the tyrannosaurid occiput slopes anteroventrally, the ventroflexion moment arm is somewhat longer than depicted in this view. D, strength of functional inference for head ventroflexion by m. rectus capitis ventralis in Tyrannosaurus rex. E, strength of functional inference for neck lateroflexion by m. iliocostalis cervicis of Tyrannosaurus rex.
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.