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9,302 results for “DETECT”
Research Data for Comparative Evaluation of RT-PCR and Antigen-based Rapid Diagnostic Tests (Ag-RDTs) for SARS-CoV-2 Detection: Performance, Variant Specificity, and Clinical Implications
<p>This dataset represents laboratory findings for the comparative evaluation of the diagnostic performance of Ag-RDTs (Flourescence Immunoassay and Lateral Flow Immunoassay) with RT-PCR</p>
Fig. 3 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 3. Non-invasive diagnostic techniques for the detection of Orthohalarachne spp. (A) Sampling of sneezed mucus droplets and mucous nasal discharges from substrates of resting places. (B) Metal clothes hanger bent to form a square frame, covered with clingfilm and mounted on a telescopic rod and (C) sterile petri dishes mounted on a telescopic rod to directly collect sputum samples from the animals.
Fig. 2 in First molecular detection of Francisella tularensis in turtle (Testudo graeca) and ticks (Hyalomma aegyptium) in Northwest of Iran
Fig. 2. The evolutionary lineage was determined using the Maximum Likelihood method and the Tamura-Nei model. The displayed tree represents the one with the most favorable log likelihood (429.22). Additionally, the branches are accompanied by the percentage denoting how frequently the related taxa formed clusters in the trees. The initial trees for exploratory purposes were automatically created using the Neighbor-Join and BioNJ algorithms. This was accomplished by utilizing a matrix of pairwise distances, which were calculated employing the Tamura-Nei model. From these initial trees, the one with the most favorable log likelihood value was selected. This analysis was conducted on a collection of 31 nucleotide sequences. The encompassed codon positions consisted of 1st+2nd+3rd +Noncoding. The final dataset consisted of a total of 306 positions. The evolutionary analyses were performed utilizing MEGA11.
Fig. 1 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 1. Sampling area of Orthohalarachne spp. of South American sea lions in Valdivia, Chile. The exact sampling location is shown in the section (upper-left) as a red-framed black star. Map created with QGIS (https://qgis.org/en/site/) and map data used from OpenStreetMap (openstreetmap.org/copyright). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Tapeworms detected in wolf populations in Central Italy (Umbria and Marche regions): A long-term study
Fig. 2. Neighbor-Joining phylogenetic tree of the sequenced Taenia species and E. granulosus s.s. G3. Maximum Composite Likelihood method, 1000 bootstraps (MEGA11 Software).
Fig. 5 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 5. Haplotype (TCS) networks of Orthohalarachne diminuata and Orthohalarachne attenuata based on 16S rDNA sequences. (A) Network analysis based on countries of origin, (B) network analysis based on the pinniped host species (CSL=California sea lion, GFS = Guadalupe fur seal, NFS=Northern fur seal, SAS=South American sea lion). For better visualization a combined network analysis of Or. attenuata and Or. diminuata sequences is shown, however, the calculated distance (48 mutations) between species was clipped. Or. attenuata haplotypes are encircled in black boxes with dashed lines, whereas Or. diminuata haplotypes are encircled in light grey boxes with dashed lines based on estimated MOTUs by ABGD.
Fig. 2 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 2. Nasal discharge in three individuals (A, B, C) of the "urban" colony of South American sea lions Otaria flavescens in Valdivia, Chile.
Fig. 1 in Tapeworms detected in wolf populations in Central Italy (Umbria and Marche regions): A long-term study
Fig. 1. Details of sampling and results: number of wolves by region (A); number of positive wolves (B); percentages of positive and negative samples (C); geolocation of parasites (D).
Fig. 4 in Non-invasive detection of Orthohalarachne attenuata (Banks, 1910) and Orthohalarachne diminuata (Doetschman, 1944) (Acari: Halarachnidae) in free-ranging synanthropic South American sea lions Otaria flavescens (Shaw, 1800)
Fig. 4. Larval stages of (A) Orthohalarachne attenuata and (B) Orthohalarachne diminuata showing distinct differences in idiosoma length.
Fig. 3 in First molecular detection of Francisella tularensis in turtle (Testudo graeca) and ticks (Hyalomma aegyptium) in Northwest of Iran
Fig. 3. The lineage's evolutionary narrative was deduced through the application of the Neighbor-Joining technique. The most advantageous tree configuration is depicted. Adjacent to the branches, the percentages reflect how often the related taxa aggregated within the bootstrap test, comprising 1000 replicates. Evolutionary distances were calculated using the Maximum Composite Likelihood method, expressed as the count of base substitutions per site. In this study, a collective of 32 nucleotide sequences were taken into account. The codon positions covered 1st+2nd+3rd + Noncoding. Ambiguous positions were excluded for each sequence pair, following the pairwise deletion technique. In the culminating dataset, a collective count of 542 positions was encompassed. The evolutionary analyses were executed using MEGA11.
Buoy-based detection of low-energy cosmic-ray neutrons (Seelhausener See, July 15 to Dec 02, 2014)
<p>Contains two resources used in Schrön & Rasche et al. (2024):</p> <ol> <li><strong>Raw</strong> measurement data files from the buoy detector. Column names are provided in the header of the files. For detailed information about column names and descriptions, see the readme.</li> <li><strong>Processed</strong> measurement data of the buoy detector. Data has been stored as CSV files, the column names are described in `Buoy.csv.readme`. Additional PDF files show the corresponding plots. Two versions of data are provided: <ol> <li><strong>Buoy-1h</strong> contains data aggregated to 1 hour, and</li> <li><strong>Buoy-1h-mavg25</strong> contains the same data but the neutrons underwent a moving average filter with a window size of 25 (1 day).</li> </ol> </li> </ol> <p>Processing has been performed using Corny v0.8.2 (<a title="Corny" href="https://git.ufz.de/CRNS/cornish_pasdy">git.ufz.de/CRNS/cornish_pasdy</a>) with the configuration file <code>Buoy-1h.cfg</code>.</p>
Fig. 3 in Detection and molecular characterization of the mosquito-borne filarial nematode Setaria tundra in Danish roe deer (Capreolus capreolus)
Fig. 3. Neighbor-Joining phylogenetic relationship of four isolates of Setaria tundra from distant localities in Denmark. The analysis was based on cox1 gene sequences (578 bp). Percentage bootstrap support from 1000 replicate samples is indicated at the right of the supported node. Accession numbers for sequences obtained from GenBank are given in parentheses, followed by origin of isolate, only applicable to S. tundra. The scale bar indicates distance.
Fig. 1 in Detection and molecular characterization of the mosquito-borne filarial nematode Setaria tundra in Danish roe deer (Capreolus capreolus)
Fig. 1. Geographical origin (black dots) of Setaria tundra recovered from six infected roe deer. A: October 2010, B: May 2011, C: December 2012, D: May 2013 (two cases), and E: March 2014.
Fig. 2 in Detection and molecular characterization of the mosquito-borne filarial nematode Setaria tundra in Danish roe deer (Capreolus capreolus)
Fig. 2. Morphology of adult worms of Setaria tundra (A‾C) and microfilaria (D and E) recovered from roe deer in Denmark. A: Cephalic region showing the bifid projections (bp) carried on top of a peribuccal crown (pc) and one of the four cephalic papillae (cp). B: Posterior end of male worm with papillae weakly visible (arrowheads). C: Posterior end of female worm showing a knob at the tip of the tail (arrow head), that possesses longitudinal grooves and pores, a papilla (pa), and a collar composed of a row of bosses (co). D: Microfilaria collected from a female worm. The length of the microfilaria including the sheath (white arrow heads) was approximately 316 Mm, whereas the microfilaria was approximately 287 Mm, with a blunt anterior end and a tapering posterior end. E: Setaria tundra coiled under the liver capsule (case 3). Scale bars indicated for all but figure E.
Fig. 4 in First report of successful Naegleria detection from environmental resources of some selected areas of Rawlakot, Azad Jammu and Kashmir, Pakistan
Fig. 4. (A) Primary sequence alignment was obtained with reference sequences already available in Gen Bank. Neighbour joining phylogenetic relationship between the partial sequences of 18S rRNA of Naegleria from isolates obtained in this study and reference sequences present in Gen Bank. (B). Neighbour joining phylogenetic relationship between the partial sequences of 18S rRNA of Naegleria from isolates obtained in this study and reference sequences present in Gen Bank. The tree was generated in CLC Main Workbench version 6.6.2 using 1000 bootstrap replications. Branch length is proportional to the calculated genetic distance (scale shown).
Fig. 3 in First report of successful Naegleria detection from environmental resources of some selected areas of Rawlakot, Azad Jammu and Kashmir, Pakistan
Fig. 3. To confirm the incidence of Naegleria populations in water and soil samples, DNA were extracted from amoebae retrieved from NNA plates with 2 weeks time and utilized for PCR examination as demonstrated in methods section. PCR products were obtained in all DNA samples verifying the existence of Naegleria. Lane 1: 250 bp DNA ladder; Lane 2: RAW STW4; Lane 3: RAW LW1; Lane 4: RAW PW8; Lane 5: RAW DS1; Lane 6: RAW STW7; Lane 7: RAW TW3; Lane 8: RAW DS2; Lane 9: RAW DS3; Lane 10: RAW DS4; Lane 11: RAW DS5; Lane 12: RAW DS6; Lane 13: RAW DS7; Lane 14: RAW DS8; Lane 15: RAW DS9; Lane 16: RAW DS10; Lane 17: +ve control; Lane 18: -ve control.
Fig. 2 in First report of successful Naegleria detection from environmental resources of some selected areas of Rawlakot, Azad Jammu and Kashmir, Pakistan
Fig. 2. Naegleria cysts detection on NNA under inverted microscope (×400). Water and soil samples were filtered and pored respectively and inoculated on NNA plate seeded with E. coli as demonstrated in methods section. Plates were monitored for amoebic outgrowth up to two weeks, and images were taken. Only representative samples of water (a) RAW STW7 and soil (b) RAW DS7 are shown here.
Pockmark Bounding Box Detection and Segmentation Labels
<p>This dataset contains 256x256 pixel jpeg images of gridded depth values as well as binary masks for pixels containing pockmarks (these jpegs are merged together with the depth image on the left and the mask on the right, making a 512x256 image). These are contained within the subdirectory 'PockmarkMaskAnnotations'.</p> <p>Additionally, this dataset contains a csv containing bounding box annotations (label, bounding box coordinates in terms of image pixels, and a unique integer for the label) of pockmarks in each image. These are contained within the subdirectory 'PockmarkBoxAnnotations'.</p> <p>Together, these annotations can be used to construct either a bounding box object detector, a bounding box and mask object detector, or a semantic segmentation model.</p> <p>These were the labels used for the experiments described in Lundine et al., 2023. See this reference to find original data sources to the collected bathymetry data.</p> <p>Lundine, M., Brothers, L., Trembanis, A., Deep learning-based pockmark detection: implications for quantitative seafloor characterization, Geomorphology, 2023, Volume 421, 108524, <a href="https://doi.org/10.1016/j.geomorph.2022.108524">https://doi.org/10.1016/j.geomorph.2022.108524</a>.</p> <p> </p>
FREE-ROAMING DOGS DETECTED USING GOOGLE STREET VIEW
<p>Datasets to count free-roaming dogs using Google Street View, and compare with population of free-roaming dog from surveys in Arequipa, Peru.</p>
Fate and detectability of rare gas hydride ions in nova ejecta: A case study with nova templates
<p>The electron-impact HeH+ rovibrational data at temperatures up to 20,000 K used in the paper: "Fate and detectability of rare gas hydride ions in Novae ejecta: A case study with Nova templates".</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.