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9,302 results for “DETECT”
Supplementary material - Broadband Stimulated Raman Imaging based on Multi channel Lock-in Detection for Spectral Histopathology
<p>Supplementary material</p>
Data from: The prevalence of c.2268dup and detection of two novel alterations, c.670_672del and c.1186C>T, in the TPO gene in a cohort of Malaysian-Chinese with thyroid dyshormonogenesis
Objectives: The c.2268dup mutation in the thyroid peroxidase (TPO) gene is the most common TPO alteration reported in Taiwanese patients with thyroid dyshormonogenesis. The ancestors of these patients are believed to originate from the southern province of China. Our previous study showed that this mutation leads to reduced abundance of the TPO protein and loss of TPO enzyme activity in a Malaysian-Chinese family with goitrous hypothyroidism. The aim of our study was to provide further data on the incidence of the c.2268dup mutation in a cohort of Malaysian-Chinese and its possible phenotypic effects. Setting: Cohort study. Participants: Twelve biologically unrelated Malaysian-Chinese patients with congenital hypothyroidism were recruited in this study. All patients showed high TSH and low fT4 levels at the time of diagnosis with proven presence of thyroid gland Primary outcome measure: Screening of the c.2268dup mutation in the TPO gene in all patients was carried out using PCR-direct DNA sequencing method. Secondary outcome measure: Further screening for mutations in other exonic regions of the TPO gene was carried out if the patient is a carrier for the c.2268dup mutation Results: The c.2268dup mutation was detected in 4 out of the 12 patients. Apart from the c.2268dup and a previously documented mutation, c.2647C>T, two novel TPO alterations namely c.670_672del and c.1186C>T were also detected in our patients. In silico analyses predicted that the novel alteration affect the structure/function of the TPO protein. Conclusion: The c.2268dup was detected in approximately one third of the Malaysian-Chinese with thyroid dyshormonogenesis. The detection of the novel c.670_672del and c.1186C>T alterations expand the mutation spectrum of TPO associated with thyroid dyshormonogenesis.
Classical Center-Surround Receptive Fields Facilitate Novel Object Detection in Retinal Bipolar Cells
<p>Database and Figures in Igor format</p>
Accuracy of EEG Biomarkers in the Detection of Clinical Outcome in Disorders of Consciousness after Severe Acquired Brain Injury: Preliminary Results of a Pilot Study Using a Machine Learning Approach
<p>Dataset for the accepted publication: "Accuracy of EEG Biomarkers in the Detection of Clinical Outcome in Disorders of Consciousness after Severe Acquired Brain Injury: Preliminary Results of a Pilot Study Using a Machine Learning Approach"</p> <p> </p>
ASVs detected in the microbiome of marine invertebrates.
<p>Data table.</p>
Features detected in methanolic extracts of marine invertebrates.
<p>Data table.</p>
Detecting Code Smells in React-based Web Apps
<p>Detecting Code Smells in React-based Web Apps - Dataset</p>
auto_dataset_for_object_detection
<p>auto_dataset_for_object_detection</p>
Supplementary material 1 from: Wilson CR, Cooke-McEwen C, Gilligan TM, Tembrock LR (2022) Detection of Centistes sp. (Hymenoptera, Braconidae) from intercepted Diabrotica undecimpunctata (Coleoptera, Chrysomelidae) using CO1 DNA barcodes and larval morphology. Journal of Hymenoptera Research 91: 69-81. https://doi.org/10.3897/jhr.91.84139
DNA alignments and figures
Detecting periodicities in time-series (for exoplanet detection)
<p>Recording of the presentation given at the Summer School</p>
LIGO/Virgo/KAGRA Observing Capabilities: Simulated Detections and Localization for O4 and O5 (October 2022 edition)
<p>Simulated detections and localizations for LIGO, Virgo, and KAGRA</p>
Robust and fast post-processing of single-shot spin qubit detection events with a neural network
<p>Dataset to the paper 'Robust and fast post-processing of single-shot spin qubit detection events with a neural network'</p>
Supplementary material 1 from: García-Díaz P, Ross JV, Vall-llosera M, Cassey P (2019) Low detectability of alien reptiles can lead to biosecurity management failure: a case study from Christmas Island (Australia). NeoBiota 45: 75-92. https://doi.org/10.3897/neobiota.45.31009
: Data type: measurement
Microseismic event catalogue for the April 2022 third stimulation at FORGE Enhanced Geothermal System (Utah, US) generated applying a semblance-based detection method to DAS data
<p>The dataset contains microseismic event detections for the third stimulation stage (started on 21 April 2022 at 13:48:22 UTC) performed at FORGE Enhanced Geothermal System (Utah, US) (EGIUU, 2022). We created the catalogue of detections using the semblance-based detection method described in Porras et al. (2024). We applied the detector only to the optical fibre in the observational well 78B-32 (EGIUU, 2022). </p> <p>The catalogue contains events detected from 21 April 2022 at 13:00 UTC to 22 April 2022 at 13:00 UTC and is compared with the Short-Term Average/Long-Term Average catalogue created by Silixa LLC for the same time interval (EGIUU, 2022).</p> <p>The semblance-based detection method detects 2187 events in comparison to the 1169 events reported in the Silixa LLC catalogue. Notice that both catalogues are declustered by removing detections less than 0.7 seconds apart (we keep the earliest detection in case of two or more events within 0.7 seconds). We inspect for common events in both catalogues by considering a time interval of ± 0.6 seconds from the detection time of the events in our catalogue (in the case of more than one event we keep only the closest detection). We find 1086 common events, 83 events only contained in the Silixa's catalogue, and 1101 events only contained in the catalogue from Porras et al. (2024). We manually inspect all the detected events and classify as false detection 6 out of the 1086 events common to both catalogues, 64 out of the 83 events only in the Silixa's catalogue, and 116 of the 1101 events only in the catalogue from Porras et al. (2024). False detections, in addition to noise where no clear P and/or S-waves are visible, include codas of microseismic events (e.g. the same event is picked multiple times especially in the cases where the events occur across two files), and seismic events not related to the FORGE stimulation. In summary, our catalogue contains 2187 microseismic events with 122 potential false detections (5.6 %), while the Silixa's catalogue contains 1169 microseismic events with 70 potential false detections (6.0 %).</p> <p>In this data repository we also include a catalogue "microseismicity_catalogue.csv" with the detection times, the catalogue to which the detection belong (i.e., common detection to both Silixa's catalogue and the catalog from this study, only the Silixa's catalogue, only the catalogue from this study), and a description of the detection (i.e., real event, or false detection). We also upload the figures of all the detections where the figure name correspond to the detection time. The figures are obtained using the original sampling rate of the data (i.e., 4 kHz) and applying a Frequency-Wavenumber (FK) filter to remove the K=0 and unwanted energy (an example of the used F-K filter is also included in this repository). Traces in the figures have amplitudes normalized between -1 and 1. </p> <p>For additional details about the method used to obtain the catalogue we refer the reader to Porras et al. (2024)</p> <p>References:</p> <p>EGIUU, Energy and Geoscience Institute at the University of Utah. (2022). Utah FORGE: Well 16A(78)-32 2022 Stimulation Silixa Microseismic Report [data set]. Retrieved from https://dx.doi.org/10.15121/1893532.</p> <p>Porras, J., Pecci, D., Bocchini, G. M., Gaviano, S., De Solda, M., Tuinstra, K., Tognarelli, A., Lanza, F., Stucchi, E., and Grigoli, F. (2023). A Semblance-based Microseismic Event Detector for DAS Data. Geophysical Journal International, ggae016, https://doi.org/10.1093/gji/ggae016</p>
Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata
<p>Genetic and Environmental datasets used to perform population structure, isolation-by-distance, and GLMM analysis. See the paper for abbreviations and units of DEM-derived variables.</p>
Figure 3 from: Hartgerink C, Wicherts J, van Assen M (2016) The value of statistical tools to detect data fabrication. Research Ideas and Outcomes 2: e8860. https://doi.org/10.3897/rio.2.e8860
Figure 3 - Data table from Ruys and Stapel (2008), retracted due to data fabrication. This table includes 15 duplicates (highlighted) in 32 cells, which can be seen as a serious data anomaly that could have been detected with, for example, automated screening procedures.
BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection
<p>Artifacts for the paper titled <strong><em>BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection</em></strong>.</p> <p>This artifact repository contains 3 compressed folders, as follows: </p> <table> <tbody> <tr> <td><strong>File Name</strong></td> <td><strong>Benchmark System</strong></td> </tr> <tr> <td>fse-ob.zip</td> <td>Online Boutique</td> </tr> <tr> <td>fse-ss.zip</td> <td>Sock Shop</td> </tr> <tr> <td>fse-tt.zip</td> <td>Train Ticket</td> </tr> </tbody> </table> <p>Each zip file contains the collected data from the corresponding microservice benchmark systems (e.g., fse-ob.zip contains metrics data collected from the Online Boutique system). </p> <p><strong><strong>Data description</strong></strong></p> <p>To collect the metrics data, we deploy three benchmark microservice systems: Online Boutique, Sock Shop, and Train Ticket, on a Kubernetes cluster consisting of one master node and five worker nodes. Then, we deploy a monitoring system to monitor and collect resource-level and service-level metrics. To generate traffic, we use the load generators supplied by these systems and tailor them to explore all services with a load of 40-50 requests per second. Initially, we operate the applications normally to gather metrics data under normal conditions. Then, we inject faults into the running services. We execute into the designated container using kubectl exec. For CPU hog and memory leak, we use stress-ng to stress the container resource. For network delay and packet loss, we use tc (traffic control) to manipulate the traffic of the container. Specifically, we inject faults into five targeted services of Sock Shop (carts, catalogue, orders, payment, and user), five targeted services of Online Boutique (adservice, cartservice, checkoutservice, currencyservice, and productcatalogue), and five targeted services of Train Ticket (ts-auth-service, ts-order-service, ts-route-service, ts-train-service, ts-travel-service). For each combination of fault type and targeted service, we repeat the operation (i.e., fault injection and metrics data collection) five times, resulting in 100 failure cases for each benchmark microservice system.</p> <p><strong>Code</strong></p> <p>The code to reproduce the experimental results in the paper is available at <a href="https://github.com/phamquiluan/baro">https://github.com/phamquiluan/baro</a>.</p>
Trained Machine Learning Model to Detect Surface Events from Seismograms
Open the record for dataset details and reuse information.
A Deep Learning-Based Approach for Efficient Detection and Classification of Local Ca²⁺ Release Events in Full-Frame Confocal Imaging
<p>U-Net implementation and project code: <a href="https://github.com/dottipr/sparks_project">https://github.com/dottipr/sparks_project</a></p> <p>GUI's github repository: <a href="https://github.com/r-janicek/xytCalciumSignalsDetection">https://github.com/r-janicek/xytCalciumSignalsDetection</a></p>
Estradiol reference intervals in children, postmenopausal women and men using a noncompetitive immunoassay detection system
Open the record for dataset details and reuse information.
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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.