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4,325
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ShareScore release 0.9.0
Dataset results
4,325 results for “real”
Data from: Persistent near real-time passive acoustic monitoring for baleen whales from a moored buoy: system description and evaluation
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Data from: Evolutionary online behaviour learning and adaptation in real robots
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Data from: Real-time modulation of perceptual eye dominance in humans
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Human walking in the real world: interactions between terrain type, gait parameters, and energy expenditure
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Sionna ray tracing vs. real-world measurements: Signal strength comparison in rural scenarios with foliage
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Data from: Repeatable, continuous and real-time estimates of coupled nitrogenase activity and carbon exchange at the whole-plant scale
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Machine learning to extract muscle fascicle length changes from dynamic ultrasound images in real-time
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CroCoord v1.0 – an Android application for nearly real-time 3D PPP multi-frequency multi-GNSS static surveying using smartphones
<p>Two hour of GNSS data collected on 31st December 2019 on one point with Android dual-frequency smartphone Xiaomi Mi Mix-3 and permanent station in the surrounding of the measured point.</p>
Demand data belonging to paper "A Practical Optimization Scheme for Real-Time Operation of Water Distribution Systems"
<p>The CSV file contains the demand data used in the paper "A Practical Optimization Scheme for Real-Time Operation of Water Distribution Systems" published in the Journal of Water Resources Planning and Management (2020)</p> <p><a href="https://doi.org/10.1061/(ASCE)WR.1943-5452.0001188">https://doi.org/10.1061/(ASCE)WR.1943-5452.0001188</a></p> <p>The demand data is for the test case and consists of one year of hourly demand values for the 8 demand nodes of the demo network. The data is in units of cubic meters per hour.</p>
Data for manuscript "Estimate of airborne transmission of SARS-CoV-2 using real time tracking of healthcare workers."
<p>These are the data sets for a manuscript to calculate the transmissability of SARS CoV-2 via the airborne route. These data have the duration of exposure of healthcare workers to SARS CoV-2 and the code used to analyze to estimate q, and the comparison to other pathogens.</p>
Dataset for the paper: "The Gas Accessible Membrane Electrode (GAME): A Versatile Platform for Elucidating Electrocatalytic Processes Using Real Time and In Situ Hyphenated Electrochemical Techniques"
<p>The data in this spreadsheet was used to produce the figures in the paper</p> <p>Authors: Guohui Zhang, Anthony Kucernak</p> <p>Title: The Gas Accessible Membrane Electrode (GAME): A Versatile Platform for Elucidating Electrocatalytic Processes Using Real Time and In Situ Hyphenated Electrochemical Techniques </p> <p>Journal: ACS Catalysis, 2020</p> <p>DOI: 10.1021/acscatal.0c02433</p> <p>Please cite the above reference if you wish to use this data<br> DOI of data:10.5281/zenodo.3985811</p>
Data from: Automated CT perfusion imaging for acute ischemic stroke: pearls and pitfalls for real world use
Recent positive trials have thrust acute cerebral perfusion imaging into the routine evaluation of acute ischemic stroke. Updated guidelines state that in patients with anterior circulation large vessel occlusions presenting beyond 6 hours from time last known well, advanced imaging selection including perfusion based selection is necessary. Centers that receive acute stroke patients must now have the capability to perform and interpret CT or MR perfusion imaging, or provide rapid transfer to centers with the capability of selecting patients for a highly impactful endovascular therapy, particularly in delayed time windows. Many stroke centers are quickly incorporating the use of automated perfusion processing software to interpret perfusion raw data. As CT perfusion is being assimilated in real world clinical practice, it is essential to understand the basics of perfusion acquisition, quantification and interpretation. It is equally important to recognize the common technical and clinical diagnostic challenges of automated CTP including ischemic core and penumbral misclassifications that could result in underestimation or overestimation of the core and penumbra volumes. This review highlights the pitfalls of automated CT perfusion along with practical pearls to address the common challenges. This is particularly tailored to aid the acute stroke clinician who must interpret automated perfusion studies, in an emergency setting to make time-dependent treatment decisions for acute ischemic stroke patients.
On the use of real-time mortality data in modelling and analysis during an epidemic outbreak - underlying data
<p>This project contains the primary data set analyzed in the paper "On the use of real-time mortality data in modelling and analysis during an epidemic outbreak ". The data was generated by downloading the <em>D<sup>T</sup></em>-series daily from the Public Health Agency of Sweden between 2020-04-02 and 2020-07-09. </p> <p>This project contains the following files:</p> <ul> <li>FHM_Covid_Download.zip. (Zip-archive of raw downloaded files with Swedish deaths data.)</li> <li>swedish_covid_deaths_data.csv. (Swedish deaths data collated from the raw data files in a .csv format.)</li> <li>swedish_covid_deaths_data.xlsx. (Swedish deaths data collated from the raw data files in a .xlsx format.)</li> </ul>
Synthetic and real datasets for "Seismic source tracking with six degree-of-freedom ground motion observations"
<p>Synthetic datasets for the 2D and 3D rupture tracking and real datasets for the traffic noise tracking used in the manuscript "Seismic source tracking with six degree-of-freedom ground motion observations". The README file describes the data structures.</p>
Using real-time UV-visible spectrophotometer to assess an Al-Zn-Mg-Cu alloy's dissolution in acidic solution
<p>Applicability and limitations of using online non-destructive UV-vis spectrophotometer to monitor the dissolution of an Al-Zn-Mg-Cu alloy in HCl-containing solution were studied. ICP-AES results indicate that the spectrum absorbance at 252 nm is mainly attributed to Cu-containing complexes. Surprisingly, an hours-long "induction" period was observed from UV-vis results. This is not a real indicator of induction for Al dissolution as revealed by electrochemical impedance spectrum, actually it reflects the alloy's galvanic corrosion nature that Cu species are released after Al, Zn, Mg species.</p>
Dataset for Capturing roaming molecular fragments in real-time
<p>experimental data (ion and electron)</p> <p>quasi-classical trajectory data</p> <p>potential energies and gradients of triply charged state</p>
Data from: Online spatial normalization for real-time fMRI
Real-time functional magnetic resonance imaging (rtfMRI) is a recently emerged technique that demands fast data processing within a single repetition time (TR), such as a TR of 2 seconds. Data preprocessing in rtfMRI has rarely involved spatial normalization, which can not be accomplished in a short time period. However, spatial normalization may be critical for accurate functional localization in a stereotactic space and is an essential procedure for some emerging applications of rtfMRI. In this study, we introduced an online spatial normalization method that adopts a novel affine registration (AFR) procedure based on principal axes registration (PA) and Gauss-Newton optimization (GN) using the self-adaptive β parameter, termed PA-GN(β) AFR and nonlinear registration (NLR) based on discrete cosine transform (DCT). In AFR, PA provides an appropriate initial estimate of GN to induce the rapid convergence of GN. In addition, the β parameter, which relies on the change rate of cost function, is employed to self-adaptively adjust the iteration step of GN. The accuracy and performance of PA-GN(β) AFR were confirmed using both simulation and real data and compared with the traditional AFR. The appropriate cutoff frequency of the DCT basis function in NLR was determined to balance the accuracy and calculation load of the online spatial normalization. Finally, the validity of the online spatial normalization method was further demonstrated by brain activation in the rtfMRI data.
Selection and exploitation of prevalent, tandemly repeated genomic targets for improved real-time PCR-based detection of Wuchereria bancrofti and Plasmodium falciparum in mosquitoes
<p><b>Background</b></p> <p>Optimization of polymerase chain reaction (PCR)-based diagnostics requires the careful selection of molecular targets that are both highly repetitive and pathogen-specific. Advances in both next-generation sequencing (NGS) technologies and bioinformatics-based analysis tools are facilitating this selection process, informing target choices and reducing labor. Once developed, such assays provide disease control and elimination programs with an additional set of tools capable of evaluating and monitoring intervention successes. The importance of such tools is heightened as intervention efforts approach their endpoints, as accurate and complete information is an essential component of the informed decision-making process. As global efforts for the control and elimination of both lymphatic filariasis and malaria continue to make significant gains, the benefits of diagnostics with improved analytical and clinical/field-based sensitivities and specificities will become increasingly apparent.</p> <p><b>Methodology/Principal Findings </b></p> <p>Coupling Illumina-based NGS with informatics approaches, we have successfully identified the tandemly repeated elements in both the <i>Wuchereria bancrofti </i>and <i>Plasmodium falciparum </i>genomes of putatively greatest copy number. Utilizing these sequences as quantitative real-time PCR (qPCR)-based targets, we have developed assays capable of exploiting the most abundant tandem repeats for both organisms. For the detection of <i>P. falciparum</i>, analysis and development resulted in an assay with improved analytical and field-based sensitivity vs. an established ribosomal sequence-targeting assay. Surprisingly, analysis of the <i>W. bancrofti </i>genome predicted a ribosomal sequence to be the genome's most abundant tandem repeat. While resulting cycle quantification values comparing a qPCR assay targeting this ribosomal sequence and a commonly targeted repetitive DNA sequence from the literature supported our finding that this ribosomal sequence was the most prevalent tandemly repeated target in the <i>W. bancrofti </i>genome, the resulting assay did not significantly improve detection sensitivity in conjunction with field sample testing. </p> <p><b>Conclusions/Significance </b></p> <p>Examination of pathogen genomes facilitates the development of PCR-based diagnostics targeting the most abundant and specific genomic elements. While in some instances currently available tools may deliver equal or superior performance, systematic analysis of potential targets provides confidence that the selected assays represent the most advantageous options available and that informed assay selection is occurring in the context of a particular study's objectives.</p>
Data from: Diffantom: whole-brain diffusion MRI phantoms derived from real datasets of the Human Connectome Project
Diffantom is a whole-brain diffusion MRI (dMRI) phantom publicly available through the Dryad Digital Repository (doi:10.5061/dryad.4p080). The dataset contains two single-shell dMRI images, along with the corresponding gradient information, packed following the BIDS standard (Brain Imaging Data Structure, Gorgolewski et al., 2015). The released dataset is designed for the evaluation of the impact of susceptibility distortions and benchmarking existing correction methods. In this Data Report we also release the software instruments involved in generating diffantoms, so that researchers are able to generate new phantoms derived from different subjects, and apply these data in other applications like investigating diffusion sampling schemes, the assessment of dMRI processing methods, the simulation of pathologies and imaging artifacts, etc. In summary, Diffantom is intended for unit testing of novel methods, cross-comparison of established methods, and integration testing of partial or complete processing flows to extract connectivity networks from dMRI.
Data from: Integrating viscoelastic mass spring dampers into position-based dynamics to simulate soft tissue deformation in real time
We propose a novel method to simulate soft tissue deformation for virtual surgery applications. The method considers the mechanical properties of soft tissue, such as its viscoelasticity, nonlinearity, and incompressibility; its speed, stability, and accuracy also meet the requirements for a surgery simulator. Modifying the traditional equation for mass spring dampers introduces nonlinearity and viscoelasticity into the calculation of elastic force. Then, the elastic force is used in the constraint projection step for naturally reducing constraint potential. The node position is enforced by the combined spring force and constraint conservative force through Newton's second law. We conduct a comparison study of conventional mass spring dampers and position based dynamics (PBD) for our new integrating method. Our approach enables stable, fast, and large step simulation by freely controlling visual effects based on nonlinearity, viscoelasticity and incompressibility. We implement a laparoscopic cholecystectomy simulator to demonstrate the practicality of our method, in which liver and gallbladder deformation can be simulated in real time. Our method is an appropriate choice for the development of real-time virtual surgery applications.
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.