Find research datasets worth reusing

opencc-by-sa-4.0Nov 2018View details →

Real-time solution of coupled Ehrenfest-Maxwell-Pauli-Kohn-Sham equations for a nanoplasmonic dimer, distance d = 0.5 nm

Here we provide the movie mentioned in https://arxiv.org/abs/1812.05049 that shows the real-time dynamics of the nanoplasmonic dimer with distance $ d_1=0.5 $ nm. The time-evolution in the movie corresponds to the runs that we discuss in section VI. In the figure, we show a frame of the movie at time 8.33 fs. The upper two panels show contour plots of matter variables, the absolute value of the current density and the electron localized function (ELF). The most relevant Maxwell field variables, the electric field along the laser polarization direction z and the total Maxwell energy are presented in the lower panels. In the top of the figure, we show the incident laser pulse and at the center the geometry of the nanoplasmonic dimer.

opencc-by-sa-4.0Nov 2018View details →

Real-time solution of coupled Ehrenfest-Maxwell-Pauli-Kohn-Sham equations for a nanoplasmonic dimer, distance d = 0.1 nm

Here we provide the movie mentioned in https://arxiv.org/abs/1812.05049 that shows the real-time dynamics of the nanoplasmonic dimer with distance $ d_1=0.1 $ nm. The time-evolution in the movie corresponds to the runs that we discuss in section VI. In the figure, we show a frame of the movie at time 6.89 fs. The upper two panels show contour plots of matter variables, the absolute value of the current density and the electron localized function (ELF). The most relevant Maxwell field variables, the electric field along the laser polarization direction z and the total Maxwell energy are presented in the lower panels. In the top of the figure, we show the incident laser pulse and at the center the geometry of the nanoplasmonic dimer.

opencc-zeroNov 2022View details →

Efficient Real-Time Selective Genome Sequencing on Resource-Constrained Devices

This dataset contains the curated nanopore raw signal data in <a href="https://www.nature.com/articles/s41587-021-01147-4">BLOW5 format </a>used to benchmark <a href="https://github.com/beebdev/HARU/">Hardware Accelerated Read Until (HARU)</a>. This dataset was created by using the publicly available datasets: <a href="https://community.artic.network/t/links-to-raw-fast5-fastq-data-for-artic-protocol/17">SARS-CoV-2 SP1</a> (1.382M reads) and <a href="https://ncbi.nlm.nih.gov/sra/SRX11368475">NA12878 PromethION subset</a> (500,000 reads). The tarball when extracted will have the following directory structure: haru-data ├── na12878-rfc1 │   ├── blow5-rawsignal │   │   ├── na12878_dna_0.blow5 │   │   ├── na12878_dna_100.blow5 │   │   ├── na12878_dna_101.blow5 │   │   ├── na12878_dna_102.blow5 │   │   ├── ... │   └── reference │       └── rfc1.fa └── SARS-CoV-2-sp1     ├── blow5-rawsignal     │   ├── readgroup0     │   │   ├── reads_0_0.blow5     │   │   ├── reads_0_10.blow5     │   │   ├── reads_0_11.blow5     │   │   ├── reads_0_12.blow5     │   │   ├── ...     │   └── readgroup1     │       ├── reads_1_0.blow5     │       ├── reads_1_10.blow5     │       ├── reads_1_11.blow5     │       ├── ....     └── reference         └── nCoV-2019.reference.fasta nCoV-2019.reference.fasta is the SARS-CoV-2 MN908947.3 reference genome. rfc1.fa is the genomic region hr4:39262456-39391375 extracted from hg38 human genome.

openother-openDec 2022View details →

dhaw/fluCodeImperial: Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis

All codes and data used for "Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis" are included in this folder. The file "runExamples.m" contains a step-by-step method for reproducing figures and running model fits. Ensure that all data and code files are in the same directory, then a single execution of “runExamples” on the command line will generate all main and supplementary figures in the manuscript. There is one line of code per figure, clearly marked, that can be commented out as desired. In order to run the MCMC adaptive algorithm, a single line of code, also clearly marked, must be commented back in. Instructions to change the single-state example are given at the top of the file “runExamples.m”. The saved state selection of California (“state=1”) is consistent with all results presented in the manuscript.    Plots make use of files from the following sources, with some modifications: Holger Hoffmann (2022). Violin Plot (https://www.mathworks.com/matlabcentral/fileexchange/45134-violin-plot); Evan (2022). Plot Groups of Stacked Bars (https://www.mathworks.com/matlabcentral/fileexchange/32884-plot-groups-of-stacked-bars); John Onofrey (2022). Shaded Plots and Statistical Distribution Visualizations (https://www.mathworks.com/matlabcentral/fileexchange/69203-shaded-plots-and-statistical-distribution-visualizations)

opencc-by-4.0Apr 2022View details →

Real-time Alignments for Predicting Decision-Making Time for Diagnostics over NGS Cycles

Input datasets for an interpretable learning approach to predict decision-making time for diagnostics over NGS cycles. The dataset contains alignment files of two clinical sputum samples sequenced with an Illumina MiSeq sequencing device, and following a real-time sequencing protocol. The datasets consist of real-time alignment files for specific sequencing cycle intervals. The alignment has been performed to a database of respiratory microbes. Data preprocessing, including the removal of human host DNA, is integrated into the real-time alignment approach that has been applied to generate the alignments.

opencc-by-4.0Mar 2023View details →

High-rate GNSS Raw Doppler Positive Impact on Cascading Filter-based Approach for Improving Real-time Transient Coseismic Velocities Modeling

The high-rate GNSS average and instantaneous coseismic velocity waveforms for the 2016 Mw 6.6 Norcia earthquake and the 2011 Mw 9.1 Tohoku earthquake are included in this repository.

opencc-by-4.0Mar 2023View details →

Real-time frequency estimation of a qubit without single-shot-readout

Dataset for figures 3a, 3b and 4b in our manuscript.

opencc-by-4.0Oct 2022View details →

Effect of magnetic configuration on real-time wall conditioning in DIII-D

Using EMC3-EIRENE modeling, the impact of parallel impurity forces on the edge transport of injected material and ionized impurities, including scrape-off layer (SOL) main ion flows, has been investigated. The study involved comparing impurity powder injections in different divertor configurations, namely DIII-D lower single null, upper single null, and double null configurations, with plasma edge transport and dust migration and ablation modeling. The injections, which were in powder and granular form, were conducted for real-time wall conditioning, ELM control, and divertor power exhaust at DIII-D [1]. Divertor configuration changes resulted in a redirection of SOL flows, which affected the conditioning of plasma-facing components on either the low field side or the high field side. Moreover, the injection location's poloidal shifts could modify the injected materials' penetration depths and trajectories in the plasma boundary. These changes had an impact on the local deposition of materials on plasma-facing components, which is essential for active conditioning and replenishment of functional coatings in future long-pulse scenarios. [1] F. Effenberg et al 2022 Nucl. Fusion 62 106015 DOI 10.1088/1741-4326/ac899d

opencc-by-4.0Jul 2023View details →

Incorporating real-time traffic data into air quality mapping uncovers more severe exposure disparities at the community level

Data and codes for the XGBoost model training in our manuscript titled "Incorporating real-time traffic data into air quality mapping uncovers more severe exposure disparities at the community level"

opencc-by-4.0Aug 2023View details →

Machine Learning Integrated High Quantum Yield Blue Light Carbon Dots for Real-time and On-site Detection of Cr(VI) in Groundwater and Drinking Water

RGB和Kmeans提取后含有Cr(VI)水样的图像数据

opencc-by-4.0Oct 2023View details →

Datasets and code for "Multi-site transfer function approach for real-time modeling of the ground electric field induced by laterally-nonuniform ionospheric source" by Kruglyakov et al. (2023)

<ol> <li>Archive calculate_weights_for_rt.tgz contains the code for calculation of weights used for computation of electric fields based on multi-site transfer function approach following Kruglyakov et al. (2023). The code is written in Fortran 2003 and the only external dependency is LAPACK/BLAS -compatible library, for example OpenBLAS from https://www.openblas.net. See READ.ME for details.</li> <li>Files GICs*.dat contain observed and modelled geomagnetically induced currents (GICs) at Mäntsälä compressor station in southern Finland (60.6 N, 25.2 E) (https://space.fmi.fi/gic/) for three events (in 2000, 2001, and 2003).</li> <li>Files E_x*. E_y* contain corresponding components of measured (detrended and downsampled from 1s to 10s) and modeled electric fields at sites M02 and M05 from 05:15 to 06:15 UT, 11 Sep 2005.</li> <li>Files MS_TF*.dat contain multi-site transfer functions for different sets of IMAGE magnetometers (based on the data availability during the simulated events) in the frequency domain and the corresponding weights for calculation of electric field in the time domain.</li> <li>File E_to_GICs_W.dat contains coefficients for computation of GICs at Mäntsälä station from electric fields at 18 sites used in the simulation. See Equation (15) of Kruglyakov et al. (2023) for details.</li> </ol>

opencc-by-4.0Oct 2023View details →

Real-Time Delphi data: How to identify and interpret weak signals of change in the forest bioeconomy

Data from: Mauno, T., Catelo, F., Bengston, D.N., Pykäläinen, J. & Hujala, T. 2023. How to identify and interpret weak signals of change in the forest bioeconomy. Forest Policy and Economics. <a href="https://doi.org/10.1016/j.forpol.2023.103075?_gl=1*a2eeob*_ga*NDE0MDgzOTYwLjE2OTY0ODY2MTY.*_ga_NY8L5SJPMB*MTY5NjQ5NDIxNi4yLjEuMTY5NjUwMTI0Mi4wLjAuMA..">https://doi.org/10.1016/j.forpol.2023.103075</a> This exploratory study sought to understand how to identify and interpret weak signals of change that may have an impact on the forest bioeconomy. An international panel of experts in the forest bioeconomy and in foresight provided their views through a two-stage Real-Time Delphi method which utilized the multiple rounds of traditional Delphi and the instantaneous feedback of the Real-Time Delphi method. The Real-Time Delphi exercise was conducted in two stages through the eDelphi software (edelphi.org); the first stage was focused on Changes and the second on Weak Signals. For the Real-Time Delphi exercise, two expert matrices (forest bioeconomy matrix and futures & foresight matrix) were prepared with the aim of obtaining diverse expertise to participate in the study. The first stage was conducted during a 10-day period in early September 2022 (Sep 5, 2022 – Sep 14, 2022). The second stage was also conducted during a 10-day period later in September 2022 (Sep 21, 2022 – Sep 30, 2022). A total of 11 (6 forest bioeconomy experts and 5 futures research and foresight specialists) participated in both eDelphi stages. This dataset includes: (i) completed Real-Time Delphi stages (including anonymized answers and discussions of 11 participants) (ii) questions for both Real-Time Delphi stages, and (iii) anonymized expert matrices (forest bioeconomy matrix and futures & foresight matrix) For more information, please contact the corresponding author (data controller): Tuomas Mauno (University of Eastern Finland), tuomas.mauno@uef.fi

Cognitive Behavioral Therapy and Real-Time Pain Management Intervention for Sickle Cell Via Mobile Applications

ClinicalTrials.gov study NCT04419168. IPD Sharing: NO. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →

Automated Real-time Feedback on CPR Study

ClinicalTrials.gov study NCT00539539. IPD Sharing: Not stated. Countries: 2. Publications: 1.

Improving Spine Surgical Care With Real-Time Objective Patient Tracking Using the Apple Watch

ClinicalTrials.gov study NCT04379921. IPD Sharing: NO. Countries: 1. Publications: 15.

controlledIPD-YESFeb 2026View details →

Real-time Effort Driven VENTilator Management

ClinicalTrials.gov study NCT03266016. IPD Sharing: YES. Countries: 1. Publications: 7.

Reliability and Acceptability of Real-time Virtual Video Pediatric Gait, Arms, Legs and Spine (V-pGALS)

ClinicalTrials.gov study NCT04668820. IPD Sharing: NO. Countries: 1. Publications: 4.

Diabetes Education With Real-time Continuous Glucose Monitoring

ClinicalTrials.gov study NCT05394844. IPD Sharing: NO. Countries: 1. Publications: 1.

Real-time Lymphatic Channel Visualization Improves Bilateral Sentinel Lymph Node Detection in Endometrial Cancer

ClinicalTrials.gov study NCT05191212. IPD Sharing: NO. Countries: 1. Publications: 3.