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10,006 results for “randomness”
Random cohesion field
<p>This file contains a 2D random cohesion field used that can be used as an initial condition for the simulation of shear banding.</p>
Observation of entanglement transition of pseudo-random mixed states
<p>Experimental data in the manuscript "Observation of entanglement transition of pseudo-random mixed states".</p>
Angular distribution of photodesorbed gas from random sphere packings
<p>This folder contains output obtained by simulating trajectories of photodesorbed trace particles in computer-generated random sphere packings.<br> This initial direction of photodesorbed gas, described here as a function of solar incidence angle of a surface element of regolith, <br> is expected to enable higher-fidelity models of surface-bounded exospheres in the solar system (e.g., Moon, Mercury, and other "airless" bodies covered by regolith), where, because of the lack of collisions in vacuum, it is important to accurately prescribe the exit angle distribution of gas from regolith. </p>
Random Numbers / Zufallszahlen
<p>List with <strong>500 random numbers</strong> (<strong>Zufallszahlen</strong>) from 0 to 9. Each number has the same probability to appear.</p> <p>The list with the random numbers can be used to make a random group selection, especially important in RCT-trials. </p>
Effectiveness of Using 2D Atlas and 3D PDF as a Teaching Tool in Anatomy Lectures in Initial Learner Medical Students: A Randomized Controlled Trial
<p><strong>Dataset Info</strong></p> <p><strong>1) Immediate Test</strong></p> <p># The first row of the dataset identifies the columns.<br> # The first column represents the participant ids.<br> # The second column represents the participants' assigned group.<br> # The third column represents represents the genders of participants (1: Female, 2: Male)<br> # The fourth column represents the years of participants' in their six-year-long medical schools (1: Year-1 students, 2: Year-2 students).<br> # The fifth column represents participants' repeating year status. (0: No, 1: Yes)<br> # The sixth to the fifteenth columns (liver_q1_max2points to liver_q10_max2points) represent the scores in the first to tenth questions of the liver test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The sixteenth column (livertotalscore_max20points) represents the total score in the liver test.<br> # The seventeenth to the thirty fifth columns (genitalia_q1_max3points to genitalia_q19_max2points) represent the scores in the first to nineteenth questions of the genitalia test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The thirty sixth column (genitaliatotalscore_max40points) represents the total score in the genitalia test.</p> <p> </p> <p><strong>2) Delayed Test</strong></p> <p># The first row of the dataset identifies the columns.<br> # The first column represents the participant ids.<br> # The second column represents the participants' assigned group.<br> # The third column represents represents the genders of participants (1: Female, 2: Male)<br> # The fourth column represents the years of participants' in their six-year-long medical schools (1: Year-1 students, 2: Year-2 students).<br> # The fifth column represents participants' repeating year status. (0: No, 1: Yes)<br> # The sixth to the fifteenth columns (liver_q1_max2points to liver_q10_max2points) represent the scores in the first to tenth questions of the liver test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The sixteenth column (livertotalscore_max20points) represents the total score in the liver test.<br> # The seventeenth to the thirty fifth columns (genitalia_q1_max3points to genitalia_q19_max2points) represent the scores in the first to nineteenth questions of the genitalia test. Maximum points of the questions can be seen on the first row of the relevant column.<br> # The thirty sixth column (genitaliatotalscore_max40points) represents the total score in the genitalia test.</p>
Data for "Randomness in Local Optima Network Sampling" (GECCO Companion Proceedings, 2023)
<p>Data for "Randomness in Local Optima Network Sampling" (GECCO Companion Proceedings, 2023)</p>
Random Filter Mappings as Optimization Problem Feature Extractors
<p>Artifacts produced as part of the paper Random Filter Mappings as Optimization Problem Feature Extractors</p>
Safety and immunogenicity of heterologous booster immunization with Ad5-nCoV after three-dose priming with inactivated SARS-CoV-2 vaccine in Chinese adults: a randomized, double-blind, parallel-controlled trial
<p>Data on safety and immunity of heterologous booster (fourth dose) after three-dose priming with inactivated SARS-CoV-2 vaccine are limited in Chinese adults. Here, we evaluate the safety and immunogenicity of immunization with Ad5-nCoV in a randomized, double-blind, parallel-controlled phase 4 clinical trial in Zhejiang, China (NCT05373030). Participants aged 18-80 years (100 participants per group) who have administered three doses of inactivated SARS-CoV-2 vaccine ≥ 6-month earlier were enrolled and randomized at 1:1 into two groups, then administered intramuscular Ad5-nCoV or different inactivated SARS-CoV-2 vaccine (CoronaVac or Covilo) respectively. All observed adverse reactions were predictable and manageable. Ad5-nCoV elicited significantly higher RBD-specific IgG levels, with a GMC of 2924.0 on day 14 post-booster, 7.8-fold that of the inactivated vaccine. Pseudovirus-neutralizing antibodies to Omicron BA.4/5 showed a similar pattern, with GMT of 228.9 in the Ad5-nCoV group and 65.5 in the inactivated vaccine group. The Ad5-nCoV booster-maintained a high antibody levels on day 90, with seroconversion of 71.4%, while the inactivated vaccine group was 5.2%, closed to pre-booster levels. In summary, a fourth Ad5-nCoV vaccination following three-dose inactivated SARS-CoV-2 vaccination is immunogenic, tolerable, and more efficient than inactivated SARS-CoV-2 vaccine. Ad5-nCoV elicits a stronger humoral response against Omicron BA.4/5 and maintains antibody levels for longer than homologous boosting.</p>
Random bitstring generated by using quantum-dot based RNG
<p>Random bitstring used in the manuscript of "Randomnhess enhancement is a quantum dot-based quantum random number generator by corrector functions"</p>
Predicting species richness and diversity using satellite remote sensing and random forest machine learning algorithm
<p><strong>Aims</strong>: Remote sensing approaches could be beneficial for monitoring and compiling essential biodiversity data because it is cost-effective and allows for coverage of large areas over a short period. This study investigated the relationship between multispectral remote sensing data from Landsat 8 and Sentinel 2 and species richness and diversity in mountainous and protected grasslands.</p> <p><strong>Locations</strong>: Golden Gate Highlands National Park, Free State, South Africa. </p> <p><strong>Methods</strong>: In-situ data of plant species composition and cover from 142 plots with 16 releves each were distributed across the study site and used to calculate species richness and Shannon-wiener species diversity index (species diversity. We used a machine-learning random forest algorithm to optimise the prediction of species richness and diversity. The algorithm was used to identify the optimal spectral bands and vegetation indices for estimating species richness and diversity. Subsequently, the selected bands and vegetation indices were used to estimate species richness through random forest regression. </p> <p><strong>Results</strong>: This research found weak relationships between remote sensing vegetation indices and the diversity metrics, but significant relationships were found between some spectral bands and diversity metrics. Moreover, using machine learning random forest, the multispectral datasets exhibited strong predictive powers. In this investigation, for both sensors, near-infrared (NIR) seemed to be the most selected band to explain species diversity in mountainous grasslands.</p> <p><strong>Main</strong> <strong>conclusions</strong>: This finding further ascertains the efficiency of using NIR in vegetation mapping. This research shows that NIR, SAVI and EVI are the most adequate for predicting species richness and diversity in mountainous grasslands with relatively good accuracies.</p>
Data from: Identifying and overcoming breastfeeding challenges using two-way short message service, a randomized controlled trial
<p>Breastfeeding challenges, such as pain and perception of insufficient milk supply, prevent many women from exclusively breastfeeding their babies for the six-month duration recommended by the World Health Organization. Mobile health strategies may help women identify and overcome breastfeeding challenges. This study evaluated a two-way short message service (SMS) intervention that delivered breastfeeding messages to women in Kiambu County, Kenya, and its impact on rates of exclusive breastfeeding and breastfeeding behavior at 1, 4, and 6 months post-delivery. Women in the control group received a general package of messages containing postnatal information; women in the intervention group received these messages, plus messages related to breastfeeding and surveys which offered more information about breastfeeding challenges. Both groups of women had access to a help desk agent who responded to questions via SMS.</p> <p>There was no significant difference in the rate of exclusive breastfeeding between the intervention and control at any time point (p=.861). Women in the intervention group were more likely to report experiencing breastfeeding challenges such as pain and perceived insufficient milk supply than those in the control group (32% vs. 24%, p=0.00). Of the women in the intervention group who reported experiencing breastfeeding challenges, 70% of them found a resolution to their challenge, and 23% of them resolved their challenges using SMS. SMS may help women in low-resource settings to identify and overcome their breastfeeding challenges.</p>
Randomly stacked open cylindrical shells as functional mechanical energy absorber
<p>Experimental and simulation data for the paper entitled <em>Randomly stacked open cylindrical shells as functional mechanical energy absorber. </em></p> <p>Download and unzip the AllFigureData.zip. </p> <p>Contact</p> <p>Experiments: sano@mech.keio.ac.jp</p> <p>Simulations: florence.bertails@inria.fr</p>
Output - Results of Random Forest and Multiple Linear regression analysis.
<p><strong>Hybrid streamflow modelling using machine learning and multi-model combination.</strong></p> <p> </p> <p><strong>Structure:</strong></p> <p><strong>MLR_output:</strong></p> <ul> <li>Validate <ul> <li>Different setups</li> </ul> </li> </ul> <p><strong>RF_output:</strong></p> <ul> <li>tune <ul> <li><em>all_stations</em></li> </ul> </li> <li>train <ul> <li><em>Different setups</em></li> </ul> </li> <li>Validate <ul> <li><em>Different setups</em></li> </ul> </li> </ul>
Leukocyte- and Platelet-Rich Fibrin in endoscopic endonasal skull base reconstruction: study protocol for a multicenter prospective, parallel-group, single-blinded randomized controlled non-inferiority trial.
<p>Instruction video on how to prepare Leukocyte- and Platelet-Rich Fibrin for endoscopic endonasal skull base reconstruction reinforcement. </p>
Dataset: Harmonic Integration via Randomized Kaczmarz Algorithms
<p>The dataset used for the analyses in our paper: "<a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4365845">On the Conjugate Symmetry and Sparsity of the Harmonic Decomposition of Parametric Surfaces with the Randomised Kaczmarz Method</a>".</p> <p>The codes are available on our <a href="https://github.com/eesd-epfl/harmonic-integration-via-kaczmarz">EESD GitHub webpage</a>.</p> <p>The attached files are all MAT files (Matlab 7.0). These files will be read and processed directly with our Python3.8 codes. The codes that generated these input data are referred to in our paper (via Spherical harmonics, spherical cap harmonics, and disk harmonics approaches).</p>
Presence of perennial halophilous scrubs in 2016 in the former saltworks of Salins de Giraud, random forest classification on WV2
<p>The presence of perennial halophilous scrubs (<em>S. fruticosa</em> and <em>A. macrostachyum</em>) was mapped using a Worldview 2 (WV2) very-high resolution imagery acquired the 31st of August 2016, strictly cloudless. Multispectral indices, among the most used, were adapted to the bands of WV2. The Random Forest model (RF) package into the R software was used to perform image classification. RF OBB and omission errors for the class “presence” and the class “absence” were less important when the classification was done for each species individually, hence this raster is a combination of both classifications. The OBB error for <em>S.fruticosa</em> is 1.43% and for <em>A. macrostachyum</em> is 2.18%.</p>
Single-Scattering property database of randomly oriented very complex ice crystals in the microwave
<p>A database consisting of the single-scattering properties of budding rosette aggregates and rosette aggregates calculated at frequencies in the mm-wave and sub-mm-wave regions of the electromagnetic spectrum. The full set of single-scattering properties have been made available at the temperatures of -83 degree C, -43 degree C, and -3 degree C at the frequencies of 50, 183 and 243 GHz. Other frequencies will become available once completed in the sub-mm-wave region of the spectrum. The maximum dimensions of the ice crystals vary between 10 and 10,000 microns. The accompanying data is made available under the terms of the Non-Commercial Government License https://www.nationalarchives.gov.uk/doc/non-commercial-<br> government-licence/version/2/</p>
Inflammatory and metabolic biomarker assessment in a randomized presurgical trial of curcumin and anthocyanin supplements in patients with colorectal adenomas
<p>Supplementary Figures of the manuscript entitled: Inflammatory and metabolic biomarker assessment in a randomized presurgical trial of curcumin and anthocyanin supplements in patients with colorectal adenomas.</p> <p>Supplementary Figure S1. Univariate analysis of IL-10 changes by BMI</p> <p>Supplementary Figure S2. Univariate analysis of leptin changes by dietary anthocyanin intake</p> <p>Supplementary Figure S3. Mixed models analysis of post-intervention IGFBP-3 by colorectal cancer family history</p> <p>Supplementary Figure S4. Mixed models analysis of adiponectin by treatment arm</p>
Effect of hyperparameters on variable selection in random forests
<p>These are data used to generate the results presented in simulation studies conducted in Fouodo et al. 2023. Each dataset is an R object in RDS format with 100 lists. For each element of the list, parameters used to generate the data are presented, followed by the simulated data. <a href="https://github.com/imbs-hl/RF-hyperparameters-and-variable-selection">Here</a> is the git repository of the R code used to conduct simulations in the manuscript. The files <a href="https://github.com/imbs-hl/RF-hyperparameters-and-variable-selection/tree/main/R-code/01-scenario1">01-data-only.R</a> and <a href="https://github.com/imbs-hl/RF-hyperparameters-and-variable-selection/tree/main/R-code/02-scenario2">02-data-only.R</a> contain the functions and more details about how the data have been simulated for studies 1 and 2.</p>
CONSORT Checklist for The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by clinical pharmacist: A Randomized Clinical Trial
<p>CONSORT Checklist for The assessment of educational and supportive care to the infertile females undergoes In Vitro Fertilization procedure by clinical pharmacist: A Randomized Clinical Trial</p>
ScienceDex guides
Understand access before you commit
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.