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10,006 results for “randomness”
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I was boried ok don't judge me if its terrible. Source: Objaverse 1.0 / Sketchfab
A novel thermal compression device for perioperative warming: A randomized trial for safety and efficacy - dataset
<p>Data set for <strong>A novel thermal compression device for perioperative warming: A randomized trial for safety and efficacy </strong></p>
Behavioural Weight Loss Treatment Plus Motivational Interviewing versus Attention Control: A Randomized Controlled Trial
<p>Studies evaluating the benefit of adding motivational interviewing (MI) to behavioural weight loss programs (BWLPs) have yielded mixed findings. The aims of this randomized controlled trial were to: (1) assess the efficacy of adding MI to a BWLP on weight loss and adherence among 135 overweight and obese individuals (77.8% female; mean BMI = 33.6 kg/m<sup>2</sup>) enrolled in a 12-week BWLP, and (2) explore levels of importance, confidence, and readiness for change ratings. Participants, who were randomized to receive 2 MI sessions or 2 attention control sessions, were assessed at baseline, end of BWLP, and 6 months post-BWLP. Both groups decreased their weight from baseline to end of the BWLP; however, there was no weight change from baseline to 6 months post-BWLP in either group. We observed no group differences in importance, confidence, and readiness for change after each session. Participants may not have benefited from MI because they were already highly motivated to change. These findings suggest that pre-treatment assessment and treatment monitoring may help enhance MI+BWLP efficacy by guiding a stepped-care approach that identifies individuals for whom additional MI sessions are needed, and when. A focus on refining elements of treatment remains an important direction for effective obesity treatment.</p>
fire-randomizer: first release
<p>Tool to assess fire selectivity with Monte Carlo simulations.</p>
some random stuff
<p>random tests</p>
Spectral Ergodicity in Deep Learning Architectures via Surrogate Random Matrices
<p>The new methodology combines approaches inspired from the Thirumalai-Mountain (TM) metric and<br> metric rooted in Kullbach-Leibler (KL) divergence. The method is applied to a general study of<br> deep and recurrent neural networks via the analysis of random matrix ensembles mimicking typical<br> weight matrices of those systems. In particular, we examine different size circular random matrix<br> ensembles: circular unitary ensemble (CUE), circular orthogonal ensemble (COE), and circular<br> symplectic ensemble (CSE). Eigenvalue spectra and spectral ergodicity are computed for those<br> ensembles as a function of connectivity in the system. The dataset and Python notebook are provided.</p>
Learning topological states from randomized measurements using variational tensor network tomography
<p>Dataset for paper <strong>Learning topological states from randomized measurements using variational tensor network tomography.</strong><br>The numerical code can be found at the repo: https://github.com/teng10/tn-shadow-qst</p>
Dataset and additional info for "Serious adverse events of special interest following mRNA vaccination in randomized trials" (Fraiman et al. 2022)
<p>Dataset for:</p> <p>Fraiman J, Erviti J, Jones M, Greenland S, Whelan P, Kaplan RM, Doshi P. Serious adverse events of special interest following mRNA COVID-19 vaccination in randomized trials in adults. Vaccine. 2022 Aug 30;40(40):5798–805. doi: 10.1016/j.vaccine.2022.08.036. Epub ahead of print. PMID: 36055877; PMCID: PMC9428332. <a href="https://doi.org/10.1016/j.vaccine.2022.08.036">https://doi.org/10.1016/j.vaccine.2022.08.036</a> </p>
Random Woody Crown Network (WCN) from 1 to 248 nodes
<p>Those woody crown networks are part of data of manuscript to consider publication </p>
Data of decomposition, topology, and the corresponding graphs of Random Woody Crown Networks with size from 10 to 248 nodes
<p>Data of decomposition, topology and the corresponding graphs of Random Woody Crown Networks with size from 10 to 248 nodes</p>
Dataset for Ha and Aylward 'Automated classification of giant virus genomes using a random forest model built on trademark protein families'
<ul><li>Genome sets used for model training and testing</li><li>Custom Python script that generated fragmented genomes at random completeness levels</li></ul>
HRFMD (Hydrological model based Random Forest Model Diagnostics) results
<p>Results accompanying the publication titled: Advancing Hydrological Model Diagnostics: An Exploratory Approach Using Random Forest Models and Large-sample Catchment Dataset</p>
A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest
<p>Code to reproduce the work in the manuscript ' A Grid Model for Vertical Correction of Precipitable Water Vapor over the Chinese Mainland and Surrounding Areas Using Random Forest', Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, Feijuan Li, submitted to GMD.</p>
Impact of Probiotic Veillonella atypica FB0054 Supplementation on Anaerobic Capacity and Lactate Changes: A Randomized, Crossover Pilot
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Therapeutic Evaluation of Bifidobacterium animalis subsp. lac-tis MH-02, as an Adjunctive Treatment in Patients with Reflux Esophagitis: A Randomized, Double-Blind, Placebo-Controlled Trial
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A mode-locked random laser generating transform-limited optical pulses
<p>Ever since the mid-1960's, locking the phases of modes enabled the generation of laser pulses of duration limited only by the uncertainty principle, opening the field of ultrafast science. In contrast to conventional lasers, mode spacing in random lasers is ill-defined because optical feedback comes from scattering centres at random positions, making it hard to use mode locking in transform limited pulse generation. Here the generation of sub-nanosecond transform-limited pulses from a mode-locked random fibre laser is reported. Rayleigh backscattering from decimetre-long sections of telecom fibre serves as laser feedback, providing narrow spectral selectivity to the Fourier limit. The laser is adjustable in pulse duration (0.34-20 ns), repetition rate (0.714-1.22 MHz) and can be temperature tuned. The high spectral-efficiency pulses are applied in distributed temperature sensing with 9.0 cm and 3.3×10⁻³ K resolution, exemplifying how the results can drive advances in the fields of spectroscopy, telecommunications, and sensing.</p>
Random Sampling with prior-based estimation of IE selection 30_270
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Random Sampling with prior-based estimation of BME selection 30_270
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Random lasing data for HNTs-RhB composites
<p>Here, natural HNTs with different lengths and diameters have been employed as passive scatterers for the generation of random laser (RL) emission from rhodamine B (RhB) in a colloidal phase. Upon pumping at 532 nm, mixed HNT-RhB disordered colloidal systems are shown to yield orange RL emission with a linewidth as small as ∼4 nm. Moreover, a statistical analysis of shot-to-shot correlations among RL modes reveals an obvious photonic paramagnetic to spin-glass transition with increasing pump energy, which is a unique statistical fingerprint of RL. Interestingly, besides acting as scatterers, the HNTs are also found to improve the photostability of RhB molecules. Indeed, HNTs help to better dissipate the excess energy deposited in the gain medium, thus protecting the dye from photodegradation and facilitating the achievement of RL. The results contribute to the theoretical understanding and technical development of low-cost RL devices based on widely available sources in view of multiple prospective applications in photonics.</p>
Dataset of Random Reordered Encodings of Parity Problems
<p>Dataset created and used for the paper:</p> <p><em>Hardness of Random Reordered Encodings of Parity for Resolution and CDCL</em>, Leroy Chew, Alexis de Colnet, Friedrich Slivovsky and Stefan Szeider, AAAI 2023</p> <p>report.rmd is an R Markdown file that can be opened in RStudio and used to generate the figures in the submission</p> <p>_stats file: lists the permutations used<br>.cnf file: DIMACS representation of unsat formulas<br>.gr : DIMACS representation of the Tseitin graph<br>.edges: alternative representation of the Tseitin graph<br>_half: DIMACS representation of the Tseitin graph for G*</p> <p>n: number of input variables<br>p: probability of selection for each variable<br>s: random seed used<br>m: mode number used<br> 0 : uniformly random<br> 1: Mallows(n,q), q= (1/n)^(1/(k*k))<br> 3: performs k number of random adjacent swaps to make the permutation<br> 4: performs 10000000 potential random adjacent swaps but forbids the distance being >k<br> 5: uniformly but rerolls until the maximum permutation distance is k<br> 6: 3 parity constraints<br>k: integer parameter for mode</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.