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10,006 results for “randomness”
Research integrity assessment for randomized controlled trials in systematic reviews
<p>A tool to assess the integrity of research reported in randomized controlled trials (RCTs) of investigational medicinal products. The assessment uses signalling questions to identify problematic RCTs and is used when studies are being considered for inclusion into systematic reviews.</p> <p>RCTs with red flags regarding research integrity should be excluded and RCTs with open questions should be held in awaiting classification until clarified.</p> <p>The results of the research integrity assessment should be transparently reported and published together with the systematic review.</p> <p> </p>
Single-incision laparoscopic cholecystectomy versus conventional multi-port laparoscopic cholecystectomy: A systematic review, meta-analysis, and meta-regression of randomized controlled trials
<p>Single-incision laparoscopic cholecystectomy versus conventional multi-port laparoscopic cholecystectomy: A systematic review, meta-analysis, and meta-regression of randomized controlled trials</p>
''Eight-year efficacy update of the HOBOE randomized phase 3 trial in premenopausal patients with hormone-receptor positive early breast cancer comparing triptorelin plus either Tamoxifen or Letrozole or Zoledronic acid + Letrozole'' - dataset
<p>Dataset for analysis of the manuscript ''Eight-year efficacy update of the HOBOE randomized phase 3 trial in premenopausal patients with hormone-receptor positive early breast cancer comparing triptorelin plus either Tamoxifen or Letrozole or Zoledronic acid + Letrozole''</p>
Nest shape influences colony organization in ants: spatial distribution and connectedness of colony members differs from that predicted by random movement and is affected by nest space
<p><strong>Overview</strong></p> <p>Data used for the manuscript: Nest shape influences colony organization in ants: spatial distribution and connectedness of colony members differs from that predicted by random movement and is affected by available space</p> <p><strong>Purpose of the study</strong></p> <p>Investigating how nest shape influences how <em>Temnothorax rugatulus</em> colonies spatially organize in their nests. This includes physical location of colony members and their distances from the entrance, mobile colony member distance to the brood center, worker distance to the physical center of the nest, and comparing worker distributions with those predicted by a random walk model.</p> <p><strong>Structure of the data</strong></p> <p>EMPIRICAL DATA</p> <p>WORKERS: FullDataCoordWorkers.csv, FullDataCoordWorkersRD2.csv</p> <p>Raw experimental data with worker x and y position in nests</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Day: The experimental day that the observation was collected on</li> <li>ScaledX: X-axis coordinate, scaled from original (px) to (cm) in the software Fiji (Schindelin et al., 2012)</li> <li>ScaledY: Y-axis coordinate, scaled from original (px) to (cm) in the software Fiji</li> <li>ColorID: The unique color marking assigned to an individual worker's head, thorax, abdomen1, abdomen2 (i.e., Yellow, White, Green, Green = Y,W,G,G)</li> <li>Density: The density treatment (High / Low)</li> </ul> <p>BROOD / QUEENS: FullDataCoordBrood.csv, FullDataCoordBroodRD2.csv; FullDataCoordQueen.csv, FullDataCoordQueenRD2.csv</p> <p>Raw experimental data with brood (OR) queen x and y position in nests</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Day: The experimental day that the observation was collected on</li> <li>ScaledX: X-axis coordinate, scaled from original (px) to (cm) in the software Fiji (Schindelin et al., 2012)</li> <li>ScaledY: Y-axis coordinate, scaled from original (px) to (cm) in the software Fiji</li> <li>Density: The density treatment (High / Low)</li> </ul> <p>ALATES: FullDataCoordAlate.csv</p> <p>Raw experimental data with alate (winged reproductive individuals) x and y position in nests</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Day: The experimental day that the observation was collected on</li> <li>ScaledX: X-axis coordinate, scaled from original (px) to (cm) in the software Fiji (Schindelin et al., 2012)</li> <li>ScaledY: Y-axis coordinate, scaled from original (px) to (cm) in the software Fiji</li> <li>SexID: The unique sex assignment and number given to an individual alate: Sex, SexNumber, TotalNumber (i.e., the first male alate observation that came after three queen alates making it the fourth total observation = M,1,4)</li> </ul> <p>NETLOGO SIMULATIONS: ArchitectureMoveModelFull.csv</p> <p>Raw netlogo simulation data with agent x and y positions in nests</p> <ul> <li>RunNumber: The simulation number - 1 to 4000 - there are 1000 simulations for each combination of nest shape and size</li> <li>NestSize: The size of the nest area that agents were allowed to move throughout (Small / Large)</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>TimeStep: The duration of each simulation (should be 50000)</li> <li>xcor: a list of every agent x coordinate position at the end of the simulation</li> <li>ycor: a list of every agent y coordinate position at the end of the simulation</li> </ul> <p>REFERENCE DATA </p> <p>NEST BINS: Empirical</p> <p>BinsNullFull.csv</p> <p>Null data sheet with eight bins for tube and circle nests in every colony</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Bin: Nest section identifier (1-8)</li> </ul> <p>BinCoordFull.csv</p> <p>Reference binning coordinates to group empirical coordinates into nest sections</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>CoordID: The unique coordinate identifier within each colony and nest combination</li> <li>ScaledX: X-axis coordinate, scaled from original (px) to (cm) in the software Fiji (Schindelin et al., 2012)</li> <li>ScaledY: Y-axis coordinate, scaled from original (px) to (cm) in the software Fiji</li> </ul> <p>NEST BINS: Netlogo Simulations</p> <p>BinsNullNetlogo.csv</p> <p>Null data sheet with eight bins for tube and circle nests in each simulation treatment</p> <ul> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>NestSize: The size treatment for simulations (Small / Large)</li> <li>Bin: Nest section identifier (1-8)</li> </ul> <p>BinCoordNetlogo.csv</p> <p>Reference binning coordinates to group Netlogo simulation coordinates into nest sections</p> <ul> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>NestSize: The size treatment for simulations (Small / Large)</li> <li>ScaledX: X-axis coordinate</li> <li>ScaledY: Y-axis coordinate</li> <li>CoordID: The unique coordinate identifier within each colony and nest combination</li> </ul> <p>CORNERS: Empirical</p> <p>CornerFull.csv</p> <p>Whether a nest section has a corner or not</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Bin: Nest section identifier (1-8)</li> <li>Corner: Presence of a corner (Y / N)</li> </ul> <p>CORNERS: Empirical</p> <p>CornerFullSim.csv</p> <ul> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Bin: Nest section identifier (1-8)</li> <li>Corner: Presence of a corner (Y / N)</li> </ul> <p>REFERENCE DATA </p> <p>DISTANCES IN THE NEST: Empirical</p> <p>DistBinsFull.csv</p> <p>Reference coordinates for the entrance of nest sections (Bin) front-to-back and shortest distance to the entrance from each nest section entrance</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Distance: Reference shortest distance from a nest section to the entrance</li> <li>Bin: Nest section identifier (1-8)</li> <li>BinX: X-axis reference coodinate for a nest section entrance</li> <li>BinY: Y-axis reference coodinate for a nest section entrance</li> <li>Xmax: Max X-axis coordinate possible within the nest</li> <li>Ymax: Max Y-axis coordinate possible within the nest</li> <li>MaxDist: Max possible shortest distance from the nest entrance</li> <li>TubeRatio: Ratio of shortest distance to the nest entrance in circle nest / tube nest</li> </ul> <p>DISTANCES IN THE NEST: Netlogo Simulations</p> <p>DistBinsFullNetlogo.csv</p> <p>Reference coordinates for the entrance of nest sections (Bin) front-to-back and shortest distance to the entrance from each nest section entrance</p> <ul> <li>NestSize: The size treatment for simulations (Small / Large)</li> <li>Nest: The nest shape treatment (Tube / Circle)</li> <li>Distance: Reference shortest distance from a nest section to the entrance</li> <li>Bin: Nest section identifier (1-8)</li> <li>BinX: X-axis reference coodinate for a nest section entrance</li> <li>BinY: Y-axis reference coodinate for a nest section entrance</li> <li>Xmax: Max X-axis coordinate possible within the nest</li> <li>Ymax: Max Y-axis coordinate possible within the nest</li> <li>MaxDist: Max possible shortest distance from the nest entrance</li> <li>TubeRatio: Ratio of shortest distance to the nest entrance in circle nest / tube nest</li> </ul> <p>REFERENCE DATA </p> <p>WORKER SITE FIDELITY (SPATIAL FIDELITY & OCCURRENCE ZONE SIZES), ALSO RELATING SIZES TO DISTANCES IN THE NEST</p> <p>ColorRefFull.csv</p> <p>Reference of all possible unique color identifiers paint marked workers</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Head: Head color mark</li> <li>Thorax: Thorax color mark</li> <li>Abd1: Left side abdomen mark</li> <li>Abd2: Right side abdomen mark</li> </ul> <p>NestAreaFull.csv</p> <p>Reference for colony size (number of workers in the colony) and nest area</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Number.ants: Number of workers in the colony after painting</li> <li>Diameter: The diameter of the circle nest</li> <li>Area: The area of the nest</li> </ul> <p>ScalingCircleSFZ.csv</p> <p>Reference to scale the radius of circle nests to make coordinates representing fidelity zone bins</p> <ul> <li>Colony: Unique experimental colony identifiers</li> <li>Scaling: The scaling factor that is applied to the radius of each circle nest</li> </ul>
Data from: Is there a benefit for anesthesiologists of adding difficult airway scenarios for learning fiberoptic intubation skills using virtual reality training? A randomized controlled study
<p><strong><span>Introduction</span></strong><span><strong>:</strong> Fiberoptic intubation for a difficult airway requires significant experience. Traditionally only normal airways were available for high fidelity bronchoscopy simulators. It is not clear if training on difficult airways offers an advantage over training on normal airways. This study investigates the added value of difficult airway scenarios during virtual reality fiberoptic intubation training.</span></p> <p><span><strong>Methods:</strong> </span><span>A prospective multicentric randomized study was conducted 2019 to 2020, among 86 inexperienced anesthesia residents, fellows and staff. Two groups were compared: Group N (control, n=43) first trained on a normal airway and Group D (n=43) first trained on a normal, followed by three difficult airways. All were then tested by comparing their Global Rating Scores (GRS) on 5 scenarios (1 normal and 4 difficult airways).</span></p> <p><span><strong>Results:</strong> </span><span>The final evaluation GRS score for the normal airway testing scenario was significantly higher for group N than group D: median score 76% (IQR 56.5 - 90) versus 58% (IQR 51.5 - 69, p = 0.0039), but there was no difference in GRS scores for the difficult intubation testing scenarios. </span></p> <p><span><strong>Conclusions:</strong> </span><span>A single exposure to each of 3 different difficult airway scenarios did not lead to better fiberoptic intubation skills on previously unseen difficult airways, when compared to multiple exposures to a normal airway scenario. This finding may be due to the learning curve of approximately 5-10 exposures to a specific airway scenario required to reach proficiency. </span></p>
Efficacy of a multiple-component and multifactorial personalized fall prevention program in a mixed population of community-dwelling older adults with stroke, Parkinson's disease, or frailty compared to usual care: The PRE.C.I.S.A. Randomized Controlled Trial
<p>Raw data associated with the scientific publication 'Efficacy of a multiple-component and multifactorial personalized fall prevention program in a mixed population of community-dwelling older adults with stroke, Parkinson’s disease, or frailty compared to usual care: The PRE.C.I.S.A. Randomized Controlled Trial'.</p>
Crack simulations in random heterogeneous media: worm burrows
<p>The folders correspond to the panels of Figure 5 in the referencing paper. The top row of figures are in the kic subfolder, cov_minus, baseline and cov_plus from left to right. The bottom two rows are in the kikic folder cov_minus, baseline and cov_plus from left to right.</p> <p> </p> <p>Data is in the .mat files, each of which contains three variables. x1_path contains the horizontal locations of the crack tip during its propagation and x2 path contains the vertical position.</p> <p> </p> <p>The data can be recreated by executing the .m files in each subfolder, having downloaded and extracted the entire archive. The files are matlab files which must be executed in matlab. </p> <p> </p> <p>The simulation engine is in burrow_prop_03.m</p>
Figure 3 in Density estimations of the Asiatic black bear: application of the random encounter model
Figure 3. Monthly variation in the distance moved as calculated from 1-hour positioning with global positioning system (GPS) collars and estimated via GLMM.
Figure 2 in Density estimations of the Asiatic black bear: application of the random encounter model
Figure 2. Relationship between the fixed interval of the global positioning system (GPS) collar and the distance moved (km/h) as calculated based on the interval.
Figure 1 in Density estimations of the Asiatic black bear: application of the random encounter model
Figure 1. Shirakawa Village, Gifu Prefecture, Japan, where the field study was conducted, including the locations of the sensor cameras.
Figure 4 in Density estimations of the Asiatic black bear: application of the random encounter model
Figure 4. Coefficient of variation of the estimated density and its confidence interval when the number of cameras is varied from 1 to 100. The coefficients of variation are calculated for each session. The black straight line indicates a border at CV = 0.2.
Supplementary data for: Maternal testosterone and offspring birth weight: A Mendelian randomization study
<p><span>Evidence showed maternal androgen levels in both healthy/general population and populations with hyperandrogenic disorders were inversely associated with offspring's birth weight. We aimed to investigate the causal effect of maternal testosterone levels in general population on offspring's birth weight and preterm delivery risk using two-sample Mendelian randomization (MR) method.</span></p> <p><span>We obtained independent genetic instruments from a sex-specific genome wide association study with up to 230,454 females of European descent from UK biobank. Genetic instruments with consistent testosterone effects but no aggregate effect on sex-hormone binding globulin were used to perform the main analysis. Summary-level data of offspring's birth weight with offspring's genotype adjusted was obtained from a study with 210,406 females of European descent. Summary-level data of preterm delivery was obtained from the FinnGen study (6,736 cases and 116,219 controls).</span></p> <p><span>For outcome of offspring's birth weight, the numbers of instruments included in final MR analyses were 123, 128 and 91 respectively. For outcome of preterm delivery, the numbers were 115, 120 and 83 respectively. The present data files show the genetic instruments and their effects on exposures and outcomes. Pleiotropic genetic instruments that excluded in the MR analysis were also provided in the files.</span></p>
Engineering random spin models with atoms in a high-finesse cavity
<p>Data corresponding to the article "Engineering random spin models with atoms in a high-finesse cavity".</p>
case60nordic random power grid dataset
<p>Dataset of randomly generated power grids derived from the case60nordic (also known as nordic32).</p> <p>Data generation script available at : <a href="https://github.com/bdonon/powerdatagen">https://github.com/bdonon/powerdatagen</a></p>
case60nordic random topology power grid dataset
<p>Dataset of randomly generated power grids derived from the case60nordic (also known as nordic32).</p> <p>Random object disconnections.</p> <p>Data generation script available at : <a href="https://github.com/bdonon/powerdatagen">https://github.com/bdonon/powerdatagen</a></p>
Supplemental material for "Statins, type 2 diabetes and body mass index: a univariable and multivariable Mendelian randomization study"
<p>Supplemental material for "Statins, type 2 diabetes and body mass index: a univariable and multivariable Mendelian randomization study" by Guoyi Yang and C Mary Schooling.</p>
Mesh biaxial specimen with random elasticity field
<p>Mesh biaxial specimen with random elasticity field</p>
Genetically predicted lipid traits, diabetes mellitus liability and carotid intima-media thickness in African ancestry individuals: a Mendelian randomization study
<p>Genetic variants used for the analysis of 'Genetically predicted lipid traits, diabetes mellitus liability and carotid intima-media thickness in African ancestry individuals: a Mendelian randomization study'.</p>
Clustering Data for Passive Tracers in Random Velocity Fields
<p>Contains the post-processed model output. All detected clusters from each individual model run used to compile statistics are included as well as python scripts to manipulate cluster objects and create figures.</p>
Random Photogrammetry Test #1
Photogrammetry Test model of Ganesh Idol my family kept in our study... Source: Objaverse 1.0 / Sketchfab
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.