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Mixed Precision Optimization Method acceleration time and numerical simulation results

The stored data are the speedup ratios of the MPFlow method and other acceleration algorithms, as well as the elastic wave response data obtained by numerical simulation using the MPFlow method.

opencc-zeroJul 2024View details →

dryad36/100

Mate-choice copying accelerates species range expansion

Mate-choice copying is a type of social learning in which females can change their mate preference after observing the choice of others. This behaviour can potentially affect population evolution and ecology, namely through increased dispersal and reduced local adaptation. Here, we simulated the effects of mate-choice copying in populations expanding across an environmental gradient to understand whether it can accelerate or retard the expansion process. Two mate-choice copying strategies were used: when females target a single individual, and when females target similar individuals. We also simulated cases where the male trait singled out by females with mate-choice maps perfectly onto their genotype or is influenced by genotype-by-environment interactions. These rules have different effects on the results. When a trait is determined by genotype alone, populations where copier females target all similar males expand faster, and the number of potential copiers increases. However, when preference is determined by genotype-by-environment interactions, populations where copier females target a single male have higher dispersal and also expand faster, but the potential number of copiers decreases. The results show that mate-choice copying can accelerate the expansion process, although its adaptiveness depends on the information animals use in different contexts.

opencc-by-4.0Jul 2024View details →

Data Release for "First joint oscillation analysis of Super-Kamiokande atmospheric and T2K accelerator neutrino data"

This archive contains the electronic version in ROOT and pdf formats of the measurements of oscillation parameters obtained with the analyses from the paper “First joint oscillation analysis of Super-Kamiokande atmospheric and T2K accelerator neutrino data”. It is published in <a href="https://doi.org/10.1103/PhysRevLett.134.011801">Physical Review Letters</a> and is available on the <a href="https://arxiv.org/abs/2405.12488">arXiv:2405.12488 [hep-ex]</a>.  ************************************** ***** Results included in this release ************************************** This release includes the results of the measurements of the different oscillation parameters obtained with the four analyses appearing in the paper. This corresponds to various 1D and 2D DeltaChi^2 and posterior probability maps as well as 2D confidence/credible regions for the parameters sin^2(theta13), sin^2(theta23), dm^2_32/|dm^2_31|, delta_cp, J_cp. The results are separated into different files for the four analyses. Additional details on these analyses can be found below, but two of them use a Bayesian approach (producing posterior probabilities and credible intervals/regions) and two of them follow a frequentist approach (producing  DeltaChi^2 maps and confidence intervals/regions). A tag in the TGraph and histogram names also allow to differentiate the different types of intervals/regions: "cred" for credible interval from the Bayesian analysis, "conf" for confidence interval from the frequentist analysis. The tag “posterior” indicates that the object corresponds to a posterior probability distribution, while “chi2” indicates a DeltaChi^2 one. Results for each mass ordering hypothesis are provided, denoted "NO" for normal ordering and "IO" for inverted ordering. The Bayesian files also include results marginalised over the mass ordering, denoted by the tag "both" in the object names. The frequentist files include results profiled over the mass ordering, indicated by a tag “profMO” in the object names. The Bayesian and frequentist results use different conventions for the mass splitting in the inverted ordering: the Bayesian results are in term of #Deltam^{2}_{32} for both NO and IO, whereas the frequentist results are plotted versus #Deltam^{2}_{32} for the NO, and |#Deltam^{2}_{31}| for the IO.  A constraint on theta13 from reactor experiment measurements is used for all results in this release. It corresponds to the value in the PDG 2019 review: sin^2(2theta_13)=(8.53+-0.27) x 10^{-2}. This is commonly referred to as "the reactor constraint", and a tag “wRC” is included in the name of the different objects as a reminder that it is used for these results. ************************************** ***** Brief descriptions of the four analyses ************************************** Results are provided for the four analyses mentioned in the “Oscillation analysis” part of the paper. They were given names (Bayesian1, Bayesian2, Frequentist1, Frequentist2) based on the statistical approach they follow. The Bayesian analyses are based on the two T2K analyses described in Eur. Phys. J. C 83, 782 (2023), extended to include the Super-Kamiokande atmospheric data, and with modifications to use the model described in the paper to which the present release is attached to. These analyses use Markov Chain Monte Carlo methods to compute marginal likelihoods for the parameter of interests.   For the frequentist analyses, Frequentist1 is a modified version of Bayesian1, optimized for speed to be able to address the computational challenges of producing frequentist results from an ensemble of pseudo-experiments. Frequentist2 is based on the Super-Kamiokande atmospheric analysis described in PTEP 2019, 053F01 (2019), extended to include the T2K data, and also with modifications to follow the model described in the paper. These two analyses compute profile likelihood on a grid of oscillation parameters of interest to produce measurements of these parameters. In terms of the differences between analyses mentioned in the paper, Bayesian2 is the analysis that does a simultaneous fit of the T2K near detector data with the events observed at SK, and the one for which the momentum scale uncertainty is not correlated between the atmospheric and T2K events observed at SK. The three other analyses use a covariance matrix to propagate the constraint on systematic uncertainties from T2K near detector data to the analysis of the events observed at SK, and treat the momentum scale uncertainty as correlated between atmospheric and T2K far detector events. ************************************** ***** Example codes ************************************** Example codes are provided for each of the four analyses, showing how to produce the pdf file from this analysis from the corresponding ROOT file. How to run these example codes is indicated in the comments at the start of each of the example files. ************************************** ***** Objects inside the ROOT files ************************************** The ROOT objects contained inside the files are named first with an identifier of which parameter(s) are being shown, followed by the reactor constraint tag, followed by the mass ordering tag. For the Bayesian results, there is an additional tag to indicate if the results was obtained with a prior probability uniform in deltaCP (“flatdcp”) or uniform in sin(deltaCP) (“flatsindcp”) A glossary is provided at the end of this readme. ************************************** *** 2D regions ************************************** Objects of the form: gr2D_varX_varY_wRC_<NO,IO,both>_<conf,cred><68,90,955,997>(_N) are TGraphs corresponding to the 2D confidence ("conf") or credible ("cred") regions for the 2 variables (varX, varY).  N is the iterator for different TGraphs corresponding to the same region; these occur when confidence regions are discontinuous (for example when deltaCP loops over from +pi to -pi). 68, 90, 955, 997 are the percentage credible/confidence levels. Most of the 2D frequentist regions were computed using the standard DeltaChi^2 values (from the Gaussian case), and therefore have only approximate coverage. However, the {sin^2(theta_23), deltaCP} confidence regions of analysis Frequentist1 were built using critical DeltaChi^2 values computed with the Feldman-Cousins method. To distinguish them from other confidence regions, a tag "FC" is included in the name of the corresponding TGraph. The best fit markers are also provided for the 2D results: gr2D_varX_varY_wRC_<NO,IO,both>_bestfit The best fit markers and contour lines are generally for each MO *separately*, i.e. assuming DeltaChi^2 is 0 at the minimum or that the total posterior probability integrates to 1 in the mass ordering considered. There are some exceptions, in particular some 2D regions for (sin^2(theta_23), dcp) are also provided using a best fit over both MO to allow for comparisons with other experiments using this convention. This special set of contours has an extra tag "globalMO" in its name to distinguish it from the others. ************************************** *** 1D and 2D histograms ************************************** Objects of the form h1D_var_<chi2,posterior>_wRC,_<NO,IO, both, profMO> h2D_var1_var2_<chi2,posterior>_wRC_<NO,IO, both> are respectively TH1D of the DeltaChi^2 ("chi2") or posterior probability ("posterior") for oscillation parameter "var" or TH2D for the couple of parameters (var1, var2) The Bayesian and frequentist results use different conventions with respect to the mass ordering: - DeltaChi^2 plots use a global minimum over both hierarchies - Posterior probability plots integrate to unity *individually* ************************************** ***** Critical values for frequentist results ************************************** For the 1D plots, critical delta chi2 values obtained with the Feldman-Cousins method are provided for theta23 and deltaCP  grCritical_{variable}_chi2_wRC_{NO,IO,profMO}_conf{68, 90, 955} variable: th23, dCP The FC-corrected confidence intervals for these 2 variables can be obtained as the region for which the corresponding 1D DeltaChi^2 histogram is below the grCritical graph of a given level. ************************************** ***** Additional notes for Bayesian results ************************************** For plots involving the mass splitting, the mass ordering is given by the sign:   dm32>0 is normal hierarchy (Delta m^2_{32} > 0)   dm32<0 is inverted hierarchy (Delta m^2_{32} < 0) Note that the posteriors have not been smoothed, and may contain small discontinuities due to MCMC statistical uncertainties. Plots with "_bestfit" appended indicate the point in the 2D parameter space (marginalized over the other parameters) with the highest posterior density, and is not necessarily the global minimum of the likelihood. For the 1D posterior distributions, the user can freely calculate credible intervals from the distributions. It is recommended to start at the point of the highest posterior density, and moving down in posterior density to produce highest posterior credible intervals, which is the kind of credible intervals reported in the paper.  ************************************** ***** Glossary of tags used in objects names ************************************** "wRC"   - Uses “reactor constraint” on theta13, sin^2(2theta_13)=(8.53+-0.27) x 10^{-2} "FC"    - Feldman-Cousins "NO"    - Normal mass Ordering "IO"    - Inverted mass Ordering "both"  - Marginalised over normal and inverted mass orderings "profMO"  - Profiled over normal and inverted mass orderings "cred"  - Credible interval "conf"  - Confidence interval "68"  - 68.3% (1 sigma) "90"  - 90% "955" - 95.5% (2 sigma) "997" - 99.7% (3 sigma) "chi2"  - DeltaChi^2 (-2lnL) for parameter "Critical" - Critical DeltaChi^2 computed using Feldman-Cousins method "th13"  - sin^2(theta_13) "th23"  - sin^2(theta_23) "dCP"   - delta CP "dm2"   - Delta m^2_{23} (NO), |Delta m^2_{13} (IO)| for confidence intervals; used for frequentist analyses results. "dm32"  - Delta m^{2_{23} regardless of mass ordering; in the Bayesian analyses, Delta m^2_{23} is always the variable that is plotted. "jarlskog" - Jarlskog invariant "flatdcp" - Using prior probability uniform in deltaCP "flatsindcp" - Using prior probability uniform in sin(deltaCP)

opencc-by-4.0Nov 2023View details →

The dataset of the manuscript "GPU-HADVPPM4HIP V1.0: higher model accuracy on China's domestically GPU-like accelerator using heterogeneous compute interface for portability (HIP) technology to accelerate the piecewise parabolic method (PPM) in an air quality model (CAMx V6.10)"

bcfile.zip: the clean boundary condition files. CAMxv6x_cpp.zip: the source code of CAMx-HIP version which coupled with HIP-HADVPPM scheme. data.zip: final data tables used to plot figures. emisfile.zip: the emission files. icfile.zip: the clean initial condition files. tuvfile.zip and o3mapfile.zip: the photolysis files. outputfile.zip: the computation results outputted by CAMx model for Fortran version on the Intel Xeon E5-2682 v4 CPU, CUDA version on the NVIDIA K40m and V100 clusters, and HIP version on the China' s domestically heterogeneous cluster A. wrfcamx.zip: the meteorological files. offline_test_cuda.zip: the advection module code written in CUDA C language offline_test_fortran.zip: the advection module code written in Fortran language offline_test_hip.zip: the advection module code written in HIP C language

opencc-by-4.0Jul 2024View details →

Enriching productive mutational paths accelerates enzyme evolution

Quantum mechanical calculations of the Kemp elimination catalyzed by HG3.R5: cluster model transition structures (full QM) in MOL2 format), and enzyme-substrate complex and transition structures (hybrid QM/MM) in PDB format.

Supplemental Material for "Slow-to-fast Transition and Shear Localization in Accelerating Creep of Clayey Soil"

<div> Dataset and plotter for "Slow-to-fast Transition and Shear Localization in Accelerating Creep of Clayey Soil" by Chengrui Chang. This dataset contains all 40 fluid-injection shear experiments on clayey soil. Each .mat file includes raw data and constrained parameters for the accelerating creep. A spreadsheet summarizes the experimental protocols and constrained parameters. </div> <div>Article information:</div> <div>Chang, C., Noda, H., Xu, Q., Huang, D., & Yamaguchi, T. (2024). Slow‐to‐fast transition and shear localization in accelerating creep of clayey soil. Geophysical Research Letters, 51, e2024GL111839. <a href="https://doi.org/10.1029/2024GL111839">https://doi.org/10.1029/2024GL111839</a></div>

opencc-by-4.0Jan 2018View details →

Laser-driven acceleration by microstructured silicon targets

Diagnostic data from a high power laser plasma experiment realised at the Central Laser Facility, UK. Target Area Petawatt with the VULCAN OPCPA laser system was used, to compare microstructured silicon targets (produced at the Detektor- & Targetlabor at the Institut für Kernphysik, Technische Universität Darmstadt, Germany) with flat silicon foils. This spreadsheet shows the laser parameters together with the diagnostic data for 1053nm reflection from target, 527nm emission from target, characteristic X-ray, electron and ion spectra.

opencc-by-4.0Mar 2019View details →

Replication data for Evaluation of movements with greater trunk acceleration and their properties during volleyball games

The present study aimed to elucidate the movements that require greater trunk acceleration and their frequency during volleyball matches and compare their acceleration components. A triaxial accelerometer was used to measure trunk acceleration during volleyball matches. The moments that generated resultant accelerations >4G, >5G and >6G were extracted, and movements that coincided with the extracted moments were identified. The ratios and frequencies of the extracted movements were calculated, and the resultant, mediolateral, vertical and anteroposterior accelerations among the top seven volleyball-specific extracted movements were compared. For attackers, 361, 185 and 97 movements were extracted with acceleration thresholds of 4G, 5G and 6G, respectively. At 6G, landing (77%) was the most frequently observed movement. For receivers, 297, 115 and 38 movements were extracted with acceleration thresholds of 4G, 5G and 6G, respectively. At 4G, running (49%) and steps (31%) were the most frequently observed movements. Resultant and vertical accelerations of spike landing were significantly greater than those of the other six movements (p < 0.001, respectively). Stationary or directional steps observed in receivers showed greater anteroposterior acceleration. Frequency or magnitude of trunk acceleration during these movements might determine the risk of injury during volleyball.

opencc-by-4.0Apr 2019View details →

Laser wakefield acceleration with active feedback at 5 Hz

The data and code used to produce the plots in Dann et al., "Laser wakefield acceleration with active feedback at 5 Hz", Phys. Rev. Accel. Beams (2019). This is a sub-set of the data collected during an experiment investigating the use of active feedback in laser wakefield acceleration driven by a 5 Hz, 20 TW laser. The complete data set weighed in at over 800 GB, so this only includes the data used in the above-mentioned publication.

opencc-by-4.0Jul 2019View details →

Single-shot multi-keV X-ray absorption spectroscopy using an ultrashort laser wakefield accelerator source

The data contained in this repository was used to generate the figures for the publication "Single-shot multi-keV X-ray absorption spectroscopy using an ultrashort laser wakefield accelerator source".

opencc-by-4.0Aug 2019View details →

Strategies for Prioritizing Needs for Accelerated Construction after Hazard Events

Corresponding data set for Tran-SET Project No. 18PPLSU04. Abstract of the final report is stated below for reference: "There is a need for rapid and responsive infrastructure repair and construction after natural disaster events such as hurricanes, wildfires, and tornadoes. These natural disasters often shut down basic infrastructure systems, as experienced recently in several Region 6 states as well as in other states around the country. Accelerated construction practices are often used in these situations to speed up the traditional, and often slow, project delivery process. However, after a natural disaster, several and different types of transportation infrastructure components are in need of inspection, rehabilitation or reconstruction, and transportation agencies are challenged with the task of prioritizing these accelerated projects. This study conducted an extensive literature review of current accelerated methods, infrastructure prioritization practices, and institutional barriers. Interviews with professionals from the transportation industry, including both private and public services, were conducted. Significant input from the railroad industry was used to compare private and public transportation systems responses after disasters. The results of this survey were used to quantify the importance of the accelerate methods and prioritization criteria, and which are the barriers to implement a prioritization model. Lastly, a decision support tool for prioritizing needs for accelerated construction after disaster events, specifically hurricanes and flooding, which commonly affect Region 6, was developed using the data collected."

Autooxidation of nitrous acid to nitric acid in supermicron aqueous droplets is acid accelerated

This is the processed Raman data and calibration data for the experiments used in "Autooxidation of nitrous acid to nitric acid in supermicron aqueous droplets is acid accelerated" submitted to Chemical Science on Aug 2024

Supporting Data for "Extending GPU-Accelerated Gaussian Integrals in the TeraChem Software Package to f Type Orbitals: Implementation and Applications."

Raw data and output files for "Extending GPU-Accelerated Gaussian Integrals in the TeraChem Software Package to f Type Orbitals: Implementation and Applications."

opencc-by-4.0Aug 2024View details →

Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery

Dataset of transition metal complex structures in .xyz file format, computed and predicted energies in comma delimited format, model information in JSON format, and the Mathematica script for uncertainty analysis for associated manuscript.

The accelerating loss of resilience in suburban woodlands can largely be attributed to changes in urban precipitation patterns

Vegetation resilience holds significant importance for stabilizing ecosystem service functions in a changing climate. While global land surface vegetation resilience changes have been extensively studied, the impact of urbanization on the resilience of suburban woodlands remains inadequately understood. In this study, we utilized two Critical Slowing Down (CSD) indicators, namely lag-one autocorrelation (LOA) and variance (VA), to assess the vegetation resilience, its long-term trends, and influencing factors in suburban woodlands across 1,356 cities worldwide. The recovery rates estimated by LOA (rr1) and VA (rr2) showed close alignment in suburban woodlands with low suburban forest coverage (SFC) areas (correlation coefficient (r)=0.95). However, a notable divergence was observed in areas with high SFC (r=0.73). Suburban woodlands with high SFC typically exhibited lower recovery rate estimates, thus indicating greater vegetation resilience compared to areas with lower SFC. From 1986 to 2022, the recovery rates of suburban woodland areas in over 83% of the cities demonstrated a significant upward trend, with an average of 3.23×10−3 yr−1 for both rr1 and rr2, signifying a widespread decline in vegetation resilience. The accelerating pace of urbanization led to higher rising rates of rr1 and rr2 during 2010-2022 (5.11×10−3 yr−1) compared to 1986-1999 (0.49×10−3 yr−1). The notable decrease in resilience of forestland was primarily attributed to reduced precipitation in urban suburbs, which can be explained by urbanization-induced heat island and building barrier effects, causing a shift of precipitation center from urban suburbs to central cities. In summary, this study revealed that urbanization diminishes the vegetation resilience of urban suburban woodlands by altering urban precipitation patterns. These findings underscore the necessity of augmenting water availability in urban suburbs to restore resilience in these woodlands, thereby enhancing their ecosystem service value.

The accelerating loss of resilience in suburban woodlands can largely be attributed to changes in urban precipitation patterns

Dataset for 'Warmer Oceans may Accelerate the Marine-to-Land Transition of a West Greenland Outlet Glacier'

Monthly hydrographic records from 2008-2023, collected from the standard station GF10 (64°36.6N, 51°57.5 W; maximum depth: 576 m) as part of Greenland Climate Research Centre “Long-term standard hydrographic fjord research program”. Note that the date values reflect the last day of each month, not necessarily the date that the measurements were obtained. Please cite this reference if dataset were used in any way. Correspondence to John Mortensen at jomo@natur.gl

Systemic inflammation accelerates neurodegeneration in a rat model of Parkinson's disease overexpressing human alpha synuclein

Parkinson’s disease (PD) involves genetic and environmental risk factors. Increasing research efforts have been made to understand how they interact to impair homeostasis and elevate risk. Inflammation could be one unifying factor. In this study, wild-type (WT) and overexpressing human α-synuclein (Snca+/+) rats were intraperitoneally injected with a single dose of lipopolysaccharide (LPS) or with saline (SAL). In these animals we assessed the development of PD-like symptoms by immunohistology, high-dimensional flow cytometry, electrophysiology, and behavioral analyses. A single injection of LPS to both WT and Snca+/+ rats triggered long-lasting increased activation of pro-inflammatory microglial markers, infiltrating monocytes and T-lymphocytes. However, only LPS Snca+/+ rats displayed dopaminergic neuronal loss in the substantia nigra pars compacta (SNpc), associated with a reduction of evoked dopamine release in the striatum. No significant changes were observed in the behavioral domain.

Tau accelerates tubulin exchange in the microtubule lattice

This dataset contains the data and source code for Figures 1-4 and and the source code for Supplementary Figures S5-S10 from the following publication:  <div> Tau accelerates tubulin exchange in the microtubule lattice </div> <div>by</div> <div> </div> <div>Subham Biswas, Rahul Grover, Cordula Reuther, Chetan S. Poojari, M. Reza Shaebani, Mona Grünewald, Amir Zablotsky, Jochen S. Hub, Stefan Diez, Karin John, Laura Schaedel</div> <div> </div> <div>doi: https://doi.org/10.1101/2024.10.05.616777</div>