cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/rgctdkjyzx.1
title: PRMT1 is critical for the transcriptional activity and the stability of the progesterone receptor. Malbeteau et al

description: The progesterone receptor (PR) is an inducible transcription factor that plays critical roles in female reproductive processes and in several aspects of breast cancer tumorigenesis. Our report describes the type I protein arginine methyltransferase 1 (PRMT1) as a cofactor controlling progesterone pathway, through the direct methylation of PR. Mechanistic assays in breast cancer cells indicate that PRMT1 methylates PR at the arginine 637 and reduces the stability of the receptor, thereby accelerating its recycling and finally its transcriptional activity. Depletion of PRMT1 decreases the expression of a subset of progesterone-inducible genes, controlling breast cancer cells proliferation and migration. Consistently, Kaplan–Meier analysis revealed that low expression of PRMT1 predicts a longer survival among the subgroup with high PR. Our study highlights PR methylation as a molecular switch adapting the transcription requirement of breast cells during tumorigenesis.
DOI: 10.17632/rpgcbzzhdt.1
title: VegasFlow: Accelerating Monte Carlo simulation across multiple hardware platforms

description: We present VegasFlow, a new software for fast evaluation of high dimensional integrals based on Monte Carlo integration techniques designed for platforms with hardware accelerators. The growing complexity of calculations and simulations in many areas of science have been accompanied by advances in the computational tools which have helped their developments. VegasFlow enables developers to delegate all complicated aspects of hardware or platform implementation to the library so they can focus on the problem at hand. This software is inspired on the Vegas algorithm, ubiquitous in the particle physics community as the driver of cross section integration, and based on Google’s powerful TensorFlow library. We benchmark the performance of this library on many different consumer and professional grade GPUs and CPUs.
DOI: 10.17632/c3dhycyvj8.1
title: A high-order non field-aligned approach for the discretization of strongly anistropic diffusion operators in magnetic fusion

description: In this work we present a hybrid discontinuous Galerkin scheme for the solution of extremely anisotropic diffusion problems arising in magnetized plasmas for fusion applications. Unstructured meshes, non-aligned with respect to the dominant diffusion direction, allow an unequalled flexibility in discretizing geometries of any shape, but may lead to spurious numerical diffusion. Curved triangles or quadrangles are used to discretize the poloidal plane of the machine, while a structured discretization is used in the toroidal direction. The proper design of the numerical fluxes guarantees the correct convergence order at any anisotropy level. Computations performed on well-designed 2D and 3D numerical tests show that non-aligned discretizations are able to provide spurious diffusion free solutions as long as high-order interpolations are used. Introducing an explicit measure of the numerical diffusion, a careful investigation is carried out showing an exponential increase of this latest with respect to the non-alignment of the mesh with the diffusion direction, as well as an exponential decrease with the polynomial degree of interpolation. A brief assessment of the method with respect to two finite-difference schemes using non-aligned discretization, but classically used in fusion modeling, is also presented.
DOI: 10.5281/zenodo.3873392
title: GTDB release89

description: <pre>GTDB R04-RS89 Release date: June 17th, 2019 GTDB R04-RS89 contains 23,458 bacterial and 1,248 archaeal species clusters which span 145,904 genomes. </pre> <pre>Additional information ---------------------- Please consult the following GTDB publications for additional information: Parks, D. H., et al. (2018). A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nature Biotechnology, 36: 996-1004. Parks DH, et al. (2019). Selection of representative genomes for 24,706 bacterial and archaeal species clusters provide a complete genome-based taxonomy. bioRxiv: https://doi.org/10.1101/771964 Chaumeil P-A, et al. (2019). GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics, btz848: https://doi.org/10.1093/bioinformatics/btz848. </pre>
DOI: 10.5281/zenodo.3873391
title: GTDB release89

description: <pre>GTDB R04-RS89 Release date: June 17th, 2019 GTDB R04-RS89 contains 23,458 bacterial and 1,248 archaeal species clusters which span 145,904 genomes. </pre> <pre>Additional information ---------------------- Please consult the following GTDB publications for additional information: Parks, D. H., et al. (2018). A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nature Biotechnology, 36: 996-1004. Parks DH, et al. (2019). Selection of representative genomes for 24,706 bacterial and archaeal species clusters provide a complete genome-based taxonomy. bioRxiv: https://doi.org/10.1101/771964 Chaumeil P-A, et al. (2019). GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics, btz848: https://doi.org/10.1093/bioinformatics/btz848. </pre>
DOI: 10.17632/wzzv2wc7fd.1
title: A MATLAB tool for computing the spherical harmonic fractal dimension of the cerebral cortex

description: Fractal dimension (FD) has become a very useful tool in neuroscience with a wide range of applications in characterizing several neurodegenerative diseases. The most commonly used method for computing the FD of brain tissues is box-counting. This technique performs very well on 2D images and 3D volumes; however, it presents several drawbacks when processing cortical surfaces in 3D. In this study, we present a MATLAB program for computing the FD of 3D surfaces based on spherical harmonics. We developed a novel MATLAB program, called UJA-SHFD, based on a spherical harmonics FD algorithm which overcomes the limitations of the classical box-counting algorithm when processing 3D surfaces. Moreover, spherical-harmonic-based FD (SHFD) enables the processing of both global (providing a single FD value for the entire surface) and local level assessments in each cortical surface vertex. UJA-SHFD has been specifically designed and tested for processing cortical surfaces obtained from the FreeSurfer software suite. Nevertheless, the program can also process any kind of surface in the Wavefront OBJ format. UJA-SHFD can be used both through a graphical user interface and at the command line. The present study demonstrates the usefulness of UJA-SHFD through its application to a neuroimaging study looking at the progression of brain atrophy in Alzheimer’s disease. UJA-SHFD is a novel MATLAB program with the goal of developing neuroimaging analyses of FD computation for the investigation of brain morphological changes in neurodegenerative and neuropsychiatric disorders. The MATLAB source code of UJA-SHFD is freely available.
DOI: 10.17632/zhb728dc4z.1
title: Birdsong rhythm: Onsets/intervals of a zebra finch song corpus and 3 thrush nightingale song corpora

description: ZEBRA FINCH DATA: file "IntervalData_ZebraFinch_corpus.mat" This file contains variable "ZebraFinch_intervals_ms": A vector of syllable onset-onset intervals of zebra finch song in ms. NAN entries mark boundaries of singing bouts. Song is from 93 captive zebra finches recorded at the Rockefeller field center in Millbrook, NY. Details are described in file "METHODS4IntervalData_processing of birdsong.pdf". THRUSH NIGHTINGALE DATA: file "IntervalData_ThrushNightingale_3corpora.mat" This file contains the following datasets: Corpus 1 - full song dataset: "ThrushNightingaleSongs_intervals_ms": vector of syllable onset-onset intervals of thrush nightingale song. NAN entries mark song boundaries. Songs are a subset of 45 recordings obtained from the publicly available birdsong library http://www.xeno-canto.org. Identifiers of the xeno-canto recordings are provided in the file "Pointers_to_xeno-canto_data.mat". Corpus 2 - stable rhythm dataset: "ThrushNightingaleStableRhythms_intervals_ms", a subset of Corpus 1 onset-onset intervals. They include only ‘stable rhythms’, i.e. song epochs with stably repeated interval dyads. A description of how this dataset was generated is provided in the file "METHODS4IntervalData_processing of birdsong.pdf". Corpus 3 - "same syllable type" dataset: "ThrushNightingaleSameSyllableEpochs_intervals_ms": A vector of syllable onset-onset intervals of trains of same-syllable repetitions from the same 45 xeno-canto recordings underlying Corpus 1. Same-syllable epochs were manually identified as described in file "METHODS4IntervalData_processing of birdsong.pdf". "ThrushNightingale_SameSyllableEpochs_onsets_ms": same dataset, onset times in ms, from the beginning of each same-note train.
DOI: 10.17632/mkcxrky9jc.1
title: A fast algorithm for computing a matrix transform used to detect trends in noisy data

description: A recently discovered universal rank-based matrix method to extract trends from noisy time series is described in Ierley and Kostinski (2019) but the formula for the output matrix elements, implemented there as an open-access supplement MATLAB computer code, is O(N^4), with N the matrix dimension. This can become prohibitively large for time series with hundreds of sample points or more. Based on recurrence relations, here we derive a much faster O(N^2) algorithm and provide code implementations in MATLAB and in open-source JULIA. In some cases one has the output matrix and needs to solve an inverse problem to obtain the input matrix. A fast algorithm and code for this companion problem, also based on the recurrence relations, are given. Finally, in the narrower, but common, domains of (i) trend detection and (ii) parameter estimation of a linear trend, users require, not the individual matrix elements, but simply their accumulated mean value. For this latter case we provide a yet faster O(N) heuristic approximation that relies on a series of rank one matrices. These algorithms are illustrated on a time series of high energy cosmic rays with N &gt; 4 x 10^4 .
DOI: 10.17632/p55pjxztwy.1
title: WOS

description: Bases juntas
DOI: 10.17632/vb2m5x5xhr.1
title: Survey Dataset on Face to Face Students' intention to use Social Media and Emerging Technologies for Continuous Learning

description: One of the sectors that felt the impact of the Corona Virus Disease 2019 (COVID-19) pandemic was the educational sector. The outbreak led to the immediate closure of schools at all levels thereby sending billions of students away from their various institutions of learning. However, the shut down of academic institutions was not a total one as some institutions that were solely running online programmes were not affected. Those who were running face to face and online modes quickly switched over to the online mode. Unfortunately, institutions that have not fully embraced online mode of study were greatly affected. 85% of academic institutions in Nigeria are operating face to face mode of study, therefore, majority of Nigerian students at all levels were affected by the COVID-19 lockdown. Social media platforms and emerging technologies were the major backbones of institutions that are running online mode of study, therefore, this survey uses the unified theory of acceptance and use of technology (UTAUT) model to capture selected Face to face Nigerian University students accessibility, usage, intention and willingness to use these social media platforms and emerging technologies for learning. The challenges that could mar the usage of these technologies were also revealed. Eight hundred and fifty undergraduate students participated in the survey. The dataset includes the questionnaire used to retrieve the data, the responses obtained in spreadsheet format, the charts generated from the responses received, the Statistical Package of the Social Sciences (SPSS) file and the descriptive statistics for all the variables captured. Authors believed that the dataset will enhance understanding of how face to face students use social media platforms and how these platforms could be used to engage the students outside their classroom activities. Also, the dataset exposes how familiar face to face University students are to these emerging teaching and learning technologies.
DOI: 10.17632/tz5zwgs85v.2
title: Micro X-ray CT images of two cores (Original and Filtered)

description: Because of technical problems, the 2nd version has been uploaded. Please, use the 2nd version for further calculations. The micro x-ray CT images of two rock samples have been reconstructed. The data type of images: uint8 Spatial Resolution: 1.2 micrometer/voxel Size: 400X400X400 The reconstructed or "Original" images are suffering from existence of artifacts, roundoff errors, and different types of visual or mathematical noises in the reconstructed CT images. Each image has been applied with a series of bandpass and bilateral filters.
DOI: 10.5281/zenodo.3888502
title: Chang'E-4 rover spectra revealing micro-scale surface thermophysical properties of the Moon

description: Dataset of the article 'Chang’E-4 rover spectra revealing micro-scale surface thermophysical properties of the Moon'
DOI: 10.25386/genetics.12456206
title: Supplemental Material for Garge et al., 2020

description: Supplemental material from Garge et. al 2020
DOI: 10.5281/zenodo.3888492
title: Ionospheric Horizontal Correlation Length Derived From IRI-2016 Model Errors

description: Ionospheric horizontal correlation length based on IRI-2016 model and JPL Global Ionospheric Maps. This metadata can be used for the construction of the covariance matrix for ionospheric data assimilation. each .nc file corresponds to one bin. Binning in season (winter, summer, equinox): 00=month 1,2,11,12<br> 01=month 5,6,7,8<br> 02=month 3,4,9,10<br> <br> Binning in F10.7 solar flux (low, moderate, high): 00=0-100 s.f.u<br> 01=100-150 s.f.u.<br> 02=150-350 s.f.u. <br> <br> Binning in UT: 2-h frames. Example: <br> The name of the .nc file: <br> Corr_Length_IRI_seazon_01_sf_00_UT_18.nc <br> would correspond to summer season, low solar flux, 18-20 UT. Inside of the .nc files: longitudes=array of geomagnetic longitudes (degrees)<br> latitudes=array of geomagnetic latitudes (degrees)<br> zonal_corr_length=array of size (nlon, nlat), is a map of zonal correlation lengths<br> merid_corr_length=array of size (nlon, nlat), is a map of meridional correlation lengths<br> L_4d=array of size (nlon, nlat, 4), is a map of correlation lengths in 4 perpendicular azimuthal directions; 0=0 deg, 1=90 deg, 2=180 deg, 3=-90 deg<br> L_az=array of size (nlon, nlat, 36), is a map of correlation lengths in 36 azimuthal directions (0,10,20,30,...,350 deg)<br>
DOI: 10.5281/zenodo.3888491
title: Ionospheric Horizontal Correlation Length Derived From IRI-2016 Model Errors

description: Ionospheric horizontal correlation length based on IRI-2016 model and JPL Global Ionospheric Maps. This metadata can be used for the construction of the covariance matrix for ionospheric data assimilation. each .nc file corresponds to one bin. Binning in season (winter, summer, equinox): 00=month 1,2,11,12<br> 01=month 5,6,7,8<br> 02=month 3,4,9,10<br> <br> Binning in F10.7 solar flux (low, moderate, high): 00=0-100 s.f.u<br> 01=100-150 s.f.u.<br> 02=150-350 s.f.u. <br> <br> Binning in UT: 2-h frames. Example: <br> The name of the .nc file: <br> Corr_Length_IRI_seazon_01_sf_00_UT_18.nc <br> would correspond to summer season, low solar flux, 18-20 UT. Inside of the .nc files: longitudes=array of geomagnetic longitudes (degrees)<br> latitudes=array of geomagnetic latitudes (degrees)<br> zonal_corr_length=array of size (nlon, nlat), is a map of zonal correlation lengths<br> merid_corr_length=array of size (nlon, nlat), is a map of meridional correlation lengths<br> L_4d=array of size (nlon, nlat, 4), is a map of correlation lengths in 4 perpendicular azimuthal directions; 0=0 deg, 1=90 deg, 2=180 deg, 3=-90 deg<br> L_az=array of size (nlon, nlat, 36), is a map of correlation lengths in 36 azimuthal directions (0,10,20,30,...,350 deg)<br>
DOI: 10.17632/y995g2k9zf.1
title: Data for: Three-dimensional rGO@sponge framework/paraffin wax composite shape-stabilized phase change materials for solar-thermal energy conversion and storage

description: Partial data uploaded
DOI: 10.5519/qd.mbnf2oao
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (232 records)
DOI: 10.5281/zenodo.3888414
title: Catalan United Nations v1.0 test set

description: Catalan version [1] of the test set from the United Nations v1.0 [2]. The translation was performed in two steps: we did a first automatic translation from the Spanish test set version into Catalan and then a professional translator post-edited the output. <br> [1] Marta R. Costa-Jussà, Noé Casas, Carlos Escolano, and José A. R. Fonollosa. 2019. Chinese-Catalan: A Neural Machine Translation Approach Based on Pivoting and Attention Mechanisms. <em>ACM Trans. Asian Low-Resour. Lang. Inf. Process.</em> 18, 4, Article 43 (August 2019), 8 pages. DOI:https://doi.org/10.1145/3312575 [2] Michal Ziemski, Marcin Junczys-Dowmunt, and Bruno Pouliquen. 2016. The United Nations parallel corpus v1.0. In<br> Proceedings of the LREC, 2016
description: This work is supported by the Spanish Ministerio de Economía y Competitividad and European Regional Development Fund, through the postdoctoral senior grant Ramón y Cajal.
description: {"references": ["Costa-juss\u00e0, M.R., Casas, N., Escolano, C. and Fonollosa, J.A.R., Chinese-Catalan: A Neural Machine Translation Approach based on Pivoting and Attention Mechanisms, ACM Transactions on Asian and Low-Resource Language Information Processing, Vol 18, No 4, Art. 43, 2019", "Michal Ziemski, Marcin Junczys-Dowmunt, and Bruno Pouliquen. 2016. The United Nations parallel corpus v1.0. In Proceedings of the LREC, 2016"]}
DOI: 10.5281/zenodo.3888413
title: Catalan United Nations v1.0 test set

description: Catalan version [1] of the test set from the United Nations v1.0 [2]. The translation was performed in two steps: we did a first automatic translation from the Spanish test set version into Catalan and then a professional translator post-edited the output. <br> [1] Marta R. Costa-Jussà, Noé Casas, Carlos Escolano, and José A. R. Fonollosa. 2019. Chinese-Catalan: A Neural Machine Translation Approach Based on Pivoting and Attention Mechanisms. <em>ACM Trans. Asian Low-Resour. Lang. Inf. Process.</em> 18, 4, Article 43 (August 2019), 8 pages. DOI:https://doi.org/10.1145/3312575 [2] Michal Ziemski, Marcin Junczys-Dowmunt, and Bruno Pouliquen. 2016. The United Nations parallel corpus v1.0. In<br> Proceedings of the LREC, 2016
description: This work is supported by the Spanish Ministerio de Economía y Competitividad and European Regional Development Fund, through the postdoctoral senior grant Ramón y Cajal.
description: {"references": ["Costa-juss\u00e0, M.R., Casas, N., Escolano, C. and Fonollosa, J.A.R., Chinese-Catalan: A Neural Machine Translation Approach based on Pivoting and Attention Mechanisms, ACM Transactions on Asian and Low-Resource Language Information Processing, Vol 18, No 4, Art. 43, 2019", "Michal Ziemski, Marcin Junczys-Dowmunt, and Bruno Pouliquen. 2016. The United Nations parallel corpus v1.0. In Proceedings of the LREC, 2016"]}
DOI: 10.15129/36c7c50d-38f5-4a51-8540-b0a7857cde1d
title: Data for: "Thermodynamic favorability of end products of anaerobic glucose metabolism"

description: Data for paper in ACS Omega. Two Excel files contain all the data and calculations underlying the paper. The file Metabol thermo.xlsx contains all the calculations underlying the paper. The file Detherm downloads.xlsx includes information downloaded from the Detherm database which was then used in calculations shown in Metabol thermo.xlsx.
DOI: 10.5281/zenodo.3887188
title: estherlee0000/MLCan2.0: Data for AZ

description: datasets for Lee, Kumar, Knowles, et al, WRR 2020 (in review) AZ_CM_MLCanForcing2015-2016.mat: forcing file for Charleston Mesquite (CM) site to run Multi-layer canopy (MLCan) model. Forcing file includes leaf area indices of coexisting plants, leaf area density over the canopy, etc. CM20XX.mat: measured flux tower data at Charleston Mesquite (CM) site. Each file provides 30-minutes interval data for a year. Data includes precipitation, solar radiation, energy fluxes, etc. (flux tower data provided by USDA-ARS. Please contact Russ Scott at russ.scott@ars.usda.gov if you have any questions) CMsoil20XX.mat: measured soil moisture and soil temperature over depth at Charleston Mesquite (CM) site. Each file provides 30-minutes interval data for a year. (soil data provided by USDA-ARS. Please contact Russ Scott at russ.scott@ars.usda.gov if you have any questions) readme.txt: readme file for CMsoil20XX.mat provides depths of soil where soil moisture and temperature are measured. CM_mean_nighttime_sapvelocity.xlsx: measured sap flow through the trunk, taproot, and lateral root of mesquite at Charleston Mesquite (CM) site. Data provides mean nighttime sap flow velocity (cm/hr) during the monsoon period in 2015, pre-monsoon and monsoon periods in 2016. Link to Github: https://github.com/HydroComplexity/MLCan2.0
DOI: 10.5281/zenodo.3885825
title: estherlee0000/MLCan2.0: Data for AZ

description: datasets for Lee, Kumar, Knowles, et al, WRR 2020 (in review) AZ_CM_MLCanForcing2015-2016.mat: forcing file for Charleston Mesquite (CM) site to run Multi-layer canopy (MLCan) model. Forcing file includes leaf area indices of coexisting plants, leaf area density over the canopy, etc. CM20XX.mat: measured flux tower data at Charleston Mesquite (CM) site. Each file provides 30-minutes interval data for a year. Data includes precipitation, solar radiation, energy fluxes, etc. (flux tower data provided by USDA-ARS. Please contact Russ Scott at russ.scott@ars.usda.gov if you have any questions) CMsoil20XX.mat: measured soil moisture and soil temperature over depth at Charleston Mesquite (CM) site. Each file provides 30-minutes interval data for a year. (soil data provided by USDA-ARS. Please contact Russ Scott at russ.scott@ars.usda.gov if you have any questions) readme.txt: readme file for CMsoil20XX.mat provides depths of soil where soil moisture and temperature are measured. CM_mean_nighttime_sapvelocity.xlsx: measured sap flow through the trunk, taproot, and lateral root of mesquite at Charleston Mesquite (CM) site. Data provides mean nighttime sap flow velocity (cm/hr) during the monsoon period in 2015, pre-monsoon and monsoon periods in 2016. Link to Github: https://github.com/HydroComplexity/MLCan2.0
DOI: 10.25386/genetics.12456206.v1
title: Supplemental Material for Garge et al., 2020

description: Supplemental material from Garge et. al 2020
DOI: 10.25919/5ee10b7b69a6d
title: Parkes observations for project P958 semester 2020APRS_14

description: Fast radio bursts (FRBs) continue to raise more questions than they answer. Until last year, only one burst – the only one known to repeat - had been localized to a bright radio nebula (either a young supernova remnant or pulsar wind nebulae) in a distant dwarf galaxy. Over the last three years searches with the Australian Square Kilometre Array Pathfinder (ASKAP) have detected 35 bursts, eight of which have been localised to host galaxies at redshifts ranging from 0.1 to 0.5. These bursts and their hosts are very unlike the repeater, suggesting there may be a dichotomy in the population. However one of the arcminute-localised ASKAP FRBs has recently been found to repeat. Here we propose to search and study repetitions in this FRB population. Our comprehensive sample and a dense monitoring campaign of well localised bursts, at a fluence limit more than 60 times lower than that of their detections to characterise the fraction of bursts that repeat. For bursts that repeat the unique wide bandwidth observations will be used to test leading models of burst emission.