cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10149218
title: Numerical simulation of the equatorial plasma bubble: the effect of seeding by the vertical winds and random background noise perturbations.

description: A wide variety of small-amplitude waves widely exist in the ionosphere and have significant effects on the evolution of equatorial plasma bubbles. In this paper, we simulated equatorial plasma bubbles (EPB) seeded by vertical neutral wind perturbations with wavelengths of 125 km and 250 km, and compared the morphology characteristics of plasma bubble structures with those under random noise perturbations in the background density. The numerical results showed that both vertical winds and random background noise perturbations can contribute to the growth of plasma bubbles, and the perturbations under additional random background noise can promote the growth of the plasma bubble structures faster. Additionally, several processes of the nonlinear behavior of bifurcated EPB structures, including bifurcation, pinching, and small-scale turbulent structures, were successfully obtained. Our simulation captured supersonic flows within the low-density plasma structures characterized by vertical velocities of about 1.5 km/s, which is consistent with experimental studies found in the literature.
DOI: 10.5281/zenodo.10149217
title: Numerical simulation of the equatorial plasma bubble: the effect of seeding by the vertical winds and random background noise perturbations.

description: A wide variety of small-amplitude waves widely exist in the ionosphere and have significant effects on the evolution of equatorial plasma bubbles. In this paper, we simulated equatorial plasma bubbles (EPB) seeded by vertical neutral wind perturbations with wavelengths of 125 km and 250 km, and compared the morphology characteristics of plasma bubble structures with those under random noise perturbations in the background density. The numerical results showed that both vertical winds and random background noise perturbations can contribute to the growth of plasma bubbles, and the perturbations under additional random background noise can promote the growth of the plasma bubble structures faster. Additionally, several processes of the nonlinear behavior of bifurcated EPB structures, including bifurcation, pinching, and small-scale turbulent structures, were successfully obtained. Our simulation captured supersonic flows within the low-density plasma structures characterized by vertical velocities of about 1.5 km/s, which is consistent with experimental studies found in the literature.
DOI: 10.5281/zenodo.10149409
title: Phlorest phylogeny derived from Lee & Hasegawa 2011 'Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages'

description: Cite the source of the dataset as:




Lee S, Hasegawa T (2011) Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings of the Royal Society B: Biological Sciences, 278(1725):3662–9.
DOI: 10.5281/zenodo.8250175
title: Phlorest phylogeny derived from Lee & Hasegawa 2011 'Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages'

description: Cite the source of the dataset as: Lee S, Hasegawa T (2011) Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings of the Royal Society B: Biological Sciences, 278(1725):3662–9.
DOI: 10.34740/kaggle/ds/4017081
title: 📞3.6 Million WhatsApp Google Store Reviews
DOI: 10.5519/qd.b6vtelds
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1 records)
DOI: 10.5281/zenodo.8144241
title: Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"

description: <strong>Abstract</strong> <strong>Background</strong> In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays. In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor. <strong>Methods </strong> 114 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images. <strong>Findings</strong> From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%). Upon cross-validation, ComBat algorithm obtained a mean R<sup>2</sup> higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R<sup>2</sup> in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat. <strong>Interpretation</strong> This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.
DOI: 10.5281/zenodo.8159059
title: Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"

description: <strong>Abstract</strong> <strong>Background</strong> In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays. In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor. <strong>Methods </strong> 114 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images. <strong>Findings</strong> From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%). Upon cross-validation, ComBat algorithm obtained a mean R<sup>2</sup> higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R<sup>2</sup> in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat. <strong>Interpretation</strong> This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.
DOI: 10.5281/zenodo.8379082
title: Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"

description: <strong>Abstract</strong> <strong>Background</strong> In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays. In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor. <strong>Methods </strong> 114 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images. <strong>Findings</strong> From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%). Upon cross-validation, ComBat algorithm obtained a mean R<sup>2</sup> higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R<sup>2</sup> in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat. <strong>Interpretation</strong> This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.
DOI: 10.5281/zenodo.10053247
title: Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"

description: Abstract
 
Background
 
In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays.  In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor.
 
Methods
 
112 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images.
 
Findings
 
From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%).
Upon cross-validation, ComBat algorithm obtained a mean R2 higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R2 in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat.
 
 
Interpretation
 
This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.
DOI: 10.5281/zenodo.10053317
title: Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"

description: Abstract
 
Background
 
In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays.  In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor.
 
Methods
 
112 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images.
 
Findings
 
From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%).
Upon cross-validation, ComBat algorithm obtained a mean R2 higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R2 in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat.
 
 
Interpretation
 
This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.
DOI: 10.5281/zenodo.8119320
title: Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"

description: Abstract
 
Background
 
In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays.  In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor.
 
Methods
 
112 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images.
 
Findings
 
From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%).
Upon cross-validation, ComBat algorithm obtained a mean R2 higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R2 in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat.
 
 
Interpretation
 
This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.
DOI: 10.5281/zenodo.8119321
title: Dataset related to article "A reference framework for standardization and harmonization of CT Radiomics features: the "CadAIver" analysis"

description: <strong>Abstract</strong> <strong>Background</strong> In recent years, Radiomics features (RFs) have been developed to provide quantitative, standardized information about shape, density/intensity and texture patterns on radiological images. Several studies showed limitations in the reproducibility of RFs in different acquisition settings. To date, reproducibility studies using CT images mainly rely on phantoms, due to the harness of patient exposure to X-rays. In this study we analyze the effects of CT acquisition parameters on RFs of lumbar vertebrae in a cadaveric donor. <strong>Methods </strong> 114 unique CT acquisitions from cadaveric truck were performed on 3 different CT scanners varying KV, mA, field of view and reconstruction kernel settings. Lumbar vertebrae were segmented through a deep learning convolutional neural network and RFs were computed. The effects of each protocol on each RFs were assessed by univariate and multivariate Generalized Linear Model. Further, we compared the GLM model to the ComBat algorithm in the efficiency in harmonizing CT images. <strong>Findings</strong> From GLM, mA variation was not associated with alteration of RFs , whereas kV modification was associated with exponential variation of several RFs, including First Order (94.4%), GLCM (87.5%) and NGTDM (100%). Upon cross-validation, ComBat algorithm obtained a mean R<sup>2</sup> higher than 0.90 in 1 RFs (0.90%), whereas GLM model obtained high R<sup>2</sup> in 21 RFs (19.6%), showing that the proposed GLM could effectively harmonize acquisitions better than ComBat. <strong>Interpretation</strong> This study represents the first attempt in describing the effects of CT acquisition parameters in bone RFs in a cadaveric donor. Our analyses showed that RFs could be substantially different according to the variation of each acquisition parameter and in dataset obtained from different CT scanners. These differences can be minimized using the proposed GLM model. Publicly available dataset and GLM could foster the research of Radiomics-based studies by increasing harmonization across CT protocols and vendors.
DOI: 10.25345/c5qn5zn9x
title: MassIVE MSV000093416 - Ttttttttttttttttttttttttttttttttttttttteszt10
title: sdafdwFWewafgeasgeqrgfeqgfqegfeqerqgearfeawerwfgrtge2gfwefgewq
DOI: 10.5281/zenodo.10149385
title: EPDnew: FTP directory, Nov 2023

description: Snapshot of the EPDnew FTP directory of November 2023. The acronym EPDnew refers to the newer versions of the Eukaryotic Promoter Database published in the format introduced in 2013. The directory contains all database versions for 15 model organisms released since then.
DOI: 10.5281/zenodo.10149386
title: EPDnew: FTP directory, Nov 2023

description: Snapshot of the EPDnew FTP directory of November 2023. The acronym EPDnew refers to the newer versions of the Eukaryotic Promoter Database published in the format introduced in 2013. The directory contains all database versions for 15 model organisms released since then.
DOI: 10.5281/zenodo.10149480
title: GitHub Public Repository Metadata

description: Metadata (i.e. no code) of all public repositories with 5+ stars on GitHub
 
This dataset is obtained from the Github API and contains only public repository-level metadata.It may be useful for anyone interested in studying the Github ecosystem. It contains approximately 3.1 million entries.
The Github API Terms of Service apply.

You may not use this dataset for spamming purposes, including for the purposes of selling GitHub users' personal information, such as to recruiters, headhunters, and job boards.
The data format is a JSON array of entries, an example of which is given below.
Redacted for anonymity.
DOI: 10.5281/zenodo.10149481
title: GitHub Public Repository Metadata

description: Metadata (i.e. no code) of all public repositories with 5+ stars on GitHub
 
This dataset is obtained from the Github API and contains only public repository-level metadata.It may be useful for anyone interested in studying the Github ecosystem. It contains approximately 3.1 million entries.
The Github API Terms of Service apply.

You may not use this dataset for spamming purposes, including for the purposes of selling GitHub users' personal information, such as to recruiters, headhunters, and job boards.
The data format is a JSON array of entries, an example of which is given below.
Redacted for anonymity.
DOI: 10.5281/zenodo.10149406
title: Dataset for the paper "Test Polarity: Detecting Positive and Negative Tests"

description: Dataset for the paper "Test Polarity: Detecting Positive and Negative Tests".
Test polarity results for 12 Python Standard Libraries: gzip, email, calendar, ftplib, collections, os, tarfile, pathlib, logging, smtplib, argparse, and configparser.
DOI: 10.6084/m9.figshare.21174397
title: Phylogenetic reconstructions of Micromonas commoda RCC299 light stress response proteins from the manuscript "Phosphate limitation responses in marine green algae are linked to reprogramming of the tRNA epitranscriptome and codon usage bias"

description: Phylogenetic reconstructions of Micromonas commoda RCC299 light stress response proteins in nexus (*.tre) and pdf format (*.pdf), corresponding to Fig. 4, Fig. S5 and Dataset S3 in the manuscript "Phosphate limitation responses in marine green algae are linked to reprogramming of the tRNA epitranscriptome and codon usage bias". Trees were inferred using IQ-TREE, using the best LG model identified for each alignment separately, node support was calculated using 1000 ultrafast bootstrap replicates. Filenames for phylogenies contain, in that order, the <i>Micromonas commoda</i> RCC299 protein ID(s), the name of the gene(s) as described in the manuscript and the model used for tree reconstruction.
DOI: 10.6084/m9.figshare.21174397.v1
title: Phylogenetic reconstructions of Micromonas commoda RCC299 light stress response proteins

description: Phylogenetic reconstructions of Micromonas commoda RCC299 light stress response proteins in nexus (*.tre) and pdf format (*.pdf), corresponding to Fig. 4, Fig. S5 and Dataset S3 in the manuscript. Trees were inferred using IQ-TREE, using the best LG model identified for each alignment separately, node support was calculated using 1000 ultrafast bootstrap replicates. Filenames for phylogenies contain, in that order, the <em>Micromonas commoda</em> RCC299 protein ID(s), the name of the gene(s) as described in the manuscript and the model used for tree reconstruction.