cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22723603.v1
title: Surges in volcanic activity on the Moon about two billion years ago

description: This is the source data
DOI: 10.6084/m9.figshare.22723603
title: Surges in volcanic activity on the Moon about two billion years ago

description: This is the source data
DOI: 10.6084/m9.figshare.23143871.v1
title: Practical arrhythmias detection algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset

description: These data include main text, figures and tables.
DOI: 10.6084/m9.figshare.23143871
title: Practical arrhythmias detection algorithm for wearable 12-lead ECG via self-supervised learning on large-scale dataset

description: These data include main text, figures and tables.
DOI: 10.6084/m9.figshare.22698628.v1
title: Dissolved-Cl<sub>2</sub> Triggered Redox Reaction Enables High-performance Perovskite Solar Cells

description: Source data underlying line plots, statistical plots, and tables of this work are provided.
DOI: 10.6084/m9.figshare.22698628
title: Dissolved-Cl<sub>2</sub> Triggered Redox Reaction Enables High-performance Perovskite Solar Cells

description: Source data underlying line plots, statistical plots, and tables of this work are provided.
DOI: 10.6084/m9.figshare.22895708.v1
title: Specific post-translational modifications of soluble tau protein distinguish between Alzheimer’s disease and primary tauopathies

description: The Source Data file contains all data which graphs and tables of the manuscript are from : “Specific post-translational modifications of the soluble tau protein distinguish between Alzheimer’s disease and primary tauopathies”. Sheet 1: Uncropped Westernblot results (Fig2) Sheet 2: Absolute quantities of tau 4R and 3R tau isoforms in insoluble (left table) and soluble (right table) used to produce Fig. 3. Sheet 3: Abundances values (extracted ions chromatogram area under the curve) of the tau protein different PTMs, for insoluble (upper table) and soluble brain fractions (bottom panel), that were used to produce Figures 4, 5, 6 and 7. Sheet 4: Subjects characteristics used to produce Table 1. Sheet 5: Wilcoxon test’s p-value scores used to produce Table 2 and Supplementary Table 4.
DOI: 10.6084/m9.figshare.22895708
title: Specific post-translational modifications of soluble tau protein distinguish between Alzheimer’s disease and primary tauopathies

description: The Source Data file contains all data which graphs and tables of the manuscript are from : “Specific post-translational modifications of the soluble tau protein distinguish between Alzheimer’s disease and primary tauopathies”. Sheet 1: Uncropped Westernblot results (Fig2) Sheet 2: Absolute quantities of tau 4R and 3R tau isoforms in insoluble (left table) and soluble (right table) used to produce Fig. 3. Sheet 3: Abundances values (extracted ions chromatogram area under the curve) of the tau protein different PTMs, for insoluble (upper table) and soluble brain fractions (bottom panel), that were used to produce Figures 4, 5, 6 and 7. Sheet 4: Subjects characteristics used to produce Table 1. Sheet 5: Wilcoxon test’s p-value scores used to produce Table 2 and Supplementary Table 4.
DOI: 10.34740/kaggle/dsv/6002425
title: Google Trends
DOI: 10.5281/zenodo.7016474
title: Datasets and codes related to the unpublished manuscript "What makes birds' diverse flight possible?: Phylogenetic Comparative Analysis of avian alula morphology"

description: "alula_data_187.csv" is the Dataset 1 used in PGLS analysis including all species and "alula_data_162.csv" is the Dataset 2 used in PGLS analysis excluding species which migration distances were incalculable. "consensus187.tre" is the concensus tree used in PGLS analysis of Dataset1, and "consensus162.tre" is the concensus tree used in PGLS analysis of Dataset 2. "code.txt" includes three R scripts for (1) extracting the essential distribution data from the BirdLife distribution dataset for calculating migration distances, (2) caluculating centroids and migration distances of each species and (3) PGLS and phylogenetic signal analysis.
DOI: 10.5281/zenodo.7016473
title: Datasets and scripts related to the manuscript "What makes the diverse flight of birds possible? Phylogenetic comparative analysis of avian alula morphology"

description: "alula_data187.csv" and "alula_data162.csv" include the two duck sister species, Anas platyrhynchos and A. poecilorhyncha. The former lacks the migratory distance, while the latter contains the variable. "alula_data185.csv" and "alula_data160.csv" are similar to "alula_data187.csv" and "alula_data162.csv", respectively, but exclude the two duck species. "alula_data151.csv" and "alula_data130.csv" are similar to "alula_data185.csv" and "alula_data160.csv", respectively, but further exclude species based on female specimens. "consensus187.tre" is the consensus tree used for the phylogenetic comparative analyses. "scripts.txt" includes two R scripts for (1) calculating the migratory distance and (2) the phylogenetic comparative analyses.
DOI: 10.5281/zenodo.7247774
title: Datasets and scripts related to the unpublished manuscript "What makes birds' diverse flight possible?: Phylogenetic Comparative Analysis of avian alula morphology"

description: "alula_data_187.csv" is the Dataset 1 used in the PGLS analysis including all species and "alula_data_162.csv" is the Dataset 2 used in the PGLS analysis excluding species which migration distances were incalculable. "consensus187.tre" is the concensus tree used in the PGLS analysis of Dataset1, and "consensus162.tre" is the concensus tree used in the PGLS analysis of Dataset 2. "scripts.txt" includes three R scripts for (1) extracting the essential distribution data from the BirdLife distribution dataset for calculating migratory distances, (2) caluculating mean locations of distribution range and migratory distances of each species and (3) the PGLS and the phylogenetic signal analysis.
DOI: 10.5281/zenodo.7248450
title: Datasets and scripts related to the manuscript "What makes the diverse flight of birds possible? Phylogenetic comparative analysis of avian alula morphology"

description: "alula_data187.csv" and "alula_data162.csv" include the two duck sister species, Anas platyrhynchos and A. poecilorhyncha. The former lacks the migratory distance, while the latter contains the variable. "alula_data185.csv" and "alula_data160.csv" are similar to "alula_data187.csv" and "alula_data162.csv", respectively, but exclude the two duck species. "alula_data151.csv" and "alula_data130.csv" are similar to "alula_data185.csv" and "alula_data160.csv", respectively, but further exclude species based on female specimens. "consensus187.tre" is the consensus tree used for the phylogenetic comparative analyses. "scripts.txt" includes two R scripts for (1) calculating the migratory distance and (2) the phylogenetic comparative analyses.
DOI: 10.5281/zenodo.8047735
title: ARM precip data

description: TBR data from the ARM Lamont I10 site for MSc Maths4ML project at Bath Uni.
DOI: 10.5281/zenodo.8047734
title: ARM precip data

description: TBR data from the ARM Lamont I10 site for MSc Maths4ML project at Bath Uni.
DOI: 10.5281/zenodo.8073333
title: On the Outdatedness of Workflows in the GitHub Actions Ecosystem

description: This replication package contains all the material required to replicate the analyses we made for the paper entitled "On the Outdatedness of Workflows in the GitHub Actions Ecosystem" for Journal of Systems and Software. Refer to the README file(s) for more details on the content of this replication package.
DOI: 10.5281/zenodo.8073332
title: On the Outdatedness of Workflows in the GitHub Actions Ecosystem

description: This replication package contains all the material required to replicate the analyses we made for the paper entitled "On the Outdatedness of Workflows in the GitHub Actions Ecosystem" for Journal of Systems and Software. Refer to the README file(s) for more details on the content of this replication package.
DOI: 10.6084/m9.figshare.23566086
title: upload_data.Rdata

description: This dataset contains 26 m6a related genes of ovarian cancer
DOI: 10.6084/m9.figshare.23566086.v1
title: upload_data.Rdata

description: This dataset contains 26 m6a related genes of ovarian cancer
DOI: 10.6084/m9.figshare.23566122
title: The dataset of model averaged estimation of the restricted average survival causal effect

description: This dataset contains 26 m6a-related genes of ovarian cancer
DOI: 10.6084/m9.figshare.23566122.v1
title: The dataset of model averaged estimation of the restricted average survival causal effect

description: This dataset contains 26 m6a-related genes of ovarian cancer
DOI: 10.6084/m9.figshare.23566131
title: The dataset of model averaged estimation of the restricted average survival causal effect

description: The dataset includes 26 m6a related genes of ovarian cancer
DOI: 10.6084/m9.figshare.23566131.v1
title: The dataset of model averaged estimation of the restricted average survival causal effect

description: The dataset includes 26 m6a related genes of ovarian cancer
DOI: 10.15151/esrf-es-1251041225
title: Cryo-electron microscopy EPN BAG

description: At the EPN campus level structural biology work is carried out in all the 4 institutes (IBS, ESRF, ILL and EMBL). Today all structural biology groups are turning to cryo-EM. The EM demand is therefore extremely high and present in the 4 Institutes. In a nutshell, there are more than 45 PIs that could benefit from Krios time on the EPN campus (more than 90 different samples). Around 20 % of the sample are ready for high resolution data collection with already prepared grids that have been pre-screened on Glacios microscopes. Whereas some work could be carried out on Glacios microscopes, for difficult samples the use of a krios is indispensable (heterogeneous sample or limited concentration requiring a large number of images; small protein etc). Only these samples will be selected for Krios time at the BAG level
DOI: 10.6084/m9.figshare.23566125
title: All_expressed_transcripts

description: The spreadsheet document contains all expressed transcripts in all genotype x treatment combinations in at least two out of in total three samples. Expressed values are presented in transcripts per million (tpm).
DOI: 10.25442/hku.21904359
title: Effects of Sleep Deprivation on Habitual Control of Food-Seeking: A Randomized Crossover Experiment - Data and Codes

description: The uploaded files are data and codes for the study Effects of Sleep Deprivation on Habitual Control of Food-Seeking: A Randomized Crossover Experiment. This manuscript is currently submitted for review. <br> Description of uploaded files: <br> codes_2023_06_23 contains the R codes running all the analysis using the following datafiles: data_allparticipants.csv contains the PIT testing data data_participants_success_learning.csv contains the data of the PIT training quiry trials data_participants_success_recall.csv contains the data of PIT testing quiry trials demographic.csv contains demographic data covariates.csv contains the data of go no go, working memory, and delay discounting calorie_data.csv contains data of caloric consumption during satiation <br> <br>
DOI: 10.25442/hku.21904359.v2
title: Effects of Sleep Deprivation on Habitual Control of Food-Seeking: A Randomized Crossover Experiment - Data and Codes

description: The uploaded files are data and codes for the study Effects of Sleep Deprivation on Habitual Control of Food-Seeking: A Randomized Crossover Experiment. This manuscript is currently submitted for review. <br> Description of uploaded files: <br> codes_2023_06_23 contains the R codes running all the analysis using the following datafiles: data_allparticipants.csv contains the PIT testing data data_participants_success_learning.csv contains the data of the PIT training quiry trials data_participants_success_recall.csv contains the data of PIT testing quiry trials demographic.csv contains demographic data covariates.csv contains the data of go no go, working memory, and delay discounting calorie_data.csv contains data of caloric consumption during satiation <br> <br>
DOI: 10.25442/hku.21904359.v1
title: Effects of Sleep Deprivation on Habitual Control of Food-Seeking: A Randomized Crossover Experiment - Data and Codes

description: The uploaded files are data and codes for the study Effects of Sleep Deprivation on Habitual Control of Food-Seeking: A Randomized Crossover Experiment. This manuscript is currently under review. <br> Abstract: Prior research suggests that sleep loss may intensify habitual control of behavior, increasing cue-elicited eating that is insensitive to outcome devaluation. No previous studies have examined the effects of sleep deprivation on habitual control of food-seeking behavior. Therefore, the present study aimed to evaluate the effects of one-night total sleep deprivation (TSD) on cue-elicited food-seeking and its interaction with satiation and food palatability. It was hypothesized that TSD would lead to greater cue-elicited food-seeking that is insensitive to satiation especially when the food outcome is highly palatable. Ninety-six adults participated in this within-individual, randomized, crossover experiment, with a three-day washout period in between the TSD and normal sleep duration (NSD) conditions. Participants completed the Pavlovian-instrumental transfer (PIT) paradigm, adopted to measure the degree to which conditioned cues influenced the vigor of food-seeking responses. One-night TSD was not found to increase cue-elicited food-seeking. However, cue-elicited food-seeking was less sensitive to satiation following TSD; food-seeking responses reduced by 13% after satiation in the NSD condition compared to 1% in TSD. Pavlovian cues enhanced food-seeking responses only when the food reward was highly palatable as opposed to low-palatable food, even when subjective liking of food was controlled. To conclude, the present study for the first time showed that sleep deprivation influenced one’s modulation of cue-elicited food-seeking following satiation and that conditioned cues only influenced the motivation for highly palatable food but not low-palatability food. <br> Description of uploaded files: <br> codes_R contains the R codes running all the analysis using the following datafiles: data_allparticipants.csv contains the PIT testing data data_participants_success_learning.csv contains the data of the PIT training quiry trials data_participants_success_recall.csv contains the data of PIT testing quiry trials demographic.csv contains demographic data covariates.csv contains the data of go no go, working memory, and delay discounting calorie_data.csv contains data of caloric consumption during satiation <br> <br>
DOI: 10.6084/m9.figshare.22309213.v13
title: Targeting Cancer Cell Signaling Using Precision Oncology Towards a Holistic Approach to Cancer Therapeutics

description: Cancer is a complex and multifaceted disease having a number of composite problems to be considered including cancer immune evasion, therapy resistance, and recurrence for prevention and cure. Fundamentally it remains a genetic disease as diverse aspects of the complexity of tumor growth and cancer development relate to its genetic machinery and requires addressing the problems at the level of genome and epigenome. Presumably, the mutational changes occurring in the regulatory genes responsible for maintaining optimal cell growth, proliferation, and differentiation gradually lead to cancer progression and metastasis. Importantly, patients with the same cancer types respond differently to cancer therapies, indicating the need for a patient-specific treatment option for cancer cure. Precision oncology is the field of cancer research that focuses on the genetic profiling of individual tumors to identify targetable alterations involved in cancer development for custom-tailored personalized treatment of the disease. It is to rely upon the genomic study of cancer cells to get a clear picture of the prognosis and pathways involved in disease progression and to look for the means to selectively target them to ensure effective treatment of this deadly disease. Thus, precision oncology combines cancer diagnosis and prognosis followed by designing a treatment regimen for precise treatment of cancer at different stages and times. This article aims to briefly explain the foundations and frontiers of precision oncology in the context of technological advances being made in this direction to assess its scope and importance in the realization of a proper cure for cancer.
DOI: 10.6084/m9.figshare.22309213.v12
title: Targeting Cancer Cell Signaling Using Precision Oncology Towards a Holistic Approach to Cancer Therapeutics

description: Cancer is a complex and multifaceted disease having a number of composite problems to be considered including cancer immune evasion, therapy resistance, and recurrence for prevention and cure. Fundamentally it remains a genetic disease as diverse aspects of the complexity of tumor growth and cancer development relate to its genetic machinery and requires addressing the problems at the level of genome and epigenome. Presumably, the mutational changes occurring in the regulatory genes responsible for maintaining optimal cell growth, proliferation, and differentiation gradually lead to cancer progression and metastasis. Importantly, patients with the same cancer types respond differently to cancer therapies, indicating the need for a patient-specific treatment option for cancer cure. Precision oncology is the field of cancer research that focuses on the genetic profiling of individual tumors to identify targetable alterations involved in cancer development for custom-tailored personalized treatment of the disease. It is to rely upon the genomic study of cancer cells to get a clear picture of the prognosis and pathways involved in disease progression and to look for the means to selectively target them to ensure effective treatment of this deadly disease. Thus, precision oncology combines cancer diagnosis and prognosis followed by designing a treatment regimen for precise treatment of cancer at different stages and times. This article aims to briefly explain the foundations and frontiers of precision oncology in the context of technological advances being made in this direction to assess its scope and importance in the realization of a proper cure for cancer.
DOI: 10.5281/zenodo.8073260
title: pavel-fibich/disturbance-agents: tifsANDdata

description: Complete input data with modeled and projected models stored in geotifs.
DOI: 10.5281/zenodo.8073259
title: pavel-fibich/disturbance-agents: tifsANDdata

description: Complete input data with modeled and projected models stored in geotifs.
DOI: 10.5281/zenodo.7995646
title: Dataset for "Imaging frontside and backside attack in radical ion-molecule reactive scattering"

description: Dataset for "Imaging frontside and backside attack in radical ion-molecule reactive scattering"
DOI: 10.5281/zenodo.7995645
title: Dataset for "Imaging frontside and backside attack in radical ion-molecule reactive scattering"

description: Dataset for "Imaging frontside and backside attack in radical ion-molecule reactive scattering"
DOI: 10.6084/m9.figshare.23566149
title: <strong>W</strong><strong>ater management in northwest of Mexico</strong>

description: National Census of Municipal Governments and Territorial Demarcations of Mexico City in 2019 (Census) data about the statistical and geographic information on the management and performance of the institutions that make up the Public Administration of each municipality with respect to drinking water and sanitation functions for the years 2017, 2018, and 2019. The information is related to the drinking water service from the public network, water collection for public supply, drinking water plants, and administration. The dataset covers 109 municipalities from the Baja California peninsula and the Pacific coast in the Northwest region of Mexico, representing 90.83% of all municipalities. Due to missing data, 11 municipalities were eliminated from the dataset.
DOI: 10.34740/kaggle/dsv/6002918
title: AutoXGB
DOI: 10.48420/23547975
title: Data for 289 peer-reviewed empirical journal articles on the weather effects on the spread of COVID-19

description: This Excel spreadsheet contains the data used in Tan and Schultz (2023). <br> These data consist of 289 peer-reviewed empirical journal articles on the relationship between weather and COVID-19 during 2020 and 2021. These data also include 24 review articles on the same topic. <br> Tan, L., and D. M. Schultz, 2023: Weather effects on the spread of COVID-19: Characteristics and critical analysis of the first and second years of scientific research. <em>Bull. Amer. Meteor. Soc.,</em> https://doi.org/10.1175/BAMS-D-23-0071.1.
DOI: 10.48420/23547975.v1
title: Data for 289 peer-reviewed empirical journal articles on the weather effects on the spread of COVID-19

description: This Excel spreadsheet contains the data used in Tan and Schultz (2023). <br> These data consist of 289 peer-reviewed empirical journal articles on the relationship between weather and COVID-19 during 2020 and 2021. These data also include 24 review articles on the same topic. <br> Tan, L., and D. M. Schultz, 2023: Weather effects on the spread of COVID-19: Characteristics and critical analysis of the first and second years of scientific research. <em>Bull. Amer. Meteor. Soc.,</em> https://doi.org/10.1175/BAMS-D-23-0071.1.
DOI: 10.34740/kaggle/dsv/6002910
title: LUFlow Network Intrusion Detection Data Set
DOI: 10.5281/zenodo.7391340
title: Dataset for FigS2F in "DNA is the allosteric driver for the asymmetric binding of homodimer estrogen-related receptor"

description: <strong>Abstract</strong> The estrogen-related receptors (ERRs, NR3B), orphan members of the steroid hormone receptor (SR) subfamily (NR3), are crucial for the transcriptional control of cellular energy metabolism. As basal members of NR3 subfamily, the ERRs are key elements for the understanding of how the binding of SRs to DNA evolved from monomeric to dimeric palindromic binding sites. To unravel the initial steps of DNA selection by SRs, we combined structural, biophysical and phylogenetic studies. Our results unveil the molecular mechanisms of the ERR dimerization which are imprinted in the protein itself with DNA acting as an allosteric driver by allowing the formation of a novel extended asymmetric dimerization region (KR-box). Phylogenetic analyses suggest that the dimerization asymmetry used by ERRs is an ancestral feature necessary for establishing a strong overall dimerization interface, which was progressively lost in the course evolution by other SRs. <strong>Methods</strong> Ancestral character reconstruction and stochastic mapping were performed under R version 4.1.2 using the make.simmap function as implemented in the phytools package version 1.0-1. Character evolution was inferred using a model of symmetrical transition rates between the character states (SYM). 10 000 character histories were sampled to allow the incorporation of the uncertainty associated with the transition between different states. Inferred state frequencies for ancestral nodes were plotted using the describe.simmap function. <strong>Usage Notes</strong> This dataset contains all the files necessary to reproduce Figure S2 of the associated paper (Patel et al., in preparation). Those files are: - script_FigS2F.R : the R script necessary to load the data and process them as indicated in the methods section. The outputs of character mappings are also indicated in the script file, in order that the user can compare them with the results he would get on his/her own computer. - tree_FigS2F.nex: the backbone tree used for character mapping - FigS2F_KR_box.csv: the data table containing the presence-absence data regarding the KR box motif for each nuclear receptor.