cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/b2mj3s
title: Salix pseudopentandra in the Herbarium (MAG) of the Institute of Biological Problems of the North, Far East Branch RAS

description: The Herbarium of the Institute of Biological Problems of the North, Far East Branch RAS (IBPN FEB RAS), was founded in 1970 by A.P. Khokhryakov. The collection representing more than 1,700 species of vascular plants comprises more than 110,000 samples. The collection also includes fungi, lichens and mosses. Collections from Magadan Region, Chukotka, Kamchatka and other regions of the Russian Far East constitute the major part of the holdings. At the initiative of A.N. Berkutenko, the international acronym (MAG) was assigned to the Herbarium in 1997 and registered in the Index Herbariorum. Vascular plants are arranged according to the Engler system, genera are given numbers by Dalla Torre, inside genera they are arranged in alphabetical order. The geographical principle of distribution is also observed. The target area for the regional herbarium is Magadan Region. Flora of Magadan Region comprises about 1,450 species and subspecies (Flora…, 2010), including 39 species in genus Salix L.
DOI: 10.6084/m9.figshare.12045582
title: Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals

description: Supplementary tables for the Paper published
DOI: 10.6084/m9.figshare.12045582.v12
title: Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals

description: Supplementary tables for the Paper published
DOI: 10.6084/m9.figshare.12045582.v11
title: Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals

description: Supplementary tables for the Paper published
DOI: 10.6084/m9.figshare.13159190
title: Additional file 1 of Development and validation of a novel stem cell subtype for bladder cancer based on stem genomic profiling

description: Additional file 1 : Table S1. The 26 stem gene sets used for identification of BLCA subtype. BLCA: Bladder cancer. Figure S1. Clustering heat map of stem cell subtype in (A) E-MTAB-4321, (B) GSE13507, (C) GSE31684, (D) GSE32548, and (E) GSE32894. Figure S2. Evaluation of immune cell infiltration level, tumor purity, and stromal content in BLCA. (A–F) Immune score, (G–L) stromal score (stromal content), and (M–R) tumor purity in all six datasets. *P &lt; 0.05, **P &lt; 0.01, ***P &lt; 0.001; ns means not significant. BLCA: bladder cancer. Figure S3. Comparisons of the expression levels of immune-related genes between BLCA subtypes. (A–C) Expression levels of HLA genes between BLCA subtypes in TCGA, E-MTAB-4321 and GSE32894. (D–E) Expression levels of immune cell subgroup marker genes between BLCA subtypes. Kruskal–Wallis test, *P &lt; 0.05, **P &lt; 0.01, ***P &lt; 0.001; ns means not significant. BLCA: bladder cancer. Figure S4. Difference analysis of 22 human immune cell subgroups of BLCA stem cell subtypes in CIBERSORT. Immune cell subgroups with significant differences in BLCA stem cell subtypes in (A) TCGA, (B) GSE32894, (C) GSE31684, (D) E-MTAB-4321, (E) GSE13507, and (F) GSE32548 cohort with CIBERSORT. Fraction of different immune cell subgroups among the four subtypes evaluated using Kruskal–Wallis tests, * P &lt; 0.05, ** P &lt; 0.01, *** P &lt; 0.001. Kaplan–Meier survival curve based on median ssGSEA score for (G) TCGA, (H) GSE13507, (I) GSE32548, and (J) GSE32894, and best cut-off for (K) E-MTAB-4321 cohort in OS for macrophage M0, together with median ssGSEA score for (L) TCGA in OS for macrophage M2. BLCA: bladder cancer; TCGA: The Cancer Genome Atlas. Table S2. Univariate Cox analysis for all six datasets. Table S3. GSEA for BLCA stem cell subtypes.
DOI: 10.5281/zenodo.4152438
title: Replication Package for the Paper: "An Empirical Analysis of the Manual Detection of Code Smells via Code Review"

description: This repository contains the data and results from the paper "An Empirical Analysis of the Manual Detection of Code Smells via Code Review" submitted to SANER 2021. <strong>1. "data.zip" file contains the following three folders: </strong> <strong>1). data folder</strong> The data folder contains the retrieved 1,174 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell, Code Smell Discussion, and Source Code URL. <strong>2). scripts folder</strong> The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms. <em>keywords.txt</em> contains the keywords keywords asociated with code smells, such as "smell, duplication, and dead". <em>get_changes.py</em> is used for getting code changes from OpenStack. <em>get_comments.py</em> is used for getting review comments for each code change. <em>keywords_search.py</em> is used for searching review comments that contain at least one keyword. keywords_improve.py is used for improving the keyword-based mining approach. tools.py is used for supporting the process of keywords improving. <strong>3). project folder</strong> The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download. <em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool. <em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool. <strong>2. Keywords associated with code smells.pdf</strong> This file contains the final set of keywords asociated with code smells that we identified by following the systematic approach proposed by Bosu and his colleagues in their paper: Identifying the Characteristics of Vulnerable Code Changes: An Empirical Study, FSE 2014.
DOI: 10.5281/zenodo.4152437
title: Replication Package for the Paper: "An Empirical Analysis of the Manual Detection of Code Smells via Code Review"

description: This repository contains the data and results from the paper "An Empirical Analysis of the Manual Detection of Code Smells via Code Review" submitted to SANER 2021. <strong>1. "data.zip" file contains the following three folders: </strong> <strong>1). data folder</strong> The data folder contains the retrieved 1,174 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell, Code Smell Discussion, and Source Code URL. <strong>2). scripts folder</strong> The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms. <em>keywords.txt</em> contains the keywords keywords asociated with code smells, such as "smell, duplication, and dead". <em>get_changes.py</em> is used for getting code changes from OpenStack. <em>get_comments.py</em> is used for getting review comments for each code change. <em>keywords_search.py</em> is used for searching review comments that contain at least one keyword. keywords_improve.py is used for improving the keyword-based mining approach. tools.py is used for supporting the process of keywords improving. <strong>3). project folder</strong> The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download. <em>Data Labeling & Encoding for RQ2.mx12</em> is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool. <em>Data Labeling & Encoding for RQ3.mx12</em> is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool. <strong>2. Keywords associated with code smells.pdf</strong> This file contains the final set of keywords asociated with code smells that we identified by following the systematic approach proposed by Bosu and his colleagues in their paper: Identifying the Characteristics of Vulnerable Code Changes: An Empirical Study, FSE 2014.
DOI: 10.6084/m9.figshare.13158476.v1
title: Reference-grade genome sequences and annotations of three diploid cotton species

description: The reference-grade cotton genome assemblies and annotation of <i>Gossypium rotundifolium</i> (<sub>K2</sub>), <i>G. arboreum</i> (<sub>A2</sub>) and <i>G. raimondii</i> (<sub>D5</sub>) using Oxford Nanopore sequencing technology.
DOI: 10.6084/m9.figshare.13158467.v1
title: Reference-grade genome sequences and annotations of three diploid cotton species

description: The reference-grade cotton genome assemblies and annotation of <i>Gossypium rotundifolium</i> (<sub>K2</sub>), <i>G. arboreum</i> (<sub>A2</sub>) and <i>G. raimondii</i> (<sub>D5</sub>) using Oxford Nanopore sequencing technology.
DOI: 10.6084/m9.figshare.13158479.v1
title: eference-grade genome sequences and annotations of three diploid cotton species

description: The reference-grade cotton genome assemblies and annotation of <i>Gossypium rotundifolium</i> (<sub>K2</sub>), <i>G. arboreum </i>(<sub>A2</sub>) and <i>G. raimondii</i> (<sub>D5</sub>) using Oxford Nanopore sequencing technology.
DOI: 10.6084/m9.figshare.13158479.v2
title: reference-grade genome sequences and annotations of Gossypium rotundifolium (K2)

description: The reference-grade cotton genome assemblies and annotation of <i>Gossypium rotundifolium</i> (K<sub>2</sub>) using Oxford Nanopore sequencing technology.
DOI: 10.34740/kaggle/dsv/1601468
title: COVID-19 Indonesia Dataset
DOI: 10.17632/b5gwh2y65d.5
title: Auditory DID: ERP signature of target processing

description: Data from a behavioral study including the factors 'distractor number' (0,1,or n), cue-target SOA (0 va 300 ms), and presentation mode (separated vs superimposed streams). Data from an ERP experiment including the factors 'cue-alone vs cue+target', 'hit vs miss', and electrode position. PsychoPy Presentation Code and Stimulus Material Results of a randomization test (repeated t-tests for randomly selected subsamples, including a control with random assignment of conditions=
DOI: 10.17632/kxffj7rzhg.4
title: Data for: The Potential of Material Productivity alongside Energy Productivity in Climate Mitigation: Evidence from Convergence Tests in the EU28

description: This document present data and code files used in the paper "The Potential of Material Productivity alongside Energy Productivity in Climate Mitigation: Evidence from Convergence Tests in the EU28".
DOI: 10.17632/8kvs86k6c4.1
title: Sustainable Housing Assessment Tool (SHAT): An Indicator Set

description: This data file is related to the manuscript "How to measure sustainable housing: A proposal for an indicator-based assessment tool". The data file presents an original indicator set of SHAT (Sustainable Housing Tool Assessment) operationalizing the Geneva UN Charter on Sustainable Housing. It consists of 55 proposed indicators, where 11 of them are extended by, in total, 53 dashboard single indicators. The data include proposed indicators' names, description, units, information about sources, initial phenomenons derived from the Geneva Geneva UN Charter on Sustainable Housing and categorization of proposed indicators (sustainability dimensions, sustainable housing components and types of indicators).
DOI: 10.6084/m9.figshare.13158479.v3
title: Reference-grade genome sequences and annotations of Gossypium rotundifolium (K2)

description: The reference-grade cotton genome assemblies and annotation of <i>Gossypium rotundifolium</i> (K<sub>2</sub>) using Oxford Nanopore sequencing technology.
DOI: 10.6084/m9.figshare.13158476.v2
title: Reference-grade genome sequence and annotation of Gossypium raimondii (D5)

description: The reference-grade cotton genome assemblies and annotations of <i>Gossypium </i><i>raimondii</i> (D<sub>5</sub>) using Oxford Nanopore sequencing technology.
DOI: 10.17632/xjt3r82tv7.1
title: Okamoto et al. Raw data set 2020.10.27

description: Raw data for Figures
DOI: 10.17632/6x5bkz42k7.1
title: Amygdala gene expression

description: Amygdala gene expression profiles in rats exposed to social defeat- and witness stress. Data was generated with NanoString analysis using a custom code set containing 383 genes. Supporting table to "Avp expression in the amygdala is positively correlated with stress-induced comorbid escalated alcohol intake and anxiety-like behavior" by Barchiesi et al.
DOI: 10.17632/x2jxhx6rhw.1
title: Medfly dataset

description: Medfly dataset from the field
DOI: 10.17632/b7bc9y232m.2
title: Data Acquired by a Single Object Sensor (IMU) of Table Tennis Forehand Strokes

description: The sensory data were collected from a total of 16 Table Tennis players mixed gender, aged between 19 and 38 years, who used the IMU mounted Racket. We considered the Basic, Topspin, and Push as the sample type of performed Forehand strokes. The Table Tennis Forehand strokes quality evaluation values were collected from a total of 3 Table Tennis highly educated and ranked coaches who manually scored the performed strokes based on the experiment evaluation metrics. The players used the IMU mounted racket when samples were collecting. Each subject's performance was evaluated, scored, and labeled by the coaches who placed around Table Tennis's table. Acquiring simultaneously by the Racket, the strokes' evaluation metrics values, and their labels, each player carried out a predetermined stroke performing protocols when data was gathering. Capturing order of the samples are: 1) the players started performing strokes, 2) paused for five seconds by the coaches at the end of each stroke performing, 3) stored the sensory data by the software into a single CSV file, 4) labeled and scored the players' performance by the coaches manually.
DOI: 10.17632/3kthrpngct.1
title: grain parameters

description: EBSD data for grain parameters of mylonite developed from troctolite. The sample has been dredged at 16.5°N along the Mid Atlantic Ridge during the The RV Knorr cruise 210 Leg 5. Each sample and sub-sample contain consists of several grain parameters such as: i) grain area, ii) grain size, iii) Axial ratio, iv) convexity, v) tortuosity, vi) shape factor and vii) solidity. All these parameters are provided for all minerals of the assemblage plagioclase + olivine + pyroxene + Ti-pargasite.
DOI: 10.17632/sdpnh7c3zk.1
title: Data for MARGO-D-20-00181
DOI: 10.17632/5383t3p7t6.1
title: eWOM & B5M-Research Data

description: Dataset consists of 647 participants in Vietnam regarding their behavioral intention for tourism destinations. Potential participants were identified as individuals wishing to travel or planning to travel in the coming year and using social networking sites (i.e. Facebook and Instagram) which were the most popular social networks in Vietnam. The data analysis shows that personality (specifically the traits of agreeableness, extraversion, and imagination) affects information adoption regarding tourism destinations. However, the impact of personality on behavioral intention could only be partly explained by IAM, suggesting that other variables play a role. The findings suggest avenues for future research linking personality and eWOM, as well as ways for companies to improve their customer targeting and advertising content that can be involved in eWOM.
DOI: 10.17632/586yjn978x.1
title: Fleas are parasitic scorpionflies
DOI: 10.17632/mvn2yv7mvj.2
title: Mutale River Hydrometeological Data

description: River gage and weather station data from the Mutale River, Limpopo, South Africa. Stations: Mbehela (22.810210 S, 30.452066 E), Mutale Weir (22.772766 S, 30.536355 E) ***This is archived data. Due to funding requirements, the data will be kept current on the project website, duq.edu/limpopo, and click on Data. This links to the USAID data repository, https://data.usaid.gov/Environment/Limpopo-Resilience-Lab-Hydrology-and-Meteorology-D/kd6k-e7uv. ***
DOI: 10.17632/m3y5mf57br.1
title: Data set ; The expert-level distinction of systemic sclerosis from hand photographs using the deep convolutional neural network

description: Dataset
DOI: 10.17632/v7bd34dpsp.1
title: ATBU_Bauchi_Micrclimate Data & Simulation Outputs
DOI: 10.17632/zyv26t6x5r.1
title: Draft genome assembly dataset of four prospective probiotic Bifidobacterium strains

description: Draft genome sequences dataset of four Bifidobacterium strains is presented. Genomic DNA was isolated from pure cultures of four Bifidobacterium strains from Russian National Collection of Industrial Microorganisms (VKPM): B. adolescentis VKPM=Ac-1245, B. bifidum VKPM=Ac-1579, B. longum subsp. longum VKPM=Ac-1635, B. bifidum VKPM=Ac-1784. Genome sequencing was performed on Illumina Miseq system. De novo genome assembly and annotation was made using ZGA pipeline (https://github.com/laxeye/zga/) and resulted in four high-quality draft genomes with high completeness and low contamination levels. Genes related to utilization of human milk oligosaccharides and mucin were identified as well as bite salt hydrolase. Genome of B. bifidum VKPM=Ac-1784 showed presence of two putative bacteriocin gene clusters.
DOI: 10.17632/rc6wk4btnj.1
title: Data for: “Selection of Optimal Geometrical Profile for Design and Development of D12-D45, 3 Leg Bezier Curve Governed Flexural Suspension for Micro Drill Machine Tool.”

description: ANOM, ANNOVA,INTERACTION PLOTS,REGRESSION ANALYSIS
DOI: 10.17632/n5cs6wjpjp.1
title: Data for "Cellular control of viscosity counters changes in temperature and energy availability"

description: Raw data for "Cellular control of viscosity counters changes in temperature and energy availability". File contents are as follows: Raw Data 1.zip: Example FRAP movies Raw Data 2.zip: FRAP data for t-half Determination using easyFRAP Raw Data 3.zip: FRAP movies for diffusion coefficient determination using simFRAP Descriptions: Raw Data 1. Example FRAP movies, Related to Figures 2-5 and 7 and Figures S2-4, S6, and S7. Containing the following sub-folders: Movies 1. FRAP on GFP in cells transferred to multiple temperatures, non-steady state, Related to Figure 2B Movies 2. FRAP on GFP in cells in logarithmic growth at steady state for multiple temperatures, Related to Figure 2D Movies 3. FRAP on GFP in cells acutely heat shocked at 42°C in strains with and without impaired synthesis of glycogen, trehalose, or both, Related to Figure 3C Movies 4. FRAP on GFP in cells recovered from heat shocked with and without DAB and Validamycin A treatment, Related to Figure 3D Movies 5. FRAP on GFP in cells experiencing different conditions of nutrient deprivation, Related to Figures 4E and S4B Movies 6. In vitro FRAP on purified GFP in solutions of varying glycogen and trehalose content at 22°C and 40°C, Related to Figure 5A Movie 7. Magnetic beads puncture an inclusion in a lysate from cells heat shocked at 45°C for 30 minutes prior to lysis. Beads begin on one edge of the lysate and are drawn through the lysate by use of a strong magnet. and images are taken at 10x using brightfield illumination on an epifluorescent microscope, Related to Figure 6B-C Movies 8. FRAP on GFP in the Reg1 knockout strain in logarithmic growth and stationary phase, Related to Figures 6F and S6F. Movies 9. FRAP on GFP in wildtype yeast treated with the mitochondrial poisons sodium azide, sodium arsenite, or a combination of Antimycin A, Oligomycin A, and FCCP, with an untreated control, Related to Figure 7A. Raw Data 2. Data extracted from in vitro and in vivo FRAP movies for the determination of t-half values, Related to Main Figures 1-5 and 7 and Figures S2-4, S6, and S7. Data is in the form of excel spreadsheets of the format [column 1: time, column 2: intensity of bleached region, column 3: intensity of unbleached control region, and column 4: intensity of a non-fluorescent background region]. Spreadsheets were used as the input for the online tool easyFRAP (Koulouras et al., 2018). Related to Figures 1-7 and Figures S2-4,S6-7. Raw Data 3. Unprocessed FRAP movies used for determination of the diffusion coefficient of GFP in vitro and in vivo. Movies were used directly with the imagej software simFRAP (Blumenthal et al., 2015). Related to Figures 1 and 2.
DOI: 10.5281/zenodo.3958837
title: Replication Package for the Paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List"

description: This is the replication package for the paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List". It contains the source code and dataset of our experiment for the replication by other researchers. In the meanwhile, we provide brief description of the files in the replication package below. <strong>1. code folder</strong> <em>experiment.py </em>contains the source code for our experiment, which is conducted on Windows 10 and Python 3.7.0. <strong>Note that you may get slightly</strong> <strong>different experiment results when conducting the experiments on different environment configurations.</strong> <em>requirement.txt</em> records all the installation packages and their version numbers needed for the current program to run. You can use "<em>pip install -r requirement.txt</em>" to rebuild the project and install all dependencies. <strong>Note that you may get slightly different experiment results when using different packages or versions. </strong> <strong>2. dataset folder</strong> <em>decisions.xlsx </em>contains 844 labelled sentence-level decisions from the Hibernate developer mailing list.
DOI: 10.5281/zenodo.3958836
title: Replication Package for the Paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List"

description: This is the replication package for the paper: "A Machine Learning Based Ensemble Method for Automatic Classification of Decisions: A Study of the Hibernate Developer Mailing List". It contains the source code and dataset of our experiment for the replication by other researchers. In the meanwhile, we provide brief description of the files in the replication package below. <strong>1. code folder</strong> <em>experiment.py </em>contains the source code for our experiment, which is conducted on Windows 10 and Python 3.7.0. <strong>Note that you may get slightly</strong> <strong>different experiment results when conducting the experiments on different environment configurations.</strong> <em>requirement.txt</em> records all the installation packages and their version numbers needed for the current program to run. You can use "<em>pip install -r requirement.txt</em>" to rebuild the project and install all dependencies. <strong>Note that you may get slightly different experiment results when using different packages or versions. </strong> <strong>2. dataset folder</strong> <em>decisions.xlsx </em>contains 844 labelled sentence-level decisions from the Hibernate developer mailing list.
DOI: 10.17632/f8fx53r5yj.1
title: SUPPLEMENTARY FILES FOR FLEXURAL SPINDLE HEAD

description: The supplementary files contain the relevant files releated to project: a)MATLAB code b)Final MATLAB output generated for Aluminium Specimen c)Final Drilled Test Specimens by Flexural Spindle Head