cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5327599
title: Table 2. Published ethnobotanical studies made within the original areas of Caatinga. Abbreviations: ART (Number of articles); AUTHORS; URB (Urbanization level of studied community); COM (Type of community studied), LR (Local residents), RA (Raizeiros), RB (Rezadores and Benzedores), ST (Sem Terras), QL (Quilombolas), IN (indigenous groups); FIT (Phytophysiognomy related to the study): SW (Shrubby/Woody), WO (Woody), SH (Shrubby), PA (Park), CA (Carrasco), RF (Riparian Forest); STA

description: Table 2
DOI: 10.6084/m9.figshare.5327596
title: Table 1. Published ethnobotanical studies made within the original areas of Atlantic Forest. Abbreviations: ART (Number of articles); AUT; URB (Urbanization level of studied community); NU (Non-urbanized), U (Urbanized), NU/U (Works made in urbanized and non-urbanized locations); COM (Type of community studied): CA (Caiçaras), ID (Italian descendants), GD (German descendants), GI (German and Italian descendants), AF (Artisanal fisherman), SI (Sitiantes), AZ (Azoreans), PR (Producers), QL (Quilom

description: Table 1
DOI: 10.6084/m9.figshare.5327713.v1
title: Data versjon 01.01.15 PLOS ONE.sav

description: Data used in study "Prevalence of several somatic diseases depends on the presence and severity of obstructive sleep apnea."<br>The objective was to investigate the prevalence of heart attack, angina pectoris, stroke, hypertension, diabetes mellitus, chronic obstructive pulmonary disease, asthma and obesity in relation to the presence and severity of obstructive sleep apnea. <br>The sample consisted of 1887 patients, with mean age of 48.6 years (range 16-83 years), referred to a university hospital on suspicion of obstructive sleep apnea. The patients filled out a questionnaire asking whether they were previously diagnosed with the comorbidities in interest. Obstructive sleep apnea was diagnosed and categorised based on a standard respiratory polygraphic sleep study using a type 3 portable monitor. The patients' weight, height and blood pressure were measured during the consultations.
DOI: 10.6084/m9.figshare.5327593
title: Published ethnobotanical studies made within the original areas of Atlantic Forest. Abbreviations: ART (Number of articles); AUT; URB (Urbanization level of studied community); NU (Non-urbanized), U (Urbanized), NU/U (Works made in urbanized and non-urbanized locations); COM (Type of community studied): CA (Caiçaras), ID (Italian descendants), GD (German descendants), GI (German and Italian descendants), AF (Artisanal fisherman), SI (Sitiantes), AZ (Azoreans), PR (Producers), QL (Quilombola.docx

description: Table 1<br><br><br>
DOI: 10.6084/m9.figshare.5327596.v1
title: Table 1. Published ethnobotanical studies made within the original areas of Atlantic Forest. Abbreviations: ART (Number of articles); AUT; URB (Urbanization level of studied community); NU (Non-urbanized), U (Urbanized), NU/U (Works made in urbanized and non-urbanized locations); COM (Type of community studied): CA (Caiçaras), ID (Italian descendants), GD (German descendants), GI (German and Italian descendants), AF (Artisanal fisherman), SI (Sitiantes), AZ (Azoreans), PR (Producers), QL (Quilom

description: Table 1
DOI: 10.6084/m9.figshare.5327599.v1
title: Table 2. Published ethnobotanical studies made within the original areas of Caatinga. Abbreviations: ART (Number of articles); AUTHORS; URB (Urbanization level of studied community); COM (Type of community studied), LR (Local residents), RA (Raizeiros), RB (Rezadores and Benzedores), ST (Sem Terras), QL (Quilombolas), IN (indigenous groups); FIT (Phytophysiognomy related to the study): SW (Shrubby/Woody), WO (Woody), SH (Shrubby), PA (Park), CA (Carrasco), RF (Riparian Forest); STA

description: Table 2
DOI: 10.6084/m9.figshare.5327713.v3
title: Prevalence of several somatic diseases depends on the presence and severity of obstructive sleep apnea

description: Data used in study "Prevalence of several somatic diseases depends on the presence and severity of obstructive sleep apnea."<br>The objective was to investigate the prevalence of heart attack, angina pectoris, stroke, hypertension, diabetes mellitus, chronic obstructive pulmonary disease, asthma and obesity in relation to the presence and severity of obstructive sleep apnea. <br>The sample consisted of 1887 patients, with mean age of 48.6 years (range 16-83 years), referred to a university hospital on suspicion of obstructive sleep apnea. The patients filled out a questionnaire asking whether they were previously diagnosed with the comorbidities in interest. Obstructive sleep apnea was diagnosed and categorised based on a standard respiratory polygraphic sleep study using a type 3 portable monitor. The patients' weight, height and blood pressure were measured during the consultations.
DOI: 10.6084/m9.figshare.5327593.v1
title: Published ethnobotanical studies made within the original areas of Atlantic Forest. Abbreviations: ART (Number of articles); AUT; URB (Urbanization level of studied community); NU (Non-urbanized), U (Urbanized), NU/U (Works made in urbanized and non-urbanized locations); COM (Type of community studied): CA (Caiçaras), ID (Italian descendants), GD (German descendants), GI (German and Italian descendants), AF (Artisanal fisherman), SI (Sitiantes), AZ (Azoreans), PR (Producers), QL (Quilombola.docx

description: Table 1<br>
DOI: 10.6084/m9.figshare.5327713.v2
title: Prevalence of several somatic diseases depends on the presence and severity of obstructive sleep apnea

description: Data used in study "Prevalence of several somatic diseases depends on the presence and severity of obstructive sleep apnea."<br>The objective was to investigate the prevalence of heart attack, angina pectoris, stroke, hypertension, diabetes mellitus, chronic obstructive pulmonary disease, asthma and obesity in relation to the presence and severity of obstructive sleep apnea. <br>The sample consisted of 1887 patients, with mean age of 48.6 years (range 16-83 years), referred to a university hospital on suspicion of obstructive sleep apnea. The patients filled out a questionnaire asking whether they were previously diagnosed with the comorbidities in interest. Obstructive sleep apnea was diagnosed and categorised based on a standard respiratory polygraphic sleep study using a type 3 portable monitor. The patients' weight, height and blood pressure were measured during the consultations.
DOI: 10.6084/m9.figshare.5327527
title: Data cleaning EVI2

description: Scripts to clean EVI2 data obtained from the VIP lab (University of Arizona) website (https://vip.arizona.edu/about.php and https://vip.arizona.edu/viplab_data_explorer.php). Data obtained in 2012.- outlier detection and removal/replacement- alignment of 2 periods<br>The manuscript detailing the methods and resulting data sets has been accepted for publication in Nature Scientific Data (05/11/2019).<br>Instructions: use the R Markdown html file for instructions!<br>Code last manipulated and tested in R 3.4.3 ("Kite-Eating Tree")
DOI: 10.6084/m9.figshare.5327536.v1
title: 4 DFA

description: Script to run Dynamic Factor Analysis. EVI2 is the response variable. Same code is run for all 4 clusters, with different input files (see separate item in collection)
DOI: 10.6084/m9.figshare.5327413.v2
title: chinese politics.docx

description: This research was based on a need to interpret the role of China as a global power. Its methodology is predominantly analytical. Appropriate citations have been provided.
DOI: 10.6084/m9.figshare.5327065
title: RIFT: A Rule Induction Framework for Twitter Sentiment Analysis

description: The rapid evolution of microblogging and the emergence of sites such as Twitter have propelled online communities to flourish by enabling people to create, share and disseminate free-flowing messages and information globally. The exponential growth of product-based user reviews has become an ever-increasing resource playing a key role in emerging Twitter-based sentiment analysis (SA) techniques and applications to collect and analyse customer trends and reviews. Existing studies on supervised black-box sentiment analysis systems do not provide adequate information, regarding rules as to why a certain review was classified to a class or classification. The accuracy in some ways is less than our personal judgement. To address these shortcomings, alternative approaches, such as supervised white-box classification algorithms, need to be developed to improve the classification of Twitter-based microblogs. The purpose of this study was to develop a supervised white-box microblogging SA system to analyse user reviews on certain products using rough set theory (RST)-based rule induction algorithms. RST classifies microblogging reviews of products into positive, negative, or neutral class using different rules extracted from training decision tables using RST-centric rule induction algorithms. The primary focus of this study is also to perform sentiment classification of microblogs (i.e. also known as tweets) of product reviews using conventional, and RST-based rule induction algorithms. The proposed RST-centric rule induction algorithm, namely Learning from Examples Module version: 2, and LEM2 +" role="presentation" style="box-sizing: border-box; display: inline-table; line-height: normal; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;"&gt;++ Corpus-based rules (LEM2 +" role="presentation" style="box-sizing: border-box; display: inline-table; line-height: normal; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative;"&gt;++ CBR),which is an extension of the traditional LEM2 algorithm, are used. Corpus-based rules are generated from tweets, which are unclassified using other conventional LEM2 algorithm rules. Experimental results show the proposed method, when compared with baseline methods, is excellent, with regard to accuracy, coverage and the number of rules employed. The approach using this method achieves an average accuracy of 92.57% and an average coverage of 100%, with an average number of rules of 19.14.
DOI: 10.6084/m9.figshare.5326900
title: Dataset for: A proteomic analysis of contextual fear conditioned rats reveals dynamic modifications in neuron and oligodendrocyte protein expression in the dentate gyrus

description: Contextual memory is an intricate process involving synaptic plasticity and network rearrangement. Both are governed by many molecular processes including phosphorylation and modulation of protein expression. However, little is known about the molecules involved in it. Here, we exploited the advantages of a quantitative proteomic approach to identify a great number of molecules in the rat dentate gyrus after a contextual fear conditioning session. Our results allowed us to highlight protein expression patterns, not only related to neuroplasticity, but also to myelin structure, such as myelin basic protein and myelin proteolipid protein showing a decrease in expression. Validation of the modification in protein expression reveals a dynamic profile during the 48 hours following the fear conditioning session. The expression of proteins involved in neurite outgrowth, such as BASP-1 and calcineurin B1, and in synaptic structure and function, VAMP2 and RAB3C, was increased in the dentate gyrus of rats submitted to fear conditioning compared to controls. We showed that the increase in BASP-1 protein was specific to fear conditioning learning as it was not present in immediate shock rats, neither in rats exposed to a novel environment without being shocked. Since myelin is known to stabilize synaptic network, the decrease in myelin proteins suggests a neuroglia interactive process taking place in the dentate gyrus in the 24 hours following contextual fear learning which has never been demonstrated before. These results therefore open the way to the study of new plasticity mechanisms underlying learning and memory.
DOI: 10.6084/m9.figshare.5326876
title: A framework for the estimation of the proportion of true discoveries in single nucleotide variant detection studies for human data - supplemental files

description: <br>The data were originally downloaded from Bioplanet’s Genome Comparison & Analytic Testing (GCAT) tool website that is no longer functioning:<br>https://www.biostars.org/p/69341/The files contain Illumina reads from a targeted exome sequencing of the well known NA12878 sample with TrueSeq sequencing kit. The original files names are preserved.There are five files in total:<br>gcat_set_025_*.fastq - two files with 30X coveragegcat_set_053_*.fastq - two files with 150X coveragegcat_set_025.bed - target region from TrueSeq kit (about 45 Megabases). Bioplanet also provided a file named gcat_set_053.bed for 150X coverage, but these two files are identical.<strong><br></strong><strong><br></strong><strong><br></strong><br><br>
DOI: 10.6084/m9.figshare.5326894
title: Polarized light use in the nocturnal bull ant, Myrmecia midas Data Repository

description: For a detailed description of the methods and results of this project please see:<br>Freas CA, Narendra A, Lemesle C, Cheng K. 2017 Polarized light use in the nocturnal bull ant, Myrmecia midas. R. Soc. open sci. 4: 170598. http://dx.doi.org/10.1098/rsos.170598
DOI: 10.6084/m9.figshare.5326876.v1
title: A framework for the estimation of the proportion of true discoveries in single nucleotide variant detection studies for human data - supplemental files

description: <br>The data were originally downloaded from Bioplanet’s Genome Comparison & Analytic Testing (GCAT) tool website that is no longer functioning:<br>https://www.biostars.org/p/69341/The files contain Illumina reads from a targeted exome sequencing of the well known NA12878 sample with TrueSeq sequencing kit. The original files names are preserved.There are five files in total:<br>gcat_set_025_*.fastq - two files with 30X coveragegcat_set_053_*.fastq - two files with 150X coveragegcat_set_025.bed - target region from TrueSeq kit (about 45 Megabases). Bioplanet also provided a file named gcat_set_053.bed for 150X coverage, but these two files are identical.<strong><br></strong><strong><br></strong><strong><br></strong><br><br>
DOI: 10.6084/m9.figshare.5326882
title: Data for polarized light use in the nocturnal bull ant, Myrmecia midas

description: For a detailed description of the methods and results of this project please see:<br>Freas CA, Narendra A, Lemesle C, Cheng K. 2017 Polarized light use in the nocturnal bull ant, Myrmecia midas. R. Soc. open sci. 4: 170598. http://dx.doi.org/10.1098/rsos.170598 <br>
DOI: 10.6084/m9.figshare.5326900.v1
title: Dataset for: A proteomic analysis of contextual fear conditioned rats reveals dynamic modifications in neuron and oligodendrocyte protein expression in the dentate gyrus

description: Contextual memory is an intricate process involving synaptic plasticity and network rearrangement. Both are governed by many molecular processes including phosphorylation and modulation of protein expression. However, little is known about the molecules involved in it. Here, we exploited the advantages of a quantitative proteomic approach to identify a great number of molecules in the rat dentate gyrus after a contextual fear conditioning session. Our results allowed us to highlight protein expression patterns, not only related to neuroplasticity, but also to myelin structure, such as myelin basic protein and myelin proteolipid protein showing a decrease in expression. Validation of the modification in protein expression reveals a dynamic profile during the 48 hours following the fear conditioning session. The expression of proteins involved in neurite outgrowth, such as BASP-1 and calcineurin B1, and in synaptic structure and function, VAMP2 and RAB3C, was increased in the dentate gyrus of rats submitted to fear conditioning compared to controls. We showed that the increase in BASP-1 protein was specific to fear conditioning learning as it was not present in immediate shock rats, neither in rats exposed to a novel environment without being shocked. Since myelin is known to stabilize synaptic network, the decrease in myelin proteins suggests a neuroglia interactive process taking place in the dentate gyrus in the 24 hours following contextual fear learning which has never been demonstrated before. These results therefore open the way to the study of new plasticity mechanisms underlying learning and memory.
DOI: 10.6084/m9.figshare.5326870
title: GCMP Australia sequence data, OTU tables, and metadata

description: Raw fastq data, OTU tables, and associated files from the Global Coral Microbiome Project Australia analysis.
DOI: 10.6084/m9.figshare.5326882.v1
title: Data for polarized light use in the nocturnal bull ant, Myrmecia midas

description: For a detailed description of the methods and results of this project please see:<br>Freas CA, Narendra A, Lemesle C, Cheng K. 2017 Polarized light use in the nocturnal bull ant, Myrmecia midas. R. Soc. open sci. 4: 170598. http://dx.doi.org/10.1098/rsos.170598 <br>
DOI: 10.6084/m9.figshare.5326786
title: mentalist_data_part01

description: Part 01 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326783
title: mentalist_data_part06

description: Part 06 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326777
title: CeMEE RIL haplotype reconstructions

description: Founder haplotype reconstructions at each diallelic marker (RABBIT HMM), filtered to posterior probability &gt; 0.2. Files are split by sub-panel and chromosome. Format is marker / genetic position / line ID / founder haplortype / posterior probability.
DOI: 10.6084/m9.figshare.5326780
title: mentalist_data_part00

description: Part 00 (first) of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326786.v1
title: mentalist_data_part01

description: Part 01 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326657
title: mentalist_data_part03

description: Part 03 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326783.v1
title: mentalist_data_part06

description: Part 06 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326654
title: mentalist_data_part02

description: Part 02 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326657.v1
title: mentalist_data_part03

description: Part 03 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326777.v1
title: CeMEE RIL haplotype reconstructions

description: Founder haplotype reconstructions at each diallelic marker (RABBIT HMM), filtered to posterior probability &gt; 0.2. Files are split by sub-panel and chromosome. Format is marker / genetic position / line ID / founder haplortype / posterior probability.
DOI: 10.6084/m9.figshare.5326651
title: mentalist_data_part04

description: Part 04 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326780.v1
title: mentalist_data_part00

description: Part 00 (first) of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326648
title: mentalist_data_part05

description: Part 05 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326627
title: mentalist_data_part07

description: Part 07 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br><br>
DOI: 10.6084/m9.figshare.5326651.v1
title: mentalist_data_part04

description: Part 04 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326654.v1
title: mentalist_data_part02

description: Part 02 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326648.v1
title: mentalist_data_part05

description: Part 05 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br>
DOI: 10.6084/m9.figshare.5326627.v1
title: mentalist_data_part07

description: Part 07 of the entire test dataset for MentaLiST. You will need all parts to be able to join into a .tar.gz file and then decompress:<br>cat mentalist_data_part* &gt; mentalist.tar.gztar xzf mentalist.tar.gz<br><br>
DOI: 10.6084/m9.figshare.5325607
title: Property Graphs

description: Five data sets serialized in Turtle, YARS, GraphML, GML, GEXF, and METIS.<br>
DOI: 10.6084/m9.figshare.5325607.v1
title: Property Graphs

description: Five data sets serialized in Turtle, YARS, GraphML, GML, GEXF, and METIS.<br>
DOI: 10.6084/m9.figshare.5325574
title: Supplementary_DarwinCore

description: This file includes the meta data of the specimens from Supplementary file 1, using the template provided by GBIF for upload using the Integrated Publishing Toolkit (https://www.gbif.org/news/82852/new-darwin-core-spreadsheet-templates-simplify-data-preparation-and-publishing).