cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.a4hp5v
title: Occurrence Download

description: A dataset containing 142065 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON(((151.074647179584 -33.8681528666959,151.0759709402 -33.8670314433385,151.07717191841 -33.8658184774247,151.078240975802 -33.8645232040525,151.07916997948 -33.8631554845465,151.07995186386 -33.8617257313003,151.080580684303 -33.8602448284342,151.081051662169 -33.8587240488742,151.081361220979 -33.8571749684865,151.081507013386 -33.8556093779233,151.081487938782 -33.8540391928517,151.0813041514 -33.8524763632511,151.080957058867 -33.8509327824691,151.080449311219 -33.8494201967278,151.079784780478 -33.8479501157698,151.078968530946 -33.8465337253213,151.078006780455 -33.845181802037,151.076906852879 -33.8439046315727,151.075677122253 -33.8427119304054,151.074326948962 -33.8416127719928,151.072866608455 -33.8406155178323,151.07130721305 -33.8397277539388,151.069660627419 -33.8389562332229,151.067939378385 -33.8383068242032,151.066156559731 -33.8377844664419,151.064325732727 -33.8373931330366,151.06246082314 -33.8371358004553,151.060576015485 -33.8370144259382,151.058685645335 -33.8370299326388,151.056804090493 -33.8371822026162,151.054945661837 -33.8374700777298,151.053124494683 -33.8378913684321,151.051354441458 -33.8384428703906,151.049648966508 -33.8391203888166,151.048021043842 -33.839918770314,151.046483058555 -33.8408319420116,151.045046712711 -33.8418529576812,151.043722936367 -33.8429740504943,151.042521804434 -33.8441866920196,151.041452459993 -33.8454816570154,151.040523044664 -33.846849093527,151.039740636537 -33.8482785977595,151.039111196167 -33.8497592931586,151.038639521028 -33.8512799131022,151.038329208786 -33.852828886574,151.038182629681 -33.8543944261703,151.038200908225 -33.8559646177726,151.038383914372 -33.8575275112031,151.038730264231 -33.8590712111748,151.039237330334 -33.860583967844,151.039901261368 -33.8620542662745,151.040717011251 -33.8634709141326,151.041678377331 -33.864823126942,151.042778047419 -33.8661006102499,151.044007655299 -33.8672936380739,151.045357844318 -33.8683931270308,151.046818338549 -33.8693907055799,151.048378021002 -33.8702787778497,151.050025018284 -33.8710505815601,151.051746791065 -33.8717002395935,151.053530229647 -33.8722228048218,151.055361753923 -33.8726142978435,151.057227416942 -33.8728717373407,151.059113011295 -33.8729931628248,151.061004177506 -33.8729776495935,151.062886513584 -33.8728253157862,151.064745684912 -33.8725373214828,151.066567533611 -33.8721158598526,151.068338186545 -33.8715641404214,151.070044161144 -33.870886364586,151.071672468219 -33.8700876935635,151.073210710995 -33.8691742090221,151.074647179584 -33.8681528666959)))"
 ]
}

 The dataset includes 142065 records from 47 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106165-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.g4v36m
title: Occurrence Download

description: A dataset containing 19476 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Spain",
 "TaxonKey is Pyrrhula pyrrhula (Linnaeus, 1758)",
 "Year 2019-2024"
 ]
}

 The dataset includes 19476 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106179-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.htmzrb
title: Occurrence Download

description: A dataset containing 16 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Mylabris olivieri Billberg, 1813",
 "Year 1950-2024"
 ]
}

 The dataset includes 16 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106181-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wqgxex
title: Occurrence Download

description: A dataset containing 30998 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON((-8.90167 37.87709,-8.80798 37.87709,-8.80798 37.95747,-8.90167 37.95747,-8.90167 37.87709))"
 ]
}

 The dataset includes 30998 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106182-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26862224
title: Prevalence and clinical correlates of nonmotor symptoms in Parkinson’s disease in a tertiary health-care center in Turkey

description: The objective was to determine the prevalence and clinical correlates of nonmotor symptoms in Parkinson’s disease patients in movement disorders outpatient clinics. We enrolled all consecutive PD patients who visited our movement disorders outpatient clinics between January and December 2023; and agreed to participate in the study. In addition to the evaluation of demographic and clinical features, clinical scales, including the MDS-UPDRS, NMSS, and FOOGQ, were performed. Overall, we enrolled 163 PD subjects with a mean age of 63.9 ± 10.4 (F/M = 27/136). The disease duration was 3.5 (20) y [median (range)]. The median score of the NMSS was 41 points. The NMSs burden levels were severe in 25.2%, and very severe in 25.2% of the subjects. The subitems with the highest scores were sleep/fatigue, mood/cognition, urinary, and miscellaneous. The analyses within the patient group with newly diagnosed PD also revealed high NMSS scores. Comparisons of the NMSS between distinct PD stages revealed greater NMSS scores in the severe stage than in the mild stage (<i>p</i> = 0.001). Correlation analyses between the clinical scores and the NMSS scores revealed positive correlations between the NMSS scores and the scores on all the clinical scales including the MDS-UPDRS 1–4, and FOGQ. We reported the first data regarding the NMS burden in PD patients from Turkey. We found a high prevalence and severity of various domains of NMSs, most of which were sleep/fatigue, mood/cognition, urinary, and miscellaneous. More than half of the patients had severe to very severe NMS burden. Although NMSs were more common severe-stage disease, they were also prevalent in the subgroup with newly diagnosed patients.
DOI: 10.6084/m9.figshare.26862224.v1
title: Prevalence and clinical correlates of nonmotor symptoms in Parkinson’s disease in a tertiary health-care center in Turkey

description: The objective was to determine the prevalence and clinical correlates of nonmotor symptoms in Parkinson’s disease patients in movement disorders outpatient clinics. We enrolled all consecutive PD patients who visited our movement disorders outpatient clinics between January and December 2023; and agreed to participate in the study. In addition to the evaluation of demographic and clinical features, clinical scales, including the MDS-UPDRS, NMSS, and FOOGQ, were performed. Overall, we enrolled 163 PD subjects with a mean age of 63.9 ± 10.4 (F/M = 27/136). The disease duration was 3.5 (20) y [median (range)]. The median score of the NMSS was 41 points. The NMSs burden levels were severe in 25.2%, and very severe in 25.2% of the subjects. The subitems with the highest scores were sleep/fatigue, mood/cognition, urinary, and miscellaneous. The analyses within the patient group with newly diagnosed PD also revealed high NMSS scores. Comparisons of the NMSS between distinct PD stages revealed greater NMSS scores in the severe stage than in the mild stage (<i>p</i> = 0.001). Correlation analyses between the clinical scores and the NMSS scores revealed positive correlations between the NMSS scores and the scores on all the clinical scales including the MDS-UPDRS 1–4, and FOGQ. We reported the first data regarding the NMS burden in PD patients from Turkey. We found a high prevalence and severity of various domains of NMSs, most of which were sleep/fatigue, mood/cognition, urinary, and miscellaneous. More than half of the patients had severe to very severe NMS burden. Although NMSs were more common severe-stage disease, they were also prevalent in the subgroup with newly diagnosed patients.
DOI: 10.15468/dl.p3w7z2
title: Occurrence Download

description: A dataset containing 2007586 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Milvus migrans (Boddaert, 1783)",
 "HasCoordinate is true",
 "Year is greater than or equal to 2011",
 "Year is less than or equal to 2024"
 ]
}

 The dataset includes 2007586 records from 3168 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0106180-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10659929
title: Single-Cell Lung Cancer Dataset

description: The last dataset is a lung cancer dataset, which collected a total of 27 sample single-cell data from 10.5 million cells  (31 features measured per cell). The condition of progression-free survival (PFS) was defined as a predicted label. The age, sex, systemic immunosuppressive treatment for adverse events, and drug-related adverse events were defined as covariates.





Here is the file structure that fits in CytoCo-set input format (symbol "X(____)X" defined as file name describe):

data folder



fcs_info.csv

filenames_X(trials_number)X.json

lung_fcs



all



X(sample_file_name)X.fcs

test_labels_X(trials_number)X.csv

train_labels_X(trials_number)X.csv



marker.csv



tripletlists_X(covariate)X_X(trials_number)X



X(covariate)X_tripletlist_subpick_test_rffX(medianpooling_or_maxpooling)X_sameX(same_threhold_percange)X_diffX(diff_threhold_percange)X.txt

X(covariate)X_tripletlist_subpick_trainval_rffX(medianpooling_or_maxpooling)X_sameX(same_threhold_percange)X_diffX(diff_threhold_percange)X.txt




 

The dataset uploaded all the sample's raw features data (fcs file) and some file examples. fcs_info.csv records all sample's true labels and covariates.
DOI: 10.5281/zenodo.10659930
title: Single-Cell Lung Cancer Dataset

description: The last dataset is a lung cancer dataset, which collected a total of 27 sample single-cell data from 10.5 million cells  (31 features measured per cell). The condition of progression-free survival (PFS) was defined as a predicted label. The age, sex, systemic immunosuppressive treatment for adverse events, and drug-related adverse events were defined as covariates.





Here is the file structure that fits in CytoCo-set input format (symbol "X(____)X" defined as file name describe):

data folder



fcs_info.csv

filenames_X(trials_number)X.json

lung_fcs



all



X(sample_file_name)X.fcs

test_labels_X(trials_number)X.csv

train_labels_X(trials_number)X.csv



marker.csv



tripletlists_X(covariate)X_X(trials_number)X



X(covariate)X_tripletlist_subpick_test_rffX(medianpooling_or_maxpooling)X_sameX(same_threhold_percange)X_diffX(diff_threhold_percange)X.txt

X(covariate)X_tripletlist_subpick_trainval_rffX(medianpooling_or_maxpooling)X_sameX(same_threhold_percange)X_diffX(diff_threhold_percange)X.txt




 

The dataset uploaded all the sample's raw features data (fcs file) and some file examples. fcs_info.csv records all sample's true labels and covariates.
DOI: 10.5281/zenodo.10660030
title: Research data supporting article on implementation and validation of OpenMC cell-based R2S shutdown dose rate capabilities

description: This file contains an archive of all research data that supports the article on implementation and validation of a cell-based R2S shutdown dose rate workflow in OpenMC.
description: This work is supported by the U.S. Department of Energy Office of Fusion Energy Sciences under award number DE-SC0022033.
DOI: 10.5281/zenodo.8360396
title: Research data supporting article on implementation and validation of OpenMC cell-based R2S shutdown dose rate capabilities

description: This file contains an archive of all research data that supports the article on implementation and validation of a cell-based R2S shutdown dose rate workflow in OpenMC.
description: This work is supported by the U.S. Department of Energy Office of Fusion Energy Sciences under award number DE-SC0022033.
DOI: 10.6084/m9.figshare.25209389
title: Effects of CO<sub>2</sub>, O<sub>3</sub> and humidity on the biology of MPB and their symbiotic fungi.xlsx

description: Mountain pine beetles pose a substantial threat to North American pine forests, causing extensive tree mortality over large areas. Their tree-killing ability is closely linked to mass aggregation on host trees triggered <i>via</i> pheromones and dependence on their symbiotic fungi. However, the influence of a changing climate on the biology of mountain pine beetles and their co-evolved interactions with their fungal symbionts remains uncertain. To investigate this, male and female pairs of beetles were introduced into freshly cut logs from lodgepole pine trees and placed in controlled climate chambers with manipulated environmental conditions, including two levels of CO<sub>2</sub> (ambient vs. 1,000ppm), O<sub>3</sub> (ambient vs. 100ppb), and humidity (33% vs. 65%)The beetle-infested logs were left in these chambers for one month and then returned to ambient conditions until brood emergence. Emerging broods were collected for further analysis. Additionally, three species of fungal symbionts (<i>Grosmannia clavigera</i>, <i>Ophiostoma montium</i>, and <i>Leptographium longiclavatum</i>) were subjected to the same CO<sub>2</sub>,<sub> </sub>O<sub>3</sub>, and humidity conditions for five days. Lower humidity promoted mountain pine beetle reproduction and fungal growth. Elevated CO<sub>2</sub> accelerated larval growth and emergence while improving brood pheromone production. Elevated O<sub>3</sub> had a negative impact on mountain pine beetle reproduction and brood fitness while improving its immune responses to an entomopathogenic fungus (<i>Beauveria bassiana</i>). It also inhibited fungal growth and reproduction, whereas elevated CO<sub>2</sub> had varied (positive or negative) effects on fungal growth and ergosterol (proxy to fungal mass) production depending on the fungal species. Together, these findings suggest that climate change can potentially alter the interactions between mountain pine beetles and their fungal symbionts, highlighting the importance of understanding how climate change affects forest pests and their symbiotic relationships to develop effective management strategies in the future.
DOI: 10.5883/ds-ilh2023
title: New records of introduced Lepidoptera in the Hawaiian Islands for the year 2023

description: DNA barcode data hosted in the Data Portal of the Barcode of Life Data Systems. Records consist of specimen metadata, specimen images, and sequence data.
DOI: 10.26189/kpv8-6m21
title: Embracing Cultural Identity in an Australian Regional Community: A collaboration of social workers, librarians, and Punjabi Indian migrants
DOI: 10.6084/m9.figshare.25222529.v1
title: Mobility Data for One Participant.csv

description: The data provided is in a CSV file format containing three columns: "Participant ID," "Capture_time," and "Type_Code." It includes information for one simulated participant. The "Capture_time" column indicates the time of telecommunication transactions, while the "Type_Code" column denotes the types of places the participant is in during these transactions. This CSV file allows for the construction of sequences of places visited by the participant over multiple days.
DOI: 10.6084/m9.figshare.23671647
title: The landscape of abiotic and biotic stress-responsive splice variants using RNA-seq datasets in hot pepper

description: <b>1.</b><b>Overview of the pepper transcriptomes used in this study.</b><b>2.Quality assessment of raw read preprocessing on 132 raw RNA-seq datasets from </b><b><i>C. annuum</i></b><b> infected with </b><b><i>P. capsici</i></b><b>, TMV-P2, Xag8ra, Xcv1, and Xcv3.</b> (a-e) Quality scores of reads for <i>P. </i><i>capsici</i>, TMV-P2, Xag8ra, Xcv1 and Xcv3, respectively. <i>X</i>-axis represents mean sequence quality (Phred score) and y-axis represents read counts. (f-j) Graphs for quality scores per position. The <i>x</i>-axis represents the position (bp), and the <i>y</i>-axis Phred score.<b>3</b><b>.</b><b>P</b><b>rincipal </b><b>components analysis (PCA) for RNA-seq datasets infected with biotic stressors in hot pepper. </b>PCA plots with normalized data of (a) <i>P. </i><i>capsici</i><i>; </i>(b) TMV-P2; (c) Xag8ra; (d) Xcv1; (e) Xcv3.<b>4</b><b>.</b><b>P</b><b>roportion of alternative splicing events detected in hot pepper under different conditions. </b>The graphs indicate the number of alternative splicing events in response to biotic and abiotic stressors, tissues and signaling molecules. Blue, exon skipping (SE); yellow, intron retention (RI); light grey, mutually exclusive exons (MXE); green, alternative 5’ splice site (A5SS); pink, alternative 3’ splice site (A3SS).<b>5.Statistical summary of mapping rates</b>:Information about mapping rates for 425 RNA-seq datasets<br><b>6.Information of AS events results</b>: Information of AS events under environmental stressors, tissues, and signaling molecules.<br><b>7</b><b>. The list of AS gene, DAS gene, and description of DAS gene</b>Sheet 1: AS gene listSheet 2: DAS gene listSheet 3: DAS gene descriptionSheet 4: AS type information of DAS gene<br><b>8.Distribution of AS types in DAS genes under four intersection set</b>Sheet 1 (Abio&Biotic&Tissue&Phytohormone): Distribution of AS types in DAS genes under ABTS intersection setSheet 2 (Abiotic&Biotic&Tissue): Distribution of AS types in DAS genes under ABT intersection setSheet3 (Abiotic&Tissue): Distribution of AS types in DAS genes under AT intersection setSheet4 (Biotic&Tissue): Distribution of AS types in DAS genes under BT intersection set<br><b>9.Code availability. zip</b>: <b>1. Annotated gene_filtering.pl</b> - Filtering code of transcripts containing two or more annotated genes: <b>2. Stop codon_filtering.pl </b>- Filtering code of transcripts that didn't have a stop codon: <b>3. AS_counting code.pl</b> - code for counting the number of AS: <b>4. </b><b>DAS_gene_counting code.pl</b> - code for counting the DAS genes
DOI: 10.6084/m9.figshare.23671647.v6
title: The landscape of abiotic and biotic stress-responsive splice variants using RNA-seq datasets in hot pepper

description: <b>1.</b><b>Overview of the pepper transcriptomes used in this study.</b><b>2.Quality assessment of raw read preprocessing on 132 raw RNA-seq datasets from </b><b><i>C. annuum</i></b><b> infected with </b><b><i>P. capsici</i></b><b>, TMV-P2, Xag8ra, Xcv1, and Xcv3.</b> (a-e) Quality scores of reads for <i>P. </i><i>capsici</i>, TMV-P2, Xag8ra, Xcv1 and Xcv3, respectively. <i>X</i>-axis represents mean sequence quality (Phred score) and y-axis represents read counts. (f-j) Graphs for quality scores per position. The <i>x</i>-axis represents the position (bp), and the <i>y</i>-axis Phred score.<b>3</b><b>.</b><b>P</b><b>rincipal </b><b>components analysis (PCA) for RNA-seq datasets infected with biotic stressors in hot pepper. </b>PCA plots with normalized data of (a) <i>P. </i><i>capsici</i><i>; </i>(b) TMV-P2; (c) Xag8ra; (d) Xcv1; (e) Xcv3.<b>4</b><b>.</b><b>P</b><b>roportion of alternative splicing events detected in hot pepper under different conditions. </b>The graphs indicate the number of alternative splicing events in response to biotic and abiotic stressors, tissues and signaling molecules. Blue, exon skipping (SE); yellow, intron retention (RI); light grey, mutually exclusive exons (MXE); green, alternative 5’ splice site (A5SS); pink, alternative 3’ splice site (A3SS).<b>5.Statistical summary of mapping rates</b>:Information about mapping rates for 425 RNA-seq datasets<br><b>6.Information of AS events results</b>: Information of AS events under environmental stressors, tissues, and signaling molecules.<br><b>7</b><b>. The list of AS gene, DAS gene, and description of DAS gene</b>Sheet 1: AS gene listSheet 2: DAS gene listSheet 3: DAS gene descriptionSheet 4: AS type information of DAS gene<br><b>8.Distribution of AS types in DAS genes under four intersection set</b>Sheet 1 (Abio&Biotic&Tissue&Phytohormone): Distribution of AS types in DAS genes under ABTS intersection setSheet 2 (Abiotic&Biotic&Tissue): Distribution of AS types in DAS genes under ABT intersection setSheet3 (Abiotic&Tissue): Distribution of AS types in DAS genes under AT intersection setSheet4 (Biotic&Tissue): Distribution of AS types in DAS genes under BT intersection set<br><b>9.Code availability. zip</b>: <b>1. Annotated gene_filtering.pl</b> - Filtering code of transcripts containing two or more annotated genes: <b>2. Stop codon_filtering.pl </b>- Filtering code of transcripts that didn't have a stop codon: <b>3. AS_counting code.pl</b> - code for counting the number of AS: <b>4. </b><b>DAS_gene_counting code.pl</b> - code for counting the DAS genes
DOI: 10.15131/shef.data.23556273
title: Raw and processed data for "Bayesian Learning from Multi-Way EEG Feedback for Robot Navigation and Target Identification"

description: The contents of each file is described in README.txt and below:

 <em>easy.zip</em> - Raw EEG recordings.
 <em>concatNumStepsToCTI</em> - Concatenated data showing all numbers of steps to Correct Target Identifications.
 <em>multiwayMultifiltClassified_CV_p*.mat - </em>Classified movement action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.
 <em>GClassified_CV_p*.mat</em> - Classified target identification action data, including pre-processed training and test sets, cross-validation contingency tables, test data contingency tables, and feature selection information.
 <em>full_MTCI_MNS_tables.mat -</em>Tables containing average PTCI and MNS results for each participant at each stringency level of the Bayesian Inference strategy.
 <em>rand_react_B0pt1_B0pt9_tables.mat - </em>Tables containing average PTCI and MNS results for the random strategy, and each participant with the react strategy and Bayesian Inference at stringency of 0.1 and 0.9.
 <em>stepCountData.zip - </em>Zipped directory containing step counts for all runs of all participants on small and large grids using all strategies.

<br>
This work has been approved by the Automatic Control and Systems Engineering ethics committee, ethics reference number: 022698. This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) Doctoral training partnership.