cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14727840
title: Effect of Flatfoot on Rearfoot Eversion Moment During the Support Phase of Walking.xlsx

description: Excessive eversion of the talus and calcaneus (i.e., the rearfoot) during the support phase of walking occurs as a result of excessive moments about the ankle caused by ground reaction forces (GRF) and may eventually lead to chronic lower limb injuries. In this study, I investigated whether individuals with flatfoot are susceptible to excessive rearfoot eversion during walking. Healthy adult male participants (n = 29) were divided, by normalized truncated navicular height, into 2 groups—individuals with flatfoot (n = 14, low values) and individuals with normal foot characteristics (n = 14, high values; the participant with the median value was excluded). Rearfoot eversion moments and the factors generating moments (ankle height, mediolateral GRF, mediolateral distance of COP, mediolateral distance of center of the ankle, vertical GRF) were calculated. These variables were compared between groups. Participants with flatfoot had significantly larger eversion moments than those in the control group after foot contact and during the loading phase; ankle joint centers in participants with flatfoot were located significantly medial to those of participants in the control group, and as a result, the mediolateral distance between the COP and the ankle (the eversion moment arm of vertical GRF) was significantly larger. Because individuals with flatfoot have ankle joint centers located medial to those with normal foot characteristics during the support phase of walking, and consequently, have an increased mediolateral distance between COP and the center of the ankle, individuals with flatfoot are susceptible to large rearfoot eversion moments.
DOI: 10.48569/l000012
title: Western Australian Marine Science Institution Data

description: In mid 2006, the State Government committed $21m over five years to the establishment of the Western Australian Marine Science Institution (WAMSI). Data from WAMSI1 are organised into six nodes and related to the following objectives: Implementation of Integrated Fisheries Management and Ecosystem Based Management of Fisheries; Marine Conservation Reserves (in particular through the Ningaloo Research Program) and Consequences and impacts of climate change. WAMSI2 was focussed on two nodes: Kimberley Marine Research Program and Dredging Science Node. WAMSI data was also stored at Commonwealth Scientific and Industrial Research Organisation (CSIRO) and Australian Institute of Marine Science (AIMS) with metadata stored at the Australian Ocean Data Network (AODN) catalogue.
DOI: 10.3886/e141142v1-88002
title: Mental Illness on Social Communication

description: This article presents research within an area of study between psychology and social communication. The study approaches how the term “mental illness” is used in academic communication within a dataset compared with other two online databases: one of newspaper articles and another of film abstracts. More than 5000 abstracts extracted from those databases have been analyzed using computational techniques with R programming: network relations, longitudinal analysis, correlations calculus and sentiment analysis. We have been able to describe the social imaginaries present in communication about mental illness in those datasets. Our findings revealed a significant gap between the scientific standards and common view on mental health, somehow related with the stigma linked to mental illness. Two social imaginaries of mental illness have been identified mining those three datasets: the academical and the popular social imaginary of mental illness. Between them, what is relevant for one tends to be opaque in the other. Only by understanding how complexity is simplified in social communication would be able to manage better, not just the suffering of living with a mental illness, but also the stigma surrounding mental illness.
DOI: 10.5281/zenodo.4739738
title: A single-cell and spatially resolved atlas of human breast cancers | spatial transcriptomics data

description: This repository contains spatial transcriptomics data related to the Wu et al. 2021 study "<strong>A single-cell and spatially resolved atlas of human breast cancers</strong>". Processed count matrices, brightfield HE-images (plain and annotated) and meta-data (containing clinical information and spot pathological details) for 6 primary breast cancers profiled using the Visium assay (10X Genomics). If you use this dataset in your research, please consider citing the above study. The content of the files are:<br> raw_count_matrices.tar.gz - spaceranger processed raw count matrices. spatial.tar.gz - spaceranger processed spatial files (images, scalefactors, aligned fiducials, position lists) filtered_count_matrices.tar.gz - filtered count matrices. metadata.tar.gz - metadata for tissues and spots of filtered count matrices, including clinical subtype and pathological annotation of each spot. images.pdf - pdf detailing the H&E and annotation images.
DOI: 10.34740/kaggle/dsv/2301253
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.6084/m9.figshare.8074577
title: Posters (Knight DR et al)

description: Collection of conference proceedings
DOI: 10.6084/m9.figshare.8074577.v6
title: Posters (Knight DR et al)

description: Collection of conference proceedings
DOI: 10.6084/m9.figshare.8074577.v5
title: Posters (Knight DR et al)

description: Collection of conference proceedings
DOI: 10.3886/e141741
title: A Pilot Mixed Method Quasi-Experimental Identity Capital Intervention for Young People Exiting Homelessness

description: This is a database for a study from a six-week intervention designed to foster social and economic inclusion for young people who have exited homelessness. Nineteen young people (aged 18 – 26) who had transitioned out of homelessness within the past three years were provided scholarships to participate in a six-week intervention focused on building identity capital and providing career direction. Each time we met with participants, we used questionnaires to capture what we believe are important indicators of socioeconomic inclusion: hope, physical community integration (e.g., attending a community event), psychological community integration, social connectedness (e.g., feeling like one belongs), and self-esteem.
DOI: 10.3886/e141741v1
title: A Pilot Mixed Method Quasi-Experimental Identity Capital Intervention for Young People Exiting Homelessness

description: This is a database for a study from a six-week intervention designed to foster social and economic inclusion for young people who have exited homelessness. Nineteen young people (aged 18 – 26) who had transitioned out of homelessness within the past three years were provided scholarships to participate in a six-week intervention focused on building identity capital and providing career direction. Each time we met with participants, we used questionnaires to capture what we believe are important indicators of socioeconomic inclusion: hope, physical community integration (e.g., attending a community event), psychological community integration, social connectedness (e.g., feeling like one belongs), and self-esteem.
DOI: 10.6084/m9.figshare.14727900
title: Evidence of sexual dimorphism in Fingerprint patterns of Children with Learning Disability

description: <b>Background</b>: Fingerprints are unique, permanent impressions on the finger, which is genetically determined at birth. Fingerprint pattern is an infallible means of personal bio identification and could be a predictive marker for several congenital disorders. The relationship between learning disability (LD) and fingerprint pattern is yet to be established. <b>Objectives</b>: This study compared the fingerprint patterns between students with LD and Non-LD students with a sexual dimorphic lens. <b>Materials and Methods</b>: 300 students (150 LD students and 150 non-LD students), aged between 3-25 years were recruited for this descriptive cross-sectional study. Each study group consisted of 75 males and 75 females. The different fingerprint patterns (arch, whorl, ulnar loop, and radial loop), as well as the following ridge counts: total finger ridge count (TFRC), absolute ridge count (ARC), ulnar ridge count (URC), and radial ridge count (RRC) were accessed using a digital scanner and a fingerprint reader. <b>Results</b>: Students with LD showed a higher frequency of whorl (32.87%), while non-LD students showed a higher occurrence of the ulnar loop (32.53%). TFRC, ARC, and URC were significantly higher in females with LD than non-LD females (<i>p</i>=0.01, 0.03, and 0.00, respectively). In contrast, males with LD showed significantly lower TFRC, RRC, and URC count than the non-LD males (<i>p=</i>0.02, 0.01, and 0.00, respectively). <b>Conclusion</b>: Fingerprints pattern and fingerprint ridge counts showed sexual dimorphism in LD and non-LD students. The finger ridge count is amplified in subjects with LD and could be a good predictive tool for LD.
DOI: 10.6084/m9.figshare.14727900.v1
title: Evidence of sexual dimorphism in Fingerprint patterns of Children with Learning Disability

description: <b>Background</b>: Fingerprints are unique, permanent impressions on the finger, which is genetically determined at birth. Fingerprint pattern is an infallible means of personal bio identification and could be a predictive marker for several congenital disorders. The relationship between learning disability (LD) and fingerprint pattern is yet to be established. <b>Objectives</b>: This study compared the fingerprint patterns between students with LD and Non-LD students with a sexual dimorphic lens. <b>Materials and Methods</b>: 300 students (150 LD students and 150 non-LD students), aged between 3-25 years were recruited for this descriptive cross-sectional study. Each study group consisted of 75 males and 75 females. The different fingerprint patterns (arch, whorl, ulnar loop, and radial loop), as well as the following ridge counts: total finger ridge count (TFRC), absolute ridge count (ARC), ulnar ridge count (URC), and radial ridge count (RRC) were accessed using a digital scanner and a fingerprint reader. <b>Results</b>: Students with LD showed a higher frequency of whorl (32.87%), while non-LD students showed a higher occurrence of the ulnar loop (32.53%). TFRC, ARC, and URC were significantly higher in females with LD than non-LD females (<i>p</i>=0.01, 0.03, and 0.00, respectively). In contrast, males with LD showed significantly lower TFRC, RRC, and URC count than the non-LD males (<i>p=</i>0.02, 0.01, and 0.00, respectively). <b>Conclusion</b>: Fingerprints pattern and fingerprint ridge counts showed sexual dimorphism in LD and non-LD students. The finger ridge count is amplified in subjects with LD and could be a good predictive tool for LD.
DOI: 10.6084/m9.figshare.14727902.v1
title: In silico identification of pseudo-exon activation events in personal genome and transcriptome data

description: Causative mutations for human genetic disorders have mainly been identified in exonic regions that code for amino acid sequences. Recently, however, it has been reported that mutations in deep intronic regions can also cause certain human genetic disorders by creating novel splice sites, leading to pseudo-exon activation. To investigate how frequently pseudo-exon activation events occur in normal individuals, we conducted in silico identification of such events using personal genome data and corresponding high-quality transcriptome data. With rather stringent conditions, on average, 2.6 pseudo-exon activation events per individual were identified. More pseudo-exon activation events were found in 5′ donor splice sites than in 3′ acceptor splice sites. Although pseudo-exon activation events have sporadically been reported as causative mutations in genetic disorders, it is revealed in this study that such events can be observed in normal individuals at a certain frequency. We estimate that human genomes typically contain on average at least 10 pseudo-exon activation events. The actual number should be higher than this, because we used stringent criteria to identify pseudo-exon activation events. This suggests that it is worth considering the possibility of pseudo-exon activation when searching for causative mutations of genetic disorders if candidate mutations are not identified in coding regions or RNA splice sites.
DOI: 10.5281/zenodo.4898463
title: Supporting data for the submission to the WRR journal

description: Experimental data of the Perugia Test [Keramat et al. (2019)]. It is supporting data for the submission entitled "Uncertainty Quantification of Transient-based Leakage Identification: A Frequency Domain Approach" to the WRR journal. Keramat, A., Louati, M., Wang, X., Meniconi, S., Brunone, B., Ghidaoui, M.S. (2019). Objective Functions for Transient-Based Pipeline Leakage Detection in a Noisy Environment: Least Square and Matched-Filter. Journal of Water Resources Planning and Management, ASCE, 145(10), 04019042.
DOI: 10.21947/1356352
title: Surface Meteorological Station - ARL 2m, Sonic + irga flux, Prineville - Reviewed Data

description: The dataset provides eddy covariance flux measurements. The turbulent flux data has also been pulled out into daily files.
DOI: 10.21947/1367867
title: Surface Meteorological Station - ARL 2m, Sonic + irga flux, Boardman - Reviewed Data

description: These data provide eddy covariance flux measurements. The turbulent flux data has also been pulled out into daily files.
DOI: 10.5281/zenodo.4620323
title: Emissions changes in 31 Chinese cities due to the Chinese Spring Festival

description: This dataset contains the air quality data and codes for estimating the emission changes due to the Chinese Spring Festival in 2015-2020. The 2020 Spring Festival is overlapped with the intervention of COVID-19 lockdown.
DOI: 10.5281/zenodo.4898376
title: MITgcm model setup and output for "Dense water downslope flow and AABW production in a numerical model: sensitivity to horizontal and vertical resolution in the region off Cape Darnley Polynya"

description: MITgcm model setup and output for "<em>Dense water downslope flow and AABW production in a numerical model: sensitivity to horizontal and vertical resolution in the region off Cape Darnley Polynya</em>" <strong>(Vigan Mensah, Yoshihiro Nakayama, Masakazu Fujii, Yoshifumi Nogi, and Kay I. Ohshima, <em>Ocean Modelling</em>, 2021).</strong> <strong>(Contents)</strong><br> Here it contains<br> - code.zip (code to run this simulation at 40m vertical, 2 km horizontal resolution)<br> - input.zip (input file required for this simulation at 40m vertical, 2 km horizontal resolution)<br> - run40m2km.zip (model output for the control run at 40m vertical resolution and 2 km horizontal resolution for year 2008) <br> <strong>(How to compile)</strong><br> - 40m1km.zip: The directory include the code and input folders needed to compile and run the model with a 40m vertical, 1km horizontal resolution. <br> <strong>To run this simulation</strong>, After unzipping all folders:<br> 1) Create your work directory ( thereafter called “config”) within your MITgcm directory :<br> 2) Copy “code” into “config”<br> 3) Then, in the MITgcm directory run the following commands<br> &gt; cd config<br> &gt; mkdir build<br> &gt; cd build<br> &gt; ../../../tools/genmake2 -of ../../../tools/build_options/&lt;your_option_file&gt; -mpi -mods ../code/ (the -mpi is optional)<br> &gt; make depend<br> &gt; make 4) copy the mitgcmuv file generated in build into the directory of your choice (input in our case) <strong>(How to submit a job)</strong><br> In input, the file run_omp_high_t1.pbs is used to submit a job for running simulation.<br> This file may need to be modified so the commands are in accordance with the commands accepted by your supercomputer. <strong>(Note on forcing files)</strong><br> The era_xx folder which contains the forcing file can be found under https://ecco.jpl.nasa.gov/drive/files/Version5/Alpha<br> The model user needs to change the path to the era_xx folder in the file input/data.exf <br> For more info please send an email to vmensah@lowtem.hokudai.ac.jp<br>
DOI: 10.5281/zenodo.4898375
title: MITgcm model setup and output for "Dense water downslope flow and AABW production in a numerical model: sensitivity to horizontal and vertical resolution in the region off Cape Darnley Polynya"

description: MITgcm model setup and output for "<em>Dense water downslope flow and AABW production in a numerical model: sensitivity to horizontal and vertical resolution in the region off Cape Darnley Polynya</em>" <strong>(Vigan Mensah, Yoshihiro Nakayama, Masakazu Fujii, Yoshifumi Nogi, and Kay I. Ohshima, <em>Ocean Modelling</em>, 2021).</strong> <strong>(Contents)</strong><br> Here it contains<br> - code.zip (code to run this simulation at 40m vertical, 2 km horizontal resolution)<br> - input.zip (input file required for this simulation at 40m vertical, 2 km horizontal resolution)<br> - run40m2km.zip (model output for the control run at 40m vertical resolution and 2 km horizontal resolution for year 2008) <br> <strong>(How to compile)</strong><br> - 40m1km.zip: The directory include the code and input folders needed to compile and run the model with a 40m vertical, 1km horizontal resolution. <br> <strong>To run this simulation</strong>, After unzipping all folders:<br> 1) Create your work directory ( thereafter called “config”) within your MITgcm directory :<br> 2) Copy “code” into “config”<br> 3) Then, in the MITgcm directory run the following commands<br> &gt; cd config<br> &gt; mkdir build<br> &gt; cd build<br> &gt; ../../../tools/genmake2 -of ../../../tools/build_options/&lt;your_option_file&gt; -mpi -mods ../code/ (the -mpi is optional)<br> &gt; make depend<br> &gt; make 4) copy the mitgcmuv file generated in build into the directory of your choice (input in our case) <strong>(How to submit a job)</strong><br> In input, the file run_omp_high_t1.pbs is used to submit a job for running simulation.<br> This file may need to be modified so the commands are in accordance with the commands accepted by your supercomputer. <strong>(Note on forcing files)</strong><br> The era_xx folder which contains the forcing file can be found under https://ecco.jpl.nasa.gov/drive/files/Version5/Alpha<br> The model user needs to change the path to the era_xx folder in the file input/data.exf <br> For more info please send an email to vmensah@lowtem.hokudai.ac.jp<br>
DOI: 10.5281/zenodo.4898488
title: Integrative analyses of serum proteome and metabolome uncovers novel biomarkers for disease activity monitoring and clinical diagnoses for systemic lupus erythematosus

description: Objective: To systematically determine the serum protein and metabolite expression characteristics, to identify novel biomarkers for disease activity monitoring and clinical diagnoses in patients with systemic lupus erythematosus (SLE).<br> Methods: Serum samples from 121 SLE patients and 106 healthy controls were conducted to proteomics and metabolomics analyses. Disease activity score (SLEDAI) was compared with protein and metabolite expression and clinical data. Random forest machine learning model was performed to identify biomarkers for SLE classification. The clinical utility of the biomarkers was further validated in an independent patient cohort.<br> Results: Screening of the serum proteome and metabolome identified 90 proteins and 76 metabolites significantly changed in SLE patients. Pathway analyses of these molecules revealed SLE related alterations, including immune response, endocytosis and lipid metabolism. Several apolipoproteins and the metabolite arachidonic acid were significantly associated with disease activity. Besides, except some well-known biomarkers, novel molecules such as the protein Apolipoprotein A-IV (APOA4) and the metabolites LysoPC(16:0), punicic acid and stearidonic acid were correlated with renal function in SLE condition. Random forest model by using the significantly changed proteins and metabolites identified 11 proteins and 5 metabolites as potential biomarkers. Among them, 9 proteins (AUC=0.895) and 5 metabolites (AUC=0.902) were validated in an independent patient cohort, which showed good performance for SLE classification.
DOI: 10.5281/zenodo.4898487
title: Integrative analyses of serum proteome and metabolome uncovers novel biomarkers for disease activity monitoring and clinical diagnoses for systemic lupus erythematosus

description: Objective: To systematically determine the serum protein and metabolite expression characteristics, to identify novel biomarkers for disease activity monitoring and clinical diagnoses in patients with systemic lupus erythematosus (SLE).<br> Methods: Serum samples from 121 SLE patients and 106 healthy controls were conducted to proteomics and metabolomics analyses. Disease activity score (SLEDAI) was compared with protein and metabolite expression and clinical data. Random forest machine learning model was performed to identify biomarkers for SLE classification. The clinical utility of the biomarkers was further validated in an independent patient cohort.<br> Results: Screening of the serum proteome and metabolome identified 90 proteins and 76 metabolites significantly changed in SLE patients. Pathway analyses of these molecules revealed SLE related alterations, including immune response, endocytosis and lipid metabolism. Several apolipoproteins and the metabolite arachidonic acid were significantly associated with disease activity. Besides, except some well-known biomarkers, novel molecules such as the protein Apolipoprotein A-IV (APOA4) and the metabolites LysoPC(16:0), punicic acid and stearidonic acid were correlated with renal function in SLE condition. Random forest model by using the significantly changed proteins and metabolites identified 11 proteins and 5 metabolites as potential biomarkers. Among them, 9 proteins (AUC=0.895) and 5 metabolites (AUC=0.902) were validated in an independent patient cohort, which showed good performance for SLE classification.
DOI: 10.5281/zenodo.4898541
title: mirTarRnaSeq miRanda files

description: miRanda files for package mirTarRnaSeq
DOI: 10.5281/zenodo.4615669
title: mirTarRnaSeq miRanda files

description: miRanda files for package mirTarRnaSeq
DOI: 10.6084/m9.figshare.14728221.v1
title: Meis1 rep1 P15 Ventricles mm9

description: For UCSC
DOI: 10.6084/m9.figshare.14728221
title: Meis1 rep1 P15 Ventricles mm9

description: For UCSC
DOI: 10.6084/m9.figshare.13204316
title: A location conversion method for roads through deep learning-based semantic matching and simplified qualitative direction knowledge representation

description: The data and codes that support the findings of the study. Configure of experimental environment and instructions for use are described in readme.docx.
DOI: 10.18112/openneuro.ds003677.v1.0.0
title: A test-retest resting and cognitive state EEG dataset
DOI: 10.18112/openneuro.ds003677.v1.0.1
title: A test-retest resting and cognitive state EEG dataset
DOI: 10.5063/1r6nz1
title: Corals and Gobies of Lizard Island, Great Barrier Reef, from 2014 to 2018

description: Coral reef systems are being disturbed by multiple extreme climatic events in tandem. Much work has focused on assessing how corals survive these disturbances, yet coral reef fishes may not respond similarly to corals.Here we monitored populations of corals and gobies of Lizard Island throughout multiple disturbances. The island is in the upper portion of the Great Barrier Reef in Queensland, Australia.The original work was collected from surveys all around the island depending on the accessibility and weather patterns.The datasets consist of observations of scleractinian Acropora corals and coral-dwelling gobies with different collection parameters.The datasets consist of 3 data tables.
DOI: 10.6084/m9.figshare.14728530
title: H3K27ac P1_1.5dpi rep1 mm10

description: For UCSC
DOI: 10.6084/m9.figshare.14728530.v1
title: H3K27ac P1_1.5dpi rep1 mm10

description: For UCSC
DOI: 10.6084/m9.figshare.14721282.v2
title: THINGS-EEG

description: EEG data for 1854 object concepts presented in RSVP streams. Data from 50 participants.