cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10629060
title: Handwriting and posture quality measures of children while interacting with a social robot in handwriting activities

description: About Dataset

This dataset is regarding posture quality measures and handwriting quality measures of children (around 10 y.o.) while interacting with a social robot for about 30 minutes.

About Data collection methodology

The interaction between the robot and the participant was designed combining the phases of by following sequence:1. The greeting phase2. A previous handwriting evaluation (HWE1)3. The first training phase4. An intermediate handwriting evaluation (HWE2)5. The second training phase6. A last handwriting evaluation (HWE3)7. The goodbye phase at the end.

The minimum time for the training phases (steps 3 and 5) was set to 5 minutes. This means that after 5 minutes of training, instead of suggesting the next game, the robot guided the student to the next phase, which in this case was always a HWE.

The data of this dataset is the posture and handwriting measures collected during the steps 2, 4, and 6 of the interaction.

The handwriting measures were collected using the Dynamilis app, whereas the posture were coded by the authors to provide the measures of Rapid entire body assessment (REBA), and Rapid Upper Limb Assessment (RULA). 

The handwriting measure is based on the text they wrote during the evaluation phases while the posture measures are the average score of all the corresponding readings of that specific measure during the period children took to perform the text writing.

Description of the data

Data structure:

Root Dir/  -HandwritingEvaluation/    -ID01.csv    -ID02.csv    -...    -ID031.csv  -ergo_analysis_all_subs_complementary.csv  -README.md

The file "ergo_analysis_all_subs_complementary.csv" contains the posture measures, where the column "sub_id" is the Id of the subject, the column "type" is the phase evaluated (being "A" and "B" for pre- and post- test, respectively, and “1” for after the instructor correcting the subject's posture). All the other columns are the corresponding average of REBA or RULA measures (according to the column's name) read by our system. Names of the columns follow the pattern of "<method_name>_<measure>", for instance the column "REBA_neck_score" tells that the number there is the neck score average using the REBA method.

The handwriting evaluation measures are stored in the files inside the directory "HandwritingEvaluation", where each file contains the 3 handwriting measures of the subject indicated in the file's name. The rows' order is related to their order in the experiment, so row 1 corresponds to the first measure ("A" type in posture measure files), the second row corresponds to the second evaluation phase ("B" in posture) and so on.

Authors



Tozadore, Daniel. 

Wang, Chenyang.

Bruno, Barbara.

Dillenbourg, Pierre.


All authors were with the EPFL at the time of this data collection.

License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details

Acknowledgments

We acknowledge the SNF for funding this project under the registration FNS 200021E_189475/1.
DOI: 10.5281/zenodo.10629196
title: АНАЛИЗ РАЗВИТИЯ СФЕРЫ СВЯЗИ И ПУТИ РЕШЕНИЯ ПРОБЛЕМ
DOI: 10.5281/zenodo.10629197
title: АНАЛИЗ РАЗВИТИЯ СФЕРЫ СВЯЗИ И ПУТИ РЕШЕНИЯ ПРОБЛЕМ
DOI: 10.6084/m9.figshare.22600969
title: Additional file 3 of Identification of alternative splicing events related to fatty liver formation in duck using full-length transcripts

description: Additional file 3.
DOI: 10.6084/m9.figshare.22600969.v1
title: Additional file 3 of Identification of alternative splicing events related to fatty liver formation in duck using full-length transcripts

description: Additional file 3.
DOI: 10.5281/zenodo.10629217
title: СОЗДАНИЯ НОВЫХ ФОРМ ХЛОПЧАТНИКА В ЭКСТРЕМАЛЬНЫХ УСЛОВИЯХ ПРИАРАЛЬЯ
DOI: 10.5281/zenodo.10629218
title: СОЗДАНИЯ НОВЫХ ФОРМ ХЛОПЧАТНИКА В ЭКСТРЕМАЛЬНЫХ УСЛОВИЯХ ПРИАРАЛЬЯ
DOI: 10.6084/m9.figshare.25158554.v1
title: Hashtags used by museums Twitter accounts from REMED

description: This study consists of quantitative, explanatory, and non-experimental research using inductive inference longitudinally. Thus, the use of hashtags by the Twitter accounts of the set of museums that are part of REMED is studied, and the analysis of hashtag trends by Twitter users in Spanish is performed.The primary variable is the favorite count, and it is hypothesized from this study that it is possible to predict the primary variable five weeks later. The field of study is formed by the 104 Twitter accounts of the museums that are part of REMED (Red de Museos y Estrategias Digitales).Seven analysis variables explain the information related to the use of hashtags, both in the size of the Twitter accounts of museums of the sample chosen (prefix "m_" in the variables) and Twitter users in Spanish in general (prefix "tw_" in variables). All variables represent the data in count mode, which means that they sum up the total of the data collected for each tweet of each hashtag processed:Number of tweets (variable name "num_tweets")Number of retweets (variable name "retweet_count") Number of favorites (variable name "favorite_count")Number of followers of tweeters (variable name "user_num_followers")Number of tweets published by tweeters (variable name "user_num_tweets")Age in days of tweeters' Twitter accounts (variable name "user_age")Number of tweets including a URL (variable name "url_inclusion")With the variables above, an investigation has been carried out by checking the correlations between the variables and performing a regression analysis. Thus, the relationships between the variables are ascertained and analyzed to determine if it is possible to predict the number of favorites of the hashtags used by museums. The first initial intake is presented in the file cimed-2021-ini.csv, and the intake made 5 weeks later is presented in the file cimed-2021-end.csv.This dataset has contributed to the elaboration of the book chapter:Yeste Moreno, V.; Calduch-Losa, Á.; Serrano-Cobos, J. (2022). Estudio predictivo del uso colectivo de hashtags en museos de la red REMED. En CIMED21 - I Congreso internacional de museos y estrategias digitales. Editorial Universitat Politècnica de València. 251-265. https://doi.org/10.4995/CIMED21.2021.12281
DOI: 10.5281/zenodo.10626056
title: Data for "Structure prediction of stable sodium germanides at 0 and 10 GPa"

description: This repository contains the data and accompanying analysis notebooks to support "Structure prediction of stable sodium germanides at 0 and 10 GPa"
DOI: 10.5281/zenodo.10626057
title: Data for "Structure prediction of stable sodium germanides at 0 and 10 GPa"

description: This repository contains the data and accompanying analysis notebooks to support "Structure prediction of stable sodium germanides at 0 and 10 GPa"
DOI: 10.5281/zenodo.6414082
title: Electrophysiological evidence of subclinical trigeminal dysfunction in patients with COVID-19 and smell impairment: a pilot study

description: The dataset includes raw data regarding the study ‘Electrophysiological evidence of subclinical trigeminal dysfunction in patients with COVID-19 and smell impairment’.


In the excel file clinical, demographic and electrophysiological data of the healthy subjects and patients enrolled in the study are reported. Electrophysiological data include findings from exteroceptive suppression of the masseter (or masseter inhibitory reflex, MIR) and blink reflex (BR). Clinical scale scores are reported at baseline (T0) and at 1 month (T1) and 20 month (T2) follow-up. Data from electrophysiological assessment were collected at baseline (T0) in all subjects, and at 20-month follow-up (T2) in a group of 7 patients.
description: Funding: Ricerca Corrente 2020-2021, Ministry of Health (Italy)
DOI: 10.5281/zenodo.6414083
title: Electrophysiological evidence of subclinical trigeminal dysfunction in patients with COVID-19 and smell impairment: a pilot study

description: The dataset includes raw data regarding the study ‘Electrophysiological evidence of subclinical trigeminal dysfunction in patients with COVID-19 and smell impairment’.


In the excel file clinical, demographic and electrophysiological data of the healthy subjects and patients enrolled in the study are reported. Electrophysiological data include findings from exteroceptive suppression of the masseter (or masseter inhibitory reflex, MIR) and blink reflex (BR). Clinical scale scores are reported at baseline (T0) and at 1 month (T1) and 20 month (T2) follow-up. Data from electrophysiological assessment were collected at baseline (T0) in all subjects, and at 20-month follow-up (T2) in a group of 7 patients.
description: Funding: Ricerca Corrente 2020-2021, Ministry of Health (Italy)
DOI: 10.6084/m9.figshare.22601024
title: Additional file 7 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 7: Table S5. Lookup of all prioritized lipid genes in the Therapeutic Target Database 2022.
DOI: 10.6084/m9.figshare.22601014.v1
title: Additional file 4 of Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

description: Additional file 4: Table S3. The layer-specific markers found from our human postmortem Visium SRT dataset and the previously known layer markers.
DOI: 10.6084/m9.figshare.22601036
title: Additional file 8 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 8: Table S6. Association of lipid index variants with CAD, T2D and NAFLD.
DOI: 10.6084/m9.figshare.22600997
title: Additional file 4 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 4: Table S3. Text mining results for the PoPS+ prioritized genes.
DOI: 10.6084/m9.figshare.22601023
title: Additional file 7 of Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

description: Additional file 7: Table S6. The AD upregulated DEGs, downregulated DEGs, and the GO pathway analyses of those DEGs in our Visium SRT dataset. We also include the 14 published AD-related gene lists, the overlapped genes between 14 previously published AD-related gene lists and AD upregulated/downregulated DEGs identified in our Visium SRT datasets, and the Fisher exact test results in this table.
DOI: 10.6084/m9.figshare.22601014
title: Additional file 4 of Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

description: Additional file 4: Table S3. The layer-specific markers found from our human postmortem Visium SRT dataset and the previously known layer markers.
DOI: 10.6084/m9.figshare.22601024.v1
title: Additional file 7 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 7: Table S5. Lookup of all prioritized lipid genes in the Therapeutic Target Database 2022.
DOI: 10.6084/m9.figshare.22601057
title: Additional file 10 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 10: Table S7. DESE phenotype-tissue association results using both GTEx gene-level and transcript-level selective expression.
DOI: 10.6084/m9.figshare.22601017.v1
title: Additional file 5 of Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

description: Additional file 5: Table S4. The proportion of spots with Aβ+, AT8+, Aβ+/AT8+ pathology which is normalized to the total number of spots in each layer from three AD cases.
DOI: 10.6084/m9.figshare.22601032.v1
title: Additional file 10 of Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

description: Additional file 10: Table S9. The number of spots with Aβ, AT8, and Aβ/AT8 pathology, the number of their adjacent 3-level spots, the AD pathology-associated gene signatures, and GO pathway analyses corresponding to each pathology are shown in this table.
DOI: 10.6084/m9.figshare.22600958.v1
title: Additional file 1 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 1: Table S1. Characteristics of contributing cohorts (as provided by each participating cohort).
DOI: 10.6084/m9.figshare.22600970.v1
title: Additional file 2 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 2: Table S2. Association results for the multi-ancestry index SNPs with the gene prioritization.
DOI: 10.6084/m9.figshare.22601029
title: Additional file 9 of Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease

description: Additional file 9: Table S8. The gene list of eight gene modules and their GO pathway analyses in our Visium SRT dataset. We also include the comparison and Fisher Exact test results by comparing 8 gene modules with 14 published AD-related gene lists in this table.
DOI: 10.6084/m9.figshare.22600958
title: Additional file 1 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 1: Table S1. Characteristics of contributing cohorts (as provided by each participating cohort).
DOI: 10.6084/m9.figshare.22600970
title: Additional file 2 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis

description: Additional file 2: Table S2. Association results for the multi-ancestry index SNPs with the gene prioritization.
DOI: 10.7910/dvn/9argzn/hjlyss
title: Model_oc_91_V2 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/hjnms9
title: Model_oc_102_M&A (v0=1e13).tab

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DOI: 10.7910/dvn/9argzn/jzkacc
title: Model_ic_57_V2 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/kzamal
title: Venus_mantle_V2.dat

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DOI: 10.7910/dvn/9argzn/lbpp34
title: Model_ic_10_M&A (v0=1e12).tab

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title: Model_oc_141_M&A (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/m2jwt3
title: TBL_V1.ps

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DOI: 10.7910/dvn/9argzn/m4obne
title: Model_oc_36_V3 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/mcimjf
title: Model_oc_181_V3 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/mjirsf
title: Model_ic_2_M&A (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/nlk7ny
title: Model_oc_97_M&A (v0=1e12).tab

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DOI: 10.7910/dvn/9argzn/nsbcpo
title: Model_ic_28_M&A (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/nunolk
title: Model_ic_14_V2 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/q2c13a
title: Model_oc_115_V2 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/rbkstj
title: Model_ic_11_V1 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/rkltz9
title: Model_oc_164_V1 (v0=1e14).tab

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title: Model_oc_260_M&A (v0=1e12).tab

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title: Model_oc_76_V1 (v0=1e14).tab

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title: Model_oc_279_M&A (v0=1e13).tab

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title: Model_oc_22_V2 (v0=1e14).tab

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title: Model_oc_103_M&A (v0=1e13).tab

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title: Model_oc_61_V3 (v0=1e14).tab

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title: Model_oc_13_M&A (v0=1e13).tab

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title: Model_oc_21_V1 (v0=1e14).tab

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title: Model_oc_14_M&A (v0=1e13).tab

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title: Model_oc_77_V3 (v0=1e14).tab

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title: Model_oc_184_V3 (v0=1e14).tab

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title: Model_oc_49_V3 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/tuhuhb
title: Model_oc_112_M&A (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/ujn4ln
title: Model_ic_39_V2 (v0=1e14).tab

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title: Model_oc_204_M&A (v0=1e14).tab

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title: Model_oc_239_V2 (v0=1e14).tab

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title: Model_oc_97_V3 (v0=1e14).tab

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title: Model_oc_118_V3 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/ykcenm
title: Model_ic_1_V3 (v0=1e14).tab

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DOI: 10.7910/dvn/9argzn/zcoq0m
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title: Model_ic_20_M&A (v0=1e14).tab

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DOI: 10.21227/0jcz-t470
title: Metro vehicle vibration energy harvesting data

description: We collect 200 hours of metro vehicle vibration energy harvesting data in total at intervals of 2 min.
DOI: 10.21227/29av-0j37
title: Metro vehicle vibration energy harvesting data

description: We collect 200 hours of metro vehicle vibration energy harvesting data in total at intervals of 2 min.
DOI: 10.25934/00005903
title: Test Integrity of upload of M02-556

description: Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
DOI: 10.7910/dvn/9argzn/09kf88
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