cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/d88r6svvds.1
title: Study data: Systematic massage prevents the increase in pain during 100-m freestyle sprint in young swimmers: A Randomized Controlled Clinical Trial

description: This study aimed to investigate the effects of repeated bouts of massage, adjusted to swimmer’s training on perceptive, functional and performance outcomes over a sprint and the effects of single bout of short massage on swimmer’s self-reported perceptions after resistance training. This cross-over randomized controlled trial with concealed allocation, assessor blinding and intention-to-treat analysis included 19 male and female competitive swimmers between 12 and 20 years old. Participants were subjected to three 12 min interventions (control, superficial or deep massage) over a week between a resistance and a swimming training and monitored regarding training load and perceptions. After the intervention week we assessed: perceptive (well-being, heaviness, tiredness, discomfort and pain), performance (Sprint time, FINA Points, Stroke characteristics), functional (Flexibility, Squat Jump, Bench press, Proprioception), beliefs and preferences. Analysis: Effects of single massage on perceptive outcomes were analyzed by generalized estimating equations (GEE) with ordinal distribution and cumulative logit link function. Intervention group, training time-points and day of application were used as predictors in the model. Dependent variables were rated by a 5-point likert scale and the first category (nothing) was used as reference unless otherwise stated. Effects of repeated massage on proprioception was analyzed by GEE and remaining outcomes were analyzed by Generalized Linear Mixed Model, both with Gamma distribution and cumulative logit link function. Bonferroni adjustments were used for all significant main effect. Parameter estimates (B) and Exp(B) were reported along with 95% Confidence Intervals, descriptive data were reported as median with minimum and maximum values for categorical data and means with standard errors for continuous data. Pearson’s test was used to explore the correlation between training load and performance and interpreted as small (0.00-0.25), fair (0.26-0.50), moderate to good (0.51-0.75) and excellent (&gt;0.75) . Results: Control had more chances of reporting extreme pain over the first stages of the swimming training (Exp(B)=5.88 CI95%=1.70, 20.28) while the chances for superficial and deep massage were not different throughout the training. Repeated bouts of superficial massage promoted more chances of reporting no pain over the sprint than deep massage (Exp(B)=6.19 CI95%=1.58, 24.15) and control (Exp(B)=4.93 CI95%=1.76, 13.83) but had effects over performance and functional outcomes. Pearson’s correlation showed no important influence of training load over performance (Sprint time r2=0.01 P=0.16; FINA Points r2=0.004 P=0.81). *The dataset is as entered in SPSS for Generalized Linear Mixed Model analyses. **Functional and performance data are in ANOVA format as well to facilitate use by other reseachers.
DOI: 10.17632/7sgjcvjpt9.1
title: mTORC1 promotes cell growth via m6A-dependent mRNA degradation
DOI: 10.17632/w84gwxgbtm.1
title: Dataset for 'Satellite based Budyko framework reveals the human imprint on long-term surface water partitioning across India'

description: The folder 'Fitting_Budyko_Parameter' contains codes and data for obtaining calibrated values of Tixeront- Fu's omega from long-term mean annual precipitation, potential evapotranspiration, and actual evapotranspiration. Codes for performing a split sample test to check the performance of the omega calibration are also in the same folder. Data for the remaining portion of the analysis is extracted from 'ProcessedData.xlsx'. The file contains all physio-climatic and socio-economic characteristics used for analysis. 'CorrelationAnalysis.r' is used to generate correlograms for identifying correlated characteristics. Intra-category correlations are identified from generated correlograms to shortlist characteristics. Further correlations are eliminated by examining a combined correlogram having factors from all categories. 'Main_Code.r' calls the functions 'CART_func.r' and 'RF_func.r' iteratively for each omega threshold defined in 'CART_RF_Model_Thresholds.xlsx'. Pruned and unpruned trees for class prediction are extracted as outputs from 'CART_func.r'. Pruned trees are used to develop a circos plot using the online tool on ‘http://mkweb.bcgsc.ca/tableviewer/visualize/’. Pruning is done using the 1-SE rule (Breiman et al., 1984) Factor predictive importance computed using permutation of variable importance quantification is obtained from 'RF_func.r'. The function also generates confusion matrices indicating the categorization performance of each trained random forest model. Outputs are written to the 'Outputs' folder in appropriately named sub-folders
DOI: 10.17632/hstfswp5nv.1
title: Late-onset Hidradenitis Suppurativa: a cluster analysis of the National Italian Registry IRHIS

description: We analyzed data of 1,100 consecutive newly diagnosed Hidradenitis Suppurativa (HS) patients from 17 Italian outpatient clinics, participating in the IRHIS registry, with the aim of assessing the existence of clusters in the distribution of HS age-at-onset, and of evaluating differences between clusters in demographics, clinical characteristics and HS phenotypes. A detailed description of the methods is reported in Supplementary Materails. In the analysis, we relied on both k-means and Gaussian mixture model (GMM) clustering algorithms. Both methods indicated that a two-clusters model best fitted our data, with early-onset HS peaking in the late teen years (mean= 17.0) and late-onset HS peaking at around age 40 (mean=38.4), with an optimal separation threshold at 28 years. Both univariate and age and sex-adjusted multivariable logistic regression analysis were performed.
DOI: 10.17632/ghvrstw7pw.2
title: SAFmaps - Eucalyptus

description: Developed in the context of SAFmaps containing the georeferenced database and a case study report on SAF production based on the FT-SPK / eucalyptus pathway. SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.17632/5498jdrm87.2
title: SAFmaps - Macaw palm

description: Developed in the context of SAFmaps containing the georeferenced database and a case study report on SAF production based on the HEFA-SPK / macaw palm pathway. SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.17632/jpwggmp9zy.2
title: SAFmaps - Soybean

description: Developed in the context of SAFmaps containing the georeferenced database and a case study report on SAF production based on the HEFA-SPK / soybean pathway. SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.17632/t59v47sshp.2
title: SAFmaps - Palm oil

description: Developed in the context of SAFmaps containing the georeferenced database and a case study report on SAF production based on the HEFA-SPK / palm oil pathway. SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.17632/dp4y36fjw5.2
title: SAFmaps - Sugarcane

description: Developed in the context of SAFmaps containing the georeferenced database and a case study report on SAF production based on the ATJ-SPK / ethanol (from sugarcane & corn) pathway. SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.17632/2zc8p9dgg9.2
title: SAFmaps - Beef tallow

description: Developed in the context of SAFmaps containing the georeferenced database and a case study report on SAF production based on the HEFA-SPK pathway, combing feedstocks (one of them is beef tallow). SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.6084/m9.figshare.14079807
title: Modeling metallicity code and data

description: Code and data for generating Figures for the paper 'Modeling metallicity: Low level visual features support robust material perception' by Joshua Harvey and Hannah Smithson.<br>To run the code fully, you must download and unzip the directories 'images' and 'pyramids', and place these in the /Metallicity_share/Figures/Figure3 directory.
DOI: 10.6084/m9.figshare.14079807.v1
title: Modeling metallicity -- code and data for generating figures

description: Code and data for generating Figures for the paper 'Modeling metallicity: Low level visual features support robust material perception' by Joshua Harvey and Hannah Smithson.<br>To run the code fully, you must download and unzip the directories 'images' and 'pyramids', and place these in the /Metallicity_share/Figures/Figure3 directory.
DOI: 10.17632/nj7f67k8vv.2
title: SAFmaps - Steel off-gases

description: Case study report on SAF production based on ATJ-SPK pathway, using steel off-gases, developed in the context of SAFmaps. SAFmaps is a database platform with information on the potential of promising feedstock for the production of Sustainable Aviation Fuels (SAF) in Brazil. SAFmaps includes a database of different feedstocks, background information and assessment results.
DOI: 10.17632/zs5z2bvkk6.1
title: LES Simulation Data for Dust Entrainment

description: Description: This dataset includes one MATLAB script and LES simulation data for one ensemble. Several such ensembles were used to compute the conditionally averaged quantities of the flow in the paper “An entrainment paradox: how hysteretic saltation and secondary transport augment atmospheric uptake of aeolian source materials” by Santosh Rana, William Anderson, and Mackenzie Day. Metadata: Metadata_ConditionalStress.txt - File name descriptions for surface stress. Metadata_ ConditionalVelocity.txt - File name descriptions for velocity fluctuations. Metadata_STATS_FA.txt - File name descriptions for Reynolds averaged velocities. Metadata_MATLABscript.txt – Information about the MATLAB script. Data: ConditionalStress*.dat.c* - Each of these files contains two columns of data. The first and second column correspond to stresses T_xy and T_yz respectively. In the paper, only T_xy is used in the results section. The first * in the filename can have value “Alpha”, “Beta” or “Gamma” corresponding to Mode 1, Mode 2 and Mode3 conditional averaging. The second * in the filename can have a numerical value between 0 and 15 indicating the number of parallel process. ConditionalVelocity*.dat.c* - Each of these files contains three columns of data for conditionally averaged streamwise velocity (u), spanwise velocity (v) and wall-normal velocity (w). The first * in the filename can have value “Alpha”, “Beta” or “Gamma” corresponding to Mode 1, Mode 2 and Mode3 conditional averaging. The second * in the filename can have a numerical value between 0 and 15 indicating the number of parallel process. STATS_FA.dat.c* - These files contain data for Reynolds averaged streamwise velocity (u), spanwise velocity (v) and wall-normal velocity (w). The * in the filename can have a numerical value between 0 and 15 indicating the number of parallel process. Script: PostProcess.m – This script calculates Reynolds averaged and conditionally averaged streamwise velocity (u), spanwise velocity (v) and wall-normal velocity and their fluctuations. Additional information: Alpha, Beta and Gamma as used in the file names indicate Mode 1, Mode 2 and Mode 3 dust entrainment respectively.
DOI: 10.17632/mj8sxgfzyj.2
title: Digital Data Amount (DDA) - Data Base

description: Scrips and data base of digital water from multiple precipitation sources in the São Paulo State, Brazil.
DOI: 10.17632/4js9b8pkrk.2
title: Muller-Lyer_illusion_DiB

description: The dataset provides data on cognitive and temperamental determinants of the Müller-Lyer illusion recorded in a group of 170 participants aged 20-33. The cognitive predictors included: the field dependent-independent cognitive style and the efficacy of attention networks: alerting, orienting, and executive control. The temperamental indicators were searched in the context of the Strelau’s Regulative Theory of Temperament. The results confirmed that susceptibility to the M-L illusion is associated with field dependence. Rhythmicity as a temperament trait moderated the relationship between susceptibility to the Müller-Lyer illusion and the efficacy of alerting. At a low level of Rhythmicity, a relationship between lower efficacy of the alerting network and higher susceptibility to the illusion was observed.
DOI: 10.17632/h2pfbjngbh.1
title: Global data analysis supports tobacco smoking is the fundamental element of geographic gender disparities in hidradenitis suppurativa supplementary file

description: The supplementary table for the article "Global data analysis supports tobacco smoking is the fundamental element of geographic gender disparities in hidradenitis suppurativa"
DOI: 10.17632/8zmjdkkknc.1
title: Araucanos

description: This dataset contains the bathymetry and turbidity maps of five Araucanian Lakes .
DOI: 10.17632/stwvcrkswf.1
title: Shen_et al 2021_SARS-CoV-2 Variant B.1.1.7 Neutralization_Neutralization Titration Data

description: Serum dilution data for Figure 2 of manuscript titled "SARS-CoV-2 variant B.1.1.7 is susceptible to neutralizing antibodies elicited by ancestral Spike vaccines".
DOI: 10.17632/r3hybw89zz.1
title: Safe and sound: fireflies produce ultrasonic clicks during flight – a potential aposematic anti-bat signal - data

description: Audio recordings of fireflies and the example of the code
DOI: 10.25345/c55z2g
title: MassIVE MSV000086934 - Untargeted lipidomics of NPC1 mouse cerebellum
title: Untargeted lipidomics of NPC1 mouse cerebellum at both a presymptomatic and symptomatic point of disease
DOI: 10.25345/c5250v
title: MassIVE MSV000086935 - Proteomic analysis of the NPC1 null mouse after treatment with HPBCD
title: Proteomic analysis of the NPC1 null mouse after treatment with HPBCD
DOI: 10.5281/zenodo.4556265
title: CoVaxxy Tweet IDs data set

description: A collection of Tweet IDs related to Covid-19 Vaccines, gathered from Twitter since Jan 4, 2021. Please see https://arxiv.org/abs/2101.07694 for more information.
DOI: 10.3886/e132982v1
title: A five-factor inventory with evaluatively neutralized items

description: Personality is normally measured by means of self-ratings. Despite some drawbacks, the method is here to stay, and improving on it, particularly with regards to social desirability, is essential. One way to do this is evaluative neutralization, i.e. to rephrase items such that it is less obvious to the respondent what would be a desirable response. We present an evaluatively neutralized five-factor inventory and compare it to the IPIP-NEO (Goldberg et al., 2006). Psychometric analyses revealed that the new inventory has high factor homogeneity, relatively independent facets with acceptable homogeneity and normally distributed ratings, and generally evaluatively neutral ratings (as indicated by level of item popularity). In sum, this new inventory captures the same personality variance as other five factor inventories but with less influence from individual differences in evaluative responding, resulting in less correlation between factors and a factor structure more in line with the simple structure model than many other five factor inventories. Evaluatively neutralized inventories should be particularly useful when the factor structure is central to the research question and when focus is on discriminant validity, such as identification of theoretically valid relationships between personality and other concepts.
DOI: 10.3886/e133002
title: COVID-19 Stress and Eating and Drinking Behaviors in the United States during the Early Stages of the Pandemic

description: https://osf.io/myfts/
DOI: 10.3886/e133002v1
title: COVID-19 Stress and Eating and Drinking Behaviors in the United States during the Early Stages of the Pandemic

description: https://osf.io/myfts/
DOI: 10.5517/ccdc.csd.cc24d9f9
title: CCDC 1978030: Experimental Crystal Structure Determination

description: Related Article: Robert T. Kumah, Paranthaman Vijayan, Stephen O. Ojwach|2020|Catal.Lett|151|344|doi:10.1007/s10562-020-03311-y
DOI: 10.6084/m9.figshare.14080049
title: BRAVO TNBC Expression dataset

description: Expression data from a cohort of triple negative breast cancer.
DOI: 10.6084/m9.figshare.14080040
title: An analysis of sarcopenia increasing osteopenia risk

description: <br><b><b>Characteristics of the 20 eligible studies</b></b>
DOI: 10.6084/m9.figshare.13349282
title: Drosophila central brain connectivity

description: See https://github.com/mhturner/SC-FC for analysis code and figure generation using this dataset<br><br>-StructuralMatrix_branson.csv and CorrelationMatrix_Branson.csv are the fine-grained Branson segmentation based structural and functional connectivity matrices shown in Fig. S3.<br>-body_ids.csv is the list of unique body ID numbers in the Hemibrain connectome that were used to compute structural connectivity.<br><br>data_TurnerMannClandinin:<br>Compressed directory containing these subdirectories (in <b>bold</b>):<b>-atlas_data</b> contains original Ito and Branson brain atlas/segmentation files<br><b></b><b>-ito_68_atlas</b> & <b>branson_999_atlas</b> each contain .nii.gz image files containing the registered brain atlas mask for each fly. The mask numbers correspond to the regions as in Original_Index_panda_full.csv and atlas_roi_values<br><br><b>-ito_responses</b> & <b>branson_responses</b> each contain pandas dataframes, one for each fly, describing raw fluorescence responses for each brain region in that atlas. The sampling rate is 1.2 Hz.<br>-<b>connectome_connectivity</b> contains computed pandas dataframe files for various structural connectivity metrics, for the regions included in the main paper analysis<br>-<b>hemi_2_atlas</b> contains results of structural connectivity computations from R code included in the corresponding GitHub repository.<br><br>-<b>subsample</b> contains numpy data the result of the region subsampling analysis<br>-<b>template_brains</b> contains template brain files in the original (JFRC2) brain template space as well as the same atlases transformed to JRC2018 space (in both .tif and .nii.gz format)<br>registration.xform.xipTransform file (CMTK format) to convert from JFRC2 template brain space, where the Ito atlas and Branson segmentation are, to JRC2018 template brain space<br><br>
DOI: 10.25345/c5xf71
title: MassIVE MSV000086936 - GNPS_MetanolAgua_1-5_Pyropia_sp6
title: Pyropia acanthophora, MeOH_extract, metabolomics profiles
DOI: 10.6084/m9.figshare.13349282.v2
title: Drosophila central brain connectivity

description: See https://github.com/mhturner/SC-FC for analysis code and figure generation using this dataset<br><br>data_TurnerMannClandinin:<br>Compressed directory containing these subdirectories (in <b>bold</b>):<b>-atlas_data</b> contains original Ito and Branson brain atlas/segmentation files<br><b></b><b>-ito_68_atlas</b> & <b>branson_999_atlas</b> each contain .nii.gz image files containing the registered brain atlas mask for each fly. The mask numbers correspond to the regions as in Original_Index_panda_full.csv and atlas_roi_values<br><br><b>-ito_responses</b> & <b>branson_responses</b> each contain pandas dataframes, one for each fly, describing raw fluorescence responses for each brain region in that atlas. The sampling rate is 1.2 Hz.<br>-<b>connectome_connectivity</b> contains computed pandas dataframe files for various structural connectivity metrics, for the regions included in the main paper analysis<br>-<b>hemi_2_atlas</b> contains results of structural connectivity computations from R code included in the corresponding GitHub repository.<br><br>-<b>subsample</b> contains numpy data the result of the region subsampling analysis<br>-<b>template_brains</b> contains template brain files in the original (JFRC2) brain template space as well as the same atlases transformed to JRC2018 space (in both .tif and .nii.gz format)<br>registration.xform.xipTransform file (CMTK format) to convert from JFRC2 template brain space, where the Ito atlas and Branson segmentation are, to JRC2018 template brain space<br><br>
DOI: 10.5281/zenodo.4554488
title: Painel do WHO Coronavirus Disease (COVID-19)

description: Painel do WHO Coronavirus Disease (COVID-19) Última atualização dos dados: 2021/2/21, 4:21 pm CET Dados diários agregados de caso e contagem de óbitos De 31 de dezembro de 2019 a 21 de março de 2020, um OMS coletou os números de casos e óbitos COVID-19 confirmados por meio de comunicações oficiais no âmbito do Regulamento Sanitário Internacional (RSI, 2005), complementadas pelo monitoramento dos sites oficiais dos ministérios da saúde e contas de mídia social. Desde 22 de março de 2020, os dados globais são compilados por meio de painéis específicos da região da OMS (consulte os links abaixo) e / ou dados de contagem agregados relatados à sede da OMS diariamente. Mais em: https://covid19.who.int/info Globalmente, a partir das 14h43 CEST, 18 de outubro de 2020, houve 39.596.858 casos confirmados de COVID-19, incluindo 1.107.374 mortes, notificados à OMS. Última atualização de dados: 18/10/2020, 14h43 CEST Todas as publicações publicadas por WHO CC BY-NC-SA 3.0 IGO ;
description: Fonte da informação Painel de Emergência de Saúde da OMS https://covid19.who.int/
DOI: 10.5281/zenodo.4104936
title: Painel do WHO Coronavirus Disease (COVID-19)

description: Painel do WHO Coronavirus Disease (COVID-19) Última atualização dos dados: 2021/2/21, 4:21 pm CET Dados diários agregados de caso e contagem de óbitos De 31 de dezembro de 2019 a 21 de março de 2020, um OMS coletou os números de casos e óbitos COVID-19 confirmados por meio de comunicações oficiais no âmbito do Regulamento Sanitário Internacional (RSI, 2005), complementadas pelo monitoramento dos sites oficiais dos ministérios da saúde e contas de mídia social. Desde 22 de março de 2020, os dados globais são compilados por meio de painéis específicos da região da OMS (consulte os links abaixo) e / ou dados de contagem agregados relatados à sede da OMS diariamente. Mais em: https://covid19.who.int/info Globalmente, a partir das 14h43 CEST, 18 de outubro de 2020, houve 39.596.858 casos confirmados de COVID-19, incluindo 1.107.374 mortes, notificados à OMS. Última atualização de dados: 18/10/2020, 14h43 CEST Todas as publicações publicadas por WHO CC BY-NC-SA 3.0 IGO ;
description: Fonte da informação Painel de Emergência de Saúde da OMS https://covid19.who.int/
DOI: 10.25345/c5sn53
title: MassIVE MSV000086937 - Proteomics - LCWE Kawasaki Model
title: Murine vasculitis was induced via Lactobacillus casei cell wall extract (LCWE) injection in 5-week-old male mice. Groups of mice were injected with LCWE alone, LCWE and the IL-1 receptor antagonist anakinra, or saline for controls. Upper heart tissue was assessed by quantitative mass spectrometry analysis.
DOI: 10.14457/ku.res.2019.1
title: ประสิทธิภาพของสารสกัดหยาบจากพืชวงศ์ขิงต่อการยับยั้งการเจริญของเชื้อรา Fusarium sp. สาเหตุโรคเหี่ยวแคนตาลูปในห้องปฏิบัติการ (เรื่องเต็มการประชุมทางวิชาการของมหาวิทยาลัยเกษตรศาสตร์ ครั้งที่ 57: สาขาพืช, สาขาสัตว์, สาขาสัตวแพทยศาสตร์, สาขาประมง, สาขาส่งเสริมการเกษตรและคหกรรมศาสตร์)