cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.35078/xkuxhv/qnpzk7
title: Boa Vista B.jpg

description: :unav
DOI: 10.35078/xkuxhv/grlmyg
title: Joaquim F. Campos D.jpg

description: :unav
DOI: 10.35078/xkuxhv/nouuul
title: Gameleira C.jpg

description: :unav
DOI: 10.35078/xkuxhv/y1d9vk
title: Joaquim Salvador B.jpg

description: :unav
DOI: 10.35078/xkuxhv/nplxpb
title: Geraldo Pereira Santos A.jpg

description: :unav
DOI: 10.35078/xkuxhv/qytr9q
title: Cabeceira do Engenho B.jpg

description: :unav
DOI: 10.35078/xkuxhv/rknxjo
title: Manoel da Anita C.jpg

description: :unav
DOI: 10.35078/xkuxhv/2v523u
title: Boa Vista A.jpg

description: :unav
DOI: 10.35078/xkuxhv/10uuj7
title: Goiabas Pov. B.jpg

description: :unav
DOI: 10.35078/xkuxhv/fqubym
title: Gameleira A.jpg

description: :unav
DOI: 10.35078/xkuxhv/wkasvh
title: Goiabas Pov. A.jpg

description: :unav
DOI: 10.35078/xkuxhv/pm0ber
title: Guarani B.jpg

description: :unav
DOI: 10.35078/xkuxhv/2tmbbz
title: Gameleira B.jpg

description: :unav
DOI: 10.35078/xkuxhv/drho7o
title: José Lambança B.jpg

description: :unav
DOI: 10.35078/xkuxhv/qgp9fb
title: Prata B.jpg

description: :unav
DOI: 10.35078/xkuxhv/ndzcxe
title: Prata A.jpg

description: :unav
DOI: 10.35078/xkuxhv/xshffy
title: Manoel da Anita B.jpg

description: :unav
DOI: 10.35078/xkuxhv/v57bhf
title: José de Freitas B.jpg

description: :unav
DOI: 10.35078/xkuxhv/ttmgwq
title: José de Freitas A.jpg

description: :unav
DOI: 10.35078/xkuxhv/xuwtfe
title: Amável N. Ferreira B.jpg

description: :unav
DOI: 10.35078/xkuxhv/8mdqos
title: DICIONARIO_KARDEX_PROGRAMA_CONTROLE_DOENÇA_CHAGAS.pdf

description: Dicionário para interpretação da ficha epidemiologica (Kardex)
DOI: 10.3886/e169162
title: Lessons from Montana Cannabis Initiative I-190's passing

description: Montana passed a medical cannabis law in 2004 but in 2011 restricted it severely enough to effectively nullify the legislation. Restrictions were loosened in 2016 and 2019, leading to a recreational cannabis bill in 2020. This paper investigates factors involved in Montana’s cannabis legislation. Cannabis legalization has largely been a political issue and Montana being a majority republican state makes recent changes to its cannabis laws particularly interesting. This paper examines demographic factors that could help explain Montana’s passing its recreational cannabis law; specifically what effect age and related factors had on the results.
DOI: 10.3886/e169162v1
title: Lessons from Montana Cannabis Initiative I-190's passing

description: Montana passed a medical cannabis law in 2004 but in 2011 restricted it severely enough to effectively nullify the legislation. Restrictions were loosened in 2016 and 2019, leading to a recreational cannabis bill in 2020. This paper investigates factors involved in Montana’s cannabis legislation. Cannabis legalization has largely been a political issue and Montana being a majority republican state makes recent changes to its cannabis laws particularly interesting. This paper examines demographic factors that could help explain Montana’s passing its recreational cannabis law; specifically what effect age and related factors had on the results.
DOI: 10.6084/m9.figshare.19678881
title: IRB21-004451

description: IRB21-004451 Metastatic Prostate Cancer Cohort
DOI: 10.6084/m9.figshare.19678881.v1
title: IRB21-004451

description: IRB21-004451 Metastatic Prostate Cancer Cohort
DOI: 10.6084/m9.figshare.19678833
title: IRB19-006675 Localized PCa Part 2

description: 12 files for last 4 urine samples in IRB19-006675 Localized PCa cohort.
DOI: 10.6084/m9.figshare.19678833.v1
title: IRB19-006675 Localized PCa Part 2

description: 12 files for last 4 urine samples in IRB19-006675 Localized PCa cohort.
DOI: 10.6084/m9.figshare.19678638
title: IRB19-006675 Localized PCa Part 1

description: IRB19-006675 Localized PCa Cohort
DOI: 10.6084/m9.figshare.19678638.v1
title: IRB19-006675 Localized PCa Part 1

description: IRB19-006675 Localized PCa Cohort
DOI: 10.6084/m9.figshare.19678467
title: IRB19-006675 BPH

description: IRB19-006675 BPH Cohort Files
DOI: 10.6084/m9.figshare.19678467.v1
title: IRB19-006675 BPH

description: IRB19-006675 BPH Cohort Files
DOI: 10.6084/m9.figshare.19375088.v2
title: Herpes simplex virus

description: this data obtained from pregnant women in wadmadani Sudan<br>
DOI: 10.5281/zenodo.6367546
title: Generalized Rayleigh-Taylor Instability: Ion Inertia, Acceleration Forces, and E Region Drivers

description: electron density and growth rate data files
DOI: 10.5281/zenodo.6367545
title: Generalized Rayleigh-Taylor Instability: Ion Inertia, Acceleration Forces, and E Region Drivers

description: electron density and growth rate data files
DOI: 10.23641/asha.19661130
title: Self-reported hearing loss and risk factors (Dillard et al., 2022)

description: <strong>Purpose:</strong> The purpose of this study was to determine the prevalence of self-reported hearing loss and associated risk factors in a representative population-based study of Wisconsin residents. <strong>Method:</strong> Survey of the Health of Wisconsin participants with data on self-reported hearing loss were included. We reported prevalence of self-reported hearing loss with corresponding 95% confidence intervals (CIs), overall, and stratified by age and sex. Age- and sex-adjusted and multivariable logistic regression models were used to evaluate determinants of self-reported hearing loss, and results are presented as odds ratios with corresponding 95% CIs. <strong>Results: </strong>There were 2,767 participants (50.7% men) with a mean age of 46 years (range: 21–74) in this study. Prevalence of self-reported hearing loss was 26.8% (24.4, 28.4) and was higher in men (30.3% [27.1, 33.4]) than in women (22.5% [19.9, 25.0]). Prevalence increased with age. After multivariable adjustment, age (per +1 year increase; 1.05 [1.04, 1.06]), male sex (1.57 [1.18, 2.08]), having two chronic diseases (vs. 0; 1.93 [1.16, 3.23]), occupational (2.47 [1.91, 3.19]) and recreational (1.58 [1.22, 2.04]) noise exposure, and poor diet (1.88 [1.28, 2.78]) were associated with higher odds of self-reported hearing loss. <strong>Conclusions: </strong>Hearing loss is a highly prevalent public health concern and may be at least partially modifiable via interventions to reduce noise exposure and promote health. Statewide prevalence and risk factor data can be used to inform public health practice and promote hearing loss prevention. <br> <strong>Supplemental Material S1. </strong>Odds ratios (<em>OR</em>s) and corresponding 95% confidence intervals (CI) from separate age-adjusted models of self-reported hearing loss stratified by sex. Estimates are weighted for the sampling design. <br> <strong>Supplemental Material S2.</strong> Odds ratios (<em>OR</em>s) and corresponding 95% confidence intervals (CI) from multivariable-adjusted models of self-reported hearing loss stratified by sex. Estimates are weighted for the sampling design. <br> Dillard, L. K., Walsh, M. C., Merten, N., Cruickshanks, K. J., & Schultz, A. (2022). Prevalence of self-reported hearing loss and associated risk factors: Findings from the Survey of the Health of Wisconsin.<em> Journal of Speech, Language, and Hearing Research</em>. Advance online publication. https://doi.org/10.1044/2022_JSLHR-21-00580
DOI: 10.22003/xfel.eu-data-002834-00
title: Dynamics of exciton condensation in a charge-density-wave system
DOI: 10.22003/xfel.eu-data-002819-00
title: Structural Biology of Bacterial Insecticides
DOI: 10.22003/xfel.eu-data-002770-00
title: How does photolyase repair DNA?
DOI: 10.22003/xfel.eu-data-002859-00
title: Relativistic laser driven dynamics of solids and heating of buried layers probed with high spatial and temporal resolution
DOI: 10.22003/xfel.eu-data-003226-00
title: Set-up of eTOFs and Pump-Probe
DOI: 10.6084/m9.figshare.19625997
title: The antiSMASH results of the Umbilicaria spp and Dermatocarpon miniatum and the candidate gyrophoric acid gene clusters from Umbilicaria spp. Article: A candidate gene cluster for the bioactive natural product gyrophoric acid in lichen-forming fungi

description: The antiSMASH results of the Umbilicaria spp and Dermatocarpon miniatum and the candidate gyrophoric acid gene clusters from Umbilicaria spp. Article: A candidate gene cluster for the bioactive natural product gyrophoric acid in lichen-forming fungi
DOI: 10.23641/asha.19661130.v1
title: Self-reported hearing loss and risk factors (Dillard et al., 2022)

description: <strong>Purpose:</strong> The purpose of this study was to determine the prevalence of self-reported hearing loss and associated risk factors in a representative population-based study of Wisconsin residents. <strong>Method:</strong> Survey of the Health of Wisconsin participants with data on self-reported hearing loss were included. We reported prevalence of self-reported hearing loss with corresponding 95% confidence intervals (CIs), overall, and stratified by age and sex. Age- and sex-adjusted and multivariable logistic regression models were used to evaluate determinants of self-reported hearing loss, and results are presented as odds ratios with corresponding 95% CIs. <strong>Results: </strong>There were 2,767 participants (50.7% men) with a mean age of 46 years (range: 21–74) in this study. Prevalence of self-reported hearing loss was 26.8% (24.4, 28.4) and was higher in men (30.3% [27.1, 33.4]) than in women (22.5% [19.9, 25.0]). Prevalence increased with age. After multivariable adjustment, age (per +1 year increase; 1.05 [1.04, 1.06]), male sex (1.57 [1.18, 2.08]), having two chronic diseases (vs. 0; 1.93 [1.16, 3.23]), occupational (2.47 [1.91, 3.19]) and recreational (1.58 [1.22, 2.04]) noise exposure, and poor diet (1.88 [1.28, 2.78]) were associated with higher odds of self-reported hearing loss. <strong>Conclusions: </strong>Hearing loss is a highly prevalent public health concern and may be at least partially modifiable via interventions to reduce noise exposure and promote health. Statewide prevalence and risk factor data can be used to inform public health practice and promote hearing loss prevention. <br> <strong>Supplemental Material S1. </strong>Odds ratios (<em>OR</em>s) and corresponding 95% confidence intervals (CI) from separate age-adjusted models of self-reported hearing loss stratified by sex. Estimates are weighted for the sampling design. <br> <strong>Supplemental Material S2.</strong> Odds ratios (<em>OR</em>s) and corresponding 95% confidence intervals (CI) from multivariable-adjusted models of self-reported hearing loss stratified by sex. Estimates are weighted for the sampling design. <br> Dillard, L. K., Walsh, M. C., Merten, N., Cruickshanks, K. J., & Schultz, A. (2022). Prevalence of self-reported hearing loss and associated risk factors: Findings from the Survey of the Health of Wisconsin.<em> Journal of Speech, Language, and Hearing Research</em>. Advance online publication. https://doi.org/10.1044/2022_JSLHR-21-00580
DOI: 10.5281/zenodo.6505565
title: Pupal epidermis ATAC-seq (D. melanogaster) (processed BAM files)

description: Processed Binary Alignment Map files for fruitfly pupal epidermis ATAC-seq data
DOI: 10.5281/zenodo.6505564
title: Pupal epidermis ATAC-seq (D. melanogaster) (processed BAM files)

description: Processed Binary Alignment Map files for fruitfly pupal epidermis ATAC-seq data
DOI: 10.6084/m9.figshare.3761562.v2203
title: Online Labour Index: Measuring the Online Gig Economy for Policy and Research

description: Data repository for the data underlying the Online Labour Index. See http://ilabour.oii.ox.ac.uk online-labour-index/ for details.
DOI: 10.25318/3810014901-eng
title: Urban greenness and normalized difference vegetation index by population centre

description: Greenness measures based on normalized difference vegetation index (NDVI), including percentage area classed as green and average NDVI, by population centre.
DOI: 10.25318/3810014901-fra
title: Verdure urbaine et indice de végétation par différence normalisée selon le centre de population

description: Mesures de verdure dérivées de l'indice de végétation par différence normalisée (IVDN), y compris le pourcentage de la superficie classée comme verte et l'IVDN moyen, selon le centre de population.
DOI: 10.57703/ce-g3cbs
title: Nanoparticle-Coated Bottom Surface of a Brain Implant Probe

description: Associated publication: Ding, R.; Miller, N. C.; Woeppel K. M.; Cui X. T.; Jacobs T. D. B. Surface area and local curvature: Why roughness improves the bioactivity of neural implants. Langmuir 2022, Accepted.

Material: Neural Implant, Nanoparticle-coated, Bottom Surface;

Make and model: A1×16-3 mm-100-703, NeuroNexus, Ann Arbor, MI, USA. Subsequently coated with thiolated silica nanoparticles;

For more details: See Associated Publication.
DOI: 10.57703/ce-6z4nb
title: Uncoated Top Surface of a Brain Implant Probe

description: Associated publication: Ding, R.; Miller, N. C.; Woeppel K. M.; Cui X. T.; Jacobs T. D. B. Surface area and local curvature: Why roughness improves the bioactivity of neural implants. Langmuir 2022, Accepted.

Material: Neural Implant, Uncoated, Top Surface;

Make and model: A1×16-3 mm-100-703, NeuroNexus, Ann Arbor, MI, USA. Subsequently modified by mercaptopropyl trimethoxysilane;

For more details: See Associated Publication.
DOI: 10.5281/zenodo.6506583
title: Action Planning Makes Physical Activity More Automatic, Only If it Is Autonomously Regulated: A Moderated Mediation Analysis

description: Dataset used for analysis.
description: If you have any question about the dataset, please send an email to: silvio.maltagliati@univ-grenoble-alpes.fr
DOI: 10.5281/zenodo.6506582
title: Action Planning Makes Physical Activity More Automatic, Only If it Is Autonomously Regulated: A Moderated Mediation Analysis

description: Dataset used for analysis.
description: If you have any question about the dataset, please send an email to: silvio.maltagliati@univ-grenoble-alpes.fr
DOI: 10.57703/ce-pht67
title: Uncoated Bottom Surface of a Brain Implant Probe

description: Associated publication: Ding, R.; Miller, N. C.; Woeppel K. M.; Cui X. T.; Jacobs T. D. B. Surface area and local curvature: Why roughness improves the bioactivity of neural implants. Langmuir 2022, Accepted.

Material: Neural Implant, Uncoated, Bottom Surface

Make and model: A1×16-3 mm-100-703, NeuroNexus, Ann Arbor, MI, USA. Subsequently modified by mercaptopropyl trimethoxysilane;

For more details: See Associated Publication.
DOI: 10.6084/m9.figshare.19686621
title: Exploring the types of blogs cited in urban planning research

description: This is biblomteric data for citing blogs in academic publications.
DOI: 10.5281/zenodo.6506560
title: Annotated 3D-Models of cuneiform tablets

description: This dataset contains two 3D models of cuneiform clay tablets. The first 3D model is a Middle-Assyrian clay tablet excavated in Haft Tappeh, Iran, the second 3D model covers the cuneiform clay tablet 3D scan of HS 1174, a tablet of the Hilprecht collection which is already published at the university library of Heidelberg. Both tablets are annotated in 2D and 3D and are provided in different representations which included their annotations.
DOI: 10.5281/zenodo.6287171
title: Annotated 3D-Models of cuneiform tablets

description: This dataset contains two 3D models of cuneiform clay tablets. The first 3D model is a Middle-Assyrian clay tablet excavated in Haft Tappeh, Iran, the second 3D model covers the cuneiform clay tablet 3D scan of HS 1174, a tablet of the Hilprecht collection which is already published at the university library of Heidelberg. Both tablets are annotated in 2D and 3D and are provided in different representations which included their annotations.
DOI: 10.6084/m9.figshare.19686639
title: Dataset_ML_KMT2Ar.RData

description: The KMT2A (MLL) gene rearrangements (KMT2A-r) are associated with a diverse spectrum of acute leukemias. Although most KMT2A-r are restricted to nine partner genes, we have recently revealed that KMT2A-USP2 fusions are often missed during FISH screening of these genetic alterations. Therefore, complementary methods are important for appropriate detection of any KMT2A-r. Here we use a machine learning model to unravel the most appropriate markers for prediction of KMT2A-r in various types of acute leukemia. The RData file - <code>Dataset_ML_KMT2Ar.RData</code> - available only contains the TARGET and Beat-AML data due to the control of the others (EGA studies). Downloading and obtaining data are described in the materials and methods section of the paper.
DOI: 10.6084/m9.figshare.19686639.v1
title: Dataset_ML_KMT2Ar.RData

description: The KMT2A (MLL) gene rearrangements (KMT2A-r) are associated with a diverse spectrum of acute leukemias. Although most KMT2A-r are restricted to nine partner genes, we have recently revealed that KMT2A-USP2 fusions are often missed during FISH screening of these genetic alterations. Therefore, complementary methods are important for appropriate detection of any KMT2A-r. Here we use a machine learning model to unravel the most appropriate markers for prediction of KMT2A-r in various types of acute leukemia. The RData file - <code>Dataset_ML_KMT2Ar.RData</code> - available only contains the TARGET and Beat-AML data due to the control of the others (EGA studies). Downloading and obtaining data are described in the materials and methods section of the paper.
DOI: 10.5281/zenodo.6484857
title: Spatial heterogeneity effects on land surface modeling of water and energy partitioning

description: Related code and data used in the manuscript https://doi.org/10.5194/gmd-2022-4, &lt;Spatial heterogeneity effects on land surface modeling of water and energy partitioning&gt;. The latest source code of ELMv1 is available from https://github.com/E3SM-Project/E3SM (last access: September 2020). If you have any questions, please contact lingchengliwhu@gmail.com
DOI: 10.5281/zenodo.6484856
title: Spatial heterogeneity effects on land surface modeling of water and energy partitioning

description: Related code and data used in the manuscript https://doi.org/10.5194/gmd-2022-4, &lt;Spatial heterogeneity effects on land surface modeling of water and energy partitioning&gt;. The latest source code of ELMv1 is available from https://github.com/E3SM-Project/E3SM (last access: September 2020). If you have any questions, please contact lingchengliwhu@gmail.com
DOI: 10.6084/m9.figshare.19686672
title: MIFlowCyt Report

description: MIFlowCyt Report
DOI: 10.6084/m9.figshare.19686672.v1
title: MIFlowCyt Report

description: MIFlowCyt Report
DOI: 10.6084/m9.figshare.19686699
title: MIFlowCyt-EV Report

description: MIFlowCyt-EV Report
DOI: 10.6084/m9.figshare.19686699.v1
title: MIFlowCyt-EV Report

description: MIFlowCyt-EV Report
DOI: 10.5281/zenodo.6506654
title: Data for Microkinetic modeling of the transient CO2 methanation with DFT-based uncertainties in a Berty reactor

description: Dataset and scripts for the manuscript "Microkinetic modeling of the transient CO2 methanation with DFT-based uncertainties in a Berty reactor", which has been submitted for review. The file contains all the raw data and the evaluation of the experiments. Additionally, all scripts for the microkinetic model are provided to perform transient simulations with all 5000 methanation mechanisms investigated in the manuscript.
DOI: 10.6084/m9.figshare.15121272
title: Metabolic flux analysis of cancer models in 2D and 3D culture

description: Datasets for the publication titled: Metabolic flux analysis of 3D spheroids reveals significant differences in glucose metabolism from matched 2D cultures of colorectal cancer and pancreatic ductal adenocarcinoma cell lines. (BMC Cancer & Metabolism, doi: 10.1186/s40170-022-00285-w) <br> From two colorectal cancer and two pancreatic ductal adenocarcinoma cell lines, matched 2D and 3D spheroid cultures were grown and assessed for simple growth properties. Metabolic flux analysis, focused on glucose metabolism, was performed using Seahorse Bioscience XF analyzers. Measurement of glucose, glutamine, and lactate in culture media was performed using standard assay kits and levels of metabolically-relevant proteins (GLUT1, MCT1, MCT4, TOMM20, UCP2) were measured via flow cytometry.
DOI: 10.6084/m9.figshare.15121272.v4
title: Metabolic flux analysis of cancer models in 2D and 3D culture

description: Datasets for the publication titled: Metabolic flux analysis of 3D spheroids reveals significant differences in glucose metabolism from matched 2D cultures of colorectal cancer and pancreatic ductal adenocarcinoma cell lines. (BMC Cancer & Metabolism, doi: 10.1186/s40170-022-00285-w) <br> From two colorectal cancer and two pancreatic ductal adenocarcinoma cell lines, matched 2D and 3D spheroid cultures were grown and assessed for simple growth properties. Metabolic flux analysis, focused on glucose metabolism, was performed using Seahorse Bioscience XF analyzers. Measurement of glucose, glutamine, and lactate in culture media was performed using standard assay kits and levels of metabolically-relevant proteins (GLUT1, MCT1, MCT4, TOMM20, UCP2) were measured via flow cytometry.
DOI: 10.6084/m9.figshare.15121272.v3
title: Metabolic flux analysis of cancer models in 2D and 3D culture

description: Datasets for the publication titled: Metabolic flux analysis of 3D spheroids reveals significant differences in glucose metabolism from matched 2D cultures of colorectal cancer and pancreatic ductal adenocarcinoma cell lines. (submitted, under review)<br>From two colorectal cancer and two pancreatic ductal adenocarcinoma cell lines, matched 2D and 3D spheroid cultures were grown and assessed for simple growth properties. Metabolic flux analysis, focused on glucose metabolism, was performed using Seahorse Bioscience XF analyzers. Measurement of glucose, glutamine, and lactate in culture media was performed using standard assay kits and levels of metabolically-relevant proteins (GLUT1, MCT1, MCT4, TOMM20, UCP2) were measured via flow cytometry.
DOI: 10.6084/m9.figshare.19686447
title: Supplementary Table S1. Patient-level Data

description: Demographics, clinicopathological characteristics and EV data for all patient cohorts
DOI: 10.6084/m9.figshare.19686447.v2
title: Supplementary Table S1. Patient-level Data

description: Demographics, clinicopathological characteristics and EV data for all patient cohorts
DOI: 10.6084/m9.figshare.19686447.v1
title: Supplementary Table S1. Patient-level Data

description: Demographics, clinicopathological characteristics and EV data for all patient cohorts
DOI: 10.57703/ce-r6qzw
title: Neural Implant, Nanoparticle-coated, Top Surface, SEM Cross-section

description: Associated publication: Ruikang Ding, Nathaniel C. Miller, Kevin M. Woeppel, Xinyan T. Cui, Tevis D. B. Jacobs “Surface area and local curvature: Why roughness improves the bioactivity of neural implants” Langmuir 2022 “Accepted”

Material: Nanoparticle-coated neural implant;

Make and model: A1×16-3 mm-100-703, NeuroNexus, Ann Arbor, MI, USA. Subsequently coated with thiolated silica nanoparticles;

Surface: Top cross-sectioned by focused ion beam;

For more details: See Associated Publication.
DOI: 10.5281/zenodo.6506679
title: SVAFotate supporting files and data

description: Here we provide input BED files for use with SVAFotate that are derived from the SV datasets generated by CCDG, gnomAD, and 1000G. These are provided for GRCh37 and GRCh38 reference builds and the files are named:<br> <br> SVAFotate_core_SV_popAFs.GRCh37.bed.gz<br> SVAFotate_core_SV_popAFs.GRCh38.bed.gz Additional data files are included that contain the information necessary to generate the NeoSeq analysis as described in the SVAFotate manuscript. These correspond to SV calls made by the variant callers Smoove and Manta and annotations provided by SVAFotate using the provisional BED files listed above and also a custom NeoSeq-specific BED file. These files are named:<br> <br> manta_proband_GTs_AFs_NeoSeq_BED.txt<br> manta_proband_GTs_AFs_provisional_BED.txt<br> smoove_proband_GTs_AFs_NeoSeq_BED.txt<br> smoove_proband_GTs_AFs_provisional_BED.txt