cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19497933
title: Additional file 3 of The temporal pattern and lifestyle associations of respiratory virus infection in a cohort study spanning the first two years of life

description: Additional file 3: Table S5. Clinical variables and respiratory virus swab results for visits to 24 months.
DOI: 10.6084/m9.figshare.19497933.v1
title: Additional file 3 of The temporal pattern and lifestyle associations of respiratory virus infection in a cohort study spanning the first two years of life

description: Additional file 3: Table S5. Clinical variables and respiratory virus swab results for visits to 24 months.
DOI: 10.6084/m9.figshare.19497930
title: Additional file 2 of The temporal pattern and lifestyle associations of respiratory virus infection in a cohort study spanning the first two years of life

description: Additional file 2: Table S4. Data for exploring the association between early respiratory viral infection and later wheeze.
DOI: 10.6084/m9.figshare.19497922
title: Additional file 1 of A microCT-based atlas of the central nervous system and midgut in sea spiders (Pycnogonida) sheds first light on evolutionary trends at the family level

description: Additional file 1: Table S1. List of species studied, collection sites and methods applied.
DOI: 10.6084/m9.figshare.19497922.v1
title: Additional file 1 of A microCT-based atlas of the central nervous system and midgut in sea spiders (Pycnogonida) sheds first light on evolutionary trends at the family level

description: Additional file 1: Table S1. List of species studied, collection sites and methods applied.
DOI: 10.6084/m9.figshare.19497973
title: Additional file 1 of Influence of Device Geometry and Imperfections on the Interpretation of Transverse Magnetic Focusing Experiments

description: Additional file 1. Derivation of mean free path formula (Eq. 11).
DOI: 10.6084/m9.figshare.19497973.v1
title: Additional file 1 of Influence of Device Geometry and Imperfections on the Interpretation of Transverse Magnetic Focusing Experiments

description: Additional file 1. Derivation of mean free path formula (Eq. 11).
DOI: 10.6084/m9.figshare.19497979
title: Additional file 2 of The Bergen Facebook Addiction Scale: its psychometric properties and invariance among women with eating disorders

description: Additional file 2. Additional analysis not included in the manuscript (exploratory factor analysis, BFAS difference across different age groups, multicollinearity of the BFAS.
DOI: 10.6084/m9.figshare.19497979.v1
title: Additional file 2 of The Bergen Facebook Addiction Scale: its psychometric properties and invariance among women with eating disorders

description: Additional file 2. Additional analysis not included in the manuscript (exploratory factor analysis, BFAS difference across different age groups, multicollinearity of the BFAS.
DOI: 10.6073/pasta/08517214b023f020199e178f4e6750c9
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 11 meteorological station: Daily summary data: 2013 - ongoing

description: This data package contains hourly air temperature, relative humidity, wind speed, wind direction, and precipitation summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-11 met station. Air temperature, relative humidity, wind speed, wind direction, and precipitation are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset.
DOI: 10.6073/pasta/fd8fd38df17f997138195cdfa079b087
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 11 meteorological station: 1-second summary precipitation data: 2017 - ongoing

description: 1-second summary precipitation data at CSIS Block-11 met station. Total precipitation per second is recorded only if there is measurable precipitation. This is recorded at an automated meteorological station installed at Jornada LTER CSIS Block-11 site.. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset. IMPORTANT: Rainfall is only recorded when a bucket tip occurs on the tipping bucket rain gauge. If there is missing data due to equipment or other problems, there will be no indication of this within this dataset. The user needs to review precipitation values in the 30 minute or hourly summary datasets to determine if there are missing data in this 1 second detailed precipitation dataset.
DOI: 10.6084/m9.figshare.19498035
title: Additional file 1 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 1. Tables 1 to 4.
DOI: 10.6084/m9.figshare.19498035.v1
title: Additional file 1 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 1. Tables 1 to 4.
DOI: 10.6084/m9.figshare.19498038
title: Additional file 2 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 2. Results and statistical analysis of synthetic tests.
DOI: 10.6084/m9.figshare.19498038.v1
title: Additional file 2 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 2. Results and statistical analysis of synthetic tests.
DOI: 10.6084/m9.figshare.19498041.v1
title: Additional file 3 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 3. Results and statistical analysis of toy data sets.
DOI: 10.6084/m9.figshare.19498041
title: Additional file 3 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 3. Results and statistical analysis of toy data sets.
DOI: 10.6084/m9.figshare.19498050
title: Additional file 6 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 6. Processed sample by ASV matrices, associated metadata, indicator species results, and statistical analyses, parameter testing results, training time results.
DOI: 10.6084/m9.figshare.19498050.v1
title: Additional file 6 of LANDMark: an ensemble approach to the supervised selection of biomarkers in high-throughput sequencing data

description: Additional file 6. Processed sample by ASV matrices, associated metadata, indicator species results, and statistical analyses, parameter testing results, training time results.
DOI: 10.6084/m9.figshare.19498090
title: Additional file 2 of ENNGene: an Easy Neural Network model building tool for Genomics

description: Additional file 2. RBP24 model parameters. Complete list of the ENNGene parameters used to obtain the final models. Parameters from Preprocessing, Training, and Evaluation modules are reported and ensure full reproducibility of the results.
DOI: 10.6084/m9.figshare.19498090.v1
title: Additional file 2 of ENNGene: an Easy Neural Network model building tool for Genomics

description: Additional file 2. RBP24 model parameters. Complete list of the ENNGene parameters used to obtain the final models. Parameters from Preprocessing, Training, and Evaluation modules are reported and ensure full reproducibility of the results.
DOI: 10.6084/m9.figshare.19498123
title: Additional file 2 of The changing clinical landscape in acupuncture for women’s health: a cross-sectional online survey in New Zealand and Australia

description: Additional file 2.
DOI: 10.6084/m9.figshare.19498123.v1
title: Additional file 2 of The changing clinical landscape in acupuncture for women’s health: a cross-sectional online survey in New Zealand and Australia

description: Additional file 2.
DOI: 10.6084/m9.figshare.19498200
title: Additional file 2 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional file 2: Table S1. (Sensitivity) List of experiments performed with prime-seq including key characteristics of the experiments and data quality.
DOI: 10.6084/m9.figshare.19498200.v1
title: Additional file 2 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional file 2: Table S1. (Sensitivity) List of experiments performed with prime-seq including key characteristics of the experiments and data quality.
DOI: 10.6084/m9.figshare.19498206
title: Additional file 4 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional file 4: Table S2. (Lysis Costs) Calculations for per sample costs of different commercial and non-commercial extraction methods.
DOI: 10.6084/m9.figshare.19498209
title: Additional file 5 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional file 5: Table S3. (Lysis Time) Time needed for extraction of 24, 48 and 96 samples with SPRI beads or Silica Columns.
DOI: 10.6084/m9.figshare.19498209.v1
title: Additional file 5 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional file 5: Table S3. (Lysis Time) Time needed for extraction of 24, 48 and 96 samples with SPRI beads or Silica Columns.
DOI: 10.6084/m9.figshare.19498206.v1
title: Additional file 4 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional file 4: Table S2. (Lysis Costs) Calculations for per sample costs of different commercial and non-commercial extraction methods.
DOI: 10.6084/m9.figshare.19498212
title: Additional file 6 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional file 6: Table S4. (Method Cost) Per sample cost calculations for popular commercial and non-commercial RNA-seq methods including all consumables and reagents.
DOI: 10.6084/m9.figshare.19498215
title: Additional file 7 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional File 7: Table S5. (Method Time) Time needed for performing for popular commercial and non-commercial RNA-seq methods.
DOI: 10.6084/m9.figshare.19498215.v1
title: Additional file 7 of Prime-seq, efficient and powerful bulk RNA sequencing

description: Additional File 7: Table S5. (Method Time) Time needed for performing for popular commercial and non-commercial RNA-seq methods.
DOI: 10.6084/m9.figshare.19498227
title: Additional file 1 of Assignment of unimodal probability distribution models for quantitative morphological phenotyping

description: Additional file 1: Supplementary text. Supplementary Figure S1. Possible values of cellular features used in QMP. Supplementary Figure S2. Probability models for CalMorph measures. Supplementary Figure S3. Conversion of the CV to noise values. Supplementary Figure S4. Flowchart of the methodology for checking the modality of the CalMorph parameters. Supplementary Figure S5. An example of the effect of confounding factors on modality. Supplementary Figure S6. An example of the effect of outliers on modality. Supplementary Figure S7. Comparison of this study with our previous results. Supplementary Figure S8. Comparison of results between UNIMO and Box-Cox transformed methods. Supplementary Figure S9. Canonical correlation analysis used for extraction of 32 pairs of canonical variables. Supplementary Figure S10. Phenotypic similarity network of non-essential genes. Supplementary Figure S11. Enrichment of KEGG categories. Supplementary Figure S12. Morphological defects of autophagy mutants. Supplementary Figure S13. Multimodal CalMorph parameters. Supplementary Figure S14. Outlines of generalization of UNIMO. Supplementary Figure S15. An example of versatility of UNIMO. Supplementary Figure S16. Defining characteristics of the 130 functional groups. Supplementary Table S1. Selection of the probability distribution for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S2. Population level modality check for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S3. The best probability distribution and final modality for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S4. List of non-essential mutants. Supplementary Table S5. List of the representative GO terms enriched in each functional group. Supplementary Table S6. KEGG pathway enrichment (FDR = 0.05). Supplementary Table S7. Data types and probability distributions employed for a typical quantitative morphological phenotyping (QMP) experiment. Supplementary Table S8. List of measurements extracted by CellProfiler. Supplementary Table S9. An example of generalization and versatility of UNIMO using morphological data presented in Mattiazzi Usaj et al. (2020).
DOI: 10.6084/m9.figshare.19498227.v1
title: Additional file 1 of Assignment of unimodal probability distribution models for quantitative morphological phenotyping

description: Additional file 1: Supplementary text. Supplementary Figure S1. Possible values of cellular features used in QMP. Supplementary Figure S2. Probability models for CalMorph measures. Supplementary Figure S3. Conversion of the CV to noise values. Supplementary Figure S4. Flowchart of the methodology for checking the modality of the CalMorph parameters. Supplementary Figure S5. An example of the effect of confounding factors on modality. Supplementary Figure S6. An example of the effect of outliers on modality. Supplementary Figure S7. Comparison of this study with our previous results. Supplementary Figure S8. Comparison of results between UNIMO and Box-Cox transformed methods. Supplementary Figure S9. Canonical correlation analysis used for extraction of 32 pairs of canonical variables. Supplementary Figure S10. Phenotypic similarity network of non-essential genes. Supplementary Figure S11. Enrichment of KEGG categories. Supplementary Figure S12. Morphological defects of autophagy mutants. Supplementary Figure S13. Multimodal CalMorph parameters. Supplementary Figure S14. Outlines of generalization of UNIMO. Supplementary Figure S15. An example of versatility of UNIMO. Supplementary Figure S16. Defining characteristics of the 130 functional groups. Supplementary Table S1. Selection of the probability distribution for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S2. Population level modality check for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S3. The best probability distribution and final modality for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S4. List of non-essential mutants. Supplementary Table S5. List of the representative GO terms enriched in each functional group. Supplementary Table S6. KEGG pathway enrichment (FDR = 0.05). Supplementary Table S7. Data types and probability distributions employed for a typical quantitative morphological phenotyping (QMP) experiment. Supplementary Table S8. List of measurements extracted by CellProfiler. Supplementary Table S9. An example of generalization and versatility of UNIMO using morphological data presented in Mattiazzi Usaj et al. (2020).
DOI: 10.6073/pasta/609cb12a6df4e3f2de4c69249a2ff1d3
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 12 meteorological station: 30-minute summary data: 2017 - ongoing

description: This data package contains 30-minute air temperature, relative humidity, and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-1 met station. Average air temperature, relative humidity, wind speed and wind direction are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively. This is an ONGOING dataset.
DOI: 10.21227/p4bk-2392
title: A UHF Band, Multiple Environment Path Loss Dataset

description:  Accurate path loss models are fundamental to good wireless communication network design. Machine Learning models have demostrated better prediction accuracies than the Empirical models and Deterministic models. However, Empirical and Deterministic models have specified range of parameters in which they are valid. This feature makes Empirical models to be used in Radio Frequency Planning softwares due to flexibility and less computational complexity when compared with Deterministic models.  Machine Learning models are most of the  time developed taking into consideration fixed parameter values interms of frequencies and antenna heights, which limits their incoorporation in Radio Frequency Planning softwares due to low user flexibiliity even though they have the best accuracy. This dataset is aimed for developing a multiple parameter path loss model. The parameters considered are frequency, antenna height, and environment, so as to improve flexibility.
DOI: 10.6084/m9.figshare.19498283
title: APITEST

description: Test description of article
DOI: 10.6084/m9.figshare.19498283.v1
title: APITEST

description: Test description of article
DOI: 10.6084/m9.figshare.19498286
title: APITEST

description: Test description of article
DOI: 10.6084/m9.figshare.19498286.v1
title: APITEST

description: Test description of article
DOI: 10.6084/m9.figshare.19498289
title: APITEST

description: Test description of article
DOI: 10.6084/m9.figshare.19498289.v1
title: APITEST

description: Test description of article
DOI: 10.6073/pasta/e2d337d5a9d94ec6caef287e8ef06e56
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 12 meteorological station: 5-minute summary wind and air temperature data: 2013 - ongoing

description: This data package contains 5-minute air temperature and wind summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-12 met station. Average air temperature, wind speed, and wind direction are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. This is a subset of baseline weather data collected at the 15 Jornada Basin LTER CSIS study blocks, New Mexico. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. The met station variables measured include air temperature, precipitation, relative humidity, wind direction, wind speed. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset.
DOI: 10.6073/pasta/e08be6628dae3853f7cf07bedc3fd39e
title: Jornada Basin LTER Cross-scale Interactions Study (CSIS) Block 12 meteorological station: 1-hour summary data: 2017 - ongoing

description: This data package contains hourly air temperature, relative humidity, wind speed, wind direction, and precipitation summary data from Jornada Basin LTER Cross Scale Interactions Study (CSIS) Block-12 met station. Air temperature, relative humidity, wind speed, wind direction, and precipitation are measured and calculated at an automated meteorological station connected to a 900 MHz spread spectrum wireless network. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximate 2.5m. Measurements are aggregated at intervals of 5, 30, 60 minutes and daily, with precipitation additionally provided with 1 second aggregation during precipitation events. Precipitation is not measured at Block 1 and Block 12 because of proximity to Block 2 and Block 13, respectively . This is an ONGOING dataset.
DOI: 10.6084/m9.figshare.19498309
title: Additional file 3 of The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

description: Additional file 3 contains all the validated variants and their details. The file is formatted to include separate rows for unique PMID-variant-gene triples, therefore variants that regulate multiple genes and variants that have been validated in more than one publication have more than one row in the file.
DOI: 10.6084/m9.figshare.19498338
title: Additional file 1 of Measuring disability-adjusted life years (DALYs) due to COVID-19 in Scotland, 2020

description: Additional file 1:. Daily COVID-19 infection data by health state for Scotland, 2020
DOI: 10.6084/m9.figshare.19498338.v1
title: Additional file 1 of Measuring disability-adjusted life years (DALYs) due to COVID-19 in Scotland, 2020

description: Additional file 1:. Daily COVID-19 infection data by health state for Scotland, 2020
DOI: 10.6084/m9.figshare.19498366
title: Additional file 1 of Socio-economic determinants of maternal health care utilization in Kailahun District, Sierra Leone, 2020

description: Additional file 1.
DOI: 10.6084/m9.figshare.19498366.v1
title: Additional file 1 of Socio-economic determinants of maternal health care utilization in Kailahun District, Sierra Leone, 2020

description: Additional file 1.
DOI: 10.6084/m9.figshare.19445186
title: Additional file 2 of Phylogenomic analysis of Syngnathidae reveals novel relationships, origins of endemic diversity and variable diversification rates

description: Additional file 2. Table of sampling data for all included specimens.
DOI: 10.6084/m9.figshare.19445186.v1
title: Additional file 2 of Phylogenomic analysis of Syngnathidae reveals novel relationships, origins of endemic diversity and variable diversification rates

description: Additional file 2. Table of sampling data for all included specimens.
DOI: 10.6084/m9.figshare.19498389
title: Additional file 3 of Status of fish health management and biosecurity measures in fish farms, cages and hatcheries in Western Kenya

description: Additional file 3. Raw data file.
DOI: 10.6084/m9.figshare.19498389.v1
title: Additional file 3 of Status of fish health management and biosecurity measures in fish farms, cages and hatcheries in Western Kenya

description: Additional file 3. Raw data file.
DOI: 10.6084/m9.figshare.19498407
title: Additional file 2 of A systematic review and recommendations for prom instruments for older people with frailty in emergency care

description: Additional file 2. Data extraction sheet.
DOI: 10.6084/m9.figshare.19498407.v1
title: Additional file 2 of A systematic review and recommendations for prom instruments for older people with frailty in emergency care

description: Additional file 2. Data extraction sheet.
DOI: 10.6084/m9.figshare.19498410.v1
title: Additional file 3 of A systematic review and recommendations for prom instruments for older people with frailty in emergency care

description: Additional file 3. COSMIN scoring summary.
DOI: 10.6084/m9.figshare.19498410
title: Additional file 3 of A systematic review and recommendations for prom instruments for older people with frailty in emergency care

description: Additional file 3. COSMIN scoring summary.