cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15787/vtt1/9swahy
title: Development of a Diagnostic System for Air Brakes in Autonomous and Connected Trucks (​04-100)

description: Project Description: This data was collected for the project “Diagnostics Using Machine Learning for Air Brakes in Commercial Vehicles”. This data was collected in June 2023 in Dr. Swaroop Darbha’s lab Doherty 301A, Texas A&M University, College Station, Texas. The setup described in the final report was used to collect the data. Data Scope: This data describes the pressures in the rear and front chambers of the air brakes in a typical commercial vehicle under hard braking. The data also contains pedal travel(mm) and air leakage velocity (ft/min) from the system. This data was used to build a machine learning model to predict the amount of leakage in the system, given the pressure traces of any chamber under hard braking. All the data reported is time series data and there are 23 tests performed under various different conditions. The files are named according to each test scenario, as “Dataleak.csv”. The data given is also labelled in case of any discrepancies. Data Specification: There are 4 Rear Chambers and 2 Front Chambers in the experimental setup. The data given has been labelled accordingly as RearChamber1,RearChamber2 etc. The time data is given in seconds and the zero point is calibrated to the test start point. The pedal travel is given in mm. The Leak Velocity is given in ft/min. Finally, a table named “dataset.csv” is included which contains derived data from all 23 scenarios. This table was used to build the machine learning model.
DOI: 10.5281/zenodo.8338674
title: Inferring B cell phylogenies from paired heavy and light chain BCR sequences with Dowser

description: In our publication, we created simulations of paired heavy and light chain BCR sequences. Uploaded here is all the data needed to rerun the simulations, as well as the output of the simulations we ran. The output of BCR phylo included here are the lineage trees, unpickled and put into one file (true_trees.tsv), and the fasta files ('starting_fastas' folder). The naive BCR sequences we used as a starting point are found in the 'naive_data' folder. The post-simulation data for all 20 iterations (combined heavy and light chain data through both simulation frameworks) can be found in the 'simulation_data' folder.
DOI: 10.5281/zenodo.8338673
title: Inferring B cell phylogenies from paired heavy and light chain BCR sequences with Dowser

description: In our publication, we created simulations of paired heavy and light chain BCR sequences. Uploaded here is all the data needed to rerun the simulations, as well as the output of the simulations we ran. The output of BCR phylo included here are the lineage trees, unpickled and put into one file (true_trees.tsv), and the fasta files ('starting_fastas' folder). The naive BCR sequences we used as a starting point are found in the 'naive_data' folder. The post-simulation data for all 20 iterations (combined heavy and light chain data through both simulation frameworks) can be found in the 'simulation_data' folder.
DOI: 10.6084/m9.figshare.24126849
title: matrixobr.dta

description: STATA dta file. Weight matrices for regions of Russia.<br>
DOI: 10.6084/m9.figshare.24126849.v1
title: matrixobr.dta

description: STATA dta file. Weight matrices for regions of Russia.<br>
DOI: 10.6084/m9.figshare.24113817.v1
title: Data from the six included studies.xlsx

description: The demographic data for included studies included study design, sample size, mean age, mean BMl, FIGO stage, mean tumor size, and follow-up period. The following results were compared by: (1) perioperative results: operation time, blood loss, blood transfusion rate, complication rate, length of hospitalization; (2) survival results: recurrence and mortality. Specific complications were also summarized.
DOI: 10.6084/m9.figshare.24113817
title: Data from the six included studies.xlsx

description: The demographic data for included studies included study design, sample size, mean age, mean BMl, FIGO stage, mean tumor size, and follow-up period. The following results were compared by: (1) perioperative results: operation time, blood loss, blood transfusion rate, complication rate, length of hospitalization; (2) survival results: recurrence and mortality. Specific complications were also summarized.
DOI: 10.5281/zenodo.8338667
title: symplocos_macrophylla_zanfona_1.fasta.gz

description: .
DOI: 10.5281/zenodo.8338666
title: symplocos_macrophylla_zanfona_1.fasta.gz

description: .
DOI: 10.6084/m9.figshare.24126795
title: DATA.dta

description: Socio-economic indicators of Russian regions, including in the field of health care (2012-2019)
DOI: 10.34740/kaggle/dsv/6459430
title: Prime Number Pattern 1-30K on Square Grid of 7
DOI: 10.5281/zenodo.8338197
title: NPL P-AMS testing dataset

description: Dataset from parallel tests of four pairs of different P-AMS instruments measuring low concentrations (&lt;10 mg.m-3) of HCl in the NPL Stack Simulator facility. Measurements were made in June 2021. More details on the Metadata tab in the file.
description: Funding: EMPIR programme project 18NRM04 Heroes. http://empir.npl.co.uk/heroes/
DOI: 10.5281/zenodo.8338198
title: NPL P-AMS testing dataset

description: Dataset from parallel tests of four pairs of different P-AMS instruments measuring low concentrations (&lt;10 mg.m-3) of HCl in the NPL Stack Simulator facility. Measurements were made in June 2021. More details on the Metadata tab in the file.
description: Funding: EMPIR programme project 18NRM04 Heroes. http://empir.npl.co.uk/heroes/
DOI: 10.5281/zenodo.8338285
title: NPL EN 1911 laboratory performance ILC dataset

description: Dataset from a blind ILC for the laboratory analysis of EN 1911 samples carried out by NPL in 2021. 14 test samples were sent to 7 ISO 17025 accredited laboratories for analysis. The anonymised results and laboratory supplied uncertainties are included in this dataset. Further information is included in the metadata tab of the file.
description: Funding: EMPIR programme project 18NRM04 Heroes. http://empir.npl.co.uk/heroes/
DOI: 10.5281/zenodo.8338284
title: NPL EN 1911 laboratory performance ILC dataset

description: Dataset from a blind ILC for the laboratory analysis of EN 1911 samples carried out by NPL in 2021. 14 test samples were sent to 7 ISO 17025 accredited laboratories for analysis. The anonymised results and laboratory supplied uncertainties are included in this dataset. Further information is included in the metadata tab of the file.
description: Funding: EMPIR programme project 18NRM04 Heroes. http://empir.npl.co.uk/heroes/
DOI: 10.6084/m9.figshare.24126981
title: matrixobr.dta

description: STATA dta file. Weight matrices for regions of Russia.
DOI: 10.17894/ucph.d893fbbd-0569-40f2-9d1c-320a3124cd00
title: Data for the paper Acoustic frequency atomic spin oscillator in the quantum regime
DOI: 10.5281/zenodo.8338716
title: siren_reticulata_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.8338715
title: siren_reticulata_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.24126867
title: Unexpected Reduction in Megacities' Anthropogenic CO2 Emissions in Lower middle Reaches of the Yangtze River during Extreme 2022 Heatwave

description: This dataset provides the daily surface air temperature, dew point temperature, surface pressure, wind, cloud, and precipitation from 2021 to 2022 at 11 stations in 8 megacities over the lower-middle reaches of the Yangtze River.Data format:<br>Field 1: Pos 1-4, Length 4: Observation YearYear of observation, rounded to nearest whole hour<br>Field 2: Pos 6-7, Length 2: Observation MonthMonth of observation, rounded to nearest whole hour<br>Field 3: Pos 9-11, Length 2: Observation DayDay of observation, rounded to nearest whole hour<br>Field 4: Pos 12-13, Length 2: Observation HourHour of observation, rounded to nearest whole hour<br>Field 5: Pos 14-19, Length 6: Air TemperatureThe temperature of the airUNITS: Degrees CelsiusSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 6: Pos 20-24, Length 6: Dew Point TemperatureThe temperature to which a given parcel of air must be cooled at constant pressure and water vapor content in order for saturation to occur.UNITS: Degrees CelsiusSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 7: Pos 26-31, Length 6: Sea Level PressureThe air pressure relative to Mean Sea Level (MSL).UNITS: HectopascalsSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 8: Pos 32-37, Length 6: Wind DirectionThe angle, measured in a clockwise direction, between true north and the direction from which the wind is blowing.UNITS: Angular DegreesSCALING FACTOR: 1MISSING VALUE: -9999*NOTE: Wind direction for calm winds is coded as 0.<br> Field 9: Pos 38-43, Length 6: Wind Speed RateThe rate of horizontal travel of air past a fixed point.UNITS: meters per secondSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 10: Pos 44-49, Length 6: Sky Condition Total Coverage CodeThe code that denotes the fraction of the total celestial dome covered by clouds or other obscuring phenomena.MISSING VALUE: -9999DOMAIN: 0: None, SKC or CLR 1: One okta - 1/10 or less but not zero 2: Two oktas - 2/10 - 3/10, or FEW 3: Three oktas - 4/10 4: Four oktas - 5/10, or SCT 5: Five oktas - 6/10 6: Six oktas - 7/10 - 8/10 7: Seven oktas - 9/10 or more but not 10/10, or BKN 8: Eight oktas - 10/10, or OVC 9: Sky obscured, or cloud amount cannot be estimated10: Partial obscuration11: Thin scattered12: Scattered13: Dark scattered14: Thin broken15: Broken16: Dark broken17: Thin overcast18: Overcast19: Dark overcast<br>Field 11: Pos 50-55, Length 6: Liquid Precipitation Depth Dimension - One Hour DurationThe depth of liquid precipitation that is measured over a one hour accumulation period.UNITS: millimetersSCALING FACTOR: 10MISSING VALUE: -9999*NOTE: Trace precipitation is coded as -1<br>Field 12: Pos 56-61, Length 6: Liquid Precipitation Depth Dimension - Six Hour DurationThe depth of liquid precipitation that is measured over a six hour accumulation period.UNITS: millimetersSCALING FACTOR: 10MISSING VALUE: -9999*NOTE: Trace precipitation is coded as -1<br><br>
DOI: 10.6084/m9.figshare.24126867.v2
title: Unexpected Reduction in Megacities' Anthropogenic CO2 Emissions in Lower middle Reaches of the Yangtze River during Extreme 2022 Heatwave

description: This dataset provides the daily surface air temperature, dew point temperature, surface pressure, wind, cloud, and precipitation from 2021 to 2022 at 11 stations in 8 megacities over the lower-middle reaches of the Yangtze River.Data format:<br>Field 1: Pos 1-4, Length 4: Observation YearYear of observation, rounded to nearest whole hour<br>Field 2: Pos 6-7, Length 2: Observation MonthMonth of observation, rounded to nearest whole hour<br>Field 3: Pos 9-11, Length 2: Observation DayDay of observation, rounded to nearest whole hour<br>Field 4: Pos 12-13, Length 2: Observation HourHour of observation, rounded to nearest whole hour<br>Field 5: Pos 14-19, Length 6: Air TemperatureThe temperature of the airUNITS: Degrees CelsiusSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 6: Pos 20-24, Length 6: Dew Point TemperatureThe temperature to which a given parcel of air must be cooled at constant pressure and water vapor content in order for saturation to occur.UNITS: Degrees CelsiusSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 7: Pos 26-31, Length 6: Sea Level PressureThe air pressure relative to Mean Sea Level (MSL).UNITS: HectopascalsSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 8: Pos 32-37, Length 6: Wind DirectionThe angle, measured in a clockwise direction, between true north and the direction from which the wind is blowing.UNITS: Angular DegreesSCALING FACTOR: 1MISSING VALUE: -9999*NOTE: Wind direction for calm winds is coded as 0.<br> Field 9: Pos 38-43, Length 6: Wind Speed RateThe rate of horizontal travel of air past a fixed point.UNITS: meters per secondSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 10: Pos 44-49, Length 6: Sky Condition Total Coverage CodeThe code that denotes the fraction of the total celestial dome covered by clouds or other obscuring phenomena.MISSING VALUE: -9999DOMAIN: 0: None, SKC or CLR 1: One okta - 1/10 or less but not zero 2: Two oktas - 2/10 - 3/10, or FEW 3: Three oktas - 4/10 4: Four oktas - 5/10, or SCT 5: Five oktas - 6/10 6: Six oktas - 7/10 - 8/10 7: Seven oktas - 9/10 or more but not 10/10, or BKN 8: Eight oktas - 10/10, or OVC 9: Sky obscured, or cloud amount cannot be estimated10: Partial obscuration11: Thin scattered12: Scattered13: Dark scattered14: Thin broken15: Broken16: Dark broken17: Thin overcast18: Overcast19: Dark overcast<br>Field 11: Pos 50-55, Length 6: Liquid Precipitation Depth Dimension - One Hour DurationThe depth of liquid precipitation that is measured over a one hour accumulation period.UNITS: millimetersSCALING FACTOR: 10MISSING VALUE: -9999*NOTE: Trace precipitation is coded as -1<br>Field 12: Pos 56-61, Length 6: Liquid Precipitation Depth Dimension - Six Hour DurationThe depth of liquid precipitation that is measured over a six hour accumulation period.UNITS: millimetersSCALING FACTOR: 10MISSING VALUE: -9999*NOTE: Trace precipitation is coded as -1<br><br>
DOI: 10.6084/m9.figshare.24126867.v1
title: Unexpected Reduction in Megacities' Anthropogenic CO2 Emissions in Lower-middle Reaches of the Yangtze River during Extreme 2022 Heatwave

description: This dataset provides the daily surface air temperature, dew point temperature, surface pressure, wind, cloud, and precipitation from 2021 to 2022 at 11 stations in 8 megacities over the lower-middle reaches of the Yangtze River.Data format:<br>Field 1: Pos 1-4, Length 4: Observation YearYear of observation, rounded to nearest whole hour<br>Field 2: Pos 6-7, Length 2: Observation MonthMonth of observation, rounded to nearest whole hour<br>Field 3: Pos 9-11, Length 2: Observation DayDay of observation, rounded to nearest whole hour<br>Field 4: Pos 12-13, Length 2: Observation HourHour of observation, rounded to nearest whole hour<br>Field 5: Pos 14-19, Length 6: Air TemperatureThe temperature of the airUNITS: Degrees CelsiusSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 6: Pos 20-24, Length 6: Dew Point TemperatureThe temperature to which a given parcel of air must be cooled at constant pressure and water vapor content in order for saturation to occur.UNITS: Degrees CelsiusSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 7: Pos 26-31, Length 6: Sea Level PressureThe air pressure relative to Mean Sea Level (MSL).UNITS: HectopascalsSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 8: Pos 32-37, Length 6: Wind DirectionThe angle, measured in a clockwise direction, between true north and the direction from which the wind is blowing.UNITS: Angular DegreesSCALING FACTOR: 1MISSING VALUE: -9999*NOTE: Wind direction for calm winds is coded as 0.<br> Field 9: Pos 38-43, Length 6: Wind Speed RateThe rate of horizontal travel of air past a fixed point.UNITS: meters per secondSCALING FACTOR: 10MISSING VALUE: -9999<br>Field 10: Pos 44-49, Length 6: Sky Condition Total Coverage CodeThe code that denotes the fraction of the total celestial dome covered by clouds or other obscuring phenomena.MISSING VALUE: -9999DOMAIN: 0: None, SKC or CLR 1: One okta - 1/10 or less but not zero 2: Two oktas - 2/10 - 3/10, or FEW 3: Three oktas - 4/10 4: Four oktas - 5/10, or SCT 5: Five oktas - 6/10 6: Six oktas - 7/10 - 8/10 7: Seven oktas - 9/10 or more but not 10/10, or BKN 8: Eight oktas - 10/10, or OVC 9: Sky obscured, or cloud amount cannot be estimated10: Partial obscuration11: Thin scattered12: Scattered13: Dark scattered14: Thin broken15: Broken16: Dark broken17: Thin overcast18: Overcast19: Dark overcast<br>Field 11: Pos 50-55, Length 6: Liquid Precipitation Depth Dimension - One Hour DurationThe depth of liquid precipitation that is measured over a one hour accumulation period.UNITS: millimetersSCALING FACTOR: 10MISSING VALUE: -9999*NOTE: Trace precipitation is coded as -1<br>Field 12: Pos 56-61, Length 6: Liquid Precipitation Depth Dimension - Six Hour DurationThe depth of liquid precipitation that is measured over a six hour accumulation period.UNITS: millimetersSCALING FACTOR: 10MISSING VALUE: -9999*NOTE: Trace precipitation is coded as -1<br><br>
DOI: 10.6084/m9.figshare.24127010
title: Generalised Bayesian Inference for Discrete Intractable Likelihood

description: Discrete state spaces represent a major computational challenge to statistical inference, since the computation of normalisation constants requires summation over large or possibly infinite sets, which can be impractical. This paper addresses this computational challenge through the development of a novel generalised Bayesian inference procedure suitable for discrete intractable likelihood. Inspired by recent methodological advances for continuous data, the main idea is to update beliefs about model parameters using a discrete Fisher divergence, in lieu of the problematic intractable likelihood. The result is a generalised posterior that can be sampled from using standard computational tools, such as Markov chain Monte Carlo, circumventing the intractable normalising constant. The statistical properties of the generalised posterior are analysed, with sufficient conditions for posterior consistency and asymptotic normality established. In addition, a novel and general approach to calibration of generalised posteriors is proposed. Applications are presented on lattice models for discrete spatial data and on multivariate models for count data, where in each case the methodology facilitates generalised Bayesian inference at low computational cost.
DOI: 10.6084/m9.figshare.24127010.v1
title: Generalised Bayesian Inference for Discrete Intractable Likelihood

description: Discrete state spaces represent a major computational challenge to statistical inference, since the computation of normalisation constants requires summation over large or possibly infinite sets, which can be impractical. This paper addresses this computational challenge through the development of a novel generalised Bayesian inference procedure suitable for discrete intractable likelihood. Inspired by recent methodological advances for continuous data, the main idea is to update beliefs about model parameters using a discrete Fisher divergence, in lieu of the problematic intractable likelihood. The result is a generalised posterior that can be sampled from using standard computational tools, such as Markov chain Monte Carlo, circumventing the intractable normalising constant. The statistical properties of the generalised posterior are analysed, with sufficient conditions for posterior consistency and asymptotic normality established. In addition, a novel and general approach to calibration of generalised posteriors is proposed. Applications are presented on lattice models for discrete spatial data and on multivariate models for count data, where in each case the methodology facilitates generalised Bayesian inference at low computational cost.
DOI: 10.5519/qd.mmuol94o
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (44 records)
DOI: 10.5281/zenodo.8338511
title: Non-Targeted Metabolomics of a Phytoplankton Bloom in the California Current Ecosystem 1706

description: Non-Targeted LC-MS/MS based Metabolomics of SPE (PPL) extracts of a Phytoplankton Bloom in the California Current Ecosystem 1706
DOI: 10.5281/zenodo.8338510
title: Non-Targeted Metabolomics of a Phytoplankton Bloom in the California Current Ecosystem 1706

description: Non-Targeted LC-MS/MS based Metabolomics of SPE (PPL) extracts of a Phytoplankton Bloom in the California Current Ecosystem 1706
DOI: 10.57967/hf/1096
title: doi-dataset-test
DOI: 10.5281/zenodo.8279937
title: The effects of two different fatigue protocols on movement quality during unanticipated change of direction in female soccer players (data file)

description: This dataset contains the results of soccer players who participated in our study. In our study, we investigated the effects of two fatigue protocols on movement quality during change of direction in anticipated and unanticipated conditions.
DOI: 10.5281/zenodo.8279936
title: The effects of two different fatigue protocols on movement quality during unanticipated change of direction in female soccer players (data file)

description: This dataset contains the results of soccer players who participated in our study. In our study, we investigated the effects of two fatigue protocols on movement quality during change of direction in anticipated and unanticipated conditions.
DOI: 10.3886/e170201v1
title: Data and code for "How do households respond to job loss? Lessons from multiple high-frequenct data sets"

description: How much and through which channels do households self-insure against job loss? Combining data from a large bank and from government sources, we quantify a broad range of responses to job loss in a unified empirical framework. Cumulated over a two-year period, households reduce spending by 30% of their income loss. They mainly self-insure through adjustments of liquid balances, which account for 50% of the income loss. Other channels – spousal labor supply, private transfers, home equity extraction, mortgage refinancing, and consumer credit – contribute less to self-insurance. Both overall self-insurance and the channels vary with household characteristics in intuitive ways.
DOI: 10.3886/e168101
title: Data and Code for: Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA

description: This repository contains the README, code, and the subset of data that is publicly available used to generate the results in "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA."
DOI: 10.3886/e168101v1
title: Data and Code for: Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA

description: This repository contains the README, code, and the subset of data that is publicly available used to generate the results in "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA."
DOI: 10.6084/m9.figshare.24126993
title: Chapter 2_Table S5_Model outputs

description: Model outputs of PGLS analyses.
DOI: 10.6084/m9.figshare.24126993.v1
title: Chapter 2_Table S5_Model outputs

description: Model outputs of PGLS analyses.
DOI: 10.6084/m9.figshare.24126993.v2
title: Chapter 2_Table S5_Model outputs

description: Model outputs of PGLS analyses.
DOI: 10.34740/kaggle/dsv/6459495
title: Prime Number Pattern On Square Grid of 11
DOI: 10.5281/zenodo.8338795
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Jeannette Elizabeth Graustein, http://www.wikidata.org/entity/Q92344276. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q92344276
DOI: 10.5281/zenodo.8338794
title: Natural history specimens collected and/or identified and deposited.

description: Natural history specimen data collected and/or identified by Jeannette Elizabeth Graustein, http://www.wikidata.org/entity/Q92344276. Claims or attributions were made on Bionomia, https://bionomia.net using specimen data from the Global Biodiversity Information Facility, https://gbif.org.
description: http://www.wikidata.org/entity/Q92344276