cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.19747594
title: Drive-by Data

description: Sediment concentration data from drive-by experiments.
DOI: 10.6084/m9.figshare.19747594.v1
title: Drive-by Data

description: Sediment concentration data from drive-by experiments.
DOI: 10.5517/ccdc.csd.cc2617n5
title: CCDC 2026986: Experimental Crystal Structure Determination

description: Related Article: Manoj K. Pal, A. P. Wadawale, Nitish Chauhan, Ananda Guha Majumdar, M. Subramanian, N. Bhuvanesh, Sandip Dey|2021|Polyhedron|211|115547|doi:10.1016/j.poly.2021.115547
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.19747597
title: ADCP data

description: ADCP data collected during selfie experiments A1, A2 and C3, and drive-by experiments DB1, DB2, DB3 and DB4.
DOI: 10.6084/m9.figshare.19747597.v1
title: ADCP data

description: ADCP data collected during selfie experiments A1, A2 and C3, and drive-by experiments DB1, DB2, DB3 and DB4.
DOI: 10.7284/125675
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise SAV-16-37 using a SeaBird SBE-25 instrument system onboard the platform RV Savannah

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.6084/m9.figshare.14384819
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-radial-artery-ventral-interior-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the radial artery on the forearm (between elbow and wrist, about in the middle with a slightly changing position regularly to avoid skin damage due to continuous skin obstruction and warmth), by being attached with a velcro to the interior of a cotton sports wrist band. This sensor should allow to capture circadian rhythm modulations. See the works of Dr. Antonio Martinez Nicolas for more details on wrist skin temperature rhythm and WTIO. <br> The procedure is described in: https://pubmed.ncbi.nlm.nih.gov/18761026/ <br> This dataset can be used alone or in combination with ibutton-left-nondominant-upper-arm-cotton-sports-wristband-dorsal-interior-5min and ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min to regress dorsal skin temperature and ambient temperature respectively. <br> Start using the files from the datetime (in filename): 071621 and onward. Indeed, earlier logs are redundant. Concatenate every files beyond this date to get the full log, each file containing one distinct period of time.<br> Earlier logs contain the same data as 071621, as initially it was thought that the sensor had enough memory to collect 1 year of data, but this was in fact incorrect (it's about 6-7 months of data). So it's necessary to clear the sensor's data before collecting a new period. <br> There is unfortunately some missing data from 2021-07-06 to 2021-07-16 because the internal memory was unexpectedly already filled (it should have been able to store more than a year according to the manufacturer's documentation). The maximum number of samples seems to be 62720. <br> Note that the datetime in the filename is in US format: monthdayyear.<br>
DOI: 10.6084/m9.figshare.14384819.v10
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-radial-artery-ventral-interior-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the radial artery on the forearm (between elbow and wrist, about in the middle with a slightly changing position regularly to avoid skin damage due to continuous skin obstruction and warmth), by being attached with a velcro to the interior of a cotton sports wrist band. This sensor should allow to capture circadian rhythm modulations. See the works of Dr. Antonio Martinez Nicolas for more details on wrist skin temperature rhythm and WTIO. <br> The procedure is described in: https://pubmed.ncbi.nlm.nih.gov/18761026/ <br> This dataset can be used alone or in combination with ibutton-left-nondominant-upper-arm-cotton-sports-wristband-dorsal-interior-5min and ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min to regress dorsal skin temperature and ambient temperature respectively. <br> Start using the files from the datetime (in filename): 071621 and onward. Indeed, earlier logs are redundant. Concatenate every files beyond this date to get the full log, each file containing one distinct period of time.<br> Earlier logs contain the same data as 071621, as initially it was thought that the sensor had enough memory to collect 1 year of data, but this was in fact incorrect (it's about 6-7 months of data). So it's necessary to clear the sensor's data before collecting a new period. <br> There is unfortunately some missing data from 2021-07-06 to 2021-07-16 because the internal memory was unexpectedly already filled (it should have been able to store more than a year according to the manufacturer's documentation). The maximum number of samples seems to be 62720. <br> Note that the datetime in the filename is in US format: monthdayyear.<br>
DOI: 10.6084/m9.figshare.14384819.v9
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the radial artery on the forearm (between elbow and wrist, about in the middle with a slightly changing position regularly to avoid skin damage due to continuous skin obstruction and warmth), by being attached with a velcro to the interior of a cotton sports wrist band. See the works of Dr. Antonio Martinez Nicolas for more details on wrist skin temperature rhythm and WTIO.<br>The procedure is described in: https://pubmed.ncbi.nlm.nih.gov/18761026/<br>This dataset can be used alone or in combination with ibutton-left-nondominant-upper-arm-cotton-sports-wristband-dorsal-interior-5min and ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min to regress dorsal skin temperature and ambient temperature respectively.<br>Start using the files from the datetime (in filename): 071621 and onward. Indeed, earlier logs are redundant. Concatenate every files beyond this date to get the full log, each file containing one distinct period of time.<br>Earlier logs contain the same data as 071621, as initially it was thought that the sensor had enough memory to collect 1 year of data, but this was in fact incorrect (it's about 6-7 months of data). So it's necessary to clear the sensor's data before collecting a new period.<br>There is unfortunately some missing data from 2021-07-06 to 2021-07-16 because the internal memory was unexpectedly already filled (it should have been able to store more than a year according to the manufacturer's documentation). The maximum number of samples seems to be 62720.<br>Note that the datetime in the filename is in US format: monthdayyear.<br>
DOI: 10.6084/m9.figshare.19747459
title: Selfie Data

description: Plume concentration data from selfie experiments.
DOI: 10.6084/m9.figshare.19747459.v1
title: Selfie Data

description: Plume concentration data from selfie experiments.
DOI: 10.7284/125683
title: ADCP (Acoustic Doppler Current Profiler) data collected during research cruise SAV-16-39 using a RDI WM-300 instrument system onboard the platform RV Savannah

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/125687
title: Gyrocompass data collected during research cruise SAV-16-39 using a Yokogawa CMZ700B instrument system onboard the platform RV Savannah

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/125685
title: Meteorological Station data collected during research cruise SAV-16-39 using a RMYoung 26800 instrument system onboard the platform RV Savannah

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/125684
title: Singlebeam Echosounder data collected during research cruise SAV-16-39 using a Furuno FCV-582 instrument system onboard the platform RV Savannah

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/125688
title: TSG (Thermosalinograph) data collected during research cruise SAV-16-39 using a SeaBird SBE-21 instrument system onboard the platform RV Savannah

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.7284/125692
title: CTD (Conductivity, Temperature, Depth) data collected during research cruise SAV-16-40 using a SeaBird SBE-25 instrument system onboard the platform RV Savannah

description: Original (unprocessed) data collected during a Field_expedition
DOI: 10.23641/asha.20405730
title: Age-related differences in informational masking (Jagadeesh & Uppunda, 2022)

description: <strong>Purpose:</strong> Speech recognition in noise is a ubiquitous problem in older listeners. Speech, the most commonly encountered noise in the real world, causes greater masking than noise maskers, a phenomenon called informational masking (IM). This is due to the lexical-semantic and/or acoustic-phonetic information present in speech maskers. In this study, we aimed to observe the age-related differences in speech recognition and the magnitudes of IM when the maskers varied in the type of linguistic information. <strong>Method:</strong> In 30 young and 30 older individuals, we measured the signal-to-noise ratio required to obtain 50% correct identification under four-talker babble (lexical-semantic and acoustic-phonetic information), four-talker reverse babble (predominantly acoustic-phonetic information), and speech-shaped noise (SSN; energetic). <strong>Results:</strong> In both groups, the four-talker babble caused the greatest masking effect (worst performances), whereas the SSN resulted in the least masking effect (best performances). The effectiveness of IM due to the lexical-semantic information was comparable between the two groups. However, the effectiveness of IM due to the acoustic-phonetic information was significantly higher in the older listeners, causing worse performances. <strong>Conclusions:</strong> The greater effectiveness of IM due to the acoustic-phonetic information (worse performance) could be due to the minimal-to-mild high-frequency hearing loss and the consequent temporal processing deficits observed in the older listeners. However, it is possible that the older listeners can employ compensatory mechanisms (such as life experiences, contextual cues, employing higher listening efforts, among many possible other mechanisms) to overcome some of these deficits. <br> <strong>Supplemental Material S1.</strong> Individual thresholds at each octave frequencies for both ears, across the two groups, as well as information regarding the amplitudes of OAEs and the gender information for both groups. <br> Jagadeesh, A. B., & Uppunda, A. K. (2022). Effect of age on informational masking: Differential effects of phonetic and semantic information in the masker. <em>American Journal of Audiology</em>. Advance online publication. https://doi.org/10.1044/2022_AJA-22-00029
DOI: 10.23641/asha.20405730.v1
title: Age-related differences in informational masking (Jagadeesh & Uppunda, 2022)

description: <strong>Purpose:</strong> Speech recognition in noise is a ubiquitous problem in older listeners. Speech, the most commonly encountered noise in the real world, causes greater masking than noise maskers, a phenomenon called informational masking (IM). This is due to the lexical-semantic and/or acoustic-phonetic information present in speech maskers. In this study, we aimed to observe the age-related differences in speech recognition and the magnitudes of IM when the maskers varied in the type of linguistic information. <strong>Method:</strong> In 30 young and 30 older individuals, we measured the signal-to-noise ratio required to obtain 50% correct identification under four-talker babble (lexical-semantic and acoustic-phonetic information), four-talker reverse babble (predominantly acoustic-phonetic information), and speech-shaped noise (SSN; energetic). <strong>Results:</strong> In both groups, the four-talker babble caused the greatest masking effect (worst performances), whereas the SSN resulted in the least masking effect (best performances). The effectiveness of IM due to the lexical-semantic information was comparable between the two groups. However, the effectiveness of IM due to the acoustic-phonetic information was significantly higher in the older listeners, causing worse performances. <strong>Conclusions:</strong> The greater effectiveness of IM due to the acoustic-phonetic information (worse performance) could be due to the minimal-to-mild high-frequency hearing loss and the consequent temporal processing deficits observed in the older listeners. However, it is possible that the older listeners can employ compensatory mechanisms (such as life experiences, contextual cues, employing higher listening efforts, among many possible other mechanisms) to overcome some of these deficits. <br> <strong>Supplemental Material S1.</strong> Individual thresholds at each octave frequencies for both ears, across the two groups, as well as information regarding the amplitudes of OAEs and the gender information for both groups. <br> Jagadeesh, A. B., & Uppunda, A. K. (2022). Effect of age on informational masking: Differential effects of phonetic and semantic information in the masker. <em>American Journal of Audiology</em>. Advance online publication. https://doi.org/10.1044/2022_AJA-22-00029
DOI: 10.6084/m9.figshare.19419071
title: Data 4a.txt

description: Experimental data for the measured Stokes parameters of a LIPSS polarization converter
DOI: 10.6084/m9.figshare.19419086
title: Data 4b.txt

description: Experimental data for the measured Stokes parameters of a LIPSS polarization converter
DOI: 10.6084/m9.figshare.19419071.v1
title: Data 4a.txt

description: Experimental data for the measured Stokes parameters of a LIPSS polarization converter
DOI: 10.6084/m9.figshare.19419086.v1
title: Data 4b.txt

description: Experimental data for the measured Stokes parameters of a LIPSS polarization converter
DOI: 10.17909/8c69-1q86
title: Data from Harris 2022 paper

description: Imaging from HST program 9427, for globular cluster photometry around early-type giant galaxies
DOI: 10.6084/m9.figshare.20060927
title: Soil-atmosphere Fluxes of CO2, CH4, and N2O Across an Experimentally-grown, Successional Gradient of Biocrust Community Types

description: Biological soil crusts (biocrusts) are critical components of dryland and other ecosystems worldwide, and are increasingly recognized as novel model ecosystems from which more general principles of ecology can be elucidated. Biocrusts are often diverse communities, comprised of both eukaryotic and prokaryotic organisms with a range of metabolic lifestyles that enable the fixation of atmospheric carbon and nitrogen. However, how the function of these biocrust communities varies with succession is incompletely characterized, especially in comparison to more familiar terrestrial ecosystem types such as forests. We conducted a greenhouse experiment to investigate how community composition and soil-atmosphere trace gas fluxes of CO2, CH4, and N2O varied from early successional light cyanobacterial biocrusts to mid-successional dark cyanobacteria biocrusts and late-successional moss-lichen biocrusts and as biocrusts of each successional stage matured. Cover type richness increased as biocrusts developed, and richness was generally highest in the late-successional moss-lichen biocrusts. Microbial community composition varied in relation to successional stage, but microbial diversity did not differ significantly among stages. Net photosynthetic uptake of CO2 by each biocrust type also increased as biocrusts developed but tended to be moderately greater (by up to 20%) for the mid-successional dark cyanobacteria biocrusts than the early-successional light cyanobacterial biocrusts or the moss-lichen biocrusts. Rates of soil C accumulation were highest for the dark cyanobacteria biocrusts and early successional light cyanobacteria biocrusts, and lowest for the moss-lichen biocrusts and bare soil controls. Biocrust CH4 and N2O fluxes were not consistently distinguishable from the same fluxes measured from bare soil controls; the measured rates were also substantially lower than have been reported in previous biocrust studies. Our experiment, which uniquely used greenhouse-grown biocrusts to manipulate community composition and accelerate biocrust development, shows how biocrust function varies along a dynamic gradient of biocrust successional stages. <br> This data set includes community composition surveys, microbial sequence data, fluxes of CO2, CH4 and N2O, and measurements of organic matter content.
DOI: 10.6084/m9.figshare.20060927.v1
title: Soil-atmosphere Fluxes of CO2, CH4, and N2O Across an Experimentally-grown, Successional Gradient of Biocrust Community Types

description: Biological soil crusts (biocrusts) are critical components of dryland and other ecosystems worldwide, and are increasingly recognized as novel model ecosystems from which more general principles of ecology can be elucidated. Biocrusts are often diverse communities, comprised of both eukaryotic and prokaryotic organisms with a range of metabolic lifestyles that enable the fixation of atmospheric carbon and nitrogen. However, how the function of these biocrust communities varies with succession is incompletely characterized, especially in comparison to more familiar terrestrial ecosystem types such as forests. We conducted a greenhouse experiment to investigate how community composition and soil-atmosphere trace gas fluxes of CO2, CH4, and N2O varied from early successional light cyanobacterial biocrusts to mid-successional dark cyanobacteria biocrusts and late-successional moss-lichen biocrusts and as biocrusts of each successional stage matured. Cover type richness increased as biocrusts developed, and richness was generally highest in the late-successional moss-lichen biocrusts. Microbial community composition varied in relation to successional stage, but microbial diversity did not differ significantly among stages. Net photosynthetic uptake of CO2 by each biocrust type also increased as biocrusts developed but tended to be moderately greater (by up to 20%) for the mid-successional dark cyanobacteria biocrusts than the early-successional light cyanobacterial biocrusts or the moss-lichen biocrusts. Rates of soil C accumulation were highest for the dark cyanobacteria biocrusts and early successional light cyanobacteria biocrusts, and lowest for the moss-lichen biocrusts and bare soil controls. Biocrust CH4 and N2O fluxes were not consistently distinguishable from the same fluxes measured from bare soil controls; the measured rates were also substantially lower than have been reported in previous biocrust studies. Our experiment, which uniquely used greenhouse-grown biocrusts to manipulate community composition and accelerate biocrust development, shows how biocrust function varies along a dynamic gradient of biocrust successional stages. <br> This data set includes community composition surveys, microbial sequence data, fluxes of CO2, CH4 and N2O, and measurements of organic matter content.
DOI: 10.17909/36nb-z070
title: Data from Harris 2022 paper

description: HST imaging from program 10201, for globular cluster photometry around NGC 1272
DOI: 10.3886/icpsr38480
title: Moldova Compact - Value Chain Training: Final Program Data
title: Archival Version

description: Datasets: DS1: Moldova Compact - Value Chain Training: Final Program Data
DOI: 10.3886/icpsr38480.v1
title: Moldova Compact - Value Chain Training: Final Program Data
title: Version 1

description: Datasets: DS1: Moldova Compact - Value Chain Training: Final Program Data
DOI: 10.6084/m9.figshare.20435796.v1
title: AustralianOrdvnApr2022SDT1LONG.xlsx

description: Detrital zircon age data in Excel format, Ordovician rocks, eastern Australia
DOI: 10.6084/m9.figshare.20435796
title: AustralianOrdvnApr2022SDT1LONG.xlsx

description: Detrital zircon age data in Excel format, Ordovician rocks, eastern Australia
DOI: 10.6084/m9.figshare.14456312
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the ventral side of the forearm, by being attached with a velcro to the exterior of a cotton sports wrist band. <br> This dataset is meant to capture ambient temperature. It is placed just beside the main skin sensor but on the exterior of the cotton wristband instead of the interior, so that this sensor reflects the ambient temperature at the exact site where the main skin sensor is. This should be used in combination with the ibutton-left-nondominant-upper-arm-cotton-sports-wristband-radial-artery-ventral-interior-5min dataset (main skin sensor, placed on the radial artery). <br> Start using the files from the datetime (in filename): 071621 and onward. Indeed, earlier logs are redundant. Concatenate every files beyond this date to get the full log, each file containing one distinct period of time.<br> Earlier logs contain the same data as 071621, as initially it was thought that the sensor had enough memory to collect 1 year of data, but this was in fact incorrect (it's about 6-7 months of data). So it's necessary to clear the sensor's data before collecting a new period. <br> Note that the datetime in the filename is in US format: monthdayyear.
DOI: 10.6084/m9.figshare.14456312.v8
title: ibutton-left-nondominant-upper-arm-cotton-sports-wristband-ventral-exterior-5min

description: Skin temperature using a Maxim Thermocron iButton DS1925L set at a resolution of one sample every 5 min (max resolution) and temperature resolution of 0.0625°C (max resolution), placed on the ventral side of the forearm, by being attached with a velcro to the exterior of a cotton sports wrist band. <br> This dataset is meant to capture ambient temperature. It is placed just beside the main skin sensor but on the exterior of the cotton wristband instead of the interior, so that this sensor reflects the ambient temperature at the exact site where the main skin sensor is. This should be used in combination with the ibutton-left-nondominant-upper-arm-cotton-sports-wristband-radial-artery-ventral-interior-5min dataset (main skin sensor, placed on the radial artery). <br> Start using the files from the datetime (in filename): 071621 and onward. Indeed, earlier logs are redundant. Concatenate every files beyond this date to get the full log, each file containing one distinct period of time.<br> Earlier logs contain the same data as 071621, as initially it was thought that the sensor had enough memory to collect 1 year of data, but this was in fact incorrect (it's about 6-7 months of data). So it's necessary to clear the sensor's data before collecting a new period. <br> Note that the datetime in the filename is in US format: monthdayyear.