cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5066/p9zfkcrj
title: Low-Flow Period Seasonality, Trends, and Climate Linkages Across the United States Data Release

description: This metadata record describes data that characterize low-flow period duration and seasonality, as well as trends and climate linkages at streamgages across the conterminous United States. These data are associated with a publication which looks to answer three questions about low-flow periods in the conterminous United States: (1) how long are these periods and when do they typically start and end, (2) how are these properties changing through time, and (3) how does climate influence these properties? These data include 1145 U.S. Geological Survey streamgages with historical periods from 1951-2020. This data release contains the following:

1) low_flow_characteristics.csv: Annual low-flow period characteristics for selected streamgages, for each climate year from 1951-2020.
2) low_flow_trends.csv: Trends in low-flow period characteristics for selected streamgages, from 1951-2020.
3) climate_trends.csv: Trends in climate variables for selected streamgages related to low-flow periods from 1951-2020.
4) monthly_low_flows.csv: The number of low-flow days in each month for selected streamgages.
5) site_metadata.csv: Metadata for describing each of the selected streamgages.
6) climate_correlations.csv: Correlations between low-flow period characteristics for selected streamgages and climate variables.
7) all_percentiles_1951_2020.zip: A zip file containing all streamflow percentile data used in this analysis.
DOI: 10.34740/kaggle/dsv/7211295
title: Balochi Language to English Translation Dataset
DOI: 10.21227/ha78-f960
title: The OSHA dataset: Overtaking on Simulated HighwAys

description: Volkswagen Group of America Innovation and Engineering Center California (VW IECC) is a research facility in Belmont, California working on the future of the mobility. In the recent years exciting developments have happened for the autonomous vehicles. In general, lack of data is the main problem to tackle to solve the task of autonomous driving. One of the important tasks in this topic is the overtaking and lane changes, especially in the highway scenarios. Due to the cost and challenges of real-world data collection, specifically in a highway environment, a simulation environment named SimPilot was developed by Innovation Center Europe (ICE) for data collection in highway scenarios. To solve the task of overtaking and automatic lane changing, we release a large-scale (more than 8M frames) dataset called Overtaking in Simulated HighwAy (OSHA) of Ego vehicles driving in a highway environment with traffic, consisting of lane ID sensor maps and data frame recorded at each frame. The scene is a 3.2 km long loop consisting of 3 lanes with different traffic densities at different episodes. Other movable objects present in the scene are limited to vehicles (no busses, bikes, trucks, or pedestrians) and are controlled by SUMO.The Ego was controlled by an in-house developed rule-based algorithm to ensure the maximum safety and correctness of every lane change, as well as following the traffic rules and speed limits. The 8M frames were recorded at each step, where steps are 50ms apart from each other (about 50 hrs of Ego driving). Moreover, traffic densities are set by number of vehicles per km which varies from 5 to 35. On top of that, the speed limit is randomly changed at each episode and different sections of the road have different speed limits.
DOI: 10.6084/m9.figshare.23511972
title: <strong>Evolution of the Xerocarpa clade: evidence for the role of the Grand Canyon in the biogeographic history of the iconic beavertail cactus and relatives</strong>

description: The plastome dataset derived from genome skimming data is given along with a reduced file used for biogeographic analyses. The Mesquite dataset likewise is given, along with the full RAxML tree used in the paper.
DOI: 10.6084/m9.figshare.23511972.v1
title: <strong>Evolution of the Xerocarpa clade: evidence for the role of the Grand Canyon in the biogeographic history of the iconic beavertail cactus and relatives</strong>

description: The plastome dataset derived from genome skimming data is given along with a reduced file used for biogeographic analyses. The Mesquite dataset likewise is given, along with the full RAxML tree used in the paper.
DOI: 10.6084/m9.figshare.24243181.v2
title: Data and code needed to recreate "Impact of Adjustment for Differential Testing by Age and Sex on Apparent Epidemiology of SARS-CoV-2 Infection in Ontario, Canada".

description: Data and Stata code for recreation of "Impact of Adjustment for Differential Testing by Age and Sex on Apparent Epidemiology of SARS-CoV-2 Infection in Ontario, Canada". For questions about analysis please contact me directly at david.fisman@gmail.com or david.fisman@utoronto.ca.Paper abstract: Surveillance of communicable diseases typically relies on case counts for estimates of risk, and counts can be strongly influenced by testing rates. In the Canadian province of Ontario, testing rates varied markedly by age, sex, geography and time over the course of the SARS-CoV-2 pandemic. We applied a standardization-based approach to test-adjustment to better understand pandemic dynamics from 2020 to 2022, and to better understand when test-adjustment is necessary for accurate estimation of risk. SARS-CoV-2 case counts by age, sex, public health unit and week were obtained from Ontario’s Case and Contact Management system (CCM), which includes all SARS-CoV-2 cases from March 2020 to August 2022. Complete data on testing volumes was obtained from the Ontario Laboratory Information System (OLIS). Case counts were adjusted for under-testing using a previously published standardization-based approach that estimates case numbers that would have been expected if the entire population was tested at the same rate as most-tested age and sex groups. Logistic regression was used to identify threshold testing rates beyond which test-adjustment was unnecessary. Testing rates varied markedly by age, sex, public health unit and pandemic wave. After adjustment for under-testing, overall case counts increased threefold. Adjusted epidemic curves suggested, in contrast to reported case counts, that the first two pandemic waves were equivalent in size, and that there were three distinct pandemic waves in 2022, due to the emergence of Omicron variants. Under-reporting was greatest in children and young males, and varied significantly across public health units, with variation explained partly by testing rates and prevalence of multigenerational households. Test adjustment resulted in little change in the epidemic curve during pandemic waves when testing rates were highest; we found that test-adjustment did not increase case counts once weekly per capita testing rates exceeded 6.3%. We conclude that standardization-based adjustment for differential testing by age and sex, and for dynamic changes in testing over time, results in a different picture of infection risk during the SARS-CoV-2 pandemic in Ontario; test-adjusted epidemic curves are concordant with observed patterns of mortality during the pandemic and have face validity. This methodology offers an alternative to sero-epidemiology for identification of true burden of infection when reinfection, sero-reversion, and non-specificity of serological assays make sero-epidemiology challenging.
DOI: 10.6084/m9.figshare.24466939
title: Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions

description: We study causal inference under case-control and case-population sampling. Specifically, we focus on the binary-outcome and binary-treatment case, where the parameters of interest are causal relative and attributable risks defined via the potential outcome framework. It is shown that strong ignorability is not always as powerful as it is under random sampling and that certain monotonicity assumptions yield comparable results in terms of sharp identified intervals. Specifically, the usual odds ratio is shown to be a sharp identified upper bound on causal relative risk under the monotone treatment response and monotone treatment selection assumptions. We offer algorithms for inference on the causal parameters that are aggregated over the true population distribution of the covariates. We show the usefulness of our approach by studying three empirical examples: the benefit of attending private school for entering a prestigious university in Pakistan; the relationship between staying in school and getting involved with drug-trafficking gangs in Brazil; and the link between physicians’ hours and size of the group practice in the United States.
DOI: 10.6084/m9.figshare.24466939.v2
title: Causal Inference Under Outcome-Based Sampling with Monotonicity Assumptions

description: We study causal inference under case-control and case-population sampling. Specifically, we focus on the binary-outcome and binary-treatment case, where the parameters of interest are causal relative and attributable risks defined via the potential outcome framework. It is shown that strong ignorability is not always as powerful as it is under random sampling and that certain monotonicity assumptions yield comparable results in terms of sharp identified intervals. Specifically, the usual odds ratio is shown to be a sharp identified upper bound on causal relative risk under the monotone treatment response and monotone treatment selection assumptions. We offer algorithms for inference on the causal parameters that are aggregated over the true population distribution of the covariates. We show the usefulness of our approach by studying three empirical examples: the benefit of attending private school for entering a prestigious university in Pakistan; the relationship between staying in school and getting involved with drug-trafficking gangs in Brazil; and the link between physicians’ hours and size of the group practice in the United States.
DOI: 10.6084/m9.figshare.24466939.v1
title: Causal inference under outcome-based sampling with monotonicity assumptions

description: We study causal inference under case-control and case-population sampling. Specifically, we focus on the binary-outcome and binary-treatment case, where the parameters of interest are causal relative and attributable risks defined via the potential outcome framework. It is shown that strong ignorability is not always as powerful as it is under random sampling and that certain monotonicity assumptions yield comparable results in terms of sharp identified intervals. Specifically, the usual odds ratio is shown to be a sharp identified upper bound on causal relative risk under the monotone treatment response and monotone treatment selection assumptions. We offer algorithms for inference on the causal parameters that are aggregated over the true population distribution of the covariates. We show the usefulness of our approach by studying three empirical examples: the benefit of attending private school for entering a prestigious university in Pakistan; the relationship between staying in school and getting involved with drug-trafficking gangs in Brazil; and the link between physicians’ hours and size of the group practice in the United States.
DOI: 10.6084/m9.figshare.20410777
title: You make me feel … autonomous or controlled: A mixed-method study on for- and non-profit platform organizations

description: Digitalization supports the development of platform organizations, changing work relationships between individuals and organizations. This paper analyzes workers’ perceptions of autonomy and control in for- and non-profit platform organizations. Based on a mixed-methods study combining qualitative interviews and a quantitative questionnaire in digital food supply chains, this contribution empirically evaluates the interrelation of autonomy and control for two German sample groups of riders and volunteers. The analysis shows that the perceptions of autonomy and control are constitutive of work outcomes and thus essential for understanding work relationships in platform organizations. These perceptions differ in for- and non-profit contexts, providing insights to motivation and labor processes in platform work.
DOI: 10.6084/m9.figshare.20410777.v1
title: You make me feel … autonomous or controlled: A mixed-method study on for- and non-profit platform organizations

description: Digitalization supports the development of platform organizations, changing work relationships between individuals and organizations. This paper analyzes workers’ perceptions of autonomy and control in for- and non-profit platform organizations. Based on a mixed-methods study combining qualitative interviews and a quantitative questionnaire in digital food supply chains, this contribution empirically evaluates the interrelation of autonomy and control for two German sample groups of riders and volunteers. The analysis shows that the perceptions of autonomy and control are constitutive of work outcomes and thus essential for understanding work relationships in platform organizations. These perceptions differ in for- and non-profit contexts, providing insights to motivation and labor processes in platform work.
DOI: 10.5281/zenodo.10392843
title: Wikidata query for ICONGRAPH1.0

description: This is the results of the query used to create "IICONGRAPHwikidata 1.0"
DOI: 10.5281/zenodo.10392844
title: Wikidata query for ICONGRAPH1.0

description: This is the results of the query used to create "IICONGRAPHwikidata 1.0"
DOI: 10.6084/m9.figshare.22137713
title: Biogeography and diversification of the Caribbean Clade of Miconia (Melastomataceae): a Cuban origin underlies one of the largest Antillean radiations

description: This is the 243 taxon plastome dataset of the Caribbean clade of Miconia, along with outgroups from other clades of Miconia, other tribes of Melastomataceae and the families Myrtaceae, Vochysiaceae and Alzateaceae. The RAxML tree based on 1000 bootstrap pseudoreplicates has also been included, and the biogeographic coding is supplied.
DOI: 10.5281/zenodo.10389977
title: Data used in "The Complex Role of Storms in Modulating Air-Sea CO2 Fluxes in the sub-Antarctic Southern Ocean"

description: The data included in this repository were used to generate the figures for the paper "The Complex Role of Storms in Modulating Air-Sea CO2 Fluxes in the sub-Antarctic Southern Ocean" in Geophysical Research Letter.

Abstract:

"The intra-seasonal CO2 flux (FCO2) variability across the Southern Ocean is poorly understood due to sparse observations at the required temporal and spatial scales. Twinned Waveglider-Seaglider experiments were used to investigate how storms influence FCO2 through both the gas transfer velocity (kw) and the air-sea gradient in partial pressure of CO2 (ΔpCO2) in the sub-Antarctic zone. Winter-spring storms caused ΔpCO2 to weaken (by 15-55 μatm) due to mixing/entrainment and weaker stratification. This response in ΔpCO2 was in phase with kw resulting in a counteractive weakening in FCO2 (by 6.6 - 26.5% per storm), despite the wind-driven increase in kw. Stronger stratification during summer explained the weaker sensitivity of ΔpCO2 to storms, instead its thermal drivers dominated the ΔpCO2 variability. These results highlight the importance of observing synoptic-scale variability in ΔpCO2, the absence of which may propagate significant biases to the mean annual FCO2 estimates from large-scale observing programmes and reconstructions."

The data collected from the Wave Glider, such as the concentration of CO2 in the atmosphere (xCO2air) and in the ocean (xCO2sea), surface temperature and salinity were used to calculate the different parameters of the bulk CO2 flux formula (FCO2 = kw x ko x ΔpCO2). Note that the meteorological weather station of one of the Wave Gliders was faulty and the wind speed, wind direction and wind stress data was replaced by hourly ERA5 data provided by ECMWF available at https://doi.org/10.24381/cds.bd0915c6. 

The temperature, pressure and salinity data collected by the Seaglider were used to calculate the Mixed Layer Depth and the Brunt Vaisala Frequency of the first 300m of the ocean.
DOI: 10.5281/zenodo.10389978
title: Data used in "The Complex Role of Storms in Modulating Air-Sea CO2 Fluxes in the sub-Antarctic Southern Ocean"

description: The data included in this repository were used to generate the figures for the paper "The Complex Role of Storms in Modulating Air-Sea CO2 Fluxes in the sub-Antarctic Southern Ocean" in Geophysical Research Letter.

Abstract:

"The intra-seasonal CO2 flux (FCO2) variability across the Southern Ocean is poorly understood due to sparse observations at the required temporal and spatial scales. Twinned Waveglider-Seaglider experiments were used to investigate how storms influence FCO2 through both the gas transfer velocity (kw) and the air-sea gradient in partial pressure of CO2 (ΔpCO2) in the sub-Antarctic zone. Winter-spring storms caused ΔpCO2 to weaken (by 15-55 μatm) due to mixing/entrainment and weaker stratification. This response in ΔpCO2 was in phase with kw resulting in a counteractive weakening in FCO2 (by 6.6 - 26.5% per storm), despite the wind-driven increase in kw. Stronger stratification during summer explained the weaker sensitivity of ΔpCO2 to storms, instead its thermal drivers dominated the ΔpCO2 variability. These results highlight the importance of observing synoptic-scale variability in ΔpCO2, the absence of which may propagate significant biases to the mean annual FCO2 estimates from large-scale observing programmes and reconstructions."

The data collected from the Wave Glider, such as the concentration of CO2 in the atmosphere (xCO2air) and in the ocean (xCO2sea), surface temperature and salinity were used to calculate the different parameters of the bulk CO2 flux formula (FCO2 = kw x ko x ΔpCO2). Note that the meteorological weather station of one of the Wave Gliders was faulty and the wind speed, wind direction and wind stress data was replaced by hourly ERA5 data provided by ECMWF available at https://doi.org/10.24381/cds.bd0915c6. 

The temperature, pressure and salinity data collected by the Seaglider were used to calculate the Mixed Layer Depth and the Brunt Vaisala Frequency of the first 300m of the ocean.
DOI: 10.5066/p92p2m7s
title: Analysis of Polyphenols in Water Primrose (Ludwigia hexapetala) Plants from the Sacramento-San Joaquin Delta of California

description: Water primrose (Ludwigia hexapetala) is an invasive aquatic plant that has rapidly increased in coverage throughout the Sacramento-San Joaquin Delta. Water primrose has invaded wetlands and may contribute towards mortality of tules (Schoenoplectus spp.) and cattails (Typha spp.). Little research has been completed on the mechanisms responsible for marsh loss, but previous studies have suggested that water primrose contains allelopathic chemicals that could cause plant mortality. Three major allelopathic polyphenols (myricitrin, prunin, and quercitrin) previously identified in L. hexapetala leaves were measured in leaf, water, and soil samples from Delta marshes infested with water primrose. Samples were collected in� summer 2021, fall 2022, and spring 2022 at Big Break, Latham Slough, Liberty Island, and Sherman Lake. Samples were collected at Rhode Island and Venice Cut only in summer 2021. Samples were collected at the interface between water primrose and the marsh and within the patch of floating water primrose. In analyzing leaf samples by liquid chromatography tandem mass spectrometry, ion ratios and retention times of the prunin reference standard did not align with the analyte in the samples (i.e., prunin was not detected in water primrose from the Delta). Further analysis by high resolution mass spectrometry and library matching resulted in the tentative identification of salipurposid, a structural isomer of prunin, as the potential third major polyphenol expressed by water primrose in the Delta. For the purpose of this study, salipurposid was semi-quantitated using the prunin reference standard to give concentration values. In leaves, concentrations of myricitrin, salipurposid, and quercitrin ranged 900-4397 �g/g dry weight (d.w.), 7-2913 �g/g d.w., and 363-3956 �g/g d.w., respectively. Analysis of water samples for polyphenols found the highest number of detections in summer, with many non-detects in fall and spring. Polyphenols were detected in soil samples throughout the year. Quercitrin was the most frequently detected polyphenol in water (53%, 5-3660 ng/L) and soil (67%, 11-1766 ng/g d.w.). The proliferation of water primrose likely threatens the Delta ecosystem. Additional studies could further elucidate how water primrose affects native marsh habitat and causes mortality of emergent macrophytes.
DOI: 10.25345/c5ng4h33r
title: MassIVE MSV000093672 - Exploration of adult mouse Single Cardiomyocyte Proteome using Label-Free LC-MS
title: Cardiac myocyte heterogeneity has been acknowledged based on ion channel expression, cellular electrophysiology and through transcriptomics, but the exploration of individual cardiomyocytes at the board proteome-wide level has remained challenging. We developed an entire analytical pipeline to assess the cell heterogeneity of adult primary cardiomyocytes isolated from mouse hearts. Over 700 single cell proteomes were isolated from 4 mice hearts. Each single cell image was captured by the cellenONE sorter interface and evaluated for morphological features of apoptotic cells, i.e.: hypercontracted cell shape. This imaging analysis allowed us to retain 270 rod-shaped cardiac cells for downstream single cell proteome sample processing and analysis on Bruker timsTOF SCP mass spectrometer. Final dataset UMAP dimension reduction and clustering analysis yielded 3 cardiomyocyte cell sub-populations that displayed differential: i) expression of Myh7 and Myh7b, ii) carbon metabolism signatures and iii) distribution of 7 proteins involved in calcium signaling. Single cardiomyocyte protemes demonstrated potential differences related to the metabolism and calcium ion handling between those sub-populations and could bring new insights for cardiology studies on mice.
DOI: 10.6084/m9.figshare.24843702
title: When Grinnellian generalist species seem to be more sensitive to altered habitats than specialists: the case of Orthoptera communities settled in coastal dunes

description: Numerous examples documented that species generalists for habitats are less sensitive to altered environment than specialists. However, in arid environments, an example indicated an opposite trend due to special adaptive features of organisms. We tested this hypothesis in the case of grasshopper communities, settled in the coastal dunes of northeast Algeria, as several aspects of dunes constitute stressful conditions resembling those of deserts. To define the dune-specific grasshoppers (specialists) and the dune non-specific ones (generalists), we applied the indicator value index to monthly samplings conducted in four coastal dune sites and 12 other sites of grasslands, fallow lands and scrublands in the same area. The degree of disturbance of each coastal dune site was deduced from the alteration of plant cover and richness. We investigated the relation between the specialist and generalist richness and abundance with the degree of perturbation using linear regressions. Results showed contrasting patterns for specialist and generalist grasshoppers: both abundance and richness of the generalists significantly decrease with an increasing degree of perturbation, while specialists show little to no changes. The higher resistance of specialist grasshoppers over generalists toward disturbance was not linked to the plant dune-specialists or generalists. This study is one of very few illustrating the relative resistance of specialized species toward disturbance.