cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.6725353
title: Long-term observation of the wastewater from the Parisian conurbation

description: Wastewater contains a wide range of biological and chemical markers related to human activity. The collection and analysis of these markers in the effluents (wastewater and sludge) allow make it possible to qualify the public health of the population and to evaluate the impact of the chemicals used in daily life on the environment.<br> In line with these studies, the Innovation Department of SIAAP and its scientific partners (ISA and LEESU) have created an Observatory of the city with the objectives of:<br> • Monitoring the long-term dynamics of known and/or potential pollutants according to French regulations.<br> • Contributing to studies aimed at a better understanding of anthropogenic activities.<br> • Structuring and centralizing data (wastewater and end-of-treatment sludge), ensuring their storage for 10 years.<br> • Providing technical and scientific knowledge by publishing every two years the data generated by the Observatory of the city via the open platform Zenodo.<br> Regarding the pre-treated wastewater, the Clichy pretreatment plant has been chosen as a strategic location because it collects wastewater from the Paris catchment area (2.7 million inhabitants). Data on the wastewater quality during dry weather and on rain events (biological and physicochemical global quality parameters, metals, polycyclic aromatic hydrocarbons – PAHs and polychlorinated biphenyls – PCBs) is available since 2000 (for dry weather) and from 2005 (for rain events). <strong>Dataset description</strong> The dataset “Dataset _Clichy-SEC-Inlet.xlsx” includes the monthly analysis of various micro pollutants (trace metals, PAHs and PCBs) and usual physico-chemical parameters. The oldest analyses date back to 2000. The dataset “Dataset _Clichy-CSO.xlsx” includes the monthly quantified analysis of various micro pollutants (trace metals, PAHs and PCBs) and usual physico-chemical parameters for samples collected during 384 rain events. The oldest analyses date back to 2005. Details on each analysis are provided in the “Dataset_analyticalmethods_Clichy.xlsx” The following files are available: Dataset _Clichy-SEC-Inlet.xlsx Dataset _Clichy-CSO.xlsx Dataset_analyticalmethods_Clichy.xlsx
DOI: 10.5281/zenodo.6725352
title: Long-term observation of the wastewater from the Parisian conurbation

description: Wastewater contains a wide range of biological and chemical markers related to human activity. The collection and analysis of these markers in the effluents (wastewater and sludge) allow make it possible to qualify the public health of the population and to evaluate the impact of the chemicals used in daily life on the environment.<br> In line with these studies, the Innovation Department of SIAAP and its scientific partners (ISA and LEESU) have created an Observatory of the city with the objectives of:<br> • Monitoring the long-term dynamics of known and/or potential pollutants according to French regulations.<br> • Contributing to studies aimed at a better understanding of anthropogenic activities.<br> • Structuring and centralizing data (wastewater and end-of-treatment sludge), ensuring their storage for 10 years.<br> • Providing technical and scientific knowledge by publishing every two years the data generated by the Observatory of the city via the open platform Zenodo.<br> Regarding the pre-treated wastewater, the Clichy pretreatment plant has been chosen as a strategic location because it collects wastewater from the Paris catchment area (2.7 million inhabitants). Data on the wastewater quality during dry weather and on rain events (biological and physicochemical global quality parameters, metals, polycyclic aromatic hydrocarbons – PAHs and polychlorinated biphenyls – PCBs) is available since 2000 (for dry weather) and from 2005 (for rain events). <strong>Dataset description</strong> The dataset “Dataset _Clichy-SEC-Inlet.xlsx” includes the monthly analysis of various micro pollutants (trace metals, PAHs and PCBs) and usual physico-chemical parameters. The oldest analyses date back to 2000. The dataset “Dataset _Clichy-CSO.xlsx” includes the monthly quantified analysis of various micro pollutants (trace metals, PAHs and PCBs) and usual physico-chemical parameters for samples collected during 384 rain events. The oldest analyses date back to 2005. Details on each analysis are provided in the “Dataset_analyticalmethods_Clichy.xlsx” The following files are available: Dataset _Clichy-SEC-Inlet.xlsx Dataset _Clichy-CSO.xlsx Dataset_analyticalmethods_Clichy.xlsx
DOI: 10.5281/zenodo.6725351
title: Replication Package - IoT Roadmap Observation Study

description: Replication package for a Observation Study. GOAL: This work aims to analyze the use of the IoT Roadmap with the purpose of understanding in relation to its applicability from the point of view of junior software engineers in the context of the IoT project for COVID-19 developed at the Federal University of Rio de Janeiro.
DOI: 10.5281/zenodo.6725350
title: Replication Package - IoT Roadmap Observation Study

description: Replication package for a Observation Study. GOAL: This work aims to analyze the use of the IoT Roadmap with the purpose of understanding in relation to its applicability from the point of view of junior software engineers in the context of the IoT project for COVID-19 developed at the Federal University of Rio de Janeiro.
DOI: 10.5281/zenodo.6725371
title: Bertia moriformis decontaminated gx

description: .
DOI: 10.5281/zenodo.6725370
title: Bertia moriformis decontaminated gx

description: .
DOI: 10.17632/4cws9sybng.1
title: LINF_290024000

description: histone H2A
Leishmania infantum (strain JPCM5)
DOI: 10.17632/53g442g5y7.1
title: LINF_290023900

description: histone H2A
Leishmania infantum (strain JPCM5)
DOI: 10.17632/v7ppb2xr99.1
title: SNP array data for a native European flat oyster (Ostrea edulis) population

description: Genotype data for a hatchery-derived European flat oyster population (n=840 individuals) with matching growth phenotype data (see link below). Four growth-related traits were measured in the experimental population: Body weight (BW, the weight of an individual oyster including the shell ), Shell length (SL, the maximum distance between the anterior and posterior margins), Shell height (SH, the maximum distance between the hinge to the furthermost edge), and Shell width (SW, the maximum distance at the thickest part of the two shell valves).
Individual oysters were genotyped using the combined-species Affymetrix Axiom® oyster SNP-array. The genotype data is available in VCF format for markers passing quality control (QC) filters (see steps below).
DOI: 10.17632/36vgsrpy2n.1
title: Research Data: Presupposition triggers and (not-)at-issueness

description: Here are the cleaned data file and the scripts that we used to perform the analysis for the article "Presupposition triggers and (not-)at-issueness: Insights from language acquisition into the soft-hard distinction"
DOI: 10.6084/m9.figshare.20145638.v1
title: Additional file 1 of Effect of physical therapy on bone remodelling in preterm infants: a multicenter randomized controlled clinical trial

description: Additional file 1: Table S1. Raw Data.
DOI: 10.6084/m9.figshare.20145638
title: Additional file 1 of Effect of physical therapy on bone remodelling in preterm infants: a multicenter randomized controlled clinical trial

description: Additional file 1: Table S1. Raw Data.
DOI: 10.5281/zenodo.6725472
title: Brienomyrus brachyistius decontaminated gx

description: .
DOI: 10.5281/zenodo.6725471
title: Brienomyrus brachyistius decontaminated gx

description: .
DOI: 10.5281/zenodo.4646429
title: Coherent and non-coherent Eddy Kinetic Energy and gridded coherent eddy statistics

description: This dataset includes the processed data used for the paper titled "Climatology, seasonality and trends of oceanic coherent eddies". The original data was obtained from AVISO+ SSH altimetry, Martínez-Moreno, J. <em>et.al (</em>2019)<em> </em>and Chelton, D. B., & Schlax, M. G. (2013). Further information and scripts to reproduce the result of the manuscript can be found at: https://github.com/josuemtzmo/CEKE_climatology
DOI: 10.5281/zenodo.4646428
title: Coherent and non-coherent Eddy Kinetic Energy and gridded coherent eddy statistics

description: This dataset includes the processed data used for the paper titled "Climatology, seasonality and trends of oceanic coherent eddies". The original data was obtained from AVISO+ SSH altimetry, Martínez-Moreno, J. <em>et.al (</em>2019)<em> </em>and Chelton, D. B., & Schlax, M. G. (2013). Further information and scripts to reproduce the result of the manuscript can be found at: https://github.com/josuemtzmo/CEKE_climatology
DOI: 10.5281/zenodo.6579776
title: TRPC3 interaction with cholesterol as explored through MD (raw data)

description: Transient receptor potential canonical 3 (TRPC3) channel belongs to the superfamily of transient receptor potential (TRP) channels which mediate Ca<sup>2+</sup> influx into the cell. These channels constitute essential elements of cellular signalling. TRPC3 is primarily gated by lipids, and its surface expression has been shown to be dependent on cholesterol, yet a comprehensive exploration of its interaction with this lipid has thus far not emerged. Here, through 80 µs of coarse-grained molecular dynamics simulations, we show that cholesterol interacts with multiple elements of the transmembrane machinery of TRPC3. Through our approach, we identify an annular binding site for cholesterol on the pre-S1 helix, and a non-annular site at the interface between the voltage-sensor like domain and pore domains. Here cholesterol interacts with exposed polar residues, and possibly acts to stabilise the domain interface. <br> p { margin-bottom: 0.08in; color: #000000; line-height: 0.24in; text-align: justify; orphans: 2; widows: 2; background: transparent }p.western { font-family: "Palatino Linotype", serif; font-size: 12pt }p.cjk { font-family: "Palatino Linotype", serif; font-size: 12pt; so-language: de-DE }p.ctl { font-family: "Palatino Linotype", serif }a:visited { color: #954f72; text-decoration: underline }a:link { color: #0000ff; text-decoration: underline }
description: {"references": ["Clarke, A et al (2022) Exploring TRPC3 Interaction with Cholesterol through Coarse-Grained Molecular Dynamics Simulations"]}
DOI: 10.5281/zenodo.6579775
title: TRPC3 interaction with cholesterol as explored through MD (raw data)

description: Transient receptor potential canonical 3 (TRPC3) channel belongs to the superfamily of transient receptor potential (TRP) channels which mediate Ca<sup>2+</sup> influx into the cell. These channels constitute essential elements of cellular signalling. TRPC3 is primarily gated by lipids, and its surface expression has been shown to be dependent on cholesterol, yet a comprehensive exploration of its interaction with this lipid has thus far not emerged. Here, through 80 µs of coarse-grained molecular dynamics simulations, we show that cholesterol interacts with multiple elements of the transmembrane machinery of TRPC3. Through our approach, we identify an annular binding site for cholesterol on the pre-S1 helix, and a non-annular site at the interface between the voltage-sensor like domain and pore domains. Here cholesterol interacts with exposed polar residues, and possibly acts to stabilise the domain interface. <br> p { margin-bottom: 0.08in; color: #000000; line-height: 0.24in; text-align: justify; orphans: 2; widows: 2; background: transparent }p.western { font-family: "Palatino Linotype", serif; font-size: 12pt }p.cjk { font-family: "Palatino Linotype", serif; font-size: 12pt; so-language: de-DE }p.ctl { font-family: "Palatino Linotype", serif }a:visited { color: #954f72; text-decoration: underline }a:link { color: #0000ff; text-decoration: underline }
description: {"references": ["Clarke, A et al (2022) Exploring TRPC3 Interaction with Cholesterol through Coarse-Grained Molecular Dynamics Simulations"]}
DOI: 10.17026/dans-zpj-tf75
title: Op de grens van de Stede. Rapportage over de eerste fase van het archeologisch proefonderzoek (IVO), voor de uitbreiding van winkelcentrum Streekhof G

description: Onderzoeksrapport
DOI: 10.5281/zenodo.6425657
title: Global Long-term River Width (GLOW)

description: This repository archives the Global LOng term river Width (GLOW) dataset measured from Landsat for 1984-2020. There are three datasets in this repository: Width, Cross_section, and Environmental_parameter_global. Width contains the GLOW dataset, which has three attributes: ID, date (mm/dd/yyyy), and width (unit: meters). Each cross-section is identified by a unique ID in the format of R########XS#######. The dataset is grouped into eight regions based on the geospatial location. Cross-section contains the shapefiles indicating the GLOW cross-section locations, which have three attributes: ID, lat (latitude), and lon (longitude). Environmental_parameter_global contains the environmental parameters generated in this study for the Random Forest analysis, which has eighteen parameters for all global rivers at the river reach level, including the temporal trend slope, interquartile range, 25th percentile, and 75th percentile of air temperature, snowmelt, precipitation, evapotranspiration, and river discharge. Please refer to the following paper for more details: Feng, D., Gleason C.J., Yang X., Allen G.H., and Pavelsky T.M., How have global river widths changed over time? Water Resources Research
DOI: 10.5281/zenodo.6425656
title: Global Long-term River Width (GLOW)

description: This repository archives the Global LOng term river Width (GLOW) dataset measured from Landsat for 1984-2020. There are three datasets in this repository: Width, Cross_section, and Environmental_parameter_global. Width contains the GLOW dataset, which has three attributes: ID, date (mm/dd/yyyy), and width (unit: meters). Each cross-section is identified by a unique ID in the format of R########XS#######. The dataset is grouped into eight regions based on the geospatial location. Cross-section contains the shapefiles indicating the GLOW cross-section locations, which have three attributes: ID, lat (latitude), and lon (longitude). Environmental_parameter_global contains the environmental parameters generated in this study for the Random Forest analysis, which has eighteen parameters for all global rivers at the river reach level, including the temporal trend slope, interquartile range, 25th percentile, and 75th percentile of air temperature, snowmelt, precipitation, evapotranspiration, and river discharge. Please refer to the following paper for more details: Feng, D., Gleason C.J., Yang X., Allen G.H., and Pavelsky T.M., How have global river widths changed over time? Water Resources Research
DOI: 10.17026/dans-x4t-eber
title: Archeologische begeleiding Vossenpels 3 te Nijmegen - Project Vos3

description: Vos3: Het gaat hier om de een locatie waar wtee huizen gebouwd gaan worden. Deze huizen liggen vlak naast een gebied dat tijdens eerder proefsleuvenonderzoek (Vos1) is aangegeven als een mogelijke vindplaats.
DOI: 10.5281/zenodo.6721110
title: eddymotion test data

description: This is test data for the eddymotion project: https://github.com/nipreps/eddymotion
DOI: 10.5281/zenodo.6721109
title: eddymotion test data

description: This is test data for the eddymotion project: https://github.com/nipreps/eddymotion
DOI: 10.6084/m9.figshare.20130794.v1
title: Dataset: An IoT-Enriched Event Log for Process Mining in Smart Factories

description: Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various domains, including Business Process Management (BPM) research. One main research area in BPM is process mining, which can be used to analyze event logs, e.g., for checking the conformance of running processes. However, there are only a few IoT-based event logs available for research purposes. Some of them are artificially generated and the problem occurs that they do not always completely reflect the actual physical properties of smart environments. In this paper, we present an IoT-enriched XES event log that is generated by a physical smart factory. For this purpose, we create the SensorStream XES extension for representing IoT-data in event logs. Finally, we present some preliminary analysis and properties of the log.
DOI: 10.15482/usda.adc/1526553
title: Data from: Mortality Dynamics of a Polyphagous Invasive Herbivore Reveal Clues in Its Agroecosystem Success

description: Field-based, partial life table data for immature stages of silverleaf whitefly, Bemisia argentifolii, on 6 host plants including alfalfa, broccoli, spring and fall cantaloupe, cotton, ornamental lantana, and several species of annual weeds in Maricopa, Marana and Yuma Arizona, USA. Data were collected on a total of 73 individual cohorts (each replicated 4 times) from November 2000 to April 2003 at all three study sites. For each cohort, data were generated on approximately 400 individual insects (200 eggs and 200 first instar nymphs). Data provide the marginal, cause-specific mortality for eggs, and 1st, 2nd, 3rd, and 4th instar nymphs collectively and stage-specific marginal mortality for each stage over all causes. Mortality was characterized as caused by inviability (eggs only), dislodgement, predation, parasitism (nymphs only), desiccation, and unknown. Detailed methods can be found in Naranjo and Ellsworth 2005 (Entomologia Experimentalis et Applicata 116(2): 93-108; https://doi.org/10.1111/j.1570-7458.2005.00297.x; and Naranjo and Ellsworth 2017 (Journal of Visualized Experiments, 129; https://doi.org/10.3791/56150). The method takes advantage of the sessile nature of immature stages of this insect. Briefly, an observer follows individual eggs or settled first instar nymphs from natural populations on the underside of host plant leaves in the field with a hand lens and determines causes of death for each individual over time. Weather data was monitored using the University of Arizona AzMet system. Note that these life table data do not include adult mortality or reproduction. The life table data were used to generate survivorship curves for each cohort on each host plant based on a physiological time scale of accumulated degree-days above 10C from the initiation of each cohort.
DOI: 10.5281/zenodo.6725800
title: Bangla Text Normalization Benchmark Dataset

description: This is a small benchmark dataset for Bangla Text Normalization.
DOI: 10.5281/zenodo.6725799
title: Bangla Text Normalization Benchmark Dataset

description: This is a small benchmark dataset for Bangla Text Normalization.
DOI: 10.5281/zenodo.6724911
title: Long-term observation of the end-of- treatment sludge quality from a Parisian WWTP treating wastewater from 6.5 M inhabitants

description: Wastewater contains a wide range of biological and chemical markers related to human activity. The collection and analysis of these markers in the effluents (wastewater and sludge) allow to qualify the public health of the population and to evaluate the impact of the chemicals used in daily life on the environment. In line with these studies, the Innovation Department of SIAAP and its scientific partners (ISA and LEESU) has created an Observatory of the city with the objectives of: • Monitoring the long-term dynamics of known and/or potential pollutants according to French regulations. • Contributing to studies aimed at a better understanding of anthropogenic activities. • Structuring and centralizing data (wastewater and end-of-treatment sludge), ensuring their storage for 10 years. • Providing technical and scientific knowledge by publishing every two years the data generated by the Observatory of the city via the open platform Zenodo. Regarding the end-of-treatment sludge, the Seine Aval (SAV) plant has been chosen as a strategic location, since the catchment area corresponds to the Parisian west catchment (6.5 million inhabitants). Data on the sludge micropollution (in metals, polycyclic aromatic hydrocarbons – PAHs and polychlorinated biphenyls – PCBs) are available since 1980 and are provided in the present datasets.
DOI: 10.5281/zenodo.6724910
title: Long-term observation of the end-of- treatment sludge quality from a Parisian WWTP treating wastewater from 6.5 M inhabitants

description: Wastewater contains a wide range of biological and chemical markers related to human activity. The collection and analysis of these markers in the effluents (wastewater and sludge) allow to qualify the public health of the population and to evaluate the impact of the chemicals used in daily life on the environment. In line with these studies, the Innovation Department of SIAAP and its scientific partners (ISA and LEESU) has created an Observatory of the city with the objectives of: • Monitoring the long-term dynamics of known and/or potential pollutants according to French regulations. • Contributing to studies aimed at a better understanding of anthropogenic activities. • Structuring and centralizing data (wastewater and end-of-treatment sludge), ensuring their storage for 10 years. • Providing technical and scientific knowledge by publishing every two years the data generated by the Observatory of the city via the open platform Zenodo. Regarding the end-of-treatment sludge, the Seine Aval (SAV) plant has been chosen as a strategic location, since the catchment area corresponds to the Parisian west catchment (6.5 million inhabitants). Data on the sludge micropollution (in metals, polycyclic aromatic hydrocarbons – PAHs and polychlorinated biphenyls – PCBs) are available since 1980 and are provided in the present datasets.
DOI: 10.5281/zenodo.6720690
title: Data for dynDeepDRIM evaluation

description: The data is for evaluating dynDeepDRIM https://github.com/yuxu-1/dynDeepDRIM and repeating the experiment in the related manuscript. The raw time-course single-cell RNA-seq data are from Gene Expression Omnibus (GEO) and ArrayExpress. Accession numbers: GSE79578 (mESC1), GSE65525 (mESC2), E-MTAB-3929 (hESC1), GSE75748(hESC2), GSE104158 (Mouse brain cortex). The simulation datasets (sim1, sim2, sim3, and sim4) were generated by dyngen, a scRNA-seq data simulator. These gene expression datasets were normalized by sctransform, a scRNA-seq data normalization tool based on negative binomial regression.
DOI: 10.5281/zenodo.5335937
title: Data for dynDeepDRIM evaluation

description: The data is for evaluating dynDeepDRIM https://github.com/yuxu-1/dynDeepDRIM and repeating the experiment in the related manuscript. The raw time-course single-cell RNA-seq data are from Gene Expression Omnibus (GEO) and ArrayExpress. Accession numbers: GSE79578 (mESC1), GSE65525 (mESC2), E-MTAB-3929 (hESC1), GSE75748(hESC2), GSE104158 (Mouse brain cortex). The simulation datasets (sim1, sim2, sim3, and sim4) were generated by dyngen, a scRNA-seq data simulator. These gene expression datasets were normalized by sctransform, a scRNA-seq data normalization tool based on negative binomial regression.
DOI: 10.3886/e130366
title: Date and code for: Dynamics of Markups, Concentration and Product Span

description: These files contain the programs and data for the journal article "Dynamics of Markups, Concentration and Product Span," American Economic Journal: Macroeconomics.
DOI: 10.3886/e130366v1
title: Date and code for: Dynamics of Markups, Concentration and Product Span

description: These files contain the programs and data for the journal article "Dynamics of Markups, Concentration and Product Span," American Economic Journal: Macroeconomics.