cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr21_20160613.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Rocky Point, Oregon, USA (RKPX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Rocky Point, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-06-13. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/rkpx00_xxxibtnxmbr22_20160506.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Rocky Point, Oregon, USA (RKPX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Rocky Point, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-05-06. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/shlx00_xxxibtnxmbr11_20170515.40.1
title: (:unkn)
DOI: 10.6085/aa/shlx00_xxxibtnxmbr11_20170515.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Strawberry Hill, Oregon, USA (SHLX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Strawberry Hill, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2017-05-15. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/shlx00_xxxibtnxmbr12_20160506.40.1
title: (:unkn)
DOI: 10.6085/aa/shlx00_xxxibtnxmbr12_20160506.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Strawberry Hill, Oregon, USA (SHLX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Strawberry Hill, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-05-06. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/shlx00_xxxibtnxmbr12_20170429.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Strawberry Hill, Oregon, USA (SHLX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Strawberry Hill, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2017-04-29. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/shlx00_xxxibtnxmbr21_20160506.40.1
title: (:unkn)
DOI: 10.6085/aa/shlx00_xxxibtnxmbr21_20160506.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Strawberry Hill, Oregon, USA (SHLX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Strawberry Hill, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-05-06. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/shlx00_xxxibtnxmbr22_20160613.40.1
title: (:unkn)
DOI: 10.6085/aa/shlx00_xxxibtnxmbr22_20160613.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Strawberry Hill, Oregon, USA (SHLX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Strawberry Hill, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2016-06-13. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.6085/aa/ybhx00_xxxibtnxmbr11_20150805.40.1
title: (:unkn)
DOI: 10.6085/aa/ybhx00_xxxibtnxmbr11_20150805.50.1
title: PISCO: Intertidal: bionic mussel temperature data: Yachats Beach, Oregon, USA (YBHX00)

description: This metadata record describes a mix of intertidal seawater and air temperature data collected at Yachats Beach, Oregon, USA by PISCO. Measurements were collected using micro-T Temperature Logger (NexSens DS1921G) beginning 2015-08-05. Bionic mussel temperature loggers are contained within an artificial mussel in the middle of the mussel bed. There are typically two replicates with two loggers within each replicate. These are distinguished in the file name as follows: R11 - replicate 1, 1st logger; R12 - replicate 1, 2nd logger; R21 - replicate 2, 1st logger; R22 - replicate 2, 2nd logger. Temperature is recorded at 60.0 minute intervals.
DOI: 10.25606/surf.578c6039-33b7ddf5
title: The Cosmogrid Simulation: Statistical Properties of Small Dark Matter Halos (2048-009)

description: We present the results of the "Cosmogrid" cosmological N-body simulation suites based on the concordance LCDM model. The Cosmogrid simulation was performed in a 30 Mpc box with 2048³ particles. The mass of each particle is 1.28x10^5 Msun, which is sufficient to resolve ultra-faint dwarfs. We found that the halo mass function shows good agreement with the Sheth & Tormen fitting function down to ~10^7 Msun. We have analyzed the spherically averaged density profiles of the three most massive halos which are of galaxy group size and contain at least 170 million particles. The slopes of these density profiles become shallower than -1 at the inner most radius. We also find a clear correlation of halo concentration with mass. The mass dependence of the concentration parameter cannot be expressed by a single power law, however a simple model based on the Press-Schechter theory proposed by Navarro et al. gives reasonable agreement with this dependence. The spin parameter does not show a correlation with the halo mass. The probability distribution functions for both concentration and spin are well fitted by the log-normal distribution for halos with the masses larger than ~10^8 Msun. The subhalo abundance depends on the halo mass. Galaxy-sized halos have 50% more subhalos than ~10^11 Msun halos have. This is snapshot 009 of the 2048³ resolution collection.
DOI: 10.5281/zenodo.1493848
title: Supplemental material to 'Evaluation of force-based and displacement-based out-of-plane seismic assessment methods for unreinforced masonry walls through refined model simulations'

description: This repository contains the results of discrete element simulations used to study the response of vertically-spanning unreinforced masonry walls under different wall configurations. The simulations are run using the software package UDEC 6.0 (Itasca). The dataset has served as basis for the study conducted in the following paper:


Godio M, Beyer K. Evaluation of force-based and displacement-based out-of-plane seismic assessmentmethods for unreinforced masonrywalls through refined model simulations. Earthquake Engng Struct Dyn. 2019;48:454-475. DOI:10.1002/eqe.3144


Version history:<br>
V1: datasets '01_UDEC_VALIDATION' and '02_UDEC_RESULTS are added<br>
V2: minor modifications to the datasets: deletion of unwanted temporary files from the datasets<br>
V3: '00_CONTENT' PDF-file is added
DOI: 10.21223/p3/jgbgz0
title: Replication data for: Cryopreserved potato shoot tips showed genotype-specific response to sucrose concentration in rewarming solution (RS)

description: In an experiment with 16 clonal potato accessions, the use of RS sucrose concentrations of 0.6 M and 0.9 M showed on average ~ 5% higher recovery rate, compared to the routinely used 1.2 M sucrose concentration, suggesting that sucrose can be decreased in RS. A screening experiment with a set of 85 genetically diverse potato accessions confirmed this suggestion, and sucrose concentrations of 0.3–0.9 M resulted in significantly higher recovery rates compared to the routinely used 1.2 M sucrose concentration. The genotypic specific response to low (0.0 M) and high RS sucrose concentrations (1.2 M) was variable within species/subspecies and ploidy levels. Interestingly, some genotypes showed high recovery rates of ≥80% even when sucrose was completely removed from the RS. In general, the highest recovery was observed with a RS sucrose concentration of 0.6 M (“best bet”), and therefore CIP’s routine cryopreservation protocol for potato has been changed accordingly (from 1.2 M to 0.6 M RS sucrose concentration). We recommend being cautious in generalizing experimental cryopreservation results obtained with a limited number of accessions to larger collections.
DOI: 10.5281/zenodo.1493268
title: Statistical analysis of chlorate occurrence data in food

description: In accordance with Article 29 (1) (a) of Regulation (EC) No 178/2002, the European Commission asked the European Food Safety Authority (EFSA) in 2014 for a scientific opinion on the risks for human health related to the presence of chlorate in food from all sources, taking also into account its presence in drinking water. The opinion found that “Chronic exposure of adolescent and adult age classes did not exceed the TDI. However, at the 95th percentile the TDI was exceeded in all surveys in ‘Infants’ and ‘Toddlers’ and in some surveys in ‘Other children’. Chronic exposures are of concern in particular in younger age groups with mild or moderate iodine deficiency.” Food manufacturers have started to optimise their manufacturing processes to lower chlorate residue level in foods and the European Commission in 2017 provided a revised Guidance document on good hygiene practices regarding the use of chlorinated disinfectant. It can therefore be expected that chlorate levels in foods are now lower compared with the levels found in the samples from 2011 to 2014. The European Commission (EC) requested EFSA in 2018 to provide an updated statistical analysis on chlorate occurrence levels in foods. A set of 14 Excel tables containing the statistical analysis of reported results for the analysis of chlorates from pesticides monitoring and contaminants monitoring programmes have been prepared. The data is presented at three levels of aggregation using FoodEx product categories. Analysis was performed for two time points, the 2011-2017 dataset contained 15,741 valid results and the 2015-2017 dataset contained 28,033 valid results. Mean, median and percentile (75th, 90th, 95th) for lower bound, middle bound and upper bound concentration values were calculated. Caution should be applied to percentile values calculated from a limited number of results.
description: EU; XLSX; data.collection@efsa.europa.eu
description: {"references": ["EFSA, 2015, Risks for public health related to the presence of chlorate in food, EFSA Journal 2015;13(6):4135, doi: 10.2903 j.efsa.2015.4135", "Commission notice on guidance document on addressing microbiological risks in fresh fruits and vegetables at primary production through good hygiene, OJ C 163, 23.5.2017, p. 1", "General SSD guidance: EFSA Journal 2010; 8(1):1457 doi: 10.2903", "Official catalogues of SSD controlled terminologies: DOI 10.5281/zenodo.1163629", "Reporting data on pesticide residues in food and feed according to Regulation (EC) No 396/2005 (2016 data collection) - EFSA Journal 2017;15(5):4792 - DOI: 10.2903", "Reporting data on pesticide residues in food and feed according to Regulation (EC) No 396/2005 (2015 data collection) EFSA Journal 2016;14(5):4496 - DOI: 10.2903", "Reporting data on pesticide residues in food and feed according to Regulation (EC) No 396/2005 (2014 data collection) - EFSA Journal 2015;13(7):4195 - - DOI: 10.2903"]}
DOI: 10.5281/zenodo.1493269
title: Statistical analysis of chlorate occurrence data in food

description: In accordance with Article 29 (1) (a) of Regulation (EC) No 178/2002, the European Commission asked the European Food Safety Authority (EFSA) in 2014 for a scientific opinion on the risks for human health related to the presence of chlorate in food from all sources, taking also into account its presence in drinking water. The opinion found that “Chronic exposure of adolescent and adult age classes did not exceed the TDI. However, at the 95th percentile the TDI was exceeded in all surveys in ‘Infants’ and ‘Toddlers’ and in some surveys in ‘Other children’. Chronic exposures are of concern in particular in younger age groups with mild or moderate iodine deficiency.” Food manufacturers have started to optimise their manufacturing processes to lower chlorate residue level in foods and the European Commission in 2017 provided a revised Guidance document on good hygiene practices regarding the use of chlorinated disinfectant. It can therefore be expected that chlorate levels in foods are now lower compared with the levels found in the samples from 2011 to 2014. The European Commission (EC) requested EFSA in 2018 to provide an updated statistical analysis on chlorate occurrence levels in foods. A set of 14 Excel tables containing the statistical analysis of reported results for the analysis of chlorates from pesticides monitoring and contaminants monitoring programmes have been prepared. The data is presented at three levels of aggregation using FoodEx product categories. Analysis was performed for two time points, the 2011-2017 dataset contained 15,741 valid results and the 2015-2017 dataset contained 28,033 valid results. Mean, median and percentile (75th, 90th, 95th) for lower bound, middle bound and upper bound concentration values were calculated. Caution should be applied to percentile values calculated from a limited number of results.
description: EU; XLSX; data.collection@efsa.europa.eu
description: {"references": ["EFSA, 2015, Risks for public health related to the presence of chlorate in food, EFSA Journal 2015;13(6):4135, doi: 10.2903 j.efsa.2015.4135", "Commission notice on guidance document on addressing microbiological risks in fresh fruits and vegetables at primary production through good hygiene, OJ C 163, 23.5.2017, p. 1", "General SSD guidance: EFSA Journal 2010; 8(1):1457 doi: 10.2903", "Official catalogues of SSD controlled terminologies: DOI 10.5281/zenodo.1163629", "Reporting data on pesticide residues in food and feed according to Regulation (EC) No 396/2005 (2016 data collection) - EFSA Journal 2017;15(5):4792 - DOI: 10.2903", "Reporting data on pesticide residues in food and feed according to Regulation (EC) No 396/2005 (2015 data collection) EFSA Journal 2016;14(5):4496 - DOI: 10.2903", "Reporting data on pesticide residues in food and feed according to Regulation (EC) No 396/2005 (2014 data collection) - EFSA Journal 2015;13(7):4195 - - DOI: 10.2903"]}
DOI: 10.26195/5bf790bd1b6a0
title: Network TimeServer Dataset 2016-2017
DOI: 10.14469/hpc/4813
title: peracid epoxidation of aminoethene, Reactant -438.079532

description: Gaussian Calculation
DOI: 10.5281/zenodo.1494961
title: Bodhgayā : working list of inscriptions from the site.

description: Bodhgayā : working list of inscriptions from the site.
DOI: 10.5281/zenodo.1494962
title: Bodhgayā : working list of inscriptions from the site.

description: Bodhgayā : working list of inscriptions from the site.
DOI: 10.5281/zenodo.1495060
title: Simulation data files of the article: "The dimming of RW Auriga. Is dust accretion preceding an outburst?"

description: We make available here the simulation output files used in the paper "The dimming of RW Auriga. Is dust accretion preceding an outburst?" by Gárate et al. (2019). The simulation shows the gas and dust evolution of a protoplanetry disk in the event of a dead zone reactivation. The simulations were performed using DustPy (Stammler & Birnstiel, in prep.) to solve the advection of gas and dust, along with the coagulation and fragmentation of multiple dust species. Each folder corresponds to one of the simulation sets presented in the article, with the "CORE" identifier corresponding to the fiducial parameters. Each datafile corresponds to one snapshot of a simulation, with the data0000.hdf5 being the disk conditions at the moment of the dead zone reactivation. The simulation data is saved in hdf5 format. We include the jupyter notebook as a guide of how to read and plot the simulation files. Additional comments about each simulation are included in the notebook.
DOI: 10.5281/zenodo.1495061
title: Simulation data files of the article: "The dimming of RW Auriga. Is dust accretion preceding an outburst?"

description: We make available here the simulation output files used in the paper "The dimming of RW Auriga. Is dust accretion preceding an outburst?" by Gárate et al. (2019). The simulation shows the gas and dust evolution of a protoplanetry disk in the event of a dead zone reactivation. The simulations were performed using DustPy (Stammler & Birnstiel, in prep.) to solve the advection of gas and dust, along with the coagulation and fragmentation of multiple dust species. Each folder corresponds to one of the simulation sets presented in the article, with the "CORE" identifier corresponding to the fiducial parameters. Each datafile corresponds to one snapshot of a simulation, with the data0000.hdf5 being the disk conditions at the moment of the dead zone reactivation. The simulation data is saved in hdf5 format. We include the jupyter notebook as a guide of how to read and plot the simulation files. Additional comments about each simulation are included in the notebook.
DOI: 10.15129/ac8c0e36-72d3-4156-9fbe-e60293e33a72
title: Data for: "Development of a novel continuous filtration unit for pharmaceutical process development and manufacturing"

description: Dataset related to paper Development of a novel continuous filtration unit for pharmaceutical process development and manufacturing (https://doi.org/10.1016/j.xphs.2018.07.005) and for the proceeding of the Filtech 2016 conference. This dataset comprises of one zip file which contains a number of folders containing spreadsheets, images text supporting experiments.
DOI: 10.21223/p3/68iis3
title: Dataset for: Baseline Survey for the OFDA 2016 Mitigating Drought Impacts on Livelihoods in Mozambique through Resilient, Nutritious Sweetpotato Project in the South of Mozambique

description: This dataset was carried out as the baseline survey for the Mitigating Drought Impacts in Southern Mozambique Through Resilient, Nutritious Sweet potato Project that has been implemented in 13 districts in the southern of Mozambique, namely Matutuine, Boane, Moamba, and Magude in Maputo province, Guija, Mabalane, Massangena, Chigubo, Chiculalacuala, and Mapai in Gaza province, and Funhalouro, Mabote and Govuro in Inhambane province.Primary data of about 1,200 households were collected in all 13 project target districts. The sample size was estimated using the multistage sampling method. Overall, most of the household demographics were consistent with the findings from the household budget survey 2014/15 carried out by INE in the targeted areas. The number of household members was on average 5. Almost 58% of the households visited during this exercise had a child under 5 years, with an average of two years. The average age of the household heads was 50 years, and most of them had a third-grade education level. Overall, while about 36% of the household heads were women, almost 50% of the household members were female. The recurrent and extreme events such as floods, droughts, cyclones, extreme temperatures and others are generally the causes of the disruptions of the local cropping systems and in the end food and nutrition insecurity in most of the regions in Mozambique. To better continue to understand and build resilience to these drought related events, some of the climate change related events were evaluated. Overall, 79% of the respondents directly faced droughts related effects at least once in the last five years, 11% already faced the cyclones, and 10% were affected by floods. The districts Mabote (97%), Funhalouro (90%), Massangena (89%), and Chicualacuala (86%) had highest proportion of respondents who have suffered from droughts effects in the last five years. About 22% and 20% of respondents faced floods in Chigubo and Mabalane respectively. Moamba presented relatively higher proportion (17%) of respondents who also were affected by cyclones. In relation to the damage and effects caused by droughts, almost 44% of the respondents mentioned the loss of their crops, about 28% had their fields destroyed, and nearly 23% had lost their animals by death. Matutuine presented highest proportion of respondents with the crop loss (53%), while Boane had the highest proportion of the respondents with fields destroyed (45%). The district of Chigubo had the highest proportion of animals’ death (31%).