cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14272/grwxndhdqxreiu-kjevskrmsa-m/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C24H24N.HI/c1-25-16-14-21(15-17-25)9-13-24-18-22-7-6-19-2-4-20(5-3-19)8-11-23(24)12-10-22;/h2-5,9-10,12-18H,6-8,11H2,1H3;1H/q+1;/p-1/b13-9+;

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (101 MHz, DMSO-d6,ppm) δ = 153.28 (Cquat., CAr), 145.37 (+, 2C, CH, CPy), 141.51 (Cquat., CAr), 140.67 (Cquat., CAr), 139.55 (Cquat., CAr), 139.38 (Cquat., CAr), 138.85 (+, CH, C=C), 135.83 (Cquat., CAr), 135.66 (+, CH, CAr), 134.98 (+, CH, CAr), 133.53 (+, CH, CAr), 133.43 (+, CH, CAr), 132.14 (+, CH, CAr), 131.37 (+, CH, CAr), 130.67 (+, CH, CAr), 124.12 (+, 2C, CH, CPy), 123.89 (+, CH, C=C), 47.32 (+, CH3), 35.27 (-, CH2), 35.18 (-, CH2), 34.98 (-, CH2), 33.61 (-, CH2).
DOI: 10.14272/grwxndhdqxreiu-kjevskrmsa-m/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C24H24N.HI/c1-25-16-14-21(15-17-25)9-13-24-18-22-7-6-19-2-4-20(5-3-19)8-11-23(24)12-10-22;/h2-5,9-10,12-18H,6-8,11H2,1H3;1H/q+1;/p-1/b13-9+;

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, DMSO-d6) δ = 8.87 (d, J = 6.5 Hz, 2H, HPY), 8.38 (d, J = 6.6 Hz, 2H, HPY), 7.96 (d, J = 16.1 Hz, 1H, CH=CH), 7.30 (d, J = 16.1 Hz, 1H, CH=CH), 6.96 (d, J = 1.7 Hz, 1H, HAr), 6.63 (dd, J = 7.8, J = 1.7 Hz, 1H, HAr), 6.59–6.52 (m, 3H, HAr), 6.45 (d, J = 1.1 Hz, 2H, HAr), 4.28 (s, 3H, CH3), 3.84–3.72 (m, 1H, HPC), 3.13–3.07 (m, 3H, HPC), 3.04–2.97 (m, 3H, HPC), 2.93–2.88 (m, 1H, HPC).
DOI: 10.14272/grwxndhdqxreiu-kjevskrmsa-m/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C24H24N.HI/c1-25-16-14-21(15-17-25)9-13-24-18-22-7-6-19-2-4-20(5-3-19)8-11-23(24)12-10-22;/h2-5,9-10,12-18H,6-8,11H2,1H3;1H/q+1;/p-1/b13-9+;

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ): 3009, 2922, 2871, 2850, 1639, 1612, 1587, 1564, 1514, 1500, 1480, 1468, 1449, 1319, 1208, 1183, 1154, 1143, 1118, 1101, 1082, 1050, 963, 936, 901, 885, 868, 819, 798, 728, 717, 642, 615, 582, 520, 506, 489, 470, 465, 453, 446, 428, 419, 401, 392, 384, 375 cm–1.
DOI: 10.14272/grwxndhdqxreiu-kjevskrmsa-m/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C24H24N.HI/c1-25-16-14-21(15-17-25)9-13-24-18-22-7-6-19-2-4-20(5-3-19)8-11-23(24)12-10-22;/h2-5,9-10,12-18H,6-8,11H2,1H3;1H/q+1;/p-1/b13-9+;

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 70 °C): 326.3 (100) [M-I]+, 326 (100), 327 (25); HRMS–EI (m/z): [M]+ calcd for C24H24N, 326.1903; found, 326.1909.
DOI: 10.18739/a27d2q83z
title: Collaborative Research: Community based permafrost and climate monitoring in rural Alaska. Ground temperature records, 2016-2019

description: The overarching goal of this project is to help the tribal communities of Upper Kuskokwim region take the lead in assessing and responding to the environmental changes that are coming with warming climate and thawing permafrost. Alaska's land, water, plants, wildlife, and seasons are undergoing a great upheaval, and its people, especially the tribal communities living in remote villages are directly and severely impacted by these changes. The project will help build the tribal capacity to monitor changes in local climate and permafrost by providing the Tribes the scientific knowledge and skills necessary to acquire, analyze, and interpret scientific data through training and education. The project will establish local climate and permafrost observation system and map land cover and permafrost in the Upper Kuskokwim region. It will also develop a geo-hazard map for the region to facilitate safe subsistence and recreational practices and land use. The data set contains the records of ground temperature in 2016-2019 at the 22 observation points.
DOI: 10.18739/a23n20f83
title: Active layer thickness in the watershed of the Yukon River (Indigenous Observation Network), 2020.

description: The dataset presents results of measurements of the thickness of the active layer (ALT) as a part of a continuation of the Indigenous Observing Network (ION) project (ION 2.0) led by the Yukon River Intertribal Watershed Council (YRITWC) in partnership with the University of Alaska-Fairbanks. ION 2.0 continues the measurements of water quality constituents and expands the observation and monitoring program to include measurements of changes in the state of permafrost due to dynamics of the ALT at numerous of the long-term water quality monitoring sites at the communities along the Yukon River. The ION project has documented the long-term changes in major ion chemistry that have occurred over three decades throughout the Yukon River Watershed. The investigators have interpreted these changes as being driven by thawing of discontinuous permafrost throughout this large Arctic watershed and complementary measurements of the active layer will support further interpretation and modelling. This project involves significant co-production of knowledge with members of Indigenous communities and capacity building through training in sampling methods, and sample and data analysis.
DOI: 10.5281/zenodo.4780365
title: Genetic variation in Tertiary relics: the case of eastern-Mediterranean Abies (Pinaceae)

description: The eastern-Mediterranean Abies taxa, which include both widely distributed species and taxa with minuscule ranges, represent a good model to study the impacts of range size and fragmentation on the levels of genetic diversity and differentiation. To assess the patterns of genetic diversity and phylogenetic relationships among eastern-Mediterranean Abies taxa, genetic variation was assessed by 8 nuclear microsatellite loci in 52 populations of Abies taxa with a focus on those distributed in Turkey and the Caucasus. Both at the population and the taxon level, the subspecies or regional populations of A. nordmanniana s.l. exhibited generally higher allelic richness, private allelic richness and expected heterozygosity compared to A. cilicica s.l. Results of both the STRUCTURE analysis and distance-based approaches showed a strong differentiation of the two A. cilicica subspecies from the rest as well as from each other, whereas the subspecies of A. nordmanniana were distinct but less differentiated. ABC simulations were run for a set of scenarios of phylogeny and past demographic changes. For A. ×olcayana the simulation gave a poor support for the hypothesis of being a taxon resulting from a past hybridization, the same is true for A. equi-trojani: both they represent evolutionary branches of A. bornmuelleriana.
DOI: 10.5281/zenodo.4780364
title: Genetic variation in Tertiary relics: the case of eastern-Mediterranean Abies (Pinaceae)

description: The eastern-Mediterranean Abies taxa, which include both widely distributed species and taxa with minuscule ranges, represent a good model to study the impacts of range size and fragmentation on the levels of genetic diversity and differentiation. To assess the patterns of genetic diversity and phylogenetic relationships among eastern-Mediterranean Abies taxa, genetic variation was assessed by 8 nuclear microsatellite loci in 52 populations of Abies taxa with a focus on those distributed in Turkey and the Caucasus. Both at the population and the taxon level, the subspecies or regional populations of A. nordmanniana s.l. exhibited generally higher allelic richness, private allelic richness and expected heterozygosity compared to A. cilicica s.l. Results of both the STRUCTURE analysis and distance-based approaches showed a strong differentiation of the two A. cilicica subspecies from the rest as well as from each other, whereas the subspecies of A. nordmanniana were distinct but less differentiated. ABC simulations were run for a set of scenarios of phylogeny and past demographic changes. For A. ×olcayana the simulation gave a poor support for the hypothesis of being a taxon resulting from a past hybridization, the same is true for A. equi-trojani: both they represent evolutionary branches of A. bornmuelleriana.
DOI: 10.25390/caryinstitute.13721254
title: Supplementary File 2 - Fischhoff et al. 2021

description: A file showing each species-country for species above a predicted zoonotic capacity score of 0.5. The pairing of species to country is based on IUCN Red List polygons. For each row, columns represent the country, species name, whether they are in the top 10% of our predictions, whether this particular species-country pair intersects with available artificial terrestrial habitat (and the species is known to be found in such habitats), whether this species-country pair overlaps a region with 100,000 cumulative human SARS-CoV-2 cases (as of 17 May 2021), and whether this species is found in one or more of the panels in Figure 6 of the main text.
DOI: 10.25390/caryinstitute.13721254.v3
title: Supplementary File 2 - Fischhoff et al. 2021

description: A file showing each species-country for species above a predicted zoonotic capacity score of 0.5. The pairing of species to country is based on IUCN Red List polygons. For each row, columns represent the country, species name, whether they are in the top 10% of our predictions, whether this particular species-country pair intersects with available artificial terrestrial habitat (and the species is known to be found in such habitats), whether this species-country pair overlaps a region with 100,000 cumulative human SARS-CoV-2 cases (as of 17 May 2021), and whether this species is found in one or more of the panels in Figure 6 of the main text.
DOI: 10.25390/caryinstitute.13721254.v2
title: Supplementary File 2 - Fischhoff et al. 2021

description: A file showing each species-country for species above a predicted zoonotic capacity score of 0.5. The pairing of species to country is based on IUCN Red List polygons. For each row, columns represent the country, species name, whether they are in the top 10% of our predictions, whether this particular species-country pair intersects with available artificial terrestrial habitat (and the species is known to be found in such habitats), whether this species-country pair overlaps a region with 100,000 cumulative human SARS-CoV-2 cases (as of 15 February 2021), and whether this species is found in one or more of the panels in Figure 6 of the main text.
DOI: 10.6084/m9.figshare.14342415.v1
title: Simultaneous determination and dietary risk assessment of clethodim and its metabolites in different fruits and vegetables

description: Clethodim is one of the most widely used herbicides in agriculture and, after field application, is metabolised to several metabolites. The potential toxicological negative effects of these compounds are poorly understood. Thus, recently, within the risk assessment framework, the European Food Safety Authority (EFSA) proposed to include the minor metabolites in the definition of clethodim residue. In this work, an easy to use and reliable UHPLC method coupled with a triple quadrupole MS/MS was developed and validated for the detection and quantification of the herbicide clethodim and related metabolites clethodim sulphone, clethodim sulphoxide, metabolites M17R and M18R in apple, grape, olive and rice. The five analytes were extracted by using a modified QuEChERS procedure, while the active ingredients were determined in multiple reaction monitoring (MRM) ion-switching mode. The proposed method showed calibration curve linearity with r<sup>2</sup> ≥ 0.990 for all active ingredients (a.is.) both in solvent and matrix extracts. Limits of quantitation (LOQ) of the five compounds ranged from 9.44 µg/kg for M17R in olive extract to 11.01 µg/kg for clethodim in apple extract. Recoveries values ranged from 86% to 119% at two concentration levels (LOQ and 10xLOQ), while the intraday and interday precisions of the method were both below 10% in all cases. The method was successfully used for the quantification of the five a.is. in different food matrices. Furthermore, chronic dietary risk was investigated using a hazard quotients (HQ) method based on European dietary habits. The chronic dietary exposure risk quotients ranged from 1.0 × 10<sup>−5</sup> (lower bound scenario) to 2.7 × 10<sup>−4</sup> (upper bound scenario) which were significantly lower than 1. Data obtained indicate that the dietary exposure risks were acceptable for clethodim and its major and minor metabolites applied in apple, table grape, rice and table olive.
DOI: 10.6084/m9.figshare.13873693
title: An updated estimate of benzoate intakes from non-alcoholic beverages in Canada and the United States

description: In 2017, the results of a comprehensive assessment of intake for benzoic acid and its salts from non-alcoholic beverages were published for four regions (Brazil, Canada, Mexico, and the United States [U.S.]). These regions were among those identified as having the most prevalent use of benzoates in beverages globally. The results of the 2017 study did not indicate a safety concern relative to the acceptable daily intake (ADI) established for benzoates (5 mg kg body weight<sup>-1</sup> day<sup>−1</sup>, as benzoic acid), and supported maintaining the Codex maximum benzoate level in water-based beverages (250 mg kg<sup>−1</sup>). Since this time, population-specific food consumption data have been released for public use for Canada, and updated beverage consumption data have become available for the U.S. To ensure estimated intakes remain relevant, these consumption data were incorporated with previously collected brand-specific benzoate use level and market volume data for beverages. Dietary exposure to benzoates from non-alcoholic beverages was assessed using statistical modelling, either probabilistic (non-brand loyal; considering the full distribution of use levels) or deterministic (brand loyal; assuming all regular carbonated soft drinks, the brand loyal beverage type, contain benzoates at the maximum use level, and all other beverage types in which benzoates are used contain benzoates at the market-weighted average use level). In both models, estimated daily intakes at the mean and 95<sup>th</sup> percentile were below the ADI (≤76% of the ADI) in all Canadian and U.S. population groups with a statistically reliable population size. The findings from updated Canadian and U.S. consumption data continue to support the Codex maximum benzoate level in water-based flavoured drinks at 250 mg kg<sup>−1</sup>.
DOI: 10.6084/m9.figshare.14342415
title: Simultaneous determination and dietary risk assessment of clethodim and its metabolites in different fruits and vegetables

description: Clethodim is one of the most widely used herbicides in agriculture and, after field application, is metabolised to several metabolites. The potential toxicological negative effects of these compounds are poorly understood. Thus, recently, within the risk assessment framework, the European Food Safety Authority (EFSA) proposed to include the minor metabolites in the definition of clethodim residue. In this work, an easy to use and reliable UHPLC method coupled with a triple quadrupole MS/MS was developed and validated for the detection and quantification of the herbicide clethodim and related metabolites clethodim sulphone, clethodim sulphoxide, metabolites M17R and M18R in apple, grape, olive and rice. The five analytes were extracted by using a modified QuEChERS procedure, while the active ingredients were determined in multiple reaction monitoring (MRM) ion-switching mode. The proposed method showed calibration curve linearity with r<sup>2</sup> ≥ 0.990 for all active ingredients (a.is.) both in solvent and matrix extracts. Limits of quantitation (LOQ) of the five compounds ranged from 9.44 µg/kg for M17R in olive extract to 11.01 µg/kg for clethodim in apple extract. Recoveries values ranged from 86% to 119% at two concentration levels (LOQ and 10xLOQ), while the intraday and interday precisions of the method were both below 10% in all cases. The method was successfully used for the quantification of the five a.is. in different food matrices. Furthermore, chronic dietary risk was investigated using a hazard quotients (HQ) method based on European dietary habits. The chronic dietary exposure risk quotients ranged from 1.0 × 10<sup>−5</sup> (lower bound scenario) to 2.7 × 10<sup>−4</sup> (upper bound scenario) which were significantly lower than 1. Data obtained indicate that the dietary exposure risks were acceptable for clethodim and its major and minor metabolites applied in apple, table grape, rice and table olive.
DOI: 10.6084/m9.figshare.13873693.v1
title: An updated estimate of benzoate intakes from non-alcoholic beverages in Canada and the United States

description: In 2017, the results of a comprehensive assessment of intake for benzoic acid and its salts from non-alcoholic beverages were published for four regions (Brazil, Canada, Mexico, and the United States [U.S.]). These regions were among those identified as having the most prevalent use of benzoates in beverages globally. The results of the 2017 study did not indicate a safety concern relative to the acceptable daily intake (ADI) established for benzoates (5 mg kg body weight<sup>-1</sup> day<sup>−1</sup>, as benzoic acid), and supported maintaining the Codex maximum benzoate level in water-based beverages (250 mg kg<sup>−1</sup>). Since this time, population-specific food consumption data have been released for public use for Canada, and updated beverage consumption data have become available for the U.S. To ensure estimated intakes remain relevant, these consumption data were incorporated with previously collected brand-specific benzoate use level and market volume data for beverages. Dietary exposure to benzoates from non-alcoholic beverages was assessed using statistical modelling, either probabilistic (non-brand loyal; considering the full distribution of use levels) or deterministic (brand loyal; assuming all regular carbonated soft drinks, the brand loyal beverage type, contain benzoates at the maximum use level, and all other beverage types in which benzoates are used contain benzoates at the market-weighted average use level). In both models, estimated daily intakes at the mean and 95<sup>th</sup> percentile were below the ADI (≤76% of the ADI) in all Canadian and U.S. population groups with a statistically reliable population size. The findings from updated Canadian and U.S. consumption data continue to support the Codex maximum benzoate level in water-based flavoured drinks at 250 mg kg<sup>−1</sup>.
DOI: 10.6084/m9.figshare.14292509
title: Validation of two UHPLC-MS/MS methods for fast and reliable determination of quinolone residues in honey

description: Antibiotic usage for beekeeping, including quinolones, can lead to residues in honey and these residues usually result from the drugs used in the treatment of American or European foulbrood diseases. Residues in honey may cause allergic reactions as well as increased antibiotic resistance. Within this study, rapid and breakthrough analysis methods were developed using UHPLC-ESI-MS/MS and sample preparation processes were minimised. Practical, low cost, time-effective analysis was provided utilising ‘dilute & shoot’ methodology and a QuEChERS-based procedure has been developed alternatively for improved sensitivity. Recovery values were 85%-112% for the ‘dilute & shoot’ method, and 82%-117% for the modified QuEChERS method. For accuracy studies, RSD% values were between 0.7% and 13.4% for both methods in intra-day and inter-day precision studies. CCα (1.1 μg/kg and 0.6 μg/kg) and CCβ (1.2 μg/kg and 0.6 μg/kg) mean values were calculated for the ‘dilute & shoot’ and QuEChERS method, respectively. These novel methods achieved simultaneous quantification of 21 quinolones in 7 min with high specificity and were used to analyse 50 honey samples. Quinolone residues were found in samples, and enrofloxacin, danofloxacin, pipemidic acid, lomefloxacin, cinoxacin, and ciprofloxacin were quantified.
DOI: 10.6084/m9.figshare.14292509.v1
title: Validation of two UHPLC-MS/MS methods for fast and reliable determination of quinolone residues in honey

description: Antibiotic usage for beekeeping, including quinolones, can lead to residues in honey and these residues usually result from the drugs used in the treatment of American or European foulbrood diseases. Residues in honey may cause allergic reactions as well as increased antibiotic resistance. Within this study, rapid and breakthrough analysis methods were developed using UHPLC-ESI-MS/MS and sample preparation processes were minimised. Practical, low cost, time-effective analysis was provided utilising ‘dilute & shoot’ methodology and a QuEChERS-based procedure has been developed alternatively for improved sensitivity. Recovery values were 85%-112% for the ‘dilute & shoot’ method, and 82%-117% for the modified QuEChERS method. For accuracy studies, RSD% values were between 0.7% and 13.4% for both methods in intra-day and inter-day precision studies. CCα (1.1 μg/kg and 0.6 μg/kg) and CCβ (1.2 μg/kg and 0.6 μg/kg) mean values were calculated for the ‘dilute & shoot’ and QuEChERS method, respectively. These novel methods achieved simultaneous quantification of 21 quinolones in 7 min with high specificity and were used to analyse 50 honey samples. Quinolone residues were found in samples, and enrofloxacin, danofloxacin, pipemidic acid, lomefloxacin, cinoxacin, and ciprofloxacin were quantified.
DOI: 10.5066/p9cjvpoi
title: Fire Clay Coal Zone Point Data (Chemistry) in Kentucky, Virginia and West Virginia

description: This dataset (located by latitude and longitude) is a subset of the geochemical dataset found in Chap. F, Appendix 7, Disc 1, and used in this study of the Fire Clay coal zone. That dataset is a compilation of data from the U.S. Geological Survey's (USGS) National Coal Resources Data System (NCRDS) USCHEM (U.S. geoCHEMical), and the Kentucky Geological Survey (KGS) Kentucky Coal Resources Information System (KCRIS) databases. The metadata file for the complete dataset is found in Chap. F, Appendix 8, Disc 1 (please see it for more detailed information on this geochemical dataset). This subset of the geochemical data for the Fire Clay coal zone includes ash yield, sulfur content, SO2 value, gross calorific value, arsenic content and mercury content for these records, as well as the ranking of these values, which is described later under the attributes in this metadata file. Analytical techniques are described in the references in Chap. F, Appendix 9, Disc 1. The analytical data are stored as text fields because many of the parameters contain letter qualifiers appearing after the numerical data values. The following is a list of the possible qualifier values: L - less than, G - greater than, N - not detected, or H - interference that cannot be easily resolved. Not all of these codes may be in this database.
DOI: 10.5066/p9oghf9y
title: Fire Clay Coal Zone County Statistics (Chemistry) in Kentucky, West Virginia, and Virginia

description: This dataset is a polygon coverage of counties limited to the extent of the Fire Clay coal zone resource areas and attributed with statistics on these coal quality parameters: ash yield (percent), sulfur (percent), SO2 (lbs per million Btu), calorific value (Btu/lb), arsenic (ppm) content and mercury (ppm) content. The file has been generalized from detailed geologic coverages found elsewhere in Professional Paper 1625-C. The attributes were generated from public data found in the geochemical dataset found in Chap. F, Appendix 7, Disc 1. Please see the metadata file found in Chap. F, Appendix 8, Disc 1, for more detailed information on the geochemical attributes. The county statistical data used for this data set are found in Tables 2-5 and 17-18, Chap. F, Disc 1. Additional county geochemical statistics for other parameters are found in Tables 6-16, Chap. F, Disc 1.