cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc288qcn
title: CCDC 2093751: Experimental Crystal Structure Determination

description: Related Article: Ming-Xing Zhang, Xiaofei Yang, Fen Tan, Xiaowen Ou, Guoping Zeng, Didi Chen, Zhiqiang Xu, Sheng Hua Liu|2022|Dyes Pigm.|204|110420|doi:10.1016/j.dyepig.2022.110420
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28hl6l
title: CCDC 2100349: Experimental Crystal Structure Determination

description: Related Article: Xue-Feng Bao, Pei-Hong Cao, Jin Zeng, Luo-Min Xiao, Zhi-Hui Luo, Jian Zou, Chuan-Xi Wang, Zhong-Xiang Zhao, Zheng-Qun Zhou, Hui Zhi, Hao Gao|2022|Phytochemistry|200|113249|doi:10.1016/j.phytochem.2022.113249
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.34740/kaggle/dsv/3747404
title: pair_model
DOI: 10.6084/m9.figshare.20000690.v2
title: Schima barcoding analyses

description: The folder includes alignment matrixes and phylogenetic trees.
DOI: 10.6084/m9.figshare.20001701
title: Honey endotoxin

description: The data set is for a manuscript that examined the secretory effect of Australian honey on interleukin-6 secretion by cultured fibroblasts, and endotoxin levels in honey samples.
DOI: 10.5281/zenodo.6615021
title: Ozone dry deposition and ozone fields modeled by WRF-Chem

description: This dataset includes hourly ozone dry deposition velocity v<sub>d</sub> and surface ozone concentration fields over the southeastern US in August 2016, which are simulated by the NASA Land Information System/Weather Research and Forecasting model with online Chemistry, without and with the assimilation of soil moisture retrievals from NASA’s Soil Moisture Active Passive mission. Different dry deposition parameterizations are used in this modeling/data assimilation work, as described in "Satellite soil moisture data assimilation impacts on modeling weather variables and ozone in the southeastern US – Part 2: Sensitivity to dry-deposition parameterizations", by Huang et al. (2022). The model grid definition, along with the grid-dominant land use/cover type information, is also supplied. All data are stored in NetCDF files.
description: Related publication: Huang et al.: Satellite soil moisture data assimilation impacts on modeling weather variables and ozone in the southeastern US – Part 2: Sensitivity to dry-deposition parameterizations, Atmospheric Chemistry and Physics, in press, 2022.
DOI: 10.6084/m9.figshare.20001737
title: Lipid metabolism analysis of peripheral blood in patients with alcohol-induced and steroid-induced osteonecrosis of the femoral head

description: To identify potential biomarkers of alcohol-induced and steroid-induced femoral head necrosis by lipidomics.
DOI: 10.6084/m9.figshare.20001737.v1
title: Lipid metabolism analysis of peripheral blood in patients with alcohol-induced and steroid-induced osteonecrosis of the femoral head

description: To identify potential biomarkers of alcohol-induced and steroid-induced femoral head necrosis by lipidomics.
DOI: 10.6084/m9.figshare.19860091
title: China green industrial parks

description: The dataset includes the names and geographic coordinates of the green industrial parks used in the paper <em>Heterogeneity of decoupling between economic development and carbon emission in China's Green Industrial Parks</em>.
DOI: 10.6084/m9.figshare.19860091.v1
title: China green industrial parks

description: The dataset includes the names and geographic coordinates of the green industrial parks used in the paper <em>Heterogeneity of decoupling between economic development and carbon emission in China's Green Industrial Parks</em>.
DOI: 10.34740/kaggle/dsv/3752007
title: BBC News
DOI: 10.34740/kaggle/dsv/3752081
title: Polish-Ukrainian translations from Tatoeba
DOI: 10.34740/kaggle/dsv/3752102
title: Michelin Guide Restaurants 2021
DOI: 10.6084/m9.figshare.19529617
title: Severity of scuffing injury of ‘Zesy002’ kiwifruit as influenced by maturity

description: Kiwifruit (<i>Actinidia chinensis</i> var. chinensis ‘Zesy002’) have a relatively long harvest season, where fruit will change in maturity and hence attributes. Harvest may be followed by a long postharvest storage period. Scuffing is the discolouration of kiwifruit skin in response to an injury. This injury is observed throughout the supply chain to some extent and thus, it is of interest to identify possible reasons that predispose kiwifruit to skin discolouration. In this work, maturity, as influenced by harvest date and estimated by firmness and total soluble solids, was investigated as a potential descriptor of scuffing susceptibility. ‘Zesy002’ kiwifruit were sampled from 11 orchards in New Zealand on three occasions (ISO weeks 12, 18 and 20) during the 2020 harvest season. Upon arrival to the lab, 24 fruit from each grower were non-destructively assessed prior to a deliberately controlled scuffing treatment and subsequently stored for 2 weeks at 0°C, to allow symptom development. Of the at-harvest maturity indicators, firmness was found to be the strongest indicator of scuffing susceptibility and severity of the damage. Further work is required to understand the physical or physiological reasons that cause softer fruit to be more susceptible to scuffing.
DOI: 10.6084/m9.figshare.19529617.v1
title: Severity of scuffing injury of ‘Zesy002’ kiwifruit as influenced by maturity

description: Kiwifruit (<i>Actinidia chinensis</i> var. chinensis ‘Zesy002’) have a relatively long harvest season, where fruit will change in maturity and hence attributes. Harvest may be followed by a long postharvest storage period. Scuffing is the discolouration of kiwifruit skin in response to an injury. This injury is observed throughout the supply chain to some extent and thus, it is of interest to identify possible reasons that predispose kiwifruit to skin discolouration. In this work, maturity, as influenced by harvest date and estimated by firmness and total soluble solids, was investigated as a potential descriptor of scuffing susceptibility. ‘Zesy002’ kiwifruit were sampled from 11 orchards in New Zealand on three occasions (ISO weeks 12, 18 and 20) during the 2020 harvest season. Upon arrival to the lab, 24 fruit from each grower were non-destructively assessed prior to a deliberately controlled scuffing treatment and subsequently stored for 2 weeks at 0°C, to allow symptom development. Of the at-harvest maturity indicators, firmness was found to be the strongest indicator of scuffing susceptibility and severity of the damage. Further work is required to understand the physical or physiological reasons that cause softer fruit to be more susceptible to scuffing.
DOI: 10.34740/kaggle/dsv/3752162
title: Vietnam Highschool Exam 2017 to 2021
DOI: 10.5281/zenodo.4553411
title: Probiotics modulate plant metabolites by conditioning soil microbiome and optimizing plant nutrient stoichiometry

description: This is the dataset for the published paper entitled "<strong>Effects of probiotic consortia on plant metabolites are associated with soil indigenous microbiota and fertilization regimes</strong>" in Industrial Crops and Products.
description: {"references": ["Wang, Z., Chen, Z., Leite, M.F.A., Xu, Z., Lin, Q., Kowalchuk, G.A., Fu, X., Kuramae, E.E., 2022. Effects of probiotic consortia on plant metabolites are associated with soil indigenous microbiota and fertilization regimes. Ind Crop Prod 185, 115138."]}
DOI: 10.5281/zenodo.4553410
title: Probiotics modulate plant metabolites by conditioning soil microbiome and optimizing plant nutrient stoichiometry

description: This is the dataset for the published paper entitled "<strong>Effects of probiotic consortia on plant metabolites are associated with soil indigenous microbiota and fertilization regimes</strong>" in Industrial Crops and Products.
description: {"references": ["Wang, Z., Chen, Z., Leite, M.F.A., Xu, Z., Lin, Q., Kowalchuk, G.A., Fu, X., Kuramae, E.E., 2022. Effects of probiotic consortia on plant metabolites are associated with soil indigenous microbiota and fertilization regimes. Ind Crop Prod 185, 115138."]}
DOI: 10.5281/zenodo.6615717
title: Development of a Multi-Level Dynamic Model to Measure the Resilience Level of Transportation Infrastructure Networks

description: The recent increase in disasters is making the largest critical infrastructure system namely the transportation infrastructure system susceptible to unexpected damage. Discontinuation of services provided by transportation infrastructures will create significant societal, economic, and collateral damages. Therefore, this study aims to identify dimensions to measure the resilience of the transportation infrastructures. This study also aims to develop a model to measure the resilience of the transportation infrastructures resilience. To fulfill the aims of this study, a questionnaire was developed which was supported by a comprehensive literature review. 92 valid responses were received and analyzed qualitatively and quantitatively. Statistically significant variables were used to develop a resilience measurement tool. The developed tool will provide relative resilience measures for multiple projects which will help in identifying the most vulnerable segment of the transportation infrastructure network. Exploratory factor analysis (EFA) was performed to identify the constructs and structural equation modeling (SEM) was used to develop the model. Without previous experience in reconstruction works, handling integrated assets becomes very critical. Also, such inexperience makes it difficult to handle emergency resources properly. However, such issues regarding integrated assets can be resolved by investing in locating integrated assets away from the roadways, so if a break in a railroad crossing or utility line occurs or emergency repairs are needed, the impact on the roadway operations can be minimized. To avoid issues related to access to previous disaster data for the roadway this study suggess investing in preparing an interactive online platform for recording and reviewing data related to disasters as well as previous resilience enhancing activities for the roadway with easy access credentials. The findings of this study will support practitioners and decision-makers in investing in the appropriate resilience enhancement activity project for funding and investment.
description: Tran-SET Project: 20ITSUTA27
DOI: 10.5281/zenodo.6615716
title: Development of a Multi-Level Dynamic Model to Measure the Resilience Level of Transportation Infrastructure Networks

description: The recent increase in disasters is making the largest critical infrastructure system namely the transportation infrastructure system susceptible to unexpected damage. Discontinuation of services provided by transportation infrastructures will create significant societal, economic, and collateral damages. Therefore, this study aims to identify dimensions to measure the resilience of the transportation infrastructures. This study also aims to develop a model to measure the resilience of the transportation infrastructures resilience. To fulfill the aims of this study, a questionnaire was developed which was supported by a comprehensive literature review. 92 valid responses were received and analyzed qualitatively and quantitatively. Statistically significant variables were used to develop a resilience measurement tool. The developed tool will provide relative resilience measures for multiple projects which will help in identifying the most vulnerable segment of the transportation infrastructure network. Exploratory factor analysis (EFA) was performed to identify the constructs and structural equation modeling (SEM) was used to develop the model. Without previous experience in reconstruction works, handling integrated assets becomes very critical. Also, such inexperience makes it difficult to handle emergency resources properly. However, such issues regarding integrated assets can be resolved by investing in locating integrated assets away from the roadways, so if a break in a railroad crossing or utility line occurs or emergency repairs are needed, the impact on the roadway operations can be minimized. To avoid issues related to access to previous disaster data for the roadway this study suggess investing in preparing an interactive online platform for recording and reviewing data related to disasters as well as previous resilience enhancing activities for the roadway with easy access credentials. The findings of this study will support practitioners and decision-makers in investing in the appropriate resilience enhancement activity project for funding and investment.
description: Tran-SET Project: 20ITSUTA27
DOI: 10.7910/dvn/puuftn
title: Anti-Extradition Bill movement and citizenship norms in Hong Kong

description: This is a dataset of a population survey conducted in Hong Kong in August 2020. The sample size is 817. The key variables include dutiful citizenship, engaged citizenship, and attitudes towards the Anti-ELAB Movement.
DOI: 10.5281/zenodo.6615713
title: A Three-dimensional mapping of soil microbial biomass carbon, nitrogen, phosphorus and their stoichiometry at the global scale

description: R code and predicted global maps of soil microbial biomass C, N, and P and their stoichiometric ratios at 0-30 cm depth.
DOI: 10.34740/kaggle/dsv/3752261
title: Covid data - WorldOMeter
DOI: 10.5281/zenodo.6615742
title: Modeling Crash Severity and Collision Types Using Machine Learning

description: Traffic safety analysis is the fundamental step for reducing economic, social, and environmental cost incurred due to traffic accidents. The essence of traffic safety is understanding the factors affecting crash occurrence, injury severity and collision type and their underlying relationships and predict-prevent future crash instances. Crash injury severity studies in past have utilized numerous statistical, econometric and Machine Learning (ML) and Artificial Intelligence (AI) tools to extract the underlying relationship between the crash causal factors and the consequent severity or collision type. The study aims to explore the Multi-Label Classification (MLC) tool from the domain of Artificial Intelligence (AI) for classification problems in the setting of traffic safety. MLC finds its application primarily in protein function, semantic scene, and music categorization problems. In the real world, multiple heterogenous subjective factors decide the extent of damage/severity of a particular crash instance. Theoretically, the traffic collision type and crash severity type can be correlated, and thus, it is intuitive to model them simultaneously. The ability of MLC to categorize an entity under analysis to more than one labels, correlated or uncorrelated, provides the approach an edge over the single-class (binary) or multi-class classification approach. The MLC based classification model was calibrated and tested using the historical crash data extracted for the state of Texas. The selection of study area was based on a link-level unsupervised principal component analysis-based clustering approach. Similar clustering approach was also tested at the county-level to understand the spatial behavior and thus transferability of the MLC approach to other key cities in the state. The performance of the proposed approach was tested, compared, and quantified with the conventional binary/multi-class classification tools used in the traffic safety domain. Inferences from the preliminary numerical analysis indicates that the proposed multi-label classification approach has promising performance compared to the traditional classification approaches, specifically found in traffic safety literatures.
description: Tran-SET Project: 20SAUTSA36
DOI: 10.5281/zenodo.6615741
title: Modeling Crash Severity and Collision Types Using Machine Learning

description: Traffic safety analysis is the fundamental step for reducing economic, social, and environmental cost incurred due to traffic accidents. The essence of traffic safety is understanding the factors affecting crash occurrence, injury severity and collision type and their underlying relationships and predict-prevent future crash instances. Crash injury severity studies in past have utilized numerous statistical, econometric and Machine Learning (ML) and Artificial Intelligence (AI) tools to extract the underlying relationship between the crash causal factors and the consequent severity or collision type. The study aims to explore the Multi-Label Classification (MLC) tool from the domain of Artificial Intelligence (AI) for classification problems in the setting of traffic safety. MLC finds its application primarily in protein function, semantic scene, and music categorization problems. In the real world, multiple heterogenous subjective factors decide the extent of damage/severity of a particular crash instance. Theoretically, the traffic collision type and crash severity type can be correlated, and thus, it is intuitive to model them simultaneously. The ability of MLC to categorize an entity under analysis to more than one labels, correlated or uncorrelated, provides the approach an edge over the single-class (binary) or multi-class classification approach. The MLC based classification model was calibrated and tested using the historical crash data extracted for the state of Texas. The selection of study area was based on a link-level unsupervised principal component analysis-based clustering approach. Similar clustering approach was also tested at the county-level to understand the spatial behavior and thus transferability of the MLC approach to other key cities in the state. The performance of the proposed approach was tested, compared, and quantified with the conventional binary/multi-class classification tools used in the traffic safety domain. Inferences from the preliminary numerical analysis indicates that the proposed multi-label classification approach has promising performance compared to the traditional classification approaches, specifically found in traffic safety literatures.
description: Tran-SET Project: 20SAUTSA36
DOI: 10.6084/m9.figshare.20001782
title: Variants near EGFR on CFA18 are associated with risk of chronic superficial keratitis in the Australian Racing Greyhound

description: Chronic superficial keratitis (CSK) is a progressive inflammatory condition of the eye and cornea can cause discomfort and blindness. Variation in disease risk across dog breeds strongly suggests that CSK has a genetic basis. In addition to genetic risk, the occurrence of CSK is exacerbated by exposure to ultraviolet light. Genome-wide association analysis considered 109 Greyhounds, 70 with CSK and the remainder with normal phenotype at an age over four years. Three co-located variants on CFA18 near the 5’ region of the Epidermal Growth Factor Receptor (<em>EGFR</em>) gene were associated with genome-wide significance after multiple-test correction [(BICF2P579527, CFA18:5,954,402, praw=1.765e-07, pgenome= 0.017); (BICF2P1310662, CFA18:5,963,278, praw=4.09e-07, pgenome= 0.040); (BICF2P160719, CFA18:5,973,238, praw= 4.09e-07, pgenome= 0.040)] (canFam3.1). Of the top 10 associated markers, eight were co-located with the significantly associated markers on CFA18. The associated haplotype on CFA18 is protective for the CSK condition. <em>EGFR </em>is known to play a role in corneal healing, where it initiates differentiation and proliferation of epithelial cells that in turn signal the involvement of stromal keratocytes to commence apoptosis. Further validation of the associated variants is required prior to their use in genetic testing for breeding programs.
DOI: 10.6084/m9.figshare.20001782.v1
title: Variants near EGFR on CFA18 are associated with risk of chronic superficial keratitis in the Australian Racing Greyhound

description: Chronic superficial keratitis (CSK) is a progressive inflammatory condition of the eye and cornea can cause discomfort and blindness. Variation in disease risk across dog breeds strongly suggests that CSK has a genetic basis. In addition to genetic risk, the occurrence of CSK is exacerbated by exposure to ultraviolet light. Genome-wide association analysis considered 109 Greyhounds, 70 with CSK and the remainder with normal phenotype at an age over four years. Three co-located variants on CFA18 near the 5’ region of the Epidermal Growth Factor Receptor (<em>EGFR</em>) gene were associated with genome-wide significance after multiple-test correction [(BICF2P579527, CFA18:5,954,402, praw=1.765e-07, pgenome= 0.017); (BICF2P1310662, CFA18:5,963,278, praw=4.09e-07, pgenome= 0.040); (BICF2P160719, CFA18:5,973,238, praw= 4.09e-07, pgenome= 0.040)] (canFam3.1). Of the top 10 associated markers, eight were co-located with the significantly associated markers on CFA18. The associated haplotype on CFA18 is protective for the CSK condition. <em>EGFR </em>is known to play a role in corneal healing, where it initiates differentiation and proliferation of epithelial cells that in turn signal the involvement of stromal keratocytes to commence apoptosis. Further validation of the associated variants is required prior to their use in genetic testing for breeding programs.
DOI: 10.6084/m9.figshare.16843075
title: Data obtained from whole blood RNA-Seq data of 11 CNO patients and 9 healthy control in Japan

description: 1) TPM values obtained from whole blood RNA-Seq data of 11 CNO patients and 9 healthy control in Japan: RNASeq-whole-blood-classified_TPM_combined.woBOJ.renamed.tsv <br> 2) The edge contribution value (ECv) calculated for every edge in the estimated basal gene network with respect to each sample: RNASeq-whole-blood-classified_TPM_combined_result1_ECv.renamed.txt <br> 3) The gene expression subnetworks that can be viewed using Cytoscape: cytoscape_CNO_vs_healthy.txt <br> 4) Differentially regulated edges in the gene expression subnetworks that can be imported into Cytoscape: dre_target_CNO_vs_healthy.csv <br> These data were analyzed in the following paper: <br> "Whole blood transcriptome identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis" by Hiroko Yahara et al <br> The data 3) and 4) were used to create Figure 2 (Gene expression subnetwork characteristics of CNO).<br>
DOI: 10.6084/m9.figshare.16843075.v3
title: A matrix of TPM values obtained from whole blood RNA-Seq data of 11 CNO patients and 9 healthy control in Japan

description: A matrix of TPM values obtained from whole blood RNA-Seq data of 11 CNO patients and 9 healthy control in Japan, which was analyzed in the following paper: <br> "Whole blood transcriptome identifies gene expression subnetworks and a key gene characteristic of the rare type of osteomyelitis" by Hiroko Yahara et al<br>