cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/e164302v1-134980
title: Drug Treatment Courts and Community-Level Crime: A Stacked Event Study Analysis

description: This study assessed the degree to which adult drug treatment courts impact county-level crime using a stacked event-study design. Materials included here serve as supplements to the article "Drug Treatment Courts and Community-Level Crime: A Stacked Event Study Analysis<b></b>" submitted to the Journal of Experimental Criminology in March of 2022.<br><br>Materials include:<br>- Stata code for data cleaning and setup, core analysis, counterfactual analysis, and robustness checks<br>- Analysis data with county FIPS codes anonymized <br><br>The code may be adapted for use in other contexts but identification of individual counties has been masked in the data to protect the use of the treatment court data until fully released to the public.
description: This dataset is built upon the UCR Summary Reporting Offenses Known data concatenated by Jacob Kaplan (https://www.openicpsr.org/openicpsr/project/100707/version/V17/view). To minimize measurement error, data cleaning started with UCR reporting agencies which reported all 12 months per year for the entirety of each stack (see Methods Appendix for clarification). Agencies were collapsed to the county level, then other data were merged in.
DOI: 10.34740/kaggle/dsv/5261706
title: Nifty-50 & Nifty Future 50 Dataset
DOI: 10.57967/hf/0471
title: GuanacoDataset
DOI: 10.5255/ukda-sn-856262
title: From Coercion to Consent: Social Identity, Legitimacy, and a Process Model of Police Procedural Justice, 2018-2021

description: This data collection includes quantitative data obtained during the three research strands of this project. Consent for publicly sharing the qualitative data is not in place and retrospective consent is not feasible, and accordingly a waiver has been granted for these data. Keele University strand: One interview study and one wider ethnographic study (including field notes). These data includes sensitive personally identifying information. Consent for publicly sharing this data is not in place and retrospective consent is not feasible, and accordingly a waiver has been granted for these data. London School of Economics strand: One study utilised The European Social Survey (ESS) which is a social scientific endeavour to map the attitudes, beliefs and behaviour patterns of the various populations in Europe. ESS is listed in the Registry of Research Data Repositories re3data.org University College London strand: 1. One survey study involved presenting the results from two UK-based studies that explore the identity dynamics of procedural justice theory. These data are available via related resources. 2. Another survey study assessed the extent to which police procedural justice, effectiveness, legitimacy, and perceived risk of sanction predict compliance with the law among people experiencing homelessness. Two hundred people (87% male, 49% aged 45–64, 37% White British) experiencing homelessness on the streets of an inner London borough completed a survey that included measures of procedural justice, police legitimacy, perceived risk of sanction, morality, and compliance with the law. These data are available via related resources. 3. Another study used two text-based vignette experiments and one video study, and our aims are threefold: (1) to explore the influence of suspect race in how people respond to police use of force; (2) to test the interaction between participant ethnicity and suspect race; and (3) to understand what attitudes and beliefs influence how people respond to police use of force. These data are available via related resources. 4. Another study used two online experiments to test whether different force options affected judgments about the acceptability of police action and to explore the role of trust and legitimacy in people's judgments. These data are available via related resources. 5 An ethnographic study includes sensitive personally identifying information. Consent for publicly sharing this data is not in place and retrospective consent is not feasible, and accordingly a waiver has been granted for these data.
DOI: 10.34740/kaggle/dsv/5261751
title: NSE-Scripts-Data
DOI: 10.6084/m9.figshare.16622191
title: Williams_et_al_extended_data

description: These extended data documents relate to the manuscript titled " Genome-wide association study of susceptibility to hospitalised respiratory infections", which has been submitted to Wellcome Open Research, and include the following files: · Supplementary materials and methods · Supplementary figures · Table S1: ICD-10 codes used to define the hospitalised respiratory infection phenotype. · Table S2: ICD-9 codes used to define the hospitalised respiratory infection phenotype in CHS and Partners Biobank. · Table S3: Summary statistics for the 56 sentinel variants from the discovery GWAS in UK Biobank. · Table S4: Availability of the 40 sentinel variants in the 11 follow-up cohorts. · Table S5: Results of the inverse variance-weighted fixed effects meta-analysis. · Table S6: Fine-mapping of the 56 association signals. · Table S7: Functional annotation of variants in the 95% credible sets. · Table S8: Association between variants in the 95% credible sets and gene expression across 48 tissues from GTEx (v7). · Table S9: Association between variants in the 95% credible sets and gene expression across three major human immune cell types from BLUEPRINT. · Table S10: Association between variants in the 95% credible sets and gene expression (cis-eQTLs) from eQTLGen. · Table S11: Colocalisation results from PICCOLO. · Table S12: Look-up of the sentinel variants in the 56 association signals in existing GWAS. · Table S13: Look-up of the sentinel variants in the 56 association signals in existing GWAS. · Table S14: Look-up of the sentinel variants in the 56 association signals in the COVID-19 Host Genetics Initiative meta-analysis results. Main materials and methods can be found in the main manuscript text.
DOI: 10.6084/m9.figshare.16622191.v2
title: Williams_et_al_extended_data

description: These extended data documents relate to the manuscript titled " Genome-wide association study of susceptibility to hospitalised respiratory infections", which has been submitted to Wellcome Open Research, and include the following files: · Supplementary materials and methods · Supplementary figures · Table S1: ICD-10 codes used to define the hospitalised respiratory infection phenotype. · Table S2: ICD-9 codes used to define the hospitalised respiratory infection phenotype in CHS and Partners Biobank. · Table S3: Summary statistics for the 56 sentinel variants from the discovery GWAS in UK Biobank. · Table S4: Availability of the 40 sentinel variants in the 11 follow-up cohorts. · Table S5: Results of the inverse variance-weighted fixed effects meta-analysis. · Table S6: Fine-mapping of the 56 association signals. · Table S7: Functional annotation of variants in the 95% credible sets. · Table S8: Association between variants in the 95% credible sets and gene expression across 48 tissues from GTEx (v7). · Table S9: Association between variants in the 95% credible sets and gene expression across three major human immune cell types from BLUEPRINT. · Table S10: Association between variants in the 95% credible sets and gene expression (cis-eQTLs) from eQTLGen. · Table S11: Colocalisation results from PICCOLO. · Table S12: Look-up of the sentinel variants in the 56 association signals in existing GWAS. · Table S13: Look-up of the sentinel variants in the 56 association signals in existing GWAS. · Table S14: Look-up of the sentinel variants in the 56 association signals in the COVID-19 Host Genetics Initiative meta-analysis results. Main materials and methods can be found in the main manuscript text.
DOI: 10.6084/m9.figshare.16622191.v1
title: Williams_et_al_extended_data

description: These extended data documents relate to the manuscript titled " Genome-wide association study of susceptibility to hospitalised respiratory infections", which has been submitted to Wellcome Open Research, and include the following files: · Supplementary materials and methods · Supplementary figures · Table S1: ICD-10 codes used to define the hospitalised respiratory infection phenotype. · Table S2: ICD-9 codes used to define the hospitalised respiratory infection phenotype in CHS and Partners Biobank. · Table S3: Summary statistics for the 56 sentinel variants from the discovery GWAS in UK Biobank. · Table S4: Availability of the 40 sentinel variants in the 11 follow-up cohorts. · Table S5: Results of the inverse variance-weighted fixed effects meta-analysis. · Table S6: Fine-mapping of the 56 association signals. · Table S7: Functional annotation of variants in the 95% credible sets. · Table S8: Association between variants in the 95% credible sets and gene expression across 48 tissues from GTEx (v7). · Table S9: Association between variants in the 95% credible sets and gene expression across three major human immune cell types from BLUEPRINT. · Table S10: Association between variants in the 95% credible sets and gene expression (cis-eQTLs) from eQTLGen. · Table S11: Colocalisation results from PICCOLO. · Table S12: Look-up of the sentinel variants in the 56 association signals in existing GWAS. · Table S13: Look-up of the sentinel variants in the 56 association signals in existing GWAS. · Table S14: Look-up of the sentinel variants in the 56 association signals in the COVID-19 Host Genetics Initiative meta-analysis results. Main materials and methods can be found in the main manuscript text.
DOI: 10.6084/m9.figshare.13634552.v6
title: Global Land ET by CR method

description: This is the global land surface evapotranspiration dataset produced by the calibration-free Complementary Relationship (CR) method. The dataset now covers the period of 1982-2016 with spatial and temporal resolutions of 0.25-degree and monthly, respectively. The dataset may be updated in future for an extended temporal coverage when certain inputs of the model become available. <br>
DOI: 10.6084/m9.figshare.22335640
title: SRR3414629.uniq.sorted.bam

description: This is part of the practical training in RNA-seq data analysis assignment 1.
DOI: 10.6084/m9.figshare.22335640.v4
title: SRR3414629.uniq.sorted.bam

description: This is part of the practical training in RNA-seq data analysis assignment 1.
DOI: 10.6084/m9.figshare.22335640.v3
title: SRR3414629.uniq.sorted.bam

description: This is part of the practical training in RNA-seq data analysis assignment 1.
DOI: 10.6084/m9.figshare.16823827
title: The use of text-matching software’s similarity scores

description: Popular text-matching software generates a percentage of similarity – called a “similarity score” or “Similarity Index” – that quantifies the matching text between a particular manuscript and content in the software’s archives, on the Internet and in electronic databases. Many evaluators rely on these simple figures as a proxy for plagiarism and thus avoid the burdensome task of inspecting the longer, detailed Similarity Reports. Yet similarity scores, though alluringly straightforward, are never enough to judge the presence (or absence) of plagiarism. Ideally, evaluators should always examine the Similarity Reports. Given the persistent use of simplistic similarity score thresholds at some academic journals and educational institutions, however, and the time that can be saved by relying on the scores, a method is arguably needed that encourages examining the Similarity Reports but still also allows evaluators to rely on the scores in some instances. This article proposes a four-band method to accomplish this. Used together, the bands oblige evaluators to acknowledge the risk of relying on the similarity scores yet still allow them to ultimately determine whether they wish to accept that risk. The bands – for most rigor, high rigor, moderate rigor and less rigor – should be tailored to an evaluator’s particular needs.
DOI: 10.6084/m9.figshare.16823827.v1
title: The use of text-matching software’s similarity scores

description: Popular text-matching software generates a percentage of similarity – called a “similarity score” or “Similarity Index” – that quantifies the matching text between a particular manuscript and content in the software’s archives, on the Internet and in electronic databases. Many evaluators rely on these simple figures as a proxy for plagiarism and thus avoid the burdensome task of inspecting the longer, detailed Similarity Reports. Yet similarity scores, though alluringly straightforward, are never enough to judge the presence (or absence) of plagiarism. Ideally, evaluators should always examine the Similarity Reports. Given the persistent use of simplistic similarity score thresholds at some academic journals and educational institutions, however, and the time that can be saved by relying on the scores, a method is arguably needed that encourages examining the Similarity Reports but still also allows evaluators to rely on the scores in some instances. This article proposes a four-band method to accomplish this. Used together, the bands oblige evaluators to acknowledge the risk of relying on the similarity scores yet still allow them to ultimately determine whether they wish to accept that risk. The bands – for most rigor, high rigor, moderate rigor and less rigor – should be tailored to an evaluator’s particular needs.
DOI: 10.6084/m9.figshare.22284006.v1
title: Semantic segmentation for fully automated macrofouling analysis on coatings after field exposure

description: Biofouling is a major challenge for sustainable shipping, filter membranes, heat exchangers, and medical devices. The development of fouling-resistant coatings requires the evaluation of their effectiveness. Such an evaluation is usually based on the assessment of fouling progression after different exposure times to the target medium (e.g. salt water). The manual assessment of macrofouling requires expert knowledge about local fouling communities due to high variances in phenotypical appearance, has single-image sampling inaccuracies for certain species, and lacks spatial information. Here an approach for automatic image-based macrofouling analysis was presented. A dataset with dense labels prepared from field panel images was made and a convolutional network (adapted U-Net) for the semantic segmentation of different macrofouling classes was proposed. The establishment of macrofouling localization allows for the generation of a successional model which enables the determination of direct surface attachment and in-depth epibiotic studies.
DOI: 10.6084/m9.figshare.22262447.v1
title: Facilitation of non-indigenous ascidian by marine eco-engineering interventions at an urban site

description: Marine artificial structures often support lower native species diversity and more non-indigenous species (NIS), but adding complex habitat and using bioreceptive materials have the potential to mitigate these impacts. Here, the interacting effects of structural complexity (flat, complex with pits) and concrete mixture (standard, or with oyster shell or vermiculite aggregate) on recruitment were assessed at two intertidal levels at an urban site. Complex tiles had less green algal cover, oyster shell mixtures had less brown (<i>Ralfsia</i> sp.<i>)</i> algal cover. At a low tidal elevation, the non-indigenous ascidian <i>Styela plicata</i> dominated complex tiles. Additionally, mixtures with oyster shell supported higher total cover of sessile species, and a higher cover of <i>S. plicata.</i> There were no effects of complexity or mixture on biofilm communities and native and NIS richness. Overall, these results suggest that habitat complexity and some bioreceptive materials may facilitate colonisation by a dominant invertebrate invader on artificial structures.
DOI: 10.6084/m9.figshare.22284006
title: Semantic segmentation for fully automated macrofouling analysis on coatings after field exposure

description: Biofouling is a major challenge for sustainable shipping, filter membranes, heat exchangers, and medical devices. The development of fouling-resistant coatings requires the evaluation of their effectiveness. Such an evaluation is usually based on the assessment of fouling progression after different exposure times to the target medium (e.g. salt water). The manual assessment of macrofouling requires expert knowledge about local fouling communities due to high variances in phenotypical appearance, has single-image sampling inaccuracies for certain species, and lacks spatial information. Here an approach for automatic image-based macrofouling analysis was presented. A dataset with dense labels prepared from field panel images was made and a convolutional network (adapted U-Net) for the semantic segmentation of different macrofouling classes was proposed. The establishment of macrofouling localization allows for the generation of a successional model which enables the determination of direct surface attachment and in-depth epibiotic studies.
DOI: 10.6084/m9.figshare.22262447
title: Facilitation of non-indigenous ascidian by marine eco-engineering interventions at an urban site

description: Marine artificial structures often support lower native species diversity and more non-indigenous species (NIS), but adding complex habitat and using bioreceptive materials have the potential to mitigate these impacts. Here, the interacting effects of structural complexity (flat, complex with pits) and concrete mixture (standard, or with oyster shell or vermiculite aggregate) on recruitment were assessed at two intertidal levels at an urban site. Complex tiles had less green algal cover, oyster shell mixtures had less brown (<i>Ralfsia</i> sp.<i>)</i> algal cover. At a low tidal elevation, the non-indigenous ascidian <i>Styela plicata</i> dominated complex tiles. Additionally, mixtures with oyster shell supported higher total cover of sessile species, and a higher cover of <i>S. plicata.</i> There were no effects of complexity or mixture on biofilm communities and native and NIS richness. Overall, these results suggest that habitat complexity and some bioreceptive materials may facilitate colonisation by a dominant invertebrate invader on artificial structures.
DOI: 10.6084/m9.figshare.22353484
title: SRR3414629.uniq.sorted.bam.bai

description: Index file
DOI: 10.6084/m9.figshare.22353484.v1
title: SRR3414629.uniq.sorted.bam.bai

description: Index file
DOI: 10.34740/kaggle/dsv/5261793
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5517/ccdc.csd.cc2br08d
title: CCDC 2167063: Experimental Crystal Structure Determination

description: Related Article: Yan-Rong Jia, Kai Xu, Min Xia|2023|Dyes Pigm.|214|111234|doi:10.1016/j.dyepig.2023.111234
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.cc2cbdy2
title: CCDC 2184754: Experimental Crystal Structure Determination

description: Related Article: Eric Francis Lopes, Diogo Seibert Lüdtke, Rafael Stieler|2022|CSD Communication|||
description: Related Article: Eric F. Lopes, Maiara T. Saraiva, Natalí P. Debia, Luana Silva, Otávio A. Chaves, Rafael Stieler, Bernardo A. Iglesias, Fabiano S. Rodembusch, Diogo S. Lüdtke|2023|Dyes Pigm.|214|111212|doi:10.1016/j.dyepig.2023.111212
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.cc2cbdz3
title: CCDC 2184755: Experimental Crystal Structure Determination

description: Related Article: Eric Francis Lopes, Diogo Seibert Lüdtke, Rafael Stieler|2022|CSD Communication|||
description: Related Article: Eric F. Lopes, Maiara T. Saraiva, Natalí P. Debia, Luana Silva, Otávio A. Chaves, Rafael Stieler, Bernardo A. Iglesias, Fabiano S. Rodembusch, Diogo S. Lüdtke|2023|Dyes Pigm.|214|111212|doi:10.1016/j.dyepig.2023.111212
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.cc2d718z
title: CCDC 2211300: Experimental Crystal Structure Determination

description: Related Article: xiaomin Yang, zhaoyi Yang, haoran Li, xuanmin Yang, yanrong Zhang|2023|Dyes Pigm.|214|111215|doi:10.1016/j.dyepig.2023.111215
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.cc2d741v
title: CCDC 2211386: Experimental Crystal Structure Determination

description: Related Article: xiaomin Yang, zhaoyi Yang, haoran Li, xuanmin Yang, yanrong Zhang|2023|Dyes Pigm.|214|111215|doi:10.1016/j.dyepig.2023.111215
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.cc2dfmj0
title: CCDC 2217632: Experimental Crystal Structure Determination

description: Related Article: Yunpeng Yi, Jiaming Zhang, Jiakun Zuo, Maolu Zhang, Shifa Yang, Zhongli Huang, Guiyu Li, Ruofeng Shang, Shuqian Lin|2023|Eur.J.Med.Chem.|251|115269|doi:10.1016/j.ejmech.2023.115269
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.