cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13012/b2idb-5649852_v5
title: Global News Index and Extracted Features Repository (v.1.2.0)

description: The Cline Center Global News Index is a searchable database of textual features extracted from millions of news stories, specifically designed to provide comprehensive coverage of events around the world. In addition to searching documents for keywords, users can query metadata and features such as named entities extracted using Natural Language Processing (NLP) methods and variables that measure sentiment and emotional valence. Archer is a web application purpose-built by the Cline Center to enable researchers to access data from the Global News Index. Archer provides a user-friendly interface for querying the Global News Index (with the back-end indexing still handled by Solr). By default, queries are built using icons and drop-down menus. More technically-savvy users can use Lucene/Solr query syntax via a ‘raw query’ option. Archer allows users to save and iterate on their queries, and to visualize faceted query results, which can be helpful for users as they refine their queries. Additional Resources: - Access to Archer and the Global News Index is limited to account-holders. If you are interested in signing up for an account, please fill out the <b>Archer Access Request Form</b> so we can determine if you are eligible for access or not. - Current users who would like to provide feedback, such as reporting a bug or requesting a feature, can fill out the <b>Archer User Feedback Form</b>. - The Cline Center sends out periodic email newsletters to the Archer Users Group. Please fill out this <b>form</b> to subscribe to it. <b>Citation Guidelines:</b> 1) To cite the GNI codebook (or any other documentation associated with the Global News Index and Archer) please use the following citation: Cline Center for Advanced Social Research. 2023. Global News Index and Extracted Features Repository [codebook], v1.2.0. Champaign, IL: University of Illinois. June. XX. doi:10.13012/B2IDB-5649852_V5 2) To cite data from the Global News Index (accessed via Archer or otherwise) please use the following citation (filling in the correct date of access): Cline Center for Advanced Social Research. 2023. Global News Index and Extracted Features Repository [database], v1.2.0. Champaign, IL: University of Illinois. Jun. XX. Accessed Month, DD, YYYY. doi:10.13012/B2IDB-5649852_V5 *NOTE: V4 is suppressed and V5 is replacing V4 with updated ‘Archer’ documents.
DOI: 10.13012/b2idb-5649852_v3
title: Global News Index and Extracted Features Repository (v.1.1.0)

description: The Cline Center Global News Index is a searchable database of textual features extracted from millions of news stories, specifically designed to provide comprehensive coverage of events around the world. In addition to searching documents for keywords, users can query metadata and features such as named entities extracted using Natural Language Processing (NLP) methods and variables that measure sentiment and emotional valence. Archer is a web application purpose-built by the Cline Center to enable researchers to access data from the Global News Index. Archer provides a user-friendly interface for querying the Global News Index (with the back-end indexing still handled by Solr). By default, queries are built using icons and drop-down menus. More technically-savvy users can use Lucene/Solr query syntax via a ‘raw query’ option. Archer allows users to save and iterate on their queries, and to visualize faceted query results, which can be helpful for users as they refine their queries. <b>Additional Resources:</b> - Access to Archer and the Global News Index is limited to account-holders. If you are interested in signing up for an account, please fill out the <b>Archer Access Request Form</b> so we can determine if you are eligible for access or not. - Current users who would like to provide feedback, such as reporting a bug or requesting a feature, can fill out the <b>Archer User Feedback Form</b>. - The Cline Center sends out periodic email newsletters to the Archer Users Group. Please fill out this <b>form</b> to subscribe to it. <b>Citation Guidelines:</b> 1) To cite the GNI codebook (or any other documentation associated with the Global News Index and Archer) please use the following citation: Cline Center for Advanced Social Research. 2022. Global News Index and Extracted Features Repository [codebook], v1.1.0. Champaign, IL: University of Illinois. Dec. 16. doi:10.13012/B2IDB-5649852_V3 2) To cite data from the Global News Index (accessed via Archer or otherwise) please use the following citation (filling in the correct date of access): Cline Center for Advanced Social Research. 2022. Global News Index and Extracted Features Repository [database], v1.1.0. Champaign, IL: University of Illinois. Dec. 16. Accessed Month, DD, YYYY. doi:10.13012/B2IDB-5649852_V3
DOI: 10.5281/zenodo.8067415
title: Data for article entitled 'Prosodic words are the domain of emphasis spread in Jordanian Arabic'

description: see publication
DOI: 10.5281/zenodo.8067414
title: Data for article entitled 'Prosodic words are the domain of emphasis spread in Jordanian Arabic'

description: see publication
DOI: 10.5517/ccdc.csd.cc27wyx0
title: CCDC 2082453: Experimental Crystal Structure Determination

description: Related Article: Shengbo Zhang, Yingying Xue, Yanfen Wu, Yu-Xiao Zhang, Ting Tan, Zhiqiang Niu|2023|Chemical Science|14|6558|doi:10.1039/D3SC01161E
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.cc2d13wg
title: CCDC 2205615: Experimental Crystal Structure Determination

description: Related Article: Shengbo Zhang, Yingying Xue, Yanfen Wu, Yu-Xiao Zhang, Ting Tan, Zhiqiang Niu|2023|Chemical Science|14|6558|doi:10.1039/D3SC01161E
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.cc2d13zk
title: CCDC 2205618: Experimental Crystal Structure Determination

description: Related Article: Shengbo Zhang, Yingying Xue, Yanfen Wu, Yu-Xiao Zhang, Ting Tan, Zhiqiang Niu|2023|Chemical Science|14|6558|doi:10.1039/D3SC01161E
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.cc2d145s
title: CCDC 2205624: Experimental Crystal Structure Determination

description: Related Article: Shengbo Zhang, Yingying Xue, Yanfen Wu, Yu-Xiao Zhang, Ting Tan, Zhiqiang Niu|2023|Chemical Science|14|6558|doi:10.1039/D3SC01161E
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.cc2d23zl
title: CCDC 2206579: Experimental Crystal Structure Determination

description: Related Article: Pei Li, Hongju Liu, Wanlu Tian, Zhanshan Ma, Xiaoyue Wang, Guoyong Xu, Chao Li, Muhammad Qasim, Fuzhou Wang|2023|Polymer|280|126060|doi:10.1016/j.polymer.2023.126060
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: 10.6084/m9.figshare.9919037
title: Synthesis and structural characterization of a barium coordination polymer based on a μ<sub>2</sub>-monoatomic bridging 4-nitrobenzoate

description: The synthesis, spectral characterization, crystal structure and properties of [Ba(H<sub>2</sub>O)<sub>2</sub>(NMF)<sub>2</sub>(4-nba)<sub>2</sub>], <b>1</b> (NMF = <i>N</i>-methylformamide; 4-nba = 4-nitrobenzoate), are reported. <sup>1</sup>H and <sup>13</sup>C NMR spectral data reveal the presence of NMF in <b>1</b>. A strong band at 1660 cm<sup>−1</sup> in the infrared spectrum indicates the binding of amide oxygen to Ba(II) which is confirmed by the single crystal structure. The unique Ba(II) in <b>1</b> situated on a mirror plane exhibits nine coordination and is bonded to two symmetry related monodentate terminal NMF ligands via the amide oxygen, and a terminal aqua ligand. The μ<sub>2</sub>-monoatomic bridging binding mode of each of a crystallographically independent 4-nba ligand and a unique water ligand link the Ba(II) cations into an infinite chain extending along <i>a</i>, leading to the formation of a 1D coordination polymer with Ba···Ba separations of 4.2522(3) Å. In the chain, the {BaO<sub>9</sub>} polyhedra are linked in a face sharing fashion. Thermal decomposition of <b>1</b> results in the formation of BaCO<sub>3</sub> residue. A comparative study of the structural chemistry of several barium coordination polymers is described.
DOI: 10.6084/m9.figshare.9919037.v1
title: Synthesis and structural characterization of a barium coordination polymer based on a μ<sub>2</sub>-monoatomic bridging 4-nitrobenzoate

description: The synthesis, spectral characterization, crystal structure and properties of [Ba(H<sub>2</sub>O)<sub>2</sub>(NMF)<sub>2</sub>(4-nba)<sub>2</sub>], <b>1</b> (NMF = <i>N</i>-methylformamide; 4-nba = 4-nitrobenzoate), are reported. <sup>1</sup>H and <sup>13</sup>C NMR spectral data reveal the presence of NMF in <b>1</b>. A strong band at 1660 cm<sup>−1</sup> in the infrared spectrum indicates the binding of amide oxygen to Ba(II) which is confirmed by the single crystal structure. The unique Ba(II) in <b>1</b> situated on a mirror plane exhibits nine coordination and is bonded to two symmetry related monodentate terminal NMF ligands via the amide oxygen, and a terminal aqua ligand. The μ<sub>2</sub>-monoatomic bridging binding mode of each of a crystallographically independent 4-nba ligand and a unique water ligand link the Ba(II) cations into an infinite chain extending along <i>a</i>, leading to the formation of a 1D coordination polymer with Ba···Ba separations of 4.2522(3) Å. In the chain, the {BaO<sub>9</sub>} polyhedra are linked in a face sharing fashion. Thermal decomposition of <b>1</b> results in the formation of BaCO<sub>3</sub> residue. A comparative study of the structural chemistry of several barium coordination polymers is described.
DOI: 10.5281/zenodo.8067382
title: Digital Assets for "Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey"

description: These are morphological catalogs and trained GaMPEN models for Hyper Suprime-Cam galaxies. Please refer to https://gampen.readthedocs.io/en/latest/Public_data.html and https://arxiv.org/abs/2212.00051 for more details about this data release. <strong>Catalog Files</strong> g_0_025_preds_summary.csv --&gt; Structural parameter catalog for z &lt; 0.25 HSC g-band galaxies r_025_050_preds_summary.csv --&gt; Structural parameter catalog for 0.25 &lt; z &lt; 0.50 HSC r-band galaxies i_050_075_preds_summary.csv --&gt; Structural parameter catalog for 0.50 &lt; z &lt; 0.75 HSC i-band galaxies <strong>Trained PyTorch Model Files</strong> g_0_025_real_data.pt --&gt; Trained Model for z &lt; 0.25 HSC g-band galaxies r_025_050_real_data.pt --&gt; Trained Model for 0.25 &lt; z &lt; 0.50 HSC r-band galaxies i_050_075_real_data.pt --&gt; Trained Model for 0.50 &lt; z &lt; 0.75 HSC i-band galaxies sim_g_0_025.pt --&gt; Trained Model for Simulated z &lt; 0.25 HSC g-band galaxies sim_r_025_050.pt --&gt; Trained Model for Simulated 0.25 &lt; z &lt; 0.50 HSC r-band galaxies sim_i_050_075.pt --&gt; Trained Model for Simulated 0.50 &lt; z &lt; 0.75 HSC i-band galaxies
DOI: 10.5281/zenodo.8067381
title: Digital Assets for "Morphological Parameters and Associated Uncertainties for 8 Million Galaxies in the Hyper Suprime-Cam Wide Survey"

description: These are morphological catalogs and trained GaMPEN models for Hyper Suprime-Cam galaxies. Please refer to https://gampen.readthedocs.io/en/latest/Public_data.html and https://arxiv.org/abs/2212.00051 for more details about this data release. <strong>Catalog Files</strong> g_0_025_preds_summary.csv --&gt; Structural parameter catalog for z &lt; 0.25 HSC g-band galaxies r_025_050_preds_summary.csv --&gt; Structural parameter catalog for 0.25 &lt; z &lt; 0.50 HSC r-band galaxies i_050_075_preds_summary.csv --&gt; Structural parameter catalog for 0.50 &lt; z &lt; 0.75 HSC i-band galaxies <strong>Trained PyTorch Model Files</strong> g_0_025_real_data.pt --&gt; Trained Model for z &lt; 0.25 HSC g-band galaxies r_025_050_real_data.pt --&gt; Trained Model for 0.25 &lt; z &lt; 0.50 HSC r-band galaxies i_050_075_real_data.pt --&gt; Trained Model for 0.50 &lt; z &lt; 0.75 HSC i-band galaxies sim_g_0_025.pt --&gt; Trained Model for Simulated z &lt; 0.25 HSC g-band galaxies sim_r_025_050.pt --&gt; Trained Model for Simulated 0.25 &lt; z &lt; 0.50 HSC r-band galaxies sim_i_050_075.pt --&gt; Trained Model for Simulated 0.50 &lt; z &lt; 0.75 HSC i-band galaxies
DOI: 10.6084/m9.figshare.23557119
title: Peptides structures

description: This file contains all the peptide structures used in BrainPepPass work in .mol and .SDF format.
DOI: 10.6084/m9.figshare.23557119.v1
title: Peptides structures

description: This file contains all the peptide structures used in BrainPepPass work in .mol and .SDF format.
DOI: 10.5281/zenodo.8067480
title: Infograma

description: Infográfico: Documento Arquivístico e Classificação Documental.
DOI: 10.5281/zenodo.8067481
title: Infograma

description: Infográfico: Documento Arquivístico e Classificação Documental.
DOI: 10.6084/m9.figshare.22963610
title: Influential Observations in Bayesian Regression Tree Models

description: Bayesian Classification and Regression Trees (BCART) and Bayesian Additive Regression Trees (BART) are popular Bayesian regression models widely applicable in modern regression problems. Their popularity is intimately tied to the ability to flexibly model complex responses depending on high-dimensional inputs while simultaneously being able to quantify uncertainties. This ability to quantify uncertainties is key, as it allows researchers to perform appropriate inferential analyses in settings that have generally been too difficult to handle using the Bayesian approach. However, surprisingly little work has been done to evaluate the sensitivity of these modern regression models to violations of modeling assumptions. In particular, we will consider influential observations, which one reasonably would imagine to be common—or at least a concern—in the big-data setting. In this article, we consider both the problem of detecting influential observations and adjusting predictions to not be unduly affected by such potentially problematic data. We consider three detection diagnostics for Bayesian tree models, one an analogue of Cook’s distance and the others taking the form of a divergence measure and a conditional predictive density metric, and then propose an importance sampling algorithm to re-weight previously sampled posterior draws so as to remove the effects of influential data in a computationally efficient manner. Finally, our methods are demonstrated on real-world data where blind application of the models can lead to poor predictions and inference. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.22963610.v1
title: Influential Observations in Bayesian Regression Tree Models

description: Bayesian Classification and Regression Trees (BCART) and Bayesian Additive Regression Trees (BART) are popular Bayesian regression models widely applicable in modern regression problems. Their popularity is intimately tied to the ability to flexibly model complex responses depending on high-dimensional inputs while simultaneously being able to quantify uncertainties. This ability to quantify uncertainties is key, as it allows researchers to perform appropriate inferential analyses in settings that have generally been too difficult to handle using the Bayesian approach. However, surprisingly little work has been done to evaluate the sensitivity of these modern regression models to violations of modeling assumptions. In particular, we will consider influential observations, which one reasonably would imagine to be common—or at least a concern—in the big-data setting. In this article, we consider both the problem of detecting influential observations and adjusting predictions to not be unduly affected by such potentially problematic data. We consider three detection diagnostics for Bayesian tree models, one an analogue of Cook’s distance and the others taking the form of a divergence measure and a conditional predictive density metric, and then propose an importance sampling algorithm to re-weight previously sampled posterior draws so as to remove the effects of influential data in a computationally efficient manner. Finally, our methods are demonstrated on real-world data where blind application of the models can lead to poor predictions and inference. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.22696151
title: Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes

description: We introduce a family of local inhomogeneous mark-weighted summary statistics, of order two and higher, for general marked point processes. Depending on how the involved weight function is specified, these summary statistics capture different kinds of local dependence structures. We first derive some basic properties and show how these new statistical tools can be used to construct most existing summary statistics for (marked) point processes. We then propose a local test of random labeling. This procedure allows us to identify points, and consequently regions, where the random labeling assumption does not hold, for example, when the (functional) marks are spatially dependent. Through a simulation study we show that the test is able to detect local deviations from random labeling. We also provide an application to an earthquake point pattern with functional marks given by seismic waveforms.
DOI: 10.6084/m9.figshare.22696151.v2
title: Local Inhomogeneous Weighted Summary Statistics for Marked Point Processes

description: We introduce a family of local inhomogeneous mark-weighted summary statistics, of order two and higher, for general marked point processes. Depending on how the involved weight function is specified, these summary statistics capture different kinds of local dependence structures. We first derive some basic properties and show how these new statistical tools can be used to construct most existing summary statistics for (marked) point processes. We then propose a local test of random labeling. This procedure allows us to identify points, and consequently regions, where the random labeling assumption does not hold, for example, when the (functional) marks are spatially dependent. Through a simulation study we show that the test is able to detect local deviations from random labeling. We also provide an application to an earthquake point pattern with functional marks given by seismic waveforms.
DOI: 10.6084/m9.figshare.22696151.v1
title: Local inhomogeneous weighted summary statistics for marked point processes

description: We introduce a family of local inhomogeneous mark-weighted summary statistics, of order two and higher, for general marked point processes. Depending on how the involved weight function is specified, these summary statistics capture different kinds of local dependence structures. We first derive some basic properties and show how these new statistical tools can be used to construct most existing summary statistics for (marked) point processes. We then propose a local test of random labelling. This procedure allows us to identify points, and consequently regions, where the random labelling assumption does not hold, e.g. when the (functional) marks are spatially dependent. Through a simulation study we show that the test is able to detect local deviations from random labelling. We also provide an application to an earthquake point pattern with functional marks given by seismic waveforms.
DOI: 10.5281/zenodo.8067479
title: Reproducibility Report for the paper "Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes"

description: This reproducibility report includes the datasets and computer code used for reproducing the results in the paper, Jin, Bukkapatnam, Hayes, and Ding, 2023, “Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes,” <em>ASME Transactions, Journal of Manufacturing Science and Engineering</em>, Vol.145, pp. 061007.
description: {"references": ["Jin, Bukkapatnam, Hayes, and Ding, 2023, \"Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes,\" ASME Transactions, Journal of Manufacturing Science and Engineering, Vol.145, pp. 061007."]}
DOI: 10.5281/zenodo.8067478
title: Reproducibility Report for the paper "Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes"

description: This reproducibility report includes the datasets and computer code used for reproducing the results in the paper, Jin, Bukkapatnam, Hayes, and Ding, 2023, “Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes,” <em>ASME Transactions, Journal of Manufacturing Science and Engineering</em>, Vol.145, pp. 061007.
description: {"references": ["Jin, Bukkapatnam, Hayes, and Ding, 2023, \"Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes,\" ASME Transactions, Journal of Manufacturing Science and Engineering, Vol.145, pp. 061007."]}
DOI: 10.5281/zenodo.7683383
title: GWAS dataset with simulated binary phenotypes for 1000 Genome Project

description: Phenotypes in this dataset are generated by simulating quantitative blood lipid level phenotype using the method introduced in by (https://app.terra.bio/#workspaces/amp-t2d-op/2019_ASHG_Reproducible_GWAS-V2), and binarized to be suitable as a test case for GWAS methods. ALL.shapeit2_integrated_v1a.GRCh38.20181129.phased.rsid files and allpopid.txt are the 1000 Genome Project reference data used for generating MDS plot in https://github.com/csbio/BridGE-Python
DOI: 10.5281/zenodo.7683384
title: GWAS dataset with simulated binary phenotypes for 1000 Genome Project

description: Phenotypes in this dataset are generated by simulating quantitative blood lipid level phenotype using the method introduced in by (https://app.terra.bio/#workspaces/amp-t2d-op/2019_ASHG_Reproducible_GWAS-V2), and binarized to be suitable as a test case for GWAS methods.