cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14039999.v1
title: Inference for high-dimensional linear mixed-effects models: A quasi-likelihood approach

description: Linear mixed-effects models are widely used in analyzing clustered or repeated measures data. We propose a quasi-likelihood approach for estimation and inference of the unknown parameters in linear mixed-effects models with high-dimensional fixed effects. The proposed method is applicable to general settings where the dimension of the random effects and the cluster sizes are possibly large. Regarding the fixed effects, we provide rate optimal estimators and valid inference procedures that do not rely on the structural information of the variance components. We also study the estimation of variance components with high-dimensional fixed effects in general settings. The algorithms are easy to implement and computationally fast. The proposed methods are assessed in various simulation settings and are applied to a real study regarding the associations between body mass index and genetic polymorphic markers in a heterogeneous stock mice population.
DOI: 10.6084/m9.figshare.14454606
title: Individual phylogenetic markers alignments

description: Untrimmed individual phylogenetic markers alignment.
DOI: 10.6084/m9.figshare.14454606.v2
title: Individual phylogenetic markers alignments

description: Untrimmed individual phylogenetic markers alignment.
DOI: 10.6084/m9.figshare.14454606.v1
title: Individual phylogenetic markers alignments

description: Untrimmed individual phylogenetic markers alignment.
DOI: 10.6084/m9.figshare.14049656
title: Variable Selection in the Presence of Factors: A Model Selection Perspective

description: In the context of a Gaussian multiple regression model, we address the problem of variable selection when in the list of potential predictors there are factors, that is, categorical variables. We adopt a model selection perspective, that is, we approach the problem by constructing a class of models, each corresponding to a particular selection of active variables. The methodology is Bayesian and proceeds by computing the posterior probability of each of these models. We highlight the fact that the set of competing models depends on the dummy variable representation of the factors, an issue already documented by Fernández et al. in a particular example but that has not received any attention since then. We construct methodology that circumvents this problem and that presents very competitive frequentist behavior when compared with recently proposed techniques. Additionally, it is fully automatic, in that it does not require the specification of any tuning parameters.
DOI: 10.6084/m9.figshare.14049656.v2
title: Variable Selection in the Presence of Factors: A Model Selection Perspective

description: In the context of a Gaussian multiple regression model, we address the problem of variable selection when in the list of potential predictors there are factors, that is, categorical variables. We adopt a model selection perspective, that is, we approach the problem by constructing a class of models, each corresponding to a particular selection of active variables. The methodology is Bayesian and proceeds by computing the posterior probability of each of these models. We highlight the fact that the set of competing models depends on the dummy variable representation of the factors, an issue already documented by Fernández et al. in a particular example but that has not received any attention since then. We construct methodology that circumvents this problem and that presents very competitive frequentist behavior when compared with recently proposed techniques. Additionally, it is fully automatic, in that it does not require the specification of any tuning parameters.
DOI: 10.6084/m9.figshare.14049656.v1
title: Variable selection in the presence of factors: a model selection perspective*

description: In the context of a Gaussian multiple regression model, we address the problem of variable selection when in the list of potential predictors there are factors, i.e., categorical variables. We adopt a model selection perspective, that is, we approach the problem by constructing a class of models, each corresponding to a particular selection of active variables. The methodology is Bayesian and proceeds by computing the posterior probability of each of these models. We highlight the fact that the set of competing models depends on the dummy variable representation of the factors, an issue already documented by Fernández et al. (2002) in a particular example but that has not received any attention since then. We construct methodology that circumvents this problem and that presents very competitive frequentist behavior when compared with recently proposed techniques. Additionally, it is fully automatic, in that it does not require the specification of any tunning paramters.
DOI: 10.6084/m9.figshare.14454660
title: Database_EndOfLifePatient_DATA_2019-02-10_sc_7.xlsx

description: Database for an observational study assessing the characteristics and emergency department management of patients with end-of-life conditions
DOI: 10.5281/zenodo.4559500
title: In situ bio-optical data in Lake Balaton, MONOCLE H2020 project

description: This dataset includes in situ bio-optical and biogeochemical data collected from Lake Balaton, Hungary during July 1<sup>st</sup> – July 5<sup>th</sup>, 2019 within the framework of Horizon 2020 MONOCLE project. Specifically, the following parameters are provided in the dataset: Chlorophyll-a concentration (Chl-a) Total Suspended Matter concentration (TSM) Absorption of Coloured Dissolved Organic Matters (CDOM) Turbidity Remote-sensing reflectance (Rrs) from TriOS Subsurface irradiance reflectance (R0-) from WISP Particulate absorption coefficient (apd) Particulate scattering coefficient (bp) Particulate attenuation coefficient (cpd) Particulate backscattering coefficient (bbp) Aerosol optical thickness (AOT) Downwelling irradiance (Es) from HyperOCR Data are provided in either Excel or CSV file, “NA” or “nan” indicates no data available.
DOI: 10.34740/kaggle/dsv/2140811
title: YouTube Trending Video Dataset (updated daily)
DOI: 10.5281/zenodo.4705368
title: Stable Atlantic deep water mass sourcing on glacial-interglacial timescales: Nd isotope data of IODP Site U1313

description: This dataset contains neodymium isotope data of IODP Site U1313 covering the time period of the past 100 kyr as published in Pöppelmeier et al. (2021), <em>Geophysical Research Letters</em>. For detailed information on sampling and data processing please see Pöppelmeier et al. (2021).
DOI: 10.5281/zenodo.4705367
title: Stable Atlantic deep water mass sourcing on glacial-interglacial timescales: Nd isotope data of IODP Site U1313

description: This dataset contains neodymium isotope data of IODP Site U1313 covering the time period of the past 100 kyr as published in Pöppelmeier et al. (2021), <em>Geophysical Research Letters</em>. For detailed information on sampling and data processing please see Pöppelmeier et al. (2021).
DOI: 10.5522/04/13253906.v4
title: Healthcare use by people who use illicit opioids (HUPIO): development of a cohort based on electronic primary care records in England (extended data)

description: This dataset includes:<br><br>1. Search terms used to identify codes that may represent a history of illicit opioid use 2. Codelist for identifying people with a history of illicit opioid use 3. Age- and sex-distribution of patients by product and clinical codes 4. Number of patients currently in the cohort<br>5. Age of patients at cohort entry<br>6. Internal validation based on hospital admissions for opioid dependence
DOI: 10.5522/04/13253906.v3
title: Healthcare use by people who use illicit opioids (HUPIO): development of a cohort based on electronic primary care records in England (extended data)

description: This dataset includes:<br><br>1. Search terms used to identify codes that may represent a history of illicit opioid use 2. Codelist for identifying people with a history of illicit opioid use 3. Age- and sex-distribution of patients by product and clinical codes 4. Detailed table of mortality rates and ratios 5. Number of patients currently in the cohort 6. Age of patients at cohort entry<br>7. Internal validation based on hospital admissions for opioid dependence
DOI: 10.5281/zenodo.3764827
title: Raw data for Article "Copper-Catalyzed Oxyvinylation of Diazo Compounds"

description: Raw NMR, MS and IR data for the related publication in Organic Letters: http://dx.doi.org/10.1021/acs.orglett.0c01150 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.3764826
title: Raw data for Article "Copper-Catalyzed Oxyvinylation of Diazo Compounds"

description: Raw NMR, MS and IR data for the related publication in Organic Letters: http://dx.doi.org/10.1021/acs.orglett.0c01150 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.3775991
title: Raw data for Article "Copper-Catalyzed Oxyalkynylation of C−S Bonds in Thiiranes and Thiethanes with Hypervalent Iodine Reagents"

description: Raw data for the Article "Copper-Catalyzed Oxyalkynylation of C−S Bonds in Thiiranes and Thiethanes with Hypervalent Iodine Reagents" published in <em>Org. Lett.</em> <strong>2020</strong>, <em>22</em>, 422-427. https://pubs.acs.org/doi/pdf/10.1021/acs.orglett.9b04157 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.3775990
title: Raw data for Article "Copper-Catalyzed Oxyalkynylation of C−S Bonds in Thiiranes and Thiethanes with Hypervalent Iodine Reagents"

description: Raw data for the Article "Copper-Catalyzed Oxyalkynylation of C−S Bonds in Thiiranes and Thiethanes with Hypervalent Iodine Reagents" published in <em>Org. Lett.</em> <strong>2020</strong>, <em>22</em>, 422-427. https://pubs.acs.org/doi/pdf/10.1021/acs.orglett.9b04157 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.3894256
title: Raw Data for Article "Access to Vinyl Ethers and Ketones with Hypervalent Iodine Reagents as Oxy-Allyl Cation Synthetic Equivalents"

description: NMR, IR and MS raw data for the article "Access to Vinyl Ethers and Ketones with Hypervalent Iodine Reagents as Oxy-Allyl Cation Synthetic Equivalents" published in Angewandte Chemie in 2020, DOI: 10.1002/anie.202006707 and 10.1002/ange.202006707 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.3894255
title: Raw Data for Article "Access to Vinyl Ethers and Ketones with Hypervalent Iodine Reagents as Oxy-Allyl Cation Synthetic Equivalents"

description: NMR, IR and MS raw data for the article "Access to Vinyl Ethers and Ketones with Hypervalent Iodine Reagents as Oxy-Allyl Cation Synthetic Equivalents" published in Angewandte Chemie in 2020, DOI: 10.1002/anie.202006707 and 10.1002/ange.202006707 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.3895605
title: Raw Data for Article "Oxidative Fluorination of Cyclopropylamides via Organic Photoredox Catalysis"

description: NMR, MS and IR raw data for article "Oxidative Fluorination of Cyclopropylamides via Organic Photoredox Catalysis" published in 2020 in Angewandte Chemie: DOI: 10.1002/anie.202007864 and 10.1002/ange.202007864 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.3895604
title: Raw Data for Article "Oxidative Fluorination of Cyclopropylamides via Organic Photoredox Catalysis"

description: NMR, MS and IR raw data for article "Oxidative Fluorination of Cyclopropylamides via Organic Photoredox Catalysis" published in 2020 in Angewandte Chemie: DOI: 10.1002/anie.202007864 and 10.1002/ange.202007864 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.4194211
title: Raw data for the article "Synthesis of Thiochromans via [3+3] Annulation of Aminocyclopropanes with Thiophenols"

description: Raw NMR, MS and IR data for the article "Synthesis of Thiochromans via [3+3] Annulation of Aminocyclopropanes with Thiophenols" published in the Journal Organic Letters: https://pubs.acs.org/doi/10.1021/acs.orglett.0c03528 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.4194210
title: Raw data for the article "Synthesis of Thiochromans via [3+3] Annulation of Aminocyclopropanes with Thiophenols"

description: Raw NMR, MS and IR data for the article "Synthesis of Thiochromans via [3+3] Annulation of Aminocyclopropanes with Thiophenols" published in the Journal Organic Letters: https://pubs.acs.org/doi/10.1021/acs.orglett.0c03528 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.4279268
title: Raw data for the article "Azide Radical Initiated Ring Opening of Cyclopropenes Leading to Alkenyl Nitriles and Polycyclic Aromatic Compounds"

description: Raw NMR, MS and IR data for the article "Azide Radical Initiated Ring Opening of Cyclopropenes Leading to Alkenyl Nitriles and Polycyclic Aromatic Compounds" published in Angewandte Chemie: https://onlinelibrary.wiley.com/doi/10.1002/anie.202013516 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.4279267
title: Raw data for the article "Azide Radical Initiated Ring Opening of Cyclopropenes Leading to Alkenyl Nitriles and Polycyclic Aromatic Compounds"

description: Raw NMR, MS and IR data for the article "Azide Radical Initiated Ring Opening of Cyclopropenes Leading to Alkenyl Nitriles and Polycyclic Aromatic Compounds" published in Angewandte Chemie: https://onlinelibrary.wiley.com/doi/10.1002/anie.202013516 The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.4384417
title: Raw data for the article "Small Peptide Diversification through Photoredox-Catalyzed Oxidative C-Terminal Modification"

description: Raw IR, NMR and Mass data for the article "Small Peptide Diversification through Photoredox-Catalyzed Oxidative C-Terminal Modification" published in Chemical Science: https://doi.org/10.1039/D0SC06180H The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.5281/zenodo.4384416
title: Raw data for the article "Small Peptide Diversification through Photoredox-Catalyzed Oxidative C-Terminal Modification"

description: Raw IR, NMR and Mass data for the article "Small Peptide Diversification through Photoredox-Catalyzed Oxidative C-Terminal Modification" published in Chemical Science: https://doi.org/10.1039/D0SC06180H The number of the folders correspond to compounds numbers in the article. All details concerning conditions and equipment for measurements can be found in the supporting information of the article.
DOI: 10.15468/xsh8n7
title: Sky islands of the Cameroon Volcanic Line support the westernmost clade of five new Typoderus weevils (Coleoptera: Curculionidae: Molytinae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Grebennikov, Vasily V. (2021): Sky islands of the Cameroon Volcanic Line support the westernmost clade of five new Typoderus weevils (Coleoptera: Curculionidae: Molytinae). Arthropod Systematics & amp; Phylogeny 79: 57-74, DOI: http://dx.doi.org/10.3897/asp.79.e66021, URL: http://dx.doi.org/10.3897/asp.79.e66021
DOI: 10.15468/r72f3b
title: Grappling with homoplasy: taxonomic refinements and reassignments in the ant genera Camponotus and Colobopsis (Hymenoptera: Formicidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Ward, Philip S., Boudinot, Brendon E. (2021): Grappling with homoplasy: taxonomic refinements and reassignments in the ant genera Camponotus and Colobopsis (Hymenoptera: Formicidae). Arthropod Systematics & amp; Phylogeny 79: 37-56, DOI: http://dx.doi.org/10.3897/asp.79.e66978, URL: http://dx.doi.org/10.3897/asp.79.e66978
DOI: 10.15468/mecyjq
title: An integrative taxonomic and phylogenetic approach reveals a new Neotropical swarm-founding social wasp, Pseudopolybia cryptica sp. n. (Vespidae: Polistinae: Epiponini)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Somavilla, Alexandre, Barroso, Paulo C. S., Aragao, Marcos, Mateus, Sidnei, Menezes, Rodolpho S. T. (2021): An integrative taxonomic and phylogenetic approach reveals a new Neotropical swarm-founding social wasp, Pseudopolybia cryptica sp. n. (Vespidae: Polistinae: Epiponini). Arthropod Systematics & amp; Phylogeny 79: 25-35, DOI: http://dx.doi.org/10.3897/asp.79.e64304, URL: http://dx.doi.org/10.3897/asp.79.e64304
DOI: 10.25387/g3.14245967
title: Supplemental Material for Cvetković et al., 2021

description: Supplementary information belonging to "Phylogenomics resolves deep subfamilial relationships in Malvaceae s.l."<br>
DOI: 10.25387/g3.14245967.v1
title: Supplemental Material for Cvetković et al., 2021

description: Supplementary information belonging to "Phylogenomics resolves deep subfamilial relationships in Malvaceae s.l."<br>
DOI: 10.5517/ccdc.csd.cc25ls8v
title: CCDC 2014047: Experimental Crystal Structure Determination

description: Related Article: haiyang huang|2020|CSD Communication|||
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DOI: 10.5517/ccdc.csd.cc25ls9w
title: CCDC 2014048: Experimental Crystal Structure Determination

description: Related Article: haiyang huang|2020|CSD Communication|||
description: Related Article: Shuangshuang Xu, Haiyang Huang, Chengxiong Yuan, Fen Liu, Haixin Ding, Qiang Xiao|2021|Org.Chem.Front.|8|1747|doi:10.1039/D1QO00121C
DOI: 10.5517/ccdc.csd.cc25lsbx
title: CCDC 2014049: Experimental Crystal Structure Determination

description: Related Article: haiyang huang|2020|CSD Communication|||
description: Related Article: Shuangshuang Xu, Haiyang Huang, Chengxiong Yuan, Fen Liu, Haixin Ding, Qiang Xiao|2021|Org.Chem.Front.|8|1747|doi:10.1039/D1QO00121C
DOI: 10.5517/ccdc.csd.cc25n2jg
title: CCDC 2015295: Experimental Crystal Structure Determination

description: Related Article: Lu Wang, Pan Wang, Tianzuo Guo, Wenfang Xiong, Bangxiong Kang, Chaorong Qi, Gen Luo, Yi Luo, Huanfeng Jiang|2021|Org.Chem.Front.|8|1851|doi:10.1039/D0QO01607A
DOI: 10.5517/ccdc.csd.cc25pn8t
title: CCDC 2016806: Experimental Crystal Structure Determination

description: Related Article: Shunian Li, Haifeng Lu, Zhenghu Xu, Fang Wei|2021|Org.Chem.Front.|8|1770|doi:10.1039/D0QO01597K
DOI: 10.5517/ccdc.csd.cc25w8x8
title: CCDC 2022220: Experimental Crystal Structure Determination

description: Related Article: Su Zhou, Qianqian Liu, Ming Bao, Jie Huang, Junjian Wang, Wenhao Hu, Xinfang Xu|2021|Org.Chem.Front.|8|1808|doi:10.1039/D1QO00134E
DOI: 10.5517/ccdc.csd.cc25w92g
title: CCDC 2022225: Experimental Crystal Structure Determination

description: Related Article: Su Zhou, Qianqian Liu, Ming Bao, Jie Huang, Junjian Wang, Wenhao Hu, Xinfang Xu|2021|Org.Chem.Front.|8|1808|doi:10.1039/D1QO00134E
DOI: 10.5517/ccdc.csd.cc2664td
title: CCDC 2031703: Experimental Crystal Structure Determination

description: Related Article: Rong-Rong Zhu, Tao Wang, Lijia Zhao, Liancheng He, Feng Gao, Lin Du, Qi-Hua Zhao|2021|Inorg.Chem.Front.|8|1997|doi:10.1039/D0QI01392G
DOI: 10.5517/ccdc.csd.cc2664vf
title: CCDC 2031704: Experimental Crystal Structure Determination

description: Related Article: Rong-Rong Zhu, Tao Wang, Lijia Zhao, Liancheng He, Feng Gao, Lin Du, Qi-Hua Zhao|2021|Inorg.Chem.Front.|8|1997|doi:10.1039/D0QI01392G
DOI: 10.5517/ccdc.csd.cc2664wg
title: CCDC 2031705: Experimental Crystal Structure Determination

description: Related Article: Rong-Rong Zhu, Tao Wang, Lijia Zhao, Liancheng He, Feng Gao, Lin Du, Qi-Hua Zhao|2021|Inorg.Chem.Front.|8|1997|doi:10.1039/D0QI01392G
DOI: 10.5517/ccdc.csd.cc2664xh
title: CCDC 2031706: Experimental Crystal Structure Determination

description: Related Article: Rong-Rong Zhu, Tao Wang, Lijia Zhao, Liancheng He, Feng Gao, Lin Du, Qi-Hua Zhao|2021|Inorg.Chem.Front.|8|1997|doi:10.1039/D0QI01392G
DOI: 10.5517/ccdc.csd.cc2664yj
title: CCDC 2031707: Experimental Crystal Structure Determination

description: Related Article: Rong-Rong Zhu, Tao Wang, Lijia Zhao, Liancheng He, Feng Gao, Lin Du, Qi-Hua Zhao|2021|Inorg.Chem.Front.|8|1997|doi:10.1039/D0QI01392G
DOI: 10.5517/ccdc.csd.cc2680s9
title: CCDC 2033500: Experimental Crystal Structure Determination

description: Related Article: Kirti Singh, S. Vidhyalakshmi, Debashis Adhikari|2021|Inorg.Chem.Front.|8|2078|doi:10.1039/D0QI01466D
DOI: 10.5517/ccdc.csd.cc26g61y
title: CCDC 2039429: Experimental Crystal Structure Determination

description: Related Article: Songjin Guo, Jiayi Chen, Mingjun Yi, Liuli Dong, Aijun Lin, Hequan Yao|2021|Org.Chem.Front.|8|1783|doi:10.1039/D0QO01539C
DOI: 10.5517/ccdc.csd.cc26k936
title: CCDC 2042407: Experimental Crystal Structure Determination

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DOI: 10.5517/ccdc.csd.cc26k947
title: CCDC 2042408: Experimental Crystal Structure Determination

description: Related Article: Ricardo G. Teixeira, Dimas C. Belisario, Xavier Fontrodona, Isabel Romero, Ana Isabel Tomaz, M. Helena Garcia, Chiara Riganti, Andreia Valente|2021|Inorg.Chem.Front.|8|1983|doi:10.1039/D0QI01344G
DOI: 10.5517/ccdc.csd.cc26k958
title: CCDC 2042409: Experimental Crystal Structure Determination

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