cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.21223/fdqmre/eao1wv
title: Virus.tab
DOI: 10.21223/fdqmre/wecf7w
title: ID_Information.tab
DOI: 10.21223/fdqmre/sg2yr1
title: DataDictionary_UniqueIdentifier.tab
DOI: 10.21223/fdqmre/nhxwar
title: ID_Information.tab
DOI: 10.21223/fdqmre/yja303
title: Virus.tab
DOI: 10.21223/fdqmre/jjwffz
title: ID_Information.tab
DOI: 10.6084/m9.figshare.9805547.v1
title: Transformation and Additivity in Gaussian Processes

description: We discuss the problem of approximating a deterministic function using Gaussian processes (GPs). The role of transformation in GP modeling is not well understood. We argue that transformation of the response can be used for making the deterministic function approximately additive, which can then be easily estimated using an additive GP. We call such a GP a transformed additive Gaussian (TAG) process. To capture possible interactions which are unaccounted for in an additive model, we propose an extension of the TAG process called transformed approximately additive Gaussian (TAAG) process. We develop efficient techniques for fitting a TAAG process. In fact, we show that it can be fitted to high-dimensional data much more efficiently than a standard GP. Furthermore, we show that the use of the TAAG process leads to better estimation, interpretation, visualization, and prediction. The proposed methods are implemented in the R package <i>TAG</i>.
DOI: 10.6084/m9.figshare.9805547
title: Transformation and Additivity in Gaussian Processes

description: We discuss the problem of approximating a deterministic function using Gaussian processes (GPs). The role of transformation in GP modeling is not well understood. We argue that transformation of the response can be used for making the deterministic function approximately additive, which can then be easily estimated using an additive GP. We call such a GP a transformed additive Gaussian (TAG) process. To capture possible interactions which are unaccounted for in an additive model, we propose an extension of the TAG process called transformed approximately additive Gaussian (TAAG) process. We develop efficient techniques for fitting a TAAG process. In fact, we show that it can be fitted to high-dimensional data much more efficiently than a standard GP. Furthermore, we show that the use of the TAAG process leads to better estimation, interpretation, visualization, and prediction. The proposed methods are implemented in the R package <i>TAG</i>.
DOI: 10.6084/m9.figshare.9883070
title: Statistical Modeling of Multivariate Destructive Degradation Tests With Blocking

description: In degradation tests, the test units are usually divided into several groups, with each group tested simultaneously in a test rig. Each rig constitutes a rig-layer block from the perspective of design of experiments. Within each rig, the test units measured at the same time further form a gauge-layer block. Due to the uncontrollable factors among test rigs and the common errors incurred for each measurement, the degradation measurements of the test units may differ among various blocks. On the other hand, the degradation should be more homogeneous within a block. Motivated by an application of emerging contaminants (ECs), this study proposes a multivariate statistical model to account for the two-layer block effects in destructive degradation tests. A multivariate Wiener process is first used to model the correlation among different dimensions of degradation. The rig-layer block effect is modeled by a one-dimensional frailty motivated by the degradation physics, while the gauge-layer block effect at each measurement epoch is captured by a common additive measurement error. We develop an expectation-maximization algorithm to obtain the point estimates of the model parameters and construct confidence intervals for the parameters. A procedure is proposed to test significance of the block effects in the degradation data. Through a case study on an EC degradation dataset, we show the existence of the two-layer block effects from the test. By making use of the proposed model, decision makers can readily make risk assessment of each contaminant and determine the minimal water treatment time for removal of the contaminants. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9883070.v2
title: Statistical Modeling of Multivariate Destructive Degradation Tests With Blocking

description: In degradation tests, the test units are usually divided into several groups, with each group tested simultaneously in a test rig. Each rig constitutes a rig-layer block from the perspective of design of experiments. Within each rig, the test units measured at the same time further form a gauge-layer block. Due to the uncontrollable factors among test rigs and the common errors incurred for each measurement, the degradation measurements of the test units may differ among various blocks. On the other hand, the degradation should be more homogeneous within a block. Motivated by an application of emerging contaminants (ECs), this study proposes a multivariate statistical model to account for the two-layer block effects in destructive degradation tests. A multivariate Wiener process is first used to model the correlation among different dimensions of degradation. The rig-layer block effect is modeled by a one-dimensional frailty motivated by the degradation physics, while the gauge-layer block effect at each measurement epoch is captured by a common additive measurement error. We develop an expectation-maximization algorithm to obtain the point estimates of the model parameters and construct confidence intervals for the parameters. A procedure is proposed to test significance of the block effects in the degradation data. Through a case study on an EC degradation dataset, we show the existence of the two-layer block effects from the test. By making use of the proposed model, decision makers can readily make risk assessment of each contaminant and determine the minimal water treatment time for removal of the contaminants. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9855845.v3
title: Adaptive Minimum Confidence Region Rule for Multivariate Initialization Bias Truncation in Discrete-Event Simulations

description: Initialization bias truncation is critically important for system performance assessment and warm-up length estimation in discrete-event simulations. Most of the existing methods are for univariate signals, while multivariate truncation has been rarely studied. To fill such gap, this article proposes an efficient method, called adaptive minimum confidence region rule (AMCR) for multivariate initialization bias truncation. It determines the truncation point by minimizing the modified confidence volume with a tuning parameter for the mean estimate. An elbow method is developed for adaptive selection of the tuning parameter. Theoretical properties of the AMCR rule for both data with and without autocorrelations have been derived for justification and practical guidance. The effectiveness and superiority of the AMCR rule over other existing approaches have been demonstrated through thorough numerical studies and real application. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9883070.v1
title: Statistical Modeling of Multivariate Destructive Degradation Tests with Blocking

description: In degradation tests, the test units are usually divided into several groups, with each group tested simultaneously in a test rig. Each rig constitutes a rig-layer block from the perspective of design of experiments. Within each rig, the test units measured at the same time further form a gauge-layer block. Due to the uncontrollable factors among test rigs and the common errors incurred for each measurement, the degradation measurements of the test units may differ among various blocks. On the other hand, the degradation should be more homogeneous within a block. Motivated by an application of emerging contaminants (ECs), this study proposes a multivariate statistical model to account for the two-layer block effects in destructive degradation tests. A multivariate Wiener process is first used to model the correlation among different dimensions of degradation. The rig-layer block effect is modeled by a one-dimensional frailty motivated by the degradation physics, while the gauge-layer block effect at each measurement epoch is captured by a common additive measurement error. We develop an Expectation-Maximization (EM) algorithm to obtain the point estimates of the model parameters and construct confidence intervals for the parameters. A procedure is proposed to test significance of the block effects in the degradation data. Through a case study on an EC degradation dataset, we show the existence of the two-layer block effects from the test. By making use of the proposed model, decision makers can readily make risk assessment of each contaminant and determine the minimal water treatment time for removal of the contaminants.
DOI: 10.6084/m9.figshare.9855845
title: Adaptive Minimum Confidence Region Rule for Multivariate Initialization Bias Truncation in Discrete-Event Simulations

description: Initialization bias truncation is critically important for system performance assessment and warm-up length estimation in discrete-event simulations. Most of the existing methods are for univariate signals, while multivariate truncation has been rarely studied. To fill such gap, this article proposes an efficient method, called adaptive minimum confidence region rule (AMCR) for multivariate initialization bias truncation. It determines the truncation point by minimizing the modified confidence volume with a tuning parameter for the mean estimate. An elbow method is developed for adaptive selection of the tuning parameter. Theoretical properties of the AMCR rule for both data with and without autocorrelations have been derived for justification and practical guidance. The effectiveness and superiority of the AMCR rule over other existing approaches have been demonstrated through thorough numerical studies and real application. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.9855845.v2
title: Adaptive Minimal Confidence Region Rule for Multivariate Initialization Bias Truncation in Discrete-Event Simulations

description: Initialization bias truncation is critically important for system performance assessment and warm-up length estimation in discrete-event simulations. Most of the existing methods are for univariate signals, while multivariate truncation has been rarely studied. To fill such gap, this article proposes an efficient method, called adaptive minimal confidence region rule (AMCR) for multivariate initialization bias truncation. It determines the truncation point by minimizing the modified confidence volume with a tuning parameter for the mean estimate. An elbow method is developed for adaptive selection of the tuning parameter. Theoretical properties of the AMCR rule for both data with and without autocorrelations have been derived for justification and practical guidance. The effectiveness and superiority of the AMCR rule over other existing approaches have been demonstrated through thorough numerical studies and real application. Supplementary materials for this article are available online.
DOI: 10.23641/asha.13133018
title: Malapropisms and children with hearing loss (Lowenstein & Nittrouer, 2020)

description: <b>Purpose:</b> Better auditory prostheses and earlier interventions have led to remarkable improvements in spoken language abilities for children with hearing loss (HL), but these children often still struggle academically. This study tested a hypothesis for why this may be, proposing that the language of school becomes increasingly disconnected from everyday discourse, requiring greater reliance on bottom-up phonological structure, and children with HL have difficulty recovering that structure from the speech signal.<b>Participants: </b>One hundred nineteen fourth graders participated: 48 with normal hearing (NH), 19 with moderate losses who used hearing aids (HAs), and 52 with severe-to-profound losses who used cochlear implants (CIs).<b>Method: </b>Three analyses were conducted. <b>#1:</b> Sentences with malapropisms were created, and children’s abilities to recognize them were assessed. <b>#2:</b> Factors contributing to those abilities were evaluated, including phonological awareness, phonological processing, vocabulary, verbal working memory, and oral narratives. <b>#3:</b> Teachers’ ratings of students’ academic competence were obtained, and factors accounting for those ratings were evaluated, including the five listed above, along with word reading and reading comprehension.<b>Results: #1: </b>Children with HAs and CIs performed more poorly on malapropism recognition than children with NH, but similarly to each other.<b> #2: </b>All children with HL demonstrated large phonological deficits, but they were especially large for children with CIs. Phonological awareness explained the most variance in malapropism recognition for children with CIs. Vocabulary knowledge explained malapropism recognition for children with NH or HAs, but other factors also contributed. <b>#3: </b>Teachers rated academic competence for children with CIs more poorly than for children with NH or HAs, and variance in those ratings for children with CIs were primarily explained by malapropism scores.<b>Conclusion:</b> Children with HL have difficulty recognizing acoustic–phonetic detail in the speech signal, and that constrains their abilities to follow conversations in academic settings, especially if HL is severe enough to require CIs.<br><b>Supplemental Material S1.</b> Pearson product-moment correlation coefficients for pairs of dependent measures computed for children with normal hearing (NH).<br><b>Supplemental Material S2.</b> Pearson product-moment correlation coefficients for pairs of dependent measures computed for children with hearing aids (HAs).<br><b>Supplemental Material S3. </b>Pearson product-moment correlation coefficients for pairs of dependent measures computed for children with cochlear implants (CIs).<br>Lowenstein, J. H., & Nittrouer, S. (2020). The devil in the details can be hard to spot: Malapropisms and children with hearing loss. <i>Language, Speech, and Hearing Services in Schools.</i> Advance online publication. https://doi.org/10.1044/2020_LSHSS-20-00033
DOI: 10.23641/asha.13133018.v1
title: Malapropisms and children with hearing loss (Lowenstein & Nittrouer, 2020)

description: <b>Purpose:</b> Better auditory prostheses and earlier interventions have led to remarkable improvements in spoken language abilities for children with hearing loss (HL), but these children often still struggle academically. This study tested a hypothesis for why this may be, proposing that the language of school becomes increasingly disconnected from everyday discourse, requiring greater reliance on bottom-up phonological structure, and children with HL have difficulty recovering that structure from the speech signal.<b>Participants: </b>One hundred nineteen fourth graders participated: 48 with normal hearing (NH), 19 with moderate losses who used hearing aids (HAs), and 52 with severe-to-profound losses who used cochlear implants (CIs).<b>Method: </b>Three analyses were conducted. <b>#1:</b> Sentences with malapropisms were created, and children’s abilities to recognize them were assessed. <b>#2:</b> Factors contributing to those abilities were evaluated, including phonological awareness, phonological processing, vocabulary, verbal working memory, and oral narratives. <b>#3:</b> Teachers’ ratings of students’ academic competence were obtained, and factors accounting for those ratings were evaluated, including the five listed above, along with word reading and reading comprehension.<b>Results: #1: </b>Children with HAs and CIs performed more poorly on malapropism recognition than children with NH, but similarly to each other.<b> #2: </b>All children with HL demonstrated large phonological deficits, but they were especially large for children with CIs. Phonological awareness explained the most variance in malapropism recognition for children with CIs. Vocabulary knowledge explained malapropism recognition for children with NH or HAs, but other factors also contributed. <b>#3: </b>Teachers rated academic competence for children with CIs more poorly than for children with NH or HAs, and variance in those ratings for children with CIs were primarily explained by malapropism scores.<b>Conclusion:</b> Children with HL have difficulty recognizing acoustic–phonetic detail in the speech signal, and that constrains their abilities to follow conversations in academic settings, especially if HL is severe enough to require CIs.<br><b>Supplemental Material S1.</b> Pearson product-moment correlation coefficients for pairs of dependent measures computed for children with normal hearing (NH).<br><b>Supplemental Material S2.</b> Pearson product-moment correlation coefficients for pairs of dependent measures computed for children with hearing aids (HAs).<br><b>Supplemental Material S3. </b>Pearson product-moment correlation coefficients for pairs of dependent measures computed for children with cochlear implants (CIs).<br>Lowenstein, J. H., & Nittrouer, S. (2020). The devil in the details can be hard to spot: Malapropisms and children with hearing loss. <i>Language, Speech, and Hearing Services in Schools.</i> Advance online publication. https://doi.org/10.1044/2020_LSHSS-20-00033
DOI: 10.25345/c5bf50
title: MassIVE MSV000086377 - erythrocyte membrane microdomains
title: Cholesterol-rich microdomains are membrane dynamic compartments characterized by specific lipid and protein composition and present in all cell types. These assemblies are involved in several biological processes, including infection by intracellular pathogens. This work provides a comprehensive analysis of the composition and organization of human erythrocyte membrane microdomains
DOI: 10.5281/zenodo.4147757
title: Data directly used

description: If you have any questions, please contact me by skatetangshan@vip.126.com
DOI: 10.5281/zenodo.4147756
title: Data directly used

description: If you have any questions, please contact me by skatetangshan@vip.126.com
DOI: 10.6084/m9.figshare.13157510
title: Keystroke timing information for 2,522,186 characters typed over several months

description: Keystroke dynamics for one user for 2.5M characters typed over several months. Consists of one text file, each line being a typed character, and a Unix time stamp. For privacy reasons the characters typed are randomly mapped to another character, same mapping across the whole dataset, so timing information for bigrams and trigrams can be extracted but not mapped to actual typed characters.<br>
DOI: 10.25387/g3.13157519.v1
title: Supplemental Material for Sanders et al., 2020

description: Supplemental Files S1 - S4. <br>
DOI: 10.25387/g3.13157519
title: Supplemental Material for Sanders et al., 2020

description: Supplemental Files S1 - S4. <br>
DOI: 10.6069/7bw0-7b70
title: Improving Methods to Measure Comparable Mortality by Cause - Gold Standard Verbal Autopsy Data 2011-2014

description: These data were collected and compiled as part of the Improving Methods to Measure Comparable Mortality by Cause (IMMCMC) project, funded by Australia's National Health and Medical Research Council (NHMRC). Verbal autopsies (VAs) were conducted between 2011 and 2014 in three sites: Bohol, Philippines; Chandpur and Comila Districts, Bangladesh; and Central and Eastern Highlands Provinces, Papua New Guinea. Diagnostic criteria and cause lists similar to those employed in the Population Health Metrics Research Consortium (PHMRC) study were used to identify gold standard (GS) deaths. This study added 3512 deaths (2491 adults, 320 children, and 701 neonates) to the GS VA database created from the PHMRC study. This dataset contains the combined PHMRC and IMMCMC data for an updated GS VA database.
DOI: 10.13012/b2idb-6081616_v1
title: Phylogenomics of the North American Plecoptera

description: This dataset contains the amino acid and nucleotide alignments corresponding to the phylogenetic analyses of South et al. 2020 in Systematic Entomology. This dataset also includes the gene trees that were used as input for coalescent analysis in ASTRAL.
DOI: 10.17632/4rj7k22wh6.11
title: Data for: From deforestation to afforestation: Effect of slopeland use policies on land use/cover change in Taiwan

description: slopeland land-use change in Taiwan
DOI: 10.17632/pyxd8t5js5.11
title: Data for: From deforestation to afforestation: Effect of slopeland use policies on land use/cover change in Taiwan

description: This data contains SPSS and GIS files, which regards the information of slopland in Taiwan.
DOI: 10.25345/c56n32
title: MassIVE MSV000086378 - Pseudomonas aeruginosa PA14 biofilms produce R-bodies, extendable protein polymers with roles in host colonization and virulence
title: Pseudomonas aeruginosa PA14 biofilms produce R-bodies, extendable protein polymers with roles in host colonization and virulence Bryan Wang,1 Yu-Cheng Lin,1 Jeanyoung Jo,1 Alexa Price-Whelan,1 Shujuan Tao McDonald, 1,2 Lewis M. Brown1,2, and Lars E.P. Dietrich1
DOI: 10.6084/m9.figshare.13157576
title: Sniffles SV call set for HC1-N and HC1-T

description: PacBio CLR reads were mapped to the HC1-N genome using NGMLR under default settings. SV calling was performed using Sniffles with minimum support at 2 (-s) and minimum length at 30 (-l). We filtered the SVs to obtain the final call set based on the following criteria: 1) SV that are within 50bp of a genome assembly gap, 2) minimum SV length was set to 50, and 3) minimum read support was set to 10. To obtain HC1-T specific call set, we filtered SVs that were found in HC1-N call set within 1000bp.
DOI: 10.6084/m9.figshare.13157576.v1
title: Sniffles SV call set for HC1-N and HC1-T

description: PacBio CLR reads were mapped to the HC1-N genome using NGMLR under default settings. SV calling was performed using Sniffles with minimum support at 2 (-s) and minimum length at 30 (-l). We filtered the SVs to obtain the final call set based on the following criteria: 1) SV that are within 50bp of a genome assembly gap, 2) minimum SV length was set to 50, and 3) minimum read support was set to 10. To obtain HC1-T specific call set, we filtered SVs that were found in HC1-N call set within 1000bp.
DOI: 10.6084/m9.figshare.13154429
title: mtDNA-supp-info

description: Haplotype table assignment mtDNA Cleveland Bay Horse
DOI: 10.6084/m9.figshare.13154429.v1
title: mtDNA-supp-info

description: Haplotype table assignment mtDNA Cleveland Bay Horse
DOI: 10.5281/zenodo.4147720
title: Idealista Real State property research

description: Property price research in Oviedo Asturias, carried out with Selenium and Python
DOI: 10.5281/zenodo.4147719
title: Idealista Real State property research

description: Property price research in Oviedo Asturias, carried out with Selenium and Python
DOI: 10.21227/dz92-zq33
title: Brazilian Flights Dataset

description: This webpage provides information about the Brazilian Flight Dataset (BFD). The description includes the data sources from regular flights (VRA) and weather data. The VRA is provided by ANAC (Agência Nacional de Aviação Civil) and contains all Brazilian flights. The weather data is provided by ASOS (Automated Surface Observing Systems). ASOS is managed by IOWA University (USA). It contains weather data collected by sensors installed at airports around the world.