cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.5778165
title: Bayesian PTSD-Trajectory Analysis with Informed Priors Based on a Systematic Literature Search and Expert Elicitation

description: There is a recent increase in interest of Bayesian analysis. However, little effort has been made thus far to directly incorporate background knowledge via the prior distribution into the analyses. This process might be especially useful in the context of latent growth mixture modeling when one or more of the latent groups are expected to be relatively small due to what we refer to as <i>limited data</i>. We argue that the use of Bayesian statistics has great advantages in limited data situations, but only if background knowledge can be incorporated into the analysis via prior distributions. We highlight these advantages through a data set including patients with burn injuries and analyze trajectories of posttraumatic stress symptoms using the Bayesian framework following the steps of the WAMBS-checklist. In the included example, we illustrate how to obtain background information using previous literature based on a systematic literature search and by using expert knowledge. Finally, we show how to translate this knowledge into prior distributions and we illustrate the importance of conducting a prior sensitivity analysis. Although our example is from the trauma field, the techniques we illustrate can be applied to any field.
DOI: 10.6084/m9.figshare.5778159
title: Bayesian Diagnostics of Hidden Markov Structural Equation Models with Missing Data

description: Cocaine is a type of drug that functions to increase the availability of the neurotransmitter dopamine in the brain. However, cocaine dependence or abuse is highly related to an increased risk of psychiatric disorders and deficits in cognitive performance, attention, and decision-making abilities. Given the chronic and persistent features of drug addiction, the progression of abstaining from cocaine often evolves across several states, such as addiction to, moderate dependence on, and swearing off cocaine. Hidden Markov models (HMMs) are well suited to the characterization of longitudinal data in terms of a set of unobservable states, and have increasingly been used to uncover the dynamic heterogeneity in progressive diseases or activities. However, the existence of outliers or influential points may misidentify the hidden states and distort the associated inference. In this study, we develop a Bayesian local influence procedure for HMMs with latent variables in the presence of missing data. The proposed model enables us to investigate the dynamic heterogeneity of multivariate longitudinal data, reveal how the interrelationships among latent variables change from one state to another, and simultaneously conduct statistical diagnosis for the given data, model assumptions, and prior inputs. We apply the proposed procedure to analyze a dataset collected by the UCLA center for advancing longitudinal drug abuse research. Several outliers or influential points that seriously influence estimation results are identified and removed. The proposed procedure also discovers the effects of treatment and individuals’ psychological problems on cocaine use behavior and delineates their dynamic changes across the cocaine-addiction states.
DOI: 10.6084/m9.figshare.5778159.v2
title: Bayesian Diagnostics of Hidden Markov Structural Equation Models with Missing Data

description: Cocaine is a type of drug that functions to increase the availability of the neurotransmitter dopamine in the brain. However, cocaine dependence or abuse is highly related to an increased risk of psychiatric disorders and deficits in cognitive performance, attention, and decision-making abilities. Given the chronic and persistent features of drug addiction, the progression of abstaining from cocaine often evolves across several states, such as addiction to, moderate dependence on, and swearing off cocaine. Hidden Markov models (HMMs) are well suited to the characterization of longitudinal data in terms of a set of unobservable states, and have increasingly been used to uncover the dynamic heterogeneity in progressive diseases or activities. However, the existence of outliers or influential points may misidentify the hidden states and distort the associated inference. In this study, we develop a Bayesian local influence procedure for HMMs with latent variables in the presence of missing data. The proposed model enables us to investigate the dynamic heterogeneity of multivariate longitudinal data, reveal how the interrelationships among latent variables change from one state to another, and simultaneously conduct statistical diagnosis for the given data, model assumptions, and prior inputs. We apply the proposed procedure to analyze a dataset collected by the UCLA center for advancing longitudinal drug abuse research. Several outliers or influential points that seriously influence estimation results are identified and removed. The proposed procedure also discovers the effects of treatment and individuals’ psychological problems on cocaine use behavior and delineates their dynamic changes across the cocaine-addiction states.
DOI: 10.6084/m9.figshare.5778159.v1
title: Bayesian Diagnostics of Hidden Markov Structural Equation Models with Missing Data

description: Cocaine is a type of drug that functions to increase the availability of the neurotransmitter dopamine in the brain. However, cocaine dependence or abuse is highly related to an increased risk of psychiatric disorders and deficits in cognitive performance, attention, and decision-making abilities. Given the chronic and persistent features of drug addiction, the progression of abstaining from cocaine often evolves across several states, such as addiction to, moderate dependence on, and swearing off cocaine. Hidden Markov models (HMMs) are well suited to the characterization of longitudinal data in terms of a set of unobservable states, and have increasingly been used to uncover the dynamic heterogeneity in progressive diseases or activities. However, the existence of outliers or influential points may misidentify the hidden states and distort the associated inference. In this study, we develop a Bayesian local influence procedure for HMMs with latent variables in the presence of missing data. The proposed model enables us to investigate the dynamic heterogeneity of multivariate longitudinal data, reveal how the interrelationships among latent variables change from one state to another, and simultaneously conduct statistical diagnosis for the given data, model assumptions, and prior inputs. We apply the proposed procedure to analyze a dataset collected by the UCLA center for advancing longitudinal drug abuse research. Several outliers or influential points that seriously influence estimation results are identified and removed. The proposed procedure also discovers the effects of treatment and individuals’ psychological problems on cocaine use behavior and delineates their dynamic changes across the cocaine-addiction states.
DOI: 10.6084/m9.figshare.5778117
title: Calibration of the IRR

description: Measure the step width with a wearable system composed by ad infrared range sensor, a screen and an inertual measuremetn unit
DOI: 10.6084/m9.figshare.5778117.v1
title: Calibration of the IRR

description: Measure the step width with a wearable system composed by ad infrared range sensor, a screen and an inertual measuremetn unit
DOI: 10.6084/m9.figshare.5778114
title: Final results

description: Measure the step width with a wearable system composed by ad infrared range sensor, a screen and an inertual measuremetn unit
DOI: 10.6084/m9.figshare.5778114.v1
title: Final results

description: Measure the step width with a wearable system composed by ad infrared range sensor, a screen and an inertual measuremetn unit
DOI: 10.6084/m9.figshare.5778048
title: An Introduction to Kristof’s Theorem for Solving Least-Square Optimization Problems <i>Without</i> Calculus

description: Kristof’s Theorem (Kristof, 1970) describes a matrix trace inequality that can be used to solve a wide-class of least-square optimization problems without calculus. Considering its generality, it is surprising that Kristof’s Theorem is rarely used in statistics and psychometric applications. The underutilization of this method likely stems, in part, from the mathematical complexity of Kristof’s (1964, 1970) writings. In this article, I describe the underlying logic of Kristof’s Theorem in simple terms by reviewing four key mathematical ideas that are used in the theorem’s proof. I then show how Kristof’s Theorem can be used to provide novel derivations to two cognate models from statistics and psychometrics. This tutorial includes a glossary of technical terms and an online supplement with R (R Core Team, 2017) code to perform the calculations described in the text.
DOI: 10.6084/m9.figshare.5778048.v1
title: An Introduction to Kristof’s Theorem for Solving Least-Square Optimization Problems <i>Without</i> Calculus

description: Kristof’s Theorem (Kristof, 1970) describes a matrix trace inequality that can be used to solve a wide-class of least-square optimization problems without calculus. Considering its generality, it is surprising that Kristof’s Theorem is rarely used in statistics and psychometric applications. The underutilization of this method likely stems, in part, from the mathematical complexity of Kristof’s (1964, 1970) writings. In this article, I describe the underlying logic of Kristof’s Theorem in simple terms by reviewing four key mathematical ideas that are used in the theorem’s proof. I then show how Kristof’s Theorem can be used to provide novel derivations to two cognate models from statistics and psychometrics. This tutorial includes a glossary of technical terms and an online supplement with R (R Core Team, 2017) code to perform the calculations described in the text.
DOI: 10.6084/m9.figshare.5778045
title: agu-poster-2017-wcs-v4.pdf

description: NASA’s Earth Observing System Data and Information System (EOSDIS) is evolving to expose data using standards based geospatial web services, e.g. Web Coverage Service (WCS), Web Mapping Service (WMS). There is a need for fusion of services with existing data systems, and integration with new systems such as NASA’s Cumulus, which will be a cloud-based source of NASA data.
DOI: 10.6084/m9.figshare.5778045.v1
title: agu-poster-2017-wcs-v4.pdf

description: NASA’s Earth Observing System Data and Information System (EOSDIS) is evolving to expose data using standards based geospatial web services, e.g. Web Coverage Service (WCS), Web Mapping Service (WMS). There is a need for fusion of services with existing data systems, and integration with new systems such as NASA’s Cumulus, which will be a cloud-based source of NASA data.
DOI: 10.6084/m9.figshare.5778024
title: Zimbabwe 2016 Health Professionals Survey.dta

description: This dataset provides estimates from 118 experts who are knowledgeable about induced abortion provision in Zimbabwe. For each residential (urban and rural) and poverty (poor and nonpoor) group, respondents gave estimates about the share of different types of abortions (surgical, misoprostol and other) performed by various types of providers (doctors, nurses, pharmacists, traditional providers, women themselves); the proportion from each provider and method that will result in complications; and the proportion of women who will seek treatment for her complications. This dataset also includes information on respondents' knowledge and attitudes toward the abortion law.<br><b>Residential and poverty groups</b> up = urban poor women unp = urban nonpoor women rp = rural poor women rnp = rural nonpoor women <b>Types of abortion</b> m = misoprostol s = surgical abortion o = other types of abortion <b>Provider performing abortion</b> dr = medical doctor nurse = nurse/midwife trad = traditional provider (anyone without formal training) pharm = pharmacists self = woman herself (self-induced abortion)<br>
DOI: 10.6084/m9.figshare.5778024.v1
title: Zimbabwe 2016 Health Professionals Survey.dta

description: This dataset provides estimates from 118 experts who are knowledgeable about induced abortion provision in Zimbabwe. For each residential (urban and rural) and poverty (poor and nonpoor) group, respondents gave estimates about the share of different types of abortions (surgical, misoprostol and other) performed by various types of providers (doctors, nurses, pharmacists, traditional providers, women themselves); the proportion from each provider and method that will result in complications; and the proportion of women who will seek treatment for her complications. This dataset also includes information on respondents' knowledge and attitudes toward the abortion law.<br><b>Residential and poverty groups</b> up = urban poor women unp = urban nonpoor women rp = rural poor women rnp = rural nonpoor women <b>Types of abortion</b> m = misoprostol s = surgical abortion o = other types of abortion <b>Provider performing abortion</b> dr = medical doctor nurse = nurse/midwife trad = traditional provider (anyone without formal training) pharm = pharmacists self = woman herself (self-induced abortion)<br>
DOI: 10.6084/m9.figshare.5778021
title: Zimbabwe 2016 Health Facility Survey.dta

description: This dataset contains estimates of the number of post-abortion care (PAC) cases treated annually from a national census of health facilities with PAC capacity, as well as some indicators of quality of care provided at the same facilities. It also includes the facility type, region, and weights, as well as respondents' knowledge of the abortion law.
DOI: 10.6084/m9.figshare.5778021.v1
title: Zimbabwe 2016 Health Facility Survey.dta

description: This dataset contains estimates of the number of post-abortion care (PAC) cases treated annually from a national census of health facilities with PAC capacity, as well as some indicators of quality of care provided at the same facilities. It also includes the facility type, region, and weights, as well as respondents' knowledge of the abortion law.
DOI: 10.6084/m9.figshare.5777940.v1
title: DacaletalResDATA

description: Code and data used in the analyses for Dacal et al. paper that assess thermal adaptation of soil microbial respiration.
DOI: 10.6084/m9.figshare.5777940.v2
title: Data from "Soil microbial respiration adapts to ambient temperature in global drylands"

description: R code and Data from "Dacal, M., Bradford, M. A., Plaza, C., Maestre, F. T. & García- Palacios, P. Soil microbial respiration adapts to ambient temperature in global drylands. Nature Ecology and Evolution. DOI: https://doi.org/10.1038/s41559-018-0770-5 "<br>There are two items: the first one contains the R code (DacaletalResDATA.txt) whereas the second one has the data (DacaletalResDATA.xslx). In the latter item there are two spreadsheets. The spreadsheet "DATA" contains the raw data at a microsite scale. The spreadsheet "METADATA" contains the associated metadata, where a description of all the variables and units can be found. All the methodological details can be found in the article.
DOI: 10.6084/m9.figshare.5777907
title: GFDL-CM3 Regional-Aerosol Simulations

description: Precipitation data from historical experiments (1860-2005) with the coupled model GFDL-CM3. Original data resolution 1x2.5, regridded here to 2.5x2.5. CMIP5 standard single-forcing experiments with anthropogenic aerosols (AA), greenhouse gases (GHG), and natural forcings (volcanic and solar; NAT) (3 members each); all-forcing experiment (ALL, 5 members), and 4 regional-aerosol experiments (3 members each), forced with different combinations of time-evolving anthropogenic aerosol emissions (i.e., all other forcings are kept at pre-industrial levels). Three of the ensembles have global time-varying historical emissions with the exception of those from (1) North America and Europe (PIAE, in the publication NoNAEU), (2) South Asia (PISA, in the publication NoSA), or (3) China (PICH, in the publication NoCH) fixed at pre-industrial levels. The fourth experiment has historical aerosol emissions for South Asia only and pre-industrial aerosol emissions in the rest of the world (PIRW, in the publication SAonly). For definitions of the regions see reference:<br><br>Undorf, S., D. Polson, M. Bollasina, Y. Ming, A. Schurer, and G. C. Hegerl, 2018: Detectable impact of local and remote anthropogenic aerosols on the 20th century changes of West African and South Asian monsoon precipitation. J. Geophys. Res.<br><br>When using these data, please ensure to acknowledge NOAA GFDL.<br>
DOI: 10.6084/m9.figshare.5777907.v1
title: GFDL-CM3 Regional-Aerosol Simulations

description: Precipitation data from historical experiments (1860-2005) with the coupled model GFDL-CM3. Original data resolution 1x2.5, regridded here to 2.5x2.5. CMIP5 standard single-forcing experiments with anthropogenic aerosols (AA), greenhouse gases (GHG), and natural forcings (volcanic and solar; NAT) (3 members each); all-forcing experiment (ALL, 5 members), and 4 regional-aerosol experiments (3 members each), forced with different combinations of time-evolving anthropogenic aerosol emissions (i.e., all other forcings are kept at pre-industrial levels). Three of the ensembles have global time-varying historical emissions with the exception of those from (1) North America and Europe (PIAE, in the publication NoNAEU), (2) South Asia (PISA, in the publication NoSA), or (3) China (PICH, in the publication NoCH) fixed at pre-industrial levels. The fourth experiment has historical aerosol emissions for South Asia only and pre-industrial aerosol emissions in the rest of the world (PIRW, in the publication SAonly). For definitions of the regions see reference:<br><br>Undorf, S., D. Polson, M. Bollasina, Y. Ming, A. Schurer, and G. C. Hegerl, 2018: Detectable impact of local and remote anthropogenic aerosols on the 20th century changes of West African and South Asian monsoon precipitation. J. Geophys. Res.<br><br>When using these data, please ensure to acknowledge NOAA GFDL.<br>
DOI: 10.6084/m9.figshare.5777790
title: datasets for rules

description: <b>BirhtPlace and Genre</b> <b>datasets</b> used in the experiments presented in the paper under review.Source code is available at https://github.com/lgi2p/TDwithRULES
DOI: 10.6084/m9.figshare.5777790.v1
title: datasets for rules

description: <b>BirhtPlace and Genre</b> <b>datasets</b> used in the experiments presented in the paper under review.Source code is available at https://github.com/lgi2p/TDwithRULES
DOI: 10.25377/sussex.5777712
title: Dataset for Paper: High-energy terahertz surface optical rectification

description: <b>Data for a research paper published in Nano Energy April 2018</b><br> The data provided is the data used to compile each of the 10 figures in the research paper. The .txt files contain the variables for the measured raw data contained in the related .mat file.The format of the raw data is .mat - MATLAB binary -v7, which is compatible and portable to GNU Octave version &gt;4.0 (tested). You will need access to the Matlab environment or GNU Octave environment to view these files.<br><b>Abstract</b>The interest in surface terahertz emitters lies in their extremely thin active region, typically hundreds of atomic layers, and the agile surface scalability. The ultimate limit in the achievable emission is determined by the saturation of the several different mechanisms concurring to the THz frequency conversion. Although there is a very prolific debate about the contribution of each process, surface optical rectification has been highlighted as the dominant process at high excitation, but the effective limits in the conversion are largely unknown.The current state of the art suggests that in field-induced optical rectification a maximum limit of the emission may exist and it is ruled by the photocarrier induced neutralisation of the medium's surface field. This would represent the most important impediment to the application of surface optical rectification in high-energy THz emitters.We experimentally unveil novel physical insights in the THz conversion at high excitation energies mediated by the ultrafast surface optical rectification process. The main finding is that the expected total saturation of the Terahertz emission vs pump energy does not actually occur. At high energy, the surface field region contracts towards the surface. We argue that this mechanism weakens the main saturation process, re-establishing a clearly observable quadratic dependence between the emitted THz energy and the excitation. This is relevant in enabling access to intense generation at high fluences.<br>
DOI: 10.25377/sussex.5777712.v1
title: DataSet of Paper by Peters et al, submitted to NanoEnergy (2017)

description: Data for a research paper in publication in Nanoenergy. Details of the paper will be disclosed in due time. The data provided is the data used to compile each of the 10 figures in the research paper. The .txt files contain the variables for the measured raw data contained in the related .mat file.The format of the raw data is .mat - MATLAB binary -v7, which is compatible and portable to GNU Octave version &gt;4.0 (tested). You will need access to the Matlab environment or GNU Octave environment to view these files.<br>
DOI: 10.6084/m9.figshare.5777646
title: Affordances for Drinking Alcohol: A Non-Participant Observation Study in Licensed Premises

description: This folder contains the research data related to the publication: Hill, Pilling & Foxcroft, Affordances for Drinking Alcohol A Non-Participant Observation Study in Licensed Premises.<br><br>This includes confirmation of ethical approval, observational protocol, data, reports and the analysis; as well as the visual maps.<br><br>This data and research materials are anonymised, but include in-depth, qualitative and sensitive information, including the identification and illustration of specific properties of alcogenic environments. This is why the data and related materials will not be publicly accessible.<br><br><br>
DOI: 10.6084/m9.figshare.12746531
title: Data for "Spectral characteristics of neutron bursts by cosmic ray showers and implications for terrestrial gamma-ray flash (TGF) signatures"

description: This is the raw data used to produce figure 2. in "Spectral characteristics of neutron bursts by cosmic ray showers and implications for terrestrial gamma-ray flash (TGF) signatures"
DOI: 10.6084/m9.figshare.5777583
title: Residual symptoms and disease burden among patients with rheumatoid arthritis in remission or low disease activity: a systematic literature review

description: <b>Objectives:</b> To identify, describe and summarize evidence on residual symptoms and disease burdens in rheumatoid arthritis (RA) patients qualified as being in remission or low disease activity (LDA). <b>Methods:</b> A systematic literature review (SLR) was conducted according to Cochrane collaboration guidelines. The population of interest was adult patients with RA in remission or LDA. The reported outcomes of interest were any symptoms or burdens. <b>Results:</b> Fifty-one publications were identified through an eDatabase search. Together with 17 articles found through other sources, 68 were included for full text review. The most commonly reported residual symptoms were pain (number of studies = 25), fatigue (<i>n</i> = 21) and morning stiffness (<i>n</i> = 5). Reported disease burdens included mental health (<i>n</i> = 15), sleep disturbances (<i>n</i> = 7) and work productivity (<i>n</i> = 5), impairment in quality of life (<i>n</i> = 21), and functional disability (<i>n</i> = 34). Substantial residual symptoms and disease burdens were found to be present in patients in remission or LDA. <b>Conclusion:</b> This is the first SLR to investigate residual symptoms and disease burdens in RA patients in remission or LDA. The results indicate that despite achieving conventional clinical targets, the disease continues to affect patients, suggesting the existence of unmet need under the current treatment paradigm.