cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7010354
title: Fast Computation of Exact G-Optimal Designs Via I<sub>λ</sub>-Optimality

description: Exact G-optimal designs have rarely, if ever, been employed in practical applications. One reason for this is that, due to the computational difficulties involved, no statistical software system currently provides capabilities for constructing them. Two algorithms for exact G-optimal design construction of small designs involving one to three factors have been discussed in the literature: one employing a genetic algorithm and one employing a coordinate-exchange algorithm. However, these algorithms are extremely computer intensive in small experiments and do not scale beyond two or three factors. In this paper, we develop a new method for constructing exact G-optimal designs using the integrated variance criterion, I<sub>λ</sub>-optimality. We show that with careful selection of the weight function, a difficult exact G-optimal design construction problem can be converted to an equivalent exact I<sub>λ</sub>-optimal design problem, which is easily and quickly solved. We illustrate the use of the algorithm for full quadratic models in one to five factors. The MATLAB codes used to implement our algorithm and the exact G-optimal designs produced by the algorithm for each test case are available online as supplementary material.
DOI: 10.6084/m9.figshare.7010357.v1
title: Trends in Self-reporting of Marijuana Consumption in the United States

description: To adjust for underreporting of marijuana use, researchers multiply the proportion of individuals who reported using marijuana by a constant factor, such as the US Office of National Drug Control Policy’s 1.3. Although the current adjustments are simple, they do not account for changes in reporting over time. This article presents a novel way to explore relative changes in reporting from one survey to another simply by using data already available in a self-reported survey, the National Survey on Drug Use and Health. Using domain estimation to examine the stability in reported marijuana use by age 25 in individuals older than 25, this analysis provides estimates of the trends in marijuana reporting and standard errors, as long as the survey weights properly account for sampling variability. There was no significant evidence of an upward or downward trend in reporting changes from 1979 to 2016 for all birth cohorts, although there were significant differences in reporting between years and a slight downward trend in later years. These results suggest that individuals have become increasingly less willing to report their drug use in recent years, and thus the ONDCP likely underestimated the already drastic increase in use from 1992 to 2016.
DOI: 10.6084/m9.figshare.7010336
title: Validation of fitness tracker for sleep measures in women with asthma

description: <i>Objective</i>: Nighttime wakening with asthma symptoms is a key to assessment and therapy decisions, with no gold standard objective measure. The study aims were to (1) determine the feasibility, (2) explore equivalence, and (3) test concordance of a consumer-based accelerometer with standard actigraphy for measurement of sleep patterns in women with asthma as an adjunct to self-report. <i>Methods</i>: Panel study design of women with poorly controlled asthma from a university-affiliated primary care clinic system was used. We assessed sensitivity and specificity, equivalence and concordance of sleep time, sleep efficiency, and wake counts between the consumer-based accelerometer Fitbit Charge™ and Actigraph wGT3X+. We linked data between devices for comparison both automatically by 24-hour period and manually by sleep segment. <i>Results</i>: Analysis included 424 938 minutes, 738 nights, and 833 unique sleep segments from 47 women. The fitness tracker demonstrated 97% sensitivity and 40% specificity to identify sleep. Between device equivalence for total sleep time (15 and 42-minute threshold) was demonstrated by sleep segment. Concordance improved for wake counts and sleep efficiency when adjusting for a linear trend. <i>Conclusions</i>: There were important differences in total sleep time, efficiency, and wake count measures when comparing individual sleep segments versus 24-hour measures of sleep. Fitbit overestimates sleep efficiency and underestimates wake counts in this population compared to actigraphy. Low levels of systematic bias indicate the potential for raw measurements from the devices to achieve equivalence and concordance with additional processing, algorithm modification, and modeling. Fitness trackers offer an accessible and inexpensive method to quantify sleep patterns in the home environment as an adjunct to subjective reports, and require further informatics development.
DOI: 10.6084/m9.figshare.7010336.v2
title: Validation of fitness tracker for sleep measures in women with asthma

description: <i>Objective</i>: Nighttime wakening with asthma symptoms is a key to assessment and therapy decisions, with no gold standard objective measure. The study aims were to (1) determine the feasibility, (2) explore equivalence, and (3) test concordance of a consumer-based accelerometer with standard actigraphy for measurement of sleep patterns in women with asthma as an adjunct to self-report. <i>Methods</i>: Panel study design of women with poorly controlled asthma from a university-affiliated primary care clinic system was used. We assessed sensitivity and specificity, equivalence and concordance of sleep time, sleep efficiency, and wake counts between the consumer-based accelerometer Fitbit Charge™ and Actigraph wGT3X+. We linked data between devices for comparison both automatically by 24-hour period and manually by sleep segment. <i>Results</i>: Analysis included 424 938 minutes, 738 nights, and 833 unique sleep segments from 47 women. The fitness tracker demonstrated 97% sensitivity and 40% specificity to identify sleep. Between device equivalence for total sleep time (15 and 42-minute threshold) was demonstrated by sleep segment. Concordance improved for wake counts and sleep efficiency when adjusting for a linear trend. <i>Conclusions</i>: There were important differences in total sleep time, efficiency, and wake count measures when comparing individual sleep segments versus 24-hour measures of sleep. Fitbit overestimates sleep efficiency and underestimates wake counts in this population compared to actigraphy. Low levels of systematic bias indicate the potential for raw measurements from the devices to achieve equivalence and concordance with additional processing, algorithm modification, and modeling. Fitness trackers offer an accessible and inexpensive method to quantify sleep patterns in the home environment as an adjunct to subjective reports, and require further informatics development.
DOI: 10.6084/m9.figshare.7010354.v1
title: Fast Computation of Exact G-Optimal Designs Via I<i><sub>λ</sub></i>-Optimality

description: Exact G-optimal designs have rarely, if ever, been employed in practical applications. One reason for this is that, due to the computational difficulties involved, no statistical software system currently provides capabilities for constructing them. Two algorithms for exact G-optimal design construction of small designs involving one to three factors have been discussed in the literature: one employing a genetic algorithm and one employing a coordinate-exchange algorithm. However, these algorithms are extremely computer intensive in small experiments and do not scale beyond two or three factors. In this article, we develop a new method for constructing exact G-optimal designs using the integrated variance criterion, I<sub>λ</sub>-optimality. We show that with careful selection of the weight function, a difficult exact G-optimal design construction problem can be converted to an equivalent exact I<sub>λ</sub>-optimal design problem, which is easily and quickly solved. We illustrate the use of the algorithm for full quadratic models in one to five factors. The MATLAB codes used to implement our algorithm and the exact G-optimal designs produced by the algorithm for each test case are available online as supplementary material.
DOI: 10.6084/m9.figshare.7010354.v2
title: Fast Computation of Exact G-Optimal Designs Via I<sub>λ</sub>-Optimality

description: Exact G-optimal designs have rarely, if ever, been employed in practical applications. One reason for this is that, due to the computational difficulties involved, no statistical software system currently provides capabilities for constructing them. Two algorithms for exact G-optimal design construction of small designs involving one to three factors have been discussed in the literature: one employing a genetic algorithm and one employing a coordinate-exchange algorithm. However, these algorithms are extremely computer intensive in small experiments and do not scale beyond two or three factors. In this paper, we develop a new method for constructing exact G-optimal designs using the integrated variance criterion, I<sub>λ</sub>-optimality. We show that with careful selection of the weight function, a difficult exact G-optimal design construction problem can be converted to an equivalent exact I<sub>λ</sub>-optimal design problem, which is easily and quickly solved. We illustrate the use of the algorithm for full quadratic models in one to five factors. The MATLAB codes used to implement our algorithm and the exact G-optimal designs produced by the algorithm for each test case are available online as supplementary material.
DOI: 10.6084/m9.figshare.7010336.v1
title: Validation of fitness tracker for sleep measures in women with asthma

description: <i>Objective</i>: Nighttime wakening with asthma symptoms is a key to assessment and therapy decisions, with no gold standard objective measure. The study aims were to (1) determine the feasibility, (2) explore equivalence, and (3) test concordance of a consumer-based accelerometer with standard actigraphy for measurement of sleep patterns in women with asthma as an adjunct to self-report. <i>Methods</i>: Panel study design of women with poorly controlled asthma from a university-affiliated primary care clinic system was used. We assessed sensitivity and specificity, equivalence and concordance of sleep time, sleep efficiency, and wake counts between the consumer-based accelerometer Fitbit Charge™ and Actigraph wGT3X+. We linked data between devices for comparison both automatically by 24-hour period and manually by sleep segment. <i>Results</i>: Analysis included 424 938 minutes, 738 nights, and 833 unique sleep segments from 47 women. The fitness tracker demonstrated 97% sensitivity and 40% specificity to identify sleep. Between device equivalence for total sleep time (15 and 42-minute threshold) was demonstrated by sleep segment. Concordance improved for wake counts and sleep efficiency when adjusting for a linear trend. <i>Conclusions</i>: There were important differences in total sleep time, efficiency, and wake count measures when comparing individual sleep segments versus 24-hour measures of sleep. Fitbit overestimates sleep efficiency and underestimates wake counts in this population compared to actigraphy. Low levels of systematic bias indicate the potential for raw measurements from the devices to achieve equivalence and concordance with additional processing, algorithm modification, and modeling. Fitness trackers offer an accessible and inexpensive method to quantify sleep patterns in the home environment as an adjunct to subjective reports, and require further informatics development.
DOI: 10.6084/m9.figshare.7010195
title: Chr2-chr5 updated priors

description: This tar ball contains the additional chromosome simulation results not included in the paper "Substructured population growth in the Ashkenazi Jews inferred with Approximate Bayesian Computation".<br>There are four tab-delimited file (model 2, chr2-chr5) used as input for ABCtoolbox. The first line of each file is a header. The first set of columns are the parameter values used in the simulation and the remaining columns are the population genetic summary statistics. Each row is from one simulation - thus the number of rows equals the number of simulations + 1.<br>The posterior of each chromosome simulation was used as the prior for the next chromosome.
DOI: 10.6084/m9.figshare.7010195.v1
title: Chr2-chr5 updated priors

description: This tar ball contains the additional chromosome simulation results not included in the paper "Substructured population growth in the Ashkenazi Jews inferred with Approximate Bayesian Computation".<br>There are four tab-delimited file (model 2, chr2-chr5) used as input for ABCtoolbox. The first line of each file is a header. The first set of columns are the parameter values used in the simulation and the remaining columns are the population genetic summary statistics. Each row is from one simulation - thus the number of rows equals the number of simulations + 1.<br>The posterior of each chromosome simulation was used as the prior for the next chromosome.
DOI: 10.6084/m9.figshare.7010180
title: Genome simulated data

description: This tar ball contains the additional genome simulation results not included in the paper "Substructured population growth in the Ashkenazi Jews inferred with Approximate Bayesian Computation".<br>There is one tab-delimited file (model 2) used as input for ABCtoolbox. The first line of each file is a header. The first set of columns are the parameter values used in the simulation and the remaining columns are the population genetic summary statistics. Each row is from one simulation - thus the number of rows equals the number of simulations + 1.
DOI: 10.6084/m9.figshare.7010180.v1
title: Genome simulated data

description: This tar ball contains the additional genome simulation results not included in the paper "Substructured population growth in the Ashkenazi Jews inferred with Approximate Bayesian Computation".<br>There is one tab-delimited file (model 2) used as input for ABCtoolbox. The first line of each file is a header. The first set of columns are the parameter values used in the simulation and the remaining columns are the population genetic summary statistics. Each row is from one simulation - thus the number of rows equals the number of simulations + 1.
DOI: 10.6084/m9.figshare.7008170
title: Role of Dot6 in size control in Candida albicansSupplementary data revision

description: <br><b>Figure S1. </b><b>A <i>sch9 </i>mutant adjusts cell size in response to different carbon sources.</b><b></b>Size distribution of log-phase cultures of the indicated WT (CAI4) and <i>sch9</i>strains grown in synthetic glucose (black curve) and glycerol (red) medium.<b><br></b><b>Figure S2. Localization of Dot6-GFP in the vacuole when TOR pathway is compromised. </b>Dot6-GFP fluorescence was visualized using confocal microscopy in cells treated with the TOR pathway inhibitor, rapamycin. Vacuoles were stained using CellTracker Blue CMACdye. Red and blue arrows indicate Dot6-GFP florescence in the vacuole and the nucleus, respectively.<b> </b><b><br></b><b>Table S1. </b>Strains used in the current study and their genotypes.<b><br></b><b>Table S2</b>. Primer sequences used in the current study.<b><br></b><b>Table S3</b>. Gene Set Enrichment Analysis (GSEA) of dot6 mutant transcriptome <b><br></b><b>Table S4</b>. Transcripts differentially expressed in dot6 mutant using a 1.5-fold change cut-off and a 5% false discovery rate.<br><b>Table S5. </b>Functional characterisation of downregulated transcripts in <i>dot6 </i>mutant.<br>
DOI: 10.6084/m9.figshare.7008170.v1
title: Role of Dot6 in size control in Candida albicans

description: <br><b>Figure S1. </b><b>A <i>sch9</i>mutant adjusts cell size in response to different carbon sources.</b><b></b>Size distribution of log-phase cultures of the indicated WT (CAI4) and <i>sch9</i>strains grown in synthetic glucose (black curve) and glycerol (red) medium.<b>Figure S2. Localization of Dot6-GFP in the vacuole when TOR pathway is compromised. </b>Dot6-GFP fluorescence was visualized using confocal microscopy in cells treated with the TOR pathway inhibitor, rapamycin. Vacuoles were stained using CellTracker Blue CMACdye. Red and blue arrows indicate Dot6-GFP florescence in the vacuole and the nucleus, respectively. <b>Figure S3. Dot6 is required for size homeostasis of hyphal cells.</b>Length of at least 20 hyphal cells of both WT (SFY87) and dot6 mutant grown on YPD supplemented with 10% fetal bovine serum (FBS) at 37°C. Bars represent the means ±standard errors of the means. *, <i>P </i>&lt; 0.0003 using a two-tailed t-test. <b> </b><b>Table S1. </b>Strains used in the current study and their genotypes.<b>Table S2</b>. Primer sequences used in the current study.<b>Table S3</b>. Gene Set Enrichment Analysis (GSEA) of dot6 mutant transcriptome <b>Table S4</b>. Transcripts differentially expressed in dot6 mutant using a 1.5-fold change cut-off and a 5% false discovery rate.
DOI: 10.6084/m9.figshare.7008170.v2
title: Role of Dot6 in size control in Candida albicansSupplementary data revision

description: <br><b>Figure S1. </b><b>A <i>sch9 </i>mutant adjusts cell size in response to different carbon sources.</b><b></b>Size distribution of log-phase cultures of the indicated WT (CAI4) and <i>sch9</i>strains grown in synthetic glucose (black curve) and glycerol (red) medium.<b><br></b><b>Figure S2. Localization of Dot6-GFP in the vacuole when TOR pathway is compromised. </b>Dot6-GFP fluorescence was visualized using confocal microscopy in cells treated with the TOR pathway inhibitor, rapamycin. Vacuoles were stained using CellTracker Blue CMACdye. Red and blue arrows indicate Dot6-GFP florescence in the vacuole and the nucleus, respectively.<b> </b><b><br></b><b>Table S1. </b>Strains used in the current study and their genotypes.<b><br></b><b>Table S2</b>. Primer sequences used in the current study.<b><br></b><b>Table S3</b>. Gene Set Enrichment Analysis (GSEA) of dot6 mutant transcriptome <b><br></b><b>Table S4</b>. Transcripts differentially expressed in dot6 mutant using a 1.5-fold change cut-off and a 5% false discovery rate.
DOI: 10.6084/m9.figshare.7008170.v3
title: Role of Dot6 in size control in Candida albicansSupplementary data revision

description: <br><b>Figure S1. </b><b>A <i>sch9 </i>mutant adjusts cell size in response to different carbon sources.</b><b></b>Size distribution of log-phase cultures of the indicated WT (CAI4) and <i>sch9</i>strains grown in synthetic glucose (black curve) and glycerol (red) medium.<b><br></b><b>Figure S2. Localization of Dot6-GFP in the vacuole when TOR pathway is compromised. </b>Dot6-GFP fluorescence was visualized using confocal microscopy in cells treated with the TOR pathway inhibitor, rapamycin. Vacuoles were stained using CellTracker Blue CMACdye. Red and blue arrows indicate Dot6-GFP florescence in the vacuole and the nucleus, respectively.<b> </b><b><br></b><b>Table S1. </b>Strains used in the current study and their genotypes.<b><br></b><b>Table S2</b>. Primer sequences used in the current study.<b><br></b><b>Table S3</b>. Gene Set Enrichment Analysis (GSEA) of dot6 mutant transcriptome <b><br></b><b>Table S4</b>. Transcripts differentially expressed in dot6 mutant using a 1.5-fold change cut-off and a 5% false discovery rate.<br><b>Table S5. </b>Functional characterisation of downregulated transcripts in <i>dot6 </i>mutant.<br>
DOI: 10.6084/m9.figshare.7007993
title: Compatibility of Cats with Children in the Family

description: The data include results from a survey asking parents about cat's role in families. The participants had at least one child between 3 and 12 years of age and at least one cat. This study gathered demographic data, geographic region of respondents, behavioral characteristics of cats, and responses of children to cats.<br>
DOI: 10.6084/m9.figshare.7007951
title: Exploring population responses to environmental change when there is never enough data; a factor analytic approach

description: These are the two demographic datasets used in the manuscript "Exploring population responses to environmental change when there is never enough data; a factor analytic approach".<br>Abstract1. Temporal variability in the environment drives variation in vital rates, with consequences for population dynamics and life history evolution. Integral projection models (IPMs) are data-driven structured population models widely used to study population dynamics and life history evolution in temporally variable environments. However, many data sets have insufficient temporal replication for the environmental drivers of vital rates to be identified with confidence, limiting their use for evaluating population level responses to environmental change.2. Parameter selection, where the kernel is constructed at each time step by randomly selecting the time-varying parameters from their joint probability distribution, is one approach to including stochasticity in IPMs. We consider a factor analytic (FA) approach for modelling the covariance matrix of time-varying parameters, whereby latent variable(s) describe the covariance among vital rate parameters. This decreases the number of parameters to estimate and, where the covariance is positive, the latent variable can be interpreted as a measure of environmental quality. We demonstrate this using simulation studies and two case studies.3. The simulation studies suggest the FA approach provides similarly accurate estimates of stochastic population growth rate to estimating an unstructured covariance matrix. We demonstrate how the latent parameter can be perturbed to show how selection on reproductive delays in the monocarp <i>Carduus nutans </i>changes under different environmental conditions. We develop a demographic model of the fire dependent herb <i>Eryngium cuneifolium</i> to show how a putative driver of the variation in environmental quality can be incorporated with the addition of a single parameter. Using perturbation analyses we determine optimal management strategies for this species.4. This approach estimates fewer parameters than previous approaches and allows novel eco-evolutionary insights. Predictions on population dynamics and life history evolution under different environmental conditions can be made without necessarily identifying causal factors. Putative environmental drivers can be incorporated with relatively few parameters, allowing for predictions on how populations will respond to changes in the environment.<br>The <i>Carduus nutans</i> data are owned by CSIRO. The <i>Eryngium cuneifolium </i>were provided by the Archbold Biological Station. Example code for parameterising an IPM using the FA approach are available on github with DOI: http://doi.org/10.5281/zenodo.1312855.
DOI: 10.6084/m9.figshare.7007993.v1
title: Compatibility of Cats with Children in the Family

description: The data include results from a survey asking parents about cat's role in families. The participants had at least one child between 3 and 12 years of age and at least one cat. This study gathered demographic data, geographic region of respondents, behavioral characteristics of cats, and responses of children to cats.<br>