cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.23641/asha.6987371.v1
title: RULE: Development of a reading comprehension measure (Kucheria et al., 2018)

description: <b>Purpose:</b> There is a lack of quick, reliable, and valid standardized reading comprehension assessments appropriate for postsecondary readers. We attempted to address this gap by designing Read, Understand, Learn, & Excel (RULE), a reading comprehension measure that employs sentence verification and recall tasks to assess reading comprehension. This article describes the exploratory study undertaken to construct RULE and then examines the preliminary concurrent validity and alternate form reliability of this measure.<b>Method:</b> The RULE measure was first developed by designing reading stimuli, test items for the sentence verification task, and directions for the recall test for 2 forms based on previous work (Griffiths, Sohlberg, Kirk, Fickas, & Biancarosa, 2016). Thirty undergraduate students who identified themselves as typical readers were administered the RULE measure as well as the Nelson–Denny Reading Test (Brown, Fishco, & Hanna, 1993). Students also completed questionnaires and participated in informal interviews to provide information regarding study and learning habits and academic background.<b>Results:</b> There was preliminary evidence of alternate form reliability between the sentence verification task sets of 2 chapters of RULE (<i>r</i> = .38, <i>p</i> &lt; .05). Preliminary evidence for concurrent validity between RULE and the Nelson–Denny Reading Test was provided by correlation coefficients in the low to moderate range (.03–.38).<b>Conclusion: </b>RULE design and preliminary findings of concurrent validity and alternate form reliability provide “proof of concept” for an ecologically valid testing format that assesses comprehension skills appropriate for the postsecondary level. Suggestions for strengthening validity and reliability of the tool are provided, and clinical contributions of RULE are discussed.<br><b>Supplemental Material S1. </b>Comparison between Read, Understand, Learn, & Excel (RULE) measures and alternative measures of reading comprehension. <br><b>Supplemental Material S2.</b> Comparison between Read, Understand, Learn, & Excel (RULE) measures and Learning and Study Strategies Inventory (LASSI; Weinstein, Palmer, & Acee, 2016) Information processing scale.<br>Kucheria, P., Sohlberg, M. M., Yoon, H., Fickas, S., & Prideaux, J. (2018). Read, Understand, Learn, & Excel (RULE): Development and feasibility of a reading comprehension measure for postsecondary learners. <i>American Journal of Speech-Language Pathology</i>. Advanced online publication. https://doi.org/10.1044/2018_AJSLP-17-0221
DOI: 10.6084/m9.figshare.6987323
title: OceanWaveSpectra

description: These files are all the programs and data used to produce the results reported in "Directional Surface Wave Spectra from Point Measurements of Height and Slope" by William Plant and Mark Donelan. Submitted to JGR Oceans, August 2018<b> </b> <b> </b> <br>
DOI: 10.6084/m9.figshare.6987323.v1
title: OceanWaveSpectra

description: These files are all the programs and data used to produce the results reported in "Directional Surface Wave Spectra from Point Measurements of Height and Slope" by William Plant and Mark Donelan. Submitted to JGR Oceans, August 2018<b> </b> <b> </b> <br>
DOI: 10.6084/m9.figshare.6987125
title: Enriched genes

description: Table of enriched (log 2 FC &gt; 2, p-value &lt;0.05) genes that are associated with GO terms related to transcription factor activity in composite somatotrope and lactotrope datasets.
DOI: 10.6084/m9.figshare.6987119
title: Supplemental Table 1

description: Supplemental Table 1. Total read counts for GFP and DsRed mRNAs in each FACS-sorted sample used for RNA-seq analysis.
DOI: 10.6084/m9.figshare.6987125.v1
title: Enriched genes

description: Table of enriched (log 2 FC &gt; 2, p-value &lt;0.05) genes that are associated with GO terms related to transcription factor activity in composite somatotrope and lactotrope datasets.
DOI: 10.6084/m9.figshare.6987119.v1
title: Supplemental Table 1

description: Supplemental Table 1. Total read counts for GFP and DsRed mRNAs in each FACS-sorted sample used for RNA-seq analysis.
DOI: 10.7284/108951
title: Multiplexed data collected during research cruise KN193-02 using a Hawaii UHDAS instrument system onboard the platform RV Knorr
DOI: 10.6084/m9.figshare.6987044
title: Data-Adaptive Estimation of Time-Varying Spectral Densities

description: This article introduces a data-adaptive nonparametric approach for the estimation of time-varying spectral densities from nonstationary time series. Time-varying spectral densities are commonly estimated by local kernel smoothing. The performance of these nonparametric estimators, however, depends crucially on the smoothing bandwidths that need to be specified in both time and frequency direction. As an alternative and extension to traditional bandwidth selection methods, we propose an iterative algorithm for constructing localized smoothing kernels data-adaptively. The main idea, inspired by the concept of propagation-separation, is to determine for a point in the time-frequency plane the largest local vicinity over which smoothing is justified by the data. By shaping the smoothing kernels nonparametrically, our method not only avoids the problem of bandwidth selection in the strict sense but also becomes more flexible. It not only adapts to changing curvature in smoothly varying spectra but also adjusts for structural breaks in the time-varying spectrum. Supplementary materials, including the R package tvspecAdapt containing an implementation of the routine, are available online.
DOI: 10.6084/m9.figshare.6987047
title: Construction of Two-Level Nonregular Designs of Strength Three With Large Run Sizes

description: Two-level orthogonal arrays of strength 3 permit the study of the main effects and the two-factor interactions of the experimental factors. These arrays are classified into regular and nonregular designs. Good regular designs are available in the literature for large run sizes that are a power of 2. In contrast, good nonregular designs, which have run sizes that are multiples of 8 and are more flexible alternatives to regular designs, are not available for large numbers of runs because their construction is challenging. In this article, we introduce a collection of strength-3 nonregular designs with large run sizes that, to the best of our knowledge, have not been explored before in the design literature. Using theoretical results and algorithmic approaches, we construct nonregular designs with up to 1280 runs. Our designs fill the gaps between the available strength-3 designs with large run sizes and outperform many comparably sized benchmark designs in terms of the aliasing among the two-factor interactions. We show the applicability of our collection of strength-3 designs using an infrared sensor experiment. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6987047.v1
title: Construction of Two-Level Nonregular Designs of Strength Three With Large Run Sizes

description: Two-level orthogonal arrays of strength 3 permit the study of the main effects and the two-factor interactions of the experimental factors. These arrays are classified into regular and nonregular designs. Good regular designs are available in the literature for large run sizes that are a power of 2. In contrast, good nonregular designs, which have run sizes that are multiples of 8 and are more flexible alternatives to regular designs, are not available for large numbers of runs because their construction is challenging. In this paper, we introduce a collection of strength-3 nonregular designs with large run sizes that, to the best of our knowledge, have not been explored before in the design literature. Using theoretical results and algorithmic approaches, we construct nonregular designs with up to 1280 runs. Our designs fill the gaps between the available strength-3 designs with large run sizes and outperform many comparably-sized benchmark designs in terms of the aliasing among the two-factor interactions. We show the applicability of our collection of strength-3 designs using an infrared sensor experiment. Supplementary materials for this paper are available online.
DOI: 10.6084/m9.figshare.6987044.v1
title: Data-adaptive estimation of time-varying spectral densities

description: This paper introduces a data-adaptive non-parametric approach for the estimation of time-varying spectral densities from nonstationary time series. Time-varying spectral densities are commonly estimated by local kernel smoothing. The performance of these nonparametric estimators, however, depends crucially on the smoothing bandwidths that need to be specified in both time and frequency direction. As an alternative and extension to traditional bandwidth selection methods, we propose an iterative algorithm for constructing localized smoothing kernels data-adaptively. The main idea, inspired by the concept of propagation-separation (Polzehl and Spokoiny, 2006), is to determine for a point in the time-frequency plane the largest local vicinity over which smoothing is justified by the data. By shaping the smoothing kernels nonparametrically, our method not only avoids the problem of bandwidth selection in the strict sense but also becomes more flexible. It not only adapts to changing curvature in smoothly varying spectra but also adjusts for structural breaks in the time-varying spectrum.
DOI: 10.6084/m9.figshare.6987047.v3
title: Construction of Two-Level Nonregular Designs of Strength Three With Large Run Sizes

description: Two-level orthogonal arrays of strength 3 permit the study of the main effects and the two-factor interactions of the experimental factors. These arrays are classified into regular and nonregular designs. Good regular designs are available in the literature for large run sizes that are a power of 2. In contrast, good nonregular designs, which have run sizes that are multiples of 8 and are more flexible alternatives to regular designs, are not available for large numbers of runs because their construction is challenging. In this article, we introduce a collection of strength-3 nonregular designs with large run sizes that, to the best of our knowledge, have not been explored before in the design literature. Using theoretical results and algorithmic approaches, we construct nonregular designs with up to 1280 runs. Our designs fill the gaps between the available strength-3 designs with large run sizes and outperform many comparably sized benchmark designs in terms of the aliasing among the two-factor interactions. We show the applicability of our collection of strength-3 designs using an infrared sensor experiment. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6987044.v3
title: Data-Adaptive Estimation of Time-Varying Spectral Densities

description: This article introduces a data-adaptive nonparametric approach for the estimation of time-varying spectral densities from nonstationary time series. Time-varying spectral densities are commonly estimated by local kernel smoothing. The performance of these nonparametric estimators, however, depends crucially on the smoothing bandwidths that need to be specified in both time and frequency direction. As an alternative and extension to traditional bandwidth selection methods, we propose an iterative algorithm for constructing localized smoothing kernels data-adaptively. The main idea, inspired by the concept of propagation-separation, is to determine for a point in the time-frequency plane the largest local vicinity over which smoothing is justified by the data. By shaping the smoothing kernels nonparametrically, our method not only avoids the problem of bandwidth selection in the strict sense but also becomes more flexible. It not only adapts to changing curvature in smoothly varying spectra but also adjusts for structural breaks in the time-varying spectrum. Supplementary materials, including the R package tvspecAdapt containing an implementation of the routine, are available online.
DOI: 10.6084/m9.figshare.6987047.v2
title: Construction of Two-Level Nonregular Designs of Strength Three With Large Run Sizes

description: Two-level orthogonal arrays of strength 3 permit the study of the main effects and the two-factor interactions of the experimental factors. These arrays are classified into regular and nonregular designs. Good regular designs are available in the literature for large run sizes that are a power of 2. In contrast, good nonregular designs, which have run sizes that are multiples of 8 and are more flexible alternatives to regular designs, are not available for large numbers of runs because their construction is challenging. In this article, we introduce a collection of strength-3 nonregular designs with large run sizes that, to the best of our knowledge, have not been explored before in the design literature. Using theoretical results and algorithmic approaches, we construct nonregular designs with up to 1280 runs. Our designs fill the gaps between the available strength-3 designs with large run sizes and outperform many comparably sized benchmark designs in terms of the aliasing among the two-factor interactions. We show the applicability of our collection of strength-3 designs using an infrared sensor experiment. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.6987044.v2
title: Data-Adaptive Estimation of Time-Varying Spectral Densities

description: This article introduces a data-adaptive nonparametric approach for the estimation of time-varying spectral densities from nonstationary time series. Time-varying spectral densities are commonly estimated by local kernel smoothing. The performance of these nonparametric estimators, however, depends crucially on the smoothing bandwidths that need to be specified in both time and frequency direction. As an alternative and extension to traditional bandwidth selection methods, we propose an iterative algorithm for constructing localized smoothing kernels data-adaptively. The main idea, inspired by the concept of propagation-separation, is to determine for a point in the time-frequency plane the largest local vicinity over which smoothing is justified by the data. By shaping the smoothing kernels nonparametrically, our method not only avoids the problem of bandwidth selection in the strict sense but also becomes more flexible. It not only adapts to changing curvature in smoothly varying spectra but also adjusts for structural breaks in the time-varying spectrum. Supplementary materials, including the R package tvspecAdapt containing an implementation of the routine, are available online.
DOI: 10.6084/m9.figshare.6987029
title: Detecting Changes in Slope With an <i><i>L</i><sub>0</sub></i> Penalty

description: While there are many approaches to detecting changes in mean for a univariate time series, the problem of detecting multiple changes in slope has comparatively been ignored. Part of the reason for this is that detecting changes in slope is much more challenging: simple binary segmentation procedures do not work for this problem, while existing dynamic programming methods that work for the change in mean problem cannot be used for detecting changes in slope. We present a novel dynamic programming approach, CPOP, for finding the “best” continuous piecewise linear fit to data under a criterion that measures fit to data using the residual sum of squares, but penalizes complexity based on an <i>L</i><sub>0</sub> penalty on changes in slope. We prove that detecting changes in this manner can lead to consistent estimation of the number of changepoints, and show empirically that using an <i>L</i><sub>0</sub> penalty is more reliable at estimating changepoint locations than using an <i>L</i><sub>1</sub> penalty. Empirically CPOP has good computational properties, and can analyze a time series with 10,000 observations and 100 changes in a few minutes. Our method is used to analyze data on the motion of bacteria, and provides better and more parsimonious fits than two competing approaches. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.6987029.v2
title: Detecting Changes in Slope With an <i><i>L</i><sub>0</sub></i> Penalty

description: While there are many approaches to detecting changes in mean for a univariate time series, the problem of detecting multiple changes in slope has comparatively been ignored. Part of the reason for this is that detecting changes in slope is much more challenging: simple binary segmentation procedures do not work for this problem, while existing dynamic programming methods that work for the change in mean problem cannot be used for detecting changes in slope. We present a novel dynamic programming approach, CPOP, for finding the “best” continuous piecewise linear fit to data under a criterion that measures fit to data using the residual sum of squares, but penalizes complexity based on an <i>L</i><sub>0</sub> penalty on changes in slope. We prove that detecting changes in this manner can lead to consistent estimation of the number of changepoints, and show empirically that using an <i>L</i><sub>0</sub> penalty is more reliable at estimating changepoint locations than using an <i>L</i><sub>1</sub> penalty. Empirically CPOP has good computational properties, and can analyze a time series with 10,000 observations and 100 changes in a few minutes. Our method is used to analyze data on the motion of bacteria, and provides better and more parsimonious fits than two competing approaches. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.6987023
title: Abolins_JEB_data.xlsx

description: Data associated with publication "The effect of chronic and acute stressors, and their interaction, on testes function: an experimental test during testicular recrudescence" by Abolins-Abols, etal., 2018, Journal of Experimental Biology.
DOI: 10.6084/m9.figshare.6987029.v1
title: Detecting changes in slope with an <i>L</i><sub>0</sub> penalty

description: Whilst there are many approaches to detecting changes in mean for a univariate time-series, the problem of detecting multiple changes in slope has comparatively been ignored. Part of the reason for this is that detecting changes in slope is much more challenging: simple binary segmentation procedures do not work for this problem, whilst existing dynamic programming methods that work for the change in mean problem cannot be used for detecting changes in slope. We present a novel dynamic programming approach, CPOP, for finding the “best” continuous piecewise-linear fit to data under a criterion that measures fit to data using the residual sum of squares, but penalises complexity based on an <i>L</i><sub>0</sub> penalty on changes in slope. We prove that detecting changes in this manner can lead to consistent estimation of the number of changepoints, and show empirically that using an <i>L</i><sub>0</sub> penalty is more reliable at estimating changepoint locations than using an <i>L</i><sub>1</sub> penalty. Empirically CPOP has good computational properties, and can analyse a time-series with 10,000 observations and 100 changes in a few minutes. Our method is used to analyse data on the motion of bacteria, and provides better and more parsimonious fits than two competing approaches.
DOI: 10.6084/m9.figshare.6987014
title: Adaptive Component-Wise Multiple-Try Metropolis Sampling

description: One of the most widely used samplers in practice is the component-wise Metropolis–Hastings (CMH) sampler that updates in turn the components of a vector-valued Markov chain using accept–reject moves generated from a proposal distribution. When the target distribution of a Markov chain is irregularly shaped, a “good” proposal distribution for one region of the state–space might be a “poor” one for another region. We consider a component-wise multiple-try Metropolis (CMTM) algorithm that chooses from a set of candidate moves sampled from different distributions. The computational efficiency is increased using an adaptation rule for the CMTM algorithm that dynamically builds a better set of proposal distributions as the Markov chain runs. The ergodicity of the adaptive chain is demonstrated theoretically. The performance is studied via simulations and real data examples. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.6987023.v1
title: Abolins_JEB_data.xlsx

description: Data associated with publication "The effect of chronic and acute stressors, and their interaction, on testes function: an experimental test during testicular recrudescence" by Abolins-Abols, etal., 2018, Journal of Experimental Biology.
DOI: 10.6084/m9.figshare.6987011
title: A review of transfer theory and characterization of measured performance for differential mobility analyzers

description: Particle transfer theory for steady-state differential mobility analyzers (DMAs) with and without diffusion is reviewed in detail with a particular focus on the assumptions and approximations made in the analysis. Impacts of the approximations are discussed and, where available, methods to reduce the errors of these approximations are suggested. The nondiffusing theory uses just one approximation, affecting the centroid calculation, which can be readily addressed via numerical modeling of the electric field. The diffusing theory makes numerous approximations to achieve an analytical expression. One of the most serious of these, neglecting secondary flows in the vicinities of the aerosol entrance and exit slits, could be improved upon using a numerical model of the flow field. Losses in the aerosol entrance plumbing can perturb the inlet profile to the classification region. The maximum effects on the transfer function are estimated to be a 1% increase in the mean mobility and a 14% reduction of the nondiffusing contribution to the variance. Methods of fitting transfer theory to measurements are also reviewed. Tandem differential mobility analyzer measurements generally do not have the resolving power to distinguish different shapes of the transfer function but newer measurements using truly monomobile ions have the potential to more rigorously test the diffusive transfer model. In adjusting the width of the theoretical transfer function to fit measurements from a real DMA demonstrating nonideal performance, it is physically more meaningful and accurate to use an additive adjustment to the variance as opposed to a multiplicative adjustment to the width. Copyright (c) 2018 American Association for Aerosol Research
DOI: 10.7284/108960
title: Gravimeter data collected during research cruise KN193-05 using a Bell BGM-3 instrument system onboard the platform RV Knorr