cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.1325063.v5
title: Gibberellin driven growth in <i>elf3</i> mutants requires PIF4 and PIF5

description: The regulatory connections between the circadian clock and hormone signaling are essential to understand, as these two regulatory processes work together to time growth processes relative to predictable environmental events. Gibberellins (GAs) are phytohormones that control many growth processes throughout all stages of the plant life cycle, including germination and flowering. An increasing number of examples demonstrate that the circadian clock directly influences GA biosynthesis and signaling. EARLY FLOWERING 3 (ELF3) participates in a tripartite transcriptional complex known as the Evening Complex (EC). In this capacity, ELF3 is fundamental to core circadian clock activity, as well as time-of-day specific regulation of genes directly responsible for growth control, namely the <i>PHYTOCHROME INTERACTING FACTOR 4</i> (<i>PIF4</i>) and <i>PIF5</i> genes. Here we show that the GA biosynthesis inhibitor paclobutrazol substantially reduces the long hypocotyl and petiole phenotypes of Arabidopsis <i>elf3</i> mutants. In addition, loss of ELF3 activity causes upregulation of the key GA biosynthesis genes <i>GA20ox1</i> and <i>GA20ox2</i>. Moreover, <i>GA20ox1</i> and <i>GA20ox2</i> expression depends strongly on the redundant activities of <i>PIF4</i> and <i>PIF5</i>. These findings indicate that the defining growth phenotypes of <i>elf3</i> mutants arise from altered GA biosynthesis due to misregulation of <i>PIF4</i> and <i>PIF5</i>. These observations agree with recent work linking increased GA production with the elongated growth phenotypes of the barley <i>elf3</i> mutant. Thus, the role of the EC in regulation of GA biosynthesis and signaling in eudicots is shared with monocots and, therefore, is a highly conserved mechanism for growth control.
DOI: 10.6084/m9.figshare.1323273.v3
title: Sequential Exploration of Complex Surfaces Using Minimum Energy Designs

description: A new space-filling design, called minimum energy design (MED), is proposed to explore unknown regions of the design space of particular interest to an experimenter. The key ideas involved in constructing the MED are the visualization of each design point as a charged particle inside a box, and minimization of the total potential energy of these particles. It is shown through theoretical arguments and simulations that with a proper choice of the charge function, the MED can asymptotically generate any arbitrary probability density function. A version of the MED, which adaptively updates the design by “learning” about the unknown response surface sequentially, is proposed and implemented. Two potential applications of MED in simulation of complex probability densities and optimization of complex response surfaces are discussed and demonstrated with examples. This article has supplementary material online.
DOI: 10.6084/m9.figshare.1323267
title: Statistical Inference for Power-Law Process With Competing Risks

description: The focus of this article is on failure history of a repairable system for which the relevant data comprise successive event times for a recurrent phenomenon along with an event-count indicator. We undertake an investigation for analyzing failures from repairable systems that are subject to multiple failure modes. Failure data representing a cluster of recurrent events from a single system are studied under the parametric framework of a <i>power-law process</i>, a model that has found considerable attention in industrial applications. Some interesting and nonstandard asymptotic results ensue in this context that are discussed in detail. Extensive simulation has been carried out that supplements the theoretical findings. An extension to the case where the specific cause of failure may be missing is investigated in detail. The methodology has been implemented on recurrent failure data obtained from a warranty claim database for a fleet of automobiles. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.1323269
title: Nonparametric Variable Transformation in Sufficient Dimension Reduction

description: Sufficient dimension reduction (SDR) techniques have proven to be very useful data analysis tools in various applications. Underlying many SDR techniques is a critical assumption that the predictors are elliptically contoured. When this assumption appears to be wrong, practitioners usually try variable transformation such that the transformed predictors become (nearly) normal. The transformation function is often chosen from the log and power transformation family, as suggested in the celebrated Box–Cox model. However, any parametric transformation can be too restrictive, causing the danger of model misspecification. We suggest a nonparametric variable transformation method after which the predictors become normal. To demonstrate the main idea, we combine this flexible transformation method with two well-established SDR techniques, sliced inverse regression (SIR) and inverse regression estimator (IRE). The resulting SDR techniques are referred to as TSIR and TIRE, respectively. Both simulation and real data results show that TSIR and TIRE have very competitive performance. Asymptotic theory is established to support the proposed method. The technical proofs are available as supplementary materials.
DOI: 10.6084/m9.figshare.1323273.v2
title: Sequential Exploration of Complex Surfaces Using Minimum Energy Designs

description: A new space-filling design, called minimum energy design (MED), is proposed to explore unknown regions of the design space of particular interest to an experimenter. The key ideas involved in constructing the MED are the visualization of each design point as a charged particle inside a box, and minimization of the total potential energy of these particles. It is shown through theoretical arguments and simulations that with a proper choice of the charge function, the MED can asymptotically generate any arbitrary probability density function. A version of the MED, which adaptively updates the design by “learning” about the unknown response surface sequentially, is proposed and implemented. Two potential applications of MED in simulation of complex probability densities and optimization of complex response surfaces are discussed and demonstrated with examples. This article has supplementary material online.
DOI: 10.6084/m9.figshare.1323266
title: Geodesic Gaussian Processes for the Parametric Reconstruction of a Free-Form Surface

description: Reconstructing a free-form surface from 3-dimensional (3D) noisy measurements is a central problem in inspection, statistical quality control, and reverse engineering. We present a new method for the statistical reconstruction of a free-form surface patch based on 3D point cloud data. The surface is represented parametrically, with each of the three Cartesian coordinates (<i>x</i>, <i>y</i>, <i>z</i>) a function of surface coordinates (<i>u</i>, <i>v</i>), a model form compatible with computer-aided-design (CAD) models. This model form also avoids having to choose one Euclidean coordinate (say, <i>z</i>) as a “response” function of the other two coordinate “locations” (say, <i>x</i> and <i>y</i>), as commonly used in previous Euclidean kriging models of manufacturing data. The (<i>u</i>, <i>v</i>) surface coordinates are computed using parameterization algorithms from the manifold learning and computer graphics literature. These are then used as locations in a spatial Gaussian process model that considers correlations between two points on the surface a function of their <i>geodesic</i> distance on the surface, rather than a function of their Euclidean distances over the <i>xy</i> plane. We show how the proposed geodesic Gaussian process (GGP) approach better reconstructs the true surface, filtering the measurement noise, than when using a standard Euclidean kriging model of the “heights”, that is, <i>z</i>(<i>x</i>, <i>y</i>). The methodology is applied to simulated surface data and to a real dataset obtained with a noncontact laser scanner. Supplementary materials are available online.
DOI: 10.6084/m9.figshare.1323269.v2
title: Nonparametric Variable Transformation in Sufficient Dimension Reduction

description: Sufficient dimension reduction (SDR) techniques have proven to be very useful data analysis tools in various applications. Underlying many SDR techniques is a critical assumption that the predictors are elliptically contoured. When this assumption appears to be wrong, practitioners usually try variable transformation such that the transformed predictors become (nearly) normal. The transformation function is often chosen from the log and power transformation family, as suggested in the celebrated Box–Cox model. However, any parametric transformation can be too restrictive, causing the danger of model misspecification. We suggest a nonparametric variable transformation method after which the predictors become normal. To demonstrate the main idea, we combine this flexible transformation method with two well-established SDR techniques, sliced inverse regression (SIR) and inverse regression estimator (IRE). The resulting SDR techniques are referred to as TSIR and TIRE, respectively. Both simulation and real data results show that TSIR and TIRE have very competitive performance. Asymptotic theory is established to support the proposed method. The technical proofs are available as supplementary materials.
DOI: 10.6084/m9.figshare.1323266.v2
title: Geodesic Gaussian Processes for the Parametric Reconstruction of a Free-Form Surface

description: Reconstructing a free-form surface from 3-dimensional (3D) noisy measurements is a central problem in inspection, statistical quality control, and reverse engineering. We present a new method for the statistical reconstruction of a free-form surface patch based on 3D point cloud data. The surface is represented parametrically, with each of the three Cartesian coordinates (<i>x</i>, <i>y</i>, <i>z</i>) a function of surface coordinates (<i>u</i>, <i>v</i>), a model form compatible with computer-aided-design (CAD) models. This model form also avoids having to choose one Euclidean coordinate (say, <i>z</i>) as a “response” function of the other two coordinate “locations” (say, <i>x</i> and <i>y</i>), as commonly used in previous Euclidean kriging models of manufacturing data. The (<i>u</i>, <i>v</i>) surface coordinates are computed using parameterization algorithms from the manifold learning and computer graphics literature. These are then used as locations in a spatial Gaussian process model that considers correlations between two points on the surface a function of their <i>geodesic</i> distance on the surface, rather than a function of their Euclidean distances over the <i>xy</i> plane. We show how the proposed geodesic Gaussian process (GGP) approach better reconstructs the true surface, filtering the measurement noise, than when using a standard Euclidean kriging model of the “heights”, that is, <i>z</i>(<i>x</i>, <i>y</i>). The methodology is applied to simulated surface data and to a real dataset obtained with a noncontact laser scanner. Supplementary materials are available online.
DOI: 10.6084/m9.figshare.1323267.v2
title: Statistical Inference for Power-Law Process With Competing Risks

description: The focus of this article is on failure history of a repairable system for which the relevant data comprise successive event times for a recurrent phenomenon along with an event-count indicator. We undertake an investigation for analyzing failures from repairable systems that are subject to multiple failure modes. Failure data representing a cluster of recurrent events from a single system are studied under the parametric framework of a <i>power-law process</i>, a model that has found considerable attention in industrial applications. Some interesting and nonstandard asymptotic results ensue in this context that are discussed in detail. Extensive simulation has been carried out that supplements the theoretical findings. An extension to the case where the specific cause of failure may be missing is investigated in detail. The methodology has been implemented on recurrent failure data obtained from a warranty claim database for a fleet of automobiles. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.1323269.v1
title: Nonparametric Variable Transformation in Sufficient Dimension Reduction

description: Sufficient dimension reduction (SDR) techniques have proven to be very useful data analysis tools in various applications. Underlying many SDR techniques is a critical assumption that the predictors are elliptically contoured. When this assumption appears to be wrong, practitioners usually try variable transformation such that the transformed predictors become (nearly) normal. The transformation function is often chosen from the log and power transformation family, as suggested in the celebrated Box–Cox model. However, any parametric transformation can be too restrictive, causing the danger of model misspecification. We suggest a nonparametric variable transformation method after which the predictors become normal. To demonstrate the main idea, we combine this flexible transformation method with two well-established SDR techniques, sliced inverse regression (SIR) and inverse regression estimator (IRE). The resulting SDR techniques are referred to as TSIR and TIRE, respectively. Both simulation and real data results show that TSIR and TIRE have very competitive performance. Asymptotic theory is established to support the proposed method. The technical proofs are available as supplementary materials.
DOI: 10.6084/m9.figshare.1323267.v1
title: Statistical Inference for Power-Law Process With Competing Risks

description: The focus of this article is on failure history of a repairable system for which the relevant data comprise successive event times for a recurrent phenomenon along with an event-count indicator. We undertake an investigation for analyzing failures from repairable systems that are subject to multiple failure modes. Failure data representing a cluster of recurrent events from a single system are studied under the parametric framework of a <i>power-law process</i>, a model that has found considerable attention in industrial applications. Some interesting and nonstandard asymptotic results ensue in this context that are discussed in detail. Extensive simulation has been carried out that supplements the theoretical findings. An extension to the case where the specific cause of failure may be missing is investigated in detail. The methodology has been implemented on recurrent failure data obtained from a warranty claim database for a fleet of automobiles. Supplementary material for this article is available online.
DOI: 10.6084/m9.figshare.1322231
title: FORMULATION AND CHARACTERIZATION OF ROSUVASTATIN CALCIUM NANOPARTICLES

description: The aim of this study is to formulate and characterize Rosuvastatin loaded Chitosan nanoparticles prepared by ionic-gelation method. Rosuvastatin Calcium has a low bioavailability (20%) due to poor absorption of the drug. Chitosan is a polymer of linear polysaccharide, which enhances transport of drug across epithelial surfaces and is biocompatible and biodegradable. The nanoparticles obtained were evaluated for percentage yield of drug, drug entrapment efficiency, particle size and morphology using Scanning Electron Microscopy (SEM), compatibility studies using Fourier-Transform Infrared Spectroscopy (FTIR) and Differential Scanning Calorimetry (DSC) and in vitro release kinetics. Among the four different drug to polymer ratios, 1:1 ratio showed high encapsulation efficiency and drug loading. The nanoparticles obtained were spherical in shape with a smooth surface with particle size range between 231.52 ± 24.12 nm to 405.25 ± 17.42 nm. The nanoparticles prepared proved to be a promising dosage form of Rosuvastatin, with improved bioavailability.
DOI: 10.6084/m9.figshare.1322231.v1
title: FORMULATION AND CHARACTERIZATION OF ROSUVASTATIN CALCIUM NANOPARTICLES

description: The aim of this study is to formulate and characterize Rosuvastatin loaded Chitosan nanoparticles prepared by ionic-gelation method. Rosuvastatin Calcium has a low bioavailability (20%) due to poor absorption of the drug. Chitosan is a polymer of linear polysaccharide, which enhances transport of drug across epithelial surfaces and is biocompatible and biodegradable. The nanoparticles obtained were evaluated for percentage yield of drug, drug entrapment efficiency, particle size and morphology using Scanning Electron Microscopy (SEM), compatibility studies using Fourier-Transform Infrared Spectroscopy (FTIR) and Differential Scanning Calorimetry (DSC) and in vitro release kinetics. Among the four different drug to polymer ratios, 1:1 ratio showed high encapsulation efficiency and drug loading. The nanoparticles obtained were spherical in shape with a smooth surface with particle size range between 231.52 ± 24.12 nm to 405.25 ± 17.42 nm. The nanoparticles prepared proved to be a promising dosage form of Rosuvastatin, with improved bioavailability.
DOI: 10.6084/m9.figshare.1322182
title: ICU patients

description: monitoring of icu patients
DOI: 10.6084/m9.figshare.1322177
title: references

description: some references
DOI: 10.6084/m9.figshare.1322182.v1
title: ICU patients

description: monitoring of icu patients
DOI: 10.6084/m9.figshare.1322177.v3
title: references

description: some references
DOI: 10.6084/m9.figshare.1322177.v2
title: references

description: some references
DOI: 10.6084/m9.figshare.1322110
title: Latex Peel of Theropod tracks from the Paluxy River

description: Latex Peel of Theropod tracks from the Paluxy River, Glen Rose, TX.
DOI: 10.6084/m9.figshare.1321884
title: AD Model Builder and AutoHotkey Code for Evaluating Genetic Stock Identification Software

description: AD Model Builder .tpl and .dat files and AutoHotkey script for conducting simulations described in Brenden, T.O., J.R. Bence, W. Liu, I. Tsehaye, and K.T. Scribner. In press. Comparison of the accuracy and consistency of likelihood-based estimation routines for genetic stock identification. Methods in Ecology and Evolution combined.ahk - AutoHotkey script for running ONCOR and SPAM main.dat - AD Model Builder .dat file containing factors and factor levels to evaluate during simulations main.tpl - AD Model Builder .tpl file which is the driver program that loops over the factor levels and repeatedly calls the simulation program to produce a dataset and calls the other estimation routines to analyze the dataset mixbayes.tpl - AD Model Builder .tpl that implements the conditional penalized maximum likelihood estimation routine. This file also generate the files (baseline, mixture, control program) needed to run SPAM and ONCOR mixbayes_MLE.tpl - AD Model Builder .tpl that implements the condition maximum likelihood estimation routine. sim.tpl - AD Model Builder .tpl that simulates the actual source population and mixture data for a given combination of factor levels These files are provided without warranty of any kind and in no event shal the authors be liable for any claim, damages or any liabilit.
DOI: 10.6084/m9.figshare.1321794
title: Kazakiewicz et al., 2015

description: Supplementary files for Kazakiewicz D, Karr JR, Langner KM & Plewczynski D. Combined systems and structural modeling repositions antibiotics for Mycoplasma genitalium. (In submission).
DOI: 10.6084/m9.figshare.1321643
title: Lithium vs Age for Low-Mass Stars and Brown Dwarfs

description: This figure shows the lithium mass fraction versus age for low-mass stars and brown dwarfs, in a similar format than the Burrows (2001) figure created by Michael C. Cushing (see link below). These tracks are based on the AMES-Cond evolutionary models (Baraffe et al. 2003; 2nd link below).
DOI: 10.6084/m9.figshare.1321402
title: Radius vs Age for Low-Mass Stars and Brown Dwarfs

description: This figure shows the radii versus age for low-mass stars and brown dwarfs, in a similar format than the Burrows (2001) figure created by Michael C. Cushing (see link below). These tracks are based on the AMES-Cond evolutionary models (Baraffe et al. 2003; 2nd link below). Note that the .eps version is bitmap-compressed because of transparency effects.
DOI: 10.6084/m9.figshare.1321643.v2
title: Lithium vs Age for Low-Mass Stars and Brown Dwarfs

description: This figure shows the lithium mass fraction versus age for low-mass stars and brown dwarfs, in a similar format than the Burrows (2001) figure created by Michael C. Cushing (see link below). These tracks are based on the AMES-Cond evolutionary models (Baraffe et al. 2003; 2nd link below).
DOI: 10.6084/m9.figshare.1321794.v1
title: new fileset

description: Supplementary files for Kazakiewicz D, Karr JR, Langner KM & Plewczynski D. Combined systems and structural modeling repositions antibiotics for Mycoplasma genitalium. (In submission).
DOI: 10.6084/m9.figshare.1321402.v2
title: Radius vs Age for Low-Mass Stars and Brown Dwarfs

description: This figure shows the radii versus age for low-mass stars and brown dwarfs, in a similar format than the Burrows (2001) figure created by Michael C. Cushing (see link below). These tracks are based on the AMES-Cond evolutionary models (Baraffe et al. 2003; 2nd link below). Note that the .eps version is bitmap-compressed because of transparency effects.
DOI: 10.6084/m9.figshare.1321402.v1
title: Low-Mass Stars and Brown Dwarfs Radius vs Age

description: This figure shows the radii versus age for low-mass stars and brown dwarfs, in a similar format than the Burrows (2001) figure created by Michael C. Cushing (see link below). These tracks are based on the AMES-Cond evolutionary models (Baraffe et al. 2003; 2nd link below). Note that the .eps version is bitmap-compressed because of transparency effects.
DOI: 10.6084/m9.figshare.1321364
title: Wellcome Trust open access (OA) spend and compliance montoring 2013-14: an explanation of the dataset

description: A short "Readme" file that seeks to describe the 2013-14 OA dataset, published in Figshare
DOI: 10.6084/m9.figshare.1321366
title: Reversible Photo Actuated Bulk Nanocomposite with Nematic Liquid Crystalline Elastomer Matrix

description: Liquid crystal elastomers (LCEs) are excellent actuator materials. However, current LCE materials are generally made in the forms with thin thickness, such as films or fibers, which have limitations in forming actuators. We have developed a bulk LCE material with the three-dimensional elastic skeleton network of polyurethane and the matrix of nematic LCE incorporating single-wall carbon nanotubes (SWCNTs). This LCE nanocomposite bulk (LCENB) exhibited sensitive and reversible photo actuation. It could evenly contract by up to 25% of the initial height under a uniform irradiation, or bend towards the incident light by up to 40° under an asymmetrical irradiation. A photo-driven scanning mirror with superior scanning angle, implementing this LCENB as the actuator, was also demonstrated.
DOI: 10.6084/m9.figshare.1321794.v2
title: Kazakiewicz et al., 2015

description: Supplementary files for Kazakiewicz D, Karr JR, Langner KM & Plewczynski D. Combined systems and structural modeling repositions antibiotics for Mycoplasma genitalium. (In submission).