cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.7624424
title: MacroPCA: An All-in-One PCA Method Allowing for Missing Values as Well as Cellwise and Rowwise Outliers

description: Multivariate data are typically represented by a rectangular matrix (table) in which the rows are the objects (cases) and the columns are the variables (measurements). When there are many variables one often reduces the dimension by principal component analysis (PCA), which in its basic form is not robust to outliers. Much research has focused on handling rowwise outliers, that is, rows that deviate from the majority of the rows in the data (e.g., they might belong to a different population). In recent years also cellwise outliers are receiving attention. These are suspicious cells (entries) that can occur anywhere in the table. Even a relatively small proportion of outlying cells can contaminate over half the rows, which causes rowwise robust methods to break down. In this article, a new PCA method is constructed which combines the strengths of two existing robust methods to be robust against both cellwise and rowwise outliers. At the same time, the algorithm can cope with missing values. As of yet it is the only PCA method that can deal with all three problems simultaneously. Its name MacroPCA stands for PCA allowing for Missingness And Cellwise & Rowwise Outliers. Several simulations and real datasets illustrate its robustness. New residual maps are introduced, which help to determine which variables are responsible for the outlying behavior. The method is well-suited for online process control.
DOI: 10.7284/113824
title: Gyrocompass data collected during research cruise EN534 using a Sperry MK-37 instrument system onboard the platform RV Endeavor
DOI: 10.6084/m9.figshare.7624424.v2
title: MacroPCA: An All-in-One PCA Method Allowing for Missing Values as Well as Cellwise and Rowwise Outliers

description: Multivariate data are typically represented by a rectangular matrix (table) in which the rows are the objects (cases) and the columns are the variables (measurements). When there are many variables one often reduces the dimension by principal component analysis (PCA), which in its basic form is not robust to outliers. Much research has focused on handling rowwise outliers, that is, rows that deviate from the majority of the rows in the data (e.g., they might belong to a different population). In recent years also cellwise outliers are receiving attention. These are suspicious cells (entries) that can occur anywhere in the table. Even a relatively small proportion of outlying cells can contaminate over half the rows, which causes rowwise robust methods to break down. In this article, a new PCA method is constructed which combines the strengths of two existing robust methods to be robust against both cellwise and rowwise outliers. At the same time, the algorithm can cope with missing values. As of yet it is the only PCA method that can deal with all three problems simultaneously. Its name MacroPCA stands for PCA allowing for Missingness And Cellwise & Rowwise Outliers. Several simulations and real datasets illustrate its robustness. New residual maps are introduced, which help to determine which variables are responsible for the outlying behavior. The method is well-suited for online process control.
DOI: 10.6084/m9.figshare.7624424.v1
title: MacroPCA: An all-in-one PCA method allowing for missing values as well as cellwise and rowwise outliers

description: Multivariate data are typically represented by a rectangular matrix (table) in which the rows are the objects (cases) and the columns are the variables (measurements). When there are many variables one often reduces the dimension by principal component analysis (PCA), which in its basic form is not robust to outliers. Much research has focused on handling rowwise outliers, i.e. rows that deviate from the majority of the rows in the data (for instance, they might belong to a different population). In recent years also cellwise outliers are receiving attention. These are suspicious cells (entries) that can occur anywhere in the table. Even a relatively small proportion of outlying cells can contaminate over half the rows, which causes rowwise robust methods to break down. In this paper a new PCA method is constructed which combines the strengths of two existing robust methods in order to be robust against both cellwise and rowwise outliers. At the same time, the algorithm can cope with missing values. As of yet it is the only PCA method that can deal with all three problems simultaneously. Its name MacroPCA stands for PCA allowing for Missingness And Cellwise & Rowwise Outliers. Several simulations and real data sets illustrate its robustness. New residual maps are introduced, which help to determine which variables are responsible for the outlying behavior. The method is well-suited for online process control. Supplementary material is available online.
DOI: 10.6084/m9.figshare.7624412
title: Projections of Definitive Screening Designs by Dropping Columns: Selection and Evaluation

description: <b><i>Abstract–</i>Definitive screening designs permit the study of many quantitative factors in a few runs more than twice the number of factors. In practical applications, researchers often require a design for <i>m</i> quantitative factors, construct a definitive screening design for more than <i>m</i> factors and drop the superfluous columns. This is done when the number of runs in the standard <i>m</i>-factor definitive screening design is considered too limited or when no standard definitive screening design (sDSD) exists for <i>m</i> factors. In these cases, it is common practice to arbitrarily drop the last columns of the larger design. In this article, we show that certain statistical properties of the resulting experimental design depend on the exact columns dropped and that other properties are insensitive to these columns. We perform a complete search for the best sets of 1–8 columns to drop from sDSDs with up to 24 factors. We observed the largest differences in statistical properties when dropping four columns from 8- and 10-factor definitive screening designs. In other cases, the differences are small, or even nonexistent.</b>
DOI: 10.7284/113825
title: Gyrocompass data collected during research cruise EN534 using a Sperry MK-37 instrument system onboard the platform RV Endeavor
DOI: 10.6084/m9.figshare.7624373
title: Analysis of upper threshold mechanisms of spherical neurons during extracellular stimulation - figure 9 supplements

description: animated videos to Figure 9, case A-E<br>
DOI: 10.6084/m9.figshare.7624406
title: Optimal Experimental Design in the Presence of Nested Factors

description: A common occurrence in practical design of experiments is that one factor, called a nested factor, can only be varied for some but not all the levels of a categorical factor, called a branching factor. In this case, it is possible, but inefficient, to proceed by performing two experiments. One experiment would be run at the level(s) of the branching factor that allow for varying the second, nested, factor. The other experiment would only include the other level(s) of the branching factor. It is preferable to perform one experiment that allows for assessing the effects of both factors. Clearly, the effect of the nested factor then is conditional on the levels of the branching factor for which it can be varied. For example, consider an experiment comparing the performance of two machines where one machine has a switch that is missing for the other machine. The investigator wants to compare the two machines but also wants to understand the effect of flipping the switch. The main effect of the switch is conditional on the machine. This article describes several example situations involving branching factors and nested factors. We provide a model that is sensible for each situation, present a general method for constructing appropriate models, and show how to generate optimal designs given these models.
DOI: 10.6084/m9.figshare.7624406.v1
title: Optimal Experimental Design in the Presence of Nested Factors

description: A common occurrence in practical design of experiments is that one factor, called a nested factor, can only be varied for some but not all the levels of a categorical factor, called a branching factor. In this case, it is possible, but inefficient, to proceed by performing two experiments. One experiment would be run at the level(s) of the branching factor that allow for varying the second, nested, factor. The other experiment would only include the other level(s) of the branching factor. It is preferable to perform one experiment that allows for assessing the effects of both factors. Clearly, the effect of the nested factor then is conditional on the levels of the branching factor for which it can be varied. For example, consider an experiment comparing the performance of two machines where one machine has a switch that is missing for the other machine. The investigator wants to compare the two machines but also wants to understand the effect of flipping the switch. The main effect of the switch is conditional on the machine. This article describes several example situations involving branching factors and nested factors. We provide a model that is sensible for each situation, present a general method for constructing appropriate models, and show how to generate optimal designs given these models.
DOI: 10.6084/m9.figshare.7624337
title: Stories of a ruined space: filmic and sonic approaches to practice-as-research

description: This article reflects on the authors’ work in investigating how audiovisual practices might represent the experience of disused or ruined structures. With backgrounds in visual and sound practice respectively, the authors have, in their most recent experimental film project <i>Coccolith</i> [UK: Coccolith Productions], conceived the Ramsgate wartime tunnels in Kent as a point of collision for divergent artistic approaches to the representation of space. Challenging the site’s association with wartime mythology, the project sought to reconfigure the relationship between film and sound practice in order to articulate an alternative representation of the tunnels’ history, heritage and temporality. The article reflects on the role of the sound designer in developing soundscapes that embodied the ruined space, and on the role of the director in visually conceiving a spatial experience of the tunnels characterized by the absence of sound – silence. We argue that in conceiving an audiovisual project in terms of texture and gesture, it is possible to reconceptualize both the role of the soundtrack in relation to a film’s diegesis, and the role of the director in relation to sound design.
DOI: 10.6084/m9.figshare.7624412.v2
title: Projections of Definitive Screening Designs by Dropping Columns: Selection and Evaluation

description: <b><i>Abstract–</i>Definitive screening designs permit the study of many quantitative factors in a few runs more than twice the number of factors. In practical applications, researchers often require a design for <i>m</i> quantitative factors, construct a definitive screening design for more than <i>m</i> factors and drop the superfluous columns. This is done when the number of runs in the standard <i>m</i>-factor definitive screening design is considered too limited or when no standard definitive screening design (sDSD) exists for <i>m</i> factors. In these cases, it is common practice to arbitrarily drop the last columns of the larger design. In this article, we show that certain statistical properties of the resulting experimental design depend on the exact columns dropped and that other properties are insensitive to these columns. We perform a complete search for the best sets of 1–8 columns to drop from sDSDs with up to 24 factors. We observed the largest differences in statistical properties when dropping four columns from 8- and 10-factor definitive screening designs. In other cases, the differences are small, or even nonexistent.</b>
DOI: 10.7284/113827
title: Speedlog data collected during research cruise EN534 using a EDO MRQ-4015D instrument system onboard the platform RV Endeavor
DOI: 10.6084/m9.figshare.7624337.v1
title: Stories of a ruined space: filmic and sonic approaches to practice-as-research

description: This article reflects on the authors’ work in investigating how audiovisual practices might represent the experience of disused or ruined structures. With backgrounds in visual and sound practice respectively, the authors have, in their most recent experimental film project <i>Coccolith</i> [UK: Coccolith Productions], conceived the Ramsgate wartime tunnels in Kent as a point of collision for divergent artistic approaches to the representation of space. Challenging the site’s association with wartime mythology, the project sought to reconfigure the relationship between film and sound practice in order to articulate an alternative representation of the tunnels’ history, heritage and temporality. The article reflects on the role of the sound designer in developing soundscapes that embodied the ruined space, and on the role of the director in visually conceiving a spatial experience of the tunnels characterized by the absence of sound – silence. We argue that in conceiving an audiovisual project in terms of texture and gesture, it is possible to reconceptualize both the role of the soundtrack in relation to a film’s diegesis, and the role of the director in relation to sound design.
DOI: 10.6084/m9.figshare.7624412.v1
title: Projections of Definitive Screening Designs by Dropping Columns: Selection and Evaluation

description: <b><i>Abstract–</i>Definitive screening designs permit the study of many quantitative factors in a few runs more than twice the number of factors. In practical applications, researchers often require a design for <i>m</i> quantitative factors, construct a definitive screening design for more than <i>m</i> factors and drop the superfluous columns. This is done when the number of runs in the standard <i>m</i>-factor definitive screening design is considered too limited or when no standard definitive screening design (sDSD) exists for <i>m</i> factors. In these cases, it is common practice to arbitrarily drop the last columns of the larger design. In this article, we show that certain statistical properties of the resulting experimental design depend on the exact columns dropped and that other properties are insensitive to these columns. We perform a complete search for the best sets of 1–8 columns to drop from sDSDs with up to 24 factors. We observed the largest differences in statistical properties when dropping four columns from 8- and 10-factor definitive screening designs. In other cases, the differences are small, or even nonexistent.</b>
DOI: 10.7284/113826
title: TSG (Thermosalinograph) data collected during research cruise EN534 using a Sea-Bird SBE-45 instrument system onboard the platform RV Endeavor
DOI: 10.6084/m9.figshare.7624325
title: Penalized Orthogonal Iteration for Sparse Estimation of Generalized Eigenvalue Problem

description: We propose a new algorithm for sparse estimation of eigenvectors in generalized eigenvalue problems (GEPs). The GEP arises in a number of modern data-analytic situations and statistical methods, including principal component analysis (PCA), multiclass linear discriminant analysis (LDA), canonical correlation analysis (CCA), sufficient dimension reduction (SDR), and invariant co-ordinate selection. We propose to modify the standard generalized orthogonal iteration with a sparsity-inducing penalty for the eigenvectors. To achieve this goal, we generalize the equation-solving step of orthogonal iteration to a penalized convex optimization problem. The resulting algorithm, called penalized orthogonal iteration, provides accurate estimation of the true eigenspace, when it is sparse. Also proposed is a computationally more efficient alternative, which works well for PCA and LDA problems. Numerical studies reveal that the proposed algorithms are competitive, and that our tuning procedure works well. We demonstrate applications of the proposed algorithm to obtain sparse estimates for PCA, multiclass LDA, CCA, and SDR. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7624373.v1
title: Figure 9 Supplement

description: Videos to Figure 9<br>
DOI: 10.6084/m9.figshare.7624316
title: Figure 3 of Spatially-entangled Photon-pairs Generation Using Partial Spatially Coherent Pump Beam

description: The folder contains:- DefienneGigan_figure3_rawdata.mat contains raw data- DefienneGigan_Figure3 is the Matlab code to analyze the data.<br>
DOI: 10.6084/m9.figshare.7624325.v1
title: Penalized Orthogonal Iteration for Sparse Estimation of Generalized Eigenvalue Problem

description: We propose a new algorithm for sparse estimation of eigenvectors in generalized eigenvalue problems (GEPs). The GEP arises in a number of modern data-analytic situations and statistical methods, including principal component analysis (PCA), multiclass linear discriminant analysis (LDA), canonical correlation analysis (CCA), sufficient dimension reduction (SDR), and invariant co-ordinate selection. We propose to modify the standard generalized orthogonal iteration with a sparsity-inducing penalty for the eigenvectors. To achieve this goal, we generalize the equation-solving step of orthogonal iteration to a penalized convex optimization problem. The resulting algorithm, called penalized orthogonal iteration, provides accurate estimation of the true eigenspace, when it is sparse. Also proposed is a computationally more efficient alternative, which works well for PCA and LDA problems. Numerical studies reveal that the proposed algorithms are competitive, and that our tuning procedure works well. We demonstrate applications of the proposed algorithm to obtain sparse estimates for PCA, multiclass LDA, CCA, and SDR. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.7624289
title: Zoonotic hosts and land use change (PREDICTS) code and data

description: Code pipeline and data for Gibb et al, 'Land use has systematic effects on local zoonotic host communities'. Full description of dataset and code in README.rtf.<br>
DOI: 10.6084/m9.figshare.7624307
title: Supplementary Material for: Intracameral Air and Fibrin Glue for the Management of Late Bleb Leak following Glaucoma Surgery

description: <b><i>Background and Objectives:</i></b> To report a case of delayed-onset bleb-associated endophthalmitis (BAE) with bleb leak successfully managed with pars plana vitrectomy, intravitreal antibiotics, intracameral air, and fibrin glue. <b><i>Patient and Methods:</i></b> A 66-year-old pseudophakic female presented with BAE and bleb leak. A 25-gauge pars plana vitrectomy, cultures, and intravitreal antibiotics and steroid injections were performed. The infusion was switched to air filling the anterior chamber and bleb with air. Fibrin glue (Tisseel®) was applied over the leaking bleb. <b><i>Results:</i></b> BAE and bleb leak resolved with return of visual acuity to 20/25 and a functioning bleb with no recurrence of bleb leak after 1 year of follow-up. <b><i>Conclusion:</i></b> The combination of intracameral air and fibrin glue may have a role in the management of bleb leaks.
DOI: 10.6084/m9.figshare.7624307.v1
title: Supplementary Material for: Intracameral Air and Fibrin Glue for the Management of Late Bleb Leak following Glaucoma Surgery

description: <b><i>Background and Objectives:</i></b> To report a case of delayed-onset bleb-associated endophthalmitis (BAE) with bleb leak successfully managed with pars plana vitrectomy, intravitreal antibiotics, intracameral air, and fibrin glue. <b><i>Patient and Methods:</i></b> A 66-year-old pseudophakic female presented with BAE and bleb leak. A 25-gauge pars plana vitrectomy, cultures, and intravitreal antibiotics and steroid injections were performed. The infusion was switched to air filling the anterior chamber and bleb with air. Fibrin glue (Tisseel®) was applied over the leaking bleb. <b><i>Results:</i></b> BAE and bleb leak resolved with return of visual acuity to 20/25 and a functioning bleb with no recurrence of bleb leak after 1 year of follow-up. <b><i>Conclusion:</i></b> The combination of intracameral air and fibrin glue may have a role in the management of bleb leaks.
DOI: 10.6084/m9.figshare.7624316.v1
title: Figure 3 of Spatially-entangled Photon-pairs Generation Using Partial Spatially Coherent Pump Beam

description: The folder contains:- DefienneGigan_figure3_rawdata.mat contains raw data- DefienneGigan_Figure3 is the Matlab code to analyze the data.<br>
DOI: 10.7284/113832
title: Multiplexed data collected during research cruise EN535 using a Hawaii UHDAS instrument system onboard the platform RV Endeavor
DOI: 10.6084/m9.figshare.7624241
title: Supplementary Material for: Vascular Risk Factors and Findings on Brain MRI of Elderly Adult American Indians: The Strong Heart Study

description: <b><i>Background:</i></b> Clinical stroke is prevalent in American Indians, but the risk factors for cerebrovascular pathology have not been well-studied in this population. The purpose of this study was to correlate abnormalities on brain magnetic resonance imaging (MRI) with clinical risk factors in a cohort of elderly American Indians. <b><i>Methods:</i></b> Brain MRI scans from 789 participants of the Strong Heart Study were analyzed for infarcts, hemorrhage, white matter disease, and measures of cerebral atrophy including ventricular and sulcal grade and total brain volume. Clinical risk factors included measures of hypertension, diabetes, and high levels of low-density lipoprotein (LDL) cholesterol. Regression models adjusted for potential confounders were used to estimate associations between risk factors and brain MRI outcomes. <b><i>Results:</i></b> ­Hypertension was associated with the presence of infarcts (<i>p</i> = 0.001), ventricle enlargement (<i>p</i> = 0.01), and increased white matter hyperintensity volume (<i>p</i> = 0.01). Diabetes was associated with increased prevalence of cerebral atrophy (<i>p</i> &lt; 0.001), ventricular enlargement (<i>p</i> = 0.001), and sulcal widening (<i>p</i> = 0.001). High LDL was not significantly associated with any of the measured cranial imaging outcomes. <b><i>Conclusions:</i></b> This study found risk factors for cerebrovascular disease in American Indians similar to those seen in other populations and provides additional evidence for the important roles of hypertension and diabetes in promoting cerebral infarcts and brain atrophy, respectively.
DOI: 10.7284/113838
title: Fluorometer data collected during research cruise EN535 using a Turner 10-AU instrument system onboard the platform RV Endeavor

description: Original (unprocessed) data collected during a Field_expedition