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2021-December-Uh Alumni Homecoming Newsletter December 2021, University School, East Tennessee State University, University Marketing And Communication, East Tennessee State University

ETSU News

Link to University School Alumni Homecoming Newsletter, December 2021

Greetings to our University, Training and Model School Alumni, we hope this message finds each of you doing well!  As we wrap up the semester and final school week for 2021, I would like to take a moment to thank you all for your continued support of University School. The tradition of excellence which has been established at University School is one that we value tremendously and take great pride in continuing!  We believe this is a direct impact of the commitment of our alumni, staff (both past and present) …

Author Correction To: Corticostriatal Functional Connectivity Of Bothersome Tinnitus In Single-Sided Deafness (Scientific Reports, (2019), 9, 1, (19552), 10.1038/S41598-019-56127-1), Jennifer Henderson-Sabes, Yingying Shang, Philip L. Perez, Jolie L. Chang, Seth E. Pross, Anne M. Findlay, Danielle Mizuiri, Leighton B. Hinkley, Srikantan S. Nagarajan, Steven W. Cheung

All Faculty Scholarship

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

“Now I Feel A Little Bit More Secure”: The Impact Of Snap Enrollment On Older Adult Ssi Recipients, Katie Savin, Alena Morales, Ronli Levi, Dora Alvarez, Hilary Seligman

All Faculty Scholarship

In June 2019, California expanded Supplemental Nutrition Assistance Program (SNAP) eligibility to Supplemental Security Income (SSI) beneficiaries for the first time. This research assesses the experience and impact of new SNAP enrollment among older adult SSI recipients, a population characterized by social and economic precarity. We conducted semi-structured, in-depth interviews with 20 SNAP participants to explore their experiences with new SNAP benefits. Following initial coding, member-check groups allowed for participants to provide feedback on preliminary data analysis. Findings demonstrate that SNAP enrollment improved participants’ access to nutritious foods of their choice, contributed to overall budgets, eased mental distress resulting from …

Specific Splice Junction Detection In Single Cells With Sicilian, Roozbeh Dehghannasiri, Julia E. Olivieri, Ana Damljanovic, Julia Salzman

All Faculty Articles - School of Engineering and Computer Science

Precise splice junction calls are currently unavailable in scRNA-seq pipelines such as the 10x Chromium platform but are critical for understanding single-cell biology. Here, we introduce SICILIAN, a new method that assigns statistical confidence to splice junctions from a spliced aligner to improve precision. SICILIAN is a general method that can be applied to bulk or single-cell data, but has particular utility for single-cell analysis due to that data’s unique challenges and opportunities for discovery. SICILIAN’s precise splice detection achieves high accuracy on simulated data, improves concordance between matched single-cell and bulk datasets, and increases agreement between biological replicates. SICILIAN …

Metabolic Syndrome And Acute Respiratory Distress Syndrome In Hospitalized Patients With Covid-19, Joshua L Denson, Aaron S Gillet, Yuanhao Zu, Margo Brown, Thaidan Pham, Yilin Yoshida, Franck Mauvais-Jarvis, Ivor S Douglas, Mathew Moore, Kevin Tea, Andrew Wetherbie, Rachael Stevens, John Lefante, Jeffrey G Shaffer, Donna Lee Armaignac, Katherine Belden, Margit Kaufman, Smith F Heavner, Valerie C Danesh, Sreekanth R Cheruku, Catherine A St Hill, Karen Boman, Neha Deo, Vikas Bansal, Vishakha K Kumar, Allan J Walkey, Rahul Kashyap, Society Of Critical Care Medicine Discovery Viral Infection And Respiratory Illness Universal Study (Virus): Covid-19 Registry Investigator Group

Division of Infectious Diseases and Environmental Medicine Faculty Papers

Importance: Obesity, diabetes, and hypertension are common comorbidities in patients with severe COVID-19, yet little is known about the risk of acute respiratory distress syndrome (ARDS) or death in patients with COVID-19 and metabolic syndrome.

Objective: To determine whether metabolic syndrome is associated with an increased risk of ARDS and death from COVID-19.

Design, setting, and participants: This multicenter cohort study used data from the Society of Critical Care Medicine Discovery Viral Respiratory Illness Universal Study collected from 181 hospitals across 26 countries from February 15, 2020, to February 18, 2021. Outcomes were compared between patients with metabolic syndrome (defined …

Index To Volume 89

Nebraska Bird Review

Adams, Marie 52

to

Zonotrichia leucophrys gambelii 168 leucophrys 75, 168-169 oriantha 75, 169

Review Of The Sandhill Crane State: A Naturalist’S Guide To Nebraska By Paul Johnsgard, Ruth Stearns

Nebraska Bird Review

Dr. Paul Austin Johnsgard left us one last gift, in this reference guide to all places natural in Nebraska. Published posthumously, and available for purchase or free via UNL’s Digital Commons, this book arrived at my doorstep like a veritable “seed catalog” of Nebraska’s places of wonder to delight and inspire fair weather adventures just before the long winter set in. He wants us to explore the state as he had done, to be excited by all the out-ofdoors Nebraska has to offer.

Northern Saw-Whet Owl Autumn Migration In Eastern Nebraska: Results From A Three-Year Banding Study, Stephen J. Brenner, Joel G. Jorgensen

Nebraska Bird Review

Prior to 2019, records of NSWOs in Nebraska during fall were limited. There were fewer than five accepted reports in eastern Nebraska since the 1950s (Silcock and Jorgensen, 2021). The Hitchcock banding station along the Missouri River bluffs in nearby western Iowa has captured, banded, and released 20-50 birds during autumn migration for a number of years (J. Toll, personal communication). Furthermore, a single season banding study in central Nebraska during fall 2004 captured 14 NSWOs (Kim 2005), suggesting the species may migrate annually over much of the state in fall, or at least in more years than previously thought. …

Review Of Nest Records Of Nebraska Birds By Wayne J. Mollhoff, W. Ross Silcock

Nebraska Bird Review

This book summarizes a lifetime of investigation of Nebraska’s breeding birds by Wayne Mollhoff. Even though I say the book summarizes a lifetime of investigation, I would not be surprised if Wayne resurfaces in a few years with a follow-up of some sort, intrepid investigator that he is. Over the years Wayne has spent innumerable days in the field climbing trees in full forestry gear, wading and kayaking marshes and rivers, hiking over prairies, and bushwhacking through dense forests (there are still a few in Nebraska). But this isn’t the totality of Wayne’s talents; he is a determined researcher with …

News From The Bioconductor Project, Bioconductor Core Team

The R Journal

Bioconductor provides tools for the analysis and comprehension of high-throughput genomic data. Bioconductor 3.14 was released on 27 October, 2021. It is compatible with R 4.1.0 and consists of 2083 software packages, 408 experiment data packages, 904 up-to-date annotation packages, and 29 workflows.

Changes In R, Tomas Kalibera, Sebastian Meyer, Kurt Hornik, Gennadiy Starostin, Luke Tierney

The R Journal

We present important changes in the development version of R (referred to as R-devel, to become R 4.2) and give a summary of the new search engine interfaced by RSiteSearch(). Some statistics on bug tracking activities in 2021 are also provided.

Rpese: Risk And Performance Estimators Standard Errors With Serially Dependent Data, Anthony-Alexander Christidis, R Douglas Martin

The R Journal

The R package RPESE (Risk and Performance Estimators Standard Errors) implements a new method for computing accurate standard errors of risk and performance estimators when returns are serially dependent. The new method makes use of the representation of a risk or performance estimator as a summation of a time series of influence-function (IF) transformed returns, and computes estimator standard errors using a sophisticated method of estimating the spectral density at frequency zero of the time series of IF-transformed returns. Two additional packages used by RPESE are introduced, namely RPEIF which computes and provides graphical displays of the IF of risk …

The Vote Package: Single Transferable Vote And Other Electoral Systems In R, Adrian E. Raftery, Hana ŠevčÍková, Bernard W. Silverman

The R Journal

We describe the vote package in R, which implements the plurality (or first-past-the-post), two-round runoff, score, approval, and Single Transferable Vote (STV) electoral systems, as well as methods for selecting the Condorcet winner and loser. We emphasize the STV system, which we have found to work well in practice for multi-winner elections with small electorates, such as committee and council elections, and the selection of multiple job candidates. For single-winner elections, STV is also called Instant Runoff Voting (IRV), Ranked Choice Voting (RCV), or the alternative vote (AV) system. The package also implements the STV system with equal preferences, for …

Volume Approximation And Sampling For Convex Polytopes In R, Apostolos Chalkis, Vissarion Fisikopoulos

The R Journal

Sampling from high-dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering, artificial intelligence, and machine learning. In this paper, we present volesti, an R package that provides efficient, scalable algorithms for volume estimation, uniform, and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language

Bssm: Bayesian Inference Of Non-Linear And Non-Gaussian State Space Models In R, Jouni Helske, Matti Vihola

The R Journal

We present an R package bssm for Bayesian non-linear/non-Gaussian state space modeling. Unlike the existing packages, bssm allows for easy-to-use approximate inference based on Gaussian approximations such as the Laplace approximation and the extended Kalman filter. The package also accommodates discretely observed latent diffusion processes. The inference is based on fully automatic, adaptive Markov chain Monte Carlo (MCMC) on the hyperparameters, with optional importance sampling post-correction to eliminate any approximation bias. The package also implements a direct pseudo-marginal MCMC and a delayed acceptance pseudo-marginal MCMC using intermediate approximations. The package offers an easy-to-use interface to define models with linear-Gaussian state …

Openskies - Integration Of Aviation Data Into The R Ecosystem, Rafael Ayala, Daniel Ayala, Lara Sellés Vidal, David Ruiz

The R Journal

Aviation data has become increasingly more accessible to the public thanks to the adoption of technologies such as Automatic Dependent Surveillance-Broadcast (ADS-B) and Mode S, which provide aircraft information over publicly accessible radio channels. Furthermore, the OpenSky Network provides multiple public resources to access such air traffic data from a large network of ADS-B receivers. Here, we present openSkies, the first R package for processing public air traffic data. The package provides an interface to the OpenSky Network resources, standardized data structures to represent the different entities involved in air traffic data, and functionalities to analyze and visualize such …

Passed: Calculate Power And Sample Size For Two Sample Tests, Jinpu Li, Ryan .. Knigge, Kaiyi Chen, Emily V. Leary

The R Journal

Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis. The relevant statistical theory, calculations, and examples for each distribution using PASSED are discussed in this paper.

Automatic Time Series Forecasting With Ata Method In R: Ataforecasting Package, Ali Sabri Taylan, Güçkan Yapar, Hanife Taylan Selamlar

The R Journal

Ata method is a new univariate time series forecasting method that provides innovative solutions to issues faced during the initialization and optimization stages of existing methods. The Ata method’s forecasting performance is superior to existing methods in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or deseasonalized time series, where the deseasonalization can be performed via any preferred decomposition method. The R package ATAforecasting was developed as a comprehensive toolkit for automatic time series forecasting. It focuses on modeling all types of time series components with any preferred Ata methods and handling seasonality patterns by …

A New Versatile Discrete Distribution, Rolf Turner

The R Journal

This paper introduces a new flexible distribution for discrete data. Approximate moment estimators of the parameters of the distribution, to be used as starting values for numerical optimization procedures, are discussed. “Exact” moment estimation, effected via a numerical procedure, and maximum likelihood estimation, are considered. The quality of the results produced by these estimators is assessed via simulation experiments. Several examples are given of fitting instances of the new distribution to real and simulated data. It is noted that the new distribution is a member of the exponential family. Expressions for the gradient and Hessian of the log-likelihood of the …

Robustbf: An R Package For Robust Solution To The Behrens-Fisher Problem, Gamze Güven, ŞÜkrü Acıtaş, Hatice ŞAmkar, Birdal ŞEnoğLu

The R Journal

Welch’s two-sample t-test based on least squares (LS) estimators is generally used to test the equality of two normal means when the variances are not equal. However, this test loses its power when the underlying distribution is not normal. In this paper, two different tests are proposed to test the equality of two long-tailed symmetric (LTS) means under heterogeneous variances. Adaptive modified maximum likelihood (AMML) estimators are used in developing the proposed tests since they are highly efficient under LTS distribution. An R package called RobustBF is given to show the implementation of these tests. Simulated Type I error rates …

Volesti: Volume Approximation And Sampling For Convex Polytopes In R, Apostolos Chalkis, Vissarion Fisikopoulos

The R Journal

Sampling from high-dimensional distributions and volume approximation of convex bodies are fundamental operations that appear in optimization, finance, engineering, artificial intelligence, and machine learning. In this paper, we present volesti, an R package that provides efficient, scalable algorithms for volume estimation, uniform, and Gaussian sampling from convex polytopes. volesti scales to hundreds of dimensions, handles efficiently three different types of polyhedra and provides non existing sampling routines to R. We demonstrate the power of volesti by solving several challenging problems using the R language.

Passed: Calculate Power And Sample Size For Two Sample Tests, University Of Missouri Li, Ryan P. Knigge, Kaiyi Chen, Emily V. Leary

The R Journal

Power and sample size estimation are critical aspects of study design to demonstrate minimized risk for subjects and justify the allocation of time, money, and other resources. Researchers often work with response variables that take the form of various distributions. Here, we present an R package, PASSED, that allows flexibility with seven common distributions and multiple options to accommodate sample size or power analysis. The relevant statistical theory, calculations, and examples for each distribution using PASSED are discussed in this paper.

Robust And Efficient Optimization Using A Marquardt-Levenberg Algorithm With R Package Marqlevalg, Viviane Philipps, Boris P. Hejblum, Mélanie Prague, Daniel Commenges, Cécile Proust-Lima

The R Journal

Implementations in R of classical general-purpose algorithms for local optimization generally have two major limitations which cause difficulties in applications to complex problems: too loose convergence criteria and too long calculation time. By relying on a Marquardt-Levenberg algorithm (MLA), a Newton-like method particularly robust for solving local optimization problems, we provide with marqLevAlg package an efficient and general-purpose local optimizer which (i) prevents convergence to saddle points by using a stringent convergence criterion based on the relative distance to minimum/maximum in addition to the stability of the parameters and of the objective function; and (ii) reduces the computation time in …

Emss: New Em-Type Algorithms For The Heckman Selection Model In R, Kexuan Yang, Sang Kyu Lee, Jun Zhao, Hyoung-Moon Kim

The R Journal

When investigators observe non-random samples from populations, sample selectivity problems may occur. The Heckman selection model is widely used to deal with selectivity problems. Based on the EM algorithm, Zhao et al. (2020) developed three algorithms, namely, ECM, ECM(NR), and ECME(NR), which also have the EM algorithm’s main advantages: stability and ease of implementation. This paper provides the implementation of these three new EM-type algorithms in the package EMSS and illustrates the usage of the package on several simulated and real data examples. The comparison between the maximum likelihood estimation method (MLE) and three new EM-type algorithms in robustness issues …

Bayessenmc: An R Package For Bayesian Sensitivity Analysis Of Misclassification, Jinhui Yang, Lifeng Lin, Haitao Chu

The R Journal

In case–control studies, the odds ratio is commonly used to summarize the association between a binary exposure and a dichotomous outcome. However, exposure misclassification frequently appears in case–control studies due to inaccurate data reporting, which can produce bias in measures of association. In this article, we implement a Bayesian sensitivity analysis of misclassification to provide a full posterior inference on the corrected odds ratio under both non-differential and differential misclassification. We present an R (R Core Team, 2018) package BayesSenMC, which provides user-friendly functions for its implementation. The usage is illustrated by a real data analysis on the association between …

Dad: An R Package For Visualisation, Classification And Discrimination Of Multivariate Groups Modelled By Their Densities, Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Sabine Demotes-Mainard

The R Journal

Multidimensional scaling (MDS), hierarchical cluster analysis (HCA), and discriminant analysis (DA) are classical techniques which deal with data made of n individuals and p variables. When the individuals are divided into T groups, the R package dad associates with each group a multivariate probability density function and then carries out these techniques on the densities, which are estimated by the data under consideration. These techniques are based on distance measures between densities: chi-square, Hellinger, Jeffreys, Jensen-Shannon, and L^p for discrete densities, Hellinger , Jeffreys, L² , and 2-Wasserstein for Gaussian densities, and L² for numeric non-Gaussian densities …

Stratigrapher: Concepts For Litholog Generation In R, Sébastien Wouters, Anne-Christine Da Silva, Frédéric Boulvain, Xavier Devleeschouwer

The R Journal

The StratigrapheR package proposes new concepts for the generation of lithological logs, or lithologs, in R. The generation of lithologs in a scripting environment opens new opportunities for the processing and analysis of stratified geological data. Among the new concepts presented: new plotting and data processing methodologies, new general R functions, and computer-oriented data conventions are provided. The package structure allows for these new concepts to be further improved, which can be done independently by any R user. The current limitations of the package are highlighted, along with the limitations in R for geological data processing, to help identify the …

Msae: An R Package Of Multivariate Fay-Herriot Models For Small Area Estimation, Novia Permatasari, Azka Ubaidillah

The R Journal

The paper introduces an R Package of multivariate Fay-Herriot models for small area estimation named msae. This package implements four types of Fay-Herriot models, including univariate Fay-Herriot model (model 0), multivariate Fay-Herriot model (model 1), autoregressive multivariate Fay-Herriot model (model 2), and heteroskedastic autoregressive multivariate Fay-Herriot model (model 3). It also contains some datasets generated based on multivariate Fay-Herriot models. We describe and implement functions through various practical examples. Multivariate Fay-Herriot models produce a more efficient parameter estimation than direct estimation and univariate model.

Estimating Social Influence Effects In Networks Using A Latent Space Adjusted Approach In R, Ran Xu

The R Journal

Social influence effects have been extensively studied in various empirical network research. However, many challenges remain in estimating social influence effects in networks, as influence effects are often entangled with other factors, such as homophily in the selection process and the common social-environmental factors that individuals are embedded in. Methods currently available either do not solve these problems or require stringent assumptions. Recent works by Xu (2018) and others have shown that a latent space adjusted approach based on the latent space model has the potential to disentangle the influence effects from other processes, and the simulation evidence has shown …

G2f As A Novel Tool To Find And Fill Gaps In Metabolic Networks, Daniel Osorio, Kelly Botero, Andrés Pinzón Velasco, Nicolás Mendoza-Mejía, Felipe Rojas-Rodríguez, George Barreto, Janneth González

The R Journal

During the building of a genome-scale metabolic model, there are several dead-end metabolites and substrates which cannot be imported, produced, nor used by any reaction incorporated in the network. The presence of these dead-end metabolites can block out the net flux of the objective function when it is evaluated through Flux Balance Analysis (FBA), and when it is not blocked, bias in the biological conclusions increase. In this aspect, the refinement to restore the connectivity of the network can be carried out manually or using computational algorithms. The g2f package was designed as a tool to find the gaps from …