Physical Sciences and Mathematics Commons^™

Magnetic Massive Stars As Progenitors Of ‘Heavy’ Stellar-Mass Black Holes, V. Petit, Z. Keszthelyi, R. Macinnis, D. H. Cohen, R. H. D. Townsend, G. A. Wade, S. L. Thomas, S. P. Owocki, J. Puls, A. Ud-Doula

Aerospace, Physics, and Space Science Faculty Publications

The groundbreaking detection of gravitational waves produced by the inspiralling and coales- cence of the black hole (BH) binary GW150914 confirms the existence of ‘heavy’ stellar-mass BHs with masses >25 M . Initial characterization of the system by Abbott et al. supposes that the formation of BHs with such large masses from the evolution of single massive stars is only feasible if the wind mass-loss rates of the progenitors were greatly reduced relative to the mass-loss rates of massive stars in the Galaxy, concluding that heavy BHs must form in low-metallicity (Z ,:S 0.25 0.5 Z ) environments. However, strong …

Teaching Android Security Through Examples: A Publicly Available Database Of Vulnerable Apps, Daniel E. Krutz, Samuel A. Malachowsky

Articles

Security is hard, and teaching security can be even harder. Here we describe a public educational activity to assist in the instruction of both students and developers in creating secure Android apps. Our set of activities includes example vulnerable applications, information about each vulnerability, steps on how to repair the vulnerabilities, and information about how to confirm that the vulnerability has been properly repaired. Our primary goal is to make these activities available to other instructors for use in their classrooms ranging from the K-12 to university settings. A secondary goal of this project is to foster interest in security …

Solving Boundary Value Problems On Various Domains, Ibraheem Otuf

Graduate Theses/Dissertations

Domain-sensitivity is a hallmark in the realm of solving boundary value problems in partial differential equations. For example, the method used in solving a boundary value problem on an finite cylindrical domain is very different from one that arises from a rectangular domain. The difference is also reflected in the types of functions employed in the processes of solving these boundary value problems, as are the mathematical tools utilized in deriving an analytic solution. In this thesis, we solve an important class of partial differential equations with boundary conditions coming from various domains, such as the n dimensional cube, circles, …

Deep Feature Transfer Learning In Combination With Traditional Features Predicts Survival Among Patients With Lung Adenocarcinoma, Rahul Paul, Samuel H. Hawkings, Matthew B. Schabath, Robert J. Gilies, Lawrence O. Hall, Dmitry Goldgof

Computer Science and Engineering Faculty Publications

Lung cancer is the most common cause of cancer-related deaths in the USA. It can be detected and diagnosed using computed tomography images. For an automated classifier, identifying predictive features from medical images is a key concern. Deep feature extraction using pretrained convolutional neural networks (CNNs) has recently been successfully applied in some image domains. Here, we applied a pretrained CNN to extract deep features from 40 computed tomography images, with contrast, of non-small cell adenocarcinoma lung cancer, and combined deep features with traditional image features and trained classifiers to predict short- and long-term survivors. We experimented with several pretrained …

Incremental And Decremental Svm For Regression, Honorius Gâlmeanu, Lucian Mircea Sasu, Rǎzvan Andonie

All Faculty Scholarship for the College of the Sciences

Training a support vector machine (SVM) for regression (function approximation) in an incremental/decremental way consists essentially in migrating the input vectors in and out of the support vector set with specific modification of the associated thresholds. We introduce with full details such a method, which allows for defining the exact increments or decrements associated with the thresholds before vector migrations take place. Two delicate issues are especially addressed: the variation of the regularization parameter (for tuning the model performance) and the extreme situations where the support vector set becomes empty. We experimentally compare our method with several regression methods: the …

Geosciences Newsletter - 2016, Department Of Geosciences

Geological and Environmental Sciences News

Vol. 8, No. 2

• Greetings from the Chair
• Faculty & Staff
• Michigan Geological Survey
• MGRRE
• CoreKids
• Geosciences Advisory Council
• 2016 Distinguished Alumni Award
• Endowments and Donors
• Department Publications
• Student Scholarships & Awards
• Our Students
• Student Organizations

Message From The Vice President Of Research, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Scholarships, The Mcnair Team

McNair Scholars Research Journal

No abstract provided.

Genomics And Csf Analyses Implicate Thyroid Hormone In Hippocampal Sclerosis Of Aging, Peter T. Nelson, Yuriko Katsumata, Kwangsik Nho, Sergey C. Artiushin, Gregory A. Jicha, Wang-Xia Wang, Erin L. Abner, Andrew J. Saykin, Walter A. Kukull, Alzheimer’S Disease Neuroimaging Initiative (Adni), David W. Fardo

Sanders-Brown Center on Aging Faculty Publications

We report evidence of a novel pathogenetic mechanism in which thyroid hormone dysregulation contributes to dementia in elderly persons. Two single nucleotide polymorphisms (SNPs) on chromosome 12p12 were the initial foci of our study: rs704180 and rs73069071. These SNPs were identified by separate research groups as risk alleles for non-Alzheimer’s neurodegeneration. We found that the rs73069071 risk genotype was associated with hippocampal sclerosis (HS) pathology among people with the rs704180 risk genotype (National Alzheimer’s Coordinating Center/Alzheimer’s Disease Genetic Consortium data; n = 2113, including 241 autopsy-confirmed HS cases). Furthermore, both rs704180 and rs73069071 risk genotypes were associated with widespread brain …

Review Of Booming From The Mists Of Nowhere: The Story Of The Greater Prairie-Chicken By Greg Hoch, Ross H. Hier

The Prairie Naturalist

The Greater Prairie-Chicken (Tympanuchus cupido pinnatus) is an iconic species inhabiting one of the most iconic and rarest habitats in the world—the tallgrass prairies of central North America. To tell the story of the Greater Prairie-Chicken is a monumental task. Its history is intricately woven into pre- and post-European settlement of the North American prairies in such a way that knowledge of the species is spread over several centuries. Thus, researching the “old and the new” regarding the Greater Prairie-Chicken requires a substantial literature review, much of which occurs in publications from the 1800s. Hoch has done a …

Finding The Best Remaining Black Hills Montane Grasslands, The First Step In Conservation, Hollis Marriott, Don Faber-Langendoen, David J. Ode

The Prairie Naturalist

Black Hills Montane Grassland is a rare and endangered plant community endemic to the Black Hills of western South Dakota and northeastern Wyoming. It is restricted to higher elevations on the Limestone Plateau in the western part of the uplift. Early visitors to the Black Hills wrote glowing reports of flower-filled grasslands on the Limestone Plateau. Lieutenant Colonel George A. Custer and his soldiers reveled in lush grass, and decorated the headgear of their horses with flowers (Custer 1875). Expedition botanist A. B. Donaldson “estimated the number of flowers in bloom in Floral Valley at 50, while an equal number …

Changes In The Prairie Naturalist For 2017: Some Bumps In The Road During Transition, Christopher N. Jacques

The Prairie Naturalist

By now it is obvious to most of our members and authors that The Prairie Naturalist (TPN) has experienced some delays in conducting journal-related business over the past few months. Publication of the June 2016 issue was slightly delayed and the December 2016 was mailed much later than planned. So I wanted to update our members on the current status, and other aspects, of TPN. As most of you know, when I transitioned into the Editorship of TPN, one of my first orders of business was to secure a new publication venue for the journal. Fortunately, the Department …

Reproductive Characteristics Of Landlocked Fall Chinook Salmon From Lake Oahe, South Dakota, Kelsen L. Young, Michael E. Barnes, Jeremy L. Kientz

The Prairie Naturalist

Lake Oahe, South Dakota, USA, landlocked fall Chinook salmon (Oncorhynchus tshawytscha) reproductive characteristics were examined over a 27 year period, from 1988 to 2015. Mean total lengths of spawning females ranged from 665 mm (1995) to 812 mm (2015) with considerable year-to-year variation. Post-spawn female weights varied, ranging from 2.02 kg (2000) to 5.55 kg (2015), with an overall mean of 3.04 kg. Fecundity peaked at 4,555 eggs per female in 2003, which was just 3 years after a low of 2,011 eggs per female in 2000. Relative fecundity based on female weight was greatest at 1,211 eggs/kg …

Assessment Of Smallmouth Bass Growth And Mortality In Nebraska Waters, Benjamin J. Schall, Keith D. Koupal, Casey W. Schoenebeck, Keith L. Hurley

The Prairie Naturalist

Smallmouth bass (Micropterus dolomieu) have been introduced across Nebraska into a variety of waterbodies. However, an estimate of smallmouth bass growth and mortality in Nebraska waters has not been produced. The objectives of this study were to use historic sampling data to describe the growth of smallmouth bass in Nebraska lakes in relation to other regional models, growth among waterbody types (reservoirs, Interstate 80 [I-80] lakes, and rivers), estimates of age at quality, preferred, and memorable lengths, and mortality for Nebraska smallmouth bass populations. Mean length ± SE of Nebraska smallmouth bass at age 7 was 383 ± …

Review Of Plants Have So Much To Give Us, All We Have To Do Is Ask: Anishinaabe Botanical Teachings By Mary Siisip Geniusz (Edited By Wendy Makoons Geniusz, Illustrated By Annmarie Geniusz), Natasha Myhal, Kelly Kindscher

The Prairie Naturalist

Plants Have So Much to Give Us, All We Have to Do Is Ask offers a new look at Anishinaabe (Ojibwe) ethnobotany as told through traditional stories. Botanical teachings through stories are a way to pass down traditional knowledge from generation to generation. For example, Anishinaabe knowledge on plants was written and recorded in communities willing to share their knowledge with early scholars, such as Albert B. Reagan (1928), Huron H. Smith (1932), and Melvin R. Gilmore (1933). Each of these scholars spent time with an Anishinaabe community to learn about plants and primarily to provide written descriptions of plants …

Changes In R, R Core Team

The R Journal

CHANGES IN R 3.3.2 patched

Mctest: An R Package For Detection Of Collinearity Among Regressors, Muhammad Imdadullah, Muhammad Aslam, Saima Altaf

The R Journal

It is common for linear regression models to be plagued with the problem of multicollinearity when two or more regressors are highly correlated. This problem results in unstable estimates of regression coefficients and causes some serious problems in validation and interpretation of the model. Different diagnostic measures are used to detect multicollinearity among regressors. Many statistical software and R packages provide few diagnostic measures for the judgment of multicollinearity. Most widely used diagnostic measures in these software are: coefficient of determination (R2), variance inflation factor/tolerance limit (VIF/TOL), eigenvalues, condition number (CN) and condition index (CI) etc. In this manuscript, we …

Subgroup Discovery With Evolutionary Fuzzy Systems In R: The Sdefsr Package, Ángel M. García, Francisco Charte, Pedro González, Cristóbal J. Carmona, María J. Del Jesus

The R Journal

Subgroup discovery is a data mining task halfway between descriptive and predictive data mining. Nowadays it is very relevant for researchers due to the fact that the knowledge extracted is simple and interesting. For this task, evolutionary fuzzy systems are well suited algorithms because they can find a good trade-off between multiple objectives in large search spaces. In fact, this paper presents the SDEFSR package, which contains all the evolutionary fuzzy systems for subgroup discovery presented throughout the literature. It is a package without dependencies on other software, providing functions with recommended default parameters. In addition, it brings a graphical …

Diverse: An R Package To Analyze Diversity In Complex Systems, Miguel R. Guevara, Dominik Hartmann, Marcelo Mendoza

The R Journal

The package diverse provides an easy-to-use interface to calculate and visualize different aspects of diversity in complex systems. In recent years, an increasing number of research projects in social and interdisciplinary sciences, including fields like innovation studies, scientometrics, economics, and network science have emphasized the role of diversification and sophistication of socioeconomic systems. However, so far no dedicated package exists that covers the needs of these emerging fields and interdisciplinary teams. Most packages about diversity tend to be created according to the demands and terminology of particular areas of natural and biological sciences. The package diverse uses interdisciplinary concepts of …

Qpot: An R Package For Stochastic Differential Equation Quasi-Potential Analysis, Christopher M. Moore, Christopher R. Stieha, Ben C. Nolting, Maria K. Cameron, Karen C. Abbott

The R Journal

QPot (pronounced ky oo + p¨ at) is an R package for analyzing two-dimensional systems of stochastic differential equations. It provides users with a wide range of tools to simulate, analyze, and visualize the dynamics of these systems. One of QPot’s key features is the computation of the quasi-potential, an important tool for studying stochastic systems. Quasi-potentials are particularly useful for comparing the relative stabilities of equilibria in systems with alternative stable states. This paper describes QPot’s primary functions, and explains how quasi-potentials can yield insights about the dynamics of stochastic systems. Three worked examples guide users through the application …

Normal Tolerance Interval Procedures In The Tolerance Package, Derek S. Young

The R Journal

Statistical tolerance intervals are used for a broad range of applications, such as quality control, engineering design tests, environmental monitoring, and bioequivalence testing. tolerance is the only R package devoted to procedures for tolerance intervals and regions. Perhaps the most commonly-employed functions of the package involve normal tolerance intervals. A number of new procedures for this setting have been included in recent versions of tolerance. In this paper, we discuss and illustrate the functions that implement these normal tolerance interval procedures, one of which is a new, novel type of operating characteristic curve.

Micompr: An R Package For Multivariate Independent Comparison Of Observations, Nuno Fachada, João Rodrigues, Vitor V. Lopes, Rui C. Martins, Agostinho C. Rosa

The R Journal

The R package micompr implements a procedure for assessing if two or more multivariate samples are drawn from the same distribution. The procedure uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar high-dimension multivariate observations

Rnrfa: An R Package To Retrieve, Filter And Visualize Data From The Uk National River Flow Archive, Claudia Vitolo, Matthew Fry, Wouter Buytaert

The R Journal

The UK National River Flow Archive (NRFA) stores several types of hydrological data and metadata: daily river flow and catchment rainfall time series, gauging station and catchment information. Data are served through the NRFA webservices via experimental RESTful APIs. Obtaining NRFA data can be unwieldy due to complexities in handling HTTP GET requests and parsing responses in JSON and XML formats. The rnrfa package provides a set of functions to programmatically access, filter, and visualize NRFA data using simple R syntax. This paper describes the structure of the rnrfa package, including examples using the main functions gdf() and cmr() for …

Simulating Correlated Binary And Multinomial Responses Under Marginal Model Specification: The Simcormultres Package, Anestis Touloumis

The R Journal

We developed the R package SimCorMultRes to facilitate simulation of correlated categorical (binary and multinomial) responses under a desired marginal model specification. The simulated correlated categorical responses are obtained by applying threshold approaches to correlated continuous responses of underlying regression models and the dependence structure is parametrized in terms of the correlation matrix of the latent continuous responses. This article provides an elaborate introduction to the SimCorMultRes package demonstrating its design and usage via three examples. The package can be obtained via CRAN.

Nmfgpu4r: Gpu-Accelerated Computation Of The Non-Negative Matrix Factorization (Nmf) Using Cuda Capable Hardware, Sven Koitka, Christoph M. Friedrich

The R Journal

In this work, a novel package called nmfgpu4R is presented, which offers the computation of Non-negative Matrix Factorization (NMF) on Compute Unified Device Architecture (CUDA) platforms within the R environment. Benchmarks show a remarkable speed-up in terms of time per iteration by utilizing the parallelization capabilities of modern graphics cards. Therefore the application of NMFgets more attractive for real-world sized problems because the time to compute a factorization is reduced by an order of magnitude.

Comf: An R Package For Thermal Comfort Studies, Marcel Schweiker

The R Journal

The field of thermal comfort generated a number of thermal comfort indices. Their code implementation needs to be done by individual researchers. This paper presents the R package, comf, which includes functions for common and new thermal comfort indices. Additional functions allow comparisons between the predictive performance of these indices. This paper reviews existing thermal comfort indices and available code implementations. This is followed by the description of the R package and an example how to use the R package for the comparison of different thermal comfort indices on data from a thermal comfort study.

Quantreg.Nonpar: An R Package For Performing Nonparametric Series Quantile Regression, Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov, Iván Fernández-Val

The R Journal

The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. It also provides point-wise and uniform confidence intervals over a region of covariate values and/or quantile indices for the same functions using analytical and resampling methods. This paper serves as an introduction to the package and displays basic functionality of the functions contained within.

Two-Tier Latent Class Irt Models In R, Silvia Bacci, Francesco Bartolucci

The R Journal

In analyzing data deriving from the administration of a questionnaire to a group of individuals, Item Response Theory (IRT) models provide a flexible framework to account for several aspects involved in the response process, such as the existence of multiple latent traits. In this paper, we focus on a class of semi-parametric multidimensional IRT models, in which these traits are represented through one or more discrete latent variables; these models allow us to cluster individuals into homogeneous latent classes and, at the same time, to properly study item characteristics. In particular, we follow a within-item multidimensional formulation similar to that …

Qtools: A Collection Of Models And Tools For Quantile Inference, Marco Geraci

The R Journal

Quantiles play a fundamental role in statistics. The quantile function defines the distribution of a random variable and, thus, provides a way to describe the data that is specular but equivalent to that given by the corresponding cumulative distribution function. There are many advantages in working with quantiles, starting from their properties. The renewed interest in their usage seen in the last years is due to the theoretical, methodological, and software contributions that have broadened their applicability. This paper presents the R package Qtools, a collection of utilities for unconditional and conditional quantiles.

R Foundation News, Torsten Hothorn

The R Journal

New benefectors

Donations

New supporting institutions

New supporting members