University of Alabama

About: University of Alabama is a education organization based out in Tuscaloosa, Alabama, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 27323 authors who have published 48609 publications receiving 1565337 citations. The organization is also known as: Alabama & Bama.

Lessons learned from whole exome sequencing in multiplex families affected by a complex genetic disorder, intracranial aneurysm

Abstract: Genetic risk factors for intracranial aneurysm (IA) are not yet fully understood. Genomewide association studies have been successful at identifying common variants; however, the role of rare variation in IA susceptibility has not been fully explored. In this study, we report the use of whole exome sequencing (WES) in seven densely-affected families (45 individuals) recruited as part of the Familial Intracranial Aneurysm study. WES variants were prioritized by functional prediction, frequency, predicted pathogenicity, and segregation within families. Using these criteria, 68 variants in 68 genes were prioritized across the seven families. Of the genes that were expressed in IA tissue, one gene (TMEM132B) was differentially expressed in aneurysmal samples (n=44) as compared to control samples (n=16) (false discovery rate adjusted p-value=0.023). We demonstrate that sequencing of densely affected families permits exploration of the role of rare variants in a relatively common disease such as IA, although there are important study design considerations for applying sequencing to complex disorders. In this study, we explore methods of WES variant prioritization, including the incorporation of unaffected individuals, multipoint linkage analysis, biological pathway information, and transcriptome profiling. Further studies are needed to validate and characterize the set of variants and genes identified in this study.

Radar-Based Human-Motion Recognition With Deep Learning: Promising applications for indoor monitoring

Abstract: Deep learning (DL) has shown tremendous promise in radar applications that involve target classification and imaging. In the field of indoor monitoring, researchers have shown an interest in DL for classifying daily human activities, detecting falls, and monitoring gait abnormalities. Driving this interest are emerging applications related to smart and secure homes, assisted living, and medical diagnosis. The success of DL in providing an accurate real-time accounting of observed humanmotion articulations fundamentally depends on the neural network structure, input data representation, and proper training. This article puts DL in the context of data-driven approaches for motion classification and compares its performance with other approaches employing handcrafted features. We discuss recent proposed enhancements of DL classification performance and report on important challenges and possible future research to realize its full potential.

Individual, Organizational/Work and Environmental Influences on Expatriate Turnover Tendencies: An Empirical Study

Abstract: Foreign postings for executives are costly undertakings for multinational corporations, especially when they fail. Yet little research has been done on the causes of expatriate turnover. This 155-expatriate survey assesses individual, organizational/work and environmental influences on both internal and external turnover tendencies. It was found that job autonomy and material life satisfaction were key predictors for both internal and external turnover tendencies. Only for organizational turnover did job autonomy supersede material life satisfaction as the lead predictor of turnover tendencies. American expatriates attach much importance to maintaining living standards in postings to foreign locations.

Basic vibration signal processing for bearing fault detection

Abstract: Faculty in the College of Engineering at the University of Alabama developed a multidisciplinary course in applied spectral analysis that was first offered in 1996. The course is aimed at juniors majoring in electrical, mechanical, industrial, or aerospace engineering. No background in signal processing or Fourier analysis is assumed; the requisite fundamentals are covered early in the course and followed by a series of laboratories in which the fundamental concepts are applied. In this paper, a laboratory module on fault detection in rolling element bearings is presented. This module is one of two laboratory modules focusing on machine condition monitoring applications that were developed for this course. Background on the basic operational characteristics of rolling element bearings is presented, and formulas given for the calculation of the characteristic fault frequencies. The shortcomings of conventional vibration spectral analysis for the detection of bearing faults is examined in the context of a synthetic vibration signal that students generate in MATLAB. This signal shares several key features of vibration signatures measured on bearing housings. Envelope analysis and the connection between bearing fault signatures and amplitude modulation/demodulation is explained. Finally, a graphically driven software utility (a set of MATLAB m-files) is introduced. This software allows students to explore envelope analysis using measured data or the synthetic signal that they generated. The software utility and the material presented in this paper constitute an instructional module on bearing fault detection that can be used as a stand-alone tutorial or incorporated into a course.

Influence of occupational socialization on beginning teachers' interpretation and delivery of sport education

Abstract: The purpose of this study was to determine the extent to which newly qualified teachers employed the Sport Education (SE) model. In addition, we attempted to discover factors that led to and facilitated beginning teachers employing the model and those that did not. Participants were six American and four British beginning teachers. Data were collected by formally interviewing each teacher. Analysis procedures employed were analytic induction and constant comparison. Occupational socialization was the theoretical framework that guided data collection and analysis procedures. The results indicated that teachers interpreted and delivered SE in one of three different ways: full version, watered down version and cafeteria style. Moreover, the teachers’ acculturation, professional socialization and organizational socialization largely explained why teachers interpreted and delivered SE as they did.