Title: Effects of minimal dose of resistance training on body composition and running performance in female recreational runners Objective: The purpose of this study was to analyse the extent to which minimal dose resistance training would elicit improvements in running performance and body composition for female recreational runners. Methods: Forty-one female recreational runners were randomly assigned to one of three groups (endurance running [V] n=14; combined endurance running and resistance training program once [VR30] n=14 and twice a week [VR60] n=13, respectively). During the 10-week training program, the V group completed 3 hours of continuous endurance running per week; VR30 completed 2 ½ hours of continuous endurance running and 1 x 30 min of resistance training per week, while VR60 group completed 2 hours of continuous endurance running and 2x30 min of resistance training per week. Body composition (FM, FFM, ECM/BCM), standing long jump, running economy, ventilatory anaerobic threshold and maximal endurance performance characteristics were assessed using ANOVA with repeated measures. Body composition was assessed via whole-body bio impedance. Performance parameters were determined during running on a treadmill. Results: Thirty-one female recreational runners completed 10-week...

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This study examines the performance of concurrent algorithms for B-trees and linear hashing. B-trees are widely used as an access method for large, single key, database files, stored in lexicographic order on secondary storage devices. Linear hashing is a fast and reliable hash algorithm, suitable for accessing records stored unordered in buckets. This dissertation presents performance results on implementations of concurrent Bunk-tree and linear hashing algorithms, using lock-based, partitioned and distributed methods on the Sequent Symmetry shared memory multiprocessor system and on a network of distributed processors created with PVM (Parallel Virtual Machine) software. Initial experiments, which started with empty data structures, show good results for the partitioned implementations and lock-based linear hashing, but poor ones for lock-based Blink-trees. A subsequent test, which started with loaded data structures, shows similar results, but with much improved performances for locked Blink- trees. The data also highlighted the high cost of split operations, which reached up to 70% of the total insert time.

The present study investigated the effects of a concurrent schedules arrangement, in which three dimensions of reinforcement (duration, attention, and stimuli) were manipulated, on choice responding, appropriate behavior, and problem behavior for three participants with disabilities who had escape-maintained problem behavior. Three experiments were conducted in which participants could choose between work, break, or problem behavior. In the first experiment, the choice analysis, three reinforcement dimensions were varied simultaneously for choice responses. In the second experiment, the component choice analysis, reinforcement dimensions were evaluated in isolation. In the third experiment, the effort analysis, increasing task demand requirements and how they affected response allocation were investigated. Results of the first experiment were consistent across all participants, and suggested that participants allocated their choices in favor of reinforcement contingencies that resulted in breaks with the longest duration, high preference stimuli, and high quality attention. Results of the second and third experiments, however, were idiosyncratic across participants. Component choice analysis results suggested that only specific reinforcement dimensions maintained responding for some participants, whereas all reinforcement dimensions maintained response allocation for others. Results of the third experiment suggested that as task demands increased, reinforcement contingencies that previously maintained responding in the second experiment did not always continue to maintain responding for all participants. This study contributes to and extends the literature on choice making in several ways. The majority of previously published investigations evaluated different dimensions of reinforcement when only two response options were concurrently available, and many of these studies only examined one or two reinforcement dimensions. The present study used a concurrent schedules arrangement in which three concurrently available response options existed. Like previous research the present study suggests that quality of reinforcement can be manipulated to effectively bias individuals' responding in favor of adaptive responses, and the quality variables that impact choice responding may or may not be related to the function of problem behavior. However, further research is needed to understand how choice responding is impacted by increasing demand requirements, as this study demonstrated that choice responding was idiosyncratically affected by changing task demands.

The purpose of this study was to assess the concurrent validity of the JAPQ in predicting the work output and tenure levels of persons employed in the occupation of Data Entry Operator-Financial Keyer. Three separate hypotheses were tested: (1) JAPQ-D2 differences based on employee tenure and output loads; (2) JAPQ dimension preference differences, which may not be reflected in JAPQ-D2 scores; and, (3) the relationship between employee tenure and employee output. Separate research questions focused on the applicability of the JAPQ in predicting employee tenure and employee output, based on multiple regression results. Sixty financial keyers were administered the JAPQ for comparison against a concurrent PAQ job analysis. For hypothesis testing, the subjects were separated into four groups according to tenure or output. No differences were found in the overall JAPQ-D2 score, comparing "high" (D2 = 6.53) vs. "low" (D2 = 6.60) output keyers and "long" (JAPQ-D2 = 6.26) vs. "short" (D2 = 7.16) tenured keyers. The keyer dimension profiles were highly similar, as indicated by positive correlations in the ranking of JAPQ dimension preferences for "high" vs. "low" output keyers (rho = .962; p ≥ .001) and for "long" vs. "short" tenured keyers (rho = .979; p ≥ .001). No relationship was found between keyer tenure and keyer output (r = .088; df = 58). When viewing the data incorporated in this area, two employees with extensive tenure and below average output appeared to have skewed the data. The data for these two employees was deleted and a second correlation was completed, resulting in a positive relationship between keyer tenure and keyer output (r = .426; df = 56; p < .01). Multiple regressions of JAPQ dimensions indicated promising predictability for "high output" keyers (adjusted R = .335; p ≥ .01) and for "long tenured" keyers (adjusted R = .433; ≥ .001). All results were discussed in respect to use of the JAPQ as an instrument for use in the personnel office. Recommendations for similar research is also mentioned.

Concurrent enrollment of high school students in college classes is becoming more common but it has not been clear if high school students can learn the material as well as college students. This study examined high-school and college students' learning by exposing them to the same text, a similar lesson plan, and the same test questions, while controlling for demographic, attitudinal, and experiential variables. Two questions were addressed: (a) Was there a practical difference between high school and college students in their ability to learn the material; and (b) was there a difference in the way they learned the material? The difference between college and high-school student learning as it was reflected by their test scores was less than three percentage points, with college students averaging higher. Although this was a statistically significant difference, there appeared to be no practical difference between high school and college students in their ability to learn the material. However, simple mean comparisons indicated that besides age, grade level, and scores, college and high-school students differed in a statistically significant way in their perception of teacher involvement, and how easy the class was. Furthermore, hierarchically regressing scores on a-order correlates, with a dichotomous variable representing high-school or college status entered last, still yielded a statistically significant difference between high-school and college student scores. Learning differences between groups were further defined using separate regression equations based on the expected independence of college students compared with the dependence of high school students. The expectation that there may have been a difference in the way students learned in high school and college appeared to have been confirmed. That is, factors related to independence seemed to predict college student scores better than those of high school students, and factors related to dependence predicted high-school student scores better than those of college students.

Nursing leaders have called for more bachelor-of-science-in-nursing-(BSN)-prepared nurses to meet workforce demands. There is limited capacity in BSN programs to meet the projected demand. Currently, associate degree in nursing (ADN) programs produce the majority of registered nurses. To increase the number of BSN graduates, nurse educators recommend innovative educational models for seamless progression from the ADN to the BSN. Concurrent enrollment ADN-BSN programs offer one potential model to produce more BSN graduates. The purpose of this study was to describe the process of developing and implementing concurrent enrollment ADN-BSN programs. The research question was as follows: What is the experience of nurse educators in developing and implementing concurrent enrollment ADN-BSN completion programs? The method of inquiry was a generic qualitative descriptive study. Seventeen participants were recruited from concurrent enrollment programs across the country. Data collection occurred through semi-structured email interviews. The data was manually coded using holistic, descriptive and in vivo coding methods and then analyzed using situational mapping for similar patterns and thematic concepts. There were five conceptual themes that described the process of developing and implementing concurrent enrollment ADN-BSN programs. The five themes emerged as championing the program, establishing partnerships, predicting student success, promoting student success, and adapting to change. The implications to nurse educators are a better understanding of an innovative educational model to produce more BSN graduates. More BSN graduates benefits the nursing profession. Further research is needed to understand the benefits and drawbacks of concurrent enrollment programs and the factors that influence adoption of this educational model.

Somatic Copy Number Alterations (CNAs) are common events in human cancers. Identifying CNAs and Significant Copy number Aberrations (SCAs) in cancer genomes is a critical task in searching for cancer-associated genes. Advanced genome profiling technologies, such as SNP array technology, facilitate copy number study at a genome-wide scale with high resolution. However, due to normal tissue contamination, the observed intensity signals are actually the mixture of copy number signals contributed from both tumor and normal cells. This genetic confounding factor would significantly affect the subsequent copy number analyses. In order to accurately identify significant aberrations in contaminated cancer genome, we develop a Java AISAIC package (Accurate Identification of Significant Aberrations in Cancer) that incorporates recent novel algorithms in the literature, BACOM (Bayesian Analysis of Copy number Mixtures) and SAIC (Significant Aberrations in Cancer). Specifically, BACOM is used to estimate the normal tissue contamination fraction and recover the "true" copy number profiles. And SAIC is used to detect SCAs using large recovered tumor samples. Considering the popularity of modern multi-core computers and clusters, we adopt concurrent computing using Java Fork/Join API to speed up the analysis. We evaluate the performance of the AISAIC package in both empirical family-wise type I error rate and detection power on a large number of simulation data, and get promising results. Finally, we use AISAIC to analyze real cancer data from TCGA portal and detect many SCAs that not only cover majority of reported cancer-associated genes, but also some novel genome regions that may worth further study. / Master of Science

The increasing prevalence of multi and many core processors has brought the issues of concurrency and parallelism to the forefront of everyday computing. Even for applications amenable to traditional parallelization techniques, the subtleties of concurrent programming are known to introduce concurrency bugs. Due to the potential of concurrency bugs, programmers find it hard to write correct concurrent code. To take full advantage of parallel shared memory platforms, application programmers need safe and efficient mechanisms that can support a wide range of parallel applications. In addition, a large body of applications are inherently hard-to-parallelize; their data and control dependencies impose execution order constraints that preclude the use of traditional parallelization techniques. Sensitive to their input data, a substantial number of applications fail to scale well, leaving cores idle. To improve the performance of such applications, application programmers need effective mechanisms that can fully leverage multi and many core architectures. These challenges stand in the way of realizing the true potential of emerging many core platforms. The techniques described in this dissertation address these challenges. Specifically, this dissertation contributes techniques to transparently detect and eliminate several concurrency bugs, including deadlocks, asymmetric write-write data races, priority inversion, live-locks, order violations, and bugs that stem from the presence of asynchronous signaling and locks. A second major contribution of this dissertation is a programming framework that exploits coarse-grain speculative parallelism to improve the performance of otherwise hard-to-parallelize applications. / Ph. D.