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Saint Joseph's University is a private, coeducational Roman Catholic Jesuit university located in the Overbrook neighborhood of Philadelphia, Pennsylvania, United States of America, and the Lower Merion Township on the historic Pennsylvania Main Line. The University was founded in 1851 as Saint Joseph's College by the Society of Jesus Wikipedia.

Schatz P.,Saint Josephs University
American Journal of Sports Medicine

Background: Prevalence rates of invalid baseline scores on computerized neurocognitive assessments for high school, collegiate, and professional athletes have been published in the literature. At present, there is limited research on the prevalence of invalid baseline scores in pre-high school athletes. Hypothesis: Pre-high school athletes assessed with baseline neurocognitive tests would show higher prevalence rates of invalidity than older youth athletes, and those athletes, regardless of age, who were tested in a large group setting would show a higher prevalence rate of invalidity than athletes tested in a small group setting. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 502 athletes between the ages of 10 and 18 years completed preseason baseline neurocognitive tests in ''large'' or ''small'' groups. All athletes completed the online version of ImPACT (Immediate Post-Concussion Assessment and Cognitive Testing). Baseline test results that were ''flagged'' by the computer software as being of suspect validity and labeled with a ''11'' symbol were identified for analysis. Participants were retrospectively assigned to 2 independent groups: large group or small group. Test administration of the large group occurred off-site in groups of approximately 10 athletes, and test administration of the small group took place at a private-practice neuropsychology center with only 1 to 3 athletes present. Results: Chi-square analyses identified a significantly greater proportion of participants obtaining invalid baseline results on the basis of age; younger athletes produced significantly more invalid baseline scores (7.0%, 17/244) than older athletes (2.7%, 7/258) (x2 (1) = 4.99; P = .021). Log-linear analysis revealed a significant age (10-12 years, 13-18 years) 3 size (small, large) interaction effect (x2 (4) = 66.1; P<.001) on the prevalence of invalidity, whereby younger athletes tested in larger groups were significantly more likely to provide invalid results (11.9%) than younger athletes tested in smaller groups (5.4%), older athletes tested in larger groups (2.7%), and older athletes tested in smaller groups (2.7%). Conclusion: Younger athletes tend to exhibit a greater prevalence of invalid baseline results on neurocognitive computerized tests than older youth athletes; the prevalence increases when testing is conducted in a large group and nonclinical setting. © 2013 The Author(s). Source

Schatz P.,Saint Josephs University | Sandel N.,Widener University
American Journal of Sports Medicine

Background: The utility of postconcussion neurocognitive testing versus symptom data has been debated. The sensitivity of the desktop version of the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) tool has been documented, but psychometric properties of the recently released online version of ImPACT have yet to be fully established. Purpose: To document the sensitivity of the online ImPACT version in samples of (1) symptomatic concussed (high school and collegiate) athletes, and (2) asymptomatic concussed (high school and collegiate) athletes suspected of hiding their concussions. Study Design: Cohort study; Level of evidence, 3. Methods: A total of 81 athletes observed to sustain a concussion by a certified athletic trainer or team physician, a finding that was confirmed with reported postconcussion symptoms, completed the ImPACT test within 3 days of injury. Data were compared with an independent sample of 81 athletes who completed preseason baseline cognitive assessments using ImPACT and who were matched (with concussed athletes) on the basis of sex, age, sport, concussion history, and absence of attention deficit hyperactivity disorder and learning disability. An independent group of 37 athletes who were also observed to sustain a concussion completed ImPACT within 3 days of injury. These athletes reported no postconcussion symptoms but were noted for suspected invalid response patterns on ImPACT (Impulse Control index >30 and Verbal Memory index <69%). The subscale data from the assessments (excluding those contributing to the aforementioned indices) were compared with a matched sample of 37 athletes who completed preseason baseline cognitive assessments in ImPACT (using the same criteria described above). Results: Data from the ImPACT online version yielded 91.4% sensitivity and 69.1% specificity. For asymptomatic athletes suspected of hiding their concussion, data from ImPACT yielded 94.6% sensitivity and 97.3% specificity. Conclusion: The online version of the ImPACT tool is a valid measure of neurocognitive performance at the acute stages of concussion, with high levels of sensitivity and specificity, even when athletes appear to be denying postconcussion symptoms. © 2012 The Author(s). Source

Regis R.G.,Saint Josephs University
Journal of Computational Science

This paper develops the OPUS (Optimization by Particle swarm Using Surrogates) framework for expensive black-box optimization. In each iteration, OPUS considers multiple trial positions for each particle in the swarm and uses a surrogate model to identify the most promising trial position. Moreover, the current overall best position is refined by finding the global minimum of the surrogate in the neighborhood of that position. OPUS is implemented using an RBF surrogate and the resulting OPUS-RBF algorithm is applied to a 36-D groundwater bioremediation problem, a 14-D watershed calibration problem, and ten mostly 30-D test problems. OPUS-RBF is compared with a standard PSO, CMA-ES, two other surrogate-assisted PSO algorithms, and an RBF-assisted evolution strategy. The numerical results suggest that OPUS-RBF is promising for expensive black-box optimization. © 2013 Elsevier B.V. Source

This paper presents a new algorithm for derivative-free optimization of expensive black-box objective functions subject to expensive black-box inequality constraints. The proposed algorithm, called ConstrLMSRBF, uses radial basis function (RBF) surrogate models and is an extension of the Local Metric Stochastic RBF (LMSRBF) algorithm by Regis and Shoemaker (2007a) [1] that can handle black-box inequality constraints. Previous algorithms for the optimization of expensive functions using surrogate models have mostly dealt with bound constrained problems where only the objective function is expensive, and so, the surrogate models are used to approximate the objective function only. In contrast, ConstrLMSRBF builds RBF surrogate models for the objective function and also for all the constraint functions in each iteration, and uses these RBF models to guide the selection of the next point where the objective and constraint functions will be evaluated. Computational results indicate that ConstrLMSRBF is better than alternative methods on 9 out of 14 test problems and on the MOPTA08 problem from the automotive industry (Jones, 2008 [2]). The MOPTA08 problem has 124 decision variables and 68 inequality constraints and is considered a large-scale problem in the area of expensive black-box optimization. The alternative methods include a Mesh Adaptive Direct Search (MADS) algorithm (Abramson and Audet, 2006 [3]; Audet and Dennis, 2006 [4]) that uses a kriging-based surrogate model, the Multistart LMSRBF algorithm by Regis and Shoemaker (2007a) [1] modified to handle black-box constraints via a penalty approach, a genetic algorithm, a pattern search algorithm, a sequential quadratic programming algorithm, and COBYLA (Powell, 1994 [5]), which is a derivative-free trust-region algorithm. Based on the results of this study, the results in Jones (2008) [2] and other approaches presented at the ISMP 2009 conference, ConstrLMSRBF appears to be among the best, if not the best, known algorithm for the MOPTA08 problem in the sense of providing the most improvement from an initial feasible solution within a very limited number of objective and constraint function evaluations. © 2010 Elsevier Ltd. Source

This article develops two new algorithms for constrained expensive black-box optimization that use radial basis function surrogates for the objective and constraint functions. These algorithms are called COBRA and Extended ConstrLMSRBF and, unlike previous surrogate-based approaches, they can be used for high-dimensional problems where all initial points are infeasible. They both follow a two-phase approach where the first phase finds a feasible point while the second phase improves this feasible point. COBRA and Extended ConstrLMSRBF are compared with alternative methods on 20 test problems and on the MOPTA08 benchmark automotive problem (D.R. Jones, Presented at MOPTA 2008), which has 124 decision variables and 68 black-box inequality constraints. The alternatives include a sequential penalty derivative-free algorithm, a direct search method with kriging surrogates, and two multistart methods. Numerical results show that COBRA algorithms are competitive with Extended ConstrLMSRBF and they generally outperform the alternatives on the MOPTA08 problem and most of the test problems. © 2013 Taylor & Francis. Source

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