Diversity in the fitness industry : a cross-case comparison /

This cross-case study explored the extent to which two fitness facilities were accommodating diversity with respect to age, ethnicity, gender, social class, sex-role socialization, and persons with a disability among both members and staflf. The sites were purposely chosen in a large city and a smaller city in order to provide as representative an example as possible of health clubs within a small sample population. The interview participants were selected by a combination of stratified, typical case, and snowball sampling strategies. . , .. , The intent of the exploration was a two-fold examination of diversity issues within both the membership and the staff of the organization. Data were collected and analysis was done using a triangulation method involving personal interviews, observations, and facility documentation. The results ofthe study showed that the members and staff at each facility were rather homogeneous in ethnicity, age, social class, physical ability, and physical appearance. From a membership standpoint, the environment of the sites presented the impression of being affordable only to the middle- and upper-middle classes, unwelcoming to the older, less fit, or overweight participant, economically exclusive for youth, and nonaccommodating for people with a disability. With respect to staff, the findings indicated that the fitness facilities purported to be team-oriented in theory, but were hierarchical in practice, with the major decision making being made by the male executives. The paper concludes with the recommendation that students must be given a practical toolkit for dealing with these issues in their postsecondary courses.

Variational Monte Carlo estimation of the dissociation energy of CuH using correlated sampling

A new approach to treating large Z systems by quantum Monte Carlo has been developed. It naturally leads to notion of the 'valence energy'. Possibilities of the new approach has been explored by optimizing the wave function for CuH and Cu and computing dissociation energy and dipole moment of CuH using variational Monte Carlo. The dissociation energy obtained is about 40% smaller than the experimental value; the method is comparable with SCF and simple pseudopotential calculations. The dipole moment differs from the best theoretical estimate by about 50% what is again comparable with other methods (Complete Active Space SCF and pseudopotential methods).

Bio-inspired optimization & sampling technique for side-chain packing in MCCE

The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.

Cognitive Behavior Therapy for Obsessive-Compulsive Behavior in Children with Autism Spectrum Disorder: A Comparison of Hierarchical Linear Modelling and Visual Analysis

Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.