A Behavioral Approach to Building Cognitive Foundations for Effective Thought and Action

This research documents the process and results of an approach to teaching university undergraduates intentional self-development skills designed to promote self-generated goals, routines, and lifestyle choices. These skills may provide effective behavioral foundations for developing metacognitive awareness, intentionality, and individual well-being. The results of six original behavioral interventions, implemented in two James Madison University courses, provide initial support for the effectiveness of these instructional methodologies.     

Retrieval constraints and word frequency distributions a log-logistic model for IR

We first present in this paper an analytical view of heuristic retrieval constraints which yields simple tests to determine whether a retrieval function satisfies the constraints or not. We then review empirical findings on word frequency distributions and the central role played by burstiness in this context. This leads us to propose a formal definition of burstiness which can be used to characterize probability distributions with respect to this phenomenon. We then introduce the family of information-based IR models which naturally captures heuristic retrieval constraints when the underlying probability distribution is bursty and propose a new IR model within this family, based on the log-logistic distribution. The experiments we conduct on several collections illustrate the good behavior of the log-logistic IR model: It significantly outperforms the Jelinek-Mercer and Dirichlet prior language models on most collections we have used, with both short and long queries and for both the MAP and the precision at 10 documents. It also compares favorably to BM25 and has similar performance to classical DFR models such as InL2 and PL2.     

Body composition of female road and track endurance cyclists: Normative values and typical changes

The aims of this study were to describe normative values and seasonal variation of body composition in female cyclists comparing female road and track endurance cyclists, and to validate the use of anthropometry to monitor lean mass changes. Anthropometric profiles (seven site skinfolds) were measured over 16 years from 126 female cyclists. Lean mass index (LMI) was calculated as body weight?×?skinfolds^?x. The exponent (x) was calculated as the slope of the natural logarithm of body weight and skinfolds. Percentage changes in LMI were compared to lean mass changes measured using dual-energy X-ray absorptiometry (DXA) in a subset of 25 road cyclists. Compared to sub-elite and elite cyclists, world class cyclists were (mean [95% CI]) 1.18?kg [0.46, 1.90] and 0.60?kg [0.05, 1.15] lighter and had skinfolds that were 7.4?mm [3.8, 11.0] and 4.6?mm [1.8, 7.4] lower, respectively. Body weight (0.41?kg [0.04, 0.77]) and skinfolds (4.0?mm [2.1, 6.0]) were higher in the off-season compared to the early-season. World class female road cyclists had lower body weight (6.04?kg [2.73, 9.35]) and skinfolds (11.5?mm [1.1, 21.9]) than track endurance cyclists. LMI (mean exponent 0.15 [0.13, 0.18]) explained 87% of the variance in DXA lean mass. In conclusion, higher performing female cyclists were lighter and leaner than their less successful peers, road cyclists were lighter and leaner than track endurance cyclists, and weight and skinfolds were lowest early in the season. LMI appears to be a reasonably valid tool for monitoring lean mass changes.