Gender differences in first-year College students’ academic expectations

Based on a multidimensional definition of academic expectations (AEs), the authors examine students’ AE component scores across countries and genders. Two samples (343 Portuguese and 358 Spanish students) completed the Academic Perceptions Questionnaire (APQ) six months after enrolling in their universities. Factorial invariance was ensured across countries and genders, allowing us to study AEs using the APQ for both genders and in both countries. No significant differences in factor means were found between countries, indicating that AEs are not an obstacle to student mobility. Gender differences were found in some AE factor means, Training for employment, Personal and social development, Student mobility, Political engagement and citizenship, and Social pressure, with males exhibiting higher scores. Because these differences are not supported by most literature in this domain, further studies are needed to clarify the causes of women’s lower expectations and, therefore, risk of adaptation difficulties.

Modelling the relationship between biomechanics and performance of young sprinting swimmers

The aim of this study was to compute a swimming performance confirmatory model based on biomechanical parameters. The sample included 100 young swimmers (overall: 12.3 ± 0.74 years; 49 boys: 12.5 ± 0.76 years; 51 girls: 12.2 ± 0.71 years; both genders in Tanner stages 1–2 by self-report) participating on a regular basis in regional and national-level events. The 100 m freestyle event was chosen as the performance indicator. Anthropometric (arm span), strength (throwing velocity), power output (power to overcome drag), kinematic (swimming velocity) and efficiency (propelling efficiency) parameters were measured and included in the model. The path-flow analysis procedure was used to design and compute the model. The anthropometric parameter (arm span) was excluded in the final model, increasing its goodness-of-fit. The final model included the throw velocity, power output, swimming velocity and propelling efficiency. All links were significant between the parameters included, but the throw velocity–power output. The final model was explained by 69% presenting a reasonable adjustment (model’s goodness-of-fit; x2/df = 3.89). This model shows that strength and power output parameters do play a mediator and meaningful role in the young swimmers’ performance.

On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.