Age-Group differences in perception of competence, goal orientatiom attitudes, and practice of pshysical activity of girls who attend military schools

[EN]This study analysed the differences in self-perception, goal orientation and participation in physical activity (PA) in girls (N= 244) attending military schools. Girls had moderately higher levels of perceived competence, and there were no significant differences between age-groups. The figure for task-orientation was higher than ego-orientation. Girls expressed a positive attitude toward school and PE. Most girls did not practiced PA outside school, but 63,9% were involved in school sports. It seems that the military educational institutions are being successful in helping students to adopt physically active lifestyles. The development of perception of competence, task-orientation, and favourable attitudes seem to be important factors to enhance the levels of PA among students.

Reconstruction of spatiotemporal capture data by means of orthogonal functions: the case of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic

[EN] The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) on captures of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic has a number of limitations, such as gaps in the statistics for certain fleets and the level of spatiotemporal detail at which catches are reported. As a result, the quality of these data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatiotemporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction, applied here for the first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions decomposition performed with a Lanczos method. DINEOF was tested with different amounts of missing data, intentionally removing values from 3.4% to 95.2% of data loss, and then compared with the same data set with no missing data. These validation analyses show that DINEOF is a reliable methodological approach of data reconstruction for the purposes of fishery management advice, even when the amount of missing data is very high.