School Influences on Adolescent Depression: A 6-Year Longitudinal Study Amongst Catholic, Government and Independent Schools, in Victoria, Australia.

This study examined associations between school sector (Government, Catholic or Independent) and depressive symptomology over the secondary school years. Six waves of data collected annually from a representative Australian sample were examined. Multilevel piecewise linear and logistic regression controlling for a variety of demographic variables and protective factors was undertaken. In all sectors, depressive symptomology decreased between 10 and 13 years of age, but significantly increased for girls at age 13. Adolescents in Catholic schools reported significantly fewer symptoms of depression compared to those in Government and Independent schools. Adolescents in Catholic schools were less likely to report clinical levels of depressed mood compared to adolescents in Government schools.

Sparse modeling using orthogonal forward regression with PRESS statistic and regularization.

The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares (PRESS) statistic, without resorting to any other validation data set for model evaluation in the model construction process. Computational efficiency is ensured using an orthogonal forward regression, but the algorithm incrementally minimizes the PRESS statistic instead of the usual sum of the squared training errors. A local regularization method can naturally be incorporated into the model selection procedure to further enforce model sparsity. The proposed algorithm is fully automatic, and the user is not required to specify any criterion to terminate the model construction procedure. Comparisons with some of the existing state-of-art modeling methods are given, and several examples are included to demonstrate the ability of the proposed algorithm to effectively construct sparse models that generalize well.

Virtual reality and interactive 3D as effective tools for medical training.

CAVE-like displays allow a user to walk in to a virtual environment, and use natural movement to change the viewpoint of virtual objects which they can manipulate with a hand held device. This maps well to many surgical procedures offering strong potential for training and planning. These devices may be networked together allowing geographically remote users to share the interactive experience. This maps to the strong need for distance training and planning of surgeons. Our paper shows how the properties of a CAVE-Like facility can be maximised in order to provide an ideal environment for medical training. The implementation of a large 3D-eye is described. The resulting application is that of an eye that can be manipulated and examined by trainee medics under the guidance of a medical expert. The progression and effects of different ailments can be illustrated and corrective procedures, demonstrated.