Tracks to advocacy: journalism studies, animal rights and Australian media law

This article considers the role of animal rights-based journalism and its connection to teaching media law and ethics to undergraduate students in an Australian university arts faculty. An anecdotal discussion of a reflective practice informing the teaching of an undergraduate course in a journalism major relates questions of ethics and law to broader considerations of the role of advocacy in and around journalism, and media practice. It is argued that animal rights-related stories have a role in training media professionals, and also in inspiring journalists to envision their own work as part of the democratic mechanisms of social and legal reform in Australia.

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management.

On the strength of dislocation interactions and their effect on latent hardening in pure Magnesium

This study is dedicated to the quantification of latent hardening and its effect on the plasticity of pure hexagonal magnesium. To this end, discrete dislocation dynamics simulations are used to (1) extract latent hardening parameters coupling different slip systems, and to (2) assess the validity of two existing constitutive models linking slip system strength to dislocation densities on all slip systems. As hexagonal materials deform via activation of different slip modes, each with different mobilities and lattice friction stress, the effects of the latter on latent hardening evolution are also investigated. It is found that the multi-slip formulation proposed by Franciosi and Zaoui gives accurate predictions when multiple interactions are involved while the formulation suggested by Lavrentev and Pokhil systematically overestimates the flow stress. Similar to FCC materials, it is also found that collinear interactions potentially contribute the most to latent hardening. Basal/pyramidal c + a interactions are found to be very strong, while interactions involving second-order pyramidal c + a primary dislocations appear to be the weakest ones. Finally, the latent hardening parameters, extracted from the discrete dislocation dynamics simulations, are used in polycrystal simulations and the impact of finely accounting for latent hardening on predictions of the macroscopic anisotropic response is shown to be of significant importance.