Adaptive, eclectic and democratic : an alternative year 2020 vision of the place of psychiatry

It was the end of the academic year in 2020. On the third floor of the Southern Health University's administrative building, the five Vice-Chancellors of the Health Universities were gathering. Outside it was raining, but the patter of drops on the window only served to enhance the coziness of the meeting room. This annual event would take three days. The Vice-Chancellors enjoyed this meeting. They seldom saw each other during the busy academic year and under Professor Hope Brightview's 6 years of chairmanship they had been able to work well together to formulate a rational and profitable distribution of teaching, research and consultation services.

Perceptions of wellness to monitor adaptive responses to training and competition in elite Australian football

Perceptions of wellness are often used by athletes and coaches to assess adaptive responses to training. The purpose of this research was to describe how players were coping with the demands of elite level Australian football over a competitive season using subjective ratings of physical and psychological wellness and to assess the ecological validity of such a monitoring approach. Twenty-seven players completed ratings for 9 items (fatigue, general muscle, hamstring, quadriceps, pain/stiffness, power, sleep quality, stress, well-being). Players subjectively rated each item as they arrived at the training or competition venue on a 1–5 visual analog scale, with 1 representing the positive end of the continuum. A total of 2,583 questionnaires were analyzed from completions on 183 days throughout the season (92 ± 24 per player, 103 ± 20 per week; mean ± SD). Descriptive statistics and multilevel modelling were used to understand how player ratings of wellness varied over the season and during the week leading into game day and whether selected player characteristics moderated these relationships. Results indicated that subjective ratings of physical and psychological wellness were sensitive to weekly training manipulations (i.e., improve steadily throughout the week to a game day low, p < 0.001), to periods of unloading during the season (i.e., a week of no competition, p < 0.05) and to individual player characteristics (e.g., muscle strain after a game was poorer in players with high maximum speed, p < 0.01). It is concluded that self-reported player ratings of wellness provide a useful tool for coaches and practitioners to monitor player responses to the rigorous demands of training, competition, and life as a professional athlete.

Uplink power control via adaptive Hidden-Markov-Model-Based pathloss estimation

Dynamic variations in channel behavior is considered in transmission power control design for cellular radio systems. It is well known that power control increases system capacity, improves Quality of Service (QoS), and reduces multiuser interference. In this paper, an adaptive power control design based on the identification of the underlying pathloss dynamics of the fading channel is presented. Formulating power control decisions based on the measured received power levels allows modeling the fading channel pathloss dynamics in terms of a Hidden Markov Model (HMM). Applying the online HMM identification algorithm enables accurate estimation of the real pathloss ensuring efficient performance of the suggested power control scheme.

AdaM : adaptive-maximum imputation for neighborhood-based collaborative filtering

In the context of collaborative filtering, the well known data sparsity issue makes two like-minded users have little similarity, and consequently renders the k nearest neighbour rule inapplicable. In this paper, we address the data sparsity problem in the neighbourhood-based CF methods by proposing an Adaptive-Maximum imputation method (AdaM). The basic idea is to identify an imputation area that can maximize the imputation benefit for recommendation purposes, while minimizing the imputation error brought in. To achieve the maximum imputation benefit, the imputation area is determined from both the user and the item perspectives; to minimize the imputation error, there is at least one real rating preserved for each item in the identified imputation area. A theoretical analysis is provided to prove that the proposed imputation method outperforms the conventional neighbourhood-based CF methods through more accurate neighbour identification. Experiment results on benchmark datasets show that the proposed method significantly outperforms the other related state-of-the-art imputation-based methods in terms of accuracy.