An evaluation of sexual behaviour change using statistical and cognitive models. The AIDS Community Demonstration Projects

We evaluate sexual behaviour change among homosexual men enrolled in the cohorts in four AIDS Community Demonstration Projects. Behaviour change is classified following the stages of behaviour change model and described using a Markov model. Predictors of behaviour change are identified and evaluated using logit models for correlated data. Sexual behaviour change within the cohort could be modelled as a first-order Markov process. In addition, predictors suggested by models of health behaviour were correlated with particular patterns of sexual behaviour change. Our evaluation revealed a variety of patterns of sexual behaviour change in the cohorts and suggests multi-faceted interventions for promotion of behaviour change.     

Remote delivery of video services using mm-waves and optics

Advantages of a radio-based final drop for video delivery are outlined and spectral availability constraints that lead to the identification of the mm-wave region of the radio spectrum as the most appropriate for this application are discussed. The possibility of simultaneously supporting other broadband services, such as B-ISDN and traffic information systems (IVHS), enhance the attractiveness of a radio link. A large number of antenna units need to be served due to the limited propagation distances achievable at mm-wave frequencies, and therefore, a low-cost generation and delivery method has to be developed. In this paper, alternatives for the optical generation and distribution of mm-wave signals are reviewed and a new method is proposed that eases the bandwidth, and hence the cost, of the required optoelectronic components. An assessment of the relative merits of the methods is given     

Chirp compensation capability of a semiconductor laser amplifier

Performance improvement is reported resulting from incorporating a semiconductor laser amplifier (SLA) as a post-transmitter-amplifier in long-haul directly modulated optical systems operating in the 1.5 mu m region. This improvement arises from reduction of the chirp produced by the semiconductor laser as the signal passes through the SLA. Eye closure penalty improvements in excess of 5 dB are observed for an illustrative long-haul 4.8 Gbit/s system.<>     

A globally optimal estimator for the delta-lognormal modeling of fast reaching movements

Fast reaching movements are an important component of our daily interaction with the world and are consequently under investigation in many fields of science and engineering. Today, useful models are available for such studies, with tools for solving the inverse dynamics problem involved by these analyses. These tools generally provide a set of model parameters that allows an accurate and locally optimal reconstruction of the original movements. Although the solutions that they generate may provide a data curve fitting that is sufficient for some pattern recognition applications, the best possible solution is often necessary in others, particularly those involving neuroscience and biomedical signal processing. To generate these solutions, we present a globally optimal parameter extractor for the delta-lognormal modeling of reaching movements based on the branch-and-bound strategy. This algorithm is used to test the impact of white noise on the delta-lognormal modeling of reaching movements and to benchmark the state-of-the-art locally optimal algorithm. Our study shows that, even with globally optimal solutions, parameter averaging is important for obtaining reliable figures. It concludes that physiologically derived rules are necessary, in addition to global optimality, to achieve meaningful ?Λ extractions which can be used to investigate the control patterns of these movement primitives.     

Operation of a full-scale pumped flow biofilm reactor (PFBR) under two aeration regimes

A novel technology suitable for centralised and decentralised wastewater treatment has been developed, extensively tested at laboratory-scale, and trialled at a number of sites for populations ranging from 15 to 400 population equivalents (PE). The two-reactor-tank pumped flow biofilm reactor (PFBR) is characterised by: (i) its simple construction; (ii) its ease of operation and maintenance; (iii) low operating costs; (iv) low sludge production; and (v) comprising no moving parts or compressors, other than hydraulic pumps. By operating the system in a sequencing batch biofilm reactor (SBBR) mode, the following treatment can be achieved: 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD) and total suspended solids (TSS) reduction; nitrification and denitrification. During a 100-day full-scale plant study treating municipal wastewater and operating at 165 PE and 200 PE (Experiments 1 and 2, respectively), maximum average removals of 94% BOD5, 86% TSS and 80% ammonium-nitrogen (NH4-N) were achieved. During the latter part of Experiment 2, effluent concentrations averaged: 14 mg BOD5/l; 32 mg COD(filtered)/l; 14 mg TSS/l; 4.4 mg NH4-N/l; and 4.0 mg NO3-N/l (nitrate-nitrogen). The average energy consumption was 0.46-0.63 kWh/m3(treated) or 1.25-1.76 kWh/kg BOD5 removed. No maintenance was required during these experiments. The PFBR technology offers a low energy, minimal maintenance technology for the treatment of municipal wastewater.     

Making working memory work: a computational model of learning in the prefrontal cortex and basal ganglia

The prefrontal cortex has long been thought to subserve both working memory (the holding of information online for processing) and executive functions (deciding how to manipulate working memory and perform processing). Although many computational models of working memory have been developed, the mechanistic basis of executive function remains elusive, often amounting to a homunculus. This article presents an attempt to deconstruct this homunculus through powerful learning mechanisms that allow a computational model of the prefrontal cortex to control both itself and other brain areas in a strategic, task-appropriate manner. These learning mechanisms are based on subcortical structures in the midbrain, basal ganglia, and amygdala, which together form an actor-critic architecture. The critic system learns which prefrontal representations are task relevant and trains the actor, which in turn provides a dynamic gating mechanism for controlling working memory updating. Computationally, the learning mechanism is designed to simultaneously solve the temporal and structural credit assignment problems. The model's performance compares favorably with standard backpropagation-based temporal learning mechanisms on the challenging 1-2-AX working memory task and other benchmark working memory tasks.