Temporal PDMs for gait classification

Gait classification is a developing research area, particularly with regards to biometrics. It aims to use the distinctive spatial and temporal characteristics of human motion to classify differing activities. As a biometric, this extends to recognising different people by the heterogeneous aspects of their gait. This research aims to use a modified deformable model, the temporal PDM, to distinguish the movements of a walking and miming person. The movement of 2D points on the moving form is used to provide input into the model and classify the type of gait present.

Adaptive model for foreground extraction in adverse lighting conditions

Background elimination models are widely used in motion tracking systems. Our aim is to develop a system that performs reliably under adverse lighting conditions. In particular, this includes indoor scenes lit partly or entirely by diffuse natural light. We present a modified "median value" model in which the detection threshold adapts to global changes in illumination. The responses of several models are compared, demonstrating the effectiveness of the new model.

Identification of surface heterogeneity effects in cyclic voltammograms derived from analysis of an individually addressable gold array electrode

Voltammetric behavior at gold electrodes in aqueous media is known to be strongly dependent on electrode polishing and history. In this study, an electrode array consisting of 100 nominally identical and individually addressable gold disks electrodes, each with a radius of 127 µm, has been fabricated. The ability to analyze both individual electrode and total array performance enables microscopic aspects of the overall voltammetric response arising from variable levels of inhomogeneity in each electrode to be identified. The array configuration was initially employed with the reversible and hence relatively surface insensitive [Ru(NH₃)₆]^3+/2+ reaction and then with the more highly surface sensitive quasi-reversible [Fe(CN)₆]^3−/4− process. In both these cases, the reactants and products are solution soluble and, at a scan rate of 50 mV s⁻¹, each electrode in the array is assumed to behave independently, since no evidence of overlapping of the diffusion layers was detected. As would be expected, the variability of the individual electrodesʼ responses was significantly larger than found for the summed electrode behavior. In the case of cytochrome c voltammetry at a 4,4′-dipyridyl disulfide modified electrode, a far greater dependence on electrode history and electrode heterogeneity was detected. In this case, voltammograms derived from individual electrodes in the gold array electrode exhibit shape variations ranging from peak to sigmoidal. However, again the total response was always found to be well-defined. This voltammetry is consistent with a microscopic model of heterogeneity where some parts of each chemically modified electrode surface are electroactive while other parts are less active. The findings are consistent with the common existence of electrode heterogeneity in cyclic voltammetric responses at gold electrodes, that are normally difficult to detect, but fundamentally important, as electrode nonuniformity can give rise to subtle forms of kinetic and other forms of dispersion.

Characterising nonuniform electrodeposition and electrodissolution using the novel wire beam electrode method

An electrochemically integrated multi-electrode system namely the wire beam electrode (WBE) has been applied as a new method of characterising nonuniform electrodeposition and electrodissolution, by measuring and identifying characteristic patterns in electrodeposition and electrodissolution current distribution maps. Various patterns of electrodeposition current distribution have been obtained from Watts nickel plating and bright acid copper plating baths with the effects of several affecting factors such as bath concentration, temperature, agitation and electrolyte flow. Typical patterns of electrodissolution current distribution have also been detected over a WBE surface under anodic dissolution. This work suggests that the WBE method can be used as a new tool for monitoring, characterising and optimising electrodeposition and electrodissolution processes in the laboratory, and can also be applied as an experimental method to verify the accuracy and completeness of mathematical models for electrodeposition and electrodissolution.

Reducing herbicide discharge to sensitive environments using membrane bioreactors

A hybrid MBR/UV/GAC treatment system was researched to remove Ametryn, which is a commonly used herbicide in Australian farmlands, from wastewater. The research revealed that the hybrid system could be successfully used for 100% removal of Ametryn. Two mathematical models were developed to predict the frequency of chemical cleaning of MBR-membrane and the mechanism of fouling of membrane.

Depression, diet and exercise

Unhealthy lifestyle behaviour is driving an increase in the burden of chronic non-communicable diseases worldwide.

Recent evidence suggests that poor diet and a lack of exercise contribute to the genesis and course of depression.

While studies examining dietary improvement as a treatment strategy in depression are lacking, epidemiological evidence clearly points to diet quality being of importance to the risk of depression.

Exercise has been shown to be an effective treatment strategy for depression, but this is not reflected in treatment guidelines, and increased physical activity is not routinely encouraged when managing depression in clinical practice.

Recommendations regarding dietary improvement, increases in physical activity and smoking cessation should be routinely given to patients with depression.

Specialised and detailed advice may not be necessary. Recommendations should focus on following national guidelines for healthy eating and physical activity.

A marginalised Markov Chain Monte Carlo approach for model based analysis of EEG data

The work presented in this paper focuses on fitting of a neural mass model to EEG data. Neurophysiology inspired mathematical models were developed for simulating brain's electrical activity imaged through Electroencephalography (EEG) more than three decades ago. At the present well informative models which even describe the functional integration of cortical regions also exists. However, a very limited amount of work is reported in literature on the subject of model fitting to actual EEG data. Here, we present a Bayesian approach for parameter estimation of the EEG model via a marginalized Markov Chain Monte Carlo (MCMC) approach.

Knowledge exchange in the Pacific : The TROPIC (translational research into obesity prevention policies for communities) project

Background
Policies targeting obesogenic environments and behaviours are critical to counter rising obesity rates and lifestyle-related non-communicable diseases (NCDs). Policies are likely to be most effective and enduring when they are based on the best available evidence. Evidence-informed policy making is especially challenging in countries with limited resources. The Pacific TROPIC (Translational Research for Obesity Prevention in Communities) project aims to implement and evaluate a tailored knowledge-brokering approach to evidence-informed policy making to address obesity in Fiji, a Pacific nation challenged by increasingly high rates of obesity and concomitant NCDs.
Methods
The TROPIC project draws on the concept of ‘knowledge exchange’ between policy developers (individuals; organisations) and researchers to deliver a knowledge broking programme that maps policy environments, conducts workshops on evidence-informed policy making, supports the development of evidence-informed policy briefs, and embeds evidence-informed policy making into organisational culture. Recruitment of government and nongovernment organisational representatives will be based on potential to: develop policies relevant to obesity, reach broad audiences, and commit to resourcing staff and building a culture that supports evidence-informed policy development. Workshops will increase awareness of both obesity and policy cycles, as well as develop participants’ skills in accessing, assessing and applying relevant evidence to policy briefs. The knowledge-broking team will then support participants to: 1) develop evidence-informed policy briefs that are both commensurate with national and organisational plans and also informed by evidence from the Pacific Obesity Prevention in Communities project and elsewhere; and 2) collaborate with participating organisations to embed evidence-informed policy making structures and processes. This knowledge broking initiative will be evaluated via data from semi-structured interviews, a validated self-assessment tool, process diaries and outputs.
Discussion
Public health interventions have rarely targeted evidence-informed policy making structures and processes to reduce obesity and NCDs. This study will empirically advance understanding of knowledge broking processes to extend evidence-informed policy making skills and develop a suite of national obesity-related policies that can potentially improve population health outcomes.

Monitoring the impacts of trade agreements on food environments

The liberalization of international trade and foreign direct investment through multilateral, regional and bilateral agreements has had profound implications for the structure and nature of food systems, and therefore, for the availability, nutritional quality, accessibility, price and promotion of foods in different locations. Public health attention has only relatively recently turned to the links between trade and investment agreements, diets and health, and there is currently no systematic monitoring of this area. This paper reviews the available evidence on the links between trade agreements, food environments and diets from an obesity and non-communicable disease (NCD) perspective. Based on the key issues identified through the review, the paper outlines an approach for monitoring the potential impact of trade agreements on food environments and obesity/NCD risks. The proposed monitoring approach encompasses a set of guiding principles, recommended procedures for data collection and analysis, and quantifiable 'minimal', 'expanded' and 'optimal' measurement indicators to be tailored to national priorities, capacity and resources. Formal risk assessment processes of existing and evolving trade and investment agreements, which focus on their impacts on food environments will help inform the development of healthy trade policy, strengthen domestic nutrition and health policy space and ultimately protect population nutrition.

Monitoring policy and actions on food environments: rationale and outline of the INFORMAS policy engagement and communication strategies

 The International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support (INFORMAS) proposes to collect performance indicators on food policies, actions and environments related to obesity and non-communicable diseases. This paper reviews existing communications strategies used for performance indicators and proposes the approach to be taken for INFORMAS. Twenty-seven scoring and rating tools were identified in various fields of public health including alcohol, tobacco, physical activity, infant feeding and food environments. These were compared based on the types of indicators used and how they were quantified, scoring methods, presentation and the communication and reporting strategies used. There are several implications of these analyses for INFORMAS: the ratings/benchmarking approach is very commonly used, presumably because it is an effective way to communicate progress and stimulate action, although this has not been formally evaluated; the tools used must be trustworthy, pragmatic and policy-relevant; multiple channels of communication will be needed; communications need to be tailored and targeted to decision-makers; data and methods should be freely accessible. The proposed communications strategy for INFORMAS has been built around these lessons to ensure that INFORMAS's outputs have the greatest chance of being used to improve food environments.

Monitoring food and non-alcoholic beverage promotions to children

Food and non-alcoholic beverage marketing is recognized as an important factor influencing food choices related to non-communicable diseases. The monitoring of populations' exposure to food and non-alcoholic beverage promotions, and the content of these promotions, is necessary to generate evidence to understand the extent of the problem, and to determine appropriate and effective policy responses. A review of studies measuring the nature and extent of exposure to food promotions was conducted to identify approaches to monitoring food promotions via dominant media platforms. A step-wise approach, comprising ‘minimal’, ‘expanded’ and ‘optimal’ monitoring activities, was designed. This approach can be used to assess the frequency and level of exposure of population groups (especially children) to food promotions, the persuasive power of techniques used in promotional communications (power of promotions) and the nutritional composition of promoted food products. Detailed procedures for data sampling, data collection and data analysis for a range of media types are presented, as well as quantifiable measurement indicators for assessing exposure to and power of food and non-alcoholic beverage promotions. The proposed framework supports the development of a consistent system for monitoring food and non-alcoholic beverage promotions for comparison between countries and over time.

International network for food and obesity/NCD research, monitoring and action support: benchmarking food environments towards healthier diets

Background and objectives: 

DDoS attack detection at local area networks using information theoretical metrics

DDoS attacks are one of the major threats to Internet services. Sophisticated hackers are mimicking the features of legitimate network events, such as flash crowds, to fly under the radar. This poses great challenges to detect DDoS attacks. In this paper, we propose an attack feature independent DDoS flooding attack detection method at local area networks. We employ flow entropy on local area network routers to supervise the network traffic and raise potential DDoS flooding attack alarms when the flow entropy drops significantly in a short period of time. Furthermore, information distance is employed to differentiate DDoS attacks from flash crowds. In general, the attack traffic of one DDoS flooding attack session is generated by many bots from one botnet, and all of these bots are executing the same attack program. As a result, the similarity among attack traffic should higher than that among flash crowds, which are generated by many random users. Mathematical models have been established for the proposed detection strategies. Analysis based on the models indicates that the proposed methods can raise the alarm for potential DDoS flooding attacks and can differentiate DDoS flooding attacks from flash crowds with conditions. The extensive experiments and simulations confirmed the effectiveness of our proposed detection strategies.