A snapshot of the scope of obesity prevention practice in Australia.

Community-based initiatives (CBIs) that build capacity and promote healthy environments hold promise for preventing obesity and non-communicable disease, however their characteristics remain poorly understood and lessons are learned in isolation. This limits understanding of likely effectiveness of CBIs; the potential for actively supporting practice; and the translation of community-based knowledge into policy. Building on an initial survey (2010), an online survey was launched (2013) with the aim to describe the reach and characteristics of Australian CBIs and identify and evaluate elements known to contribute to best practice, effectiveness and sustainability. Responses from 104 CBIs were received in 2013. Geographic location generally reflected population density in Australia. Duration of CBIs was short-term (median 3 years; range 0.2-21.0 years), delivered mostly by health departments and local governments. Median annual funding had more than doubled since the 2010 survey, but average staffing had not increased. CBIs used at least two strategy types, with a preference for individual behaviour change strategies. Targeting children was less common (31%) compared with the 2010 survey (57%). Logic models and theory were used in planning, but there was low use of research evidence and existing prevention frameworks. Nearly, all CBIs had an evaluation component (12% of budget), but dissemination was limited. This survey provides information on the scope and varied quality of the current obesity prevention investment in Australia. To boost the quality and effectiveness of CBIs, further support systems may be required to ensure that organizations adopt upstream, evidence-informed approaches; and integrate CBIs into systems, policies and environments.

A review of the relationships between implication, negation and aggregation functions from the point of view of material implication

Implication and aggregation functions play important complementary roles in the field of fuzzy logic. Both have been intensively investigated since the early 1980s, revealing a tight relationship between them. However, the main results regarding this relationship, published by Fodor and Demirli DeBaets in the 1990s, have been poorly disseminated and are nowadays somewhat obsolete due to the subsequent advances in the field. The present paper deals with the translation of the classical logical equivalence p → q = ¬pvq, often called material implication, to the fuzzy framework, which establishes a one-to-one correspondence between implication functions and disjunctors (the class of aggregation functions that extend the Boolean disjunction to the unit interval). The construction of implication functions from disjunctors via negation functions, and vice versa, is reviewed, stressing the properties of disjunctors (respectively, implication functions) that ensure certain properties of implication functions (disjunctors).

Family networks and the Australian pastoral industry: a case study of the Port Phillip District and Victoria during the nineteenth century

This article highlights the important function of family and kinship networks in the pastoral industry of the Port Phillip District and Victoria, Australia, during the nineteenth century. Using the core case study of the extended Cameron family--or the Cameron “clan” from the Scottish Highlands--in the Western District of Victoria, it demonstrates how family networks assisted in the accumulation and consolidation of large pastoral properties and enterprises, and thus aided the agricultural entrepreneurialism of migrants who saw greater commercial opportunities throughout the Empire than at home.

State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems - a review

Given the considerable recent attention to distributed power generation and interest in sustainable energy, the integration of photovoltaic (PV) systems to grid-connected or isolated microgrids has become widespread. In order to maximize power output of PV system extensive research into control strategies for maximum power point tracking (MPPT) methods has been conducted. According to the robust, reliable, and fast performance of artificial intelligence-based MPPT methods, these approaches have been applied recently to various systems under different conditions. Given the diversity of recent advances to MPPT approaches a review focusing on the performance and reliability of these methods under diverse conditions is required. This paper reviews AI-based techniques proven to be effective and feasible to implement and very common in literature for MPPT, including their limitations and advantages. In order to support researchers in application of the reviewed techniques this study is not limited to reviewing the performance of recently adopted methods, rather discusses the background theory, application to MPPT systems, and important references relating to each method. It is envisioned that this review can be a valuable resource for researchers and engineers working with PV-based power systems to be able to access the basic theory behind each method, select the appropriate method according to project requirements, and implement MPPT systems to fulfill project objectives.