Managing the Brisbane River and Moreton Bay: an integrated research/management program to reduce impacts on an Australian estuary

The Brisbane River and Moreton Bay Study, an interdisciplinary study of Moreton Bay and its major tributaries, was initiated to address water quality issues which link sewage and diffuse loading with environmental degradation. Runoff and deposition of fine-grained sediments into Moreton Bay, followed by resuspension, have been linked with increased turbidity and significant loss of seagrass habitat. Sewage-derived nutrient enrichment, particularly nitrogen (N), has been linked to algal blooms by sewage plume maps. Blooms of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay have resulted in significant impacts on human health (e.g., contact dermatitis) and ecological health (e.g., seagrass loss), and the availability of dissolved iron from acid sulfate soil runoff has been hypothesised. The impacts of catchment activities resulting in runoff of sediments, nutrients and dissolved iron on the health of the Moreton Bay waterways are addressed. The Study, established by 6 local councils in association with two state departments in 1994, forms a regional component of a national and state program to achieve ecologically sustainable use of the waterways by protecting and enhancing their health, while maintaining economic and social development. The Study framework illustrates a unique integrated approach to water quality management whereby scientific research, community participation and the strategy development were done in parallel with each other. This collaborative effort resulted in a water quality management strategy which focuses on the integration of socioeconomic and ecological values of the waterways. This work has led to significant cost savings in infrastructure by providing a clear focus on initiatives towards achieving healthy waterways. The Study's Stage 2 initiatives form the basis for this paper.

Theory and applications of fuzzy Volterra integral equations

Formulations of fuzzy integral equations in terms of the Aumann integral do not reflect the behavior of corresponding crisp models. Consequently, they are ill-adapted to describe physical phenomena, even when vagueness and uncertainty are present. A similar situation for fuzzy ODEs has been obviated by interpretation in terms of families of differential inclusions. The paper extends this formalism to fuzzy integral equations and shows that the resulting solution sets and attainability sets are fuzzy and far better descriptions of uncertain models involving integral equations. The investigation is restricted to Volterra type equations with mildly restrictive conditions, but the methods are capable of extensive generalization to other types and more general assumptions. The results are illustrated by integral equations relating to control models with fuzzy uncertainties.

CDT, GGT, and AST as markers of alcohol use: The WHO/ISBRA Collaborative Project

Background: Estimates of the performance of carbohydrate deficient transferrin (CDT) and gamma glutamyltransferase (GGT) as markers of alcohol consumption have varied widely. Studies have differed in design and subject characteristics. The WHO/ISBRA Collaborative Study allows assessment and comparison of CDT, GGT, and aspartate aminotransferase (AST) as markers of drinking in a large, well-characterized, multicenter sample. Methods: A total of 1863 subjects were recruited from five countries (Australia, Brazil, Canada, Finland, and Japan). Recruitment was stratified by alcohol use, age, and sex. Demographic characteristics, alcohol consumption, and presence of ICD-10 dependence were recorded using an interview schedule based on the AUDADIS, CDT was assayed using CDTect(TM) and GGT and AST by standard methods. Statistical techniques included receiver operating characteristic (ROC) analysis. Multiple regression was used to measure the impact of factors other than alcohol on test performance. Results: CDT and GGT had comparable performance on ROC analysis, with AST performing slightly less well. CDT was a slightly but significantly better marker of high-risk consumption in men. All were more effective for detection of high-risk rather than intermediate-risk drinking. CDT and GGT levels were influenced by body mass index, sex, age, and smoking status. Conclusions: CDT was little better than GGT in detecting high- or intermediate-risk alcohol consumption in this large, multicenter, predominantly community-based sample. As the two tests are relatively independent of each other, their combination is likely to provide better performance than either test alone, Test interpretation should take account sex, age. and body mass index.

Alcohol, tobacco and breast cancer - collaborative reanalysis of individual data from 53 epidemiological studies, including 58 515 women with breast cancer and 95 067 women without the disease

Alcohol and tobacco consumption are closely correlated and published results on their association with breast cancer have not always allowed adequately for confounding between these exposures. Over 80% of the relevant information worldwide on alcohol and tobacco consumption and breast cancer were collated, checked and analysed centrally. Analyses included 58515 women with invasive breast cancer and 95067 controls from 53 studies. Relative risks of breast cancer were estimated, after stratifying by study, age, parity and, where appropriate, women's age when their first child was born and consumption of alcohol and tobacco. The average consumption of alcohol reported by controls from developed countries was 6.0 g per day, i.e. about half a unit/drink of alcohol per day, and was greater in ever-smokers than never-smokers, (8.4 g per day and 5.0 g per day, respectively). Compared with women who reported drinking no alcohol, the relative risk of breast cancer was 1.32 (1.19 - 1.45, P < 0.00001) for an intake of 35 - 44 g per day alcohol, and 1.46 (1.33 - 1.61, P < 0.00001) for greater than or equal to 45 g per day alcohol. The relative risk of breast cancer increased by 7.1% (95% CI 5.5-8.7%; P

Evaluation of collaborative strategies for ecotourism and recreational activities in natural parks of Rio de Janeiro

In the city of Rio de Janeiro, the management agencies of environmental conservation units of the park type have been attempting to meet five primary objectives set by the National System for Conservation Units (NSCU), using participatory management guidelines for these units. Two of these objectives relate to the development of recreation activities that involve contact with nature and ecological tourism. This article presents the analyses and conclusions regarding the implementation of collaborative strategies with businesses to achieve such objectives; it is part of a series of research studies having a broader scope. Case studies were conducted in eight parks by means of dozens of interviews with managers and other interested social actors, as well as by documentary research and direct observation. The results suggest that the ecotourism objective is still far from being reached, and that the collaborative strategies used are not sufficient to compensate for the organizational, material and human limitations that encumber these agencies. It was also concluded for the sample that there lacks a strategic vision on the part of the three branches of government involved in the management of these parks in the sense of viewing ecotourism in the city's conservation units as a powerful means to foster local sustainable development.

Elements of a methodology to assess the alignment of core-values in collaborative networks

Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed.

KDD, SEMMA and CRISP-DM: a parallel overview

In the last years there has been a huge growth and consolidation of the Data Mining field. Some efforts are being done that seek the establishment of standards in the area. Included on these efforts there can be enumerated SEMMA and CRISP-DM. Both grow as industrial standards and define a set of sequential steps that pretends to guide the implementation of data mining applications. The question of the existence of substantial differences between them and the traditional KDD process arose. In this paper, is pretended to establish a parallel between these and the KDD process as well as an understanding of the similarities between them.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

Clustering and selecting categorical features

In data clustering, the problem of selecting the subset of most relevant features from the data has been an active research topic. Feature selection for clustering is a challenging task due to the absence of class labels for guiding the search for relevant features. Most methods proposed for this goal are focused on numerical data. In this work, we propose an approach for clustering and selecting categorical features simultaneously. We assume that the data originate from a finite mixture of multinomial distributions and implement an integrated expectation-maximization (EM) algorithm that estimates all the parameters of the model and selects the subset of relevant features simultaneously. The results obtained on synthetic data illustrate the performance of the proposed approach. An application to real data, referred to official statistics, shows its usefulness.

An integrated recycling approach for GFRP pultrusion wastes: recycling and reuse assessment into new composite materials using Fuzzy Boolean Nets

In this study, efforts were made in order to put forward an integrated recycling approach for the thermoset based glass fibre reinforced polymer (GPRP) rejects derived from the pultrusion manufacturing industry. Both the recycling process and the development of a new cost-effective end-use application for the recyclates were considered. For this purpose, i) among the several available recycling techniques for thermoset based composite materials, the most suitable one for the envisaged application was selected (mechanical recycling); and ii) an experimental work was carried out in order to assess the added-value of the obtained recyclates as aggregates and reinforcement replacements into concrete-polymer composite materials. Potential recycling solution was assessed by mechanical behaviour of resultant GFRP waste modified concrete-polymer composites with regard to unmodified materials. In the mix design process of the new GFRP waste based composite material, the recyclate content and size grade, and the effect of the incorporation of an adhesion promoter were considered as material factors and systematically tested between reasonable ranges. The optimization process of the modified formulations was supported by the Fuzzy Boolean Nets methodology, which allowed finding the best balance between material parameters that maximizes both flexural and compressive strengths of final composite. Comparing to related end-use applications of GFRP wastes in cementitious based concrete materials, the proposed solution overcome some of the problems found, namely the possible incompatibilities arisen from alkalis-silica reaction and the decrease in the mechanical properties due to high water-cement ratio required to achieve the desirable workability. Obtained results were very promising towards a global cost-effective waste management solution for GFRP industrial wastes and end-of-life products that will lead to a more sustainable composite materials industry.

A framework for the development of parallel and distributed real-time embedded systems

Embedded real-time applications increasingly present high computation requirements, which need to be completed within specific deadlines, but that present highly variable patterns, depending on the set of data available in a determined instant. The current trend to provide parallel processing in the embedded domain allows providing higher processing power; however, it does not address the variability in the processing pattern. Dimensioning each device for its worst-case scenario implies lower average utilization, and increased available, but unusable, processing in the overall system. A solution for this problem is to extend the parallel execution of the applications, allowing networked nodes to distribute the workload, on peak situations, to neighbour nodes. In this context, this report proposes a framework to develop parallel and distributed real-time embedded applications, transparently using OpenMP and Message Passing Interface (MPI), within a programming model based on OpenMP. The technical report also devises an integrated timing model, which enables the structured reasoning on the timing behaviour of these hybrid architectures.