The use of wastewater analysis in forensic intelligence: drug consumption comparison between Sydney and different European cities

© 2019, © 2019 The Author(s). Published by Taylor & Francis Group on behalf of the Academy of Forensic Science. Wastewater analysis offers objective and complementary information to illicit drug agencies by monitoring patterns of illicit drug consumption. In this study, wastewater samples from three different wastewater treatment plants in Sydney, Australia were collected in March 2016. Ten targeted drugs were analysed and temporal and geographical analyses were performed to obtain a better understanding of the type and amount of illicit drugs consumed in Sydney in comparison with similar studies conducted around Australia and in Europe. Among the targeted drugs, methamphetamine was consumed the most, followed by cocaine and 3,4-methylenedioxymethamphetamine (MDMA). Weekly patterns were observed where a peak during the weekend was present. The geographical analysis showed differences between the regions targeted. This observation may be related to socio-demographic aspects. The comparison of our study to other data sources from Australia showed a high consumption of methamphetamine in Sydney and Western Australia. The comparison between Sydney and different European cities revealed a difference in consumption, which is in line with traditional market indicators. The information obtained through wastewater analysis provides complementary information regarding illicit drug consumption, the size, and the evolution of the illicit drug market. This, ultimately, will assist authorities in making informed decisions

Past, present and future mathematical models for buildings (i)

This is the first of two articles presenting a detailed review of the historical evolution of mathematical models applied in the development of building technology, including conventional buildings and intelligent buildings. After presenting the technical differences between conventional and intelligent buildings, this article reviews the existing mathematical models, the abstract levels of these models, and their links to the literature for intelligent buildings. The advantages and limitations of the applied mathematical models are identified and the models are classified in terms of their application range and goal. We then describe how the early mathematical models, mainly physical models applied to conventional buildings, have faced new challenges for the design and management of intelligent buildings and led to the use of models which offer more flexibility to better cope with various uncertainties. In contrast with the early modelling techniques, model approaches adopted in neural networks, expert systems, fuzzy logic and genetic models provide a promising method to accommodate these complications as intelligent buildings now need integrated technologies which involve solving complex, multi-objective and integrated decision problems

Past, present and future mathematical models for buildings (ii)

This article is the second part of a review of the historical evolution of mathematical models applied in the development of building technology. The first part described the current state of the art and contrasted various models with regard to the applications to conventional buildings and intelligent buildings. It concluded that mathematical techniques adopted in neural networks, expert systems, fuzzy logic and genetic models, that can be used to address model uncertainty, are well suited for modelling intelligent buildings. Despite the progress, the possible future development of intelligent buildings based on the current trends implies some potential limitations of these models. This paper attempts to uncover the fundamental limitations inherent in these models and provides some insights into future modelling directions, with special focus on the techniques of semiotics and chaos. Finally, by demonstrating an example of an intelligent building system with the mathematical models that have been developed for such a system, this review addresses the influences of mathematical models as a potential aid in developing intelligent buildings and perhaps even more advanced buildings for the future