Boiler room scams destroy lives yet police blame victims

The Queensland Organised Crime Commission of Inquiry recently handed down its findings examining how organised crime has been policed in recent years. While media attention has been focused on the implications for child sexual exploitation and paedophilia, the report also made some substantial findings related to financial crimes such as investment fraud (commonly known as boiler rooms scams). Quite disturbingly, the report notes a strong victim blaming mentality that police expressed towards individuals who invested in fraudulent companies and who subsequently lost money in these boiler room scams. The attitude of the police towards boiler room victims was largely one of apathy towards the likelihood of any investigation, and of blame towards victims for not doing what was perceived to be “due diligence”. This finding illustrates several myths which are argued to exist around investment fraud victims, particularly around the concept of “due diligence”. It also feeds into the idea that victims are greedy/naïve and financially illiterate/not investment savvy. These are both problematic and largely inaccurate. Drawing on examples from my own research with fraud victims, the article will illustrate the complexity and sophistication of many boiler room schemes and demonstrate the difficulties in identifying fraudulent investment opportunities.

Efficient regression analysis with ranked-set sampling

This article is motivated by a lung cancer study where a regression model is involved and the response variable is too expensive to measure but the predictor variable can be measured easily with relatively negligible cost. This situation occurs quite often in medical studies, quantitative genetics, and ecological and environmental studies. In this article, by using the idea of ranked-set sampling (RSS), we develop sampling strategies that can reduce cost and increase efficiency of the regression analysis for the above-mentioned situation. The developed method is applied retrospectively to a lung cancer study. In the lung cancer study, the interest is to investigate the association between smoking status and three biomarkers: polyphenol DNA adducts, micronuclei, and sister chromatic exchanges. Optimal sampling schemes with different optimality criteria such as A-, D-, and integrated mean square error (IMSE)-optimality are considered in the application. With set size 10 in RSS, the improvement of the optimal schemes over simple random sampling (SRS) is great. For instance, by using the optimal scheme with IMSE-optimality, the IMSEs of the estimated regression functions for the three biomarkers are reduced to about half of those incurred by using SRS.

Biorefineries – creating economic opportunities from biofuels and bio-products

Biorefineries, producing fuels, green chemicals and bio-products, offer great potential for improving the profitability and sustainability of tropical agricultural industries. Biomass from tropical crops like sugarcane, sweet sorghum, palm and cassava offer great potential because of the high biomass growth potential under favourable climatic conditions. Biorefineries aim to convert waste residues through biochemical and enzymatic processes to low cost fermentable sugars which are a platform for value-adding. Through subsequent fermentation utilising microbial biotechnologies or chemical synthesis, the sugars can be converted to fuels including ethanol and butanol, oils, organic acids such as lactic and levulinic acid and polymer precursors. Other biorefinery products can include food and animal feeds, plastics, fibre products and resins. Pretreatment technologies are a key to unlocking this potential and new technologies are emerging. This paper will address the opportunities available for tropical biorefineries to contribute to the future profitability of tropical agricultural industries. The importance of pretreatment technologies will be discussed.

The economic value of new tropical biorefinery industries in Australia

Biorefineries, co-producing fuels, green chemicals and bio-products, offer great potential for enhancing agricultural value, and developing new industries in the bioeconomy. Biomass biorefineries aim to convert agricultural crops and wastes through biochemical and enzymatic processes to low cost fermentable sugars and other products which are platforms for value-adding. Through subsequent fermentation or chemical synthesis, the bio-based platforms can be converted to fuels including ethanol and butanol, oils, organic acids such as lactic and levulinic acid and polymer precursors. Other biorefinery products can include food and animal feeds, plastics, fibre products and resins. In 2014, QUT commissioned a study from Deloitte Access Economics and Correlli Consulting to assess the potential future economic value of tropical biorefineries to Queensland. This paper will report on the outcomes of this study and address the opportunities available for tropical biorefineries to contribute to the future profitability and sustainability of tropical agricultural industries in Queensland and more broadly across northern Australia.

Quality of life after early enteral feeding versus standard care for proven or suspected advanced epithelial ovarian cancer: Results from a randomised trial

Background Malnutrition is common in patients with advanced epithelial ovarian cancer (EOC), and is associated with impaired quality of life (QoL), longer hospital stay and higher risk of treatment-related adverse events. This phase III multi-centre randomised clinical trial tested early enteral feeding versus standard care on postoperative QoL. Methods From 2009 to 2013, 109 patients requiring surgery for suspected advanced EOC, moderately to severely malnourished were enrolled at five sites across Queensland and randomised to intervention (n = 53) or control (n = 56) groups. Intervention involved intraoperative nasojejunal tube placement and enteral feeding until adequate oral intake could be maintained. Despite being randomised to intervention, 20 patients did not receive feeds (13 did not receive the feeding tube; 7 had it removed early). Control involved postoperative diet as tolerated. QoL was measured at baseline, 6 weeks postoperatively and 30 days after the third cycle of chemotherapy. The primary outcome measure was the difference in QoL between the intervention and the control group. Secondary endpoints included treatment-related adverse event occurrence, length of stay, postoperative services use, and nutritional status. Results Baseline characteristics were comparable between treatment groups. No significant difference in QoL was found between the groups at any time point. There was a trend towards better nutritional status in patients who received the intervention but the differences did not reach statistical significance except for the intention-to-treat analysis at 7 days postoperatively (11.8 intervention vs. 13.8 control, p 0.04). Conclusion Early enteral feeding did not significantly improve patients' QoL compared to standard of care but may improve nutritional status.

Detecting rare events using Kullback-Leibler divergence: A weakly supervised approach

Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.

Development of salinity tolerance in rice by constitutive-overexpression of genes involved in the regulation of programmed cell death

Environmental factors contribute to over 70% of crop yield losses worldwide. Of these drought and salinity are the most significant causes of crop yield reduction. Rice is an important staple crop that feeds more than half of the world’s population. However among the agronomically important cereals rice is the most sensitive to salinity. In the present study we show that exogenous expression of anti-apoptotic genes from diverse origins, AtBAG4 (Arabidopsis), Hsp70 (Citrus tristeza virus) and p35 (Baculovirus), significantly improves salinity tolerance in rice at the whole plant level. Physiological, biochemical and agronomical analyses of transgenic rice expressing each of the anti-apoptotic genes subjected to salinity treatment demonstrated traits associated with tolerant varieties including, improved photosynthesis, membrane integrity, ion and ROS maintenance systems, growth rate, and yield components. Moreover, FTIR analysis showed that the chemical composition of salinity-treated transgenic plants is reminiscent of non-treated, unstressed controls. In contrast, wild type and vector control plants displayed hallmark features of stress, including pectin degradation upon subjection to salinity treatment. Interestingly, despite their diverse origins, transgenic plants expressing the anti-apoptotic genes assessed in this study displayed similar physiological and biochemical characteristics during salinity treatment thus providing further evidence that cell death pathways are conserved across broad evolutionary kingdoms. Our results reveal that anti-apoptotic genes facilitate maintenance of metabolic activity at the whole plant level to create favorable conditions for cellular survival. It is these conditions that are crucial and conducive to the plants ability to tolerate/adapt to extreme environments.