Can, and should, behavioural neuroscience influence public policy?

Recent years have seen enormous demand amongst policy makers for new insights from the behavioural sciences, especially neuroscience. This demand is matched by an increasing willingness on behalf of behavioural scientists to translate the policy implications of their work. But can neuroscience really help shape the governance of a nation? Or does this represent growing misuse of neuroscience to attach scientific authority to policy, plus a clutch of neuroscientists trying to overstate their findings for a taste of power?. © 2012.

Idea Competitions under scrutiny: Acquisition, intelligence or public relations mechanism?

Idea Competitions (ICs) are becoming a popular mechanism chosen by firms to perform Open Innovation. They are a way to engage with external sources of knowledge such as individual entrepreneurs and small firms who are asked to submit ideas and compete for a prize. However, little is known about the success of ICs as acquisition mechanisms. The researchers conducted interviews in five multinational companies to evaluate the effects of using ICs as an acquisition mechanism. Although still preliminary, the results of this study show that the success of ICs as an acquisition mechanism remains uncertain because their output (i.e. the number of ideas acquired) is often low compared to the input (i.e. the number of ideas submitted) and effort required to run them (e.g. to vet ideas). Across the cases observed, ICs appear to be more successful at identifying and acquiring early-stage ideas, particularly those outside the current business focus. The study shows that ICs deliver other functional benefits such as improved intelligence and public relations and that these need to be considered as part of the evaluation of the IC's success. The paper concludes by discussing the conditions in which ICs are implemented and the implications for Open Innovation theory. © 2013 Elsevier Inc.

Weighted least squares with expectation-maximization algorithm for burst detection in U.K. water distribution systems

Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.