Genetic algorithms: a pragmatic, non-parametric approach to exploratory analysis of questionnaires in educational research

Data from a survey to determine student attitudes to their courses are used as an example to show how genetic algorithms can be used in the analysis of questionnaire data. Genetic algorithms provide a means of generating logical rules which predict one variable in a data set by relating it to others. This paper explains the principle underlying genetic algorithms and gives a non-mathematical description of the means by which rules are generated. A commercially available computer program is used to apply genetic algorithms to the survey data. The results are discussed

Neighbourhood, Route and Workplace-Related Environmental Characteristics Predict Adults' Mode of Travel to Work

Commuting provides opportunities for regular physical activity which can reduce the risk of chronic disease. Commuters' mode of travel may be shaped by their environment, but understanding of which specific environmental characteristics are most important and might form targets for intervention is limited. This study investigated associations between mode choice and a range of objectively assessed environmental characteristics.Participants in the Commuting and Health in Cambridge study reported where they lived and worked, their usual mode of travel to work and a variety of socio-demographic characteristics. Using geographic information system (GIS) software, 30 exposure variables were produced capturing characteristics of areas around participants' homes and workplaces and their shortest modelled routes to work. Associations between usual mode of travel to work and personal and environmental characteristics were investigated using multinomial logistic regression.Of the 1124 respondents, 50% reported cycling or walking as their usual mode of travel to work. In adjusted analyses, home-work distance was strongly associated with mode choice, particularly for walking. Lower odds of walking or cycling rather than driving were associated with a less frequent bus service (highest versus lowest tertile: walking OR 0.61 [95% CI 0.20–1.85]; cycling OR 0.43 [95% CI 0.23–0.83]), low street connectivity (OR 0.22, [0.07–0.67]; OR 0.48 [0.26–0.90]) and free car parking at work (OR 0.24 [0.10–0.59]; OR 0.55 [0.32–0.95]). Participants were less likely to cycle if they had access to fewer destinations (leisure facilities, shops and schools) close to work (OR 0.36 [0.21–0.62]) and a railway station further from home (OR 0.53 [0.30–0.93]). Covariates strongly predicted travel mode (pseudo r-squared 0.74).Potentially modifiable environmental characteristics, including workplace car parking, street connectivity and access to public transport, are associated with travel mode choice, and could be addressed as part of transport policy and infrastructural interventions to promote active commuting

Advanced Energy Management Control for Energy Storage System

An energy management controller based on multiple charge/discharge profiles is proposed and analysed for an energy storage system. Each profile is designed to use the available energy more aggressively in different power regions, including the low or the high power regions, or both regions to minimise the rate-of-change of power source output. The performance of the energy storage system with the profiles is examined by simulation when connected to an aircraft 540V DC bus with a fault-tolerant starter/generator and high power, pulsed loads

The Democratic Biopolitics of PrEP

PrEP (Pre-Exposure Prophylaxis) is a relatively new drug-based HIV prevention technique and an important means to lower the HIV risk of gay men who are especially vulnerable to HIV. From the perspective of biopolitics, PrEP inscribes itself in a larger trend of medicalization and the rise of pharmapower. This article reconstructs and evaluates contemporary literature on biopolitical theory as it applies to PrEP, by bringing it in a dialogue with a mapping of the political debate on PrEP. As PrEP changes sexual norms and subjectification, for example condom use and its meaning for gay subjectivity, it is highly contested. The article shows that the debate on PrEP can be best described with the concepts ‘sexual-somatic ethics’ and ‘democratic biopolitics’, which I develop based on the biopolitical approach of Nikolas Rose and Paul Rabinow. In contrast, interpretations of PrEP which are following governmentality studies or Italian Theory amount to either farfetched or trivial positions on PrEP, when seen in light of the political debate. Furthermore, the article is a contribution to the scholarship on gay subjectivity, highlighting how homophobia and homonormativity haunts gay sex even in liberal environments, and how PrEP can serve as an entry point for the destigmatization of gay sexuality and transformation of gay subjectivity. ‘Biopolitical democratization’ entails making explicit how medical technology and health care relates to sexual subjectification and ethics, to strengthen the voice of (potential) PrEP users in health politics, and to renegotiate the profit and power of Big Pharma

Living with COVID-19 and preparing for future pandemics: revisiting lessons from the HIV pandemic

In April, 2020, just months into the COVID-19 pandemic, an international group of public health researchers published three lessons learned from the HIV pandemic for the response to COVID-19, which were to: anticipate health inequalities, create an enabling environment to support behavioural change, and engage a multidisciplinary effort. We revisit these lessons in light of more than 2 years’ experience with the COVID-19 pandemic. With specific examples, we detail how inequalities have played out within and between countries, highlight factors that support or impede the creation of enabling environments, and note ongoing issues with the scarcity of integrated science and health system approaches. We argue that to better apply lessons learned as the COVID-19 pandemic matures and other infectious disease outbreaks emerge, it will be imperative to create dialogue among polarised perspectives, identify shared priorities, and draw on multidisciplinary evidence

Increases in plasma sheet temperature with solar wind driving during substorm growth phases

During the substorm growth phase, magnetic reconnection extracts ~10^15 J from the solar wind through magnetic reconnection at the magnetopause, which is then stored in the magnetotail lobes. Plasma sheet pressure then increases to balance magnetic flux density increases in the lobes. We examine plasma sheet pressure, density and temperature during substorm growth phases using nine years of Cluster data (>316,000 data points). We show that plasma sheet pressure and temperature are higher during growth phases with higher solar wind driving whereas the density is approximately constant. We also show a weak correlation between plasma sheet temperature before onset and the minimum SuperMAG SML auroral index in the subsequent substorm. We discuss how energization of the plasma sheet before onset may result from thermodynamically adiabatic processes; how hotter plasma sheets may result in magnetotail instabilities and how this relates to the onset and size of the subsequent substorm expansion phase

Battery energy storage systems for the electricity grid: UK research facilities

Grid-connected battery energy storage systems with fast acting control are a key technology for improving power network stability and increasing the penetration of renewable generation. This paper describes two battery energy storage research facilities connected to the UK electricity grid. Their performance is detailed, along with hardware results, and a number of grid support services are demonstrated, again with results presented. The facility operated by The University of Manchester is rated at 236kVA, 180kWh, and connected to the 400V campus power network, The University of Sheffield operates a 2MVA, 1MWh facility connected to an 11kV distribution network

The Cascadia Initiative : a sea change In seismological studies of subduction zones

Author Posting. © The Oceanography Society, 2014. This article is posted here by permission of The Oceanography Society for personal use, not for redistribution. The definitive version was published in Oceanography 27, no. 2 (2014): 138-150, doi:10.5670/oceanog.2014.49.Increasing public awareness that the Cascadia subduction zone in the Pacific Northwest is capable of great earthquakes (magnitude 9 and greater) motivates the Cascadia Initiative, an ambitious onshore/offshore seismic and geodetic experiment that takes advantage of an amphibious array to study questions ranging from megathrust earthquakes, to volcanic arc structure, to the formation, deformation and hydration of the Juan De Fuca and Gorda Plates. Here, we provide an overview of the Cascadia Initiative, including its primary science objectives, its experimental design and implementation, and a preview of how the resulting data are being used by a diverse and growing scientific community. The Cascadia Initiative also exemplifies how new technology and community-based experiments are opening up frontiers for marine science. The new technology—shielded ocean bottom seismometers—is allowing more routine investigation of the source zone of megathrust earthquakes, which almost exclusively lies offshore and in shallow water. The Cascadia Initiative offers opportunities and accompanying challenges to a rapidly expanding community of those who use ocean bottom seismic data.The Cascadia Initiative is supported by the National Science Foundation; the CIET is supported under grants OCE- 1139701, OCE-1238023, OCE‐1342503, OCE-1407821, and OCE-1427663 to the University of Oregon

Class-based grouping in perspective images

In any object recognition system a major and primary task is to associate those image features, within an image of a complex scene, that arise from an individual object. The key idea here is that a geometric class defined in 3D induces relationships in the image which must hold between points on the image outline (the perspective projection of the object). The resulting image constraints enable both identification and grouping of image features belonging to objects of that class. The classes include surfaces of revolution, canal surfaces (pipes) and polyhedra. Recognition proceeds by first recognising an object as belonging to one of the classes (for example a surface of revolution) and subsequently identifying the object (for example as a particular vase). This differs from conventional object recognition systems where recognition is generally targetted at particular objects. These classes also support the computation of 3D invariant descriptions including symmetry axes, canonical coordinate frames and projective signatures. The constraints and grouping methods are viewpoint invariant, and proceed with no information on object pose. We demonstrate the effectiveness of this class-based grouping on real, cluttered scenes using grouping algorithms developed for rotationally symmetric surfaces, canal-surfaces and polyhedra