Mindful breath awareness meditation facilitates efficiency gains in brain networks: A steady-state visually evoked potentials study

The beneficial effects of mindfulness-based therapeutic interventions have stimulated a rapidly growing body of scientific research into underlying psychological processes. Resulting evidence indicates that engaging with mindfulness meditation is associated with increased performance on a range of cognitive tasks. However, the mechanisms promoting these improvements require further investigation. We studied changes in behavioural performance of 34 participants during a multiple object tracking (MOT) task that taps core cognitive processes, namely sustained selective visual attention and spatial working memory. Concurrently, we recorded the steady-state visually evoked potential (SSVEP), an EEG signal elicited by the continuously flickering moving objects, and indicator of attentional engagement. Participants were tested before and after practicing eight weeks of mindful breath awareness meditation or progressive muscle relaxation as active control condition. The meditation group improved their MOT-performance and exhibited a reduction of SSVEP amplitudes, whereas no such changes were observed in the relaxation group. Neither group changed in self-reported positive affect and mindfulness, while a marginal increase in negative affect was observed in the mindfulness group. This novel way of combining MOT and SSVEP provides the important insight that mindful breath awareness meditation may lead to refinements of attention networks, enabling more efficient use of attentional resources

Revisiting consistency with random utility maximisation: theory and implications for practical work

While the paradigm of utility maximisation has formed the basis of the majority of applications in discrete choice modelling for over 40 years, its core assumptions have been questioned by work in both behavioural economics and mathematical psychology as well as more recently by developments in the RUM-oriented choice modelling community. This paper reviews the basic properties with a view to explaining the historical pre-eminence of utility maximisation and addresses the question of what departures from the paradigm may be necessary or wise in order to accommodate richer behavioural patterns. We find that many, though not all, of the behavioural traits discussed in the literature can be approximated sufficiently closely by a random utility framework, allowing analysts to retain the many advantages that such an approach possesses

Developing the Questionnaire

AbstractThis chapter outlines the essential topics for developing and testing a questionnaire for a discrete choice experiment survey. It addresses issues such as the description of the environmental good, pretesting of the survey, incentive compatibility, consequentiality or mitigation of hypothetical bias. For the latter, cheap talk scripts, opt-out reminders or an oath script are discussed. Moreover, the use of instructional choice sets, the identification of protest responses and strategic bidders are considered. Finally, issues related to the payment vehicle and the cost vector design are the subject of this section

Econometric Modelling: Extensions

AbstractThis chapter is devoted to advanced issues of econometric modelling. The topics covered are, among others, models in willingness to pay space, the meaning of scale heterogeneity in discrete choice models and the application of various information processing rules such as random regret minimisation or attribute non-attendance. Other topics are anchoring and learning effects when respondents move through a sequence of choice tasks as well as different information processing strategies such as lexicographic preferences or choices based on elimination-by-aspects

Optical sensor for amine vapors based on dimer-monomer equilibrium of indium(III) octaethylporphyrin in a polymeric film

A novel transduction chemistry for the development of a polymer film-based optical sensor that responds reversibly to gas-phase amine species at sub-ppm levels is described. The sensor is based on the equilibrium of a indium(III) octaethylporphyrin hydroxide ion-bridged dimer species with corresponding monomeric porphyrins within a thin poly(vinyl chloride) film as a function of the level of volatile amine in the surrounding gas phase. The presence of amines causes the dimeric species to be converted to monomer via the ligation of the amine with the In(III) center of the porphyrin structure. This yields a significant change in the visible absorption spectrum of the film, with a decrease in the intensity of the Soret band corresponding to the dimer (lambdamax = 390 nm) and a concomitant increase in the Soret band for the monomer lambdamax = 406-408 nm). Response to different amines is based on their relative partition coefficient into the polymer film and their strength of axial ligation reactions, with a selectivity pattern of 1-butylamine &gt; 1-propylamine &gt; pyridine &gt; triethylamine &gt; ethylamine &gt; methylamine &gt; diethylamine &gt; tert-butylamine &gt; ammonia. It is further shown that a significant concentration of dimeric species within the polymer film can only be achieved if appropriate amounts of lipophilic anionic sites are also incorporated into the polymer in the form of a tetraphenylborate derivative and the resulting film is equilibrated briefly with water prior to gas-phase measurements. With optimized film compositions, 1-butylamine can be detected in the gas phase to levels approaching 0.1 ppm, while less lipophilic ammonia can be monitored down to 10 ppm, with fully reversible responses to each species. A simple mathematical model for the response of the amine sensor is presented and shown to predict the optical behavior observed.</span

Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics

This paper introduces the discrete choice model-paradigm of Random Regret Minimization (RRM) to the field of environmental and resource economics. The RRM-approach has been very recently developed in the context of travel demand modelling and presents a tractable, regret-based alternative to the dominant choice-modelling paradigm based on Random Utility Maximization-theory (RUM-theory). We highlight how RRM-basedmodels provide closed form, logit-type formulations for choice probabilities that allow for capturing semi-compensatory behaviour and choice set-composition effects while being equally parsimonious as their utilitarian counterparts. Using data from a Stated Choice experiment aimed at identifying valuations of characteristics of nature parks, we compare RRM-based models and RUM-based models in terms of parameter estimates, goodness of fit, elasticities and consequential policy implications.Infrastructures, Systems and ServicesTechnology, Policy and Managemen