Fantasy proneness and counterfactual thinking

Counterfactual thinking (CFT; mentally simulating alternatives to reality) is central to learning and motivation. Two studies explored the relationship between CFT and fantasy proneness, a personality trait typified by excessive fantasies hard to distinguish from reality. In study1, participants completed a fictional diary entry which was used to measure spontaneous CFT and the Creative Experiences Questionnaire measure of fantasy proneness. Fantasy proneness was significantly correlated with the generation of counterfactual thoughts. Both CFT and fantasy proneness have been independently associated with low mood and study2 included a measure of negative emotional state (the Depression, Anxiety and Stress scale) in addition to the CEQ and CFT. Fantasy proneness and negative emotion both predicted CFT, but no interaction between them was observed. The results suggest that individuals high in fantasy proneness have a general tendency to think counterfactually. © 2012 Elsevier Ltd

cFFR as an alternative to FFR: please do not contrast simplicity!

info:eu-repo/semantics/publishedVersio

Increase in circulating endothelial progenitor cells by statin therapy in patients with stable coronary artery disease

Background - Therapeutic neovascularization may constitute an important strategy to salvage tissue from critical ischemia. Circulating bone marrow–derived endothelial progenitor cells (EPCs) were shown to augment the neovascularization of ischemic tissue. In addition to lipid-lowering activity, hydroxymethyl glutaryl coenzyme A reductase inhibitors (statins) reportedly promote the neovascularization of ischemic tissue in normocholesterolemic animals. Methods and Results - Fifteen patients with angiographically documented stable coronary artery disease (CAD) were prospectively treated with 40 mg of atorvastatin per day for 4 weeks. Before and weekly after the initiation of statin therapy, EPCs were isolated from peripheral blood and counted. In addition, the number of hematopoietic precursor cells positive for CD34, CD133, and CD34/kinase insert domain receptor was analyzed. Statin treatment of patients with stable CAD was associated with an '1.5-fold increase in the number of circulating EPCs by 1 week after initiation of treatment; this was followed by sustained increased levels to '3-fold throughout the 4-week study period. Moreover, the number of CD34/kinase insert domain receptor–positive hematopoietic progenitor cells was significantly augmented after 4 weeks of therapy. Atorvastatin treatment increased the further functional activity of EPCs, as assessed by their migratory capacity

An extensible framework for automatic knowledge extraction from student blogs

This article introduces a framework for automatically extracting knowledge from student blogs and injecting it into a shared resource, namely a Wiki. This is motivated by the need to preserve knowledge generated by students beyond their time of study. The framework is described in the context of the Bachelor of Creative Technologies degree at the Auckland University of Technology in New Zealand where it is being deployed alongside an existing blogging and ePortfolio process. The framework uses an extensible, layered architecture that allows for incremental development of components in the system to enhance the functionality over time. The current implementation is in beta-testing and uses simple heuristics in the core components. This article presents a road map for extending the functionality to improve the quality of knowledge extraction by introducing techniques from the artificial intelligence field

Profoundly reduced neovascularization capacity of bone marrow mononuclear cells derived from patients with chronic ischemic heart disease

Background— Cell therapy with bone marrow–derived stem/progenitor cells is a novel option for improving neovascularization and cardiac function in ischemic heart disease. Circulating endothelial progenitor cells in patients with coronary heart disease are impaired with respect to number and functional activity. However, whether this impairment also extends to bone marrow–derived mononuclear cells (BM-MNCs) in patients with chronic ischemic cardiomyopathy (ICMP) is unclea

Quantifying the role of vehicle size, powertrain technology, activity and consumer behaviour on new UK passenger vehicle fleet energy use and emissions under different policy objectives

This paper quantifies the impacts of policy objectives on the composition of an optimum new passenger vehicle fleet. The objectives are to reduce individually absolute energy use and associated emissions of CO$_2$, NO$_x$ and PM$_{2.5}$. This work combines a top down, diversity-led approach to fleet composition with bottom-up models of 23 powertrain variants across nine vehicle segments. Changing the annual distance travelled only led to the smallest change in fleet composition because driving less mitigated the need to shift to smaller vehicles or more efficient powertrains. Instead, managing activity led to a ‘re-petrolisation’ of the fleet which yielded the largest reductions in emissions of NO$_x$ and PM$_{2.5}$. The hybrid approach of changing annual distance travelled and increasing willingness to accept longer payback times incorporates management of vehicle activity with consumers’ demand for novel vehicle powertrains. Combining these changes in behaviour, without feebates, allowed the hybrid approach to return the largest reductions in energy use and CO$_2$ emissions. Introducing feebates makes low-emitting vehicles more affordable and represents a supply side push for novel powertrains. The largest reductions in energy use and associated emissions occurred without any consumer behaviour change, but required large fees (£79–99 per g CO$_2$/km) on high-emitting vehicles and were achieved using the most specialised fleets. However, such fleets may not present consumers with sufficient choice to be attractive. The fleet with best diversity by vehicle size and powertrain type was achieved with both the external incentive of the feebate and consumers modifying their activity. This work has a number of potential audiences: governments and policy makers may use the framework to understand how to accommodate the growth in vehicle use with pledged reductions in emissions; and original equipment manufacturers may take advantage of the bottom-up, vehicle powertrain inputs to understand the role their technology can play in a fleet under the influence of consumer behaviour change, external incentives and policy objectives.The authors acknowledge the Engineering and Physical Sciences Research Council funding provided for this work under the Centre for Sustainable Road Freight Transport (EP/K00915X/1) and the Energy Efficient Cities Initiative (EP/ F034350/1)

Augmented body: changing interactive body play

This paper investigates the player’s body as a system capable of unfamiliar interactive movement through digital mediation in a playful environment. Body interactions with both digital and non-digital environments are suggested here as a perceptually manipulative exploration area, where by a player altering how they perceive of their body and its operations can create a new playful and original experience. It questions how player interaction can change as perception of the body changes using augmentative technology

Can UK passenger vehicles be designed to meet 2020 emissions targets? A novel methodology to forecast fuel consumption with uncertainty analysis

Vehicle manufacturers are required to reduce their European sales-weighted emissions to 95 g CO2/km by 2020, with the aim of reducing on-road fleet fuel consumption. Nevertheless, current fuel consumption models are not suited for the European market and are unable to account for uncertainties when used to forecast passenger vehicle energy-use. Therefore, a new methodology is detailed herein to quantify new car fleet fuel consumption based on vehicle design metrics. The New European Driving Cycle (NEDC) is shown to underestimate on-road fuel consumption in Spark (SI) and Compression Ignition (CI) vehicles by an average of 16% and 13%, respectively. A Bayesian fuel consumption model attributes these discrepancies to differences in rolling, frictional and aerodynamic resistances. Using projected inputs for engine size, vehicle mass, and compression ratio, the likely average 2020 on-road fuel consumption was estimated to be 7.6 L/100 km for SI and 6.4 L/100 km for CI vehicles. These compared to NEDC based estimates of 5.34 L/100 km (SI) and 4.28 L/100 km (CI), both of which exceeded mandatory 2020 fuel equivalent emissions standards by 30.2% and 18.9%, respectively. The results highlight the need for more stringent technological developments for manufacturers to ensure adherence to targets, and the requirements for more accurate measurement techniques that account for discrepancies between standardised and on-road fuel consumption.NEDC data measurements were supplied by CAP Consulting. The authors are also grateful to the Energy Efficient Cities Initiative and the EPSRC (EP/F034350/1) for funding this work.This is the author accepted mansucript. The final version is available via Elsevier at http://dx.doi.org/10.1016/j.apenergy.2015.03.04