Optical Bloch equations and enhanced decay of Rabi oscillations in strong driving fields

Optical Bloch equations are widely used for describing dynamics in a system consisting molecules, electromagnetic waves, and a thermal bath. We analyze applicability of these equations to a single molecule imbedded in a solid matrix. Classical Bloch equations and the limits of their applicability are derived from more general master equations. Simple and intuitively appealing picture based on stochastic Bloch equations shows that at low temperatures, contrary to common believes, a strong driving field can not only suppress but can also increase decay rates of Rabi oscillations. A physical system where predicted effects can be observed experimentally is suggested. (c) 2005 Elsevier B.V. All rights reserved.

Risk taking from the participant's perspective: The case of driving and accident risk

Although perceived health risk plays a prominent role in theories of health behavior. its empirical role in risk taking is less clear. In Study 1 (N = 129), 2 measures of drivers' risk-taking behavior were found to be unrelated to self-estimates of accident concern but to be related to self-ratings of driving skill and the perceived thrill of driving. In Study 2 (N = 405), out of a wide range of potential influences, accident concern had the weakest relationship with risk taking. The authors concluded that although health risk is a key feature in many theories of health behavior and a central focus for researchers and policy makers, it may not be such a prominent factor for those actually taking the risk.

The effect of auditory and visual distracters on the useful field of view: Implications for the driving task

PURPOSE. The driving environment is becoming increasingly complex, including both visual and auditory distractions within the in- vehicle and external driving environments. This study was designed to investigate the effect of visual and auditory distractions on a performance measure that has been shown to be related to driving safety, the useful field of view. METHODS. A laboratory study recorded the useful field of view in 28 young visually normal adults (mean 22.6 +/- 2.2 years). The useful field of view was measured in the presence and absence of visual distracters (of the same angular subtense as the target) and with three levels of auditory distraction (none, listening only, listening and responding). RESULTS. Central errors increased significantly (P < 0.05) in the presence of auditory but not visual distracters, while peripheral errors increased in the presence of both visual and auditory distracters. Peripheral errors increased with eccentricity and were greatest in the inferior region in the presence of distracters. CONCLUSIONS. Visual and auditory distracters reduce the extent of the useful field of view, and these effects are exacerbated in inferior and peripheral locations. This result has significant ramifications for road safety in an increasingly complex in-vehicle and driving environment.

Unsafe driving behaviour and four wheel drive vehicles: observational study

Objective To assess the level of compliance with the new law in the United Kingdom mandating penalties for rising a hand held mobile phone while driving, to compare compliance with this law with the one on the use of seat belts, and to compare compliance with these laws between drivers of four wheel drive vehicles and drivers of normal cars. Design Observational study with two phases-one within the grace period, the other starting one week after penalties were imposed on drivers using such telephones. Setting Three busy sites in London. Participants Drivers of 38 182 normal cars and 2944 four wheel drive vehicles. Main outcome measures Proportions of drivers seen to be using hand held mobile phones and not using seat belts. Results Drivers of four wheel drive vehicles were more likely than drivers of other cars to be seen using hand held mobile phones (8.2% v 2.0%) and not complying with the law on seat belts (19.5% v 15.0%). Levels of non-compliance with both laws were slightly higher in the penalty phase of observation, and breaking one law was associated with increased likelihood of breaking the other. Conclusions The level of non-compliance with the law on the use of hand held mobile phones by drivers in London is high, as is non-compliance with the law on seat belts. Drivers of four wheel drive vehicles were four times more likely than drivers of other cars to be seen using hand held mobile phones and slightly more likely not to comply with the law on seat belts.

Signal detection theory in applied tasks: The case of hazard perception in driving

Fuzzy signal detection analysis can be a useful complementary technique to traditional signal detection theory analysis methods, particularly in applied settings. For example, traffic situations are better conceived as being on a continuum from no potential for hazard to high potential, rather than either having potential or not having potential. This study examined the relative contribution of sensitivity and response bias to explaining differences in the hazard perception performance of novices and experienced drivers, and the effect of a training manipulation. Novice drivers and experienced drivers were compared (N = 64). Half the novices received training, while the experienced drivers and half the novices remained untrained. Participants completed a hazard perception test and rated potential for hazard in occluded scenes. The response latency of participants to the hazard perception test replicated previous findings of experienced/novice differences and trained/untrained differences. Fuzzy signal detection analysis of both the hazard perception task and the occluded rating task suggested that response bias may be more central to hazard perception test performance than sensitivity, with trained and experienced drivers responding faster and with a more liberal bias than untrained novices. Implications for driver training and the hazard perception test are discussed.

Multisensorial obstacles detection and classification for ADAS and autonomous driving

A reliable perception of the real world is a key-feature for an autonomous vehicle and the Advanced Driver Assistance Systems (ADAS). Obstacles detection (OD) is one of the main components for the correct reconstruction of the dynamic world. Historical approaches based on stereo vision and other 3D perception technologies (e.g. LIDAR) have been adapted to the ADAS first and autonomous ground vehicles, after, providing excellent results. The obstacles detection is a very broad field and this domain counts a lot of works in the last years. In academic research, it has been clearly established the essential role of these systems to realize active safety systems for accident prevention, reflecting also the innovative systems introduced by industry. These systems need to accurately assess situational criticalities and simultaneously assess awareness of these criticalities by the driver; it requires that the obstacles detection algorithms must be reliable and accurate, providing: a real-time output, a stable and robust representation of the environment and an estimation independent from lighting and weather conditions. Initial systems relied on only one exteroceptive sensor (e.g. radar or laser for ACC and camera for LDW) in addition to proprioceptive sensors such as wheel speed and yaw rate sensors. But, current systems, such as ACC operating at the entire speed range or autonomous braking for collision avoidance, require the use of multiple sensors since individually they can not meet these requirements. It has led the community to move towards the use of a combination of them in order to exploit the benefits of each one. Pedestrians and vehicles detection are ones of the major thrusts in situational criticalities assessment, still remaining an active area of research. ADASs are the most prominent use case of pedestrians and vehicles detection. Vehicles should be equipped with sensing capabilities able to detect and act on objects in dangerous situations, where the driver would not be able to avoid a collision. A full ADAS or autonomous vehicle, with regard to pedestrians and vehicles, would not only include detection but also tracking, orientation, intent analysis, and collision prediction. The system detects obstacles using a probabilistic occupancy grid built from a multi-resolution disparity map. Obstacles classification is based on an AdaBoost SoftCascade trained on Aggregate Channel Features. A final stage of tracking and fusion guarantees stability and robustness to the result.

Organizations driving positive social change:a review and an integrative framework of change processes

Academic and practitioner interest in how market-based organizations can drive positive social change (PSC) is steadily growing. This paper helps to recast how organizations relate to society. It integrates research on projects stimulating PSC – the transformational processes to advance societal well-being – which is fragmented across different streams of research in management and related disciplines. Focusing on the mechanisms at play in how organizations and their projects affect change in targets outside of organizational boundaries, we 1) clarify the nature of PSC as a process, 2) develop an integrative framework that specifies two distinct PSC strategies, 3) take stock of and offer a categorization scheme for change mechanisms and enabling organizational practices, and 4) outline opportunities for future research. Our conceptual framework differentiates between surface- and deep-level PSC strategies understood as distinct combinations of change mechanisms and enabling organizational practices. These strategies differ in the nature and speed of transformation experienced by the targets of change projects and the resulting quality (pervasiveness and durability), timing, and reach of social impact. Our findings provide a solid base for integrating and advancing knowledge across the largely disparate streams of management research on Corporate Social Responsibility, Social Entrepreneurship, and Base of the Pyramid, and open up important new avenues for future research on organizing for PSC and on unpacking PSC processes.

An investigation into children’s inductive reasoning strategies:What drives the development of category induction?

In a series of studies, I investigated the developmental changes in children’s inductive reasoning strategy, methodological manipulations affecting the trajectory, and driving mechanisms behind the development of category induction. I systematically controlled the nature of the stimuli used, and employed a triad paradigm in which perceptual cues were directly pitted against category membership, to explore under which circumstances children used perceptual or category induction. My induction tasks were designed for children aged 3-9 years old using biologically plausible novel items. In Study 1, I tested 264 children. Using a wide age range allowed me to systematically investigate the developmental trajectory of induction. I also created two degrees of perceptual distractor – high and low – and explored whether the degree of perceptual similarity between target and test items altered children’s strategy preference. A further 52 children were tested in Study 2, to examine whether children showing a perceptual-bias were in fact basing their choice on maturation categories. A gradual transition was observed from perceptual to category induction. However, this transition could not be due to the inability to inhibit high perceptual distractors as children of all ages were equally distracted. Children were also not basing their strategy choices on maturation categories. In Study 3, I investigated category structure (featural vs. relational category rules) and domain (natural vs. artefact) on inductive preference. I tested 403 children. Each child was assigned to either the featural or relational condition, and completed both a natural kind and an artefact task. A further 98 children were tested in Study 4, on the effect of using stimuli labels during the tasks. I observed the same gradual transition from perceptual to category induction preference in Studies 3 and 4. This pattern was stable across domains, but children developed a category-bias one year later for relational categories, arguably due to the greater demands on executive function (EF) posed by these stimuli. Children who received labels during the task made significantly more category choices than those who did not receive labels, possibly due to priming effects. Having investigated influences affecting the developmental trajectory, I continued by exploring the driving mechanism behind the development of category induction. In Study 5, I tested 60 children on a battery of EF tasks as well as my induction task. None of the EF tasks were able to predict inductive variance, therefore EF development is unlikely to be the driving factor behind the transition. Finally in Study 6, I divided 252 children into either a comparison group or an intervention group. The intervention group took part in an interactive educational session at Twycross Zoo about animal adaptations. Both groups took part in four induction tasks, two before and two a week after the zoo visits. There was a significant increase in the number of category choices made in the intervention condition after the zoo visit, a result not observed in the comparison condition. This highlights the role of knowledge in supporting the transition from perceptual to category induction. I suggest that EF development may support induction development, but the driving mechanism behind the transition is an accumulation of knowledge, and an appreciation for the importance of category membership.