Dual-task decrements in driving performance: The impact of task type,working memory,and the frequency of task performance

Driving while carrying out another (secondary) task interferes with performance, though the degree of interference may vary between tasks and individual drivers. In this study, we focused on two potentially interrelated individual difference variables that may play a role in determining dual-task interference: working memory capacity and the driver’s experience with the relevant secondary task. We used a driving simulator to measure interference, comparing single-task performance (driving alone) with driving performance during three secondary tasks: conversing on a handsfree cellphone, texting, and selecting a song on a touchscreen Mp3 player. Drivers also rated the difficulty of driving while carrying out each secondary task. For the individual difference variables, working memory was measured using the Operation Span test (OSPAN), and experience was assessed in terms of self-reported daily driving exposure and exposure to the relevant secondary tasks (frequency, duration). Overall, we found evidence of dual-task interference, though interference varied between tasks; the texting and Mp3 tasks produced significantly more interference than handsfree cellphone conversation. For the texting and Mp3 song selection tasks, interference was apparent in terms of increased steering variability, but for the Mp3 task there was also compensatory slowing, with drivers slowing down while carrying out the task. OSPAN performance and daily driving exposure were both covariates in predicting the amount of dual-task interference. However, our results suggest that in all but two cases, both involving the texting task, the effects of the OSPAN and the driving and secondary task exposure variables were independent rather than interrelated.     

The effects of secondary tasks that involve listening and speaking on young adult drivers with traits associated with autism spectrum disorders: A pilot study with driving simulation

A driver’s license is key to independence for many young adults, including those with autism spectrum disorders (ASDs). However, individuals with ASDs may face special challenges when learning to drive. If effective driver training is to be devised for this demographic, it is important to determine the nature of these challenges. Driving inherently requires multitasking (e.g. steering, speed maintenance, navigation, hazard detection) and drivers are routinely obligated to combine driving with the demands of listening and responding to others, as occurs during driving lessons. Given that individuals who display traits associated with ASDs may have special difficulties with secondary tasks and especially those that involve socialization, we examined the effects of secondary tasks that involve listening and responding to questions while driving. We compared performance when simply driving (the control condition), driving while listening (the audiobook condition), and driving while listening and speaking (the prompt: answer condition). The autism spectrum quotient (AQ:Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001), a commonly used self-report questionnaire intended to measure traits associated with ASDs in research, was used to identify young drivers with more and fewer traits related to ASDs in a community sample, (None had a clinical diagnosis of ASD.) Consistent with studies of drivers clinically diagnosed with ASDs, we found that high AQ scorers reported greater mental and physical demand, effort, and frustration when driving, and showed more moment-to-moment variability in lane position and hazard reaction compared to low AQ scorers as measured in a driving simulator. Differences between the low and high scorers were typically largest when secondary tasks were imposed, but the predicted interaction between drive condition and AQ group only emerged in terms of steering variability.     

On Modal μ-Calculus and Non-Well-Founded Set Theory

A finitary characterization for non-well-founded sets with finite transitive closure is established in terms of a greatest fixpoint formula of the modal -calculus. This generalizes the standard result in the literature where a finitary modal characterization is provided only for wellfounded sets with finite transitive closure. The proof relies on the concept of automaton, leading then to new interlinks between automata theory and non-well-founded sets.     

An evolutionary system for neural logic networks using genetic programming and indirect encoding

Nowadays, intelligent connectionist systems such as artificial neural networks have been proved very powerful in a wide area of applications. Consequently, the ability to interpret their structure was always a desirable feature for experts. In this field, the neural logic networks (NLN) by their definition are able to represent complex human logic and provide knowledge discovery. However, under contemporary methodologies, the training of these networks may often result in non-comprehensible or poorly designed structures. In this work, we propose an evolutionary system that uses current advances in genetic programming that overcome these drawbacks and produces neural logic networks that can be arbitrarily connected and are easily interpretable into expert rules. To accomplish this task, we guide the genetic programming process using a context-free grammar and we encode indirectly the neural logic networks into the genetic programming individuals. We test the proposed system in two problems of medical diagnosis. Our results are examined both in terms of the solution interpretability that can lead in knowledge discovery, and in terms of the achieved accuracy. We draw conclusions about the effectiveness of the system and we propose further research directions.     

Anomalous brain dominance and the immune system: Do left-handers have specific immunological patterns?

Geschwind and Behan (1982) and Geschwind and Galaburda (1985a, 1985b, 1985c) suggested a correlation between brain laterality and immune disorders. To test whether this hypothesis holds true not only for the frequency of immune diseases and circulating autoantibodies, but extends also to cellular immunity, we examined the association between handedness and markers of cellular immunity. Twenty-seven left-handed and 37 right-handed subjects were serologically screened for cellular parameters and 22 left-handed subjects were typed for human leukocyte antigen (HLA). When compared to the right-handers, the left-handed group showed a significant decrease in the inflammatory cell types CD3(+) T cells (total T cells), CD4(+) T cells (T-helper cells), and HLA-Dr (MHC-II, antigen-presenting cells) as well as in the CD19(+) cells (B cells) and CD16/CD57(+) cells (natural killer cells). We assume a relationship exists between cerebral hemispheric specialisation and the immune system not only for humoral but also for cellular immunity, and we discuss the role of the major histocompatibility complex in neurological and immunological development.     

Psychotherapy assessment: Theory and practice

The history and developments in psychotherapy assessment are reviewed. Suggestions for an extended assessment of several sessions derived from the clinical experience of a District Psychotherapy service are put forward with clinical illustrations. The advantages in terms of flexibility, and the ability to embrace the range of factors involved as well as the influence this has in generating a sense of containment in the patients, are discussed. The implications of this approach on technique, and its differentiation from ongoing psychotherapy, are highlighted. It is suggested that assessment should be seen as an entity in its own right, with its own clinical technique.     

Driver distraction in long-haul truck drivers

Research on driver distraction has typically been conducted by means of epidemiology or experimental testing. The study presented here uses a naturalistic approach, where real-world driving data were collected from truck drivers as they worked their normal delivery runs. Crash, near-crash, and crash-relevant conflict data from 41 long-haul truck drivers, driving approximately 140,000 miles, were examined. Of the 2737 crashes, near-crashes, and crash-relevant conflicts (collectively termed “critical incidents”) that were recorded, 178 were attributed to “driver distraction”. The 178 distraction-related critical incidents were analyzed and 34 unique distraction types were identified. Results showed that a small number of long-haul drivers were involved in a disproportionate number of distraction-related critical incidents. For example, two of the drivers accounted for 43 of the 178 distraction incidents. Important insight was also gained into the relative safety impacts of different distracting agents and behaviors. The frequency and duration of a task, along with the visual demand associated with performing the task, were found to contribute in combination to the prevalence of critical incidents. Finally, it was found that simply because a task does not necessarily require visual attention does not mean that long-haul drivers will not look (sometimes often) away from the roadway. However, it is also clear that visually demanding tasks carry the highest degree of risk, relative to other categories of tasks.     

Mimic automata: A novel formal model for mimic computing

In this paper, we aim to establish a mathematical model for mimic computing. To this end, we present a novel automaton called a mimic automaton. First, a one-dimensional cellular automaton is used for expressing some dynamic changes in the structure of a computing unit, a sequential automaton is employed to describe some state transitions, a hierarchical automaton is employed to express the different granularities of some computing units, and a probabilistic automaton is used to depict some random changes of a computing unit. Second, a mimic automaton is obtained by combining the various types of automata mentioned above in a certain logical relationship. Compared with the existing models of mimic computing, the new model portrays the operational semantics for a mimic computing system, and it can directly describe the behaviors of a system. Furthermore, the new model possesses a stronger generality.     

Philosophy for Computers: Some Explorations in Philosophical Modeling

Philosophical modeling has a long and distinguished history, but the computer offers new and powerful prospects for the creation and manipulation of models. It seems inevitable that the computer will become a major tool in future philosophical research. Here I offer an overview of explorations in philosophical computer modeling that we in the Group for Logic and Formal Semantics at SUNY Stony Brook have undertaken: explorations regarding (1) the potential emergence of cooperation in a society of egoists, (2) self-reference and paradox in fuzzy logic, (3) a fractal approach to formal systems, and (4) on-going explorations with models for the emergence of communication. The attempt is not to give a detailed report on any of these but to give a bird s-eye view of them all, emphasizing the general form that the models take, the philosophical motivations behind them, and the kinds of philosophical results that they may have to offer.