The relationship between cognitive ability, insight and self-regulatory behaviors: Findings from the older driver population

Self-regulation is often promoted as a coping strategy that may allow older drivers to drive safely for longer. Self-regulation depends upon drivers making an accurate assessment of their own ability and having a willingness to practice self-regulatory behaviors to compensate for changes in ability. The current study explored the relationship between older drivers’ cognitive ability, their driving confidence and their use of self-regulation. An additional study aim was to explore the relationship between these factors and older drivers’ interest in driving programs. Seventy Australian drivers aged 65 years and over completed a questionnaire about their driving and a brief screening measure of cognitive ability (an untimed Clock Drawing Test). While all participants reported high levels of confidence regarding their driving ability, and agreed that they would continue driving in the foreseeable future, a notable proportion performed poorly on the Clock Drawing Test. Compared to older drivers who successfully completed the Clock Drawing Test, those who failed the cognitive test were significantly less likely to report driving self-regulation, and showed significantly less interest in being involved in driving programs. Older drivers with declining cognitive abilities may not be self-regulating their driving. This group also appears to be unlikely to self-refer to driving programs.

Human–computer interaction : the impact of users’ cognitive styles on query reformulation behaviour during web searching

This paper discusses users’ query reformulation behaviour while searching information on the Web. Query reformulations have emerged as an important component of Web search behaviour and human-computer interaction (HCI) because a user’s success of information retrieval (IR) depends on how he or she formulates queries. There are various factors, such as cognitive styles, that influence users’ query reformulation behaviour. Understanding how users with different cognitive styles formulate their queries while performing Web searches can help HCI researchers and information systems (IS) developers to provide assistance to the users. This paper aims to examine the effects of users’ cognitive styles on their query reformation behaviour. To achieve the goal of the study, a user study was conducted in which a total of 3613 search terms and 872 search queries were submitted by 50 users who engaged in 150 scenario-based search tasks. Riding’s (1991) Cognitive Style Analysis (CSA) test was used to assess users’ cognitive style as wholist or analytic, and verbaliser or imager. The study findings show that users’ query reformulation behaviour is affected by their cognitive styles. The results reveal that analytic users tended to prefer Add queries while all other users preferred New queries. A significant difference was found among wholists and analytics in the manner they performed Remove query reformulations. Future HCI researchers and IS developers can utilize the study results to develop interactive and user-cantered search model, and to provide context-based query suggestions for users.

'It ain't over till it's over' : Yogi Berra bias on prediction markets

The recent expansion of prediction markets provides a great opportunity to test the market efficiency hypothesis and the calibration of trader judgements. Using a large database of observed prices, this article studies the calibration of prediction markets prices on sporting events using both nonparametric and parametric methods. While only minor bias can be observed during most of the lifetime of the contracts, the calibration of prices deteriorates very significantly in the last moments of the contracts’ lives. Traders tend to overestimate the probability of the losing team to reverse the situation in the last minutes of the game.

Maintaining a cognitive map in darkness : the need to fuse boundary knowledge with path integration

Spatial navigation requires the processing of complex, disparate and often ambiguous sensory data. The neurocomputations underpinning this vital ability remain poorly understood. Controversy remains as to whether multimodal sensory information must be combined into a unified representation, consistent with Tolman's "cognitive map", or whether differential activation of independent navigation modules suffice to explain observed navigation behaviour. Here we demonstrate that key neural correlates of spatial navigation in darkness cannot be explained if the path integration system acted independently of boundary (landmark) information. In vivo recordings demonstrate that the rodent head direction (HD) system becomes unstable within three minutes without vision. In contrast, rodents maintain stable place fields and grid fields for over half an hour without vision. Using a simple HD error model, we show analytically that idiothetic path integration (iPI) alone cannot be used to maintain any stable place representation beyond two to three minutes. We then use a measure of place stability based on information theoretic principles to prove that featureless boundaries alone cannot be used to improve localization above chance level. Having shown that neither iPI nor boundaries alone are sufficient, we then address the question of whether their combination is sufficient and - we conjecture - necessary to maintain place stability for prolonged periods without vision. We addressed this question in simulations and robot experiments using a navigation model comprising of a particle filter and boundary map. The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. We discuss our findings in light of current theories of animal navigation and neuronal computation, and elaborate on their implications and significance for the design, analysis and interpretation of experiments.

Jackknife for bias reduction in predictive regressions

One of the fundamental econometric models in finance is predictive regression. The standard least squares method produces biased coefficient estimates when the regressor is persistent and its innovations are correlated with those of the dependent variable. This article proposes a general and convenient method based on the jackknife technique to tackle the estimation problem. The proposed method reduces the bias for both single- and multiple-regressor models and for both short- and long-horizon regressions. The effectiveness of the proposed method is demonstrated by simulations. An empirical application to equity premium prediction using the dividend yield and the short rate highlights the differences between the results by the standard approach and those by the bias-reduced estimator. The significant predictive variables under the ordinary least squares become insignificant after adjusting for the finite-sample bias. These discrepancies suggest that bias reduction in predictive regressions is important in practical applications.

Towards an integration of the theory of planned behaviour and cognitive behavioural strategies : an example from a school-based injury prevention programme

Adolescent risk-taking behavior has potentially serious injury consequences and school-based behavior change programs provide potential for reducing such harm. A well-designed program is likely to be theory-based and ecologically valid however it is rare that the operationalisation process of theories is described. The aim of this paper is to outline how the Theory of Planned Behavior and Cognitive Behavioral Therapy informed intervention design in a school setting. Teacher interviews provided insights into strategies that might be implemented within the curriculum and provided detail used to operationalise theory constructs. Benefits and challenges in applying both theories are described with examples from an injury prevention program, Skills for Preventing Injury in Youth.

Spectrum sensing, detection and optimisation in cognitive radio for non-stationary primary user signals

Cognitive radio is an emerging technology proposing the concept of dynamic spec- trum access as a solution to the looming problem of spectrum scarcity caused by the growth in wireless communication systems. Under the proposed concept, non- licensed, secondary users (SU) can access spectrum owned by licensed, primary users (PU) so long as interference to PU are kept minimal. Spectrum sensing is a crucial task in cognitive radio whereby the SU senses the spectrum to detect the presence or absence of any PU signal. Conventional spectrum sensing assumes the PU signal as ‘stationary’ and remains in the same activity state during the sensing cycle, while an emerging trend models PU as ‘non-stationary’ and undergoes state changes. Existing studies have focused on non-stationary PU during the transmission period, however very little research considered the impact on spectrum sensing when the PU is non-stationary during the sensing period. The concept of PU duty cycle is developed as a tool to analyse the performance of spectrum sensing detectors when detecting non-stationary PU signals. New detectors are also proposed to optimise detection with respect to duty cycle ex- hibited by the PU. This research consists of two major investigations. The first stage investigates the impact of duty cycle on the performance of existing detec- tors and the extent of the problem in existing studies. The second stage develops new detection models and frameworks to ensure the integrity of spectrum sensing when detecting non-stationary PU signals. The first investigation demonstrates that conventional signal model formulated for stationary PU does not accurately reflect the behaviour of a non-stationary PU. Therefore the performance calculated and assumed to be achievable by the conventional detector does not reflect actual performance achieved. Through analysing the statistical properties of duty cycle, performance degradation is proved to be a problem that cannot be easily neglected in existing sensing studies when PU is modelled as non-stationary. The second investigation presents detectors that are aware of the duty cycle ex- hibited by a non-stationary PU. A two stage detection model is proposed to improve the detection performance and robustness to changes in duty cycle. This detector is most suitable for applications that require long sensing periods. A second detector, the duty cycle based energy detector is formulated by integrat- ing the distribution of duty cycle into the test statistic of the energy detector and suitable for short sensing periods. The decision threshold is optimised with respect to the traffic model of the PU, hence the proposed detector can calculate average detection performance that reflect realistic results. A detection framework for the application of spectrum sensing optimisation is proposed to provide clear guidance on the constraints on sensing and detection model. Following this framework will ensure the signal model accurately reflects practical behaviour while the detection model implemented is also suitable for the desired detection assumption. Based on this framework, a spectrum sensing optimisation algorithm is further developed to maximise the sensing efficiency for non-stationary PU. New optimisation constraints are derived to account for any PU state changes within the sensing cycle while implementing the proposed duty cycle based detector.

Experimental observations of rapid maize streak virus evolution reveal a strand-specific nucleotide substitution bias

Background. Recent reports have indicated that single-stranded DNA (ssDNA) viruses in the taxonomic families Geminiviridae, Parvoviridae and Anellovirus may be evolving at rates of ∼10-4 substitutions per site per year (subs/site/year). These evolution rates are similar to those of RNA viruses and are surprisingly high given that ssDNA virus replication involves host DNA polymerases with fidelities approximately 10 000 times greater than those of error-prone viral RNA polymerases. Although high ssDNA virus evolution rates were first suggested in evolution experiments involving the geminivirus maize streak virus (MSV), the evolution rate of this virus has never been accurately measured. Also, questions regarding both the mechanistic basis and adaptive value of high geminivirus mutation rates remain unanswered. Results. We determined the short-term evolution rate of MSV using full genome analysis of virus populations initiated from cloned genomes. Three wild type viruses and three defective artificial chimaeric viruses were maintained in planta for up to five years and displayed evolution rates of between 7.4 × 10-4 and 7.9 × 10-4 subs/site/year. Conclusion. These MSV evolution rates are within the ranges observed for other ssDNA viruses and RNA viruses. Although no obvious evidence of positive selection was detected, the uneven distribution of mutations within the defective virus genomes suggests that some of the changes may have been adaptive. We also observed inter-strand nucleotide substitution imbalances that are consistent with a recent proposal that high mutation rates in geminiviruses (and possibly ssDNA viruses in general) may be due to mutagenic processes acting specifically on ssDNA molecules. © 2008 Walt et al; licensee BioMed Central Ltd.