The crash involvement of older drivers is associated with their hazard perception latencies

Hazard perception in driving is the one of the few driving-specific skills associated with crash involvement. However, this relationship has only been examined in studies where the majority of individuals were younger than 65. We present the first data revealing an association between hazard perception and self-reported crash involvement in drivers aged 65 and over. In a sample of 271 drivers, we found that individuals whose mean response time to traffic hazards was slower than 6.68 seconds (the ROC-curve derived pass mark for the test) were 2.32 times (95% CI 1.46, 3.22) more likely to have been involved in a self-reported crash within the previous five years than those with faster response times. This likelihood ratio became 2.37 (95% CI 1.49, 3.28) when driving exposure was controlled for. As a comparison, individuals who failed a test of useful field of view were 2.70 (95% CI 1.44, 4.44) times more likely to crash than those who passed. The hazard perception test and the useful field of view measure accounted for separate variance in crash involvement. These findings indicate that hazard perception testing and training could be potentially useful for road safety interventions for this age group.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Years 2 to 6 students' ability to generalise : models, representations and theory for teaching and learning

Over the last three years, in our Early Algebra Thinking Project, we have been studying Years 3 to 5 students’ ability to generalise in a variety of situations, namely, compensation principles in computation, the balance principle in equivalence and equations, change and inverse change rules with function machines, and pattern rules with growing patterns. In these studies, we have attempted to involve a variety of models and representations and to build students’ abilities to switch between them (in line with the theories of Dreyfus, 1991, and Duval, 1999). The results have shown the negative effect of closure on generalisation in symbolic representations, the predominance of single variance generalisation over covariant generalisation in tabular representations, and the reduced ability to readily identify commonalities and relationships in enactive and iconic representations. This chapter uses the results to explore the interrelation between generalisation and verbal and visual comprehension of context. The studies evidence the importance of understanding and communicating aspects of representational forms which allowed commonalities to be seen across or between representations. Finally the chapter explores the implications of the studies for a theory that describes a growth in integration of models and representations that leads to generalisation.

Melanocyte homeostasis in vivo tolerates Rb1 loss in a developmentally independent fashion

There has been uncertainty regarding the precise role that the pocket protein Rb1 plays in murine melanocyte homeostasis. It has been reported that the TAT-Cre mediated loss of exon 19 from a floxed Rb1 allele causes melanocyte apoptosis in vivo and in vitro. This is at variance with other findings showing, either directly or indirectly, that Rb1 loss in melanocytes has no noticeable effect in vivo, but in vitro leads to a semi-transformed phenotype. In this study, we show that Rb1-null melanocytes lacking exon 19 do not undergo apoptosis and survive both in vitro and in vivo, irrespective of the developmental stage at which Cre-mediated ablation of the exon occurs. Further, Rb1 loss has no serious long-term ramifications on melanocyte homeostasis in vivo, with Rb1-null melanocytes being detected in the skin after numerous hair cycles, inferring that the melanocyte stem cell population carrying the Cre-mediated deletion is maintained. Consequently, whilst Rb1 loss in the melanocyte is able to alter cellular behaviour in vitro, it appears inconsequential with respect to melanocyte homeostasis in the mouse skin.

Rumination, post-traumatic growth, and distress : structural equation modelling with cancer survivors

Objective Theoretical models of post-traumatic growth (PTG) have been derived in the general trauma literature to describe the post-trauma experience that facilitates the perception of positive life changes. To develop a statistical model identifying factors that are associated with PTG, structural equation modelling (SEM) was used in the current study to assess the relationships between perception of diagnosis severity, rumination, social support, distress, and PTG. Method A statistical model of PTG was tested in a sample of participants diagnosed with a variety of cancers (N=313). Results An initial principal components analysis of the measure used to assess rumination revealed three components: intrusive rumination, deliberate rumination of benefits, and life purpose rumination. SEM results indicated that the model fit the data well and that 30% of the variance in PTG was explained by the variables. Trauma severity was directly related to distress, but not to PTG. Deliberately ruminating on benefits and social support were directly related to PTG. Life purpose rumination and intrusive rumination were associated with distress. Conclusions The model showed that in addition to having unique correlating factors, distress was not related to PTG, thereby providing support for the notion that these are discrete constructs in the post-diagnosis experience. The statistical model provides support that post-diagnosis experience is simultaneously shaped by positive and negative life changes and that one or the other outcome may be prevalent or may occur concurrently. As such, an implication for practice is the need for supportive care that is holistic in nature.

Genetic analysis reveals two stocks of skipjack tuna (Katsuwonus pelamis) in the north western Indian Ocean

Skipjack (SJT) (Katsuwonus pelamis) is a medium sized, pelagic, highly dispersive tuna species that occurs widely across tropical and subtropical waters. SJT constitute the largest tuna fishery in the Indian Ocean, and are currently managed as a single stock. Patterns of genetic variation in a mtDNA gene and 6 microsatellite loci were examined to test for stock structure in the northwestern Indian Ocean. 324 individuals were sampled from five major fishing grounds around Sri Lanka, and single sites in the Maldive Islands and the Laccadive Islands. Phylogenetic reconstruction of mtDNA revealed two coexisting divergent clades in the region. AMOVA (Analysis of Molecular Variance) of mtDNA data revealed significant genetic differentiation among sites (ΦST = 0.2029, P < 0.0001), also supported by SAMOVA results. AMOVA of microsatellite data also showed significant differentiation among most sampled sites (FST = 0.0256, P<0.001) consistent with the mtDNA pattern. STRUCTURE analysis of the microsatellite data revealed two differentiated stocks. While the both two marker types examined identified two genetic groups, microsatellite analysis indicates that the sampled SJT are likely to represent individuals sourced from discrete breeding grounds that are mixed in feeding grounds in Sri Lankan waters.

Estimates of crowding in long-term care: Comparing two approaches

Objective: Because studies of crowding in long-term care settings are lacking, the authors sought to: (1) generate initial estimates of crowding in nursing homes and assisted living facilities; and (2) evaluate two operational approaches to its measurement. ----- ----- Background: Reactions to density and proximity are complex. Greater density intensifies people's reaction to a situation in the direction (positive or negative) that they would react if the situation were to occur under less dense conditions. People with dementia are especially reactive to the environment. ----- ----- Methods: Using a cross-sectional correlational design in nursing homes and assisted living facilities involving 185 participants, multiple observations (N = 6,455) of crowding and other environmental variables were made. Crowding, location, and sound were measured three times per observation; ambiance was measured once. Data analyses consisted of descriptive statistics, t-tests, and one-way analysis of variance. ----- ----- Results: Crowding estimates were higher for nursing homes and in dining and activity rooms. Crowding also varied across settings and locations by time of day. Overall, the interaction of location and time affected crowding significantly (N = 5,559, df [47, 511], F = 105.69, p < .0001); effects were greater within location-by-hour than between location-by-hour, but the effect explained slightly less variance in Long-Term Care Crowding Index (LTC-CI) estimates (47.41%) than location alone. Crowding had small, direct, and highly significant correlations with sound and with the engaging subscale for ambiance; a similar, though inverse, correlation was seen with the soothing subscale for ambiance. ----- ----- Conclusions: Crowding fluctuates consistent with routine activities such as meals in long-term care settings. Furthermore, a relationship between crowding and other physical characteristics of the environment was found. The LTC-CI is likely to be more sensitive than simple people counts when seeking to evaluate the effects of crowding on the behavior of elders-particularly those with dementia-in long-term care settings. aging in place.

Attachment in relation to affect regulation and interpersonal functioning among substance use disorder inpatients

Attachment theory has been conceptualised as an affect regulation theory, proposing that attachment is associated with the expression and recognition of emotions as well as interpersonal functioning. Previous research has reported affect regulation difficulties in substance use disorders and addiction has been considered an attachment disorder. However, scarce empirical research exists on the relationship of attachment in relation to affect regulation and interpersonal functioning in those with substance use problems. Thus, the objective of the present study was to investigate potential associations between attachment, negative mood regulation (NMR) expectancies, fear of intimacy and self-differentiation in substance abusers. The revised adult attachment scale (RAAS), the NMR expectancies scale, the fear of intimacy scale and the differentiation of self inventory were administered to a sample of 100 substance use disorder inpatients. Attachment accounted for significant variance in NMR expectancies and was also a strong predictor of fear of intimacy. The predictive utility of attachment also extended to self-differentiation, suggesting that attachment was strongly related to overall self-differentiation score, Emotional reactivity, Emotional cut-off and I position. These findings support attachment theory suggesting that attachment is associated with and predicts affect regulation abilities and difficulties in interpersonal functioning in a sample of substance use disorder inpatients. The inclusion and assessment of attachment appears to be important in the development of treatment programmes for substance abusing individuals.

Computed success rates of various carrier phase integer estimation solutions and their comparison with statistical success rates

The success rate of carrier phase ambiguity resolution (AR) is the probability that the ambiguities are successfully fixed to their correct integer values. In existing works, an exact success rate formula for integer bootstrapping estimator has been used as a sharp lower bound for the integer least squares (ILS) success rate. Rigorous computation of success rate for the more general ILS solutions has been considered difficult, because of complexity of the ILS ambiguity pull-in region and computational load of the integration of the multivariate probability density function. Contributions of this work are twofold. First, the pull-in region mathematically expressed as the vertices of a polyhedron is represented by a multi-dimensional grid, at which the cumulative probability can be integrated with the multivariate normal cumulative density function (mvncdf) available in Matlab. The bivariate case is studied where the pull-region is usually defined as a hexagon and the probability is easily obtained using mvncdf at all the grid points within the convex polygon. Second, the paper compares the computed integer rounding and integer bootstrapping success rates, lower and upper bounds of the ILS success rates to the actual ILS AR success rates obtained from a 24 h GPS data set for a 21 km baseline. The results demonstrate that the upper bound probability of the ILS AR probability given in the existing literatures agrees with the actual ILS success rate well, although the success rate computed with integer bootstrapping method is a quite sharp approximation to the actual ILS success rate. The results also show that variations or uncertainty of the unit–weight variance estimates from epoch to epoch will affect the computed success rates from different methods significantly, thus deserving more attentions in order to obtain useful success probability predictions.

Plantar enthesopathy : thickening of the enthesis is correlated with energy dissipation of the plantar fat pad during walking

Background: The enthesis of the plantar fascia is thought to play an important role in stress dissipation. However, the potential link between entheseal thickening characteristic of enthesopathy and the stress-dissipating properties of the intervening plantar fat pad have not been investigated. Purpose: This study was conducted to identify whether plantar fat pad mechanics explain variance in the thickness of the fascial enthesis in individuals with and without plantar enthesopathy. Study Design: Case-control study; Level of evidence, 3. Methods: The study population consisted of 9 patients with unilateral plantar enthesopathy and 9 asymptomatic, individually matched controls. The thickness of the enthesis of the symptomatic, asymptomatic, and a matched control limb was acquired using high-resolution ultrasound. The compressive strain of the plantar fat pad during walking was estimated from dynamic lateral radiographs acquired with a multifunction fluoroscopy unit. Peak compressive stress was simultaneously acquired via a pressure platform. Principal viscoelastic parameters were estimated from subsequent stress-strain curves. Results: The symptomatic fascial enthesis (6.7 ± 2.0 mm) was significantly thicker than the asymptomatic enthesis (4.2 ± 0.4 mm), which in turn was thicker than the enthesis (3.3 ± 0.4 mm) of control limbs (P < .05). There was no significant difference in the mean thickness, peak stress, peak strain, or secant modulus of the plantar fat pad between limbs. However, the energy dissipated by the fat pad during loading and unloading was significantly lower in the symptomatic limb (0.55 ± 0.17) when compared with asymptomatic (0.69 ± 0.13) and control (0.70 ± 0.09) limbs (P < .05). The sonographic thickness of the enthesis was correlated with the energy dissipation ratio of the plantar fat pad (r = .72, P < .05), but only in the symptomatic limb. Conclusion: The energy-dissipating properties of the plantar fat pad are associated with the sonograpic appearance of the enthesis in symptomatic limbs, providing a previously unidentified link between the mechanical behavior of the plantar fat pad and enthesopathy.

Understanding the factors influencing safe and unsafe motorcycle rider intentions

The increasing popularity of motorcycles in Australia is a significant concern as motorcycle riders represent 15% of all road fatalities and an even greater proportion of serious injuries. This study assessed the psychosocial factors influencing motorcycle riders’ intentions to perform both safe and risky riding behaviours. Using an extended theory of planned behaviour (TPB), motorcycle riders (n = 229) from Queensland, Australia were surveyed to assess their riding attitudes, subjective norm (general and specific), perceived behavioural control (PBC), group norm, self-identity, sensation seeking, and aggression, as well as their intentions, in relation to three safe (e.g., handle my motorcycle skilfully) and three risky (e.g., bend road rules to get through traffic) riding behaviours. Although there was variability in the predictors of intention across the behaviours, results revealed that safer rider intentions were most consistently predicted by PBC, while riskier intentions were predicted by attitudes and sensation seeking. The TPB was able to explain a greater proportion of the variance for intentions to perform risky behaviours. Overall, this study has provided insight into the complexity of factors contributing to rider intentions and suggests that different practical strategies need to be adopted to facilitate safer and reduce risky rider decisions.

The psychological distress of the young driver : a brief report

Objective: To explore the role of psychological distress in the self-reported risky driving of young novice drivers. Design: Cross-sectional online survey of 761 tertiary students aged 17-25 years with an intermediate (Provisional) driving licence who completed Kessler’s Psychological Distress Scale and the Behaviour of Young Novice Drivers Scale. Setting: Queensland, Australia, August-October 2009. Main outcome measures: Psychological distress, risky driving. Results: Regression analyses revealed that psychological distress uniquely explained 8.5% of the variance in young novice’s risky driving, with adolescents experiencing psychological distress also reporting higher levels of risky driving. Psychological distress uniquely explained a significant 6.7% and 9.5% of variance in risky driving for males and females respectively. Conclusions: Medical practitioners treating adolescents who have been injured through risky behaviour need to aware of the potential contribution of psychological distress, whilst mental health professionals working with adolescents experiencing psychological distress need to be aware of this additional source of potential harm. The nature of the causal relationships linking psychological distress and risky driving behaviour are not yet fully understood, indicating a need for further research so that strategies such as screening can be investigated.

A comparison of registered and unregistered organ donors’ perceptions about transplant recipients

Background: We examined whether registered and unregistered donors’ perceptions about transplant recipients’ previous behavior (e.g., substance use) and responsibility for illness differed based on their deceased organ donor registration decisions. ----- ----- ----- Methods: Students and community members from Queensland, Australia were surveyed about their perceptions of transplant recipients.----- ----- ----- Results: Respondents (N = 465) were grouped based on their organ donor registration status to determine if their perceptions about transplant recipients differed. Compared to registered respondents, a higher proportion of unregistered respondents held more negative and less favorable perceptions of recipients. Multivariate analysis of variance confirmed statistically that unregistered respondents evaluated recipients more negatively than registered respondents, F(6,449) = 5.33, p <.001. Unregistered respondents were more likely to view recipients as a smoker, substance user, or alcohol dependent and as undeserving of a transplant, blameworthy, and responsible for their illness. ----- ----- ----- Conclusion: Potential donors’ perceptions of transplant recipients’ behavior and responsibility for illness differ according to their registration status. Future interventions should challenge negative perceptions about recipients’ deservingness and responsibility and promote the perspective that people from all walks of life need transplants in the aim of ultimately encouraging an increase in donor registration.

An examination of the relationship between emotional intelligence, leadership style and perceived leadership outcomes in Australian educational institutions

In the field of leadership studies transformational leadership theory (e.g., Bass, 1985; Avolio, Bass, & Jung, 1995) has received much attention from researchers in recent years (Hughes, Ginnet, & Curphy, 2009; Hunt, 1999). Many previous studies have found that transformational leadership is related to positive outcomes such as the satisfaction, motivation and performance of followers in organisations (Judge & Piccolo, 2004; Lowe, Kroeck, & Sivasubramaniam, 1996), including in educational institutions (Chin, 2007; Leithwoood & Jantzi, 2005). Hence, it is important to explore constructs that may predict leadership style in order to identify potential transformational leaders in leadership assessment and selection procedures. Several researchers have proposed that emotional intelligence (EI) is one construct that may account for hitherto unexplained variance in transformational leadership (Mayer, 2001; Watkin, 2000). Different models of EI exist (e.g., Goleman, 1995, 2001; Bar-On, 1997; Mayer & Salovey, 1997) but momentum is growing for the Mayer and Salovey (1997) model to be considered the most useful (Ashkanasy & Daus, 2005; Daus & Ashkanasy, 2005). Studies in non-educational settings claim to have found that EI is a useful predictor of leadership style and leader effectiveness (Harms & Crede, 2010; Mills, 2009) but there is a paucity of studies which have examined the Mayer and Salovey (1997) model of EI in educational settings. Furthermore, other predictor variables have rarely been controlled in previous studies and only self-ratings of leadership behaviours, rather than multiple ratings, have usually been obtained. Therefore, more research is required in educational settings to answer the question: to what extent is the Mayer and Salovey (1997) model of EI a useful predictor of leadership style and leadership outcomes? This project, set in Australian educational institutions, was designed to move research in the field forward by: using valid and reliable instruments, controlling for other predictors, obtaining an adequately sized sample of real leaders as participants and obtaining multiple ratings of leadership behaviours. Other variables commonly used to predict leadership behaviours (personality factors and general mental ability) were assessed and controlled in the project. Additionally, integrity was included as another potential predictor of leadership behaviours as it has previously been found to be related to transformational leadership (Parry & Proctor-Thomson, 2002). Multiple ratings of leadership behaviours were obtained from each leader and their supervisors, peers and followers. The following valid and reliable psychological tests were used to operationalise the variables of interest: leadership styles and perceived leadership outcomes (Multifactor Leadership Questionnaire, Avolio et al., 1995), EI (Mayer–Salovey–Caruso Emotional Intelligence Test, Mayer, Salovey, & Caruso, 2002), personality factors (The Big Five Inventory, John, Donahue, & Kentle, 1991), general mental ability (Wonderlic Personnel Test-Quicktest, Wonderlic, 2003) and integrity (Integrity Express, Vangent, 2002). A Pilot Study (N = 25 leaders and 75 raters) made a preliminary examination of the relationship between the variables included in the project. Total EI, the experiential area, and the managing emotions and perceiving emotions branches of EI, were found to be related to transformational leadership which indicated that further research was warranted. In the Main Study, 144 leaders and 432 raters were recruited as participants to assess the discriminant validity of the instruments and examine the usefulness of EI as a predictor of leadership style and perceived leadership outcomes. Scores for each leadership scale across the four rating levels (leaders, supervisors, peers and followers) were aggregated with the exception of the management-by-exception active scale of transactional leadership which had an inadequate level of interrater agreement. In the descriptive and measurement component of the Main Study, the instruments were found to demonstrate adequate discriminant validity. The impact of role and gender on leadership style and EI were also examined, and females were found to be more transformational as leaders than males. Females also engaged in more contingent reward (transactional leadership) behaviours than males, whilst males engaged in more passive/avoidant leadership behaviours than females. In the inferential component of the Main Study, multiple regression procedures were used to examine the usefulness of EI as a predictor of leadership style and perceived leadership outcomes. None of the EI branches were found to be related to transformational leadership or the perceived leadership outcomes variables included in the study. Openness, emotional stability (the inverse of neuroticism) and general mental ability (inversely) each predicted a small amount of variance in transformational leadership. Passive/avoidant leadership was inversely predicted by the understanding emotions branch of EI. Overall, EI was not found to be a useful predictor of leadership style and leadership outcomes in the Main Study of this project. Implications for researchers and human resource practitioners are discussed.

Adaptive Bayesian compound designs for dose finding studies

We consider the problem of how to efficiently and safely design dose finding studies. Both current and novel utility functions are explored using Bayesian adaptive design methodology for the estimation of a maximum tolerated dose (MTD). In particular, we explore widely adopted approaches such as the continual reassessment method and minimizing the variance of the estimate of an MTD. New utility functions are constructed in the Bayesian framework and are evaluated against current approaches. To reduce computing time, importance sampling is implemented to re-weight posterior samples thus avoiding the need to draw samples using Markov chain Monte Carlo techniques. Further, as such studies are generally first-in-man, the safety of patients is paramount. We therefore explore methods for the incorporation of safety considerations into utility functions to ensure that only safe and well-predicted doses are administered. The amalgamation of Bayesian methodology, adaptive design and compound utility functions is termed adaptive Bayesian compound design (ABCD). The performance of this amalgamation of methodology is investigated via the simulation of dose finding studies. The paper concludes with a discussion of results and extensions that could be included into our approach.