Risky driving habits and motor vehicle driver injury

Risky driving is an important cause of motor vehicle injury, but there is a lack of good epidemiological data in this field, particularly data comparing risky driving in younger drivers to those of other age groups. We examined the relationship between risky driving habits, prior traffic convictions and motor vehicle injury using cross-sectional data amongst 21,893 individuals in New Zealand, including 8029 who were aged 16–24 years. Those who reported frequently racing a motor vehicle for excitement or driving at 20 km/h or more over the speed limit, and those who had received traffic convictions over the past 12 months, were between two and four times more likely to have been injured while driving over the same time period. Driving unlicensed was a risk factor for older but not younger drivers, and driving at 20 km/h or more above the speed limits was a stronger risk factor for younger (<25 years) than older drivers. These results confirm the need for interventions targeting risky driving and suggest that different strategies may be required for different high-risk groups.

The feasibility of a sustainable energy, driver-only electric commuter vehicle for New Zealand

This paper investigates whether low technology driver-only, battery electric commuter vehicles are feasible for New Zealand. Personal passenger transport faces several challenges in the coming decades: depletion of cheap oil reserves, increasing congestion, localised pollution, the need for reduced carbon emissions and the long term goal of sustainability. One way of solving some of these problems could be to introduce low cost, comfortable, energy efficient, driver-only electric vehicles. These would still give the driver a weatherproof, safe and comfortable means of commuting, but at a fraction of the energy and running costs of conventional petrol/diesel cars. To help assess their viability, the performance and energy use of the E-POD electric commuter vehicle is used as a benchmark. The work shows that such a vehicle could be made cheaply, using readily available technology with a range of 180km and a top speed of over 90km/h. The chassis could be made from natural fibre composite materials that might reduce significantly the embedded energy required for its manufacture. The electricity taken from the grid to charge the batteries could be replaced by electricity generated from grid connected photovoltaic panels mounted on the garage roof of the vehicle owner.

Driver recognition based on dynamic handgrip pattern on steeling wheel

This paper proposes a novel biometric authentication method based on the recognition of drivers' dynamic handgrip on steering wheel. A pressure sensitive mat mounted on a steering wheel is employed to collect handgrip data exerted by the hands of drivers who intend to start the vehicle. Then, the likelihood-ratio-based classifier is designed to distinguish rightful driver of a car after analyzing their inherent dynamic features of grasping. The experimental results obtained in this study show that mean acceptance rates of 85.4% for the trained subjects and mean rejection rates of 82.65% for the un-trained ones are achieved by the classifier in the two batches of testing. It can be concluded that the driver verification approach based on dynamic handgrip recognition on steering wheel is a promising biometric technology and will be further explored in the near future in smart car design.

Driver verification based on handgrip recognition on steering wheel

This paper presents a novel driver verification algorithm based on the recognition of handgrip patterns on steering wheel. A pressure sensitive mat mounted on a steering wheel is employed to collect a series of pressure images exerted by the hands of the drivers who intend to start the vehicle. Then, feature extraction from those images is carried out through two major steps: Quad-Tree-based multi-resolution decomposition on the images and Principle Component Analysis (PCA)-based dimension reduction, followed by implementing a likelihood-ratio classifier to distinguish drivers into known or unknown ones. The experimental results obtained in this study show that the mean acceptance rates of 78.15% and 78.22% for the trained subjects and the mean rejection rates of 93.92% and 90.93% to the un-trained ones are achieved in two trials, respectively. It can be concluded that the driver verification approach based on the handgrip recognition on steering wheel is promising and will be further explored in the near future.

Climate as a driver of population variability in breeding Gentoo Penguins (Pygoscelis papua) at the Falkland Islands

Detecting and predicting how populations respond to environmental variability are eminent challenges in conservation research and management. This is particularly true for wildlife populations at high latitudes, many of which demonstrate changes in popula

The relationship between excessive daytime sleepiness and depressive and anxiety disorders in women

Objective: Excessive daytime sleepiness (EDS) is a common clinical symptom that affects women more than men. However, the association of excessive sleepiness with depressive and anxiety disorders in the broader population is unclear. The aim of this study was, therefore, to examine the association between excessive daytime sleepiness as measured by the Epworth Sleepiness Scale, and depressive and anxiety disorders in a population-based sample of women.

Methods: Using the Structured Clinical Interview for DSM-IV Disorders (Non-Patient) (SCID-I/NP), 944 women aged 20–97 years (median 49 years, IQR 33–65 years) were assessed for depressive and anxiety disorders as part of the Geelong Osteoporosis Study. EDS was assessed using the Epworth Sleepiness Scale (ESS, cut-off > 10). Lifestyle factors were documented by self-report, height and weight were measured, and socioeconomic status categorised according to the Index of Relative Socio-Economic Advantage and Disadvantage.

Results: Overall, 125 (13.2%) of the women were identified with EDS. EDS was associated with an increased likelihood for both current (OR = 2.11, 95% CI 1.10–4.06) and lifetime history (OR = 1.95, 95% CI 1.28–2.97) of depressive disorders, but not anxiety disorders, independent of age and alcohol consumption. These findings were not explained by antidepressant or sedative use, body mass index, physical activity, smoking, or socioeconomic status.

Conclusions: These results suggest that excessive daytime sleepiness is associated with current and lifetime depressive, but not anxiety disorders. Clinically, this highlights the need to take into account the possible bidirectional relationship between depressive disorders and excessive sleepiness when assessing mental health issues in patients with EDS.

Sitting behaviour-based pattern recognition for predicting driver fatigue

The proposed approach based on physiological characteristics of sitting behaviours and sophisticated machine learning techniques would enable an effective and practical solution to driver fatigue prognosis since it is insensitive to the illumination of driving environment, non-obtrusive to driver, without violating driver’s privacy, more acceptable by drivers.

Excessive daytime sleepiness and body composition: a population-based study of adults

Excessive daytime sleepiness (EDS) is often associated with increased adiposity, particularly when assessed in the context of samples of sleep-disordered patients; however, it is unclear if this relationship is sustained among non-clinical, population-based cohorts. This study aimed to investigate the relationship between EDS and a number of body composition markers among a population-based sample of men and women.

Excessive daytime sleepiness and metabolic syndrome: a cross-sectional study

Excessive daytime sleepiness (EDS) has been associated with singular independent symptoms of metabolic syndrome, such as insulin resistance and diabetes. The aim of this study was to assess whether this relationship is sustained among individuals who meet criteria for the whole syndrome.

Enabling construction innovation : The role of a no-blame culture as a collaboration behavioural driver in project alliances

A no-blame culture is widely accepted as a collaboration driver yet we see surprisingly scant literature on the theoretical underpinnings for the construction and project management context. A no-blame culture in project alliances, as conducted in Australasia, promotes innovative thinking in action. Innovation is dependent upon collaboration and true collaboration is inextricably linked with behavioural drivers. Foremost of these is a culture of openness and willingness to share the pain and gain from experimentation, one that requires that collaborators be protected from the threat of being blamed and held accountable for experimental failure. The Australasian project alliance procurement form has a unique 'no-blame' behavioural contract clause that can result in the type of breakthrough thinking crucial in developing a collaborative culture where innovation can evolve through a process of trial and error. © 2014 Taylor & Francis.

Excessive daytime sleepiness and falls among older men and women: cross-sectional examination of a population-based sample

Background: Excessive daytime sleepiness (EDS) has been associated with an increased risk for falls among clinical samples of older adults. However, there is little detailed information among population-representative samples. The current study aimed to assess the relationship between EDS and falls among a cohort of population-based older adults. Methods: This study assessed 367 women aged 60-93years (median 72, interquartile range 65-79) and 451 men aged 60-92years (median 73, interquartile range 66-80) who participated in the Geelong Osteoporosis Study between the years 2001 and 2008. Falls during the prior year were documented via self-report, and for men, falls risk score was obtained using an Elderly Fall Screening Test (EFST). Sleepiness was assessed using the Epworth Sleepiness Scale (ESS), and scores of≥10 indicated EDS. Differences among those with and without EDS in regard to falls were tested using logistic regression models. Results: Among women, 50 (13.6 %) individuals reported EDS. Women with EDS were more likely to report a fall, and were more likely to report the fall occurring outside. EDS was similarly associated with an increased risk of a fall following adjustment for use of a walking aid, cases of nocturia and antidepressant medication use (adjusted OR∈=∈2.54, 95 % CI 1.24-5.21). Multivariate modelling revealed antidepressant use (current) as an effect modifier (p∈<∈.001 for the interaction term). After stratifying the data by antidepressant medication use, the association between EDS and falls was sustained following adjustment for nocturia among antidepressant non-users (adjusted OR∈=∈2.63, 95 % CI 1.31-5.30). Among men, 72 (16.0 %) individuals reported EDS. No differences were detected for men with and without EDS in regard to reported falls, and a trend towards significance was noted between EDS and a high falls risk as assessed by the EFST (p∈=∈0.06), however, age explained this relationship (age adjusted OR∈=∈2.20, 95 % CI 1.03-1.10). Conclusions: For women, EDS is independently associated with at least one fall during the previous year, and this is more likely to occur whilst located outside. Amelioration of EDS may assist in improving functional outcomes among these individuals by reducing the risk for falls.