Predicting effects of monotony on driver’s vigilance

Monotony has been identified as a contributing factor to road crashes. Drivers’ ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks, such as driving on Australian rural roads, many of which are monotonous by nature. Highway design in particular attempts to reduce the driver’s task to a merely lane-keeping one. Such a task provides little stimulation and is monotonous, thus affecting the driver’s attention which is no longer directed towards the road. Inattention contributes to crashes, especially for professional drivers. Monotony has been studied mainly from the endogenous perspective (for instance through sleep deprivation) without taking into account the influence of the task itself (repetitiveness) or the surrounding environment. The aim and novelty of this thesis is to develop a methodology (mathematical framework) able to predict driver lapses of vigilance under monotonous environments in real time, using endogenous and exogenous data collected from the driver, the vehicle and the environment. Existing approaches have tended to neglect the specificity of task monotony, leaving the question of the existence of a “monotonous state” unanswered. Furthermore the issue of detecting vigilance decrement before it occurs (predictions) has not been investigated in the literature, let alone in real time. A multidisciplinary approach is necessary to explain how vigilance evolves in monotonous conditions. Such an approach needs to draw on psychology, physiology, road safety, computer science and mathematics. The systemic approach proposed in this study is unique with its predictive dimension and allows us to define, in real time, the impacts of monotony on the driver’s ability to drive. Such methodology is based on mathematical models integrating data available in vehicles to the vigilance state of the driver during a monotonous driving task in various environments. The model integrates different data measuring driver’s endogenous and exogenous factors (related to the driver, the vehicle and the surrounding environment). Electroencephalography (EEG) is used to measure driver vigilance since it has been shown to be the most reliable and real time methodology to assess vigilance level. There are a variety of mathematical models suitable to provide a framework for predictions however, to find the most accurate model, a collection of mathematical models were trained in this thesis and the most reliable was found. The methodology developed in this research is first applied to a theoretically sound measure of sustained attention called Sustained Attention Response to Task (SART) as adapted by Michael (2010), Michael and Meuter (2006, 2007). This experiment induced impairments due to monotony during a vigilance task. Analyses performed in this thesis confirm and extend findings from Michael (2010) that monotony leads to an important vigilance impairment independent of fatigue. This thesis is also the first to show that monotony changes the dynamics of vigilance evolution and tends to create a “monotonous state” characterised by reduced vigilance. Personality traits such as being a low sensation seeker can mitigate this vigilance decrement. It is also evident that lapses in vigilance can be predicted accurately with Bayesian modelling and Neural Networks. This framework was then applied to the driving task by designing a simulated monotonous driving task. The design of such task requires multidisciplinary knowledge and involved psychologist Rebecca Michael. Monotony was varied through both the road design and the road environment variables. This experiment demonstrated that road monotony can lead to driving impairment. Particularly monotonous road scenery was shown to have the most impact compared to monotonous road design. Next, this study identified a variety of surrogate measures that are correlated with vigilance levels obtained from the EEG. Such vigilance states can be predicted with these surrogate measures. This means that vigilance decrement can be detected in a car without the use of an EEG device. Amongst the different mathematical models tested in this thesis, only Neural Networks predicted the vigilance levels accurately. The results of both these experiments provide valuable information about the methodology to predict vigilance decrement. Such an issue is quite complex and requires modelling that can adapt to highly inter-individual differences. Only Neural Networks proved accurate in both studies, suggesting that these models are the most likely to be accurate when used on real roads or for further research on vigilance modelling. This research provides a better understanding of the driving task under monotonous conditions. Results demonstrate that mathematical modelling can be used to determine the driver’s vigilance state when driving using surrogate measures identified during this study. This research has opened up avenues for future research and could result in the development of an in-vehicle device predicting driver vigilance decrement. Such a device could contribute to a reduction in crashes and therefore improve road safety.

Effect of rain on travel demand and traffic accidents

This paper studies the effect of rain on travel demand measured on the Tokyo Metropolitan Expressway (MEX). Rainfall data monitored by the Japan Meteorological Agency's meso-scale network of weather stations are used. This study found that travel demand decreases during rainy days and, in particular, larger reductions occur over the weekend. The effect of rainfall on the number of accidents recorded on 10 routes on the MEX is also analysed. Statistical testing shows that the average frequency of accidents, during periods of rainfall, is significantly different from the average frequency at other times.

Response of cells on surface-induced nanopatterns: Fibroblasts and mesenchymal progenitor cells

Ultrathin films of a poly(styrene)-block-poly(2-vinylpyrindine) diblock copolymer (PS-b-P2VP) and poly(styrene)-block-poly(4-vinylpyrindine) diblock copolymer (PS-b-P4VP) were used to form surface-induced nanopattern (SINPAT) on mica. Surface interaction controlled microphase separation led to the formation of chemically heterogeneous surface nanopatterns on dry ultrathin films. Two distinct nanopatterned surfaces, namely, wormlike and dotlike patterns, were used to investigate the influence of topography in the nanometer range on cell adhesion, proliferation, and migration. Atomic force microscopy was used to confirm that SINPAT was stable under cell culture conditions. Fibroblasts and mesenchymal progenitor cells were cultured on the nanopatterned surfaces. Phase contrast and confocal laser microscopy showed that fibroblasts and mesenchymal progenitor cells preferred the densely spaced wormlike patterns. Atomic force microscopy showed that the cells remodelled the extracellular matrix differently as they migrate over the two distinctly different nanopatterns

Investigating the effects of preinduction on human adipose-derived precursor cells in an athymic rat model

The osteogenic potential of human adipose-derived precursor cells seeded on medical-grade polycaprolactone-tricalcium phosphate scaffolds was investigated in this in vivo study. Three study groups were investigated: (1) induced—stimulated with osteogenic factors only after seeding into scaffold; (2) preinduced—induced for 2 weeks before seeding into scaffolds; and (3) uninduced—cells without any introduced induction. For all groups, scaffolds were implanted subcutaneously into the dorsum of athymic rats. The scaffold/cell constructs were harvested at the end of 6 or 12 weeks and analyzed for osteogenesis. Gross morphological examination using scanning electron microscopy indicated good integration of host tissue with scaffold/cell constructs and extensive tissue infiltration into the scaffold interior. Alizarin Red histology and immunostaining showed a heightened level of mineralization and an increase in osteonectin, osteopontin, and collagen type I protein expression in both the induced and preinduced groups compared with the uninduced groups. However, no significant differences were observed in these indicators when compared between the induced and preinduced groups.

Modeling crash types: New insights into the effects of covariates on crashes at rural intersections

Many studies focused on the development of crash prediction models have resulted in aggregate crash prediction models to quantify the safety effects of geometric, traffic, and environmental factors on the expected number of total, fatal, injury, and/or property damage crashes at specific locations. Crash prediction models focused on predicting different crash types, however, have rarely been developed. Crash type models are useful for at least three reasons. The first is motivated by the need to identify sites that are high risk with respect to specific crash types but that may not be revealed through crash totals. Second, countermeasures are likely to affect only a subset of all crashes—usually called target crashes—and so examination of crash types will lead to improved ability to identify effective countermeasures. Finally, there is a priori reason to believe that different crash types (e.g., rear-end, angle, etc.) are associated with road geometry, the environment, and traffic variables in different ways and as a result justify the estimation of individual predictive models. The objectives of this paper are to (1) demonstrate that different crash types are associated to predictor variables in different ways (as theorized) and (2) show that estimation of crash type models may lead to greater insights regarding crash occurrence and countermeasure effectiveness. This paper first describes the estimation results of crash prediction models for angle, head-on, rear-end, sideswipe (same direction and opposite direction), and pedestrian-involved crash types. Serving as a basis for comparison, a crash prediction model is estimated for total crashes. Based on 837 motor vehicle crashes collected on two-lane rural intersections in the state of Georgia, six prediction models are estimated resulting in two Poisson (P) models and four NB (NB) models. The analysis reveals that factors such as the annual average daily traffic, the presence of turning lanes, and the number of driveways have a positive association with each type of crash, whereas median widths and the presence of lighting are negatively associated. For the best fitting models covariates are related to crash types in different ways, suggesting that crash types are associated with different precrash conditions and that modeling total crash frequency may not be helpful for identifying specific countermeasures.

A new method to quantify the application thickness of sunscreen on skin

Proper application of sunscreen is essential as an effective public health strategy for skin cancer prevention. Insufficient application is common among sunbathers, results in decreased sun protection and may therefore lead to increased UV damage of the skin. However, no objective measure of sunscreen application thickness (SAT) is currently available for field-based use. We present a method to detect SAT on human skin for determining the amount of sunscreen applied and thus enabling comparisons to manufacturer recommendations. Using a skin swabbing method and subsequent spectrophotometric analysis, we were able to determine SAT on human skin. A swabbing method was used to derive SAT on skin (in mg sunscreen per cm2 of skin area) through the concentration–absorption relationship of sunscreen determined in laboratory experiments. Analysis differentiated SATs between 0.25 and 4 mg cm−2 and showed a small but significant decrease in concentration over time postapplication. A field study was performed, in which the heterogeneity of sunscreen application could be investigated. The proposed method is a low cost, noninvasive method for the determination of SAT on skin and it can be used as a valid tool in field- and population-based studies.

Analysis of the effect of negation on information retrieval of medical data

Most information retrieval (IR) models treat the presence of a term within a document as an indication that the document is somehow "about" that term, they do not take into account when a term might be explicitly negated. Medical data, by its nature, contains a high frequency of negated terms - e.g. "review of systems showed no chest pain or shortness of breath". This papers presents a study of the effects of negation on information retrieval. We present a number of experiments to determine whether negation has a significant negative affect on IR performance and whether language models that take negation into account might improve performance. We use a collection of real medical records as our test corpus. Our findings are that negation has some affect on system performance, but this will likely be confined to domains such as medical data where negation is prevalent.

Assessing the impact of refactoring on security-critical object-oriented designs

Refactoring focuses on improving the reusability, maintainability and performance of programs. However, the impact of refactoring on the security of a given program has received little attention. In this work, we focus on the design of object-oriented applications and use metrics to assess the impact of a number of standard refactoring rules on their security by evaluating the metrics before and after refactoring. This assessment tells us which refactoring steps can increase the security level of a given program from the point of view of potential information flow, allowing application designers to improve their system’s security at an early stage.

Out of touch? On the lack of emotional support over the mobile phone

Findings from an Australian case study of adult women expose general, light and basic use of mobile phones. Participants used their mobile phone mainly for coordination and to a lesser extent for practicing intrinsic interactions motivated by emotional support purposes. This paper focuses on social and emotional support over the mobile phone. Though crucial to individuals, emotional support seems to be a neglected area of research among mobile communication studies, all the more so when focusing on adult women. This study addresses this literature gap. The empirical findings are based on a case study of 26 women over 35 years of age residing in one coastal Australian town. The research design included a combination of quantitative and qualitative methods. This paper examines the communication methods adult women use for social and emotional support, and analyses reasons and social implications of this limited intrinsic communication use pattern over the mobile phone.

The impact of socialisation on graduates’ public service motivation : a mixed method study

There is a renaissance of interest in public service motivation in public management research. Moynnihan and Pandey (2007) assert that public service motivation (PSM) has significant practical relevance as it deals with the relationship between motivation and the public interest. There is a need to explore employee needs generated by public service motivation in order to attract and retain a high calibre cadre of public servants (Gabris & Simo, 1995). Such exploration is particularly important beyond the American context which has dominated the literature to date (Taylor, 2007; Vandenabeele, Scheepers, & Hondeghem, 2006; Vandenabeele & Van de Walle, 2008).

Effect of acupressure on thirst in hemodialysis patients

Background: Thirst and dry mouth are common among hemodialysis (HD) patients. This paper reports a study to evaluate the impact of an acupressure program on HD patients’ thirst and salivary flow rates. Methods: The acupressure program included placebo, followed by true acupressure each applied for 4 weeks. Twenty-eight patients (mean age 57.6, SD = 16.13 years) first received a sticker as placebo acupressure at two acupoints CV23 and TE17 three times a week for 4 weeks, and then received true acupressure in the same area for the next 4 weeks. Salivary flow rate and thirst intensity were measured at baseline, during and after treatment completion for both the placebo and true acupressure program. Results: The true acupressure program was associated with significantly increased salivary flow rate (0.09 ± 0.08 ml/min at baseline to 0.12 ± 0.08 ml/min after treatments completion, p = 0.04). The mean thirst intensity also improved from 4.21 ± 2.66 at baseline to 2.43 ± 2.32 (p = 0.008) after treatment completion in HD patients. There was no statistically significant difference in pre-post program salivary flow rate; however, significant improvement in thirst intensity scores was observed (p = 0.009) in the placebo acupressure program. Conclusion: This study provides preliminary evidence that acupressure may be effective in improving salivary flow rates and thirst intensity.

The effect of metamictization on the Raman spectroscopy of the uranyl titanate mineral davidite (La,Ce)(Y,U,Fe2+)(Ti,Fe3+)20(O,OH)38

Raman spectra of the uranyl titanate mineral davidite-(La) (La,Ce)(Y,U,Fe2+)(Ti,Fe3+)20(O,OH)38 were analysed and related to the mineral structure. Observed bands are attributed to the TiO and (UO2)2+ stretching and bending vibrations, U-OH bending vibrations, H2O and (OH)- stretching, bending and libration modes. U-O bond lengths in uranyls and O-H…O bond lengths are calculated from the wavenumbers assigned to the stretching vibrations. Raman bands of davidite-(La) are in harmony with those of the uranyl oxyhydroxides. The mineral davidite-(La) is metamict as is evidenced by the intensity of the UO stretching and bending modes being of lower intensity than expected and with bands that are significantly broader.