Age-related changes in perception of movement in driving scenes

Purpose Age-related changes in motion sensitivity have been found to relate to reductions in various indices of driving performance and safety. The aim of this study was to investigate the basis of this relationship in terms of determining which aspects of motion perception are most relevant to driving. Methods Participants included 61 regular drivers (age range 22–87 years). Visual performance was measured binocularly. Measures included visual acuity, contrast sensitivity and motion sensitivity assessed using four different approaches: (1) threshold minimum drift rate for a drifting Gabor patch, (2) Dmin from a random dot display, (3) threshold coherence from a random dot display, and (4) threshold drift rate for a second-order (contrast modulated) sinusoidal grating. Participants then completed the Hazard Perception Test (HPT) in which they were required to identify moving hazards in videos of real driving scenes, and also a Direction of Heading task (DOH) in which they identified deviations from normal lane keeping in brief videos of driving filmed from the interior of a vehicle. Results In bivariate correlation analyses, all motion sensitivity measures significantly declined with age. Motion coherence thresholds, and minimum drift rate threshold for the first-order stimulus (Gabor patch) both significantly predicted HPT performance even after controlling for age, visual acuity and contrast sensitivity. Bootstrap mediation analysis showed that individual differences in DOH accuracy partly explained these relationships, where those individuals with poorer motion sensitivity on the coherence and Gabor tests showed decreased ability to perceive deviations in motion in the driving videos, which related in turn to their ability to detect the moving hazards. Conclusions The ability to detect subtle movements in the driving environment (as determined by the DOH task) may be an important contributor to effective hazard perception, and is associated with age, and an individuals' performance on tests of motion sensitivity. The locus of the processing deficits appears to lie in first-order, rather than second-order motion pathways.

Blur, eye movements and performance on a driving visual recognition slide test

Purpose Optical blur and ageing are known to affect driving performance but their effects on drivers' eye movements are poorly understood. This study examined the effects of optical blur and age on eye movement patterns and performance on the DriveSafe slide recognition test which is purported to predict fitness to drive. Methods Twenty young (27.1 ± 4.6 years) and 20 older (73.3 ± 5.7 years) visually normal drivers performed the DriveSafe under two visual conditions: best-corrected vision and with +2.00 DS blur. The DriveSafe is a Visual Recognition Slide Test that consists of brief presentations of static, real-world driving scenes containing different road users (pedestrians, bicycles and vehicles). Participants reported the types, relative positions and direction of travel of the road users in each image; the score was the number of correctly reported items (maximum score of 128). Eye movements were recorded while participants performed the DriveSafe test using a Tobii TX300 eye tracking system. Results There was a significant main effect of blur on DriveSafe scores (best-corrected: 114.9 vs blur: 93.2; p < 0.001). There was also a significant age and blur interaction on the DriveSafe scores (p < 0.001) such that the young drivers were more negatively affected by blur than the older drivers (reductions of 22% and 13% respectively; p < 0.001): with best-corrected vision, the young drivers performed better than the older drivers (DriveSafe scores: 118.4 vs 111.5; p = 0.001), while with blur, the young drivers performed worse than the older drivers (88.6 vs 95.9; p = 0.009). For the eye movement patterns, blur significantly reduced the number of fixations on road users (best-corrected: 5.1 vs blur: 4.5; p < 0.001), fixation duration on road users (2.0 s vs 1.8 s; p < 0.001) and saccade amplitudes (7.4° vs 6.7°; p < 0.001). A main effect of age on eye movements was also found where older drivers made smaller saccades than the young drivers (6.7° vs 7.4°; p < 0.001). Conclusions Blur reduced DriveSafe scores for both age groups and this effect was greater for the young drivers. The decrease in number of fixations and fixation duration on road users, as well as the reduction in saccade amplitudes under the blurred condition, highlight the difficulty experienced in performing the task in the presence of optical blur, which suggests that uncorrected refractive errors may have a detrimental impact on aspects of driving performance.

Drink and drug driving in Australian young adult users and non-users of illicit stimulants

- Introduction There is limited understanding of how young adults’ driving behaviour varies according to long-term substance involvement. It is possible that regular users of amphetamine-type stimulants (i.e. ecstasy (MDMA) and methamphetamine) may have a greater predisposition to engage in drink/drug driving compared to non-users. We compare offence rates, and self-reported drink/drug driving rates, for stimulant users and non-users in Queensland, and examine contributing factors. - Methods The Natural History Study of Drug Use is a prospective longitudinal study using population screening to recruit a probabilistic sample of amphetamine-type stimulant users and non-users aged 19-23 years. At the 4 ½ year follow-up, consent was obtained to extract data from participants’ Queensland driver records (ATS users: n=217, non-users: n=135). Prediction models were developed of offence rates in stimulant users controlling for factors such as aggression and delinquency. - Results Stimulant users were more likely than non-users to have had a drink-driving offence (8.7% vs. 0.8%, p < 0.001). Further, about 26% of ATS users and 14% of non-users self-reported driving under the influence of alcohol during the last 12 months. Among stimulant users, drink-driving was independently associated with last month high-volume alcohol consumption (Incident Rate Ratio (IRR): 5.70, 95% CI: 2.24-14.52), depression (IRR: 1.28, 95% CI: 1.07-1.52), low income (IRR: 3.57, 95% CI: 1.12-11.38), and male gender (IRR: 5.40, 95% CI: 2.05-14.21). - Conclusions Amphetamine-type stimulant use is associated with increased long-term risk of drink-driving, due to a number of behavioural and social factors. Inter-sectoral approaches which target long-term behaviours may reduce offending rates.

Getting mad may not mean getting even: The influence of drivers' ethical ideologies on driving anger and related behaviour

The current study explored the influence of moral values (measured by ethical ideology) on self-reported driving anger and aggressive driving responses. A convenience sample of drivers aged 17-73 years (n = 280) in Queensland, Australia, completed a self-report survey. Measures included sensation seeking, trait aggression, driving anger, endorsement of aggressive driving responses and ethical ideology (Ethical Position Questionnaire, EPQ). Scores on the two underlying dimensions of the EPQ idealism (highI/lowI) and relativism (highR/lowR) were used to categorise drivers into four ideological groups: Situationists (highI/highR); Absolutists (highI/lowR); Subjectivists (lowI/highR); and Exceptionists (lowI/lowR). Mean aggressive driving scores suggested that exceptionists were significantly more likely to endorse aggressive responses. After accounting for demographic variables, sensation seeking and driving anger, ethical ideological category added significantly, though modestly to the prediction of aggressive driving responses. Patterns in results suggest that those drivers in ideological groups characterised by greater concern to avoid affecting others negatively (i.e. highI, Situationists, Absolutists) may be less likely to endorse aggressive driving responses, even when angry. In contrast, Subjectivists (lowI, HighR), reported the lowest levels of driving anger yet were significantly more likely to endorse aggressive responses. This provides further insight into why high levels of driving anger may not always translate into more aggressive driving.

What are the driving factors influencing the size distribution of airborne synthetic clay particles emitted from a jet milling process?

In the field of workplace air quality, measuring and analyzing the size distribution of airborne particles to identify their sources and apportion their contribution has become widely accepted, however, the driving factors that influence this parameter, particularly for nanoparticles (< 100 nm), have not been thoroughly determined. Identification of driving factors, and in turn, general trends in size distribution of emitted particles would facilitate the prediction of nanoparticles’ emission behavior and significantly contribute to their exposure assessment. In this study, a comprehensive analysis of the particle number size distribution data, with a particular focus on the ultrafine size range of synthetic clay particles emitted from a jet milling machine was conducted using the multi-lognormal fitting method. The results showed relatively high contribution of nanoparticles to the emissions in many of the tested cases, and also, that both surface treatment and feed rate of the machine are significant factors influencing the size distribution of the emitted particles of this size. In particular, applying surface treatments and increasing the machine feed rate have the similar effect of reducing the size of the particles, however, no general trend was found in variations of size distribution across different surface treatments and feed rates. The findings of our study demonstrate that for this process and other activities, where no general trend is found in the size distribution of the emitted airborne particles due to dissimilar effects of the driving factors, each case must be treated separately in terms of workplace exposure assessment and regulations.

Towards the Use of Radar Winds in Numerical Weather Prediction

Numerical weather prediction (NWP) models provide the basis for weather forecasting by simulating the evolution of the atmospheric state. A good forecast requires that the initial state of the atmosphere is known accurately, and that the NWP model is a realistic representation of the atmosphere. Data assimilation methods are used to produce initial conditions for NWP models. The NWP model background field, typically a short-range forecast, is updated with observations in a statistically optimal way. The objective in this thesis has been to develope methods in order to allow data assimilation of Doppler radar radial wind observations. The work has been carried out in the High Resolution Limited Area Model (HIRLAM) 3-dimensional variational data assimilation framework. Observation modelling is a key element in exploiting indirect observations of the model variables. In the radar radial wind observation modelling, the vertical model wind profile is interpolated to the observation location, and the projection of the model wind vector on the radar pulse path is calculated. The vertical broadening of the radar pulse volume, and the bending of the radar pulse path due to atmospheric conditions are taken into account. Radar radial wind observations are modelled within observation errors which consist of instrumental, modelling, and representativeness errors. Systematic and random modelling errors can be minimized by accurate observation modelling. The impact of the random part of the instrumental and representativeness errors can be decreased by calculating spatial averages from the raw observations. Model experiments indicate that the spatial averaging clearly improves the fit of the radial wind observations to the model in terms of observation minus model background (OmB) standard deviation. Monitoring the quality of the observations is an important aspect, especially when a new observation type is introduced into a data assimilation system. Calculating the bias for radial wind observations in a conventional way can result in zero even in case there are systematic differences in the wind speed and/or direction. A bias estimation method designed for this observation type is introduced in the thesis. Doppler radar radial wind observation modelling, together with the bias estimation method, enables the exploitation of the radial wind observations also for NWP model validation. The one-month model experiments performed with the HIRLAM model versions differing only in a surface stress parameterization detail indicate that the use of radar wind observations in NWP model validation is very beneficial.

Landslide Susceptible Locations in Western Ghats: Prediction through openModeller

Many shallow landslides are triggered by heavy rainfall on hill slopes resulting in enormous casualties and huge economic losses in mountainous regions. Hill slope failure usually occurs as soil resistance deteriorates in the presence of the acting stress developed due to a number of reasons such as increased soil moisture content, change in land use causing slope instability, etc. Landslides triggered by rainfall can possibly be foreseen in real time by jointly using rainfall intensity-duration and information related to land surface susceptibility. Terrain analysis applications using spatial data such as aspect, slope, flow direction, compound topographic index, etc. along with information derived from remotely sensed data such as land cover / land use maps permit us to quantify and characterise the physical processes governing the landslide occurrence phenomenon. In this work, the probable landslide prone areas are predicted using two different algorithms – GARP (Genetic Algorithm for Rule-set Prediction) and Support Vector Machine (SVM) in a free and open source software package - openModeller. Several environmental layers such as aspect, digital elevation data, flow accumulation, flow direction, slope, land cover, compound topographic index, and precipitation data were used in modelling. A comparison of the simulated outputs, validated by overlaying the actual landslide occurrence points showed 92% accuracy with GARP and 96% accuracy with SVM in predicting landslide prone areas considering precipitation in the wettest month whereas 91% and 94% accuracy were obtained from GARP and SVM considering precipitation in the wettest quarter of the year.

3D Image Reconstruction From Truncated Helical Cone Beam Projection Data - A Linear Prediction Approach

With the introduction of 2D flat-panel X-ray detectors, 3D image reconstruction using helical cone-beam tomography is fast replacing the conventional 2D reconstruction techniques. In 3D image reconstruction, the source orbit or scanning geometry should satisfy the data sufficiency or completeness condition for exact reconstruction. The helical scan geometry satisfies this condition and hence can give exact reconstruction. The theoretically exact helical cone-beam reconstruction algorithm proposed by Katsevich is a breakthrough and has attracted interest in the 3D reconstruction using helical cone-beam Computed Tomography.In many practical situations, the available projection data is incomplete. One such case is where the detector plane does not completely cover the full extent of the object being imaged in lateral direction resulting in truncated projections. This result in artifacts that mask small features near to the periphery of the ROI when reconstructed using the convolution back projection (CBP) method assuming that the projection data is complete. A number of techniques exist which deal with completion of missing data followed by the CBP reconstruction. In 2D, linear prediction (LP)extrapolation has been shown to be efficient for data completion, involving minimal assumptions on the nature of the data, producing smooth extensions of the missing projection data.In this paper, we propose to extend the LP approach for extrapolating helical cone beam truncated data. The projection on the multi row flat panel detectors has missing columns towards either ends in the lateral direction in truncated data situation. The available data from each detector row is modeled using a linear predictor. The available data is extrapolated and this completed projection data is backprojected using the Katsevich algorithm. Simulation results show the efficacy of the proposed method.

Prediction of Breakout Noise from a Rectangular Duct with Compliant Walls

Breakout noise from HVAC ducts is important at low frequencies, and the coupling between the acoustic waves and the structural waves plays a critical role in the prediction of the transverse transmission loss. This paper describes the analytical calculation of breakout noise by incorporating three-dimensional effects along with the acoustical and structural wave coupling phenomena. The first step in the breakout noise prediction is to calculate the inside duct pressure field and the normal duct wall vibration by using the solution of the governing differential equations in terms of Green's function. The resultant equations are rearranged in terms of impedance and mobility, which results in a compact matrix formulation. The Green's function selected for the current problem is the cavity Green's function with modification of wave number in the longitudinal direction in order to incorporate the terminal impedance. The second step is to calculate the radiated sound power from the compliant duct walls by means of an ``equivalent unfolded plate'' model. The transverse transmission loss from the duct walls is calculated using the ratio of the incident power due to surface source inside the duct to the acoustic power radiated from the compliant duct walls. Analytical results are validated with the FE-BE numerical models.

Prediction of Shallow Landslide prone regions in Undulating Terrains

Genetic Algorithm for Rule-set Prediction (GARP) and Support Vector Machine (SVM) with free and open source software (FOSS) - Open Modeller were used to model the probable landslide occurrence points. Environmental layers such as aspect, digital elevation, flow accumulation, flow direction, slope, land cover, compound topographic index and precipitation have been used in modeling. Simulated output of these techniques is validated with the actual landslide occurrence points, which showed 92% (GARP) and 96% (SVM) accuracy considering precipitation in the wettest month and 91% and 94% accuracy considering precipitation in the wettest quarter of the year.

Computation of turbulent-flow in a square duct - aspects of the secondary flow and its origin

A numerical study of turbulent flow in a straight duct of square cross-section is made. An order-of-magnitude analysis of the 3-D, time-averaged Navier-Stokes equations resulted in a parabolic form of the Navier-Stokes equations. The governing equations, expressed in terms of a new vector-potential formulation, are expanded as a multi-deck structure with each deck characterized by its dominant physical forces. The resulting equations are solved using a finite-element approach with a bicubic element representation on each cross-sectional plane. The numerical integration along the streamwise direction is carried out with finite-difference approximations until a fully-developed state is reached. The computed results agree well with other numerical studies and compare very favorably with the available experimental data. One important outcome of the current investigation is the interpretation analytically that the driving force of the secondary flow in a square duct comes mainly from the second-order terms of the difference in the gradients of the normal and transverse Reynolds stresses in the axial vorticity equation.

Surface roughness noise prediction for silent aircraft experimental design SAX-40

Surface roughness noise is a potentially important contributor to airframe noise. In this paper, noise assessment due to surface roughness is performed for a conceptual Silent Aircraft design SAX-40 by means of a prediction model developed in previous theoretical work and validated experimentally. Estimates of three idealized test cases show that surface roughness could produce a significant noise level above that due to the trailing edge at high frequencies. Roughness height and roughness density are the two most significant parameters influencing surface roughness noise, with roughness height having the dominant effect. The ratio of roughness height to boundary-layer thickness is the relevant non-dimensional parameter and this decreases in the streamwise direction. The candidate surface roughness is selected for SAX-40 to meet an aggressive noise target and keep surface roughness noise at a negligible level. Copyright © 2008 by Yu Liu and Ann P. Dowling.

Cancer classification based on direction-basis-function neural networks

Automatic molecular classification of cancer based on DNA microarray has many advantages over conventional classification based on morphological appearance of the tumor. Using artificial neural networks is a general approach for automatic classification. In this paper, Direction-Basis-Function neuron and Priority-Ordered algorithm are applied to neural networks. And the leukemia gene expression dataset is used as an example to testify the classifier. The result of our method is compared to that of SVM. It shows that our method makes a better performance than SVM.

Low-compressibility and hard materials ReB2 and WB2: Prediction from first-principles study

First-principle calculations are performed to investigate the structural, elastic, and electronic properties of ReB2 and WB2. The calculated equilibrium structural parameters of ReB2 are consistent with the available experimental data. The calculations indicate that WB2 in the P6(3)/mmc space group is more energetically stable under the ambient condition than in the P6/mmm. Based on the calculated bulk modulus, shear modulus of polycrystalline aggregate, ReB2 and WB2 can be regarded as potential candidates of ultra-incompressible and hard materials. Furthermore, the elastic anisotropy is discussed by investigating the elastic stiffness constants. Density of states and electron density analysis unravel the covalent bonding between the transition metal atoms and the boron atoms as the driving force of the high bulk modulus and high shear modulus as well as small Poisson's ratio.

Is inorganic nutrient enrichment a driving force for the formation of red tides? A case study of the dinoflagellate Scrippsiella trochoidea in an embayment

Red tides (high biomass phytoplankton blooms) have frequently occurred in Hong Kong waters, but most red tides occurred in waters which are not very eutrophic. For example, Port Shelter, a semi-enclosed bay in the northeast of Hong Kong, is one of hot spots for red tides. Concentrations of ambient inorganic nutrients (e.g. N, P), are not high enough to form the high biomass of chlorophyll a (chl a) in a red tide when chl a is converted to its particulate organic nutrient (N) (which should equal the inorganic nutrient, N). When a red tide of the dinoflagellate Scrippsiella trochoidea occurred in the bay, we found that the red tide patch along the shore had a high cell density of 15,000 cells ml(-1), and high chl a (56 mu g l(-1)), and pH reached 8.6 at the surface (8.2 at the bottom), indicating active photosynthesis in situ. Ambient inorganic nutrients (NO3, PO4, SiO4, and NH4) were all low in the waters and deep waters surrounding the red tide patch, suggesting that the nutrients were not high enough to support the high chl a >50 mu g l(-1) in the red tide. Nutrient addition experiments showed that the addition of all of the inorganic nutrients to a non-red-tide water sample containing low concentrations of Scrippsiella trochoidea did not produce cell density of Scrippsiella trochoidea as high as in the red tide patch, suggesting that nutrients were not an initializing factor for this red tide. During the incubation of the red tide water sample without any nutrient addition, the phytoplankton biomass decreased gradually over 9 days. However, with a N addition, the phytoplankton biomass increased steadily until day 7, which suggested that nitrogen addition was able to sustain the high biomass of the red tide for a week with and without nutrients. In contrast, the red tide in the bay disappeared on the sampling day when the wind direction changed. These results indicated that initiation, maintenance and disappearance of the dinoflagellate Scrippsiella trochoidea red tide in the bay were not directly driven by changes in nutrients. Therefore, how nutrients are linked to the formation of red tides in coastal waters need to be further examined, particularly in relation to dissolved organic nutrients. (C) 2008 Elsevier B.V. All rights reserved.