Influence of road traffic environment and mobile phone distraction on the speed selection behaviour of young drivers

Travel speed is one of the most critical parameters for road safety; the evidence suggests that increased vehicle speed is associated with higher crash risk and injury severity. Both naturalistic and simulator studies have reported that drivers distracted by a mobile phone select a lower driving speed. Speed decrements have been argued to be a risk compensatory behaviour of distracted drivers. Nonetheless, the extent and circumstances of the speed change among distracted drivers are still not known very well. As such, the primary objective of this study was to investigate patterns of speed variation in relation to contextual factors and distraction. Using the CARRS-Q high-fidelity Advanced Driving Simulator, the speed selection behaviour of 32 drivers aged 18-26 years was examined in two phone conditions: baseline (no phone conversation) and handheld phone operation. The simulator driving route contained five different types of road traffic complexities, including one road section with a horizontal S curve, one horizontal S curve with adjacent traffic, one straight segment of suburban road without traffic, one straight segment of suburban road with traffic interactions, and one road segment in a city environment. Speed deviations from the posted speed limit were analysed using Ward’s Hierarchical Clustering method to identify the effects of road traffic environment and cognitive distraction. The speed deviations along curved road sections formed two different clusters for the two phone conditions, implying that distracted drivers adopt a different strategy for selecting driving speed in a complex driving situation. In particular, distracted drivers selected a lower speed while driving along a horizontal curve. The speed deviation along the city road segment and other straight road segments grouped into a different cluster, and the deviations were not significantly different across phone conditions, suggesting a negligible effect of distraction on speed selection along these road sections. Future research should focus on developing a risk compensation model to explain the relationship between road traffic complexity and distraction.

Automated topometric graph generation from floor plan analysis

The world is rich with information such as signage and maps to assist humans to navigate. We present a method to extract topological spatial information from a generic bitmap floor plan and build a topometric graph that can be used by a mobile robot for tasks such as path planning and guided exploration. The algorithm first detects and extracts text in an image of the floor plan. Using the locations of the extracted text, flood fill is used to find the rooms and hallways. Doors are found by matching SURF features and these form the connections between rooms, which are the edges of the topological graph. Our system is able to automatically detect doors and differentiate between hallways and rooms, which is important for effective navigation. We show that our method can extract a topometric graph from a floor plan and is robust against ambiguous cases most commonly seen in floor plans including elevators and stairwells.

Bias reduction using stochastic approximation

The paper studies stochastic approximation as a technique for bias reduction. The proposed method does not require approximating the bias explicitly, nor does it rely on having independent identically distributed (i.i.d.) data. The method always removes the leading bias term, under very mild conditions, as long as auxiliary samples from distributions with given parameters are available. Expectation and variance of the bias-corrected estimate are given. Examples in sequential clinical trials (non-i.i.d. case), curved exponential models (i.i.d. case) and length-biased sampling (where the estimates are inconsistent) are used to illustrate the applications of the proposed method and its small sample properties.

A thermometer for interdependence: Exploring patterns of interdependence using networks of affordances

Interdependence is a central concept in systems and organizations, yet our methods for measuring it are not well developed. Here, we report on a novel method for transforming digital trace data into networks of events that can be used to visualize and measure interdependence. The edges in the network represent sequential flow and the vertices represent actors, actions and artifacts. We refer to this representation as an affordance network. As with conventional approaches such as process mining, our method uses input from a stream of time-stamped occurrences, but the representation is simpler and more appropriate for exploration and theory building. As digital trace data becomes more widely available, this method may become more useful in information systems research and practice. Like a thermometer, it helps us measure a basic property of a system that would otherwise be difficult to see.

Steel–concrete–steel sandwich system in Arctic offshore structure: Materials, experiments, and design

The gravity based structure (GBS) with external Steel–Concrete–Steel (SCS) sandwich ice-resistant wall has been developed for the Arctic oil and gas drilling. This paper firstly reported the experimental studies on the mechanical properties of steel and concretes under Arctic low temperature. With the test data, design equations were developed to incorporate the influences of the low temperature on these mechanical properties. Two types of Arctic GBS structure with flower-conical SCS sandwich shell type and plate type of ice-resistant wall have been developed for the Arctic offshore structure. Besides the studies on the materials, two SCS sandwich prototype shells and plates were, respectively, prepared and tested under patch loading that simulated the localized ice-contact pressure. The structural behaviors of the SCS sandwich structure under patch loading were reported and discussions were made on the influences of different parameters on the structural behavior of the structure. Analytical models were developed to predict the punching shear resistances of the SCS sandwich structure through modifying the code provisions. The accuracies of the developed analytical models were checked through validations against 27 tests in the literature. Corresponding design procedures on resistances of SCS sandwich structure were recommended based on these discussions and validations.

DFT study of electronic and optical properties of anatase titanium dioxide tuned by nitrogen and lithium co-doping

The electronic and optical properties of anatase titanium dioxide (TiO2), co-doped by nitrogen (N) and lithium (Li), have been investigated by density functional theory plus Hubbard correction term U, namely DFT+U. It is found that Li-dopants can effectively balance the net charges brought by N-dopants and shift the local state to the top of valence band. Depending on the distribution of dopants, the adsorption edges of TiO2 may be red- or blue-shifted, being consistent with recent experimental observations.

Biometry of eyes in type 1 diabetes

This is a comprehensive study of a large range of biometric and optical parameters in people with type 1 diabetes. The parameters of 74 people with type 1 diabetes and an age matched control group were assessed. Most of the people with diabetes had low levels of neuropathy, retinopathy and nephropathy. Marginal or no significant differences were found between groups for corneal shape, corneal thickness, pupil size, and pupil decentrations. Relative to the control group, the diabetes group demonstrated smaller anterior chamber depths, more curved lenses, greater lens thickness and lower lens equivalent refractive index. While the optics of diabetic eyes make them appear as older eyes than those of people of the same age without diabetes, the differences did not increase significantly with age. Age-related changes in the optics of the eyes of people with diabetes need not be accelerated if the diabetes is well controlled.

Bayesian model comparison in cosmology with Population Monte Carlo

We use Bayesian model selection techniques to test extensions of the standard flat LambdaCDM paradigm. Dark-energy and curvature scenarios, and primordial perturbation models are considered. To that end, we calculate the Bayesian evidence in favour of each model using Population Monte Carlo (PMC), a new adaptive sampling technique which was recently applied in a cosmological context. The Bayesian evidence is immediately available from the PMC sample used for parameter estimation without further computational effort, and it comes with an associated error evaluation. Besides, it provides an unbiased estimator of the evidence after any fixed number of iterations and it is naturally parallelizable, in contrast with MCMC and nested sampling methods. By comparison with analytical predictions for simulated data, we show that our results obtained with PMC are reliable and robust. The variability in the evidence evaluation and the stability for various cases are estimated both from simulations and from data. For the cases we consider, the log-evidence is calculated with a precision of better than 0.08. Using a combined set of recent CMB, SNIa and BAO data, we find inconclusive evidence between flat LambdaCDM and simple dark-energy models. A curved Universe is moderately to strongly disfavoured with respect to a flat cosmology. Using physically well-motivated priors within the slow-roll approximation of inflation, we find a weak preference for a running spectral index. A Harrison-Zel'dovich spectrum is weakly disfavoured. With the current data, tensor modes are not detected; the large prior volume on the tensor-to-scalar ratio r results in moderate evidence in favour of r=0.

Influences of Allee effects in the spreading of malignant tumours

A recent study by Korolev et al. [Nat. Rev. Cancer, 14:371–379, 2014] evidences that the Allee effect—in its strong form, the requirement of a minimum density for cell growth—is important in the spreading of cancerous tumours. We present one of the first mathematical models of tumour invasion that incorporates the Allee effect. Based on analysis of the existence of travelling wave solutions to this model, we argue that it is an improvement on previous models of its kind. We show that, with the strong Allee effect, the model admits biologically relevant travelling wave solutions, with well-defined edges. Furthermore, we uncover an experimentally observed biphasic relationship between the invasion speed of the tumour and the background extracellular matrix density.

Structural analysis of the roles of influenza A virus membrane-associated proteins in assembly and morphology

The assembly of influenza A virus at the plasma membrane of infected cells leads to release of enveloped virions that are typically round in tissue culture-adapted strains but filamentous in strains isolated from patients. The viral proteins hemagglutinin (HA), neuraminidase (NA), matrix protein 1 (M1), and M2 ion channel all contribute to virus assembly. When expressed individually or in combination in cells, they can all, under certain conditions, mediate release of membrane-enveloped particles, but their relative roles in virus assembly, release, and morphology remain unclear. To investigate these roles, we produced membrane-enveloped particles by plasmid-derived expression of combinations of HA, NA, and M proteins (M1 and M2) or by infection with influenza A virus. We monitored particle release, particle morphology, and plasma membrane morphology by using biochemical methods, electron microscopy, electron tomography, and cryo-electron tomography. Our data suggest that HA, NA, or HANA (HA plus NA) expression leads to particle release through nonspecific induction of membrane curvature. In contrast, coexpression with the M proteins clusters the glycoproteins into filamentous membrane protrusions, which can be released as particles by formation of a constricted neck at the base. HA and NA are preferentially distributed to differently curved membranes within these particles. Both the budding intermediates and the released particles are morphologically similar to those produced during infection with influenza A virus. Together, our data provide new insights into influenza virus assembly and show that the M segment together with either of the glycoproteins is the minimal requirement to assemble and release membrane-enveloped particles that are truly virus-like.