Studying the effects of in-vehicle information systems on driver visual behaviour – implications for design

In-vehicle information systems (IVIS) are a common feature in modern vehicles. The interaction of drivers with IVIS when driving must be considered to minimise distraction whilst maintaining the benefits provided. This research investigates the glance behaviours of drivers, assessed from video data, when using two functions – a personal navigation device (study 1) and a green driving advisory device (study 2). The main focus was to establish the number of glances of 2 seconds or more to the IVIS and relate this to driver safety (as stipulated in new guidelines for use of IVIS proposed by NHTSA). In study 1, the percentage of eyes- off-road time for drivers was much greater in the experimental (with device) condition compared to the baseline condition (14.3% compared to 6.7%) but, whilst glances to the personal navigation device accounted for the majority of the increase, there were very few which exceeded 2 seconds. Drivers in study 2 spent on average 4.3% of their time looking at the system, at an average of 0.43 seconds per glance; no glances exceeded 2 seconds. The research showed that ordinary use of IVIS (excluding manual interaction) does not lead to driver visual distraction and therefore the impact on safety is minimal. The results of the study have important design implications for future in-vehicle information systems

Bayesian Spatial Binary Regression for Label Fusion in Structural Neuroimaging

Many analyses of neuroimaging data involve studying one or more regions of interest (ROIs) in a brain image. In order to do so, each ROI must first be identified. Since every brain is unique, the location, size, and shape of each ROI varies across subjects. Thus, each ROI in a brain image must either be manually identified or (semi-) automatically delineated, a task referred to as segmentation. Automatic segmentation often involves mapping a previously manually segmented image to a new brain image and propagating the labels to obtain an estimate of where each ROI is located in the new image. A more recent approach to this problem is to propagate labels from multiple manually segmented atlases and combine the results using a process known as label fusion. To date, most label fusion algorithms either employ voting procedures or impose prior structure and subsequently find the maximum a posteriori estimator (i.e., the posterior mode) through optimization. We propose using a fully Bayesian spatial regression model for label fusion that facilitates direct incorporation of covariate information while making accessible the entire posterior distribution. We discuss the implementation of our model via Markov chain Monte Carlo and illustrate the procedure through both simulation and application to segmentation of the hippocampus, an anatomical structure known to be associated with Alzheimer's disease.Comment: 24 pages, 10 figure

Robustness from flexibility in the fungal circadian clock

Background Robustness is a central property of living systems, enabling function to be maintained against environmental perturbations. A key challenge is to identify the structures in biological circuits that confer system-level properties such as robustness. Circadian clocks allow organisms to adapt to the predictable changes of the 24-hour day/night cycle by generating endogenous rhythms that can be entrained to the external cycle. In all organisms, the clock circuits typically comprise multiple interlocked feedback loops controlling the rhythmic expression of key genes. Previously, we showed that such architectures increase the flexibility of the clock's rhythmic behaviour. We now test the relationship between flexibility and robustness, using a mathematical model of the circuit controlling conidiation in the fungus Neurospora crassa. Results The circuit modelled in this work consists of a central negative feedback loop, in which the frequency (frq) gene inhibits its transcriptional activator white collar-1 (wc-1), interlocked with a positive feedback loop in which FRQ protein upregulates WC-1 production. Importantly, our model reproduces the observed entrainment of this circuit under light/dark cycles with varying photoperiod and cycle duration. Our simulations show that whilst the level of frq mRNA is driven directly by the light input, the falling phase of FRQ protein, a molecular correlate of conidiation, maintains a constant phase that is uncoupled from the times of dawn and dusk. The model predicts the behaviour of mutants that uncouple WC-1 production from FRQ's positive feedback, and shows that the positive loop enhances the buffering of conidiation phase against seasonal photoperiod changes. This property is quantified using Kitano's measure for the overall robustness of a regulated system output. Further analysis demonstrates that this functional robustness is a consequence of the greater evolutionary flexibility conferred on the circuit by the interlocking loop structure. Conclusions Our model shows that the behaviour of the fungal clock in light-dark cycles can be accounted for by a transcription-translation feedback model of the central FRQ-WC oscillator. More generally, we provide an example of a biological circuit in which greater flexibility yields improved robustness, while also introducing novel sensitivity analysis techniques applicable to a broader range of cellular oscillators

The Effect Demographics Have On The Demand For Orange Juice

This paper investigates how the demand for orange juice is affected by the demographics of consumers. There are many variables in the orange juice demand equation and demographics are only one. Demographic variables are important in determining the tastes and preferences of different regions. The data that has been collected is weekly data over a two year period of time. The seemingly unrelated regression method will be used to examine the data. This project will be beneficial to orange juice advertising firms and companies that sell orange juice.Food Consumption/Nutrition/Food Safety, Marketing,

Bryophytes and their distribution in the Blue Mountains region of New South Wales

The bryophytes (mosses, liverworts and hornworts) that occur in the Blue Mountains region of New South Wales (latitude 33˚–34˚ S, longitude 151˚–151˚40’ E) are listed and information is provided on their distribution in the region. Species lists are based on herbarium specimens and field collections. 348 bryophyte taxa have been recorded from 70 families, including 225 moss taxa (in 108 genera from 45 families), 120 liverwort taxa (in 51 genera from 24 families) and 3 hornwort taxa (in 3 genera from one family). The moss families with most taxa are the Pottiaceae (with 23 taxa in 13 genera), Bryaceae (with 15 taxa in 3 genera) and Fissidentaceae (with 13 taxa). The largest genera are Fissidens (13 taxa), Campylopus (9) and Macromitrium (8). The liverwort family with the most taxa is Lepidoziaceae, with 29 taxa in 10 genera. The largest liverwort genera are Frullania (11 taxa) and Riccardia (8). The species lists include collections from both bushland and urban areas. Natural features of the Blue Mountains, including topography, altitude, climate and vegetation appear to be important factors influencing the number of bryophyte species recorded from each location. The number of collections from particular locations has been considerably influenced by ease of access, particularly proximity to roads, public transport and railway stations. The species lists include many records from areas that were not accessible to the early collectors of the late 19th and early 20th centuries such as Wollemi National Park, Gardens of Stone National Park, Newnes Plateau and Kanangra-Boyd National Park

The Most Distant Stars in the Milky Way

We report on the discovery of the most distant Milky Way (MW) stars known to date: ULAS J001535.72$+$015549.6 and ULAS J074417.48$+$253233.0. These stars were selected as M giant candidates based on their infrared and optical colors and lack of proper motions. We spectroscopically confirmed them as outer halo giants using the MMT/Red Channel spectrograph. Both stars have large estimated distances, with ULAS J001535.72$+$015549.6 at $274 \pm 74$ kpc and ULAS J074417.48$+$253233.0 at 238 $\pm$ 64 kpc, making them the first MW stars discovered beyond 200 kpc. ULAS J001535.72$+$015549.6 and ULAS J074417.48$+$253233.0 are both moving away from the Galactic center at $52 \pm 10$ km s$^{-1}$ and $24 \pm 10$ km s$^{-1}$, respectively. Using their distances and kinematics, we considered possible origins such as: tidal stripping from a dwarf galaxy, ejection from the MW's disk, or membership in an undetected dwarf galaxy. These M giants, along with two inner halo giants that were also confirmed during this campaign, are the first to map largely unexplored regions of our Galaxy's outer halo.Comment: Accepted and in print by ApJL. Seven pages, 2 figure