Ets proteins have been implicated in the regulation of gene expression during a variety of biological processes, including growth control, differentiation, development and transformation. More than 35 related proteins containing the 'ets domain' have now been found which specifically interact with DNA sequences encompassing the core tetranucleotide GGAA. Although ets responsive genes have been identified in the epidermis, little is known about their distribution and function in this tissue. We have now demonstrated that epidermis and cultured epidermal keratinocytes synthesize numerous ets proteins. The expression of some of these proteins is regulated as a function of differentiation. Among these is a novel ets transcription factor with a dual DNA-binding specificity, which we have called jen. The expression of jen is not only epithelial specific, but it is the only ets protein so far described, and one of the very few transcription factors whose expression is restricted to the most differentiated epidermal layers. We show that two epidermal marker genes whose expression coincides with that of jen are transregulated by this protein in a complex mode which involves interactions with other transcriptional regulators such as Sp1 and AP1.

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This article presents a methodology that integrates cumulative plots with probe vehicle data for estimation of travel time statistics (average, quartile) on urban networks. The integration reduces relative deviation among the cumulative plots so that the classical analytical procedure of defining the area between the plots as the total travel time can be applied. For quartile estimation, a slicing technique is proposed. The methodology is validated with real data from Lucerne, Switzerland and it is concluded that the travel time estimates from the proposed methodology are statistically equivalent to the observed values.

This paper proposes a vehicle trajectory planning method for automated on-ramp merging. Trajectory planning tasks of an on-ramp merging vehicle and a mainline facilitating vehicle are formulated as two related optimal control problems. Rather than specifying the merge point via external computational procedures, the location and time that the onramp vehicle merges into the mainline are determined endogenously by the optimal control problem of the facilitating vehicle. Bounds on vehicle acceleration are explicitly considered. The Pontryagin Maximum Principle is applied to find the solutions of the optimal control problems. In order to accommodate the constantly changing external environment, the proposed optimal control method is subsequently implemented in a recursive planning framework. Because of the nature of the problem, the length of the planning horizon is timevarying, unlike conventional model predictive control applications where the planning horizon is of fixed length. Numerical experiments are conducted to study performances of the proposed methodology under the influence of different leading vehicle trajectories and with different lengths of the planning updating interval. In particular, an experiment involving a real-world leading vehicle trajectory and considering different traffic demand levels are presented. The proposed methodology performs well in these experiments and has demonstrated a good potential in real-time applications.

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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.

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