Phase 1 of the near term hybrid passenger vehicle development program

In order to meet project requirements and be competitive in the 1985 market, the proposed six-passenger vehicle incorporates a high power type Ni-Zn battery, which by making electric-only traction possible, permits the achievement of an optimized control strategy based on electric-only traction to a set battery depth of discharge, followed by hybrid operation with thermal primary energy. This results in a highly efficient hybrid propulsion subsystem. Technical solutions are available to contain energy waste by reducing vehicle weight, rolling resistance, and drag coefficient. Reproaching new 1985 full size vehicles of the conventional type with hybrids of the proposed type would result in a U.S. average gasoline saving per vehicle of 1,261 liters/year and an average energy saving per vehicle of 27,133 MJ/year

Exploring the Trade-offs Between Incentives for Distributed Generation Developers and DNOs

Regulators are aiming to incentivize developers and Distribution Network Operators to connect distributed generation (DG) to improve network environmental performance and efficiency. A key question is whether these incentives will encourage both parties to connect DG. Here, multiobjective optimal power flow is used to simulate how the parties' incentives affect their choice of DG capacity within the limits of the existing network. Using current U.K. incentives as a basis, this paper explores the costs, benefits and tradeoffs associated with DG in terms of connection, losses and, in a simple fashion, network deferral. © 2007 IEEE

Measuring Propagation Speed of Coulomb Fields

The problem of gravity propagation has been subject of discussion for quite a long time: Newton, Laplace and, in relatively more modern times, Eddington pointed out that, if gravity propagated with finite velocity, planets motion around the sun would become unstable due to a torque originating from time lag of the gravitational interactions. Such an odd behavior can be found also in electromagnetism, when one computes the propagation of the electric fields generated by a set of uniformly moving charges. As a matter of fact the Li\'enard-Weichert retarded potential leads to a formula indistinguishable from the one obtained assuming that the electric field propagates with infinite velocity. Feyman explanation for this apparent paradox was based on the fact that uniform motions last indefinitely. To verify such an explanation, we performed an experiment to measure the time/space evolution of the electric field generated by an uniformely moving electron beam. The results we obtain on such a finite lifetime kinematical state seem compatible with an electric field rigidly carried by the beam itself.Comment: 23 pages, 15 figure

Pseudo ainhum and facial malformation secondary to Streeter's dysplasia

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Fast three dimensional r-adaptive mesh redistribution

This paper describes a fast and reliable method for redistributing a computational mesh in three dimensions which can generate a complex three dimensional mesh without any problems due to mesh tangling. The method relies on a three dimensional implementation of the parabolic Monge–Ampère (PMA) technique, for finding an optimally transported mesh. The method for implementing PMA is described in detail and applied to both static and dynamic mesh redistribution problems, studying both the convergence and the computational cost of the algorithm. The algorithm is applied to a series of problems of increasing complexity. In particular very regular meshes are generated to resolve real meteorological features (derived from a weather forecasting model covering the UK area) in grids with over 2×107 degrees of freedom. The PMA method computes these grids in times commensurate with those required for operational weather forecasting

Neural Biclustering in Gene Expression Analysis

Clustering in high dimensional spaces is a very difficult task. Dealing with DNA microarrays is even more difficult because gene subsets are coregulated and coexpressed only under specific conditions. Biclusterng addresses the problem of finding such submanifolds by exploiting both gene and condition (tissue) clustering. The paper proposes a self-organizing neural network, GH EXIN, which builds a hierarchical tree by adapting its architecture to data. It is integrated in a framework in which gene and tissue clustering are alternated and controlled by the quality of the bicluster. Examples of the approach and a biological validation of results are also given