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A key parameter in engineering seismology and earthquake physics is seismic stress drop, which describes the relative amount of high-frequency energy radiation at the source. To identify regions with potentially significant stress drop variations, we perform a comparative analysis of source parameters in the greater San Gorgonio Pass (SGP) and Ventura basin (VB) in southern California. The identification of physical stress drop variations is complicated by large data scatter as a result of attenuation, limited recording bandwidth and imprecise modeling assumptions. In light of the inherently high uncertainties in single stress drop measurements, we follow the strategy of stacking large numbers of source spectra thereby enhancing the resolution of our method. We analyze more than 6000 high-quality waveforms between 2000 and 2014, and compute seismic moments, corner frequencies and stress drops. Significant variations in stress drop estimates exist within the SGP area. Moreover, the SGP also exhibits systematically higher stress drops than VB and shows more scatter. We demonstrate that the higher scatter in SGP is not a generic artifact of our method but an expression of differences in underlying source processes. Our results suggest that higher differential stresses, which can be deduced from larger focal depth and more thrust faulting, may only be of secondary importance for stress drop variations. Instead, the general degree of stress field heterogeneity and strain localization may influence stress drops more strongly, so that more localized faulting and homogeneous stress fields favor lower stress drops. In addition, higher loading rates, for example, across the VB potentially result in stress drop reduction whereas slow loading rates on local fault segments within the SGP region result in anomalously high stress drop estimates. Our results show that crustal and fault properties systematically influence earthquake stress drops of small and large events and should be considered for seismic hazard assessment. [ABSTRACT FROM AUTHOR]

The UN Economic Commission's Statistics of Road Traffic Accidents report of 2011 shows that every year, about 150 000 human beings lose their lives on the roads of the western world. Although it is a common belief that this figure could shrink with the use of new sensor and communication technologies, unfortunately, none such systems have hit the road to date. Ideally, if such technologies were put into place, vehicles could be part of a vehicular ad hoc network (VANET) capable of spreading relevant information about dangerous events (e.g., car accidents) to all approaching drivers. However, all this is mainly supported by simulation studies, as no practical results have been published to date, revealing the effective performances of such systems at work. In this paper, we fill this gap, presenting a detailed description of the greatest experiments (a few thousand throughout the streets of Los Angeles), to date, ever performed with an accident warning system specifically devised for highway scenarios. In particular, among all the possible candidate schemes, we ran a few thousand experiments with the accident warning system algorithm that was proven to be optimal in terms of bandwidth usage and covered distance in realistic scenarios. Our experiments confirm what has been observed before in theory and simulation, i.e., the use of such a system can reduce, by as much as 40%, the amount of vehicles involved in highway pileups. [ABSTRACT FROM PUBLISHER]

AOptix Technologies, a developer of advanced iris recognition systems and ultra-high bandwidth wireless optical communication solutions, has announced the close of a US$12.9 million dollar financing round led by Northgate Capital of Danville, CA. [Copyright &y& Elsevier]