Automated vehicles (AVs) may enter the consumer market with various stages of automation in 10 years or even sooner. Meanwhile, regional planning agencies are envisioning plans for time horizons out to 2040 and beyond. To help decision makers understand the effect of AV technology on regional plans, modeling tools should anticipate its impact on transportation networks and traveler choices. This research uses the Seattle, Washington, region's activity-based travel model to test a range of travel behavior impacts from AV technology development. The existing model was not originally designed with AVs in mind, so some modifications to the model assumptions are described in areas of roadway capacity, user values of time, and parking costs. Larger structural model changes were not yet considered. Results of four scenario tests show that improvements in roadway capacity and in the quality of the driving trip may lead to large increases in vehicle miles traveled, while a shift to per mile usage charges may counteract that trend. Travel models will need to have major improvements in the coming years, especially with regard to shared ride, taxi modes, and the effect of multitasking opportunities, to better anticipate the arrival of this technology.
Brominated indole alkaloids are a common class of metabolites reported from sponges of the order Verongida. Herein we report the isolation, structure determination, and activity of metabolites from three Florida sponges, namely, Verongula rigida (order Verongida, family Aplysinidae), Smenospongia aurea, and S. cerebriformis (order Dictyoceratida, family Thorectidae). All three species were investigated chemically, revealing similarities in secondary metabolites. Brominated compounds, as well as sesquiterpene quinones and hydroquinones, were identified from both V. rigida and S. aurea despite their apparent taxonomic differences at the ordinal level. Similar metabolites found in these distinct sponge species of two different genera provide evidence for a microbial origin of the metabolites. Isolated compounds were evaluated in the Porsolt forced swim test (FST) and the chick anxiety-depression continuum model. Among the isolated compounds, 5,6-dibromo- N,N-dimethyltryptamine ( 1) exhibited significant antidepressant-like action in the rodent FST model, while 5-bromo- N,N-dimethyltryptamine ( 2) caused significant reduction of locomotor activity indicative of a potential sedative action. The current study provides ample evidence that marine natural products with the diversity of brominated marine alkaloids will provide potential leads for antidepressant and anxiolytic drugs.
Abstract:The parallel machine replacement problem consists of finding a minimum cost replacement policy for a finite population of economically interdependent machines. In this paper, we formulate a stochastic version of the problem and analyze the structure of optimal policies under general classes of replacement cost functions. We prove that for problems with arbitrary cost functions, there can be optimal policies where a machine is replaced only if all machines in worse states are replaced (Worse Cluster Replacement Rule). We then show that, for problems with replacement cost functions exhibiting nonincreasing marginal costs, there are optimal policies such that, in any stage, machines in the same state are either all kept or all replaced (No-Splitting Rule). We also present an example that shows that economies of scale in replacement costs do not guarantee optimal policies that satisfy the No-Splitting Rule. These results lead to the fundamental insight that replacement decisions are driven by marginal costs, and not by economies of scale as suggested in the literature. Finally, we describe how the optimal policy structure, i.e., the No-Splitting and Worse Cluster Replacement Rules, can be used to reduce the computational effort required to obtain optimal replacement policies.
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