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Deployment of salt tolerant cultivars is an effective approach to minimize yield loss in a saline soil. In soybean, Glycine max (L.) Merr., substantial genetic variation exists for salt response. However, breeding for salt tolerance is hampered because no economically viable screening method has been developed for practical breeding. To facilitate the development of an effective screening method for salt tolerance in soybean, the present study was conducted to determine the heritability of salt tolerance and to identify associated quantitative trait loci (QTL). F2:5 lines from the cross of 'S-100' (salt tolerant) x 'Tokyo' (salt sensitive) were evaluated in a saline field in Hyde County, N.C., USA, in 1999 and in a greenhouse located in Raleigh, N.C., USA, in 2001. S-100 and Tokyo are ancestors of popular soybean cultivars released for the southern USA. The visual salt tolerance ratings of the F2:5 lines ranged from 0 (complete death) to 5 (normal healthy appearance). The entry-mean heritability for salt tolerance was 0.85, 0.48, and 0.57 in the field (four replications), greenhouse (two replications), and combined environments, respectively. The genotypic correlation between field and greenhouse ratings was 0.55, indicating reasonably good agreement between the two screening environments. To identify QTL associated with salt tolerance, each line was characterized with RFLP markers and an initial QTL single-factor analysis was completed. These results were used to identify genomic regions associated with the trait and to saturate the selected genomic regions with SSR markers to improve mapping precision. Subsequently, a major QTL for salt tolerance was discovered near the Sat_091 SSR marker on linkage group (LG) N, accounting for 41, 60, and 79% of the total genetic variation for salt tolerance in the field, greenhouse, and combined environments, respectively. The QTL allele associated with tolerance was derived from S-100. Pedigree tracking was used to examine the association between the salt tolerance QTL and flanking SSR marker alleles in U.S. cultivars descended from S-100 or Tokyo through 60 years of breeding. The presence of alleles from S-100 at the Sat_091 and Satt237 marker loci was always associated with salt tolerance in descendants. Alleles from Tokyo for these same markers were generally associated with salt sensitivity in descendent cultivars. The strong relationship between the SSR marker alleles and salt tolerance suggests that these markers could be used for marker-assisted selection in commercial breeding.

Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). This paper first proposes a new time-discretized multi-commodity network flow model for the VRPPDTW based on the integration of vehicles' carrying states within space-time transportation networks, so as to allow a joint optimization of passenger-to-vehicle assignment and turn-by-turn routing in congested transportation networks. Our three-dimensional state-space-time network construct is able to comprehensively enumerate possible transportation states at any given time along vehicle space-time paths, and further allows a forward dynamic programming solution algorithm to solve the single vehicle VRPPDTW problem. By utilizing a Lagrangian relaxation approach, the primal multi-vehicle routing problem is decomposed to a sequence of single vehicle routing sub-problems, with Lagrangian multipliers for individual passengers' requests being updated by sub-gradient-based algorithms. We further discuss a number of search space reduction strategies and test our algorithms, implemented through a specialized program in C++, on medium-scale and large-scale transportation networks, namely the Chicago sketch and Phoenix regional networks.Keywords: Vehicle routing problem with pickup and delivery with time windows; Lagrangian relaxation; Timedependent least-cost path problem; Forward dynamic programming; Ride-sharing service optimization. 1 IntroductionAs population and personal travel activities continue to increase, traffic congestion has remained as one of the major concerns for transportation system agencies with tight resource constraints. The next generation of transportation system initiatives aims to integrate various demand management strategies and traffic control measures to actively achieve mobility, environment, and sustainability goals. A number of approaches hold promises of reducing the undesirable effects of traffic congestion due to driving-alone trips, to name a few, demand-responsive transit services, dynamic ride-sharing, and intermodal traffic corridor management.The optimized and coordinated ride-sharing services provided by transportation network companies (TNC) can efficiently utilize limited vehicle and driver resources while satisfying time-sensitive origin-to-destination transportation service requests. In a city with numerous travelers with different purposes, each traveler has his own traveling schedule. Instead of using his own car, the traveler can (by the aid of ride-sharing) bid and call a car just a few minutes before leaving his origin, or preschedule a car a day prior to his departure. The on-demand transportation system provides a traveler with a short waiting time even if he resides in a high-demand area. Currently, several realtime ride-sharing or, more precisely, app-based transportation network and taxi companies, such as Uber and Lyft are serving passengers in many metropolitan areas. In the ...

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