Transgenic (TG) mice with TCR alpha and beta chain genes from a CD4-dependent auto-I-Ak reactive T cell clone were generated. H-2k TG mice had a large number of thymic and splenic CD4 T cells expressing the autoreactive TCR without manifestation of autoimmunity. The cells were not anergic, as they could respond to autologous antigen presenting cells and anti-TCR antibodies in vitro to proliferate and to produce interleukins. Various degrees of down-regulation of CD2 and CD44 was observed in TG mice, indicating the presence of a defective co-stimulatory process in TG T cells. These features indicate that the self tolerance in autoreactive TCR TG mice is due not to clonal deletion and anergy but to a novel mechanism where T cells cannot sufficiently respond to normally existing self ligand in vivo. That such an in vivo unresponsiveness of autoreactive T cells is dictated in the thymus during CD4 T cell differentiation atypical form of positive selection of autoreactive T cells was suggested by the abnormal surface expression of CD69 and HSA.
Trip planning services have been developed along with tourism promotion and information technology evolutions, where we must construct trip routes that simultaneously optimize multi-objective functions such as trip expenses and user satisfaction. Moreover, utilization of past-trip records is essential, because similarities to past-trip records well reflect users' general preferences and tendencies during trip planning. In this paper, we propose a multi-objective trip planning method using ant colony optimization (ACO). By effectively using the pheromones in ACO, we can construct trip routes similar to trip records stored before and the constructed route can reflect users' general preferences. In addition, we vary ants' behaviors in ACO corresponding to various objective functions and hence we can obtain multi-objective trip routes naturally. Experimental results demonstrated that our method outperforms the baseline methods in terms of point-of-interest (POI) satisfaction, POI cost, and past-trip similarity. We also conducted a user study, which clearly indicates that our method obtains high scores through various user questionnaires.INDEX TERMS multi-objective trip planning problem, ant colony optimization, past-trip records, pheromone updating, point-of-interest (POI)
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