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Traffic light recognition is being intensively researched for the purpose of reducing traffic accidents at intersections and realizing autonomous driving. However, conventional vision-based approaches have several limitations due to full image scanning, always-on operation, various different types of traffic lights, and complex driving environments. In particular, it might be impossible to recognize a relevant traffic light among multiple traffic lights at multiple intersections. To overcome such limitations, we propose an effective architecture that integrates a vision system with an accurate positioning system and an extended digital map. The recognition process is divided into four stages and we suggest an extended methodology for each stage. These stages are: ROI generation, detection, classification, and tracking. The 3D positions of traffic lights and slope information obtained from an extended digital map enable ROIs to be generated accurately, even on slanted roads, while independent design and implementation of individual recognition modules for detection and classification allow for selection according to the type of traffic light face. Such a modular architecture gives the system simplicity, flexibility, and maintainable algorithms. In addition, adaptive tracking that exploits the distance to traffic lights allows for seamless state estimation through smooth data association when measurements change from long to short ranges. Evaluation of the proposed system occurred at six test sites and utilized two different types of traffic lights, seven states, sloped roads, and various environmental complexities. The experimental results show that the proposed system can recognize traffic lights with 98.68% precision, 92.73% recall, and 95.52% accuracy in the 10.02–81.21 m range. [ABSTRACT FROM AUTHOR]

Abstract: This study proposes integrating GIS and FEATHERS in order to improve the capability of data management, spatial analysis and visualization in the model framework. GIS provides geodatabase for effectively storing and edit (non-)spatial data, useful functions of spatial analysis for defining spatial interactions between phenomena simulated by the modeling system, and interactive visualization tools. Thus, this study mainly focuses on three topics: i) why FEATHERS needs a GIS module, ii) how the GIS module is designed, and iii) what functions can be supported by the GIS module in the FEATHERS system. Moreover, we overview some transportation software adopting GIS to catch up a general trend in GIS and transportation and also suggest data schema for creating geodatabase and a source code for making map layers and map tools in python. At the end, we conclude this paper with summary and plan for the future work. [Copyright &y& Elsevier]

Abstract: The exclusive distribution of 5-HT6 receptor in the brain regions and high affinity for antipsychotic and antidepressant drugs makes 5-HT6 receptor a promising target in treatment of CNS diseases. Based on a pharmacophore model reported in the literature, we designed and synthesized a novel series of 5-HT6 receptor ligands having indole as a central aromatic core and 1-amino-4-methyl piperazine as positive ionizable group. Out of 32 compounds we have successfully identified 10 new compounds as 5-HT6 receptor antagonists. The structure–activity relationship (SAR) studies have been carried out by mapping the compounds with the 3D QSAR model. [Copyright &y& Elsevier]

Abstract: A novel series of 3-arylsulfonylamino-5,6-dihydro-6-substituted-1H-pyrazolo[3,4-c]pyridine-7-ones was designed and synthesized as 5-HT6 ligands. Among the derivatives synthesized, the lead compound, 12b, having piperidine functionality at the 6-position and (1-naphthyl)sulfonamino at the 3-position of the core structure showed the most potent 5-HT6 inhibitory activity in vitro, good stability without CYP liability, and good neuropathic pain alleviation activity in a rat animal model. [Copyright &y& Elsevier]

Abstract: The number of epidermal growth factor receptors (EGFRs) and their ligands are highly expressed in malignant tumor cells. The EGF signaling pathway is also activated in up to one-third of patients with breast cancer. In this study, we investigated the novel function of the JAK3 inhibitor, WHI-P131, on EGF-induced MMP-9 expression and the regulatory mechanism of EGF-induced MMP-9 expression in SKBR3 cells. We observed that EGF increased MMP-9 mRNA and protein expression in a dose-dependent manner. EGF also induced the phosphorylation of EGFR, ERK, and STAT-3, and these effects were inhibited by the EGFR inhibitor, AG1478. To investigate the involvement of the STAT-3 pathway on EGF-induced MMP-9 expression, we pretreated SKBR3 cells with JAK1, JAK2, and JAK3 inhibitors prior to EGF treatment. The results showed that the JAK3 inhibitor, WHI-P131, as well as JAK3 siRNA transfection, but not the JAK1 and JAK2 inhibitors, significantly decreased EGF-induced MMP-9 expression. In addition, EGF-induced STAT-3 phosphorylation was only inhibited by WHI-P131. We then transfected cells with adenoviral STAT-3 (Ad-STAT-3), followed by treatment with EGF. Interestingly, EGF-induced MMP-9 expression was decreased by Ad-STAT-3 overexpression in a dose-dependent manner, while it was significantly increased by STAT-3 siRNA transfection. Our results also showed that basal levels of MMP-9 expression were significantly increased by constitutive active-MEK (CA-MEK) overexpression. EGF-induced ERK phosphorylation was prevented by WHI-P131, but not by JAK1 and JAK2 inhibitors. On the other hand, EGF-induced MMP-9 expression was decreased by the MEK1/2 inhibitor, UO126. Therefore, for the first time, we suggest that the JAK3 inhibitor, WHI-P131, inhibits EGF-induced STAT-3 phosphorylation as well as ERK phosphorylation. The JAK3/ERK pathway may play an important role in EGF-induced MMP-9 expression in SKBR3 cells. [Copyright &y& Elsevier]