Questionnaire Investigation on the Needs at Fuji City and its Sensibility Analysis Utilizing Bayesian Network

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. These are analyzed by using Bayesian Network. Sensitivity analysis is also conducted. As there are so many items, we focus on “The image of the surrounding area at this shopping street” and pick up former half and make sensitivity analysis in this paper. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated

Bayesian Network Analysis for the Questionnaire Investigation on the Needs at Fuji Shopping Street Town

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city (two for Fuji Shopping Street Town and two for Yoshiwara Shopping Street Town). Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street Town and Yoshiwara Shopping Street Town. Therefore we focus Fuji Shopping Street Town in this paper. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated

Bayesian Network Analysis for the Questionnaire Investigation on the Impression at Yoshiwara Shopping Street in Fuji City

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street and Yoshiwara Shopping Street. Therefore we focus Yoshiwara Shopping Street in this paper. These are analyzed by using Bayesian Network. Sensitivity analysis is also conducted. As there are so many items, we focus on “The image of the surrounding area at this shopping street” and pick up former half and make sensitivity analysis in this paper. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated

Bayesian Network Analysis for the Questionnaire Investigation on the Needs at Fuji Shopping Street Town under the View Point of Service Engineering

Shopping streets at local city in Japan became old and are generally declining. In this paper, the area rebirth and/or regional revitalization of shopping street are handled. Fuji city in Japan is focused. Four big festivals are held at Fuji city (two for Fuji Shopping Street Town and two for Yoshiwara Shopping Street Town). Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street Town and Yoshiwara Shopping Street Town. Therefore Fuji Shopping Street Town is focused in this paper. These are analyzed by using Bayesian Network. These are analyzed by sensitivity analysis and odds ratio is calculated to the results of sensitivity analysis in order to obtain much clearer results. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. Fruitful results are obtained. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated

Need identification and sensitivity analysis of consumers using Bayesian Network : A case of Fuji Shopping Street Town

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. There is a big difference between Fuji Shopping Street and Yoshiwara Shopping Street. Therefore we focus Fuji Shopping Street in this paper. These are analyzed by using Bayesian Network. Sensitivity analysis is also conducted. As there are so many items, we focus on “The image of the surrounding area at this shopping street” and pick up former half and make sensitivity analysis in this paper. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. Sensitivity analysis is performed by back propagation method. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated

Bayesian Network Analysis for the Questionnaire Investigation on the Impression at Fuji City

Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street, and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street. In this paper, we mainly focus the impression the visitors feel and analyze them. These are analyzed by using Bayesian Network. The analysis utilizing Bayesian Network enabled us to visualize the causal relationship among items. Furthermore, sensitivity analysis brought us estimating and predicting the prospective visitors. These are utilized for constructing a much more effective and useful plan building. We have obtained fruitful results. To confirm the findings by utilizing the new consecutive visiting records would be the future works to be investigated

High-speed atomic force microscopy combined with inverted optical microscopy for studying cellular events.

A hybrid atomic force microscopy (AFM)-optical fluorescence microscopy is a powerful tool for investigating cellular morphologies and events. However, the slow data acquisition rates of the conventional AFM unit of the hybrid system limit the visualization of structural changes during cellular events. Therefore, high-speed AFM units equipped with an optical/fluorescence detection device have been a long-standing wish. Here we describe the implementation of high-speed AFM coupled with an optical fluorescence microscope. This was accomplished by developing a tip-scanning system, instead of a sample-scanning system, which operates on an inverted optical microscope. This novel device enabled the acquisition of high-speed AFM images of morphological changes in individual cells. Using this instrument, we conducted structural studies of living HeLa and 3T3 fibroblast cell surfaces. The improved time resolution allowed us to image dynamic cellular events

Viral RNA recognition by LGP2 and MDA5, and activation of signaling through step-by-step conformational changes

細胞内のウイルスを認識する蛋白質の仕組みを解明 --ウイルスから我々の体を守る影のヒーロー--. 京都大学プレスリリース. 2020-12-04.Cytoplasmic RIG-I-like receptor (RLR) proteins in mammalian cells recognize viral RNA and initiate an antiviral response that results in IFN-β induction. Melanoma differentiation-associated protein 5 (MDA5) forms fibers along viral dsRNA and propagates an antiviral response via a signaling domain, the tandem CARD. The most enigmatic RLR, laboratory of genetics and physiology (LGP2), lacks the signaling domain but functions in viral sensing through cooperation with MDA5. However, it remains unclear how LGP2 coordinates fiber formation and subsequent MDA5 activation. We utilized biochemical and biophysical approaches to observe fiber formation and the conformation of MDA5. LGP2 facilitated MDA5 fiber assembly. LGP2 was incorporated into the fibers with an average inter-molecular distance of 32 nm, suggesting the formation of hetero-oligomers with MDA5. Furthermore, limited protease digestion revealed that LGP2 induces significant conformational changes on MDA5, promoting exposure of its CARDs. Although the fibers were efficiently dissociated by ATP hydrolysis, MDA5 maintained its active conformation to participate in downstream signaling. Our study demonstrated the coordinated actions of LGP2 and MDA5, where LGP2 acts as an MDA5 nucleator and requisite partner in the conversion of MDA5 to an active conformation. We revealed a mechanistic basis for LGP2-mediated regulation of MDA5 antiviral innate immune responses

RecO-mediated DNA homology search and annealing is facilitated by SsbA

Bacillus subtilis RecO plays a central role in recombinational repair and genetic recombination by (i) stimulating RecA filamentation onto SsbA-coated single-stranded (ss) DNA, (ii) modulating the extent of RecA-mediated DNA strand exchange and (iii) promoting annealing of complementary DNA strands. Here, we report that RecO-mediated strand annealing is facilitated by cognate SsbA, but not by a heterologous one. Analysis of non-productive intermediates reveals that RecO interacts with SsbA-coated ssDNA, resulting in transient ternary complexes. The self-interaction of ternary complexes via RecO led to the formation of large nucleoprotein complexes. In the presence of homology, SsbA, at the nucleoprotein, removes DNA secondary structures, inhibits spontaneous strand annealing and facilitates RecO loading onto SsbA–ssDNA complex. RecO relieves SsbA inhibition of strand annealing and facilitates transient and random interactions between homologous naked ssDNA molecules. Finally, both proteins lose affinity for duplex DNA. Our results provide a mechanistic framework for rationalizing protein release and dsDNA zippering as coordinated events that are crucial for RecA-independent plasmid transformation