Over 80% of individuals infected with Helicobacter pylori (H. pylori) are asymptomatic. Increased resistance to antibiotics and decreased compliance to the therapeutic regimens have led to the failure of eradication therapy. Probiotics, with direct and indirect inhibitory effects on H. pylori in both animal models and clinical trials, have recently been used as a supplementary treatment in H. pylori eradication therapy. Probiotics have been considered useful because of the improvements in H. pylori eradication rates and therapy-related side effects although treatment outcomes using probiotics are controversial due to the heterogeneity of species, strains, doses and therapeutic duration of probiotics. Thus, despite the positive role of probiotics, several factors need to be further considered during their applications. Moreover, adverse events of probiotic use need to be noted. Further investigations into the safety of adjuvant probiotics to H. pylori eradication therapy are required.

Remote sensing (RS) image can be applied in many domains. Most research work on RS image retrieval is to meet the demand of professional user. However, there are demands for RS image that comes from non-professional users who propose the requests in natural language (NL) not filling in professional request forms. Some problems are needed to be solved to implement RS image retrieval based on NL user demand. The objective of this research was to propose a user demand semantic model to solve the problem of translation from NL user demand to value requirements. Based on plenty of materials investigated in application domains, the syntax and semantics of NL user demand was analyzed. Semantic relationship is summarized in terms of the semantic analysis. After that, a user demand semantic model is proposed and built with ontology. It can be conclude that the proposed semantic model may help to RS image retrieval based on NL user demand.

The adaptive Kalman filtering algorithm was adopted in the online estimate of navigation state of unmanned aerial vehicle (UAV) as the simplified model often used. At the moment, the alogorithms those usually applied in this territory are not perfect. Analysed the adaptive Kalman filtering based on Maximum-Likelihood Estimation and Sage-Husa Kalman filtering, take advantage the characteristics of residue, choose the estimation windows, a simplified adaptive Kalman filtering algorithm was gived.