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Background: Fatty liver disease (FLD) is highly prevalent in Western countries, but recent data have shown that FLD is also emerging in China. Aim: To investigate the prevalence and risk factors of FLD in the Shuiguohu district of Wuhan city, central China, during 1995China, during -2004. Methods: 12247 individuals (7179 men and 5068 women) over 18 years of age who were living in the area were investigated for FLD in the Zhongnan Hospital of Wuhan University from 1995 to 2004. FLD was determined by the ultrasonographic method. Height, weight, blood pressure, fasting blood sugar, alanine aminotransferase, total cholesterol and triglyceride were determined by routine laboratory methods. Results: The prevalence of FLD was 12.5% in 1995, and rose gradually to 24.5% by 2003-4. The prevalence was twice as high in men (28.1%) as in women (13.8%), and increased with age in females, and males ,60 years of age. Multivariate analysis showed that several risk factors were profoundly associated with the prevalence of FLD, including male sex, old age, obesity, hyperlipidaemia (cholesterol or triglyceride), fasting hyperglycemia and hypertension. Conclusion: The prevalence of FLD in the Shuiguohu district of Wuhan city, central China, was shown to have increased during the 10-year period, 1995 to 2004. The FLD was found to be closely associated with sex, age, obesity and other metabolic syndrome features.

An improved method based on a genetic algorithm (GA) is developed to design a broadband electrical impedance matching network for piezoelectric ultrasound transducer. A key feature of the new method is that it can optimize both the topology of the matching network and perform optimization on the components. The main idea of this method is to find the optimal matching network in a set of candidate topologies. Some successful experiences of classical algorithms are absorbed to limit the size of the set of candidate topologies and greatly simplify the calculation process. Both binary-coded GA and real-coded GA are used for topology optimization and components optimization, respectively. Some calculation strategies, such as elitist strategy and clearing niche method, are adopted to make sure that the algorithm can converge to the global optimal result. Simulation and experimental results prove that matching networks with better performance might be achieved by this improved method.

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With the advent of Internet of Health (IoH) age, traditional medical or healthy services are gradually migrating to the Web or Internet and have been producing a considerable amount of medical data associated with patients, doctors, medicine, medical infrastructure and so on. Effective fusion and analyses of these IoH data are of positive significances for the scientific disaster diagnosis and medical care services. However, IoH data are often distributed across different departments and contain partial user privacy. Therefore, it is often a challenging task to effectively integrate or mine the sensitive IoH data, during which user privacy is not disclosed. To overcome the above difficulty, we put forward a novel multi-source medical data integration and mining solution for better healthcare services, named PDFM (Privacy-free Data Fusion and Mining). Through PDFM, we can search for similar medical records in a time-efficient and privacy-preserving manner, so as to offer patients with better medical and health services. A group of experiments are enacted and implemented to demonstrate the feasibility of the proposal in this work.