Comparison of quality of life between urban and rural gastric cancer patients and analysis of influencing factors

AIM: The conception of quality of life has been widely accepted by clinic doctors. Evaluations of the treatment effect of chronic diseases have been changed to depend not only on the survival time, but also on the quality of life of the patients. Fuzhou City and Changle County are highincidence areas of the gastric cancer in Fujian Province. The aims of this research were to compare the quality of life of urban patients with that of rural patients and analyze the factors influencing quality of life of gastric cancer patients in Fujian Province. METHODS: The samples were drawn with cluster sampling. The urban sample consisted of 162 patients aged 25 to 75 with 143 males and 19 females. The rural sample consisted of 200 patients aged 32 to 78 with 166 males and 34 females. The patients in both the urban and rural areas were investigated, and their scores on 21 items reflecting the quality of life were measured. The methods of ttest and stepwise regression were used to analyze the data. RESULTS: The average total scores of quality of life of the urban patients and rural patients were 64.11 and 68.69 respectively. There was a significant difference between the means of two samples (P = 0.0004). Seven variables in the regression model estimated by the urban sample and 4 variables in the model by the rural sample were at the level of significance α=0.05. Family income, nutrition and rehabilitating exercise were selected into both the urban and rural regression models. CONCLUSION: Most of the gastric cancer patients have poor quality of life in Fujian Province and the rural patients have lower quality of life than that of urban patients. The patients having more family income have better quality of life, and enhanced nutrition and doing rehabilitating exercise are helpful in improving the quality of life of the gastric cancer patients.

Population Synthesis for the Symbiotic Stars with Main-sequence Accretors

Using a population synthesis code, we have investigated the formation of symbiotic systems in which the hot component is a main-sequence star that is accreting matter from the cool component via Roche lobe overflow (RLOF). The RLOF can be divided into two cases: dynamically unstable and stable. In the first case, the birthrate of symbiotic stars is 0.056 yr-1 or 0.045 yr-1 depending on different assumptions; in the stable RLOF case, it is 0.002 yr-1 or 0.005 yr-1. The number of symbiotic stars with main-sequence accretors and unstable RLOF in our galaxy is about 5, that with stable RLOF is about 60 to 280. Comparison between our results with those of Yungelson et al. shows that symbiotic stars with MS accretors make only a small contribution ((?) 8%) to the whole population of symbiotic stars in the Galaxy.

Tunable compact asynchronous optical sampling system using Er-doped fiber laser

We report a compact,tunable,self-starting,all-fiber laser-based asynchronous optical sampling(ASOPS)system.Two Er-doped fiber oscillators were used as the pulsed-laser source,whose repetition rate could be set at 100 MHz with a tuning range of 1.25 MHz through a fiber delay line.By employing phase-locked and temperature control loops,the repetition rate offset of the two lasers was stabilized with 7.13×10^(−11)fractional instability at an average time of 1 s.Its capabilities in the terahertz regime were demonstrated by terahertz time-domain spectroscopy,achieving a spectral bandwidth of 3 THz with a dynamic range of 30 dB.The large range of repetition rate adjustment in our ASOPS system has the potential to be a powerful tool in the terahertz regime.

Thansparent and Explicable Boiler Fouling Monitoring with Fuzzy Neural Newtwork

Fouling on boiler heating surfaces is one of the important factors that damage boiler’s economical per-formance and safety With on-line monitoring of foiling states on boiler heating surfaces, it is possible to optimize sootblower system, to visualize fouling states, to improve performance, as well as to remedy the insufficlellcy of experiment research in boiler heating surface fouling process. New method based on Fuzzy Neural Network (FNN) is presented to monitor fouling states on boiler heating surfaces on-line.Compared with regular methods, since FNN’s reasoning process is transpareot and comprehensible,it is pooible to explain and comprehend reasoning processt which makes the FNN based system perform as an additional operation consulting system.