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The wood were treated by N2,O2cold plasma with the processing power 300W, the treatment duration 5 min, then the treated wood was bonded with MUF to valve the bonding performance, the contact angles of the treated/untreated wood were tested. The chemical composition on the surface of wood with or without N2cold plasma treatment also was analyzed by X-ray photoelectron spectroscopy (XPS). The results showed: the contact angles of the surface decreased, the surface free energy increased evidently that treated by N2or O2cold plasma, and the average bonding performance of wood that treated by cold plasma (whether N2or O2) increased obviously, more than 50% comparing with that untreated. The XPS analysis showed the atomic ratio O/C has increased, and more groups were oxidized or more peroxides were formed on the surface of wood, and the N element was introduced to the wood surface after nitrogen cold plasma treatment and it was guessed to the group of –NH2.

With the development of network technology and the popularity of network applications, network server attack number and severity are significantly increased; attack alarm data is mostly produced by duplicate and invalid. Classic attribute-oriented induction (Attribute-Oriented Induction, AOI) algorithm is used for conceptual clustering can greatly improve the processing of these data workload, but does not seem to be very effective in actual work. This paper makes a detailed discussion on how to improve the algorithm.With the development of network technology, the number of attacks on web services and severity increased significantly, so intrusion detection system (IDS) has been applied to the field of network security. However, IDS protects network, at the same time also brings a new problem: IDS will produce a lot of alarm data, and most of these alarm data are duplicate and invalid. According to the characteristics of the data, effective dealing with distributed IDS has brought a lot of alarm data, and how to eliminate duplicate or invalid data becomes a realistic problem which is urgent to be solved. Although using classic attribute-oriented Induction (AOI) for conceptual clustering algorithm can greatly improve the processing of these data workload, the algorithm have not achieved the result of simple data processing on computer processing, thus how to improve the algorithm is a urgent subject of work efficiency.

Background Urinary infections are a common type of pediatric disease, and their treatment and prognosis are closely correlated with infection location. Common clinical manifestations and laboratory tests are insufficient to differentiate between acute pyelonephritis and lower urinary tract infection. This study was conducted to explore a diagnostic method for upper and lower urinary tract infection differentiation. Methods The diagnostic values of procalcitonin (PCT) and C-reactive protein (CRP) were analyzed using the receiver operating characteristic curve method for upper and lower urinary tract infection differentiation. PCT was determined using chemiluminescent immunoassay. Results The PCT and CRP values in children with acute pyelonephritis were significantly higher than those in children with lower urinary tract infection (3.90 ± 3.51 ng/ml and 68.17 ± 39.42 mg/l vs. 0.48 ± 0.39 ng/ml and 21.39 ± 14.92 mg/l). The PCT values were correlated with the degree of renal involvement, whereas the CRP values failed to show such a significant correlation. PCT had a sensitivity of 90.47% and a specificity of 88% in predicting nephropathia, whereas CRP had sensitivity of 85.71% and a specificity of 48%. Conclusions Both PCT and CRP can be used for upper and lower urinary tract infection differentiation, but PCT has higher sensitivity and specificity in predicting pyelonephritis than CRP. PCT showed better results than CRP. PCT values were also correlated with the degree of renal involvement.