ABSTRACT
This work investigates the stability and dissipativity problems for neural networks with time-varying delay. By the construction of new augmented Lyapunov-Krasovskii functionals based on integral inequality and the use of zero equality approach, three improved results are proposed in the forms of linear matrix inequalities. And, based on the stability results, the dissipativity analysis for NNs with time-varying delays was investigated. Through some numerical examples, the superiority and effectiveness of the proposed results are shown by comparing the existing works.
Subject(s)
Algorithms , Neural Networks, ComputerABSTRACT
The maximum content of cation vacancies in perovskites determines the maximum adjustment to the physical properties. By using the classical criterion of the tolerance factor, we put forward a new method to obtain the maximum content of cation vacancies in perovskites. The effective ionic radius was calculated using the weighted average method, and the limit of tolerance factors was used to determine the maximum value of the cation vacancies. The calculated results of the La1-xMnO3 and La0.75Sr0.25Mn1-yO3 materials coincide with experimental results. For application, [(A1)1-x(A2)x]1-z1(B1B2)X3 or [(A1)1-x(A2)x](B1B2)1-z2X3 (X = O, F, Cl, Br, I) inorganic and hybrid organic-inorganic perovskite materials with vacancies at the A or B sites were predicted successfully, which provides a new method to improve the physical properties of perovskite materials.
ABSTRACT
OBJECTIVE: To investigate the correlations of MC4R and MSH2 with adult obesity, a total of 46 patients with early-stage colon cancer were treated in our hospital between February 2008 and February 2009 and were enrolled. PATIENTS AND METHODS: Venous blood was regularly drawn from subjects of the observation group and 48 healthy subjects for 6 years. Expression levels of MC4R and MSH2 genes were tested using quantitative polymerase chain reaction analyses, and the ensuing proteins were determined using enzyme-linked immunosorbent assays and Western blotting and immunohistochemical analyses. Finally, correlations with body mass index (BMI) and the presence of colon cancer were identified using multivariate analyses. RESULTS: Compared with the control group, MSH2 mRNA and protein expression increased significantly over time (p < 0.05) in patients with colon cancer. Moreover, MSH2 expression was correlated with colon cancer progression, and MC4R mRNA and protein expression increase concurrently in comparison with the control group (p < 0.05). Also, the mean BMI among patients with colon cancer was 30.8, whereas that among control subjects was only 21.4. These data indicate a relationship between BMI and colon cancer. CONCLUSIONS: Expression of MSH2 in patients with colon cancer may promote the expression of the obesity gene MC4R, potentially contributing to body weight gains.
