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This paper is concerned with the problem of H ∞ filtering for discrete-time Markov jump linear system with parametric uncertainties and quantized measurements, when the jumping mode information is not accessible. By converting the quantized errors into a sector-bounded nonlinearity, the parametric uncertainties and measurements quantization are dealt with in a unified framework. The mode-independent H ∞ filter is designed, and sufficient conditions are established via Lyapunov function approach, such that for all possible uncertain parameters and quantization errors, the resulting filtering error system is robustly stochastically stable and achieves a guaranteed H ∞ filtering error performance index. A numerical example is provided to demonstrate the feasibility and effectiveness of the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study is concerned with the problem of state estimation for networked systems with a Markov plant considering the measurement uncertainties. The measurements suffer from both the randomly occurring missing phenomenon and the quantisation effects. Taking into account the statistical knowledge of the quantised measurements, an approximate minimum mean square error estimate algorithms is derived based on Gaussian assumption, which is referred to as interacting multiple model Monte Carlo (IMMMC) algorithm. A quantised measurement expectation calculated by Monte Carlo sampling method is embedded into the Kalman filter under the IMM framework. A simulation example is provided demonstrating that IMMMC is computationally appealing and presents better estimate performance than the previous algorithms. Moreover, IMMMC has better mode following ability and can clearly distinguish the occurrence of measurements missing. [ABSTRACT FROM AUTHOR]

The problem of robust H∞ filtering is investigated for discrete-time Markov jump linear system (DMJLS) with uncertain parameters and missing measurements. The missing measurements process is modelled as a Bernoulli distributed sequence. A robust H∞ filter is designed and sufficient conditions are established in terms of linear matrix inequalities via a mode-dependent Lyapunov function approach, such that, for all admissible uncertain parameters and missing measurements, the resulting filtering error system is robustly stochastically stable and a guaranteed H∞ performance constraint is achieved. Furthermore, the optimal H∞ performance index is subsequently obtained by solving a convex optimisation problem and the missing measurements effects on the H∞ performance are evaluated. A numerical example is given to illustrate the feasibility and effectiveness of the proposed filter. [ABSTRACT FROM AUTHOR]

Objective: To investigate the expression of cluster of differentiation 44 variant 6 (CD(44V6)) and proliferating cell nuclear antigen (PCNA) in ocular squamous cell carcinomas., Methods: Streptavidin-biotin complex (SABC) immunohistochemistry was used to explore the expression of CD(44V6) and PCNA in 35 cases of ocular squamous cell carcinomas, 20 cases of papillomas, and 11 cases of normal eyelid tissue., Results: The CD(44V6) positive rate was 62.9% (22/35) in ocular squamous cell carcinomas, 15.0% (3/20) in papillomas, but not detectable in the 11 cases of normal eyelid tissue. The positive expression rates of CD(44V6) in ocular squamous cell carcinomas were significantly higher than in benign tumors (chi(2) = 11.57, P < 0.01) or control tissue (P = 0.001), and the positive expression rates of CD(44V6) in metastasis were significantly higher than without metastasis (P = 0.049). PCNA labeling indexes (PI) in tumors with CD(44V6) expression were significantly higher than those without (t = 20.21, P < 0.01)., Conclusions: Overexpression of CD(44V6) is correlated with the progress and metastasis of ocular squamous cell carcinomas. CD(44V6) protein positive staining is associated with high PI. CD(44V6) and PCNA are useful for evaluating prognosis.

Objective: To investigate the relationship between P16 gene (the tumor suppressor gene) and the bcl-2 gene (the apoptosis inhibitor gene) and the incidence and development of malignant eyelid tumors., Methods: The streptavidin-biotin-peroxidase complex immunohistochemistry method was used to study the expression of P16 gene and the bcl-2 gene in 96 cases of malignant eyelid tumors., Results: Among the 96 cases, there were 40 basal cell carcinomas (BCCs), 33 squamous carcinomas and 23 sebaceous carcinoma, with P16 protein positive (nuclear staining) rates 70%, 54.6% and 56.5%, respectively. The P16 positive rate was negatively correlated with the degree of tumor histological differentiation, and the rate difference between the high differentiated carcinomas was significant (P < 0.05). Positive Bcl-2 protein expression was detected in the cytoplasm. All 40 BCC cases were Bcl-2 positive, and nearly all of the tumor cells showed positive cytoplasmic expression, while in the 33 squamous cell carcinoma cases only one showed positive focal reaction, and the staining in the other 32 cases was relatively faint. None of the 23 sebaceous carcinomas expressed Bcl-2., Conclusions: The expression of the P16 protein was related to the occurrence and degree of differentiation of malignant eyelid tumors. The overexpression of the Bcl-2 protein suggests that suppression of apoptosis might play a role in the tumorigenesis of BCC.