A general nonlinear framework for an Ishikawa-hybrid proximal point algorithm using the notion of A, η -accretive is developed. Convergence analysis for the algorithm of solving a nonlinear set-valued inclusions problem and existence analysis of solution for the nonlinear set-valued inclusions problem are explored along with some results on the resolvent operator corresponding to A, η -accretive mapping due to Lan-Cho-Verma in Banach space. The result that sequence {x n } generated by the algorithm converges linearly to a solution of the nonlinear set-valued inclusions problem with the convergence rate θ is proved.

The purpose of this paper is 1 a general nonlinear mixed set-valued inclusion framework for the over-relaxed A-proximal point algorithm based on the A, η -accretive mapping is introduced, and 2 it is applied to the approximation solvability of a general class of inclusions problems using the generalized resolvent operator technique due to Lan-Cho-Verma, and the convergence of iterative sequences generated by the algorithm is discussed in q-uniformly smooth Banach spaces. The results presented in the paper improve and extend some known results in the literature.

Aims: The objective was to investigate current situation and risk factors of vancomycin (VAN)-induced acute kidney injury (VI-AKI) in elderly Chinese patients, to assesse the outcomes and its risk factors of patients who developed VI-AKI, in order to provide suggestions for improving the prevention and treatment of VI-AKI in elderly Chinese patients. Method: We retrospectively identified elderly inpatients who received more than 3 doses of VAN therapy. We compared the VI-AKI with NO-AKI patients. The definition of VI-AKI is developing AKI during VAN therapy or within 3 days after withdrawal of VAN. Results: 647 of the 862 elderly inpatients were included. Among those excluded, (89.3%, 192/215) were excluded because of a lack of data on serum creatinine (SCr). Among the included patients, 32.5% (210/647) patients received TDM during VAN therapy. The inadequate TDM rate was 66.9% (424/634) and rate of correct TDM was 3.9% (25/634). 102 patients had confirmed VI-AKI, with an incidence of 15.8% (102/647). Multiple logistic regression analysis revealed that hyperuricemia ([OR]=3.045;p=0.000), mechanical ventilation ([OR]=1.906;p=0.022) and concomitant vasopressor therapy ([OR]=1.919,p=0.027) were independent risk factors for VI-AKI; in addition, serum albumin valley ([OR] =0.885;p=0.000) was determined to be independent protective factor for VI-AKI. Conclusions: The elderly Chinese patients treated with VAN exist the situations below: insufficient monitoring of SCr, inadequate VAN TDM rate and incorrect monitor time. We recommend hospital managers to increase investment in clinical pharmacists to strength professional management. Patients concomitant with hyperuricemia, mechanical ventilation and vasopressor therapy should be paid more attention and a higher serum albumin was more recommend.

ANN using BP is widely used in power load forecasting. But there are some existed problem of the BP algorithm: ① Convergence speed is slow, usually convergence needs more than one thousand times; ② Objective function is prone to getting into local minimum.. How to overcome the shortcoming that convergence speed is slow and network is prone to trapping in local minimum has not been resolved. Training algorithm is put forward in the paper, which is based on three adjustable parameters activation function. Although BPAdjustable activation function algorithm raised convergence speed of neural network, the essence of algorithm is to seek the most optimal value following the direction of degressive grads. When initial value is confirmed, the decent course is also confirmed. So the problem of trending local minimum also exists, and it has great contact with confirming initial value. The paper says that BPAA algorithm has the good ability of searching in partial area and ability of searching in global area. So, it can combine with two algorithms to make the best of LOA (Logistic optimal algorithm)'s fully searching ability and BP-AA algorithm's partial searching ability. Using BP-AA algorithm to resolve the weight value and parameters in neutral network. When getting in partial least, using LOA algorithm can choose new initial value of every parameter to jump out partial least. Therefore, the paper raised the Adjustable activation function and grad optimism training algorithm embedded Logistic chaotic mapping in BP network's training. This algorithm is not only efficient but also difficult to get in local minimum. The algorithm can converge to fully optimum with probability of 1. it is called BP-AAEC (Adjustable Activation function and Embedding Chaos algorithm) Algorithm. Then, combined with randomness and ergodic property of chaos, the hybrid training algorithm embedded dual searching of chaos mapping is brought forward. Capability testing and experiment has approved that the improved algorithm can achieve the requirement.