The spectral conjugate gradient (SCG) method is one of the most commonly used methods to solve large- scale nonlinear unconstrained optimization problems. It is also the research and application hot spot of optimization theorists and optimization practitioners. In this paper, a new hybrid spectral conjugate gradient method is proposed based on the classical nonlinear spectral conjugate gradient method. A new parameter  is given. Under the usual assumptions, the descending direction independent of any line search is generated, and it has good convergence performance under the strong Wolfe line  search condition . On a set of test problems, the numerical results show that the algorithm is effective.

Local thermal enhancement in target tissue is of great interest in tumor hyperthermia. In this study, we proposed a brand-new thermal enhancement protocol for tumor hyperthermia using heat generated from thermogenesis of capsaicin, which can safely deliver a totally localized heating to target tissue. A healthy male volunteer was recruited, whose partial areas of opisthenar and forearm were smeared with 1% (w/w) capsaicin solution, to determine the increase of thermogenesis in local area of human body. In addition, animal experiments on several healthy Kunming (KM) mice (20-22g) were performed to test the feasibility of this capsaicin based thermal enhancement method. Preliminary experiments on the volunteer showed an effective temperature increase in the skin area smeared with capsaicin solution. Animal experiments indicated that distinct enhancement in heating effect presents in the target tissue of mice where capsaicin solution was introduced. The thermal enhancement ability of capsaicin, therefore, suggests that capsaicin can be used as a potential therapeutic adjuvant to locally enhance heating effects in target tissue during tumor hyperthermia.

Treatment planning based on numerical simula-tion before cryosurgery is an indispensable way to achieve exactly killing of tumors. Furthermore, intraoperative pre-diction based on monitoring results can lead to more accu-rate ablation. However, conventional serial program is diffi-cult to meet the challenge of real-time assistance with com-plex treatment plans. In this study, two parallel numerical algorithms, i.e. parallel explicit scheme and Alternating Direction Implicit (ADI) scheme using the block pipelined method for parallelization, based on an effective heat capac-ity method are established to solve three-dimensional phase change problems in biological tissues subjected to multiple cryoprobes. The validation, speedups as well as efficiencies of parallelized computations of the both schemes were com-pared. It was shown that the parallel algorithms developed here can perform rapid prediction of temperature distribu-tion for cryosurgery, and that parallel computing is hopeful to assist cryosurgeons with prospective parallel treatment planning in the near future.