一类金融混沌系统的线性控制模型

针对一类金融混沌系统,建立存款利率线性控制模型、投资需求线性控制模型和综合线性控制模型,运用线性反馈控制的方法调整导致系统产生混沌的参数组合,实现对系统稳定性的有效控制.首先对控制模型进行动力学分析,从理论上分析控制模型的反馈系数的取值范围;然后通过数值模拟证明方法的可行性;最后讨论线性反馈控制对金融危机宏观调控的实际意义.     

Kinetically Controlled Layer-by-Layer Stacking of Metal Oxide 2D Nanosheets

An efficient chemical way to finely control the layer-by-layer stacking of inorganic nanosheets (NS) is developed by tuning the type and composition of intercalant ion, and the reaction temperature for restacking process. The finely controlled stacking of NS relies on a kinetic control of the self-assembly of NS in the presence of coordinating organic cations. A critical role of organic cations in this assembly highlights the importance of the appropriate activation energy. Of prime importance is that a fine-control of the interstratification of 2D NS is highly effective not only in tailoring its pore structure but also in enhancing its electrode activity. The present study clearly demonstrates that the kinetically controlled restacking of NS provides a facile and powerful method to tailor their stacking number and functionality.     

Dynamic Modulation of Enzyme Activity by Near-Infrared Light

Engineering near-infrared (NIR) light-sensitive enzymes remains a huge challenge. A photothermal effect-associated method is developed for tailoring the enzymatic activity of enzymes by exposure to NIR light. An ultrasmall platinum nanoparticle was anchored in an enzyme to generate local heating upon NIR irradiation, which enhanced the enzyme activity without increasing bulk temperature. Following NIR irradiation, the enzyme activity was tailored rapidly and reversibly, and was modulated by varying laser power density and irradiation time. Four enzymes were engineered, including glucoamylase, glucose oxidase, catalase, and proteinase K with NIR-light sensitivity, and demonstrated their utility in practical applications such as photolithography and NIR light-responsive antibacterial or anticancer actions. Our investigation suggests that this approach could be broadly used to engineer enzymes with NIR-light sensitivity for many biological applications.     

Qualitative and quantitative analysis of chemical constituents in Ardisiae Japonicae Herba

Ardisiae Japonicae Herba is a well‐known traditional Chinese medicine for the treatment of bronchitis conjunctivitis, pneumonia, and trauma. In this work, a high‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry method was first established for the separation and structural identification of the chemical constituents in Ardisiae Japonicae Herba. A total of 15 compounds including coumarins, flavonoid glycosides, and catechins were identified or tentatively characterized based on their chromatographic behaviors and mass spectral fragmentation and by comparisons with the reference standards. Furthermore, a simple high‐performance liquid chromatography with diode array detection method was developed for the simultaneous determination of five major constituents. Results obtained from method validation, including linearity, precision, repeatability, stability, and recovery, showed that the established method was reliable and accurate. Bergenin and quercitrin were found to be the most abundant constituents and could be served as chemical markers for quality control of Ardisiae Japonicae Herba.     

Optimal investment strategies for participating contracts

Participating contracts are popular insurance policies, in which the payoff to a policyholder is linked to the performance of a portfolio managed by the insurer. We consider the portfolio selection problem of an insurer that offers participating contracts and has an S-shaped utility function. Applying the martingale approach, closed-form solutions are obtained. The resulting optimal strategies are compared with portfolio insurance hedging strategies (CPPI and OBPI). We also study numerical solutions of the portfolio selection problem with constraints on the portfolio weights.     

Evolutionary Boussinesq model with nonmonotone friction and heat flux boundary conditions

In this paper we prove the existence and regularity of a solution to a two-dimensional system of evolutionary hemivariational inequalities which describes the Boussinesq model with nonmonotone friction and heat flux. We use the time retardation and regularization technique, combined with a regularized Galerkin method, and recent results from the theory of hemivariational inequalities.     

Phase II monitoring of changes in mean from high‐dimensional data

The generalized T² chart (GT‐chart), which is composed of the T² statistic based on a small number of principal components and the remaining components, is a popular alternative to the traditional Hotelling's T² control chart. However, the application of the GT‐chart to high‐dimensional data, which are now ubiquitous, encounters difficulties from high dimensionality similar to other multivariate procedures. The sample principal components and their eigenvalues do not consistently estimate the population values, and the GT‐chart relying on them is also inconsistent in estimating the control limits. In this paper, we investigate the effects of high dimensionality on the GT‐chart and then propose a corrected GT‐chart using the recent results of random matrix theory for the spiked covariance model. We numerically show that the corrected GT‐chart exhibits superior performance compared to the existing methods, including the GT‐chart and Hotelling's T² control chart, under various high‐dimensional cases. Finally, we apply the proposed corrected GT‐chart to monitor chemical processes introduced in the literature.     

A note on functional a posteriori estimates for elliptic optimal control problems

In this work, new results on functional type a posteriori estimates for elliptic optimal control problems with control constraints are presented. More precisely, we derive new, sharp, guaranteed, and fully computable lower bounds for the cost functional in addition to the already existing upper bounds. Using both, the lower and the upper bounds, we arrive at two‐sided estimates for the cost functional. We prove that these bounds finally lead to sharp, guaranteed and fully computable upper estimates for the discretization error in the state and the control of the optimal control problem. First numerical tests are presented confirming the efficiency of the a posteriori estimates derived. © 2016 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 33: 403–424, 2017     

Error Estimates for a Class of Elliptic Optimal Control Problems

In this article, functional type a posteriori error estimates are presented for a certain class of optimal control problems with elliptic partial differential equation constraints. It is assumed that in the cost functional the state is measured in terms of the energy norm generated by the state equation. The functional a posteriori error estimates developed by Repin in the late 1990s are applied to estimate the cost function value from both sides without requiring the exact solution of the state equation. Moreover, a lower bound for the minimal cost functional value is derived. A meaningful error quantity coinciding with the gap between the cost functional values of an arbitrary admissible control and the optimal control is introduced. This error quantity can be estimated from both sides using the estimates for the cost functional value. The theoretical results are confirmed by numerical tests.     

Finite Difference Method for an Optimal Control Problem for a Nonlinear Time-dependent Schrödinger Equation

The finite difference method is applied to an optimal control problem for a system governed by a nonlinear Schrödinger equation with a complex coe?cient. The optimal control problem is discretized by the finite difference method, the error estimate for the finite difference scheme is established and the convergence of difference approximations of the optimal control according to the functional is proved.