On compact vector formats in the solution of the chemical master equation with backward differentiation

A stochastic chemical system with multiple types of molecules interacting through reaction channels can be modeled as a continuous‐time Markov chain with a countably infinite multidimensional state space. Starting from an initial probability distribution, the time evolution of the probability distribution associated with this continuous‐time Markov chain is described by a system of ordinary differential equations, known as the chemical master equation (CME). This paper shows how one can solve the CME using backward differentiation. In doing this, a novel approach to truncate the state space at each time step using a prediction vector is proposed. The infinitesimal generator matrix associated with the truncated state space is represented compactly, and exactly, using a sum of Kronecker products of matrices associated with molecules. This exact representation is already compact and does not require a low‐rank approximation in the hierarchical Tucker decomposition (HTD) format. During transient analysis, compact solution vectors in HTD format are employed with the exact, compact, and truncated generated matrices in Kronecker form, and the linear systems are solved with the Jacobi method using fixed or adaptive rank control strategies on the compact vectors. Results of simulation on benchmark models are compared with those of the proposed solver and another version, which works with compact vectors and highly accurate low‐rank approximations of the truncated generator matrices in quantized tensor train format and solves the linear systems with the density matrix renormalization group method. Results indicate that there is a reason to solve the CME numerically, and adaptive rank control strategies on compact vectors in HTD format improve time and memory requirements significantly.     

Supply chain interactions due to store-brand introductions: The impact of retail competition

Store-brand products are of increasing importance in retailing, often causing channel conflict as they compete with national brands. Focusing on the interactions that arise in single-manufacturer single-retailer settings, previous research suggests that one main driver of store-brand profitability to the retailer is that it leads to a reduction of the national-brand wholesale price. Under retail competition, the Robinson Patman Act then introduces an interesting trade-off: A retailer that introduces a store brand incurs the associated costs and risks, while sharing this benefit with its competition. We show that the resulting interactions can cause retailers to play “chicken”, either of them preferring a store-brand introduction by the competitor. Such interactions do not arise in channels with a single retailer, as has been the object of most previous research, and we show that some of the key insights derived from single-retailer models fail to hold when retailers compete. We conduct a numeric study, and our findings suggest that retailers are more likely to randomize their store-brand introduction strategies when customers have strong store preferences, and when the retailers’ store-brand products are similar to the national-brand product in terms of customer valuations and production cost.     

Numerical differentiation for high orders by an integration method

This paper mainly studies the numerical differentiation by integration method proposed first by Lanczos. New schemes of the Lanczos derivatives are put forward for reconstructing numerical derivatives for high orders from noise data. The convergence rate of these proposed methods is as the noise level δ→0. Numerical examples show that the proposed methods are stable and efficient.     

A wavelet-Galerkin method for high order numerical differentiation

Numerical differentiation is a classical ill-posed problem. In this paper, we propose a wavelet-Galerkin method for high order numerical differentiation. By an appropriate choice of the regularization parameter an order optimal stability estimate of Hölder type is obtained. Some numerical examples show that the method is effective and stable.     

Mapped barycentric Chebyshev differentiation matrix method for the solution of regular Sturm-Liouville problems

In this paper, using spectral differentiation matrix and an elimination treatment of boundary conditions, Sturm-Liouville problems (SLPs) are discretized into standard matrix eigenvalue problems. The eigenvalues of the original Sturm-Liouville operator are approximated by the eigenvalues of the corresponding Chebyshev differentiation matrix (CDM). This greatly improves the efficiency of the classical Chebyshev collocation method for SLPs, where a determinant or a generalized matrix eigenvalue problem has to be computed. Furthermore, the state-of-the-art spectral method, which incorporates the barycentric rational interpolation with a conformal map, is used to solve regular SLPs. A much more accurate mapped barycentric Chebyshev differentiation matrix (MBCDM) is obtained to approximate the Sturm-Liouville operator. Compared with many other existing methods, the MBCDM method achieves higher accuracy and efficiency, i.e., it produces fewer outliers. When a large number of eigenvalues need to be computed, the MBCDM method is very competitive. Hundreds of eigenvalues up to more than ten digits accuracy can be computed in several seconds on a personal computer.     

Empirical Modeling of a Hydraulic Actuator in a Vehicle Control System

The pressure information of a hydraulic actuator plays a key role in modern vehicle control and fault diagnosis. The difficulty in measuring pressure directly naturally motivates such an indirect approach as an observer whose accuracy depends heavily upon the availability of a high fidelity model of a hydraulic actuator. Notwithstanding its success in understanding the dynamics of the first principle model of a hydraulic actuator, it is not suited to controller/observer design due to its complexity. This paper presents an alternative to the first principle modeling methodology: an empirical approach to hydraulic actuator modeling. Linear and nonlinear system identification techniques are applied to obtain low-order models of a hydraulic actuator. Experimental results show how the empirical models reproduce the key features of a hydraulic actuator with sufficient accuracy.     

Investigating How Organic Solvents Affect Tissue Culture Polystyrene Surfaces through Responses of Mesenchymal Stem Cells

Polymer coating of tissue culture polystyrene (TCPS) surfaces promotes their biofunctionality, which can aid manipulation of cellular functions. However, the effect of the solvent used for polymer coating is yet to be elucidated. In this study, solvent‐treated TCPS surfaces using water, methanol, ethanol, 2‐propanol, and dimethyl sulfoxide are fabricated. Solvent treatment of TCPS surfaces is performed by spreading solvents onto the surfaces and allowing them to dry. Solvent treatment changes the surface roughness and wettability, depending on the kind of solvents. In addition, these surface property changes affected the extension, proliferation, and differentiation of human bone marrow–derived mesenchymal stem cells. These results suggest that solvent selection for polymer coating is crucial in the regulation of cell responses. Further, treatment with an appropriate solvent can result in a more suitable culture environment for modulating cellular functions.     

Jordan标准型过渡矩阵的一种新算法

本文通过矩阵函数微分的相关知识,给出了 Jordan标准型过渡矩阵的一种新算法.