On the Differential Polynomial of a Graph

We introduce the differential polynomial of a graph. The differential polynomial of a graph G of order n is the polynomial B(G; x) :=∑?(G)k=-nB_k(G) x~(n+k), where B_k(G) denotes the number of vertex subsets of G with differential equal to k. We state some properties of B(G;x) and its coefficients.In particular, we compute the differential polynomial for complete, empty, path, cycle, wheel and double star graphs. We also establish some relationships between B(G; x) and the differential polynomials of graphs which result by removing, adding, and subdividing an edge from G.     

Well‐posedness of fractional integro‐differential equations in vector‐valued functional spaces

We study the well‐posedness of the fractional differential equations with infinite delay on Lebesgue–Bochner spaces and Besov spaces , where A and B are closed linear operators on a Banach space X satisfying ,  and . Under suitable assumptions on the kernels a and b, we completely characterize the well‐posedness of in the above vector‐valued function spaces on by using known operator‐valued Fourier multiplier theorems. We also give concrete examples where our abstract results may be applied.     

Electrochemical Characterization and Voltammetric Determination of Benzoyl Derivatives of Phenobarbital Using Glassy Carbon Electrode

The electrochemical behavior of a number of benzoyl barbiturates was studied using a glassy carbon electrode (GCE). The kinetics of the electrode process is determined, the contribution of physical adsorption to the electrochemical process is estimated, and the mechanism of the possible electrochemical reaction is proposed. It is shown that the electrochemical reduction potentials of benzoyl phenobarbital derivatives are determined by the LUMO energies, calculated by the B3LYP 6‐311+G method. It is established that the process is quasi‐reversible, complicated by adverse reactions. The influence of halogen type and its position in the benzoyl residue of the studied substances on the analytical signal is established. The effective values of the dissociation constants of various forms of benzoyl derivatives were calculated using the example of halonal, for which the values 3.16 ? 10^?8 and 6.31 ? 10^?12, respectively, were found.     

Implicit–explicit schemes for nonlinear nonlocal equations with a gradient flow structure in one space dimension

Nonlinear convection–diffusion equations with nonlocal flux and possibly degenerate diffusion arise in various contexts including interacting gases, porous media flows, and collective behavior in biology. Their numerical solution by an explicit finite difference method is costly due to the necessity of discretizing a local spatial convolution for each evaluation of the convective numerical flux, and due to the disadvantageous Courant–Friedrichs–Lewy (CFL) condition incurred by the diffusion term. Based on explicit schemes for such models devised in the study of Carrillo et al. a second‐order implicit–explicit Runge–Kutta (IMEX‐RK) method can be formulated. This method avoids the restrictive time step limitation of explicit schemes since the diffusion term is handled implicitly, but entails the necessity to solve nonlinear algebraic systems in every time step. It is proven that this method is well defined. Numerical experiments illustrate that for fine discretizations it is more efficient in terms of reduction of error versus central processing unit time than the original explicit method. One of the test cases is given by a strongly degenerate parabolic, nonlocal equation modeling aggregation in study of Betancourt et al. This model can be transformed to a local partial differential equation that can be solved numerically easily to generate a reference solution for the IMEX‐RK method, but is limited to one space dimension.     

时间延迟扩散-波动分数阶微分方程有限差分方法

本文提出求解时间延迟扩散-波动分数阶微分方程有限差分方法，方程中对时间的一阶导函数用α阶（0 < α < 1） Caputo分数阶导数代替.文章中利用Lubich线性多步法对分数阶微分进行差分离散，且文章利用分段区间证明该方法是稳定的，且利用数值实验加以验证.