Dynamical thermal effects in InGaAsP microtubes at telecom wavelengths

We report on the observation of a dynamical thermal effect in InGaAsP microtubes at telecom wavelengths. The microtubes are fabricated by releasing a strained semiconductor bilayer and are picked up by abruptly tapered optical fibers for subsequent coupling with adiabatically tapered optical fibers. As a result of absorption by InAs quantum dots embedded in the tube structure, these microtubes show dynamical thermal effects at wavelengths around 1525 nm and 1578 nm, while they are passive at longer wavelengths near 1634 nm. The photon absorption induced thermal effect is visualized by generating a pair of microbottles. The dynamical thermal effect can be avoided or exploited for passive or active applications by utilizing appropriate resonance wavelengths.     

New voltammetric strategy for simultaneous determination of norepinephrine, acetaminophen, and folic acid using a 5-amino-3′,4′-dimethoxy-biphenyl-2-ol/carbon nanotube paste electrode

A carbon paste electrode modified with 5-amino-3??,4??-dimethoxy-biphenyl-2-ol and carbon nanotubes was used for the sensitive voltammetric determination of norepinephrine (NE). The electrochemical response characteristics of the modified electrode toward NE, acetaminophen (AC), and folic acid (FA) were investigated by cyclic and square wave voltammetry (SWV). The results show an efficient catalytic activity of the electrode for the electrooxidation of NE, which leads to lowering its overpotential more than 160?mV. The modified electrode exhibits an efficient electron-mediating behavior together with well-separated oxidation peaks for NE, AC, and FA. Under the optimum pH of 7.0 in 0.1?M phosphate buffer solution, the SWV anodic peak current showed a linear relation vs. NE concentration in the range of 15.0 to 1,000.0???M with a detection limit of 8.0???M.     

A novel numerical method and its convergence for nonlinear delay Volterra integro-differential equations

In this paper, we suggest a convergent numerical method for solving nonlinear delay Volterra integro-differential equations. First, we convert the problem into a continuous-time optimization problem and then use a shifted pseudospectral method to discrete the problem. Having solved the last problem, we can achieve the pointwise and continuous approximate solutions for the main delay Volterra integro-differential equations. Here, we analyze the convergence of the method and solve some numerical examples to show the efficiency of the method.     

Classification of skew‐Hadamard matrices of order 32 and association schemes of order 31

Using a backtracking algorithm along with an essential change to the rows of representatives of known 13 710 027 equivalence classes of Hadamard matrices of order 32, we make an exhaustive computer search feasible and show that there are exactly 6662 inequivalent skew‐Hadamard matrices of order 32. Two skew‐Hadamard matrices are considered SH ‐equivalent if they are similar by a signed permutation matrix. We determine that there are precisely 7227 skew‐Hadamard matrices of order 32 up to SH ‐equivalence. This partly settles a problem posed by Kim and Solé. As a consequence, we provide the classification of association schemes of order 31.     

On a class of quaternary complex Hadamard matrices

We introduce a class of regular unit Hadamard matrices whose entries consist of two complex numbers and their conjugates for a total of four complex numbers. We then show that these matrices are contained in the Bose–Mesner algebra of an association scheme arising from skew Paley matrices.     

Neuro-fuzzy based constraint programming

Constraint programming models appear in many sciences including mathematics, engineering and physics. These problems aim at optimizing a cost function joint with some constraints. Fuzzy constraint programming has been developed for treating uncertainty in the setting of optimization problems with vague constraints. In this paper, a new method is presented into creation fuzzy concept for set of constraints. Unlike to existing methods, instead of constraints with fuzzy inequalities or fuzzy coefficients or fuzzy numbers, vague nature of constraints set is modeled using learning scheme with adaptive neural-fuzzy inference system (ANFIS). In the proposed approach, constraints are not limited to differentiability, continuity, linearity; also the importance degree of each constraint can be easily applied. Unsatisfaction of each weighted constraint reduces membership of certainty for set of constraints. Monte-Carlo simulations are used for generating feature vector samples and outputs for construction of necessary data for ANFIS. The experimental results show the ability of the proposed approach for modeling constrains and solving parametric programming problems.     

Linked systems of symmetric group divisible designs

We introduce the concept of linked systems of symmetric group divisible designs. The connection with association schemes is established, and as a consequence we obtain an upper bound on the number of symmetric group divisible designs which are linked. Several examples of linked systems of symmetric group divisible designs are provided.     

Quasi-Newton methods for multiobjective optimization problems

This work is an attempt to develop multiobjective versions of some well-known single objective quasi-Newton methods, including BFGS, self-scaling BFGS (SS-BFGS), and the Huang BFGS (H-BFGS). A comprehensive and comparative study of these methods is presented in this paper. The Armijo line search is used for the implementation of these methods. The numerical results show that the Armijo rule does not work the same way for the multiobjective case as for the single objective case, because, in this case, it imposes a large computational effort and significantly decreases the speed of convergence in contrast to the single objective case. Hence, we consider two cases of all multi-objective versions of quasi-Newton methods: in the presence of the Armijo line search and in the absence of any line search. Moreover, the convergence of these methods without using any line search under some mild conditions is shown. Also, by introducing a multiobjective subproblem for finding the quasi-Newton multiobjective search direction, a simple representation of the Karush–Kuhn–Tucker conditions is derived. The H-BFGS quasi-Newton multiobjective optimization method provides a higher-order accuracy in approximating the second order curvature of the problem functions than the BFGS and SS-BFGS methods. Thus, this method has some benefits compared to the other methods as shown in the numerical results. All mentioned methods proposed in this paper are evaluated and compared with each other in different aspects. To do so, some well-known test problems and performance assessment criteria are employed. Moreover, these methods are compared with each other with regard to the expended CPU time, the number of iterations, and the number of function evaluations.     

Continuous ant colony system and tabu search algorithms hybridized for global minimization of continuous multi-minima functions

A new hybrid optimization method, combining Continuous Ant Colony System (CACS) and Tabu Search (TS) is proposed for minimization of continuous multi-minima functions. The new algorithm incorporates the concepts of promising list, tabu list and tabu balls from TS into the framework of CACS. This enables the resultant algorithm to avoid bad regions and to be guided toward the areas more likely to contain the global minimum. New strategies are proposed to dynamically tune the radius of the tabu balls during the execution and also to handle the variable correlations. The promising list is also used to update the pheromone distribution over the search space. The parameters of the new method are tuned based on the results obtained for a set of standard test functions. The results of the proposed scheme are also compared with those of some recent ant based and non-ant based meta-heuristics, showing improvements in terms of accuracy and efficiency.     

New method for attachment of biomolecules to porous silicon

Biomolecules have been attached to porous silicon by a new linking method that forms a direct Si-C bond on the surface and retains the photoluminescence of the porous silicon.