Application of quantitative structure-activity relationship to the determination of binding constant based on fluorescence quenching

Quantitative structure-activity relationship (QSAR) model was used to predict and explain binding constant (log K) determined by fluorescence quenching. This method allowed us to predict binding constants of a variety of compounds with human serum albumin (HSA) based on their structures alone. Stepwise multiple linear regression (MLR) and nonlinear radial basis function neural network (RBFNN) were performed to build the models. The statistical parameters provided by the MLR model (R²=0.8521, RMS=0.2678) indicated satisfactory stability and predictive ability while the RBFNN predictive ability is somewhat superior (R²=0.9245, RMS=0.1736). The proposed models were used to predict the binding constants of two bioactive components in traditional Chinese medicines (isoimperatorin and chrysophanol) whose experimental results were obtained in our laboratory and the predicted results were in good agreement with the experimental results. This QSAR approach can contribute to a better understanding of structural factors of the compounds responsible for drug-protein interactions, and can be useful in predicting the binding constants of other compounds.     

Evolution of first-order sidebands from multiple FWM processes in HiBi optical fibers

The generation of two idler waves inside a high birefringent (HiBi) optical fiber through three four-wave mixing (FWM) processes is studied theoretically. The coupled-equations for the field amplitudes are derived and analytically solved, in the co-polarized and orthogonal polarization schemes. The obtained solutions take into account the delayed Raman response of the medium. The polarization sensitivity of the generation of the idler waves is analyzed. Results show that the stimulated Raman scattering does not change the efficiency of the idler wave generation in the co-polarized scheme, whereas in the orthogonal polarization scheme that nonlinear process decreases the efficiency of the four-wave mixing processes. Results also show that this set of multiple four-wave mixing processes is physically quite different from the typical single or dual pump four-wave mixing configurations. Findings show that the power transfer from the pumps to the idler fields can lead to a monotonous growth, or a periodic evolution of the sidebands along the fiber. Results show that the process efficiency varies greatly with the angle between the two pump polarizations.     

Chaos synchronization and encoding in coupled semiconductor lasers of multiple modulated time delays

We numerically investigate the synchronization performance of unidirectionally and bidirectionally coupled chaotic semiconductor lasers subject to multiple modulated time delays optical feedbacks. Moreover, by studying the autocorrelation function of the coherent feedback semiconductor laser output, we find that the signatures of time delays can be erased in systems incorporating modulated feedback time delays, which largely improve the system security. Finally, chaos masking switching (CMS) is utilized to examine the communication ability. Numerical results indicate that the messages could be successfully recovered both in unidirectionally and bidirectionally coupled lasers, which confirms the possibility of applying multiple modulated delay system in optical chaos secure communication.     

An iterative approach to solve multiobjective linear fractional programming problems

This paper suggests an iterative parametric approach for solving multiobjective linear fractional programming (MOLFP) problems which only uses linear programming to obtain efficient solutions and always converges to an efficient solution. A numerical example shows that this approach performs better than some existing algorithms. Randomly generated MOLFP problems are also solved to demonstrate the performance of new introduced algorithm.     

Solving a bi-objective Transportation Location Routing Problem by metaheuristic algorithms

In this work we consider a Transportation Location Routing Problem (TLRP) that can be seen as an extension of the two stage Location Routing Problem, in which the first stage corresponds to a transportation problem with truck capacity. Two objectives are considered in this research, reduction of distribution cost and balance of workloads for drivers in the routing stage. Here, we present a mathematical formulation for the bi-objective TLRP and propose a new representation for the TLRP based on priorities. This representation lets us manage the problem easily and reduces the computational effort, plus, it is suitable to be used with both local search based and evolutionary approaches. In order to demonstrate its efficiency, it was implemented in two metaheuristic solution algorithms based on the Scatter Tabu Search Procedure for Non-Linear Multiobjective Optimization (SSPMO) and on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) strategies. Computational experiments showed efficient results in solution quality and computing time.     

Flexible capacity strategy with multiple market periods under demand uncertainty and investment constraint

We establish a flexible capacity strategy model with multiple market periods under demand uncertainty and investment constraints. In the model, a firm makes its capacity decision under a financial budget constraint at the beginning of the planning horizon which embraces n market periods. In each market period, the firm goes through three decision-making stages: the safety production stage, the additional production stage and the optimal sales stage. We formulate the problem and obtain the optimal capacity, the optimal safety production, the optimal additional production and the optimal sales of each market period under different situations. We find that there are two thresholds for the unit capacity cost. When the capacity cost is very low, the optimal capacity is determined by its financial budget; when the capacity cost is very high, the firm keeps its optimal capacity at its safety production level; and when the cost is in between of the two thresholds, the optimal capacity is determined by the capacity cost, the number of market periods and the unit cost of additional production. Further, we explore the endogenous safety production level. We verify the conditions under which the firm has different optimal safety production levels. Finally, we prove that the firm can benefit from the investment only when the designed planning horizon is longer than a threshold. Moreover, we also derive the formulae for the above three thresholds.     

A synergy of multicriteria techniques to assess additive value models

The assessment of additive value functions in Multicriteria Decision Aid (MCDA) has to face issues of legitimacy and technical difficulties when real decision makers are involved. This paper presents a synergy of three complementary techniques to assess additive models on the whole criteria space. The synergy includes a revised MACBETH technique, the standard MAUT trade-off analysis and UTA-based methods for the assessment of both the marginal value functions and the weighting factors. The paper uses a set of original robustness measures and rules associated with revised MACBETH and UTA in order to manage multiple linear programming solutions and to extract robust conclusions from them. Finally, to illustrate the methods’ synergy, an application example is presented, dealing with the planning of metro extension lines.     

A multiple window scan statistic for time series models

In this article we extend the results derived for scan statistics in Wang and Glaz (2014) for independent normal observations. We investigate the performance of two approximations for the distribution of fixed window scan statistics for time series models. An R algorithm for computing multivariate normal probabilities established in Genz and Bretz (2009) can be used along with proposed approximations to implement fixed window scan statistics for ARMA models. The accuracy of these approximations is investigated via simulation. Moreover, a multiple window scan statistic is defined for detecting a local change in the mean of a Gaussian white noise component in ARMA models, when the appropriate length of the scanning window is unknown. Based on the numerical results, for power comparisons of the scan statistics, we can conclude that when the window size of a local change is unknown, the multiple window scan statistic outperforms the fixed window scan statistics.