Application of maximum likelihood multivariate curve resolution to noisy data sets

In this work, two different maximum likelihood approaches for multivariate curve resolution based on maximum likelihood principal component analysis (MLPCA) and on weighted alternating least squares (WALS) are compared with the standard multivariate curve resolution alternating least squares (MCR‐ALS) method. To illustrate this comparison, three different experimental data sets are used: the first one is an environmental aerosol source apportionment; the second is a time‐course DNA microarray, and the third one is an ultrafast absorption spectroscopy. Error structures of the first two data sets were heteroscedastic and uncorrelated, and the difference between them was in the existence of missing values in the second case. In the third data set about ultrafast spectroscopy, error correlation between the values at different wavelengths is present. The obtained results confirmed that the resolved component profiles obtained by MLPCA‐MCR‐ALS are practically identical to those obtained by MCR‐WALS and that they can differ from those resolved by ordinary MCR‐ALS, especially in the case of high noise. It is shown that methods that incorporate uncertainty estimations (such as MLPCA‐ALS and MCR‐WALS) can provide more reliable results and better estimated parameters than unweighted approaches (such as MCR‐ALS) in the case of the presence of high amounts of noise. The possible advantage of using MLPCA‐MCR‐ALS over MCR‐WALS is then that the former does not require changing the traditional MCR‐ALS algorithm because MLPCA is only used as a preliminary data pretreatment before MCR analysis. Copyright © 2013 John Wiley & Sons, Ltd.     

Nonlinear modeling and performance analysis of a closed-loop supply chain in the presence of stochastic noise

ABSTRACT

We study four-echelon supply chains consisting of manufacturer, wholesaler, retailer and customer with recovery center as hybrid recycling channels. In order to gain a larger market share, the retailer often takes the sales as a decision-making variable. For this purpose, in this supply chain, the retailer limits the forecast of market demand in future periods with expected logic. It also manages demand by leveraging prices and choosing market. In this paper, first, we investigate the state-space model of this supply chain system and examine the effect of complex dynamic and stochastic noise on the bullwhip effect. We analytically prove that this factor leads to the bullwhip effect. So, first, we filtered the information between nodes with extended Kalman filter after which we regulated the destructive effects of the bullwhip phenomenon by designing a non-linear quadratic Gaussian optimal controller. Eventually, the simulation results indicate the efficiency of the proposed method.     

Mechanical buckling and free vibration of thick functionally graded plates resting on elastic foundation using the higher order B-spline finite strip method

In this study, the mechanical buckling and free vibration of thick rectangular plates made of functionally graded materials (FGMs) resting on elastic foundation subjected to in-plane loading is considered. The third order shear deformation theory (TSDT) is employed to derive the governing equations. It is assumed that the material properties of FGM plates vary smoothly by distribution of power law across the plate thickness. The elastic foundation is modeled by the Winkler and two-parameter Pasternak type of elastic foundation. Based on the spline finite strip method, the fundamental equations for functionally graded plates are obtained by discretizing the plate into some finite strips. The results are achieved by the minimization of the total potential energy and solving the corresponding eigenvalue problem. The governing equations are solved for FGM plates buckling analysis and free vibration, separately. In addition, numerical results for FGM plates with different boundary conditions have been verified by comparing to the analytical solutions in the literature. Furthermore, the effects of different values of the foundation stiffness parameters on the response of the FGM plates are determined and discussed.     

Anomeric-Schleyer hyperconjugative interaction as a convenient avenue for aromaticity enhancement of phospholes

Due to the insufficient interaction of the phosphorus lone pair with the butadiene moiety, the aromaticity of the phosphole ring is lower than that of its counterpart's pyrrole, furan, and thiophene. Considering the high importance of phosphole core in organic chemistry, increasing its stability through reinforcement its aromaticity can be very valuable. In the present work, the aromaticity of the phosphole on the anomeric carbon in both the axial and equatorial conformers of the unsaturated six-membered heterocycles, using structural, electronic, energetic, and magnetic indices were investigated by the DFT-B3LYP/6-311++G(d,p) computational method. Electron pumping through anomeric and then Schleyer hyperconjugative interaction increase the aromaticity of the phosphole ring in axial conformer of compounds 1–11 . Based on various types of aromaticity indices, the results showed that the phosphole ring in the axial position has far higher aromaticity than the equatorial position. The phosphole ring containing cyano groups shows an efficient anomeric effect and, as a result, higher aromaticity. Excellent correlations were observed between aromaticity indices with different backgrounds.     

Effect of heat treatment on longitudinal gas and liquid permeability of circular and square-shaped native hardwood specimens

Effects of heat-treatment on longitudinal permeability of circular and square wood specimens were studied here. Specimens were heated to 50, 75, 100, 125, 150, and 185 °C. Results showed that permeability increased at the lowest temperature due to shrinkage; then, it decreased due to irreversible hydrogen bonding and stiffness. The highest temperature increased permeability due to micro-cracks. The higher perimeter in the square specimens aggravated the effects of heat treatment.     

Generation and propagation of novel donut beams by a spiral phase plate: Humbert beams

The theoretical conversion of the Bessel-modulated Gaussian beam with a quadratic radial dependence by a spiral phase plate (SPP) leads us to generate a novel donut family that we called it Humbert beam. In this paper, the different theoretical tools are developed to obtain these new waves. Some numerical calculations are performed to study the transformation and the propagation of this new family by a SPP with an integer topological charge through an ABCD optical system. The present study shows also that the Humbert beam generalized the Kummer family waves.     

Optical bistability and multistability in a parametric region

We study the optical bistability (OB) and optical multistability (OM) behaviors in a five-level $\Lambda $ -type parametric region atomic system by two-photon resonant transitions. We find that the intensity threshold of OB and switching from OB to OM or vice versa can be controlled via quantum interference between different two-photon transitions pathways.     

Stochastic single machine scheduling problem as a multi-stage dynamic random decision process

In this work, we study a stochastic single machine scheduling problem in which the features of learning effect on processing times, sequence-dependent setup times, and machine configuration selection are considered simultaneously. More precisely, the machine works under a set of configurations and requires stochastic sequence-dependent setup times to switch from one configuration to another. Also, the stochastic processing time of a job is a function of its position and the machine configuration. The objective is to find the sequence of jobs and choose a configuration to process each job to minimize the makespan. We first show that the proposed problem can be formulated through two-stage and multi-stage Stochastic Programming models, which are challenging from the computational point of view. Then, by looking at the problem as a multi-stage dynamic random decision process, a new deterministic approximation-based formulation is developed. The method first derives a mixed-integer non-linear model based on the concept of accessibility to all possible and available alternatives at each stage of the decision-making process. Then, to efficiently solve the problem, a new accessibility measure is defined to convert the model into the search of a shortest path throughout the stages. Extensive computational experiments are carried out on various sets of instances. We discuss and compare the results found by the resolution of plain stochastic models with those obtained by the deterministic approximation approach. Our approximation shows excellent performances both in terms of solution accuracy and computational time.