Polystyrene/Polyolefin Elastomer Blends Loaded with Halloysite Nanotubes: Morphological,Mechanical, and Gas Barrier Properties

Herein, a simple melt-blending method is utilized to disperse of halloysite nanotubes (HNTs) in polystyrene/polyolefin elastomer (PS/POE) blends. Based on morphological studies, the PS/POE/HNT nanocomposite containing up to 3 phr HNTs shows excellent nanofiller dispersion, while those filled with 5 phr HNTs exhibit nanofiller aggregation. To overcome the nanofiller aggregation issue, the polypropylene-grafted-maleic anhydride (PP-g-MA) compatibilizer is added to the PS/POE/HNT nanocomposite, which results in improved mechanical properties for the nanocomposite sheets. Furthermore, the addition of compatibilized HNTs to the PS/POE blends leads to decreased O₂ and N₂ gas permeabilities. Besides, incorporating POE, HNTs, and PP-g-MA leads to a decrease in water vapor transmission of PS. In the end, the experimentally-determined mechanical properties and gas permeabilities of the nanocomposite sheets are compared to those predicted by prevalent theoretical models, revealing a good agreement between the experimental and theoretical results. Molecular-dynamics simulations are also carried out to calculate the gas diffusion coefficients in the different sheets to further support the experimental findings in this study. Overall, the PS/POE/HNT/PP-g-MA nanocomposite sheets fabricated in this work demonstrate excellent mechanical and gas barrier properties; and hence, can be used as candidate packaging materials. However, the strength of the resulting PS/POE blend may be inferior to that of the virgin PS.     

A new hybrid approach to discrete multiple facility location problem

Locating certain facilities in predetermined sites is named the multiple facility location problems (MFLP). The objective of these kinds of problems is locating facilities to serve a given set of customers so that candidate sites and requirements are known. When the new facility sites have to be selected from a given set of candidate sites, the mentioned location problem becomes a discrete multiple facility location problem (DMFLP). In this paper, a special approach of DMFLP is considered where different multiple facilities have to be placed (location decision) and also customers have to be assigned to these facilities (allocation or assignment). The mathematical model of the proposed problem is developed, and with respect to the complexity of solving the mathematical model, especially in large scale, a new hybrid approach is proposed based on tabu search algorithm to solve the problem at each scale. Computational results on several randomly generated problems in comparison with a new proposed lower bound obtained from Lagrangian relaxation indicate that the proposed hybrid approach is both accurate and efficient.     

Stick-slip conditions in the general motion of a planar rigid body

In this paper we study combined translational and rotational (general) motion of planar rigid bodies in the presence of dry coulomb friction contact. Despite the cases where the body has pure translational/ rotational motion or can be assumed as a point mass, during the general motion, distinct points of the rigid body move in different directions which cause the friction force vector at each point to be different. Therefore, the direction and the magnitude of the overall friction force cannot be intuitively defined. Here the concept of instantaneous center of rotation is used as an effective method to determine the resultant friction force and moment. The main contribution of this paper is to propose novel stick-slip switching conditions for the general in-plane motion of rigid bodies. Simulation results for some combination of external forces are provided and some experimental tests are designed and conducted for practical verification of the proposed stick-slip conditions.     

An improved time-adaptive self-organizing map for high-speed shape modeling

In this paper, an improved active contour model based on the time-adaptive self-organizing map with a high convergence speed and low computational complexity is proposed. For this purpose, the active contour model based on the original time-adaptive self-organizing map is modified in two ways: adaptation of the speed parameter and reduction of the number of neurons. By adapting the speed parameter, the neuron motion speed is determined based on the distance of each neuron from the shape boundary which results in an increase in the speed of convergence of the contour. Using a smaller number of neurons, the computational complexity is reduced. To achieve this, the number of neurons used in the contour is determined based on the boundary curvature. The proposed model is studied and compared with the original time-adaptive self-organizing map. Both models are used in several experiments including a tracking application. Results reveal the higher speed and very good performance of the proposed model for real-time applications.     

Medication take-home doses and contingency management.

Two studies examined contingent take-home medication doses during treatment of opiate or cocaine dependence. In the first study, methadone maintenance patients were randomly assigned to one of two 8-week baseline take-home (TH) conditions differing in frequency of clinic visits per week. This was followed by a 12-week contingency management (CM) procedure in which frequent THs resulted from drug-free urines. Participants receiving more frequent THs during baseline had lower illicit drug use during the first 6 weeks of CM. In the second study, fluoxetine (0-, 20-, 40-mg) TH doses were similarly contingent in treatment of cocaine dependence. The 40-mg group used less cocaine during contingency than did other groups. The combination of fluoxetine and environmental contingencies may produce benefit where neither alone is sufficient. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An optimal scheme for fast rate fault detection based on multirate sampled data

Multirate systems are abundant in industry. In this paper, the problem studied is designing a residual generator for fault detection based on multirate sampled data. The key new feature of such a residual generator is that it operates at a fast rate for prompt fault detection. The design is based on optimizing a performance index to obtain an optimal parity space based residual generator. The lifting technique is used to convert the time-varying multirate design problem into a time-invariant one with a causality constraint for implementability. A procedure for computing an explicit optimal, causal solution is proposed. The advantages of this design are shown through an example.     

Combined Computational and Experimental Study on the Adsorption and Inhibition Effects of N2O2 Schiff Base on the Corrosion of API 5L Grade B Steel in 1 mol/L HCI

The electrochemical behavior of low carbon steel （API 5L grade B） in 1 mol/L HCI solution with different concentrations of N,Nr-bis（4-formylphenol）-trimethylenediamine Schiff base was studied by electrochemical techniques and density functional theory analysis. The inhibition efficiency was found to increase with increasing inhibitor concentration and decreased with increasing temperature. The high inhibition efficiency was attributed to the blocking of active sites by adsorption of inhibitor molecules on the steel surface. Thermodynamic parameters for the adsorption and activation processes were determined. Galvanostatic polarization data indicated that Schiff base act as a mixed-type inhibitor and the adsorption isotherm obeyed the Langmuir adsorption isotherm. Results obtained from quantum chemical studies show excellent correlations between the quantum chemical parameters and the experimental inhibition efficiencies using density functional theory at the B3LYP/6-31G（d,p） and B3LYP/3-21G basis set levels and ab initio calculations using HF/6-31G（d,p） and HF/3-21G methods.     

Simulation and Estimation of Vapor-Liquid Equilibrium for Asymmetric Binary Systems (CO2-Alcohols) Using Artificial Neural Network

Since it is not always possible to carry out experiments at all desired temperatures and pressures, generally thermodynamic models based on equations of state are used for estimation of vapor-liquid equilibrium. In this work, a method using artificial neural network (ANN) was designed and applied to simulate and estimate the VLE for the binary asymmetric systems containing CO₂ and Alcohols. The vapor-liquid equilibrium data of six systems include (CO₂-methanol), (CO₂-ethanol), (CO₂-1-butanol), (CO₂-2-butanol), (CO₂-1-pentanol) and (CO₂-2-pentanol) were used to developed the ANN for simulation of VLE. The results when using a developed ANN model or other methods such as SRK equations of state with LCVM, PSRK, WS, were compared with experimental data at various temperatures and pressures. Finally, it was observed that there is more qualitative and quantitative conformity between ANN model results and experimental data. Furthermore, the developed ANN model showed more accurate estimation over wide range of experimental conditions.     

Extracting Optimal Policies of Hydropower Multi-Reservoir Systems Utilizing Enhanced Differential Evolution Algorithm

Deriving the optimal policies of hydropower multi-reservoir systems is a nonlinear and high-dimensional problem which makes it difficult to achieve the global or near global optimal solution. In order to optimally solve the problem effectively, development of optimization methods with the purpose of optimizing reservoir operation is indispensable as well as inevitable. This paper introduces an enhanced differential evolution (EDE) algorithm to enhance the exploration and exploitation abilities of the original differential evolution (DE) algorithm. The EDE algorithm is first applied to minimize two benchmark functions (Ackley and Shifted Schwefel). In addition, a real world two-reservoir hydropower optimization problem and a large scale benchmark problem, namely ten-reservoir problem, were considered to indicate the effectiveness of the EDE. The performance of the EDE was compared with the original DE to solve the three optimization problems. The results demonstrate that the EDE would have a powerful global ability and faster convergence than the original DE to solve the two benchmark functions. In the 10-reservoir optimization problem, the EDE proved to be much more functional to reach optimal or near optimal solution and to be effective in terms of convergence rate, standard deviation, the best, average and worst values of objective function than the original DE. Also, In the case of two-reservoir system, the best values of the objective function obtained 93.86 and 101.09 for EDE and DE respectively. Based on the results, it can be stated that the most important reason to improve the performance of the EDE algorithm is the promotion of local and global search abilities of the DE algorithm using the number of novel operators. Also, the results of these three problems corroborated the superior performance, the high efficiency and robustness of the EDE to optimize complex and large scale multi-reservoir operation problems.