Polypropylene cellulose‐based composites: The effect of bagasse reinforcement and polybutadiene isocyanate treatment on the mechanical properties

Using bagasse fiber as the reinforcing filler and polypropylene as the thermoplastic matrix polymer, a reinforced composite was prepared, and its mechanical properties examined as a function of the amount of compatibilizing agents used. In the sample preparation, four levels of fiber loading (10, 20, 30, and 40 wt %), three levels of polybutadiene isocyanate (PBNCO) content (0, 2, and 4 wt %) and two levels of maleated polypropylenes (MAPP) content (0 and 3 wt %) as compatibilizing agents were used. The tensile properties of the composites improved as the fiber loading and the compatibilizing agents increased, but the impact strength was significantly decreased. The mechanical study revealed that the positive effect of compatibilizing agents on interfacial bonding. The composites treated with PBNCO showed superior tensile and impact properties than those without treatment. The findings indicated that bagasse as agro‐waste material is a valuable renewable natural resource for composite production and could be utilized as a substitute for wood in composite industries. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2009     

Solving the stochastic support vector regression with probabilistic constraints by a high-performance neural network model

This paper offers a recurrent neural network to support vector machine (SVM) learning in stochastic support vector regression with probabilistic constraints. The SVM is first converted into an equivalent quadratic programming (QP) formulation in linear and nonlinear cases. An artificial neural network for SVM learning is then proposed. The presented neural network framework guarantees obtaining the optimal solution of the SVM problem. The existence and convergence of the trajectories of the network are studied. The Lyapunov stability for the considered neural network is also shown. The efficiency of the proposed method is shown by three illustrative examples.

     

Kinetics and Mechanism of Low-Grade Manganese Ore Reduction by Natural Gas

Metallurgical and Materials Transactions B - The calcination and the reduction behaviors of a low-grade manganese ore by methane was studied at 973 K to 1273 K by several techniques. The onset...     

Evaluation of mustard (Brassica juncea) protein isolate prepared by steam injection heating for reduction of antinutritional factors

A process for the preparation of mustard protein isolate, comprising steps such as dispersion of defatted meal in 0.1 mol/l NaCl solution, incubation, extraction at alkaline pH, followed by treatment of the protein solution with activated carbon was developed. The protein, coagulated by steam injection, was subjected to separation by centrifugation, washing and spray drying. The parameters evaluated were protein yield, purity, presence of antinutritional factors and nutritional quality of proteins. The protein yield was 58-60%. The purity of the protein isolate was 95%. The hydrolysed products of glocosinolates like isothiocyanates and oxazolidine thione levels, phenolics and phytic acid levels were low in the protein isolate. The in vitro digestibility of the protein isolate was 92.4% compared to 80.6% of the meal. Chemical score of the meal and protein isolate were similar; isoleucine was the first limiting amino acid. The calculated nutritional indices, essential amino acid index, biological value, nutritional index and C-PER of protein isolate were higher compared to meal. The protein quality as indicated by amino acid profile and PDCAAS scores for 10-12-years old and adults were 100.     

Application of Fuzzy c-means algorithm for the estimation of Asphaltene precipitation

One of problematic topics in petroleum engineering is Asphaltene precipitation issue which causes problems such as tubing plugging and formation damage due to temperature, pressure and composition changes so the notability of this issue increases. In the present investigation a novel Fuzzy c-means (FCM) algorithm was developed to predict precipitated asphaltene as function of dilution ratio, carbon number of precipitants and temperature for solving the problem. The results showed that this novel approach has great ability to predict precipitated asphaltene in terms of aforementioned parameters. The coefficients of determination (R²) for training and testing steps are calculated as 0.9828 and 0.9387 respectively. This great degree of accuracy expresses that the predicting algorithm has potential to be utilized as software for prediction of asphaltene behavior.     

Microstructural and mechanical assessment of transient liquid phase bonded commercially pure titanium

Diffusion joining of commercially pure titanium was successfully prepared via transient liquid phase bonding in vacuum environment. The process was carried out using AMS 4772 silver-based filler alloy at 900–1000°C for various holding time under the vacuum of 6?×?10^?7?Torr. Optical and scanning electron microscopy equipped with an EDS analyzer was conducted for microstructural evaluations. Mechanical properties were also investigated by shear test, fractographic assessment and X-ray diffraction analyses. The tendency to achieve isothermally solidified joint increased by increasing bonding time. No sign of athermal solidification was detected of sample bonded at 1000°C for 90?min. Consequently, the bonding condition of a high quality joint was obtained. Elemental analyses revealed that filler alloy’s elements (Ag, Cu) distributed more uniformly in fully isothermal solidified bond, whereas the aggregation of these elements is considerable in athermally solidified bond. Shear test results represented that the highest shear strength attributed to the sample bonded in isothermal solidified condition (bonded at 1000°C for 90?min).     

Production planning: a DEA-based approach

In organizations with a centralized decision making environment, production usually involves the participation of more than one individual unit, each contributing in part to the total production. The planning problem involves determining the number of products to be produced by all individual units in the next season when demand changes can be forecasted. This paper introduces a data envelopment analysis approach to making future production plans in a centralized decision making environment when demand changes can be forecasted in the next production season. The approach proposed in this paper takes the size of operational units into account so that the planned production for each unit becomes proportionate to the ability of the units. A real world data set is used to illustrate the applicability of the approach.