Haemolytic activity of Aeromonas species isolated in Libya

Twenty seven Aeromonas strains (5A. hydrophila, 8A. sobria and 14A. caviae) isolated from children with diarrhoea and 34 Aeromonas strains (9A. hydrophila, 7A. sobria an 18A. caviae) isolated from children without diarrhoea were tested from haemolysin production. The results obtained showed that haemolysin production using human, horse or sheep erythrocytes was significantly associated with A.hydrophila and A sobria but not with A.caviae, regardless of whether these strains were isolated from children with or without diarrhoea. Human or horse rather than sheep erythrocytes are recommended for use in the haemolysin assay.     

Ambient‐cured polyesteramide‐based anticorrosive coatings from linseed oil—A sustainable resource

Ambient‐cured polyesteramide (APEA) coating resin synthesized from dihydroxy fatty amide obtained from linseed oil, a sustainable resource, and poly(styrene‐co‐maleic anhydride), a bifunctional acid component, was found to exhibit improved physicomechanical and anticorrosive properties. The structural elucidation of APEA resin has been carried out by FTIR, ¹H‐NMR, and ¹³C‐NMR spectroscopies. The physicomechanical and chemical resistance properties were investigated by standard methods. The corrosion resistance performance was evaluated in acid, alkali, and organic solvent. The thermal behavior was studied by TGA technique. A comparative study of these properties of APEA with reported baked polyesteramide (PEA) coatings was carried out. A remarkable improvement in the drying property of APEA was observed. The APEA coatings also showed improved physicomechanical and anticorrosive properties as compared to the baked PEA coatings. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1818–1824, 2005     

Miscibility behavior of blend of polyesteramides of linseed oil and dehydrated castor oil with poly(methacrylic acid)

Blending of two polymers in solution is a simple and cost‐effective technique to improve upon the physical and mechanical properties of the component polymers through synergism. To obtain maximum synergy in their properties, the component polymers should be miscible with each other on molecular scale. Polymer blends of complex physicomechanical properties are being actively investigated. Poly(methacrylic acid) (PMAA), a commercial polymer, yields transparent, hard, brittle, and water‐sensitive films. It has been blended with natural polymers like dextran, collagen, and gelatin to obtain films with improved physical and mechanical characteristics. Polyesteramides, which are easily synthesized from vegetable seeds oil, a sustainable resource, have found application in surface coatings. These oligomeric products do not make free standing films in the ambient condition. The polyesteramides from vegetable seeds oil can be used to obtain blend with PMMA of improved mechanical and water absorption properties. In this study, linseed oil polyesteramide (LOPEA) and dehydrated castor oil polyesteramide (DCPEA), the source oils with different unsaturation in their fatty acid chains, were blended with PMAA through mixing in solution in the ratio DCPEA/LOPEA: PMAA as 80/20, 70/30, 60/40, 50/50, 40/60, 30/70, and 20/80. In the first instance, the miscibility of the two components was investigated in solution by viscosity and ultrasonic measurements and in solid phase through differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). Moisture absorption by the blend was also studied. DCPEA and LOPEA show immiscibility with PMAA in solution phase while LOPEA with more unsaturation in the fatty acid chain of the oil was found more immiscible than DCPEA. DCPEA shows a narrow miscibility window in the solid phase while LOPEA was found immiscible with PMAA in the solid phase too. Uptake of moisture was found to be markedly reduced in the blends of DCPEA/LOPEA with PMAA. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1367–1374, 2007:     

Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA

In this study, Artificial Neural Network (ANN) and Simulated Annealing (SA) techniques were integrated labeled as integrated ANN-SA to estimate optimal process parameters in abrasive waterjet (AWJ) machining operation. The considered process parameters include traverse speed, waterjet pressure, standoff distance, abrasive grit size and abrasive flow rate. The quality of the cutting of machined-material is assessed by looking to the roughness average value (R_a). The optimal values of the process parameters are targeted for giving a minimum value of R_a. It was evidence that integrated ANN-SA is capable of giving much lower value of R_a at the recommended optimal process parameters compared to the result of experimental and ANN single-based modeling. The number of iterations for the optimal solutions is also decreased compared to the result of SA single-based optimization.     

Genetic Algorithm and Simulated Annealing to estimate optimal process parameters of the abrasive waterjet machining

In this study, two computational approaches, Genetic Algorithm and Simulated Annealing, are applied to search for a set of optimal process parameters value that leads to the minimum value of machining performance. The objectives of the applied techniques are: (1) to estimate the minimum value of the machining performance compared to the machining performance value of the experimental data and regression modeling, (2) to estimate the optimal process parameters values that has to be within the range of the minimum and maximum coded values for process parameters of experimental design that are used for experimental trial and (3) to evaluate the number of iteration generated by the computational approaches that lead to the minimum value of machining performance. Set of the machining process parameters and machining performance considered in this work deal with the real experimental data of the non-conventional machining operation, abrasive waterjet. The results of this study showed that both of the computational approaches managed to estimate the optimal process parameters, leading to the minimum value of machining performance when compared to the result of real experimental data.     

Synthesis and characterization of poly(ethylene tetrasulfide)/graphene oxide nanocomposites by in situ polymerization method

Poly(ethylene tetrasulfide) (PSP) is synthesized via interfacial polycondensation of 1,2 dichloroethane and sodium tetrasulfide, in the presence of graphene oxide (GO). This process resulted in homogeneously dispersed PSP/GO nanocomposites. Nanocomposites of 0.3 and 0.5?wt% of GO are synthesized and their morphology, chemical characteristics behavior are studied employing field emission scanning electron microscopy, Fourier transform infrared spectroscopy and X-ray diffraction techniques. Thermal characterization of composites is performed by differential scanning calorimetry and thermogravimetry analysis. Results indicate that the addition of only small amounts (0.5?wt%) of well-dispersed GO can increase the melting point more than 16°C resulting in better thermal properties for the composite. The solubility of nanocomposite is also studied and results show that the solubility depends on solvent concentration in addition to reinforcement (GO) deals.     

Towards the performance evaluation of 4th generation wireless communication standards: LTE versus Mobile WiMAX

Advances in wireless communication protocols and networking toward support of the next generation of mobile and radio broadband technologies have contributed to a strong competition among various telecommunication standards in particular Long Term Evolution (LTE) and Mobile Worldwide Interoperability for Microwave Access (WiMAX). In this paper, we provide an in‐depth comparison analysis of LTE and Mobile WiMAX at the physical (PHY) layer by studying the most similar PHY configuration scenarios for these two technologies. Our study includes a throughput analysis of downlink (DL) and uplink (UL) transmissions in time division duplex with the least overhead possible and different antenna schemes as well as modulation and code rates. This study also performs an overhead analysis in both protocols to provide a more in‐depth understanding of the PHY layer capacity in various PHY layer configurations. Our simulation results generally show higher performance for LTE in both DL and UL transmission with 7 Mbps in DL and 5 Mbps in UL, when using one antenna port. However, by increasing the number of antennas for multiple‐input/multiple‐output configurations, the results illustrate a reduction in the performance of LTE compared to Mobile WiMAX. This arises from the increase in reference signal overhead in LTE from 4.7% in single‐input/single‐output (SISO) to 14.28% in 4 × 4 multiple‐input/multiple‐output (MIMO). Copyright © 2013 John Wiley & Sons, Ltd.     

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach

Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F‐score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods.