Polylactic acid (PLA)/Silver-NP/VitaminE bionanocomposite electrospun nanofibers with antibacterial and antioxidant activity

The antibacterial property of silver nanoparticles (Ag-NPs) and the antioxidant activity of Vitamin E have been combined by incorporation of these two active components within polylactic acid (PLA) nanofibers via electrospinning (PLA/Ag-NP/VitaminE nanofibers). The morphological and structural characterizations of PLA/Ag-NP/VitaminE nanofibers were performed by Scanning Electron Microscopy (SEM), Transmission Electron Microscopy and X-ray diffraction. The average fiber diameter was 140 ± 60 nm, and the size of the Ag-NP was 2.7 ± 1.5 nm. PLA/Ag-NP/VitaminE nanofibers inhibited growth of Escherichia coli, Listeria monocytogenes and Salmonella typhymurium up to 100 %. The amount of released Ag ions from the nanofibers immersed in aqueous solution was determined by Inductively Coupled Plasma Mass Spectrometry, and it has been observed that the release of Ag ions was kept approximately constant after 10 days of immersion. The antioxidant activity of PLA/Ag-NP/VitaminE nanofibers was evaluated according to DPPH (2,2-diphenyl-1-picrylhydrazyl) method and determined as 94 %. The results of the tests on fresh apple and apple juice indicated that the PLA/Ag/VitaminE nanofiber membrane actively reduced the polyphenol oxidase activity. The multifunctional electrospun PLA nanofibers incorporating Ag-NP and Vitamin E may be quite applicable in food packaging due to the extremely large surface area of nanofibers along with antibacterial and antioxidant activities. These materials could find application in food industry as a potential preservative packaging for fruits and juices.     

A predictive model for pressure fluctuations on sloping channels using support vector machine

In this study, support vector machine (SVM) is proposed as a new predictive model for pressure fluctuations beneath free jump occurring on sloping channels. The proposed model reproduces the pressure fluctuation intensity C′_p in terms of normalized flow and channel section characteristics. The model variables were derived from dimensional analysis. The proposed model is calibrated and validated by using a wide range of experimental data. The SVM predicted C′_p with a correlation of coefficient (CC) of 0.989 and a root mean square error (RMSE) of 0.004. Also, linear and nonlinear regression analyses are applied on the same experimental data set, and the SVM model is compared to the equations obtained from these regression analyses. CC, RMSE and average absolute deviation (D_i) are used in the evaluation of performance of each model. The SVM model predicted the measured pressure fluctuations better than conventional regression equations. The results of this study reveal that the proposed SVM model can be effectively used in predicting the pressure fluctuation beneath free jump. Copyright © 2010 John Wiley & Sons, Ltd.     

Solution of fractional differential equations by using differential transform method

In this study, we implement a well known transformation technique, Differential Transform Method (DTM), to the area of fractional differential equations. Theorems that never existed before are introduced with their proofs. Also numerical examples are carried out for various types of problems, including the Bagley–Torvik, Ricatti and composite fractional oscillation equations for the application of the method. The results obtained are in good agreement with the existing ones in open literature and it is shown that the technique introduced here is robust, accurate and easy to apply.     

Seed Oils of Fifteen Ebenus Taxa Growing in Turkey

Oil yields and compositions from seeds of 15Ebenustaxa growing in Turkey were investigated. The yields were found between 4.0% and 13.0%. The seeds ofE. Barbigerashowed the highest whileE. Plumosavar.plumosashowed the lowest yield of oil among the 15 taxa investigated. GC/MS showed that linoleic acid (42.8-55.6%), palmitic acid (13.8-23.6%), and oleic acid (15.9-23.6%) are the main fatty acid components of all the species     

A new fractional derivative model for linearly viscoelastic materials and parameter identification via genetic algorithms

In this study, a new nested model consisting of springs and “spring pots” is proposed to better simulate the viscoelastic behavior of polymeric damping materials in the frequency domain. First, the one-dimensional constitutive equation that consists of ten parameters is derived. The dynamical mechanical properties, which are the storage modulus, the loss modulus, and the loss factor, are obtained from this equation. Then, the low- and high-frequency behavior of this model is investigated. Moreover, a new methodology to identify the unknown parameters that appear in the fractional derivative model, from the experimental data for the Wicket plot, by using genetic algorithms (GAs) is presented. This approach does not require shifting of the experimental data; therefore, possible errors that may arise are eliminated. The new model is fitted to experimental data for several polymeric damping materials that exist in the literature, in order to verify its success. The results are presented in a graphical form with comparison to the already existing models.     

Modelling high-tech product life cycles with short-term demand information: a case study

Increasing competition and volatile conditions in high-tech markets result in shortening product life cycles with non-cyclic demand patterns. This study illustrates the use of a demand-characterisation approach that models the underlying shape of product demands in these markets. In the approach, a Bayesian-update procedure combines the demand projections obtained from historical data with the short-term demand information provided from demand leading indicators. The goal of the Bayesian procedure is to improve the accuracy and reduce the variation of historical data-based demand projections. This paper discusses the implementation experience of the proposed approach at a semiconductor-manufacturing company; the key test results are presented using product families introduced over the last few years with a comparison to real-world benchmark demand forecasts.     

Hybrid modelling for simulation of scour and flow patterns in laboratory flumes

In this study, a hybrid numerical–mathematical model is developed, which simulates the temporal evolution of local scour and flow patterns in laboratory flumes. The mathematical module calculates the shape of the scour hole by solving an integro‐parabolic equation. The numerical module simulates the two‐dimensional laterally averaged flow patterns in the corresponding scour hole. The hybrid model is verified by experimental data taken from the literature. The hybrid model predicted the temporal evolution of local scour and simulated the flow patterns in and around the scoured zone in good agreement with the experimental ones. The proposed hybrid model proved to be efficient when used in complex local scour and turbulent flow problems. Copyright © 2009 John Wiley & Sons, Ltd.     

Calculation of the Accessibility Number and the Neighbor Integrity of a Graph

We calculate stability numbers of Butterfly and Omega networks used in computer science.We describe relations between the neighbor integrity and the accessibility number of these networks.