Dye binary mixture formulation by means of derivative ratio spectra of the Kubelka–Munk function

In this study, a new method is introduced for the determination of dye concentration in fabrics dyed with bicomponent dye mixtures. The reflectance spectra of the samples dyed with different binary mixtures of dyes were recorded between 400 and 700 nm. The obtained spectra were divided by a standard spectrum of each of the components in the mixtures and the derivative spectra were calculated. The amounts of dyes were determined by measurements in suitably selected wavelengths in the acquired derivative ratio spectra. The obtained results indicate that the developed derivative ratio spectra method is more accurate than the normal Kubelka–Munk method. The proposed derivative method is simple, accurate, and suitable for quantitative analysis of samples dyed with binary mixed shades. © 2010 Wiley Periodicals, Inc. Col Res Appl, 2010     

Probiotic yoghurt functionalised with microalgae and Zedo gum: chemical,microbiological, rheological and sensory characteristics

In this study, using a central composite design, the effects of addition of Spirulina platensis and Zedo gum to plain and probiotic yoghurt samples were investigated during storage. Lactobacillus paracasei proliferation was directly dependent on the addition of microalgae and was inversely affected by storage time. Probiotic samples containing S. platensis showed the highest antioxidative activity. Maximum stability was obtained at higher amounts of Zedo gum, while organoleptic and rheological attributes improved at 0.25% Zedo gum. Given the importance of probiotic viability, supplementation of probiotic yoghurt with Zedo gum/S. platensis may be consideredas a novel nutraceutical formulation.     

Knowledge mapping of the Iranian nanoscience and technology: a text mining approach

Nanoscience and technology (NST) is a relatively new interdisciplinary scientific domain, and scholars from a broad range of different disciplines are contributing to it. However, there is an ambiguity in its structure and in the extent of multidisciplinary scientific collaboration of NST. This paper investigates the multidisciplinary patterns of Iranian research in NST based on a selection of 1,120 ISI??indexed articles published during 1974?C2007. Using text mining techniques, 96 terms were identified as the main terms of the Iranian publications in NST. Then the scientific structure of the Iranian NST was mapped through multidimensional scaling, based upon the co-occurrence of the main terms in the academic publications. The results showed that the NST domain in Iranian publications has a multidisciplinary structure which is composed of different fields, such as pure physics, analytical chemistry, chemistry physics, material science and engineering, polymer science, biochemistry and new emerging topics.     

Estimating the scattering distribution of the received signals in multipath fading channels

This paper presents a novel approach for estimating the distribution of the incoming waves at the mobile unit antenna, i.e. the scattering distribution, in a typical micro-cellular system. This estimate is vital in determining many system parameters of interest as well as designing unbiased estimators for the velocity of mobile units in micro-cellular systems. The proposed approach deploys the zero-crossing rates of the quadrature components and the instantaneous frequency of the received signal at the mobile unit to estimate the scattering distribution. We also propose a new model for simulating multipath fading channels with non-isotropic scattering. We use the channel simulator to evaluate the performance of the proposed estimator for the scattering distribution. Simulation results show that proposed estimator exhibits small bias and root mean square error.     

Characterisation of CO/NO/SO2 emission and ash-forming elements from the combustion and pyrolysis process

Bioenergy is considered as a sustainable energy which can play a significant role in the future’s energy scenarios to replace fossil fuels, not only in the heat production, but also in the electricity and transportation sectors. Emission formation and release of main ash-forming elements during thermal conversion of biomass fuels at different conditions have been the scope of this study. The experiments were conducted in a quartz glass reactor where the temperature and atmosphere could be controlled. The selected fuels represent a wide range of biomass compositions. They are torrefied softwood, spruce bark, waste wood, miscanthus, and wheat straw. The fuels were first grinded and then pressed with a pellet maker into pellets of the same size and weight. For each fuel, the experiments were carried out under both oxidation and pyrolysis condition, with atmosphere of 3 % O₂ + 97 % N₂ and 100 % N₂, respectively, at four residence times. The selected temperatures under which experiments were performed are 800, 900, and 1,050 °C. The concentration of SO₂, NO, CO, and CO₂ emissions and O₂ were monitored online by three analysers, simultaneously. The residue weight was measured after each process, and the comparison with the ash content of the fresh pellet is made. Additionally, the release of several ash-forming elements (K, Zn, Na, and Mn) from the fuels has been quantified as function of temperature and residence time by inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectroscopy (ICP-AES). Time-dependent formation of NO and SO₂ and other emissions is presented and discussed with respect to different temperature and combustion conditions.     

Accessing the Mott Regime in 2D Optical Lattices with Strongly Interacting Fermions

We use numerical linked-cluster expansions to study finite-temperature properties of strongly interacting fermions in two-dimensional optical lattices, governed by the Hubbard model. We show the double occupancy and entropy for the infinite homogeneous system at temperatures significantly lower than those obtained by other exact methods at strong interactions. Employing a local density approximation, and using the high-precision results for the entropy, we study the density and nearest-neighbor spin correlation profiles of lattice fermions trapped in a harmonic potential during adiabatic processes. Starting with a trap that has a substantial band-insulator region at high temperatures, we show how one can access the Mott region at low temperatures by flattening the trapping potential.     

A comparative study on optimised and non‐optimised axial flow,spherical reactors in naphtha reforming process

In this study, the operating conditions of an axial flow spherical reactor have been optimised using a reliable optimisation technique and the results are compared with the results of non‐optimised conditions. The dynamic behaviour of the reactor has been considered in the optimisation process and orthogonal collocation method has been used in order to solve the obtained equations from mathematical modelling of the process. The goal of this study is to maximise the aromatics and hydrogen production rate. Therefore, the objective function is the combination of two terms which include the production rate of the mentioned components. The catalyst distribution for each reactor, the inlet pressure of the system, Length per radius for each reactor, the naphtha feed molar flow rate and the hydrogen mole fraction in the recycle stream as well as the inlet temperature of each reactor have been optimised in this study. © 2011 Canadian Society for Chemical Engineering     

Performance analysis of multi-antenna relay networks with imperfect channel estimation

In this paper, we present the performance of multi-antenna selective combining decode-and-forward (SC-DF) relay networks over independent but non-identical Nakagami-m fading channels with imperfect channel estimation. The outage probability, moment generating function (MGF) and symbol error probability (SEP) will be derived in closed-form using the SNR statistical characteristics. To make the analysis trackable, we have derived the MGF and SEP for integer values of fading severity, m. Also, to make the relations more simple, we develop high signal to noise ratio (SNR) analysis for the performance metrics of our system. Subsequently, we propose optimal and adaptive power allocation algorithms along with the equal power allocation method. Finally, for comparison with analytical formulas, we perform some Monte-Carlo simulations.     

Time–cost optimization: using GA and fuzzy sets theory for uncertainties in cost

Uncertainties should be considered in any time–cost trade‐off problems when minimizing project cost and duration, which leads to the so‐called stochastic time–cost trade‐off problem. A new approach to investigate stochastic time–cost trade‐off problems employing fuzzy logic theory is presented. The proposed approach fully embeds the fuzzy structure of the uncertainties in total direct cost into the model. An appropriate GA is used to develop a solution to the multi‐objective fuzzy time cost model. The accepted risk level of the project manager is defined through α cut approach for which a separate Pareto front with set of non‐dominated solutions has been developed. To compare the alternative set of options for any assumed project duration, associated fuzzy costs for different values of α cut are ranked employing two appropriate approaches for fuzzy costs comparison. The proposed models are applied to solve two benchmark test problems. It is shown that the models facilitate the decision‐making process by selecting specified risk levels and employing the associated Pareto front.     

Ternary gas permeation through synthesized pdms membranes: Experimental and CFD simulation basedon sorption‐dependent system using neural network model

In this study, a predictive model for the separation of gases via a polydimethylsiloxane (PDMS) membrane has been developed. This model takes into account the effects of gas composition and pressure at the membrane surfaces on the gas sorption and diffusion coefficients in the membrane. Computational fluid dynamics (CFD) modeling has been employed in order to predict the behavior of a gas mixture containing C₃H₈, CH₄, and H₂ at various operating conditions and three zones (upstream, downstream, and membrane body). Artificial neural network (ANN) modeling has been applied to predict sorption and diffusion coefficients of each component of the gas mixture in the membrane. A procedure of calculation has been applied to combine the CFD modeling and the ANN modeling in order to predict sorption, diffusion, and composition of each component at various sites of the membrane. The results determined using the developed prediction model have been found to be in agreement with those determined using experimental investigations with an average error of 10.21%. POLYM. ENG. SCI., 54:215–226, 2014. © 2013 Society of Plastics Engineers