Sharif Digital Repository

In this study, the effect of adding walnut shell-based powdered activated carbon (WS) to a bench-scale dissolved air flotation (DAF) column on oil removal was investigated. All experiments were conducted using synthetically prepared wastewater containing low but stable concentrations of heavy fuel oil. After comparing the effect of different WS doses from 0 (blank) to 40 mg/L at the saturator pressure of 5 bar and 10 min flotation time, 20 mg/L WS was chosen as the optimal concentration. In order to find the best flotation time for efficient use of WS capacity, experiments were repeated with and without 20 mg/L WS at longer flotation times. According to the obtained results, by adding WS,... 

Two sequencing batch reactors were operated to investigate the effect of influent alkalinity and reactor pH on aerobic granulation. In the first reactor R1 with high influent alkalinity the pH was adjusted in the neutral range, and in the second reactor R2 with low alkalinity the pH was held within the acidic range. The R1-dominating species were bacteria and the appearance time of granules was three weeks after reactor start-up. On the other hand, the acidic environment of R2 provided favorable conditions for fungal growth, and rapid granule formation occurred within the first week of operation. The varying microbial structure of granules resulted in different reactor performance in terms... 

Abstract Background: The aim of this study is to accelerate and improve aerobic granulation within a Sequencing Batch Reactor (SBR) by cationic polymer addition. Methods: To identify whether the polymer additive is capable of enhancing granule formation, two SBRs (R1 and R2, each 0.15 m in diameter and 2 m in height) are used by feeding synthetic wastewater. The cationic polymer with concentration of 30 to 2 ppm is added to R2, while no cationic polymer is added to R1. Results: Results show that the cationic polymer addition causes faster granule formation and consequently shorter reactor start-up period. The polymer-amended reactor contains higher concentration of biomass with better... 

The learning vector quantization (LVQ) neural network is a useful tool for pattern recognition. Based on the network weights obtained from the training set, prediction can be made for the unknown objects. In this paper, discrimination of wines based on 2D NMR spectra is performed using LVQ neural networks with orthogonal signal correction (OSC). OSC has been proposed as a data preprocessing method that removes from X information not correlated to Y. Moreover, the partial least squares discriminant analysis (PLS-DA) method has also been used to treat the same data set. It has been found that the OSC-LVQ neural networks method gives slightly better prediction results than OSC-PLS-DA © 2005... 

Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS) combined to multivariate curve resolution-alternating least-squares (MCR-ALS) is proposed for the resolution and quantification of very complex mixtures of compounds such as polycyclic aromatic hydrocarbons (PAHs) in heavy fuel oil (HFO). Different GC × GC-TOFMS data slices acquired during the analysis of HFO samples and PAH standards were simultaneously analyzed using the MCR-ALS method to resolve the pure component elution profiles in the two chromatographic dimensions as well as their pure mass spectra. Outstandingly, retention time shifts within and between GC × GC runs were not affecting... 

This paper describes the development and implementation of MCRC software, chemometric software for Multivariate Curve Resolution of two-way Chromatographic data. MCRC software is developed for chemometric analysis of chromatographic data; however, it may also be used for other types of multivariate data. It consists of five groups of techniques for preprocessing, chemical rank determination, local rank analysis, multivariate resolution and peak integration. This software has the ability of the analysis of complex multi-component chromatographic signals of gas chromatography-mass spectrometry (GC-MS) and high performance liquid chromatography-diode array detection (HPLC-DAD). The software... 

This paper presents a novel hybrid approach for intrusion detection in computer networks. The proposed approach combines an evolutionary based fuzzy system with an artificial immune system to generate high quality fuzzy classification rules. The performance of final fuzzy classification system has been investigated using the KDD-Cup99 benchmark dataset. The results indicate that in comparison to several traditional techniques, such as C4.5, Naïve Bayes, k-NN and SVM, the proposed hybrid approach achieves better classification accuracies for most of the classes of the intrusion detection classification problem. Therefore, the resulted fuzzy classification rules can be used to produce a... 

Reverse Osmosis (RO) is a rapid-developing desalination technology; however, it suffers from inefficient energy consumption. To reduce energy consumption, in this study, reverse osmosis thin-film composite membrane (TFC) module was prepared and composed of m-phenylenediamine (MPD), graphene oxide, and 1,3,5-benzenetricarbonyl chloride (TMC) by interfacial polymerization on the surface of a polysulfone substrate. The graphene oxide was embedded in the mentioned thin-film composite by adding it to MPD aqueous solution to enhance permeation flux and, thus, reduce energy consumption. This study assessed the performance of the membrane using a lab-scale RO setup and evaluated permeability and... 

We use the Fokker-Planck equation and model the dispersive dynamics of solid particles in annular protoplanetary disks whose gas component is more massive than the particle phase. We model particle-gas interactions as hard sphere collisions, determine the functional form of diffusion coefficients, and show the existence of two global unstable modes in the particle phase. These modes have spiral patterns with the azimuthal wavenumber m = 1 and rotate slowly. We show that in ring-shaped disks, the phase-space density of solid particles increases linearly in time toward an accumulation point near the location of pressure maximum, while instabilities grow exponentially. Therefore, planetesimals... 

I formulate a general finite element method (FEM) for self-gravitating stellar systems. I split the configuration space to finite elements, and express the potential and density functions over each element in terms of their nodal values and suitable interpolating functions. General expressions are then introduced for the Hamiltonian and phase-space distribution functions of the stars that visit a given element. Using the weighted residual form of Poisson's equation, I derive the Galerkin projection of the perturbed collisionless Boltzmann equation, and assemble the global evolutionary equations of nodal distribution functions. The FEM is highly adaptable to all kinds of potential and density... 

I utilize the Petrov-Galerkin formulation and develop a new method for solving the unsteady collisionless Boltzmann equation in both the linear and nonlinear regimes. In the first-order approximation, the method reduces to a linear eigen-value problem which is solved using standard numerical methods. I apply the method to the dynamics of a model stellar disk which is embedded in the field of a soft-centered logarithmic potential. The outcome is the full spectrum of eigen-frequencies and their conjugate normal modes for prescribed azimuthal wavenumbers. The results show that the fundamental bar mode is isolated in the frequency space, while spiral modes belong to discrete families that... 

This chapter covers a part of the spectrum of neural-network uses in analytical chemistry. Different architectures of neural networks are described briefly. The chapter focuses on the development of three-layer artificial neural network for modeling the anti-HIV activity of the HETP derivatives and activity parameters (pIC 50) of heparanase inhibitors. The use of a genetic algorithm-kernel partial least squares algorithm combined with an artificial neural network (GA-KPLS-ANN) is described for predicting the activities of a series of aromatic sulfonamides. The retention behavior of terpenes and volatile organic compounds and predicting the response surface of different detection systems are... 

I decompose the unstable growing modes of stellar disks to their Fourier components and present the physical mechanism of instabilities in the context of resonances. When the equilibrium distribution function is a nonunifonn function of the orbital angular momentum, the capture of stars into the corotation resonance imbalances the disk angular momentum and triggers growing bar and spiral modes. The stellar disk can then recover its angular momentum balance through the response of nonresonant stars. I carry out a complete analysis of orbital structure corresponding to each Fourier component in the radial angle and present a mathematical condition for the occurrence of van Kampen modes, which... 

In this letter, we study a receiver architecture technique for joint resource allocation in a downlink (DL) multi-user multi-carrier non-orthogonal multiple access (MC-NOMA) network with simultaneous wireless information and power transfer (SWIPT). In this framework, the subcarrier set is partitioned into two groups that are assigned to perform information decoding (ID) and energy harvesting (EH) at the receiver side based on the optimization problem. This letter seeks to maximize energy harvesting while meeting a minimum data-rate requirement for each user. The underlying optimization problem is mixed-integer non-linear programming (MINLP). To that end, we employ the monotonic optimization...