Synthesis of Clay/Poly (styrene/2-ethylhexyl acrylate) Nanocomposite Latexes via Emulsion Polymerization

Silicon - In this research, nanocomposite latex based on polystyrene-co-2-ethylhexyl acrylate with layered silicate was synthesized by emulsion polymerization procedure. For increasing...     

Effect of electric arc and ladle furnace slags on the strength and swelling behavior of cement-stabilized expansive clay

Bulletin of Engineering Geology and the Environment - The current research evaluated the effect of expansive clay stabilization using a combination of cement (0, 2, 5, 8%) with electric arc furnace...     

Role of Ribes khorassanicum in the biosynthesis of AgNPs and their antibacterial properties

Silver nanoparticles (AgNPs) have been biosynthesised through the extracts of Ribes khorassanicum fruits, which served as the reducing agents and capping agents. Biosynthesised AgNPs have been found to be ultraviolet–visible (UV–vis) absorption spectra since they have displayed one surface plasmon resonance peak at 438 nm, attesting the formation of spherical NPs. These particles have been characterised by UV–vis, field‐emission scanning electron microscopy, energy‐dispersive X‐ray spectroscopy, X‐ray diffraction, Fourier transform infrared spectroscopy, and transmission electron microscopy analysis. The formation of AgNPs at 1.0 mM concentration of AgNO₃ has resulted in NPs that contained mean diameters in a range of 20–40 nm. The green‐synthesised AgNPs have demonstrated high antibacterial effect against pathogenic bacteria (i.e. Staphylococcus aureus, Escherichia coli, and Pseudomonas aeruginosa). Biosynthesising metal NPs through plant extracts can serve as the facile and eco‐friendly alternative for chemical and/or physical methods that are utilised for large‐scale nanometal fabrication in various medical and industrial applications.Inspec keywords: X‐ray diffraction, X‐ray chemical analysis, nanofabrication, surface plasmon resonance, nanoparticles, antibacterial activity, microorganisms, scanning electron microscopy, silver, nanomedicine, visible spectra, ultraviolet spectra, transmission electron microscopy, Fourier transform infrared spectra, field emission scanning electron microscopy, biomedical materialsOther keywords: antibacterial properties, silver nanoparticles, reducing agents, capping agents, surface plasmon resonance peak, spherical NPs, field‐emission scanning electron microscopy, energy‐dispersive X‐ray spectroscopy, X‐ray diffraction, transmission electron microscopy analysis, plant extracts, ultraviolet‐visible absorption spectra, Fourier transform infrared spectroscopy, antibacterial effect, Ribes khorassanicum fruits, Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, surface plasmon resonance, AgNO₃ , Ag     

Minimal realization of nonlinear systems described by input-outputdifference equations

We consider a general class of nonlinear discrete-time systems described by their input-output (I/O) relationship. We first present the necessary and sufficient conditions for existence of a local observable state-space realization of the system and an explicit algorithm for computing it. In cases where the I/O map and its resulting realization are nonminimal, we formulate an algorithm for extracting its minimal realization whenever possible. The developed theory and algorithms are illustrated by means of several examples     

Clean treatment of rejected brine by zero liquid discharge thermal desalination in Persian Gulf countries

Clean Technologies and Environmental Policy - In this study, four zero liquid discharge thermal desalination processes were technoeconomically investigated to select the most efficient and economic...     

Vulnerability analysis of networks to detect multiphase attacks using the actor-based language Rebeca

Increasing use of networks and their complexity make the task of security analysis more and more complicated. Accordingly, automatic verification approaches have received more attention recently. In this paper, we investigate applying of an actor-based language based on reactive objects for analyzing a network environment communicating via Transport Protocol Layer (TCP). The formal foundation of the language and available tools for model checking provide us with formal verification support. Having the model of a typical network including client and server, we show how an attacker may combine simple attacks to construct a complex multiphase attack. We use Rebeca language to model the network of hosts and its model checker to find counter-examples as violations of security of the system. Some simple attacks have been modeled in previous works in this area, here we detect these simple attacks in our model and then verify the model to find more complex attacks which may include simpler attacks as their steps. We choose Rebeca because of its powerful yet simple actor-based paradigm in modeling concurrent and distributed systems. As the real network environment is asynchronous and event-based, Rebeca can be utilized to specify and verify the asynchronous systems, including network protocols.     

LADPSO: using fuzzy logic to conduct PSO algorithm

Optimization plays a critical role in human modern life. Nowadays, optimization is used in many aspects of human modern life including engineering, medicine, agriculture and economy. Due to the growing number of optimization problems and their growing complexity, we need to improve and develop theoretical and practical optimization methods. Stochastic population based optimization algorithms like genetic algorithms and particle swarm optimization are good candidates for solving complex problems efficiently. Particle swarm optimization (PSO) is an optimization algorithm that has received much attention in recent years. PSO is a simple and computationally inexpensive algorithm inspired by the social behavior of bird flocks and fish schools. However, PSO suffers from premature convergence, especially in high dimensional multi-modal functions. In this paper, a new method for improving PSO has been introduced. The Proposed method which has been named Light Adaptive Particle Swarm Optimization is a novel method that uses a fuzzy control system to conduct the standard algorithm. The suggested method uses two adjunct operators along with the fuzzy system in order to improve the base algorithm on global optimization problems. Our approach is validated using a number of common complex uni-modal/multi-modal benchmark functions and results have been compared with the results of Standard PSO (SPSO2011) and some other methods. The simulation results demonstrate that results of the proposed approach is promising for improving the standard PSO algorithm on global optimization problems and also improving performance of the algorithm.