Showing papers by "Islamic Azad University published in 2013"
TL;DR: This paper summarizes exclusively scalable techniques and focuses on strengths and limitations in respect to industrial applicability and regulatory requirements concerning liposomal drug formulations based on FDA and EMEA documents.
Abstract: Liposomes, sphere-shaped vesicles consisting of one or more phospholipid bilayers, were first described in the mid-60s. Today, they are a very useful reproduction, reagent, and tool in various scientific disciplines, including mathematics and theoretical physics, biophysics, chemistry, colloid science, biochemistry, and biology. Since then, liposomes have made their way to the market. Among several talented new drug delivery systems, liposomes characterize an advanced technology to deliver active molecules to the site of action, and at present, several formulations are in clinical use. Research on liposome technology has progressed from conventional vesicles to ‘second-generation liposomes’, in which long-circulating liposomes are obtained by modulating the lipid composition, size, and charge of the vesicle. Liposomes with modified surfaces have also been developed using several molecules, such as glycolipids or sialic acid. This paper summarizes exclusively scalable techniques and focuses on strengths, respectively, limitations in respect to industrial applicability and regulatory requirements concerning liposomal drug formulations based on FDA and EMEA documents.
2,374 citations
TL;DR: This paper comprehensively reviews the lignocellulosic wastes to bioethanol process with a focus on pretreatment methods, their mechanisms, advantages and disadvantages as well as the combinations of different pretreatment technologies.
Abstract: Pretreatment technologies are aimed to increase enzyme accessibility to biomass and yields of fermentable sugars. In general, pretreatment methods fall into four different categories including physical, chemical, physico-chemical, and biological. This paper comprehensively reviews the lignocellulosic wastes to bioethanol process with a focus on pretreatment methods, their mechanisms, advantages and disadvantages as well as the combinations of different pretreatment technologies. Moreover, the new advances in plant “omics” and genetic engineering approaches to increase cellulose composition, reduce cellulose crystallinity, produce hydrolases and protein modules disrupting plant cell wall substrates, and modify lignin structure in plants have also been expansively presented.
1,059 citations
TL;DR: This study presents an overview of the field of recommender systems with current generation of recommendation methods and examines comprehensively CF systems with its algorithms.
Abstract: Recommender Systems are software tools and techniques for suggesting items to users by considering their preferences in an automated fashion. The suggestions provided are aimed at support users in various decision- making processes. Technically, recommender system has their origins in different fields such as Information Retrieval (IR), text classification, machine learning and Decision Support Systems (DSS). Recommender systems are used to address the Information Overload (IO) problem by recommending potentially interesting or useful items to users. They have proven to be worthy tools for online users to deal with the IO and have become one of the most popular and powerful tools in E-commerce. Many existing recommender systems rely on the Collaborative Filtering (CF) and have been extensively used in E-commerce .They have proven to be very effective with powerful techniques in many famous E-commerce companies. This study presents an overview of the field of recommender systems with current generation of recommendation methods and examines comprehensively CF systems with its algorithms.
949 citations
TL;DR: In this article, the authors compared the performance of Web of Science and Scopus and provided a comprehensive comparison of these two databases to answer frequent questions which researchers ask, such as: How web of science and scopus are different? In which aspects these two database are similar? Or, if the researchers are forced to choose one of them, which one should they prefer?
Abstract: Nowadays, the world’s scientific community has been publishing an enormous number of papers in different scientific fields. In such environment, it is essential to know which databases are equally efficient and objective for literature searches. It seems that two most extensive databases are Web of Science and Scopus. Besides searching the literature, these two databases used to rank journals in terms of their productivity and the total citations received to indicate the journals impact, prestige or influence. This article attempts to provide a comprehensive comparison of these databases to answer frequent questions which researchers ask, such as: How Web of Science and Scopus are different? In which aspects these two databases are similar? Or, if the researchers are forced to choose one of them, which one should they prefer? For answering these questions, these two databases will be compared based on their qualitative and quantitative characteristics.
868 citations
TL;DR: This study introduces chaos into FA so as to increase its global search mobility for robust global optimization and shows that some chaotic FAs can clearly outperform the standard FA.
703 citations
TL;DR: This paper is a review of the recent literatures on enzyme immobilization by various techniques, the need for immobilization and different applications in industry, covering the last two decades.
Abstract: Compared to free enzymes in solution, immobilized enzymes are more robust and more resistant to environmental changes. More importantly, the heterogeneity of the immo-bilized enzyme systems allows an easy recovery of both enzymes and products, multiple re-use of enzymes, continuous operation of enzymatic processes, rapid termination of reactions, and greater variety of bioreactor designs. This paper is a review of the recent literatures on enzyme immobilization by various techniques, the need for immobilization and different applications in industry, covering the last two decades. The most recent papers, patents, and reviews on immobilization strategies and application are reviewed.
657 citations
TL;DR: In this article, a detailed description of the analysis used by the CMS Collaboration in the search for the standard model Higgs boson in pp collisions at the LHC, which led to the observation of a new boson.
Abstract: A detailed description is reported of the analysis used by the CMS Collaboration in the search for the standard model Higgs boson in pp collisions at the LHC, which led to the observation of a new boson. The data sample corresponds to integrated luminosities up to 5.1 inverse femtobarns at sqrt(s) = 7 TeV, and up to 5.3 inverse femtobarns at sqrt(s) = 8 TeV. The results for five Higgs boson decay modes gamma gamma, ZZ, WW, tau tau, and bb, which show a combined local significance of 5 standard deviations near 125 GeV, are reviewed. A fit to the invariant mass of the two high resolution channels, gamma gamma and ZZ to 4 ell, gives a mass estimate of 125.3 +/- 0.4 (stat) +/- 0.5 (syst) GeV. The measurements are interpreted in the context of the standard model Lagrangian for the scalar Higgs field interacting with fermions and vector bosons. The measured values of the corresponding couplings are compared to the standard model predictions. The hypothesis of custodial symmetry is tested through the measurement of the ratio of the couplings to the W and Z bosons. All the results are consistent, within their uncertainties, with the expectations for a standard model Higgs boson.
643 citations
TL;DR: In this paper, a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods is introduced, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions.
Abstract: In recent years there has been a growing attention towards use of solar energy. The main advantages of photovoltaic (PV) systems employed for harnessing solar energy are lack of greenhouse gas emission, low maintenance costs, fewer limitations with regard to site of installation and absence of mechanical noise arising from moving parts. However, PV systems suffer from relatively low conversion efficiency. Therefore, maximum power point tracking (MPPT) for the solar array is essential in a PV system. The nonlinear behavior of PV systems as well as variations of the maximum power point with solar irradiance level and temperature complicates the tracking of the maximum power point. A variety of MPPT methods have been proposed and implemented. This review paper introduces a classification scheme for MPPT methods based on three categories: offline, online and hybrid methods. This classification, which can provide a convenient reference for future work in PV power generation, is based on the manner in which the control signal is generated and the PV power system behavior as it approaches steady state conditions. Some of the methods from each class are simulated in Matlab/Simulink environment in order to compare their performance. Furthermore, different MPPT methods are discussed in terms of the dynamic response of the PV system to variations in temperature and irradiance, attainable efficiency, and implementation considerations.
549 citations
TL;DR: A new metaheuristic optimization algorithm, called bat algorithm (BA), is used to solve constraint optimization tasks, and the optimal solutions obtained are found to be better than the best solutions provided by the existing methods.
Abstract: In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to solve constraint optimization tasks. BA is verified using several classical benchmark constraint problems. For further validation, BA is applied to three benchmark constraint engineering problems reported in the specialized literature. The performance of the bat algorithm is compared with various existing algorithms. The optimal solutions obtained by BA are found to be better than the best solutions provided by the existing methods. Finally, the unique search features used in BA are analyzed, and their implications for future research are discussed in detail.
489 citations
TL;DR: ZnO flower-like showed significantly higher photocatalytic inactivation than ZnO rod- and sphere-like against E. coli compared with S. aureus, and it was found that the antibacterial activity of ZNO increased with decreasing crystallite size.
Abstract: ZnO materials with different morphologies have been synthesized via a simple solvothermal method using different solvents without any catalysts, templates or surfactants. The ZnO samples are employed in the inactivation of gram-negative Escherichia coli and gram-positive Staphylococcus aureus in MilliQ water. The photocatalytic activities of samples to degrade an azo dye, Acid Orange 74 (CI 18745), were also tested. XRD data showed that single-phase ZnO with the wurtzite crystal structure but different growth habits were obtained in the different solvents. SEM imaging illustrated that ZnO with flower-like, rod-like, and spherical shape were produced when water, 1-hexanol, and ethylene glycol were used as the solvent, respectively. The optical properties of the as-prepared ZnO materials were investigated by UV-vis absorption and photoluminescence spectra. The antibacterial efficiencies were affected by the physiological status of the bacterial cells, different morphologies and crystal growth habits, particle size and optical properties of ZnO samples. Results indicate that ZnO flower-like showed significantly higher photocatalytic inactivation than ZnO rod- and sphere-like against E. coli compared with S. aureus. It was found that the antibacterial activity of ZnO increased with decreasing crystallite size. The inactivation efficiencies for both organisms under light conditions were higher than under dark conditions. The obtained results were discussed according to the morphologies, optical and structural properties of ZnO powders as key parameters in photocatalytic and antibacterial activity.
391 citations
01 Feb 2013
TL;DR: A forecasting model based on chaotic mapping, firefly algorithm, and support vector regression (SVR) is proposed to predict stock market price and performs best based on two error measures, namely mean squared error (MSE) and mean absolute percent error (MAPE).
Abstract: Due to the inherent non-linearity and non-stationary characteristics of financial stock market price time series, conventional modeling techniques such as the Box-Jenkins autoregressive integrated moving average (ARIMA) are not adequate for stock market price forecasting. In this paper, a forecasting model based on chaotic mapping, firefly algorithm, and support vector regression (SVR) is proposed to predict stock market price. The forecasting model has three stages. In the first stage, a delay coordinate embedding method is used to reconstruct unseen phase space dynamics. In the second stage, a chaotic firefly algorithm is employed to optimize SVR hyperparameters. Finally in the third stage, the optimized SVR is used to forecast stock market price. The significance of the proposed algorithm is 3-fold. First, it integrates both chaos theory and the firefly algorithm to optimize SVR hyperparameters, whereas previous studies employ a genetic algorithm (GA) to optimize these parameters. Second, it uses a delay coordinate embedding method to reconstruct phase space dynamics. Third, it has high prediction accuracy due to its implementation of structural risk minimization (SRM). To show the applicability and superiority of the proposed algorithm, we selected the three most challenging stock market time series data from NASDAQ historical quotes, namely Intel, National Bank shares and Microsoft daily closed (last) stock price, and applied the proposed algorithm to these data. Compared with genetic algorithm-based SVR (SVR-GA), chaotic genetic algorithm-based SVR (SVR-CGA), firefly-based SVR (SVR-FA), artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS), the proposed model performs best based on two error measures, namely mean squared error (MSE) and mean absolute percent error (MAPE).
TL;DR: A comprehensive design-oriented study of the multiple reference frame-based and dual second-order generalized integrator-based PLLs, which simplifies the parameter design and the stability analysis and the experimental results are presented to support the theoretical analysis.
Abstract: In grid-connected applications, the synchronous reference frame phase-locked loop (SRF-PLL) is a commonly used synchronization technique due to the advantages it offers such as ease of implementation and robust performance Under ideal grid conditions, the SRF-PLL enables a fast and accurate phase/frequency detection; however, unbalanced and distorted grid conditions highly degrade its performance To overcome this drawback, several advanced PLLs have been proposed, such as the multiple reference frame-based PLL, the dual second-order generalized integrator-based PLL, and the multiple complex coefficient filter-based PLL In this paper, a comprehensive design-oriented study of these advanced PLLs is presented The starting point of this study is to derive the small-signal model of the aforementioned PLLs, which simplifies the parameter design and the stability analysis Then, a systematic design procedure to fine tune the PLLs parameters is presented The stability margin, the transient response, and the disturbance rejection capability are the key factors that are considered in the design procedure Finally, the experimental results are presented to support the theoretical analysis
TL;DR: In this article, the fundamental understanding of structure-properties relationship in automotive steels resistance spot welds is discussed. And a brief review of friction stir spot welding, as an alternative to RSW, is also included.
Abstract: Spot welding, particularly resistance spot welding (RSW), is a critical joining process in automotive industry. The development of advanced high strength steels for applications in automotive industry is accompanied with a challenge to better understand the physical and mechanical metallurgy of these materials during RSW. The present paper critically reviews the fundamental understanding of structure–properties relationship in automotive steels resistance spot welds. The focus is on the metallurgical characteristics, hardness–microstructure correlation, interfacial to pullout failure mode transition and mechanical performance of steel resistance spot welds under quasi-static, fatigue and impact loading conditions. A brief review of friction stir spot welding, as an alternative to RSW, is also included.
TL;DR: In this article, the authors used structural equation modeling to determine relations between transformational leadership, organizational learning, knowledge management, organizational innovation, and organizational performance among Iranian manufacturing companies through structural equation modelling.
Abstract: The aim of this study is to determine relations between transformational leadership, organizational learning, knowledge management, organizational innovation, and organizational performance among Iranian manufacturing companies through structural equation modeling. Two hundred eighty senior, executive, administrative, and other-level managers are selected from among 106 companies having more than 50 employees. Data are analyzed using structural equation modeling. The following findings are found: transformational leadership directly influenced organizational learning and knowledge management. Organizational learning directly and positively influenced knowledge management of manufacturing firms. Transformational leadership positively influenced organizational innovation and organizational performance of manufacturing firms. Organizational learning and knowledge management directly influenced organizational innovation; whereas organizational learning and organizational innovation directly influenced organizational performance among manufacturing firms. Meanwhile, transformational leadership positively and indirectly influenced organizational innovation through organizational learning and knowledge management. Knowledge management and organizational learning effected organizational performance indirectly by organizational innovation. The fit indices shows that the proposed model have an appropriate fit (χ2/df = 2.33, RMSEA = 0.069, NFI = 0.95, NNFI = 0.95, CFI = 97). If leaders of manufacturing firms undertake a transformational role and use organizational learning and knowledge management, this will facilitate organizational innovation and will consequently improve organizational performance to a great extent in manufacturing firms.
TL;DR: In this paper, the authors investigated the lead ion removal of the multi-walled carbon nanotubes (MWCNTs) and oxidized MWCNT-COOH surfaces as adsorbents.
Abstract: This study investigated the lead ion removal of the multi-walled carbon nanotubes (MWCNTs) and oxidized multi-walled carbon nanotubes (MWCNT-COOH). The main purpose of this work is to study the possibilities on the removal of Pb(II) ions from aqueous solutions using MWCNTs and MWCNT-COOH surfaces as adsorbents. Removal of Pb(II) ions was investigated using solutions with different concentrations in the range 10 to 100 mg/L. In this study, removal of Pb(II) ions on surfaces has been investigated by atomic absorption spectrophotometry. The microstructure of carbon nanotubes were characterized using scanning electron microscopy. Three different kinetic theories were applied to experimental data. The kinetic rates were modeled using the pseudo-first-order, four-type linear pseudo-second-order, and intraparticle diffusion. The pseudo-second-order model was found to explain the adsorption kinetics most effectively. The results indicated a significant potential of the multi-walled carbon nanotube as an adsorbent for Pb(II) ion removal.
TL;DR: In this article, the potential of the prepared nanofiber membrane for adsorption of nickel (Ni), cadmium (Cd), lead (Pb) and copper (Cu) from aqueous solution was investigated.
TL;DR: Through a detailed mathematical analysis, it is shown that these two PLL structures are equivalent to each other, from the control point of view, and a linearized model is developed which is valid for both PLLs.
Abstract: Recently, several advanced phase-locked loop (PLL) techniques have been proposed for single-phase applications Among these, the Park-PLL and the second-order-generalized-integrator-based PLL are very attractive, owing to their simple digital implementation, low computational burden, and desired performance under frequency-varying and harmonically distorted grid conditions Despite the wide acceptance and use of these two advanced PLLs, no comprehensive design guidelines to fine-tune their parameters have been reported yet Through a detailed mathematical analysis, it is shown that these two PLL structures are equivalent to each other, from the control point of view Then, a linearized model is developed which is valid for both PLLs The derived model significantly simplifies the stability analysis and the parameter design To fine-tune the PLL parameters, a systematic design approach is suggested afterward, which guarantees a fast dynamic response, a high disturbance rejection ability, and a robust performance Finally, the simulation and experimental results are presented to support the theoretical analysis
TL;DR: The approaches which are applied to develop CAD systems on mammography and ultrasound images are presented and the performance evaluation metrics of CAD systems are reviewed.
TL;DR: In this paper, the role of starch as a thermoplastic polymer, transformation and melting mechanisms, plasticization and plasticizers, reactive extrusion (REX) and modifications, retrogradation, biodegradability, filler and blenders, and nano-particle incorporation in TPS polymers were reviewed.
Abstract: Thermoplastic starch (TPS) polymers were reviewed in this article. This review was categorized into the following studies: the role of starch as a thermoplastic polymer, transformation and melting mechanisms, plasticization and plasticizers, reactive extrusion (REX) and modifications, retrogradation, biodegradability, filler and blenders, and nano-particle incorporation in thermoplasticstarch. This categorizationallows us to understandthe developments in this field in recent years and shows that the major challenges in the future are reducing sensitivity to moisture and retarding retrogradation of the thermoplastic matrix. Moreover, nano-particles such as clay can be used in TPS matrices to overcome these disadvantages.
TL;DR: In this paper, a novel time varying acceleration coefficients particle swarm optimization (TVAC-PSO) algorithm is implemented to solve combined heat and power economic dispatch (CHPED) problem.
TL;DR: In this article, the effects of substitution of sand with PET processed particles have been investigated with cubic and cylindrical specimens with different water to cement ratios and physical properties of fresh concrete were evaluated.
TL;DR: In this article, results of searches for heavy stable charged particles produced in pp collisions at 7 and 8 TeV are presented corresponding to an integrated luminosity of 5.0 and 18.8 inverse femtobarns, respectively.
Abstract: Results of searches for heavy stable charged particles produced in pp collisions at sqrt(s) = 7 and 8 TeV are presented corresponding to an integrated luminosity of 5.0 inverse femtobarns and 18.8 inverse femtobarns, respectively. Data collected with the CMS detector are used to study the momentum, energy deposition, and time-of-flight of signal candidates. Leptons with an electric charge between e/3 and 8e, as well as bound states that can undergo charge exchange with the detector material, are studied. Analysis results are presented for various combinations of signatures in the inner tracker only, inner tracker and muon detector, and muon detector only. Detector signatures utilized are long time-of-flight to the outer muon system and anomalously high (or low) energy deposition in the inner tracker. The data are consistent with the expected background, and upper limits are set on the production cross section of long-lived gluinos, scalar top quarks, and scalar tau leptons, as well as pair produced long-lived leptons. Corresponding lower mass limits, ranging up to 1322 GeV for gluinos, are the most stringent to date.
TL;DR: The results suggest that ZEO and MEO have the potential to be directly incorporated into corn starch to prepare antimicrobial biodegradable films for various food packaging applications.
01 Feb 2013
TL;DR: Based on a real case of MPFM, a new method for oil rate prediction of wells base on Fuzzy logic, Artificial Neural Networks (ANN) and Imperialist Competitive Algorithm is presented, proving the effectiveness, robustness and compatibility of the ICA-ANN model.
Abstract: Multiphase flow meters (MPFMs) are utilized to provide quick and accurate well test data in numerous numbers of oil production applications like those in remote or unmanned locations topside exploitations that minimize platform space and subsea applications. Flow rates of phases (oil, gas and water) are most important parameter which is detected by MPFMs. Conventional MPFM data collecting is done in long periods; because of radioactive sources usage as detector and unmanned location due to wells far distance. In this paper, based on a real case of MPFM, a new method for oil rate prediction of wells base on Fuzzy logic, Artificial Neural Networks (ANN) and Imperialist Competitive Algorithm is presented. Temperatures and pressures of lines have been set as input variable of network and oil flow rate as output. In this case a 1600 data set of 50 wells in one of the northern Persian Gulf oil fields of Iran were used to build a database. ICA-ANN can be used as a reliable alternative way without personal and environmental problems. The performance of the ICA-ANN model has also been compared with ANN model and Fuzzy model. The results prove the effectiveness, robustness and compatibility of the ICA-ANN model.
TL;DR: In this paper, the state-of-the-art in research works on non-isolated DC-DC buck, boost, buck-boost, Cuk and SEPIC converters and their characteristics, to find a solution best suiting an application with maximum power point tracking.
Abstract: Photovoltaic (PV) is a fast growing segment among renewable energy (RE) systems, whose development is owed to depleting fossil fuel and climate-changing environmental pollution. PV power output capacity, however, is still low and the associated costs still high, so efforts continue to develop PV converter and its controller, aiming for higher power-extracting efficiency and cost effectiveness. Different algorithms have been proposed for Maximum Power Point Tracking (MPPT). Since the choice of right converter for different application has an important influence in the optimum performance of the photovoltaic system, this paper reviews the state-of-the-art in research works on non-isolated DC–DC buck, boost, buck–boost, Cuk and SEPIC converters and their characteristics, to find a solution best suiting an application with Maximum Power Point Tracking. Review shows that there is a limitation in the system's performance according to the type of converter used. In can be concluded that the best selection of DC–DC converter which is really suitable and applicable in the PV system is the buck–boost DC–DC converter since it is capable of achieving optimal operation regardless of the load value with negotiable performance efficiency and price issue.
TL;DR: The pre-print version of the final publishing paper that is available from the link below as mentioned in this paper is also available from Amazon Mechanical Turk, however, the preprint version requires a subscription.
Abstract: The article is the pre-print version of the final publishing paper that is available from the link below.
TL;DR: The novel sensor exhibited an obviously catalytic activity towards the oxidation of Sudan I, which can be confirmed by the increased oxidation peak current and the decreased oxidation peak potential when compared with the bare carbon paste electrode (CPE).
TL;DR: In this paper, the photodecolorization of a mixture of the methylene blue and rhodamine B cationic dyes was studied using CuO/nano-zeolite X catalyst under solar irradiation.
TL;DR: The traditional uses and pharmacological effects of total extract and individual active alkaloids of P. harmala (Syrian rue) are reviewed and harmine is the most studied among these naturally occurring alkaloid.
Abstract: Wild Syrian rue (Peganum harmala L. family Zygophyllaceae) is well-known in Iran and various parts of this plant including, its seeds, bark, and root have been used as folk medicine. Recent years of research has demonstrated different pharmacological and therapeutic effects of P. harmala and its active alkaloids, especially harmine and harmaline. Analytical studies on the chemical composition of the plant show that the most important constituents of this plant are beta-carboline alkaloids such as harmalol, harmaline, and harmine. Harmine is the most studied among these naturally occurring alkaloids. In addition to P. harmala (Syrian rue), these beta-carbolines are present in many other plants such as Banisteria caapi and are used for the treatment of different diseases. This article reviews the traditional uses and pharmacological effects of total extract and individual active alkaloids of P. harmala (Syrian rue).
TL;DR: In this paper, a probabilistic framework based on 2m Point Estimate Method (2m PEM) was proposed to consider the uncertainties in the optimal energy management of the MGs.