Copper/copper oxide nanoparticles synthesis using Stachys lavandulifolia and its antibacterial activity

Nanoparticles of copper/cuprous oxide (Cu/Cu₂ O) were successfully synthesised by a green chemistry route. The synthesis process was carried out using an extract of Stachys lavandulifolia as both reducing and capping agents with a facile procedure. The nanoparticles were characterised by different techniques including X‐ray diffraction, indicating that the synthesised sample comprised both copper and cuprous oxide entity. The nanoparticles had a mean size of 80 nm and represented an impressive bactericidal effect on Pseudomonas aeruginosa.Inspec keywords: copper, copper compounds, nanoparticles, nanofabrication, nanomedicine, antibacterial activity, X‐ray diffractionOther keywords: nanoparticles synthesis, Stachys lavandulifolia, antibacterial activity, green chemistry route, reducing agents, capping agents, X‐ray diffraction, bactericidal effect, Pseudomonas aeruginosa, Cu‐Cu₂ O     

Instance of hidden instability traps in intermittent transition of moving masses along a flexible beam

The problem of an elastic beam under the periodic loading of successive moving masses is investigated as a pragmatic case for studying dynamic stability of linear time-varying systems. This model serves to highlight the odds of multi-solutions coexistence, a form of hidden instability which reveals dangerous as it may be precipitated by the slightest disturbance or variation in the model. Since no engineering model perfectly represents a physical system, such situations for which Floquet theory naively predicts stability are potentially inevitable. The harmonic balancing method is used in order to thoroughly explore the stability diagrams for detecting these instability gaps. Although this phenomenon has also been described in other physical systems, it has not been addressed for beam–moving mass systems. This result may find particular importance in applications involving self-induced vibrations of elastic structures and hence also appears of practical relevance.     

Adaptive neuro-fuzzy inference system multi-objective optimization using the genetic algorithm/singular value decomposition method for modelling the discharge coefficient in rectangular sharp-crested side weirs

In the present article, the adaptive neuro-fuzzy inference system (ANFIS) is employed to model the discharge coefficient in rectangular sharp-crested side weirs. The genetic algorithm (GA) is used for the optimum selection of membership functions, while the singular value decomposition (SVD) method helps in computing the linear parameters of the ANFIS results section (GA/SVD-ANFIS). The effect of each dimensionless parameter on discharge coefficient prediction is examined in five different models to conduct sensitivity analysis by applying the above-mentioned dimensionless parameters. Two different sets of experimental data are utilized to examine the models and obtain the best model. The study results indicate that the model designed through GA/SVD-ANFIS predicts the discharge coefficient with a good level of accuracy (mean absolute percentage error?=?3.362 and root mean square error?=?0.027). Moreover, comparing this method with existing equations and the multi-layer perceptron–artificial neural network (MLP-ANN) indicates that the GA/SVD-ANFIS method has superior performance in simulating the discharge coefficient of side weirs.     

Biosynthesis of SeNPs by Mycobacterium bovis and their enhancing effect on the immune response against HBs antigens: an in vivo study

Conventional hepatitis B vaccine contains alum but is less effective to induce Th1 response. Selenium nanoparticles and Bacillus Calmette–Guerin were reported as immune modulators. In this study, SeNPs were extracted from Mycobacterium bovis and characterised. SeNPs were mixed with HBs‐Ag and administered to the mice to investigate he immune response pattern. With an addition of Se ions at a sub‐inhibitory concentration to the Sauton medium broth after 24 h, SeNPs were extracted from M. bovis and characterised by Fourier transform infrared spectroscopy, dynamic light scattering, atomic forcemicroscopy, energy dispersive X‐ray spectrum, transmission electron microscopy, and thermogravimetric analysis. Furthermore, female inbred BALB/c mice were injected subcutaneously on the first, 14th, 28th day with 100 and 200 µg doses of that SeNPs supplemented with HBs‐Ag vaccine. Later, the total antibody, isotypes of Immunoglobulin G1, Interlukin 4, and interferon‐γ were measured by enzye‐linked immunosorbent assay. The size of the SeNPs was <150 nm. Level of total antibody and immunoglobulin G2a increased significantly in the group that received 200 µg/ml nano selenium extracted from M. bovis. SeNPs in dose of 200 µg coated with organic materials of M. bovis could induce an influential immune response in relation to the conventional HBs‐Ag vaccine.Inspec keywords: selenium, nanoparticles, nanofabrication, microorganisms, Fourier transform spectra, infrared spectra, light scattering, atomic force microscopy, X‐ray chemical analysis, transmission electron microscopy, thermal analysis, nanomedicineOther keywords: biosynthesis, selenium nanoparticles, Mycobacterium bovis, enhnced immune response, HBs antigens, Bacillus Calmette‐Guerin, immune modulators, biogenic SeNPs, immune response pattern, Sauton medium broth, Fourier transform infrared spectroscopy, dynamic light scattering, atomic force microscopy, energy dispersive X‐ray spectrum, transmission electron microscopy, thermogravimetric analysis, female inbred BALB/c mice, antibody, IgG1 isotype, IgG2a isotype, IL₄ isotype, interferon‐γ, enzyme‐linked immunosorbent assay, bacterium, time 24 h, time 14 day, time 28 day, Se     

Green synthesis of silver nanoparticles using Glaucium corniculatum (L.) Curtis extract and evaluation of its antibacterial activity

The metal nanoparticles, due to interesting features such as electrical, optical, chemical and magnetic properties, have been investigated repeatedly. Also, the mentioned nanoparticles have specific uses in terms of their antibacterial activity. The biosynthesis method is more appropriate than the chemical method for producing the nanoparticles because it does not need any special facilities; it is also economically affordable. In the current study, the silver nanoparticles (AgNPs) were obtained by using a very simple and low‐cost method via Glaucium corniculatum (L.) Curtis plant extract. The characteristics of the AgNPs were investigated using techniques including: X‐ray diffraction, transmission electron microscopy (TEM), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy. The SEM and TEM images showed that the nanoparticles had a spherical shape, and the mean diameter of them was 53.7 and 45 nm, respectively. The results of the disc diffusion test used for measuring the anti‐bacterial activity of the synthesised nanoparticles indicated that the formed nanoparticles possessed a suitable anti‐bacterial activity.Inspec keywords: silver, nanoparticles, antibacterial activity, nanomedicine, nanofabrication, X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, Fourier transform infrared spectraOther keywords: green synthesis, silver nanoparticles, Glaucium corniculatum Curtis extract, antibacterial activity, metal nanoparticles, biosynthesis method, X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, SEM, TEM, spherical shape, disc diffusion test, Ag     

Multi expression programming: a new approach to formulation of soil classification

This paper presents an alternative approach to formulation of soil classification by means of a promising variant of genetic programming (GP), namely multi expression programming (MEP). Properties of soil, namely plastic limit, liquid limit, color of soil, percentages of gravel, sand, and fine-grained particles are used as input variables to predict the classification of soils. The models are developed using a reliable database obtained from the previously published literature. The results demonstrate that the MEP-based formulas are able to predict the target values to high degree of accuracy. The MEP-based formulation results are found to be more accurate compared with numerical and analytical results obtained by other researchers.     

A modified particle swarm optimization for economic dispatch with non-smooth cost functions

This paper presents a new approach to economic dispatch (ED) problems with non-smooth cost functions using a particle swarm optimization (PSO) technique. The practical ED problems have non-smooth cost functions with equality and inequality constraints, which makes the problem of finding the global optimum difficult when using any mathematical approaches. Since, standard PSO may converge at the early stage, in this paper, a modified PSO (MPSO) mechanism is suggested to deal with the equality and inequality constraints in the ED problems. To validate the results obtained by MPSO, standard particle swarm optimization (PSO) and guaranteed convergence particle swarm optimization (GCPSO) are applied for comparison. Also, the results obtained by MPSO, PSO and GCPSO are compared with the previous approaches reported in the literature. The results show that the MPSO produces optimal or nearly optimal solutions for the study systems.     

Multi agent architecture for dynamic incremental process planning in the flexible manufacturing system

Due to rapid changes of markets and pressures of competitions, industries are adopting their production ways to support diversity of customer’s needs and increase of new product developments. This paper deals with development of an agent-based architecture of dynamic systems for process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A previously proposed negotiation protocol is customized and improved to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks and the suitable process plans are searched and generated to cope with both the dynamic status and disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans.     

Genetic-based minimum classification error mapping for accurate identifying Peer-to-Peer applications in the internet traffic

In this paper, we propose a hybrid approach using genetic algorithm and neural networks to classify Peer-to-Peer (P2P) traffic in IP networks. We first compute the minimum classification error (MCE) matrix using genetic algorithm. The MCE matrix is then used during the pre-processing step to map the original dataset into a new space. The mapped data set is then fed to three different classifiers: distance-based, K-Nearest Neighbors, and neural networks classifiers. We measure three different indexes, namely mutual information, Dunn, and SD to evaluate the extent of separation of the data points before and after mapping is performed. The experimental results demonstrate that with the proposed mapping scheme we achieve, on average, 8% higher accuracy in classification of the P2P traffic compare to the previous solutions. Moreover, the genetic-based MCE matrix increases the classification accuracy more than what the basic MCE does.