Bio-inspired route for the synthesis of spherical shaped MgO:Fe3+ nanoparticles: Structural, photoluminescence and photocatalytic investigation

MgO:Fe3+ (0.1-5 mol%) nanoparticles (NPs) were synthesized via eco-friendly, inexpensive and simple low temperature solution combustion route using Aloe vera gel as fuel. The final products were characterized by SEM, TEM and HRTEM. PXRD data and Rietveld analysis revealed the formation of cubic system. The influence of Fe3+ ion concentration on the structure morphology, UV absorption, PL emission and photocatalytic activity of MgO:Fe3+ NPs were investigated. The yellow emission with CIE chromaticity coordinates (0.44, 0.52) and average correlated color temperature value was found to be 3540 K which corresponds to warm light of NPs. The control of Fe3+. on MgO matrix influences the photocatalytic decolorization of methylene blue (MB) under UV light. The enhanced photocatalytic activity of MgO:Fe3+ (4 mol%) was attributed to dopant concentration, effective crystallite size, textural properties, decreased band gap and capability for reducing the electron hole pair recombination. Further, the trends of inhibitory effect in the presence of different radical scavengers were explored. These findings open up new avenues for the exploration of Fe-doped MgO in eco-friendly water applications and in the process of display devices. (C) 2015 Elsevier B.V. All rights reserved.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.

An Optimal Fuzzy Logic Controller tuned with Artificial Immune System

In this paper, a method for the tuning the membership functions of a Mamdani type Fuzzy Logic Controller (FLC) using the Clonal Selection Algorithm(CSA) a model of the Artificial Immune System(AIS) paradigm is examined. FLC's are designed for two problems, firstly the linear cart centering problem and secondly the highly nonlinear inverted pendulum problem. The FLC tuned by AIS is compared with FLC tuned by GA. In order to check the robustness of the designed PLC's white noise was added to the system, further, the masses of the cart and the length and mass of the pendulum are changed. The PLC's were also tested in the presence of faulty rules. Finally, Kruskal Wallis test was performed to compare the performance of the GA and AIS. An insight into the algorithms are also given by studying the effect of the important parameters of GA and AIS.

Quasi-based hierarchical clustering for land cover mapping using satellite images

This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

Clustering using Levy Flight Cuckoo Search

In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Macroporous metal oxide foams through self-sustained combustion reactions

A number of macroporous metal oxide foams were prepared through self-sustained combustion reactions starting from dough made of the corresponding metal nitrate, urea and starch. The nitrate ion acts as an oxidizing agent, urea as fuel and starch as an organic binder. The metal oxide foams are characterized by scanning electron microscopy and powder X-ray diffraction.

Crop Classification using Biologically-inspired Techniques with High Resolution Satellite Image

Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

Click Chemistry Inspired Synthesis of Novel Ferrocenyl-Substituted Amino Acids or Peptides

This work reports on the synthesis of a wide range of ferrocenyl-substituted amino acids and peptides in excellent yield. Conjugation is established via copper-catalyzed 1,3-dipolar cycloaddition. Two complementary strategies were employed for conjugation, one involving cycloaddition of amino acid derived azides with ethynyl ferrocene 1 and the other involves cycloaddition between amino acid derived alkynes with ferrocene-derived azides 2 and 3. Labeling of amino acids at multiple sites with ferrocene is discussed. A new route to 1,1'-unsymmetrically substituted ferrocene conjugates is reported. A novel ferrocenophane 19 is accessed via bimolecular condensation of amino acid derived bis-alkyne 9b with the azide 2. The electrochemical behavior of some selected ferrocene conjugates has been studied by cyclic voltammetry.

Strain hardening during constrained deformation of metal foams - Effect of shear displacement

The crush bands that form during plastic deformation of closed-cell metal foams are often inclined at 11-20 degrees to the loading axis, allowing for shear displacement of one part of the foam with respect to the other. Such displacement is prevented by the presence of a lateral constraint. This was analysed in this study, which shows that resistance against shear by the constraint leads to the strain-hardening effect in the foam that has been reported in a recent experimental study. (C) 2009 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Separation of sulfur-containing components of transfer ribonucleic acid on Bio-Gel P-2 and Sephadex G-10 columns

S-Labeled nucleosides of E. coli tRNA and some of the derivatives of thionucleosides were separated on Bio-Gel P-2 and Sephadex G-10 columns employing buffers of low salt concentration and high pH.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

Ferrous iron oxidation by foam immobilized Acidithiobacillus ferrooxidans: Experiments and modeling

Ferrous iron bio-oxidation by Acidithiobacillus ferrooxidans immobilized on polyurethane foam was investigated. Cells were immobilized on foams by placing them in a growth environment and fully bacterially activated polyurethane foams (BAPUFs) were prepared by serial subculturing in batches with partially bacterially activated foam (pBAPUFs). The dependence of foam density on cell immobilization process, the effect of pH and BAPUF loading on ferrous oxidation were studied to choose operating parameters for continuous operations. With an objective to have high cell densities both in foam and the liquid phase, pretreated foams of density 50 kg/m3 as cell support and ferrous oxidation at pH 1.5 to moderate the ferric precipitation were preferred. A novel basket-type bioreactor for continuous ferrous iron oxidation, which features a multiple effect of stirred tank in combination with recirculation, was designed and operated. The results were compared with that of a free cell and a sheet-type foam immobilized reactors. A fivefold increase in ferric iron productivity at 33.02 g/h/L of free volume in foam was achieved using basket-type bioreactor when compared to a free cell continuous system. A mathematical model for ferrous iron oxidation by Acidithiobacillus ferrooxidans cells immobilized on polyurethane foam was developed with cell growth in foam accounted by an effectiveness factor. The basic parameters of simulation were estimated using the experimental data on free cell growth as well as from cell attachment to foam under nongrowing conditions. The model predicted the phase of both oxidation of ferrous in shake flasks by pBAPUFs as well as by fully activated BAPUFs for different cell loadings in foam. Model for stirred tank basket bioreactor predicted within 5% both transient and steady state of the experiments closely for the simulated dilution rates. Bio-oxidation at high Fe2+ concentrations were simulated with experiments when substrate and product inhibition coefficients were factored into cell growth kinetics.

An Experimental Study on Energy Absorption Behavior of Polyurethane Foams

This article is concerned with a study on the energy absorption behavior of polyurethane (PU) foams such as flexible high resilience (HR), flexible viscoelastic (VE) and semi-rigid (SR) foams as a function of the overall foam density. Foam samples were prepared in the form of cubes by mixing appropriate polyol and isocyanate compounds produced by Huntsman International India Pvt. Ltd. in varying proportions leading to a range of densities for each type of foam. The cubical samples were tested under compressive load in a standard UTM. Based on the measured load-displacement behaviors, variations of peak load and energy-absorption attributes with respect to density are plotted for each type of foam and the possible existence of an optimum foam density is shown.