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.

Microstructure and Texture Evolution in Interstitial-free (IF) Steel processed by Multi-Axial Forging

In this study, severe plastic deformation (SPD) of Ti-bearing interstitial-free steel was carried out by multi-axial forging (MAF) technique. The grain refinement achieved was comparable to that by other SPD techniques. A considerable heterogeneity was observed in the microstructure and texture. Texture of multi-axially forged steels has been evaluated and reported for the first time. The material exhibited a six-fold increase in the yield strength after four cycles of MAF.

Cannibalism can drive the evolution of behavioural phase polyphenism in locusts

During outbreaks, locust swarms can contain millions of insects travelling thousands of kilometers while devastating vegetation and crops. Such large-scale spatial organization is preceded locally by a dramatic density-dependent phenotypic transition in multiple traits. Behaviourally, low-density solitarious individuals avoid contact with one another; above a critical local density, they undergo a rapid behavioural transition to the gregarious phase whereby they exhibit mutual attraction. Although proximate causes of this phase polyphenism have been widely studied, the ultimate driving factors remain unclear. Using an individual-based evolutionary model, we reveal that cannibalism, a striking feature of locust ecology, could lead to the evolution of density-dependent behavioural phase-change in juvenile locusts. We show that this behavioural strategy minimizes risk associated with cannibalistic interactions and may account for the empirically observed persistence of locust groups during outbreaks. Our results provide a parsimonious explanation for the evolution of behavioural plasticity in locusts.

Markov chain modeling of evolution of strains in reinforced concrete flexural beams

From the analysis of experimentally observed variations in surface strains with loading in reinforced concrete beams, it is noted that there is a need to consider the evolution of strains (with loading) as a stochastic process. Use of Markov Chains for modeling stochastic evolution of strains with loading in reinforced concrete flexural beams is studied in this paper. A simple, yet practically useful, bi-level homogeneous Gaussian Markov Chain (BLHGMC) model is proposed for determining the state of strain in reinforced concrete beams. The BLHGMC model will be useful for predicting behavior/response of reinforced concrete beams leading to more rational design.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Effect of isothermal aging and electromigration on the microstructural evolution of solder interconnections during thermomechanical loading

The effect of different pre-aging treatments on the microstructural evolution of lead-free solder and growth of interfacial intermetallic compound layers under thermal cycling has been investigated in this work. The results show that there are distinct differences in the microstructural changes between samples with no pretreatment, samples that have experienced thermal annealing at 125A degrees C for 750 h before thermal cycling, and those that have had direct current (DC) stressing for 750 h as pretreatment. The microstructural evolution of the solder matrix is rationalized by utilizing the science of microstructures and analysis of the influence of electron flow on the precipitation phenomena. The finite-element method is utilized to understand the loading conditions imposed on the solder interconnections during cyclic stressing. The growth of intermetallic reaction layers is further analyzed by utilizing quantitative thermodynamic calculations coupled with kinetic analysis. The latter is based on the changes in the intrinsic diffusion fluxes of elements induced by current flow and alloying elements present in the system. With this concurrent approach the differences seen in thermal cycling behavior between the different pre-aging treatments can be explained.

A finite population model of mlecular evolution: theory and computation

This article is concerned with the evolution of haploid organisms that reproduce asexually. In a seminal piece of work, Eigen and coauthors proposed the quasispecies model in an attempt to understand such an evolutionary process. Their work has impacted antiviral treatment and vaccine design strategies. Yet, predictions of the quasispecies model are at best viewed as a guideline, primarily because it assumes an infinite population size, whereas realistic population sizes can be quite small. In this paper we consider a population genetics-based model aimed at understanding the evolution of such organisms with finite population sizes and present a rigorous study of the convergence and computational issues that arise therein. Our first result is structural and shows that, at any time during the evolution, as the population size tends to infinity, the distribution of genomes predicted by our model converges to that predicted by the quasispecies model. This justifies the continued use of the quasispecies model to derive guidelines for intervention. While the stationary state in the quasispecies model is readily obtained, due to the explosion of the state space in our model, exact computations are prohibitive. Our second set of results are computational in nature and address this issue. We derive conditions on the parameters of evolution under which our stochastic model mixes rapidly. Further, for a class of widely used fitness landscapes we give a fast deterministic algorithm which computes the stationary distribution of our model. These computational tools are expected to serve as a framework for the modeling of strategies for the deployment of mutagenic drugs.

Co-evolution of content popularity and delivery in mobile P2P networks

Mobile P2P technology provides a scalable approach for content delivery to a large number of users on their mobile devices. In this work, we study the dissemination of a single item of content (e. g., an item of news, a song or a video clip) among a population of mobile nodes. Each node in the population is either a destination (interested in the content) or a potential relay (not yet interested in the content). There is an interest evolution process by which nodes not yet interested in the content (i.e., relays) can become interested (i.e., become destinations) on learning about the popularity of the content (i.e., the number of already interested nodes). In our work, the interest in the content evolves under the linear threshold model. The content is copied between nodes when they make random contact. For this we employ a controlled epidemic spread model. We model the joint evolution of the copying process and the interest evolution process, and derive joint fluid limit ordinary differential equations. We then study the selection of parameters under the content provider's control, for the optimization of various objective functions that aim at maximizing content popularity and efficient content delivery.

Evolution of structural phase coexistence in a half doped manganite Pr0.5Sr0.5MnO3: An evidence for magneto-structural coupling

Temperature dependent x-ray diffraction measurements have been performed to understand the implications of magnetic phase coexistence on crystallographic structure in a half-doped manganite Pr0.5Sr0.5MnO3. The compound shows a structural phase transition from high-temperature tetragonal-I4/mcm to low-temperature orthorhombic-Fmmm symmetry around the ferromagnetic to antiferro-magnetic transition. Rietveld analysis shows the coexistence of these two structures emerges at high temperature within the ferromagnetic state, and persists down to lowest temperature. Below around 40 K, however, this structural evolution stops, and a significant fraction (similar to 22%) of untransformed high-temperature phase remains. This agrees with earlier magnetization study, thus establishing its magneto-structural coupling. (C) 2012 Elsevier B.V. All rights reserved.

Microstructural Evolution of A356 Al Alloy During Flow Along a Cooling Slope

Cooling slope (CS) has been used in this study to prepare semi-solid slurry of A356 Al alloy, keeping in view of slurry generation on demand for Rheo-pressure die casting process. Understanding the physics of microstructure evolution during cooling slope slurry formation is important to satisfy the need of semi-sold slurry with desired shape, size and morphology of primary Al phase. Mixture of spherical and rosette shaped primary Al phase has been observed in the samples collected during melt flow through the slope as well as in the cast (mould) samples compared to that of dendritic shape, observed in case of conventionally cast A356 alloy. The liquid melt has been poured into the slope at 650 A degrees C temperature and during flow it falls below the liquidus temperature of the said alloy, which facilitates crystallization of alpha-Al crystals on the cooling slope wall. Crystal separation due to melt flow is found responsible for nearly spherical morphology of the primary Al phase.

Evolution of Microstructure During Solidification of an Aluminium Alloy Under Stirring

In the present work, the evolution of microstructure during solidification of A356 alloy under stirring is performed experimentally in a high temperature concentric viscometer. The stirring during solidification results a semisolid slurry in the annular space between the cylinders. This slurry is removed periodically during processing using a vacuum removal quartz tube and quenched in water for micrograph analysis. From the micrograph analysis, the shape, stacking arrangement and corresponding microstructural evolution of the suspended primary particles in the slurry are studied. The work also predicts the fraction of solid present in the extracted slurry. Finally, the effect of microstructure and the solid-fraction on the slurry viscosity is presented.

Time evolution of resistance in response to magnetic field: Evidence of glassy transport in La0.85Sr0.15CoO3

We demonstrate the distinct glassy transport phenomena associated with the phase separated and spin-glass-like phases of La0.85Sr0.15CoO3, prepared under different heat-treatment conditions. The low-temperature annealed (phase-separated) sample, exhibits a small change in resistance, with evolution of time, as compared to the high-temperature annealed (spin glass) one. However, the resistance change as a function of time, in both cases, is well described by a stretched exponential fit, signifying the slow dynamics. Moreover, the ultraviolet spectroscopy study evidences a relatively higher density of states in the vicinity of EF for low-temperature annealed sample and this correctly points to its less semiconducting behavior.

Texture and microstructure evolution during cold rolling of Cu-Fe laminates prepared by accumulative roll bonding

Multi-layered materials have been made from Cu-Fe with approximately equal volume fractions using the Accumulated Roll Bonding (ARB) technique with less than 1 μm thickness of the individual layers. The so-obtained multi-layers have been subjected to deformation by cold rolling to 25, 50, 75, 87 and 93% reduction in thickness. A detailed characterization has been carried out using X-ray diffraction (line profile analysis and texture measurement) and electron (scanning and transmission) microscopy. It has been found that Fe layers are disintegrated whereas Cu retains its continuity within a layer. Microstructural Characterization from X-Ray Line profile Analysis (XRDLPA) through Variance Method reveals that large amount of strain is initially carried by Cu layers during deformation. In the Cu-Fe layer, the texture is comparatively weaker in Cu layer and strong in Fe layers. Brass Component increases up to 75% reduction and then decreases, while the ratio of Cu/S and Bs/S remains almost constant through out the deformation. After 50% reduction, dynamic recovery is predominant as indicated by the increase in the amount of low angle grain boundaries and decrease in dislocation density. The presence of R component indicates continuous dynamic recovery and recrystallization (CDRR) at the advanced stage of deformation.

Deformation and Recrystallization texture evolution in Nano-crystalline Nickel

Deformation and recrystallization textures in nano-crystalline nickel with average grain size of 20 nm were investigated using X-ray diffraction, electron microscopy and differential scanning calorimetry. The deformation behaviour of nano-crystalline nickel is quite complicated due to intervention of other deformation mechanisms like grain boundary sliding and restoration mechanisms like grain growth and grain rotation to dislocation mediated slip. Recrystallization studies carried out on the deformed nano-crystalline nickel showed that the deformation texture was retained during low temperature annealing (300 degrees C), while at higher temperature (1000 degrees C), the texture got randomised. The exact mechanism of texture formation during deformation and recrystallization has been discussed.

Texture evolution in high strain rate deformed Cu-10Zn alloy

High strain rate deformation behavior of Cu-10Zn alloy was studied. A weak texture with fine grain size was observed at high strain rate. The weak texture has been attributed to activity of higher number of slip systems under dynamic loading conditions. Twinning has minimal role on texture. (C) 2012 Elsevier B.V. All rights reserved.