Cascaded walks in protein sequence space: use of artificial sequences in remote homology detection between natural proteins

Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.

Stabilized SPH-based simulations of impact dynamics using acceleration-corrected artificial viscosity

Artificial viscosity in SPH-based computations of impact dynamics is a numerical artifice that helps stabilize spurious oscillations near the shock fronts and requires certain user-defined parameters. Improper choice of these parameters may lead to spurious entropy generation within the discretized system and make it over-dissipative. This is of particular concern in impact mechanics problems wherein the transient structural response may depend sensitively on the transfer of momentum and kinetic energy due to impact. In order to address this difficulty, an acceleration correction algorithm was proposed in Shaw and Reid (''Heuristic acceleration correction algorithm for use in SPH computations in impact mechanics'', Comput. Methods Appl. Mech. Engrg., 198, 3962-3974) and further rationalized in Shaw et al. (An Optimally Corrected Form of Acceleration Correction Algorithm within SPH-based Simulations of Solid Mechanics, submitted to Comput. Methods Appl. Mech. Engrg). It was shown that the acceleration correction algorithm removes spurious high frequency oscillations in the computed response whilst retaining the stabilizing characteristics of the artificial viscosity in the presence of shocks and layers with sharp gradients. In this paper, we aim at gathering further insights into the acceleration correction algorithm by further exploring its application to problems related to impact dynamics. The numerical evidence in this work thus establishes that, together with the acceleration correction algorithm, SPH can be used as an accurate and efficient tool in dynamic, inelastic structural mechanics. (C) 2011 Elsevier Ltd. All rights reserved.

Prediction of Ground Water Levels in the Uplands of a Tropical Coastal Riparian Wetland using Artificial Neural Networks

Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

Application of Artificial Neural Networks and Particle Swarm Optimization for the Management of Groundwater Resources

Ground management problems are typically solved by the simulation-optimization approach where complex numerical models are used to simulate the groundwater flow and/or contamination transport. These numerical models take a lot of time to solve the management problems and hence become computationally expensive. In this study, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) models were developed and coupled for the management of groundwater of Dore river basin in France. The Analytic Element Method (AEM) based flow model was developed and used to generate the dataset for the training and testing of the ANN model. This developed ANN-PSO model was applied to minimize the pumping cost of the wells, including cost of the pipe line. The discharge and location of the pumping wells were taken as the decision variable and the ANN-PSO model was applied to find out the optimal location of the wells. The results of the ANN-PSO model are found similar to the results obtained by AEM-PSO model. The results show that the ANN model can reduce the computational burden significantly as it is able to analyze different scenarios, and the ANN-PSO model is capable of identifying the optimal location of wells efficiently.

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.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Clay mineral liner system for leachates containing organic contaminants

A conventional liner with a good performance against inorganic contaminants with a minimal hydraulic conductivity does not usually perform well for retention/removal of leachates containing organic contaminants. Organic modification of clay can render the naturally organophobic clay tobe organophilic. Incorporation of modified organo clay along with unmodified inorganic clay in liner systems can overcome the inherent incompatibility of conventional liners to organic contaminants and can increase organic sorption. The performance of commercially available organo clay and natural bentonite and mixtures of them in different pore fluids has been studied. It is found that the properties of mixtures improve with increase in organically modified clay particularly in non aqueous fluids from the considerations of liner application.

Variants of waters’ dual system primitives using asymmetric pairings

Waters, in 2009, introduced an important technique, called dual system encryption, to construct identity-based encryption (IBE) and related schemes. The resulting IBE scheme was described in the setting of symmetric pairing. A key feature of the construction is the presence of random tags in the ciphertext and decryption key. Later work by Lewko and Waters removed the tags and proceeding through composite-order pairings led to a more efficient dual system IBE scheme using asymmetric pairings whose security is based on non-standard but static assumptions. In this work, we have systematically simplified Waters 2009 IBE scheme in the setting of asymmetric pairing. The simplifications retain tags used in the original description. This leads to several variants, the first one of which is based on standard assumptions and in comparison to Waters’ original scheme reduces ciphertexts and keys by two elements each. Going through several stages of simplifications, we finally obtain a simple scheme whose security can be based on two standard assumptions and a natural and minimal extension of the decision Diffie-Hellman problem for asymmetric pairing groups. The scheme itself is also minimal in the sense that apart from the tags, both encryption and key generation use exactly one randomiser each. This final scheme is more efficient than both the previous dual system IBE scheme in the asymmetric setting due to Lewko and Waters and the more recent dual system IBE scheme due to Lewko. We extend the IBE scheme to hierarchical IBE (HIBE) and broadcast encryption (BE) schemes. Both primitives are secure in their respective full models and have better efficiencies compared to previously known schemes offering the same level and type of security.

Microbially induced selective flotation of sphalerite from galena using mineral-adapted strains of Bacillus megaterium

The selective flotation of sphalerite from a sphalerite-galena mineral mixture has been achieved using cells and extracellular secretions of Bacillus megaterium after adaptation to the chosen minerals. The extracellular secretions obtained after thermolysis of bacterial cells adapted to sphalerite yield the highest flotation recovery of sphalerite with a selectivity index value of 24.5, in comparison to the other cellular and extra-cellular bio-reagents studied. The protein profile for the unadapted and mineral-adapted cells has been found to differ distinctly, attesting to variation in the yield and nature of extra-cellular polymeric substances (EPS). The changes induced in the bacterial cell wall components after adaptation to sphalerite or galena with respect to the contents of phosphate, uronic acid and acetylated sugars of B. megaterium have been quantified. The role of the dissolved metal ions from the minerals as well as that of the constituents of extracellular secretions in modulating the surface charge of the bacterial cells as well as the minerals under study has been confirmed using various enzymatic treatments of the bacterial cells. It has been demonstrated that the induction of additional molecular weight protein fractions as well as the higher amount of extracellular proteins and phosphate secreted after adaptation to sphalerite vis-A-vis galena are contributory factors for the selective separation of sphalerite from galena. (C) 2013 Elsevier B.V. All rights reserved.

Filling-in Void and Sparse Regions in Protein Sequence Space by Protein-Like Artificial Sequences Enables Remarkable Enhancement in Remote Homology Detection Capability

Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like ``linker'' sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be ``plugged-into'' routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. (C) 2013 Elsevier Ltd. All rights reserved.

Basic studies on the role of components of Bacillus megaterium as flotation biocollectors in sulphide mineral separation

Studies were carried out to assess the utility of the cellular and extracellular constituents of Bacillus megaterium for the flotation of sphalerite and galena minerals. Based on the flotation results on the individual minerals, it was observed that sphalerite was preferentially floated compared to galena. A maximum selectivity index (SI) value of 11.7 was achieved in the presence of the soluble fraction of the thermolysed cells, which was higher than that obtained with the intact cells (SI of 6.5) and the insoluble fraction of the thermolysed cells (SI of 9.6). The results of the various enzymatic treatment tests revealed that extracellular DNA played a vital role in the selective flotation of sphalerite. A noteworthy finding was that the single-stranded DNA (ssDNA) had a higher biocollector capacity vis-A -vis the double-stranded DNA (dsDNA), leading to better flotation efficiency. About 95 % recovery of sphalerite could be achieved from the mineral mixture by the combined addition of the ssDNA with the non-DNA components of the bacterial cells, resulting in a maximum SI of 19.1. Calcium and phosphate components of the nutrient media were found to be essential for better selectivity of separation of sphalerite. The mechanisms of microbe-mineral interaction are discussed.

Artificial photosynthesis and the splitting of water to generate hydrogen

It is no exaggeration to state that the energy crisis is the most serious challenge that we face today. Among the strategies to gain access to reliable, renewable energy, the use of solar energy has clearly emerged as the most viable option. A promising direction in this context is artificial photosynthesis. In this article, we briefly describe the essential features of artificial photosynthesis in comparison with natural photosynthesis and point out the modest success that we have had in splitting water to produce oxygen and hydrogen, specially the latter.

Evaluation of hexane and ethyl acetate extracts of the sponge Jaspis diastra collected from Mauritius Waters on HeLa cells

Objectives Based on previous screening results, the cytotoxic effect of the hexane (JDH) and ethyl acetate extracts (JDE) of the marine sponge Jaspis diastra were evaluated on HeLa cells and the present study aimed at determining their possible mechanism of cell death. Methods Nuclear staining, membrane potential change, flow cytometry analysis of cell cycle distribution and annexin V staining were undertaken to investigate the effects of JDE and JDH. Electrospray ionization mass spectrometry (ESI-MS) and nuclear magnetic resonance were used to characterize an isolated bioactive molecule. Key findings JDE displayed an IC50 25 times more significant than the JDH. Flow cytometry analysis revealed JDE induced apoptosis in HeLa cells accompanied by the collapse of mitochondrial membrane potential. Fractionation of JDE resulted in the isolation of the known cytotoxic cyclodepsipeptide, Jaspamide. Conclusions Taking our results together suggest that JDE can be valuable for the development of anticancer drugs, especially for cervical cancer. Further investigations are currently in progress with the aim to determine and isolate other bioactive compounds from this extract.

Study the effect of electrical and mechanical shock loading on liberation and milling characteristics of mineral materials

Milling is an energy intensive process and it is considered as one of the most energy inefficient processes. Electrical and mechanical shock loading can be used to develop a pre-treatment methodology to enhance energy efficiency of comminution and liberation of minerals. Coal and Banded Hematite Jasper (BHJ) Iron ores samples were taken for the study to know the effect of shock loading. These samples were exposed to 5 electric shocks of 300 kV using an electric shock loading device. A diaphragmless shock tube was used to produce 3 and 6 compressed air shocks of Mach number 2.12 to treat the coal and Iron ore samples. Microscopic, comminution and liberation studies were carried out to compare the effectiveness of these approaches. It was found that electric shock loading can comminute the coal samples more effectively and increases the yield of carbon by 40% at 1.6 gm/cc density over the untreated coal samples. Mechanical shock loading showed improved milling performance for both the materials and 12.90% and 8.1% reduction in the D-80 of the particles was observed during grinding for treated samples of coal and iron, respectively. Liberation of minerals in BHJ Iron ore was found unaffected due to low intensity of the mechanical shock waves and non conductivity of minerals. Compressed air based shock loading is easier to operate than electrical shock loading and it needs to be explored further to improve the energy efficacy of comminution. (C) 2014 Elsevier Ltd. All rights reserved.

Experimental Characterization and Control of Miniaturized Pneumatic Artificial Muscle

Robotic surgical tools used in minimally invasive surgeries (MIS) require miniaturized and reliable actuators for precise positioning and control of the end-effector. Miniature pneumatic artificial muscles (MPAMs) are a good choice due to their inert nature, high force to weight ratio, and fast actuation. In this paper, we present the development of miniaturized braided pneumatic muscles with an outer diameter of similar to 1.2 mm, a high contraction ratio of about 18%, and capable of providing a pull force in excess of 4 N at a supply pressure of 0.8 MPa. We present the details of the developed experimental setup, experimental data on contraction and force as a function of applied pressure, and characterization of the MPAM. We also present a simple kinematics and experimental data based model of the braided pneumatic muscle and show that the model predicts contraction in length to within 20% of the measured value. Finally, a robust controller for the MPAMs is developed and validated with experiments and it is shown that the MPAMs have a time constant of similar to 10 ms thereby making them suitable for actuating endoscopic and robotic surgical tools.