A novel neural network design for long range prediction of rainfall pattern

The importance of long-range prediction of rainfall pattern for devising and planning agricultural strategies cannot be overemphasized. However, the prediction of rainfall pattern remains a difficult problem and the desired level of accuracy has not been reached. The conventional methods for prediction of rainfall use either dynamical or statistical modelling. In this article we report the results of a new modelling technique using artificial neural networks. Artificial neural networks are especially useful where the dynamical processes and their interrelations for a given phenomenon are not known with sufficient accuracy. Since conventional neural networks were found to be unsuitable for simulating and predicting rainfall patterns, a generalized structure of a neural network was then explored and found to provide consistent prediction (hindcast) of all-India annual mean rainfall with good accuracy. Performance and consistency of this network are evaluated and compared with those of other (conventional) neural networks. It is shown that the generalized network can make consistently good prediction of annual mean rainfall. Immediate application and potential of such a prediction system are discussed.

Prediction of nonlocal scaling parameter for armchair and zigzag single-walled carbon nanotubes based on molecular structural mechanics, nonlocal elasticity and wave propagation

Atomic vibration in the Carbon Nanotubes (CNTs) gives rise to non-local interactions. In this paper, an expression for the non-local scaling parameter is derived as a function of the geometric and electronic properties of the rolled graphene sheet in single-walled CNTs. A self-consistent method is developed for the linearization of the problem of ultrasonic wave propagation in CNTs. We show that (i) the general three-dimensional elastic problem leads to a single non-local scaling parameter (e(0)), (ii) e(0) is almost constant irrespective of chirality of CNT in the case of longitudinal wave propagation, (iii) e(0) is a linear function of diameter of CNT for the case of torsional mode of wave propagation, (iv) e(0) in the case of coupled longitudinal-torsional modes of wave propagation, is a function which exponentially converges to that of axial mode at large diameters and to torsional mode at smaller diameters. These results are valid in the long-wavelength limit. (C) 2011 Elsevier Ltd. All rights reserved.

Prediction of protein-protein interactions between human host and a pathogen and its application to three pathogenic bacteria

Molecular understanding of disease processes can be accelerated if all interactions between the host and pathogen are known. The unavailability of experimental methods for large-scale detection of interactions across host and pathogen organisms hinders this process. Here we apply a simple method to predict protein-protein interactions across a host and pathogen organisms. We use homology detection approaches against the protein-protein interaction databases. DIP and iPfam in order to predict interacting proteins in a host-pathogen pair. In the present work, we first applied this approach to the test cases involving the pairs phage T4 - Escherichia coli and phage lambda - E. coli and show that previously known interactions could be recognized using our approach. We further apply this approach to predict interactions between human and three pathogens E. coli, Salmonella enterica typhimurium and Yersinia pestis. We identified several novel interactions involving proteins of host or pathogen that could be thought of as highly relevant to the disease process. Serendipitously, many interactions involve hypothetical proteins of yet unknown function. Hypothetical proteins are predicted from computational analysis of genome sequences with no laboratory analysis on their functions yet available. The predicted interactions involving such proteins could provide hints to their functions. (C) 2011 Elsevier B.V. All rights reserved.

Link failure detection for maintaining session continuity in packet data networks

A link failure in the path of a virtual circuit in a packet data network will lead to premature disconnection of the circuit by the end-points. A soft failure will result in degraded throughput over the virtual circuit. If these failures can be detected quickly and reliably, then appropriate rerouteing strategies can automatically reroute the virtual circuits that use the failed facility. In this paper, we develop a methodology for analysing and designing failure detection schemes for digital facilities. Based on errored second data, we develop a Markov model for the error and failure behaviour of a T1 trunk. The performance of a detection scheme is characterized by its false alarm probability and the detection delay. Using the Markov model, we analyse the performance of detection schemes that use physical layer or link layer information. The schemes basically rely upon detecting the occurrence of severely errored seconds (SESs). A failure is declared when a counter, that is driven by the occurrence of SESs, reaches a certain threshold.For hard failures, the design problem reduces to a proper choice;of the threshold at which failure is declared, and on the connection reattempt parameters of the virtual circuit end-point session recovery procedures. For soft failures, the performance of a detection scheme depends, in addition, on how long and how frequent the error bursts are in a given failure mode. We also propose and analyse a novel Level 2 detection scheme that relies only upon anomalies observable at Level 2, i.e. CRC failures and idle-fill flag errors. Our results suggest that Level 2 schemes that perform as well as Level 1 schemes are possible.

Degradation and Failure of Field Emitting Carbon Nanotube Arrays

It has been observed experimentally that the collective field emission from an array of Carbon Nanotubes (CNTs) exhibits fluctuation and degradation, and produces thermal spikes, resulting in electro-mechanical fatigue and failure of CNTs. Based on a new coupled multiphysics model incorporating the electron-phonon transport and thermo-electrically activated breakdown, a novel method for estimating accurately the lifetime of CNT arrays has been developed in this paper. The main results are discussed for CNT arrays during the field emission process. It is shown that the time-to-failure of CNT arrays increases with the decrease in the angle of tip orientation. This observation has important ramifications for such areas as biomedical X-ray devices using patterned films of CNTs.

Passive pressure coefficients, critical failure surface and its kinematic admissibility

Using a combination of a logarithmic spiral and a straight line as a failure surface, comprehensive charts have been developed to determine the passive earth pressure coefficients and the positions of the critical failure surface for positive as well as negative wall friction angles. Translational movement of the wall has been examined in detail, considering the soil as either an associated flow dilatant material or a non-dilatant material, to determine the kinematic admissibility of the limit equilibrium solutions.

Prediction of separation factor in foam separation of proteins

A phenomenological model has been developed for predicting separation factors obtained in concentrating protein solutions using batch-foam columns. The model considers the adsorption of surface active proteins onto the air-water interface of bubbles, and drainage of liquid from the foam, which are the two predominant processes responsible for separation in foam columns. The model has been verified with data collected on casein and bovine serum albumin (BSA) solutions, for which adsorption isotherms are available in the literature. It has been found that an increase in liquid pool height above the gas distributor and the time allowed for drainage result in a better separation. Further, taller foam columns yield poorer separation at constant time of drainage. The model successfully predicts the observed results. (C) 1997 Elsevier Science Ltd.

Prediction of the senses of helical amphiphilic assemblies from effective intermolecular pair potential: Studies on chiral monolayers and bilayers

It is well-known that the senses (or the handedness) of the helical assemblies formed from compressed monolayers and bilayers of chiral amphiphiles are highly specific about the chirality of the monomers concerned. We present here a molecular approach that can successfully predict the senses of such helical morphologies. The present approach is based on a reduced tractable description in terms of an effective pair potential (EPP) which depends on the distance of separation and the relative orientations of the two amphiphiles. This approach explicitly considers the pairwise intermolecular interactions between the groups attached to the chiral centers of the two neighboring amphiphiles. It is found that for a pair of the same kind of enantiomers the minimum energy configuration favors a twist angle between molecules and that this twist from neighbor to neighbor gives rise to the helicity of the aggregate. From the known twist angles at the minimum energy configuration the successive arrangement of an array of molecules can be predicted. Therefore, the sense of the helicity can be predicted from the molecular interactions. The predicted senses of the helical structures are in complete agreement with all known experimental results.

Influence of foam/glass-epoxy interface on the macroscopic compressive failure features

The effect on the macroscopic compressive failure features of introduction of two flexible foam layers, either together at mid-region or separately at two locations that are away from the midregion, into a glass-epoxy (G-E) system is studied in this work. In this experimental approach an attempt to look at the possible influence the foam/G-E interface region has on the way the materials respond to compressive loading is made by involving an analyses of macrofractographic features. While foam-free samples fail by extensive ear formation and separation nearer to the mid-region, the foam bearing ones display pronounced interface separation. The positioning of the foam sheet(s) has a bearing on the failure features.

Regarding the effect of aging heat treatment on the failure behaviour of a SiC reinforced Al based metal matrix composite

In the present study, 6061 Al metallic matrix was reinforced by 12.2 wt% df SiC particulates using liquid metallurgy route. The composite material thus obtained was extruded and characterized in the as-solutionized and peak aged conditions in order to delineate the effect of aging associated precipitation of secondary phases on the tensile fracture behavior of the composite samples. The results' of microstructural characterization studies carried out using scanning electron microscope revealed the increased presence of precipitated secondary phases in the metallic matrix and a more pronounced interfacial segregation of alloying elements in case of peak aged samples when compared to the as-solutionized samples. The results of the fractographic studies conducted on the as-solutionized samples revealed that the failure was dominated by the SiC particulates cracking while for the peak aged samples the fracture surface revealed a comparatively more pronounced SiC/6061 Al debonding and reduced SiC particulates cracking. This change in the failure behavior was rationalized in terms of embrittlement of the interfacial region brought about by the aging heat treatment and is correlated, in addition, with the mechanical properties of the composite samples in as-solutionized and peak aged conditions.

Prediction of reaeration rates in square, stirred tanks

Experiments were conducted on the oxygen transfer coefficient, k(L)a(20), through surface aeration in geometrically similar square tanks, with a rotor of diameter D fitted with six flat blades. An optimal geometric similarity of various linear dimensions, which produced maximum k(L)a(20) for any rotational speed of rotor N by an earlier study, was maintained. A simulation equation uniquely correlating k = k(L)a(20)(nu/g(2))(1/3) (nu and g are kinematic viscosity of water and gravitational constant, respectively), and a parameter governing the theoretical power per unit volume, X = (ND2)-D-3/(g(4/3)nu(1/3)), is developed. Such a simulation equation can be used to predict maximum k for any N in any size of such geometrically similar square tanks. An example illustrating the application of results is presented. Also, it has been established that neither the Reynolds criterion nor the Froude criterion is singularly valid to simulate either k or K = k(L)a(20)/N, simultaneously in all the sizes of tanks, even through they are geometrically similar. Occurrence of "scale effects" due to the Reynolds and the Froude laws of similitude on both k and K are also evaluated.

A finite element assessment of flexural strength of prestressed concrete beams with fiber reinforcement

This paper presents an assessment of the flexural behavior of 15 fully/partially prestressed high strength concrete beams containing steel fibers investigated using three-dimensional nonlinear finite elemental analysis. The experimental results consisted of eight fully and seven partially prestressed beams, which were designed to be flexure dominant in the absence of fibers. The main parameters varied in the tests were: the levels of prestressing force (i.e, in partially prestressed beams 50% of the prestress was reduced with the introduction of two high strength deformed bars instead), fiber volume fractions (0%, 0.5%, 1.0% and 1.5%), fiber location (full depth and partial depth over full length and half the depth over the shear span only). A three-dimensional nonlinear finite element analysis was conducted using ANSYS 5.5 [Theory Reference Manual. In: Kohnke P, editor. Elements Reference Manual. 8th ed. September 1998] general purpose finite element software to study the flexural behavior of both fully and partially prestressed fiber reinforced concrete beams. Influence of fibers on the concrete failure surface and stress-strain response of high strength concrete and the nonlinear stress-strain curves of prestressing wire and deformed bar were considered in the present analysis. In the finite element model. tension stiffening and bond slip between concrete and reinforcement (fibers., prestressing wire, and conventional reinforcing steel bar) have also been considered explicitly. The fraction of the entire volume of the fiber present along the longitudinal axis of the prestressed beams alone has been modeled explicitly as it is expected that these fibers would contribute to the mobilization of forces required to sustain the applied loads across the crack interfaces through their bridging action. A comparison of results from both tests and analysis on all 15 specimens confirm that, inclusion of fibers over a partial depth in the tensile side of the prestressed flexural structural members was economical and led to considerable cost saving without sacrificing on the desired performance. However. beams having fibers over half the depth in only the shear span, did not show any increase in the ultimate load or deformational characteristics when compared to plain concrete beams. (C) 2002 Published by Elsevier Science Ltd.

Multivariate nonlinear ensemble prediction of daily chaotic rainfall with climate inputs

The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.

DNA Free Energy-Based Promoter Prediction and Comparative Analysis of Arabidopsis and Rice Genomes

The cis-regulatory regions on DNA serve as binding sites for proteins such as transcription factors and RNA polymerase. The combinatorial interaction of these proteins plays a crucial role in transcription initiation, which is an important point of control in the regulation of gene expression. We present here an analysis of the performance of an in silico method for predicting cis-regulatory regions in the plant genomes of Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) on the basis of free energy of DNA melting. For protein-coding genes, we achieve recall and precision of 96% and 42% for Arabidopsis and 97% and 31% for rice, respectively. For noncoding RNA genes, the program gives recall and precision of 94% and 75% for Arabidopsis and 95% and 90% for rice, respectively. Moreover, 96% of the false-positive predictions were located in noncoding regions of primary transcripts, out of which 20% were found in the first intron alone, indicating possible regulatory roles. The predictions for orthologous genes from the two genomes showed a good correlation with respect to prediction scores and promoter organization. Comparison of our results with an existing program for promoter prediction in plant genomes indicates that our method shows improved prediction capability.