Combining Bayes Classification and Point Group Symmetry under Boolean Framework for Enhanced Protein Quaternary Structure Inference

Our ability to infer the protein quaternary structure automatically from atom and lattice information is inadequate, especially for weak complexes, and heteromeric quaternary structures. Several approaches exist, but they have limited performance. Here, we present a new scheme to infer protein quaternary structure from lattice and protein information, with all-around coverage for strong, weak and very weak affinity homomeric and heteromeric complexes. The scheme combines naive Bayes classifier and point group symmetry under Boolean framework to detect quaternary structures in crystal lattice. It consistently produces >= 90% coverage across diverse benchmarking data sets, including a notably superior 95% coverage for recognition heteromeric complexes, compared with 53% on the same data set by current state-of-the-art method. The detailed study of a limited number of prediction-failed cases offers interesting insights into the intriguing nature of protein contacts in lattice. The findings have implications for accurate inference of quaternary states of proteins, especially weak affinity complexes.

Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.

Bounds on the Lifetime of Wireless Sensor Networks Employing Multiple Data Sinks

Employing multiple base stations is an attractive approach to enhance the lifetime of wireless sensor networks. In this paper, we address the fundamental question concerning the limits on the network lifetime in sensor networks when multiple base stations are deployed as data sinks. Specifically, we derive upper bounds on the network lifetime when multiple base stations are employed, and obtain optimum locations of the base stations (BSs) that maximize these lifetime bounds. For the case of two BSs, we jointly optimize the BS locations by maximizing the lifetime bound using a genetic algorithm based optimization. Joint optimization for more number of BSs is complex. Hence, for the case of three BSs, we optimize the third BS location using the previously obtained optimum locations of the first two BSs. We also provide simulation results that validate the lifetime bounds and the optimum locations of the BSs.

Two-mode quantum systems: Invariant classification of squeezing transformations and squeezed states

A general analysis of squeezing transformations for two-mode systems is given based on the four-dimensional real symplectic group Sp(4, R). Within the framework of the unitary (metaplectic) representation of this group, a distinction between compact photon-number-conserving and noncompact photon-number-nonconserving squeezing transformations is made. We exploit the U(2) invariant squeezing criterion to divide the set of all squeezing transformations into a two-parameter family of distinct equivalence classes with representative elements chosen for each class. Familiar two-mode squeezing transformations in the literature are recognized in our framework and seen to form a set of measure zero. Examples of squeezed coherent and thermal states are worked out. The need to extend the heterodyne detection scheme to encompass all of U(2) is emphasized, and known experimental situations where all U(2) elements can be reproduced are briefly described.

A compact proof of Fisher�s Fundamental Theorem for multiple loci

A systematic method is formulated to carry out theoretical analysis in a multilocus multiallele genetic system. As a special application, the Fundamental Theorem of Natural Selection is proved (in the continuous time model) for a multilocus multiallele system if all pairwise linkage disequilibria are zero.

Mycobacterium tuberculosis Expresses ftsE Gene Through Multiple Transcripts

Bacterial FtsE gene codes for the ATP-binding protein, FtsE, which in complex with the transmembrane protein, FtsX, participates in diverse cellular processes. Therefore, regulated expression of FtsE and FtsX might be critical to the human pathogen, Mycobacterium tuberculosis, under stress conditions. Although ftsX gene of M. tuberculosis (MtftsX) is known to be transcribed from a promoter inside the upstream gene, ftsE, the transcriptional status of ftsE gene of M. tuberculosis (MtftsE) remains unknown. Therefore, the authors initiated transcriptional analyses of MtftsE, using total RNA from M. tuberculosis cells that were grown under stress conditions, which the pathogen is exposed to, in granuloma in tuberculosis patients. Primer extension experiments showed the presence of putative transcripts, T1, T2, T3, and T4. T1 originated from the intergenic region between the upstream gene, MRA_3135, and MtftsE. T2 and T3 were found initiated from within MRA_3135. T4 was transcribed from a region upstream of MRA_3135. RT-PCR confirmed co-transcription of MRA_3135 and MtftsE. The cloned putative promoter regions for T1, T2, and T3 elicited transcriptional activity in Mycobacterium smegmatis transformants. T1, T2, and T3, but no new transcript, were present in the M. tuberculosis cells that were grown under the stress conditions, which the pathogen is exposed to in granuloma in tuberculosis patients. It showed lack of modulation of MtftsE transcripts under the stress conditions tested, indicating that ftsE may not have a stress response-specific function in M. tuberculosis.

An integrated model for optimal reservoir operation for irrigation of multiple crops

An integrated model is developed, based on seasonal inputs of reservoir inflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocations to multiple crops. The model is conceptually made up of two modules, Module 1 is an intraseasonal allocation model to maximize the sum of relative yields of all crops, for a given state of the system, using linear programming (LP). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growth with time. Module 2 is a seasonal allocation model to derive the steady state reservoir operating policy using stochastic dynamic programming (SDP). Reservoir storage, seasonal inflow, and seasonal rainfall are the state variables in the SDP. The objective in SDP is to maximize the expected sum of relative yields of all crops in a year. The results of module 1 and the transition probabilities of seasonal inflow and rainfall form the input for module 2. The use of seasonal inputs coupled with the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study, while affecting additional improvements. The model is applied to an existing reservoir in Karnataka State, India.

Blind separation of multiple co-channel BPSK signals arriving at an antenna array

In this letter, we propose a method for blind separation of d co-channel BPSK signals arriving at an antenna array. Our method involves two steps. In the first step, the received data vectors at the output of the array is grouped into 2d clusters. In the second step, we assign the 2d d-tuples with ±1 elements to these clusters in a consistent fashion. From the knowledge of the cluster to which a data vector belongs, we estimate the bits transmitted at that instant. Computer simulations are used to study the performance of our method

Cascades of Selective Pulses on Connected Single-Quantum Transitions Leading to the Selective Excitation of Multiple-Quantum Coherences

A symmetric cascade of selective pulses applied on connected transitions leads to the excitation of a selected multiple-quantum coherence by a well-defined angle. This cascade selectively operates on the subspace of the multiple-quantum coherence and acts as a generator of rotation selectively on the multiple-quantum subspace. Single-transition operator algebra has been used to explain these experiments. Experiments have been performed on two- and three-spin systems. It is shown that such experiments can be utilized to measure the relaxation times of selected multiple-quantum coherences or of a specifically prepared initial longitudinal state of the spin system.

Quasicrystals, crystals and multiple twins in rapidly solidified Al-Cr-Si, Al-Mn-Si and Al-Mn-Cr-Si alloys

The coexistence of quasicrystals and rational approximant structures (RAS) has been observed in melt-spun Al80Cr14Si6, Al80Mn14Si6 and Al75Mn10Cr5Si10 alloys. The presence of a b.c.c. alpha-AlMnSi phase in Al-Mn-Si and alpha-AlMnSi(Cr) phase in Al-Mn-Cr-Si has been seen. A multiple twinning around an irrational axis of the RAS has been reported in an aggregate of fine size cubic crystallites in all three alloys. Selected area diffraction patterns show that the crystalline aggregate symmetry is linked to the icosahedral point group symmetry (m35). Various ways of expressing the twin relationship in the cubic crystalline aggregates have been discussed. The thermal stability of the icosahedral phase at high temperatures reveals that the icosahedral phase in Al-Mn-Si and Al-Mn-Cr-Si alloys transforms to alpha-AlMnSi at temperatures of 690 and 670 K, respectively. In Al-Cr-Si alloy, heating to a high temperature (615 K) leads to the transformation of the icosahedral phase into a new metastable phase having an ordered cubic structure equivalent to alpha-AlMnSi. The occurrence of multiple twinning leading to icosahedral symmetry in the as-spun Al-Cr-Si alloy is presumably due to this metastable phase. Copyright (C) 1996 Acta Metallurgica Inc.

Choice of Classifiers in Hierarchical Recognition of Online Handwritten Kannada and Tamil Aksharas

In this paper, we propose a novel dexterous technique for fast and accurate recognition of online handwritten Kannada and Tamil characters. Based on the primary classifier output and prior knowledge, the best classifier is chosen from set of three classifiers for second stage classification. Prior knowledge is obtained through analysis of the confusion matrix of primary classifier which helped in identifying the multiple sets of confused characters. Further, studies were carried out to check the performance of secondary classifiers in disambiguating among the confusion sets. Using this technique we have achieved an average accuracy of 92.6% for Kannada characters on the MILE lab dataset and 90.2% for Tamil characters on the HP Labs dataset.

The Folding Mechanism of Barstar: Evidence for Multiple Pathways and Multiple Intermediates

The mechanism of folding of the small protein barstar in the pre-transition zone at pH 7, 25 degrees C has been characterized using rapid mixing techniques. Earlier studies had established the validity of the three-state U-S reversible arrow U-F reversible arrow N mechanism for folding and unfolding in the presence of guanidine hydrochloride (GdnHCl) at concentrations greater than 2.0 M, where U-S and U-F are the slow-refolding and fast-refolding unfolded forms, respectively, and N is the fully folded form. It is now shown that early intermediates, I-S1 and I-S2 as well as a late native-like intermediate, I-N, are present on the folding pathways of U-S, and an early intermediate I-F1 on the folding pathway of U-F, when bars tar is refolded in concentrations of GdnHCl below 2.0 M. The rates of formation and disappearance of I-N, and the rates of formation of N at three different concentrations of GdnHCl in the pre-transition zone have been measured. The data indicate that in 1.5 M GdnHCl, I-N is not fully populated on the U-S --> I-S1 --> I-N --> N pathway because the rate of its formation is so slow that the U-S reversible arrow U-F reversible arrow N pathway can effectively compete with that pathway. In 1.0 M GdnHCl, the U-S --> I-S1 --> I-N transition is so fast that I-N is fully populated. In 0.6 M GdnHCl, I-N appears not to be fully populated because an alternative folding pathway, U-S --> I-S2 --> N, becomes available for the folding of U-S, in addition to the U-S --> I-S1 --> I-N --> N pathway Measurement of the binding of the hydrophobic dye 1-anilino-8-naphthalenesulphonate (ANS) during folding indicates that ANS binds to two distinct intermediates, I-M1 and I-M2, that form within 2 ms on the U-S --> I-M1 --> I-S1 --> I-N --> N and U-S --> I-M2 --> I-S2 --> N pathways. There is no evidence for the accumulation of intermediates that can bind ANS on the folding pathway of U-F.

Direction of arrival estimation in the presence of distributed noise sources: Cumulant based approach

In the past few years there have been attempts to develop subspace methods for DoA (direction of arrival) estimation using a fourth?order cumulant which is known to de?emphasize Gaussian background noise. To gauge the relative performance of the cumulant MUSIC (MUltiple SIgnal Classification) (c?MUSIC) and the standard MUSIC, based on the covariance function, an extensive numerical study has been carried out, where a narrow?band signal source has been considered and Gaussian noise sources, which produce a spatially correlated background noise, have been distributed. These simulations indicate that, even though the cumulant approach is capable of de?emphasizing the Gaussian noise, both bias and variance of the DoA estimates are higher than those for MUSIC. To achieve comparable results the cumulant approach requires much larger data, three to ten times that for MUSIC, depending upon the number of sources and how close they are. This is attributed to the fact that in the estimation of the cumulant, an average of a product of four random variables is needed to make an evaluation. Therefore, compared to those in the evaluation of the covariance function, there are more cross terms which do not go to zero unless the data length is very large. It is felt that these cross terms contribute to the large bias and variance observed in c?MUSIC. However, the ability to de?emphasize Gaussian noise, white or colored, is of great significance since the standard MUSIC fails when there is colored background noise. Through simulation it is shown that c?MUSIC does yield good results, but only at the cost of more data.

Classification of microwatersheds based on morphological characteristics

Three classification techniques, namely, K-means Cluster Analysis (KCA), Fuzzy Cluster Analysis (FCA), and Kohonen Neural Networks (KNN) were employed to group 25 microwatersheds of Kherthal watershed, Rajasthan into homogeneous groups for formulating the basis for suitable conservation and management practices. Ten parameters, mainly, morphological, namely, drainage density (D-d), bifurcation ratio (R-b), stream frequency (F-u), length of overland flow (L-o), form factor (R-f), shape factor (B-s), elongation ratio (R-e), circulatory ratio (R-c), compactness coefficient (C-c) and texture ratio (T) are used for the classification. Optimal number of groups is chosen, based on two cluster validation indices Davies-Bouldin and Dunn's. Comparative analysis of various clustering techniques revealed that 13 microwatersheds out of 25 are commonly suggested by KCA, FCA and KNN i.e., 52%; 17 microwatersheds out of 25 i.e., 68% are commonly suggested by KCA and FCA whereas these are 16 out of 25 in FCA and KNN (64%) and 15 out of 25 in KNN and CA (60%). It is observed from KNN sensitivity analysis that effect of various number of epochs (1000, 3000, 5000) and learning rates (0.01, 0.1-0.9) on total squared error values is significant even though no fixed trend is observed. Sensitivity analysis studies revealed that microwatershecls have occupied all the groups even though their number in each group is different in case of further increase in the number of groups from 5 to 6, 7 and 8. (C) 2010 International Association of Hydro-environment Engineering and Research, Asia Pacific Division. Published by Elsevier B.V. All rights reserved.