Modeling of nonreacting and reacting turbulent spray jets using a fully stochastic separated flow approach

Numerical modeling of several turbulent nonreacting and reacting spray jets is carried out using a fully stochastic separated flow (FSSF) approach. As is widely used, the carrier-phase is considered in an Eulerian framework, while the dispersed phase is tracked in a Lagrangian framework following the stochastic separated flow (SSF) model. Various interactions between the two phases are taken into account by means of two-way coupling. Spray evaporation is described using a thermal model with an infinite conductivity in the liquid phase. The gas-phase turbulence terms are closed using the k-epsilon model. A novel mixture fraction based approach is used to stochastically model the fluctuating temperature and composition in the gas phase and these are then used to refine the estimates of the heat and mass transfer rates between the droplets and the surrounding gas-phase. In classical SSF (CSSF) methods, stochastic fluctuations of only the gas-phase velocity are modeled. Successful implementation of the FSSF approach to turbulent nonreacting and reacting spray jets is demonstrated. Results are compared against experimental measurements as well as with predictions using the CSSF approach for both nonreacting and reacting spray jets. The FSSF approach shows little difference from the CSSF predictions for nonreacting spray jets but differences are significant for reacting spray jets. In general, the FSSF approach gives good predictions of the flame length and structure but further improvements in modeling may be needed to improve the accuracy of some details of the Predictions. (C) 2011 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

Determining Top K Nodes in Social Networks using the Shapley Value

In this paper, we consider the problem of selecting, for any given positive integer k, the top-k nodes in a social network, based on a certain measure appropriate for the social network. This problem is relevant in many settings such as analysis of co-authorship networks, diffusion of information, viral marketing, etc. However, in most situations, this problem turns out to be NP-hard. The existing approaches for solving this problem are based on approximation algorithms and assume that the objective function is sub-modular. In this paper, we propose a novel and intuitive algorithm based on the Shapley value, for efficiently computing an approximate solution to this problem. Our proposed algorithm does not use the sub-modularity of the underlying objective function and hence it is a general approach. We demonstrate the efficacy of the algorithm using a co-authorship data set from e-print arXiv (www.arxiv.org), having 8361 authors.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

Synergy between the N-terminal and C-terminal domains of Mycobacterium tuberculosis HupB is essential for high-affinity binding, DNA supercoiling and inhibition of RecA-promoted strand exchange

The occurrence of DNA architectural proteins containing two functional domains derived from two different architectural proteins is an interesting emerging research theme in the field of nucleoid structure and function. Mycobacterium tuberculosis HupB, unlike Escherichia coli HU, is a two-domain protein that, in the N-terminal region, shows broad sequence homology with bacterial HU. The long C-terminal extension, on the other hand, contains seven PAKK/KAAK motifs, which are characteristic of the histone H1/H5 family of proteins. In this article, we describe several aspects of HupB function, in comparison with its truncated derivatives lacking either the C-terminus or N-terminus. We found that HupB binds a variety of DNA repair and replication intermediates with K(d) values in the nanomolar range. By contrast, the N-terminal fragment of M. tuberculosis HupB (HupB(MtbN)) showed diminished DNA-binding activity, with K(d) values in the micromolar range, and the C-terminal domain was completely devoid of DNA-binding activity. Unlike HupB(MtbN), HupB was able to constrain DNA in negative supercoils and introduce negative superhelical turns into relaxed DNA. Similarly, HupB exerted a robust inhibitory effect on DNA strand exchange promoted by cognate and noncognate RecA proteins, whereas HupB(MtbN), even at a 50-fold molar excess, had no inhibitory effect. Considered together, these results suggest that synergy between the N-terminal and C-terminal domains of HupB is essential for its DNA-binding ability, and to modulate the topological features of DNA, which has implications for processes such as DNA compaction, gene regulation, homologous recombination, and DNA repair.

Revisiting the Mechanism of the Triosephosphate Isomerase Reaction: The Role of the Fully Conserved Glutamic Acid 97 Residue

An analysis of 503 available triosephosphate isomerase sequences revealed nine fully conserved residues. Of these, four residues-K12, H95, E97 and E165-are capable of proton transfer and are all arrayed around the dihydroxyacetone phosphate substrate in the three-dimensional structure. Specific roles have been assigned to the residues K12, H95 and E165, but the nature of the involvement of E97 has not been established. Kinetic and structural characterization is reported for the E97Q and E97D mutants of Plasmodium falciparum triosephosphate isomerase (Pf TIM). A 4000-fold reduction in k(cat) is observed for E97Q, whereas the E97D mutant shows a 100-fold reduction. The control mutant, E165A, which lacks the key catalytic base, shows an approximately 9000-fold drop in activity. The integrity of the overall fold and stability of the dimeric structure have been demonstrated by biophysical studies. Crystal structures of E97Q and E97D mutants have been determined at 2.0 angstrom resolution. In the case of the isosteric replacement of glutamic acid by glutamine in the E97Q mutant a large conformational change for the critical K12 side chain is observed, corresponding to a trans-to-gauche transition about the C gamma-C delta (chi(3)) bond. In the E97D mutant, the K12 side chain maintains the wild-type orientation, but the hydrogen bond between K12 and D97 is lost. The results are interpreted as a direct role for E97 in the catalytic proton transfer cycle. The proposed mechanism eliminates the need to invoke the formation of the energetically unfavourable imidazolate anion at H95, a key feature of the classical mechanism.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

Unique Utilization of a Phosphoprotein Phosphatase Fold by a Mammalian Phosphodiesterase Associated with WAGR Syndrome

Metallophosphoesterase-domain-containing protein 2 (MPPED2) is a highly evolutionarily conserved protein with orthologs found from worms to humans. The human MPPED2 gene is found in a region of chromosome 11 that is deleted in patients with WAGR (Wilms tumor, aniridia, genitourinary anomalies, and mental retardation) syndrome, and MPPED2 may function as a tumor suppressor. However, the precise cellular roles of MPPED2 are unknown, and its low phosphodiesterase activity suggests that substrate hydrolysis may not be its prime function. We present here the structures of MPPED2 and two mutants, which show that the poor activity of MPPED2 is not only a consequence of the substitution of an active-site histidine residue by glycine but also due to binding of AMP or GMP to the active site. This feature, enhanced by structural elements of the protein, allows MPPED2 to utilize the conserved phosphoprotein-phosphatase-like fold in a unique manner, ensuring that its enzymatic activity can be combined with a possible role as a scaffolding or adaptor protein. (C) 2011 Elsevier Ltd. All rights reserved.

Structural biology of Mycobacterium tuberculosis proteins: The Indian efforts

Among the many different objectives of large scale structural genomics projects are expanding the protein fold space, enhancing understanding of a model or disease-related organism, and providing foundations for structure-based drug discovery. Systematic analysis of protein structures of Mycobacterium tuberculosis has been ongoing towards meeting some of these objectives. Indian participation in these efforts has been enthusiastic and substantial. The proteins of M. tuberculosis chosen for structural analysis by the Indian groups span almost all the functional categories. The structures determined by the Indian groups have led to significant improvement in the biochemical knowledge on these proteins and consequently have started providing useful insights into the biology of M. tuberculosis. Moreover, these structures form starting points for inhibitor design studies, early results of which are encouraging. The progress made by Indian structural biologists in determining structures of M. tuberculosis proteins is highlighted in this review. (C) 2011 Elsevier Ltd. All rights reserved.

Non Identical Duplicate Video Detection using SIFT Method

Non-Identical Duplicate video detection is a challenging research problem. Non-Identical Duplicate video are a pair of videos that are not exactly identical but are almost similar.In this paper, we evaluate two methods - Keyframe -based and Tomography-based methods to determine the Non-Identical Duplicate videos. These two methods make use of the existing scale based shift invariant (SIFT) method to find the match between the key frames in first method, and the cross-sections through the temporal axis of the videos in second method.We provide extensive experimental results and the analysis of accuracy and efficiency of the above two methods on a data set of Non- Identical Duplicate video-pair.

Ultrasound-modulated optical tomography: recovery of amplitude of vibration in the insonified region from boundary measurement of light correlation

We address a certain inverse problem in ultrasound-modulated optical tomography: the recovery of the amplitude of vibration of scatterers [p(r)] in the ultrasound focal volume in a diffusive object from boundary measurement of the modulation depth (M) of the amplitude autocorrelation of light [phi(r, tau)] traversing through it. Since M is dependent on the stiffness of the material, this is the precursor to elasticity imaging. The propagation of phi(r, tau) is described by a diffusion equation from which we have derived a nonlinear perturbation equation connecting p(r) and refractive index modulation [Delta n(r)] in the region of interest to M measured on the boundary. The nonlinear perturbation equation and its approximate linear counterpart are solved for the recovery of p(r). The numerical results reveal regions of different stiffness, proving that the present method recovers p(r) with reasonable quantitative accuracy and spatial resolution. (C) 2011 Optical Society of America