Fracture analysis of cracked plate panels using NI-MVCCI technique

The objective of this paper is to propose a numerically integrated modified virtual crack closure integral (NI-MVCCI) technique for fracture analysis of cracked plate panels. NI-MVCCI technique is generalized one and the expressions for computing the strain energy release rate (SERR) are independent of the finite element employed. NI-MVCCI technique has been demonstrated for 4-noded, 8-noded (regular and quarter-point) and 9-noded isoparametric finite elements. Numerical studies on fracture analysis of 2-D crack (mode-I and mode-II) problems have been conducted employing these elements. SERR and stress intensity factors (SIF) have been computed for these problems and found to be in good agreement with the respective analytical solutions available in the literature. The appropriate Gauss numerical integration order to be employed for each of these elements for accurate computation of SERR and SIF has been recommended based on the studies.

Sequence-Structure Similarity: Do Sequentially Identical Peptide Fragments have Similar Three-Dimensional Structures?

The rapidly growing structure databases enhance the probability of finding identical sequences sharing structural similarity. Structure prediction methods are being used extensively to abridge the gap between known protein sequences and the solved structures which is essential to understand its specific biochemical and cellular functions. In this work, we plan to study the ambiguity between sequence-structure relationships and examine if sequentially identical peptide fragments adopt similar three-dimensional structures. Fragments of varying lengths (five to ten residues) were used to observe the behavior of sequence and its three-dimensional structures. The STAMP program was used to superpose the three-dimensional structures and the two parameters (Sequence Structure Similarity Score (Sc) and Root Mean Square Deviation value) were employed to classify them into three categories: similar, intermediate and dissimilar structures. Furthermore, the same approach was carried out on all the three-dimensional protein structures solved in the two organisms, Mycobacterium tuberculosis and Plasmodium falciparum to validate our results.

Renormalization of noncommutative quantum field theories

We report on a comprehensive analysis of the renormalization of noncommutative phi(4) scalar field theories on the Groenewold-Moyal plane. These scalar field theories are twisted Poincare invariant. Our main results are that these scalar field theories are renormalizable, free of UV/IR mixing, possess the same fixed points and beta-functions for the couplings as their commutative counterparts. We also argue that similar results hold true for any generic noncommutative field theory with polynomial interactions and involving only pure matter fields. A secondary aim of this work is to provide a comprehensive review of different approaches for the computation of the noncommutative S-matrix: noncommutative interaction picture and noncommutative Lehmann-Symanzik-Zimmermann formalism. DOI: 10.1103/PhysRevD.87.064014

Second order transport from anomalies

We study parity odd transport at second order in derivative expansion for a non-conformal charged fluid. We see that there are 27 parity odd transport coefficients, of which 12 are non-vanishing in equilibrium. We use the equilibrium partition function method to express 7 of these in terms of the anomaly, shear viscosity, charge diffusivity and thermodynamic functions. The remaining 5 are constrained by 3 relations which also involve the anomaly. We derive Kubo formulae for 2 of the transport coefficients and show these agree with that derived from the equilibrium partition function.

Iodide Retention by Modified Kaolinite in the Context of Safe Disposal of High Level Nuclear Waste

Bentonite clay is identified as potential buffer in deep geological repositories (DGR) that store high level radioactive wastes (HLW) as the expansive clay satisfies the expected mechanical and physicochemical functions of the buffer material. In the deep geological disposal of HLW, iodine-129 is one of the significant nuclides, attributable to its long half-life (half life 1⁄4 1:7 × 107 years). However, the negative charge on the basal surface of bentonite particles precludes retention of iodide anions. To render the bentonite effective in retaining hazardous iodide species in DGR, improvement of the anion retention capacity of bentonite becomes imperative. The iodide retention capac-ity of bentonite is improved by admixing 10 and 20% Ag-kaolinite (Ag-K) with bentonite (B) on a dry mass basis. The present study produced Ag-kaolinite by heating silver nitrate-kaolinite mixes at 400°C. Marginal release of iodide retained by Ag-kaolinite occurred under extreme acidic (pH 1⁄4 2:5) and alkaline (pH 1⁄4 12:5) conditions. The swell pressure and iodide etention results of the B-Ag-K specimens bring out that mixing Ag-K with bentonite does not chemically modify the expansive clay; the mixing is physical in nature and Ag-K presence only contributes to iodide retention of the admixture. DOI: 10.1061/(ASCE)HZ.2153-5515.0000121. © 2012 American Society of Civil Engineers.

Accurate prediction of interfacial residues in two-domain proteins using evolutionary information: Implications for three-dimensional modeling

With the preponderance of multidomain proteins in eukaryotic genomes, it is essential to recognize the constituent domains and their functions. Often function involves communications across the domain interfaces, and the knowledge of the interacting sites is essential to our understanding of the structure-function relationship. Using evolutionary information extracted from homologous domains in at least two diverse domain architectures (single and multidomain), we predict the interface residues corresponding to domains from the two-domain proteins. We also use information from the three-dimensional structures of individual domains of two-domain proteins to train naive Bayes classifier model to predict the interfacial residues. Our predictions are highly accurate (approximate to 85%) and specific (approximate to 95%) to the domain-domain interfaces. This method is specific to multidomain proteins which contain domains in at least more than one protein architectural context. Using predicted residues to constrain domain-domain interaction, rigid-body docking was able to provide us with accurate full-length protein structures with correct orientation of domains. We believe that these results can be of considerable interest toward rational protein and interaction design, apart from providing us with valuable information on the nature of interactions. Proteins 2014; 82:1219-1234. (c) 2013 Wiley Periodicals, Inc.

Surrogate Regret Bounds for Bipartite Ranking via Strongly Proper Losses

The problem of bipartite ranking, where instances are labeled positive or negative and the goal is to learn a scoring function that minimizes the probability of mis-ranking a pair of positive and negative instances (or equivalently, that maximizes the area under the ROC curve), has been widely studied in recent years. A dominant theoretical and algorithmic framework for the problem has been to reduce bipartite ranking to pairwise classification; in particular, it is well known that the bipartite ranking regret can be formulated as a pairwise classification regret, which in turn can be upper bounded using usual regret bounds for classification problems. Recently, Kotlowski et al. (2011) showed regret bounds for bipartite ranking in terms of the regret associated with balanced versions of the standard (non-pairwise) logistic and exponential losses. In this paper, we show that such (non-pairwise) surrogate regret bounds for bipartite ranking can be obtained in terms of a broad class of proper (composite) losses that we term as strongly proper. Our proof technique is much simpler than that of Kotlowski et al. (2011), and relies on properties of proper (composite) losses as elucidated recently by Reid and Williamson (2010, 2011) and others. Our result yields explicit surrogate bounds (with no hidden balancing terms) in terms of a variety of strongly proper losses, including for example logistic, exponential, squared and squared hinge losses as special cases. An important consequence is that standard algorithms minimizing a (non-pairwise) strongly proper loss, such as logistic regression and boosting algorithms (assuming a universal function class and appropriate regularization), are in fact consistent for bipartite ranking; moreover, our results allow us to quantify the bipartite ranking regret in terms of the corresponding surrogate regret. We also obtain tighter surrogate bounds under certain low-noise conditions via a recent result of Clemencon and Robbiano (2011).

Optimal control analysis of the dynamic growth behavior of microorganisms

Understanding the growth behavior of microorganisms using modeling and optimization techniques is an active area of research in the fields of biochemical engineering and systems biology. In this paper, we propose a general modeling framework, based on Monad model, to model the growth of microorganisms. Utilizing the general framework, we formulate an optimal control problem with the objective of maximizing a long-term cellular goal and solve it analytically under various constraints for the growth of microorganisms in a two substrate batch environment. We investigate the relation between long term and short term cellular goals and show that the objective of maximizing cellular concentration at a fixed final time is equivalent to maximization of instantaneous growth rate. We then establish the mathematical connection between the generalized framework and optimal and cybernetic modeling frameworks and derive generalized governing dynamic equations for optimal and cybernetic models. We finally illustrate the influence of various constraints in the cybernetic modeling framework on the optimal growth behavior of microorganisms by solving several dynamic optimization problems using genetic algorithms. (C) 2014 Published by Elsevier Inc.

Zero-Crossings Based Spectrum Sensing Under Noise Uncertainties

In this work, the hypothesis testing problem of spectrum sensing in a cognitive radio is formulated as a Goodness-of-fit test against the general class of noise distributions used in most communications-related applications. A simple, general, and powerful spectrum sensing technique based on the number of weighted zero-crossings in the observations is proposed. For the cases of uniform and exponential weights, an expression for computing the near-optimal detection threshold that meets a given false alarm probability constraint is obtained. The proposed detector is shown to be robust to two commonly encountered types of noise uncertainties, namely, the noise model uncertainty, where the PDF of the noise process is not completely known, and the noise parameter uncertainty, where the parameters associated with the noise PDF are either partially or completely unknown. Simulation results validate our analysis, and illustrate the performance benefits of the proposed technique relative to existing methods, especially in the low SNR regime and in the presence of noise uncertainties.

Pd-Catalyzed Hydroborylation of Alkynes: A Ligand Controlled Regioselectivity Switch for the Synthesis of alpha- or beta-Vinylboronates

A ligand controlled selective hydroborylation of alkynes to alpha- or beta-vinylboronates has been developed using a Pd catalyst. The high alpha-selectivity displayed by this reaction can be switched to furnish beta-vinylboronates by altering the ligand from a trialkylphosphine to N-heterocyclic carbene. A variety of terminal alkynes are shown to furnish the corresponding alpha- or beta-vinylboronates in good to excellent selectivity and yield. The mechanistic studies suggest that the solvent is the proton source and bromobenzene functions as an important additive in driving this reaction forward.

Pd-Catalyzed Hydroborylation of Alkynes: A Ligand Controlled Regioselectivity Switch for the Synthesis of alpha- or beta-Vinylboronates

A ligand controlled selective hydroborylation of alkynes to alpha- or beta-vinylboronates has been developed using a Pd catalyst. The high alpha-selectivity displayed by this reaction can be switched to furnish beta-vinylboronates by altering the ligand from a trialkylphosphine to N-heterocyclic carbene. A variety of terminal alkynes are shown to furnish the corresponding alpha- or beta-vinylboronates in good to excellent selectivity and yield. The mechanistic studies suggest that the solvent is the proton source and bromobenzene functions as an important additive in driving this reaction forward.