A hidden symmetry of AdS resonances

Recent investigations have revealed powerful selection rules for resonant energy transfer between modes of nonlinear perturbations in global anti-de Sitter (AdS) space-time. It is likely that these selection rules are due to the highly symmetric nature of the underlying AdS background, though the precise relation has remained unclear. In this article, we demonstrate that the equation satisfied by the scalar field mode functions in AdS(d+1) has a hidden SU(d) symmetry, and explicitly specify the multiplets of this SU(d) symmetry furnished by the mode functions. We also comment on the role this structure might play in explaining the selection rules.

NUMERICAL STUDIES OF DYNAMO ACTION IN A TURBULENT SHEAR FLOW. I.

We perform numerical experiments to study the shear dynamo problem where we look for the growth of a large-scale magnetic field due to non-helical stirring at small scales in a background linear shear flow in previously unexplored parameter regimes. We demonstrate the large-scale dynamo action in the limit where the fluid Reynolds number (Re) is below unity while the magnetic Reynolds number (Rm) is above unity; the exponential growth rate scales linearly with shear, which is consistent with earlier numerical works. The limit of low Re is particularly interesting, as seeing the dynamo action in this limit would provide enough motivation for further theoretical investigations, which may focus attention on this analytically more tractable limit of Re < 1 compared to the more formidable limit of Re > 1. We also perform simulations in the regimes where (i) both (Re, Rm) < 1, and (ii) Re > 1 and Rm < 1, and compute all of the components of the turbulent transport coefficients (alpha(ij) and alpha(ij)) using the test-field method. A reasonably good agreement is observed between our results and the results of earlier analytical works in similar parameter regimes.

RNA nucleosides as chiral sensing agents in NMR spectroscopy

The study reports chiral sensing properties of RNA nucleosides. Adenosine, guanosine, uridine and cytidine are used as chiral derivatizing agents to differentiate chiral 1 degrees-amines. A three component protocol has been adopted for complexation of nucleosides and amines. The chiral differentiating ability of nucleosides is examined for different amines based on the H-1 NMR chemical shift differences of diastereomers (Delta delta(R,S)). Enantiomeric differentiation has been observed at multiple chemically distinct proton sites. Adenosine and guanosine exhibit large chiral differentiation (Delta delta(R,S)) due to the presence of a purine ring. The diastereomeric excess (de) measured by using adenosine is in good agreement with the gravimetric values.

Human Action Recognition in Compressed Domain using PBL-McRBFN Approach

Large variations in human actions lead to major challenges in computer vision research. Several algorithms are designed to solve the challenges. Algorithms that stand apart, help in solving the challenge in addition to performing faster and efficient manner. In this paper, we propose a human cognition inspired projection based learning for person-independent human action recognition in the H.264/AVC compressed domain and demonstrate a PBL-McRBEN based approach to help take the machine learning algorithms to the next level. Here, we use gradient image based feature extraction process where the motion vectors and quantization parameters are extracted and these are studied temporally to form several Group of Pictures (GoP). The GoP is then considered individually for two different bench mark data sets and the results are classified using person independent human action recognition. The functional relationship is studied using Projection Based Learning algorithm of the Meta-cognitive Radial Basis Function Network (PBL-McRBFN) which has a cognitive and meta-cognitive component. The cognitive component is a radial basis function network while the Meta-Cognitive Component(MCC) employs self regulation. The McC emulates human cognition like learning to achieve better performance. Performance of the proposed approach can handle sparse information in compressed video domain and provides more accuracy than other pixel domain counterparts. Performance of the feature extraction process achieved more than 90% accuracy using the PTIL-McRBFN which catalyzes the speed of the proposed high speed action recognition algorithm. We have conducted twenty random trials to find the performance in GoP. The results are also compared with other well known classifiers in machine learning literature.

An Optical How Feature and McFIS Based Approach for 3-Dimensional Human Action Recognition

We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.

Action Recognition from Motion Capture Data using Meta-cognitive RBF Network Classifier

Action recognition plays an important role in various applications, including smart homes and personal assistive robotics. In this paper, we propose an algorithm for recognizing human actions using motion capture action data. Motion capture data provides accurate three dimensional positions of joints which constitute the human skeleton. We model the movement of the skeletal joints temporally in order to classify the action. The skeleton in each frame of an action sequence is represented as a 129 dimensional vector, of which each component is a 31) angle made by each joint with a fixed point on the skeleton. Finally, the video is represented as a histogram over a codebook obtained from all action sequences. Along with this, the temporal variance of the skeletal joints is used as additional feature. The actions are classified using Meta-Cognitive Radial Basis Function Network (McRBFN) and its Projection Based Learning (PBL) algorithm. We achieve over 97% recognition accuracy on the widely used Berkeley Multimodal Human Action Database (MHAD).

Anisotropy in the mechanical properties of organic crystals: temperature dependence

The nanoindentation technique has recently been utilized for quantitative evaluation of the mechanical properties of molecular materials successfully, including their temperature (T) dependence. In this paper, we examine how the mechanical anisotropy varies with T in saccharin and L-alanine single crystals. Our results show that elastic modulus (E) decreases linearly in all the cases examined, with the T-dependence of E being anisotropic. Correspondence between directional dependence of the slopes of the E vs. T plots and the linear thermal expansion coefficients was found. The T-dependence of hardness (H), on the other hand, was found to be nonlinear and significant when (100) of saccharin and (001) of L-alanine are indented. While the anisotropies in E and H of saccharin and E of L-alanine enhance with T, the anisotropy in H of L-alanine was found to reduce with T. Possible mechanistic origins of these variations are discussed.

Ag+-induced reverse vesicle to helical fiber transformation in a self-assembly by adjusting the keto-enol equilibrium of a chiral salicylideneaniline

A new chiral amphiphilic salicylideneaniline bearing a terminal pyridine was synthesized. It formed reverse vesicles in toluene. The addition of Ag+, however, reversibly transforms these reverse vesicles into left-handed nanohelices accompanied by spontaneous gel formation at room temperature.

Human action recognition in H.264/AVC compressed domain using meta-cognitive radial basis function network

In this paper, we propose a H.264/AVC compressed domain human action recognition system with projection based metacognitive learning classifier (PBL-McRBFN). The features are extracted from the quantization parameters and the motion vectors of the compressed video stream for a time window and used as input to the classifier. Since compressed domain analysis is done with noisy, sparse compression parameters, it is a huge challenge to achieve performance comparable to pixel domain analysis. On the positive side, compressed domain allows rapid analysis of videos compared to pixel level analysis. The classification results are analyzed for different values of Group of Pictures (GOP) parameter, time window including full videos. The functional relationship between the features and action labels are established using PBL-McRBFN with a cognitive and meta-cognitive component. The cognitive component is a radial basis function, while the meta-cognitive component employs self-regulation to achieve better performance in subject independent action recognition task. The proposed approach is faster and shows comparable performance with respect to the state-of-the-art pixel domain counterparts. It employs partial decoding, which rules out the complexity of full decoding, and minimizes computational load and memory usage. This results in reduced hardware utilization and increased speed of classification. The results are compared with two benchmark datasets and show more than 90% accuracy using the PBL-McRBFN. The performance for various GOP parameters and group of frames are obtained with twenty random trials and compared with other well-known classifiers in machine learning literature. (C) 2015 Elsevier B.V. All rights reserved.

Compressed domain human action recognition in H.264/AVC video streams

This paper discusses a novel high-speed approach for human action recognition in H.264/AVC compressed domain. The proposed algorithm utilizes cues from quantization parameters and motion vectors extracted from the compressed video sequence for feature extraction and further classification using Support Vector Machines (SVM). The ultimate goal of the proposed work is to portray a much faster algorithm than pixel domain counterparts, with comparable accuracy, utilizing only the sparse information from compressed video. Partial decoding rules out the complexity of full decoding, and minimizes computational load and memory usage, which can result in reduced hardware utilization and faster recognition results. The proposed approach can handle illumination changes, scale, and appearance variations, and is robust to outdoor as well as indoor testing scenarios. We have evaluated the performance of the proposed method on two benchmark action datasets and achieved more than 85 % accuracy. The proposed algorithm classifies actions with speed (> 2,000 fps) approximately 100 times faster than existing state-of-the-art pixel-domain algorithms.

Effect of Surface Energy Anisotropy on the Stability of Growth Fronts in Multiphase Alloys

Eutectic growth offers a variety of examples for pattern formation which are interesting both for theoreticians as well as experimentalists. One such example of patterns is ternary eutectic colonies which arise as a result of instabilities during growth of two solid phases. Here, in addition to the two major components being exchanged between the solid phases during eutectic growth, there is an impurity component which is rejected by both solid phases. During progress of solidification, there develops a boundary layer of the third impurity component ahead of the solidification front of the two solid phases. Similar to Mullins-Sekerka type instabilities, such a boundary layer tends to make the global solidification envelope unstable to morphological perturbations giving rise to two-phase cells. This phenomenon has been studied numerically in two dimensions for the conditions of directional solidification, by Plapp and Karma (Phys Rev E 66:061608, 2002) using phase-field simulations. While, in the work by Plapp and Karma (Phys Rev E 66:061608, 2002) all interfaces are isotropic, in our presentation, we extend the phase-field model by considering interfacial anisotropy in the solid-solid and solid-liquid interfaces and characterize the role of interfacial anisotropy on the stability of the growth front through phase-field simulations in two dimensions.

Looking for BSM physics using top-quark polarization and decay-lepton kinematic asymmetries

We explore beyond-standard-model (BSM) physics signatures in the l + jets channel of the t (t) over bar pair production process at the Tevatron and the LHC. We study the effects of BSM physics scenarios on the top-quark polarization and on the kinematics of the decay leptons. To this end, we construct asymmetries using the lepton energy and angular distributions. Further, we find their correlations with the top polarization, net charge asymmetry and top forward-backward asymmetry. We show that when used together, these observables can help discriminate effectively between SM and different BSM scenarios, which can lead to varying degrees of top polarization at the Tevatron as well as the LHC. We use two types of colored mediator models to demonstrate the effectiveness of proposed observables, an s-channel axigluon and a u-channel diquark.

Influence of Anisotropy on Pavement Responses Using Adaptive Sparse Polynomial Chaos Expansion

Modeling the spatial variability that exists in pavement systems can be conveniently represented by means of random fields; in this study, a probabilistic analysis that considers the spatial variability, including the anisotropic nature of the pavement layer properties, is presented. The integration of the spatially varying log-normal random fields into a linear-elastic finite difference analysis has been achieved through the expansion optimal linear estimation method. For the estimation of the critical pavement responses, metamodels based on polynomial chaos expansion (PCE) are developed to replace the computationally expensive finite-difference model. The sparse polynomial chaos expansion based on an adaptive regression-based algorithm, and enhanced by the combined use of the global sensitivity analysis (GSA) is used, with significant savings in computational effort. The effect of anisotropy in each layer on the pavement responses was studied separately, and an effort is made to identify the pavement layer wherein the introduction of anisotropic characteristics results in the most significant impact on the critical strains. It is observed that the anisotropy in the base layer has a significant but diverse effect on both critical strains. While the compressive strain tends to be considerably higher than that observed for the isotropic section, the tensile strains show a decrease in the mean value with the introduction of base-layer anisotropy. Furthermore, asphalt-layer anisotropy also tends to decrease the critical tensile strain while having little effect on the critical compressive strain. (C) 2015 American Society of Civil Engineers.

Efficient and practical synthesis of modular chiral beta-organochalcogeno amines, ArYCH2CH(R)NH2, and single crystal structures of (S) - MsOCH2CH(Bz)NH3+ center dot Cl- and (R)-MsOCH2CH(Ph)NH3+ center dot Cl-

Modular chiral I3-organochalcogeno amines, ArYCH2CH(R)NH2 (4a-4g) where R = Me, Bz, Ph; and ArY = PhS, BzSe and 4-MeOC6H4Te respectively have been synthesized and characterized. Compounds 4a-4g were synthesized (Method II) from chiral aminoalkyl 13-methanesulfonate hydrochlorides, MsOCH2CH(R)NH3+ center dot Cl- (2a-2c) through nucleophilic displacement of MsO- with organochalcogenolate (ArY-). In another attempt (Method I) chiral beta-organotelluro amines (4a-4c) were prepared by deprotection of chiral N-boc I3-organotelluro amides, 4-MeOC6H4TeCH2CH(R)NH-Boc (3a-3c), which in turn, 13,-,1 were made from chiral N-boc 13-methanesulfonate amides (la-lc) and ArTeNa. 1H, and FTIR spectra of all the compounds (3a-3c and 4a-4g) were characteristic. The composition of 3a-3c was determined by elemental analysis. The a]TD values of 3b-3c and 4a-4g were determined. The single crystal structures of (S)-2b and (R)-2c were determined by X-Ray diffraction studies. Both (S)-2b and (R)2c were crystallized in orthorhombic system and the Flack parameter x was found 0.08(12) and 0.00(2) respectively. The crystal of (S)-2b contain two asymmetric units with gauche (A) and staggered (B) conformations. There are NH Cl-, NH-O and CH-O intra and intermolecular secondary interactions in (S)-2b and (R)-2c resulting in supramolecular structures. (C) 2015 Elsevier By. All rights reserved.

The cis-Diammineplatinum(II) Complex of Curcumin: A Dual Action DNA Crosslinking and Photochemotherapeutic Agent

Pt(cur)(NH3)(2)](NO3) (1), a curcumin-bound cis-diammineplatinum(II) complex, nicknamed Platicur, as a novel photoactivated chemotherapeutic agent releases photoactive curcumin and an active platinum(II) species upon irradiation with visible light. The hydrolytic instability of free curcumin reduces upon binding to platinum(II). Interactions of 1 with 5'-GMP and ct-DNA indicated formation of platinum-bound DNA adducts upon exposure to visible light (lambda = 400-700 nm). It showed apoptotic photocytotoxicity in cancer cells (IC50 approximate to 15 mu M), thus forming (OH)-O-center dot, while remaining passive in the darkness (IC50 > 200 mu M). A comet assay and platinum estimation suggest Pt-DNA crosslink formation. The fluorescence microscopic images showed cytosolic localization of curcumin, thus implying possibility of dual action as a chemo-and phototherapeutic agent.