Loss and gain signals in broadband stimulated-Raman spectra: Theoretical analysis

Stimulated optical signals obtained by subjecting the system to a narrow band and a broadband pulse show both gain and loss Raman features at the red and blue side of the narrow beam, respectively. Recently observed temperature-dependent asymmetry in these features Mallick et al., J. Raman Spectrosc. 42, 1883 (2011); Dang et al., Phys. Rev. Lett. 107, 043001 (2011)] has been attributed to the Stokes and anti-Stokes components of the third-order susceptibility, chi((3)). By treating the setup as a steady state of an open system coupled to four quantum radiation field modes, we show that Stokes and anti-Stokes processes contribute to both the loss and gain resonances. chi((3)) predicts loss and gain signals with equal intensity for electronically off-resonant excitation. Some asymmetry may exist for resonant excitation. However, this is unrelated to the Stokes vs anti-Stokes processes. Any observed temperature-dependent asymmetry must thus originate from effects lying outside the chi((3)) regime.

Homocysteine alters the osteoprotegerin/RANKL system in the osteoblast to promote bone loss: pivotal role of the redox regulator forkhead O1

In this study we determined the molecular mechanisms of how homocysteine differentially affects receptor activator of nuclear factor-kappa B ligand (RANKL) and osteoprotegerin (OPG) synthesis in the bone. The results showed that oxidative stress induced by homocysteine deranges insulin-sensitive FOXO1 and MAP kinase signaling cascades to decrease OPG and increase RANKL synthesis in osteoblast cultures. We observed that downregulation of insulin/FOXO1 and p38 MAP kinase signaling mechanisms due to phosphorylation of protein phosphatase 2 A (PP2A) was the key event that inhibited OPG synthesis in homocysteine-treated osteoblast cultures. siRNA knockdown experiments confirmed that FOXO1 is integral to OPG and p38 synthesis. Conversely homocysteine increased RANKL synthesis in osteoblasts through c-Jun/JNK MAP kinase signaling mechanisms independent of FOXO1. In the rat bone milieu, high-methionine diet-induced hyperhomocysteinemia lowered FOXO1 and OPG expression and increased synthesis of proresorptive and inflammatory cytokines such as RANKL, M-CSF, IL-1 alpha, IL-1 beta, G-CSF, GM-CSF, MIP-1 alpha, IFN-gamma, IL-17, and TNF-alpha. Such pathophysiological conditions were exacerbated by ovariectomy. Lowering the serum homocysteine level by a simultaneous supplementation with N-acetylcysteine improved OPG and FOXO1 expression and partially antagonized RANKL and proresorptive cytokine synthesis in the bone milieu. These results emphasize that hyperhomocysteinemia alters the redox regulatory mechanism in the osteoblast by activating PP2A and deranging FOXO1 and MAPK signaling cascades, eventually shifting the OPG:RANKL ratio toward increased osteoclast activity and decreased bone quality (C) 2013 Elsevier Inc. All rights reserved.

Efficient method of moving shadow detection and vehicle classification

Moving shadow detection and removal from the extracted foreground regions of video frames, aim to limit the risk of misconsideration of moving shadows as a part of moving objects. This operation thus enhances the rate of accuracy in detection and classification of moving objects. With a similar reasoning, the present paper proposes an efficient method for the discrimination of moving object and moving shadow regions in a video sequence, with no human intervention. Also, it requires less computational burden and works effectively under dynamic traffic road conditions on highways (with and without marking lines), street ways (with and without marking lines). Further, we have used scale-invariant feature transform-based features for the classification of moving vehicles (with and without shadow regions), which enhances the effectiveness of the proposed method. The potentiality of the method is tested with various data sets collected from different road traffic scenarios, and its superiority is compared with the existing methods. (C) 2013 Elsevier GmbH. All rights reserved.

Classification of Vehicles Using Magnetic Field Angle Model

This paper presents an efficient approach to the modeling and classification of vehicles using the magnetic signature of the vehicle. A database was created using the magnetic signature collected over a wide range of vehicles(cars). A sensor dependent approach called as Magnetic Field Angle Model is proposed for modeling the obtained magnetic signature. Based on the data model, we present a novel method to extract the feature vector from the magnetic signature. In the classification of vehicles, a linear support vector machine configuration is used to classify the vehicles based on the obtained feature vectors.

Classification, representation, and automatic extraction of deformation features in sheet metal parts

This paper presents classification, representation and extraction of deformation features in sheet-metal parts. The thickness is constant for these shape features and hence these are also referred to as constant thickness features. The deformation feature is represented as a set of faces with a characteristic arrangement among the faces. Deformation of the base-sheet or forming of material creates Bends and Walls with respect to a base-sheet or a reference plane. These are referred to as Basic Deformation Features (BDFs). Compound deformation features having two or more BDFs are defined as characteristic combinations of Bends and Walls and represented as a graph called Basic Deformation Features Graph (BDFG). The graph, therefore, represents a compound deformation feature uniquely. The characteristic arrangement of the faces and type of bends belonging to the feature decide the type and nature of the deformation feature. Algorithms have been developed to extract and identify deformation features from a CAD model of sheet-metal parts. The proposed algorithm does not require folding and unfolding of the part as intermediate steps to recognize deformation features. Representations of typical features are illustrated and results of extracting these deformation features from typical sheet metal parts are presented and discussed. (C) 2013 Elsevier Ltd. All rights reserved.

A unified view of energetic efficiency in active drag reduction, thrust generation and self-propulsion through a loss coefficient with some applications

An analysis of the energy budget for the general case of a body translating in a stationary fluid under the action of an external force is used to define a power loss coefficient. This universal definition of power loss coefficient gives a measure of the energy lost in the wake of the translating body and, in general, is applicable to a variety of flow configurations including active drag reduction, self-propulsion and thrust generation. The utility of the power loss coefficient is demonstrated on a model bluff body flow problem concerning a two-dimensional elliptical cylinder in a uniform cross-flow. The upper and lower boundaries of the elliptic cylinder undergo continuous motion due to a prescribed reflectionally symmetric constant tangential surface velocity. It is shown that a decrease in drag resulting from an increase in the strength of tangential surface velocity leads to an initial reduction and eventual rise in the power loss coefficient. A maximum in energetic efficiency is attained for a drag reducing tangential surface velocity which minimizes the power loss coefficient. The effect of the tangential surface velocity on drag reduction and self-propulsion of both bluff and streamlined bodies is explored through a variation in the thickness ratio (ratio of the minor and major axes) of the elliptical cylinders.

Low loss waveguide on chalcogenide glass using ultrafast laser at low repetition rate

In this work, we synthesized bulk amorphous GeGaS glass by conventional melt quenching technique. Amorphous nature of the glass is confirmed using X-ray diffraction. We fabricated the channel waveguides on this glass using the ultrafast laser inscription technique. The waveguides are written on this glass 100 mu m below the surface of the glass with a separation of 50 ae m by focusing the laser beam into the material using 0.67 NA lens. The laser parameters are set to 350 fs pulse duration at 100 KHz repetition rate. A range of writing energies with translation speeds 1 mm/s, 2 mm/s, 3 mm/s and 4 mm/s were investigated. After fabrication the waveguides facets were ground and polished to the optical quality to remove any tapering of the waveguide close to the edges. We characterized the loss measurement by butt coupling method and the mode field image of the waveguides has been captured to compare with the mode field image of fibers. Also we compared the asymmetry in the shape of the waveguide and its photo structural change using Raman spectra.

Classification of Myopathies on Molecular basis in Drosophila using Raman spectroscopy

Myopathies are muscular diseases in which muscle fibers degenerate due to many factors such as nutrient deficiency, infection and mutations in myofibrillar etc. The objective of this study is to identify the bio-markers to distinguish various muscle mutants in Drosophila (fruit fly) using Raman Spectroscopy. Principal Components based Linear Discriminant Analysis (PC-LDA) classification model yielding >95% accuracy was developed to classify such different mutants representing various myopathies according to their physiopathology.

Differentially private stochastic gradient descent algorithm for multiparty classification

We consider the problem of developing privacy-preserving machine learning algorithms in a dis-tributed multiparty setting. Here different parties own different parts of a data set, and the goal is to learn a classifier from the entire data set with-out any party revealing any information about the individual data points it owns. Pathak et al [7]recently proposed a solution to this problem in which each party learns a local classifier from its own data, and a third party then aggregates these classifiers in a privacy-preserving manner using a cryptographic scheme. The generaliza-tion performance of their algorithm is sensitive to the number of parties and the relative frac-tions of data owned by the different parties. In this paper, we describe a new differentially pri-vate algorithm for the multiparty setting that uses a stochastic gradient descent based procedure to directly optimize the overall multiparty ob-jective rather than combining classifiers learned from optimizing local objectives. The algorithm achieves a slightly weaker form of differential privacy than that of [7], but provides improved generalization guarantees that do not depend on the number of parties or the relative sizes of the individual data sets. Experimental results corrob-orate our theoretical findings.

Cluster labeling for multilingual scatter/gather using comparable corpora

Scatter/Gather systems are increasingly becoming useful in browsing document corpora. Usability of the present-day systems are restricted to monolingual corpora, and their methods for clustering and labeling do not easily extend to the multilingual setting, especially in the absence of dictionaries/machine translation. In this paper, we study the cluster labeling problem for multilingual corpora in the absence of machine translation, but using comparable corpora. Using a variational approach, we show that multilingual topic models can effectively handle the cluster labeling problem, which in turn allows us to design a novel Scatter/Gather system ShoBha. Experimental results on three datasets, namely the Canadian Hansards corpus, the entire overlapping Wikipedia of English, Hindi and Bengali articles, and a trilingual news corpus containing 41,000 articles, confirm the utility of the proposed system.

Classification of Myopathies on Molecular basis in Drosophila using Raman spectroscopy

Myopathies are muscular diseases in which muscle fibers degenerate due to many factors such as nutrient deficiency, infection and mutations in myofibrillar etc. The objective of this study is to identify the bio-markers to distinguish various muscle mutants in Drosophila (fruit fly) using Raman Spectroscopy. Principal Components based Linear Discriminant Analysis (PC-LDA) classification model yielding >95% accuracy was developed to classify such different mutants representing various myopathies according to their physiopathology.

Methionine down-regulates TLR4/MyD88/NF-kappa B signalling in osteoclast precursors to reduce bone loss during osteoporosis

Background and PurposeStudies have demonstrated that a moderate intake of amino acids is associated with development of bone health. Methionine, a sulphur-containing essential amino acid, has been largely implicated for improving cartilage formation, however its physiological significance on bone integrity and functionality have not been elucidated. We investigated whether methionine can prevent osteoporotic bone loss. Experimental ApproachThe anti-resorptive effect of methionine, (250mgkg(-1) body wt administered in drinking water for 10 weeks), was evaluated in ovariectomized (OVX) rats by monitoring changes in bone turnover, formation of osteoclasts from blood-derived mononuclear cells and changes in the synthesis of pro-osteoclastogenic cytokines. Key resultsMethionine improved bone density and significantly decreased the degree of osteoclast development from blood mononuclear cells in OVX rats, as indicated by decreased production of osteoclast markers tartarate resistant acid phosphatase b (TRAP5b) and MIP-1. siRNA-mediated knockdown of myeloid differentiation primary response 88 MyD88], a signalling molecule in the toll-like receptor (TLR) signalling cascade, abolished the synthesis of both TRAP5b and MIP-1 in developing osteoclasts. Methionine supplementation disrupted osteoclast development by inhibiting TLR-4/MyD88/NF-B pathway. Conclusions and ImplicationsTLR-4/MyD88/NF-B signalling pathway is integral for osteoclast development and this is down-regulated in osteoporotic system on methionine treatment. Methionine treatment could be beneficial for the treatment of postmenopausal osteoporosis.

Energy Loss in the Impact of Elastic Spheres on a Rigid Half-Space in Presence of Adhesion

Adhesion can cause energy losses in asperities or particles coming into dynamic contact resulting in frictional dissipation, even if the deformation occurring is purely elastic. Such losses are of special significance in impact of nanoparticles and friction between surfaces under low contact pressure to hardness ratio. The objective of this work is to study the effect of adhesion during the normal impact of elastic spheres on a rigid half-space, with an emphasis on understanding the mechanism of energy loss. We use finite element method for modeling the impact phenomenon, with the adhesion due to van der Waals force and the short-range repulsion included as body forces distributed over the volume of the sphere. This approach, in contrast with commonly used surface force approximation, helps to model the interactions in a more precise way. We find that the energy loss in impact of elastic spheres is negligible unless there are adhesion-induced instabilities. Significant energy loss through elastic stress waves occurs due to jump-to-contact and jump-out-of-contact instabilities and can even result in capture of the elastic sphere on the half-space.

H.264 COMPRESSED VIDEO CLASSIFICATION USING HISTOGRAM OF ORIENTED MOTION VECTORS (HOMV)

In this paper, we have proposed a simple and effective approach to classify H.264 compressed videos, by capturing orientation information from the motion vectors. Our major contribution involves computing Histogram of Oriented Motion Vectors (HOMV) for overlapping hierarchical Space-Time cubes. The Space-Time cubes selected are partially overlapped. HOMV is found to be very effective to define the motion characteristics of these cubes. We then use Bag of Features (B OF) approach to define the video as histogram of HOMV keywords, obtained using k-means clustering. The video feature, thus computed, is found to be very effective in classifying videos. We demonstrate our results with experiments on two large publicly available video database.