Structural and thermodynamic consequences of introducing {{alpha}}-aminoisobutyric acid in the S peptide of ribonuclease S

The S protein–S peptide interaction is a model systemto study binding thermodynamics in proteins. We substitutedalanine at position 4 in S peptide by     

A dual-purpose positioner-fixture for precision six-axis positioning and precision fixturing: Part I. Modeling and design

This paper introduces a moving groove fixture which can be operated in two modes; as (1) a precision fixture or (2) a six-axis nanopositioner. Actuators and flexure bearings are integrated within the structural loop of the fixture, thereby enabling controlled changes in fixtured orientation and position while retaining high fixture stiffness. The combination of positioner and fixture characteristics enables one to adjust the fixtured position/orientation and then repeatably fixture about that position/orientation. Models of the fixture's six-axis kinematic characteristics and stiffness were generated and used to design a prototype.     

Numerically efficient solution of dense linear system of equationsarising in a class of electromagnetic scattering problems

In this paper we present an efficient technique for solving a dense complex-symmetric linear system of equations arising in the method of moments (MoM) formulation. To illustrate the application of the method, we consider a finite array of scatterers, which gives rise to a large number of unknowns. The solution procedure utilizes preconditioned transpose-free QMR (PTFQMR) iterations and computes the matrix-vector products by employing a compressed impedance matrix. The compression is achieved by reduced-rank representation of the off-diagonal blocks, based on a partial-QR decomposition, which is followed by an iterative refinement. Both the preconditioning and the compression steps take advantage of the block structure of the matrix. The convergence of the iterative procedure is investigated and the performance of the proposed algorithm is compared to that achieved by other schemes. The effectiveness of the preconditioner and the degree of matrix compression are quantified. Finite arrays of variable shape and sizes are considered, and it is demonstrated that the ability to solve large problems using this technique enables one to evaluate the edge effects in the finite array. Such array is basically flat and periodic, but the algorithm is still efficient when variation with strict periodicity or flatness exists     

Investigations on hard turning with minimal cutting fluid application (HTMF) and its comparison with dry and wet turning

Environmental concerns call for the reduced use of cutting fluids in metal cutting practice. New cutting techniques are to be investigated to achieve this objective. Hard turning with Minimal Fluid application (HTMF) is one such technique, which can alleviate the pollution problems associated with cutting fluids. In the present work a specially formulated cutting fluid was applied as a high velocity, thin pulsed jet at the immediate cutting zones at an extremely low rate of 2 ml/min using a fluid application system developed for this purpose during turning of hardened steel. The performance of HTMF is studied in comparison with that of conventional hard turning in wet and dry form.     

Key issues and challenges in device level fabrication of MEMS acoustic sensors using piezo thin films doped with strontium and lanthanum

The development of next-generation piezoelectric micro-electro-mechanical systems (piezo-MEMS) demands reliable and reproducible processes to fulfil the ever-growing requirements. Research on doped PZT thin films with improved ferroelectric and piezoelectric thin films is on the rise; however, most of them mainly discuss the fabrication process flows and results. This paper attempts to present an overview of some of the key issues and challenges encountered in the device level fabrication of piezo-MEMS acoustic sensors using PZT thin films doped with Strontium and Lanthanum for underwater applications. A recipe on the technical challenges would have saved more time and cost for the researchers as several unsuccessful fabrications and damages were encountered. This paper discusses the issues starting from fabrication of sputtering target to deposition, annealing, patterning and isolation of device layers, electrical contacts, packaging as per the application requirements, etc. in detail.

     

Thermal decomposition as route for silver nanoparticles

Single crystalline silver nanoparticles have been synthesized by thermal decomposition of silver oxalate in water and in ethylene glycol. Polyvinyl alcohol (PVA) was employed as a capping agent. The particles were spherical in shape with size below 10 nm. The chemical reduction of silver oxalate by PVA was also observed. Increase of the polymer concentration led to a decrease in the size of Ag particles. Ag nanoparticle was not formed in the absence of PVA. Antibacterial activity of the Ag colloid was studied by disc diffusion method.     

Joint Estimation of Human Pose and Conversational Groups from Social Scenes

Despite many attempts in the last few years, automatic analysis of social scenes captured by wide-angle camera networks remains a very challenging task due to the low resolution of targets, background clutter and frequent and persistent occlusions. In this paper, we present a novel framework for jointly estimating (i) head, body orientations of targets and (ii) conversational groups called F-formations from social scenes. In contrast to prior works that have (a) exploited the limited range of head and body orientations to jointly learn both, or (b) employed the mutual head (but not body) pose of interactors for deducing F-formations, we propose a weakly-supervised learning algorithm for joint inference. Our algorithm employs body pose as the primary cue for F-formation estimation, and an alternating optimization strategy is proposed to iteratively refine F-formation and pose estimates. We demonstrate the increased efficacy of joint inference over the state-of-the-art via extensive experiments on three social datasets.     

Emerging Solutions in Big Data and Cloud Technologies for Mobile Networks

Mobile Networks and Applications -     

Gaussian-weighted Jensen–Shannon divergence as a robust fitness function for multi-model fitting

Model fitting is a fundamental component in computer vision for salient data selection, feature extraction and data parameterization. Conventional approaches such as the RANSAC family show limitations when dealing with data containing multiple models, high percentage of outliers or sample selection bias, commonly encountered in computer vision applications. In this paper, we present a novel model evaluation function based on Gaussian-weighted Jensen–Shannon divergence, and integrate into a particle swarm optimization (PSO) framework using ring topology. We avoid two problems from which most regression algorithms suffer, namely the requirements to specify inlier noise scale and the number of models. The novel evaluation method is generic and does not require any estimation of inlier noise. The continuous and meta-heuristic exploration facilitates estimation of each individual model while delivering the number of models automatically. Tests on datasets comprised of inlier noise and a large percentage of outliers (more than 90 % of the data) demonstrate that the proposed framework can efficiently estimate multiple models without prior information. Superior performance in terms of processing time and robustness to inlier noise is also demonstrated with respect to state of the art methods.     

Facile Development of Iron-Platinum Nanoparticles to Harness Multifunctionality in Single Entity

Engineered magnetic nanosystems exhibit attractive options for implementing unique diagnostic options and therapeutic solutions in biomedical applications. Here we report a facile, thermo-free and aqueous synthetic method to prepare ascorbic acid-stabilized iron-platinum nanoparticles. The effects of reducing agent, pH and sequence of precursor addition are investigated, and optimized reaction condition is identified to obtain a unique iron-platinum(Pt-FePt)nanosystems. The multifunctionality of the developed nanosystem has been realized by catalytic efficiency of platinum for therapeutic application and superparamagnetic property of Fe Pt for magnetic resonance imaging contrast enhancement.Moreover, the multifunctional imaging and therapeutic activities have been achieved at physiological pH. The developed multifunctional nanoparticles are monodisperse with uniform morphology as well as stable in solution and non-toxic.