Synthesis and characterization of monometallic rhenium(I) complexes and their application as selective sensors for copper(II) ions

Novel imine functionalized monometallic rhenium(I) polypyridine complexes (1-4) comprising two phenol moieties attached to 2,20-bipyridine ligands L1-L4 have been synthesized and characterized. These complexes exhibit selective and sensitive detection towards copper(II) ions and this is observed through changes in UV-visible absorption, luminescence and time-resolved spectroscopic techniques. An enormous enhancement is observed in emission intensity, quantum yield and luminescence lifetime with the addition of copper(II) ions, and this can be attributed to the restriction of C=N isomerization in the Re(I) complexes. The strong binding between copper(II) ions and these complexes reveals that the binding constant values are in the range of 1.1 x 10(3)-6.0 x 103 M-1. The absorption spectral behavior of the complexes is supported by DFT calculations.

Spectral Zero-Crossings: Localization Properties and Applications

We present an analysis of the rate of sign changes in the discrete Fourier spectrum of a sequence. The sign changes of either the real or imaginary parts of the spectrum are considered, and the rate of sign changes is termed as the spectral zero-crossing rate (SZCR). We show that SZCR carries information pertaining to the locations of transients within the temporal observation window. We show duality with temporal zero-crossing rate analysis by expressing the spectrum of a signal as a sum of sinusoids with random phases. This extension leads to spectral-domain iterative filtering approaches to stabilize the spectral zero-crossing rate and to improve upon the location estimates. The localization properties are compared with group-delay-based localization metrics in a stylized signal setting well-known in speech processing literature. We show applications to epoch estimation in voiced speech signals using the SZCR on the integrated linear prediction residue. The performance of the SZCR-based epoch localization technique is competitive with the state-of-the-art epoch estimation techniques that are based on average pitch period.

A New Successive Displacement Type Load Flow Algorithm and its Application to Radial Systems

A new successive displacement type load flow method is developed in this paper. This algorithm differs from the conventional Y-Bus based Gauss Seidel load flow in that the voltages at each bus is updated in every iteration based on the exact solution of the power balance equation at that node instead of an approximate solution used by the Gauss Seidel method. It turns out that this modified implementation translates into only a marginal improvement in convergence behaviour for obtaining load flow solutions of interconnected systems. However it is demonstrated that the new approach can be adapted with some additional refinements in order to develop an effective load flow solution technique for radial systems. Numerical results considering a number of systems-both interconnected and radial, are provided to validate the proposed approach.

Sampling Period Selection of Control Application Connected to FlexRay Bus

Flexray is a high speed communication protocol designed for distributive control in automotive control applications. Control performance not only depends on the control algorithm but also on the scheduling constraints in communication. A balance between the control performance and communication constraints must required for the choice of the sampling rates of the control loops in a node. In this paper, an optimum sampling period of control loops to minimize the cost function, satisfying the scheduling constraints is obtained. An algorithm to obtain the delay in service of each task in a node of the control loop in the hyper period has been also developed. (C) 2015 The Authors. Published by Elsevier B.V.

An Alternating l(p) - l(2) Projections Algorithm (ALPA) for Speech Modeling using Sparsity Constraints

We address the problem of separating a speech signal into its excitation and vocal-tract filter components, which falls within the framework of blind deconvolution. Typically, the excitation in case of voiced speech is assumed to be sparse and the vocal-tract filter stable. We develop an alternating l(p) - l(2) projections algorithm (ALPA) to perform deconvolution taking into account these constraints. The algorithm is iterative, and alternates between two solution spaces. The initialization is based on the standard linear prediction decomposition of a speech signal into an autoregressive filter and prediction residue. In every iteration, a sparse excitation is estimated by optimizing an l(p)-norm-based cost and the vocal-tract filter is derived as a solution to a standard least-squares minimization problem. We validate the algorithm on voiced segments of natural speech signals and show applications to epoch estimation. We also present comparisons with state-of-the-art techniques and show that ALPA gives a sparser impulse-like excitation, where the impulses directly denote the epochs or instants of significant excitation.

A Split-and-Merge Dictionary Learning Algorithm for Sparse Representation: Application to Image Denoising

In big data image/video analytics, we encounter the problem of learning an over-complete dictionary for sparse representation from a large training dataset, which cannot be processed at once because of storage and computational constraints. To tackle the problem of dictionary learning in such scenarios, we propose an algorithm that exploits the inherent clustered structure of the training data and make use of a divide-and-conquer approach. The fundamental idea behind the algorithm is to partition the training dataset into smaller clusters, and learn local dictionaries for each cluster. Subsequently, the local dictionaries are merged to form a global dictionary. Merging is done by solving another dictionary learning problem on the atoms of the locally trained dictionaries. This algorithm is referred to as the split-and-merge algorithm. We show that the proposed algorithm is efficient in its usage of memory and computational complexity, and performs on par with the standard learning strategy, which operates on the entire data at a time. As an application, we consider the problem of image denoising. We present a comparative analysis of our algorithm with the standard learning techniques that use the entire database at a time, in terms of training and denoising performance. We observe that the split-and-merge algorithm results in a remarkable reduction of training time, without significantly affecting the denoising performance.

An Unbiased Risk Estimator for Multiplicative Noise - Application to 1-D Signal Denoising

The effect of multiplicative noise on a signal when compared with that of additive noise is very large. In this paper, we address the problem of suppressing multiplicative noise in one-dimensional signals. To deal with signals that are corrupted with multiplicative noise, we propose a denoising algorithm based on minimization of an unbiased estimator (MURE) of meansquare error (MSE). We derive an expression for an unbiased estimate of the MSE. The proposed denoising is carried out in wavelet domain (soft thresholding) by considering time-domain MURE. The parameters of thresholding function are obtained by minimizing the unbiased estimator MURE. We show that the parameters for optimal MURE are very close to the optimal parameters considering the oracle MSE. Experiments show that the SNR improvement for the proposed denoising algorithm is competitive with a state-of-the-art method.

Application of principal component analysis to gas sensing characteristics of Cr0.8Fe0.2NbO4 thick film array

The transient changes in resistances of Cr0.8Fe0.2NbO4 thick film sensors towards specified concentrations of H-2, NH3, acetonitrile, acetone, alcohol, cyclohexane and petroleum gas at different operating temperatures were recorded. The analyte-specific characteristics such as slopes of the response and retrace curves, area under the curve and sensitivity deduced from the transient curve of the respective analyte gas have been used to construct a data matrix. Principal component analysis (PCA) was applied to this data and the score plot was obtained. Distinguishing one reducing gas from the other is demonstrated based on this approach, which otherwise is not possible by measuring relative changes in conductivity. This methodology is extended for three Cr0.8Fe0.2NbO4 thick film sensor array operated at different temperatures. (C) 2015 Elsevier B.V. All rights reserved.

An approximation to the QoS aware throughput region of a tree network under IEEE 802.15.4 CSMA/CA with application to wireless sensor network design

In the context of wireless sensor networks, we are motivated by the design of a tree network spanning a set of source nodes that generate packets, a set of additional relay nodes that only forward packets from the sources, and a data sink. We assume that the paths from the sources to the sink have bounded hop count, that the nodes use the IEEE 802.15.4 CSMA/CA for medium access control, and that there are no hidden terminals. In this setting, starting with a set of simple fixed point equations, we derive explicit conditions on the packet generation rates at the sources, so that the tree network approximately provides certain quality of service (QoS) such as end-to-end delivery probability and mean delay. The structures of our conditions provide insight on the dependence of the network performance on the arrival rate vector, and the topological properties of the tree network. Our numerical experiments suggest that our approximations are able to capture a significant part of the QoS aware throughput region (of a tree network), that is adequate for many sensor network applications. Furthermore, for the special case of equal arrival rates, default backoff parameters, and for a range of values of target QoS, we show that among all path-length-bounded trees (spanning a given set of sources and the data sink) that meet the conditions derived in the paper, a shortest path tree achieves the maximum throughput. (C) 2015 Elsevier B.V. All rights reserved.

Tailoring energy absorption capacity of CNT forests through application of electric field

This study examines the effect of electric field on energy absorption capacity of carbon nanotube forests (CNTFs), comprising of vertically aligned multiwalled carbon nanotubes, under both quasistatic (strain rate, (epsilon) over dot = 10(-3) s(-1)) and dynamic ((epsilon) over dot = similar to 10(3) s(-1)) loading conditions. Under quasistatic condition, the CNTFs were cyclically loaded and unloaded while electric field was applied along the length of carbon nanotube (CNT) either throughout the loading cycle or explicitly during either the loading or the unloading segment. The energy absorbed per cycle by CNTF increased monotonically with electric field when the field was applied only during the loading segment: A 7 fold increase in the energy absorption capacity was registered at an electric field of 1 kV/m whereas no significant change in it was noted for other schemes of electro-mechanical loading. The energy absorption capacity of CNTF under dynamic loading condition also increased monotonically with electric field; however, relative to the quasistatic condition, less pronounced effect was observed. This intriguing strain rate dependent effect of electric field on energy absorption capacity of CNTF is explained in terms of electric field induced strengthening of CNTF, originating from the time dependent electric field induced polarization of CNT. (C) 2015 Elsevier Ltd. All rights reserved.

Spectral characterizations and photophysical properties of one-step synthesized blue fluorescent 4 `-aryl substituted 2,2 `:6 `,2 `'-terpyridine for OLEDs application

We have synthesized a series of 4'-aryl substituted 2,2':6',2 `'-terpyridine (terpy) derivatives, namely 4'-(4-methylphenyl)-2,2':6',2 `'-terpyridine (C-1), 4'-(2-furyl)-2,2':6'2 `'-terpyridine (C-2), and 4'-(3,4,5-trimethoxyphenyl)-2,2':6',2 `'-terpyridine (C-3). The synthesized terpy compounds were characterized by elemental analyses, FTIR, NMR (H-1 and C-13), and ESI-Mass spectrometry. Photophysical, electrochemical and thermal properties of terpy compounds were systematically studied. Maximum excitation band was observed between 240 and 330 nm using UV-visible spectra, and maximum emission peaks from PL spectra were observed at 385, 405 and 440 nm for C-1, C-2 and C-3 respectively. Fluorescence lifetime (tau) of the fluorophores was found to be 035 and 1.55 ns at the excitation wavelength of 406 nm for C-1 and C-2 respectively, and tau value for C-3 was found to be 0.29 ns at the excitation wavelength of 468 nm. We noticed that the calculated values of HOMO energy levels were increased from 5.96 (C-1) to 6.08 (C-3) eV, which confirms that C-3 derivative is more electrons donating in nature. The calculated electrochemical band gaps were 2.95, 2.82 and 3.02 eV for C-1, C-2 and C-3 respectively. These blue fluorescent emitter derivatives can be used as an electron transport and electroluminescent material to design the blue fluorescent organic light emitting diode (OLED) applications. (C) 2015 Elsevier B.V: All rights reserved.

Development and Evaluation of Prussian Blue Mediated Glucose Sensor for Reverse Iontophoresis Application

The screen printed electrochemical glucose sensor is developed suitable for revere iontophoresis (RI) application. Glucose oxidase is immobilized on screen printed sensor using crosslinking method. Electrochemical and material characterization studies are conducted on the developed sensor and the obtained results confirm the suitability of the developed sensor for RI application. The developed sensor is validated by conducting clinical investigations on 10 human subjects through RI. A correlation is established between the blood glucose and extracted glucose, and correlation is found to be 0.73. (C) 2015 The Electrochemical Society. All rights reserved.

Air microjet system for non-contact force application and the actuation of micro-structures

We demonstrate a non-contact technique to apply calibrated and localized forces in the micro-Newton to milli-Newton range using an air microjet. An electromagnetically actuated diaphragm controlled by a signal generator is used to generate the air microjet. With a nozzle diameter of 150 mu m, the microjet diameter was maintained to a maximum of 1 mm at a distance of 5 mm from the nozzle. The force generated by the microjet was measured using a commercial force sensor to determine the velocity profile of the jet. Axial flow velocities of up to 25 m s(-1) were obtained at distances as long as 6 mm. The microjet exerted a force up to 1 mu N on a poly dimethyl siloxane (PDMS) micropillar (50 mu m in diameter, 157 mu m in height) and 415 mu N on a PDMS membrane (3 mm in diameter, 28 mu m thick). We also demonstrate that from a distance of 6 mm our microjet can exert a peak pressure of 187 Pa with a total force of about 84 mu N on a flat surface with 8 V operating voltage. Out of the cleanroom fabrication and robust design make this system cost effective and durable.

Synthesis and Photoluminescence Properties of Eu3+ activated Ce0.5Al0.5O2-delta Nanophosphors for WLEDs Application

A series of Eu3+ activated Ce0.5Al0.5O2-delta nanophosphors have been synthesized by the nitrate - citrate gel combustion method. All the compounds crystallized in the cubic fluorite CeO2 structure with space group Fm-3m (No. 225). FESEM revealed the flakes-like morphology. The average particle size was estimated from TEM studies and found to be in the range 15-25 nm. The values were in good agreement with the Scherer's method. In photoluminescence (PL) spectra, the D-5(0) -> F-7(2) (612 nm) transition dominates than other transitions which indicates that the Eu3+ ions occupy a site without inversion center. CIE chromaticity diagram confirmed that these nanophosphors can be useful in the fabrication of red component in white light emitting diodes (WLEDs).