Improved ferroelectric and leakage properties in symmetric BiFeO3/SrTiO3 superlattice

Symmetric BiFeO3/SrTiO3 superlattices were fabricated by pulsed laser deposition on SrTiO3 (100) substrates. Frequency independent and near saturated P-E hysteresis was observed in the case of a superlattice (periodicity of ∼ 11 nm) as compared to leaky hysteresis observed in epitaxial BiFeO3. Room temperature leakage current density of the superlattice was almost two orders of magnitude lower than that of BiFeO3. Observed leakage current behavior in case of both BiFeO3 and superlattice indicates the dominance of space charge limited conduction. Improvement in ferroelectric property was discussed in connection to enhanced epitaxial strain, reduced leakage current, and electrostatic interaction between BiFeO3 and SrTiO3.

Improved microwave dielectric properties of (Mg1-(x+y)CaxLay)(Ti1-yAly)O3 ceramics

Phase-singular solids of the composition, (Mg1−(x+y) Cax Lay)(Ti1−yAly)O3 (x = 0 to 0.88; y = 0.05 to 0.35) having the cubic perovskite-type structure were prepared by the substitution of La3+ and Al3+ in equivalent quantities which brought about complete miscibility between MgTiO3 and CaTiO3. These ceramics showed relative permittivities of 16.5 to 50 (at 6 GHz) with increasing Ca content, high Q values of 10 000 to 30 000 and retained near-zero temperature coefficients in permittivity at optimum y values. Their dielectric characteristics are better accountable in terms of the positional disorder rather than the tolerance factor of perovskite structure.

Hybrid Bayesian Classifier for Improved Classification Accuracy

The widely used Bayesian classifier is based on the assumption of equal prior probabilities for all the classes. However, inclusion of equal prior probabilities may not guarantee high classification accuracy for the individual classes. Here, we propose a novel technique-Hybrid Bayesian Classifier (HBC)-where the class prior probabilities are determined by unmixing a supplemental low spatial-high spectral resolution multispectral (MS) data that are assigned to every pixel in a high spatial-low spectral resolution MS data in Bayesian classification. This is demonstrated with two separate experiments-first, class abundances are estimated per pixel by unmixing Moderate Resolution Imaging Spectroradiometer data to be used as prior probabilities, while posterior probabilities are determined from the training data obtained from ground. These have been used for classifying the Indian Remote Sensing Satellite LISS-III MS data through Bayesian classifier. In the second experiment, abundances obtained by unmixing Landsat Enhanced Thematic Mapper Plus are used as priors, and posterior probabilities are determined from the ground data to classify IKONOS MS images through Bayesian classifier. The results indicated that HBC systematically exploited the information from two image sources, improving the overall accuracy of LISS-III MS classification by 6% and IKONOS MS classification by 9%. Inclusion of prior probabilities increased the average producer's and user's accuracies by 5.5% and 6.5% in case of LISS-III MS with six classes and 12.5% and 5.4% in IKONOS MS for five classes considered.

CNT loading into cationic cholesterol suspensions show improved DNA binding and serum stability and ability to internalize into cancer cells

Methods which disperse single-walled carbon nanotubes (SWNTs) in water as `debundled', while maintaining their unique physical properties are highly useful. We present here a family of cationic cholesterol compounds (Chol(+)) {Cholest-5en-3 beta-oxyethyl pyridinium bromide (Chol-PB+), Cholest-5en-3 beta-oxyethyl N-methyl pyrrolidinium bromide (Chol-MPB+), Cholest-5en-3 beta-oxyethyl N-methyl morpholinium bromide (Chol-MMB+) and Cholest-5en-3 beta-oxyethyl diazabicyclo octanium bromide (Chol-DOB+)}. Each of these could be easily dispersed in water. The resulting cationic cholesterol (Chol(+)) suspensions solubilized single-walled carbon nanotubes (SWCNTs) by the non-specific physical adsorption of Chol(+) to form stable, transparent, dark aqueous suspensions at room temperature. Electron microscopy reveals the existence of highly segregated CNTs in these samples. Zeta potential measurements showed an increase in potential of cationic cholesterol aggregates on addition of CNTs. The CNT-Chol(+) suspensions were capable of forming stable complexes with genes (DNA) efficiently. The release of double-helical DNA from such CNT-Chol(+) complexes could be induced upon the addition of anionic micellar solution of SDS. Furthermore, the CNT-based DNA complexes containing cationic cholesterol aggregates showed higher stability in fetal bovine serum media at physiological conditions. Confocal studies confirm that CNT-Chol(+) formulations adhere to HeLa cell surfaces and get internalized more efficiently than the cationic cholesterol suspensions alone (devoid of any CNTs). These cationic cholesterol-CNT suspensions therefore appear to be a promising system for further use in biological applications.

Font and Size Independent OCR for Printed Kannada Documents using SVM Classifiers

The following topics were dealt with: document analysis and recognition; multimedia document processing; character recognition; document image processing; cheque processing; form processing; music processing; document segmentation; electronic documents; character classification; handwritten character recognition; information retrieval; postal automation; font recognition; Indian language OCR; handwriting recognition; performance evaluation; graphics recognition; oriental character recognition; and word recognition

Improved algorithm for optimum reactive power allocation

An improvised algorithm is presented for optimal VAr allocation in a large power system using a linear programming technique. The proposed method requires less computer memory than those algorithms currently available.

Fuzzy Expert Approach with Curtailed Controllers for Improved Reactive Power Dispatch

This paper addresses the problem of curtailing the number of control actions using fuzzy expert approach for voltage/reactive power dispatch. It presents an approach using fuzzy set theory for reactive power control with the purpose of improving the voltage profile of a power system. To minimize the voltage deviations from pre-desired values of all the load buses, using the sensitivities with respect to reactive power control variables form the basis of the proposed Fuzzy Logic Control (FLC). Control variables considered are switchable VAR compensators, On Load Tap Changing (OLTC) transformers and generator excitations. Voltage deviations and controlling variables are translated into fuzzy set notations to formulate the relation between voltage deviations and controlling ability of controlling devices. The developed fuzzy system is tested on a few simulated practical Indian power systems and modified IEEE-30 bus system. The performance of the fuzzy system is compared with conventional optimization technique and results obtained are encouraging. Results obtained for a modified IEEE-30 bus test system and a 205-node equivalent EHV system a part of Indian southern grid are presented for illustration purposes. The proposed fuzzy-expert technique is found suitable for on-line applications in energy control centre as the solution is obtained fast with significant speedups with few number of controllers.

Determination of alpha(s)(M-tau(2)) from improved fixed order perturbation theory

We revisit the extraction of alpha(s)(M-tau(2)) from the QCD perturbative corrections to the hadronic tau branching ratio, using an improved fixed-order perturbation theory based on the explicit summation of all renormalization-group accessible logarithms, proposed some time ago in the literature. In this approach, the powers of the coupling in the expansion of the QCD Adler function are multiplied by a set of functions D-n, which depend themselves on the coupling and can be written in a closed form by iteratively solving a sequence of differential equations. We find that the new expansion has an improved behavior in the complex energy plane compared to that of the standard fixed-order perturbation theory (FOPT), and is similar but not identical to the contour-improved perturbation theory (CIPT). With five terms in the perturbative expansion we obtain in the (MS) over bar scheme alpha(s)(M-tau(2)) = 0.338 +/- 0.010, using as input a precise value for the perturbative contribution to the hadronic width of the tau lepton reported recently in the literature.

Robust solver based on modified particle swarm optimization for improved solution of diffusion transport through containment facilities

Accurate estimation of mass transport parameters is necessary for overall design and evaluation processes of the waste disposal facilities. The mass transport parameters, such as effective diffusion coefficient, retardation factor and diffusion accessible porosity, are estimated from observed diffusion data by inverse analysis. Recently, particle swarm optimization (PSO) algorithm has been used to develop inverse model for estimating these parameters that alleviated existing limitations in the inverse analysis. However, PSO solver yields different solutions in successive runs because of the stochastic nature of the algorithm and also because of the presence of multiple optimum solutions. Thus the estimated mean solution from independent runs is significantly different from the best solution. In this paper, two variants of the PSO algorithms are proposed to improve the performance of the inverse analysis. The proposed algorithms use perturbation equation for the gbest particle to gain information around gbest region on the search space and catfish particles in alternative iterations to improve exploration capabilities. Performance comparison of developed solvers on synthetic test data for two different diffusion problems reveals that one of the proposed solvers, CPPSO, significantly improves overall performance with improved best, worst and mean fitness values. The developed solver is further used to estimate transport parameters from 12 sets of experimentally observed diffusion data obtained from three diffusion problems and compared with published values from the literature. The proposed solver is quick, simple and robust on different diffusion problems. (C) 2012 Elsevier Ltd. All rights reserved.

Detailed investigation of a gamma-cyclodextrin inclusion complex with L-thyroxine for improved pharmaceutical formulations

Thyroxine is a naturally occurring human hormone produced by the thyroid gland. Clinical applications of thyroxine to treat several chronic disorders are limited by poor water solubility and instability under physiological conditions. An inclusion complex of levo-thyroxine (l-thyroxine), the active form of the hormone with gamma cyclodextrin (gamma-CD) has been obtained and studied with the aim of improving oral delivery rather than the injection formulation of the sodium salt. In addition to greater patient acceptability, inclusion complexes often improve aqueous solubility and bioavailability, stability, and reduce toxicity of drugs, thus providing enhanced pharmaceutical formulations. Physicochemical characterization of the inclusion complex was carried out using Fourier transform infrared spectroscopy, X-ray diffractometry, differential scanning calorimetry, scanning electron microscopy and proton nuclear magnetic resonance spectroscopy. Intermolecular dipolar interactions for the inclusion complex were also studied using 2 dimensional ROESY experiments. Formation of the inclusion complex between the protons H3 and H5 of cyclodextrin with aromatic protons of thyroxine was confirmed by their dipolar interaction. Molecular modelling was used to understand the basis for the complex formation and predict the formation of other complexes. Interestingly, we found that l-thyroxine forms an inclusion complex only with the larger gamma-CD and not with other available alpha and beta forms.

Spatial Filter Based Bessel-Like Beam for Improved Penetration Depth Imaging in Fluorescence Microscopy

Monitoring and visualizing specimens at a large penetration depth is a challenge. At depths of hundreds of microns, several physical effects (such as, scattering, PSF distortion and noise) deteriorate the image quality and prohibit a detailed study of key biological phenomena. In this study, we use a Bessel-like beam in-conjugation with an orthogonal detection system to achieve depth imaging. A Bessel-like penetrating diffractionless beam is generated by engineering the back-aperture of the excitation objective. The proposed excitation scheme allows continuous scanning by simply translating the detection PSF. This type of imaging system is beneficial for obtaining depth information from any desired specimen layer, including nano-particle tracking in thick tissue. As demonstrated by imaging the fluorescent polymer-tagged-CaCO3 particles and yeast cells in a tissue-like gel-matrix, the system offers a penetration depth that extends up to 650 mu m. This achievement will advance the field of fluorescence imaging and deep nano-particle tracking.

Recapitulating tumour microenvironment in chitosan-gelatin three-dimensional scaffolds: an improved in vitro tumour model

Owing to the reduced co-relationship between conventional flat Petri dish culture (two-dimensional) and the tumour microenvironment, there has been a shift towards three-dimensional culture systems that show an improved analogy to the same. In this work, an extracellular matrix (ECM)-mimicking three-dimensional scaffold based on chitosan and gelatin was fabricated and explored for its potential as a tumour model for lung cancer. It was demonstrated that the chitosan-gelatin (CG) scaffolds supported the formation of tumoroids that were similar to tumours grown in vivo for factors involved in tumour-cell-ECM interaction, invasion and metastasis, and response to anti-cancer drugs. On the other hand, the two-dimensional Petri dish surfaces did not demonstrate gene-expression profiles similar to tumours grown in vivo. Further, the three-dimensional CG scaffolds supported the formation of tumoroids, using other types of cancer cells such as breast, cervix and bone, indicating a possible wider potential for in vitro tumoroid generation. Overall, the results demonstrated that CG scaffolds can be an improved in vitro tool to study cancer progression and drug screening for solid tumours.

Perturbative expansion of the QCD Adler function improved by renormalization-group summation and analytic continuation in the Borel plane

We examine the large-order behavior of a recently proposed renormalization-group-improved expansion of the Adler function in perturbative QCD, which sums in an analytically closed form the leading logarithms accessible from renormalization-group invariance. The expansion is first written as an effective series in powers of the one-loop coupling, and its leading singularities in the Borel plane are shown to be identical to those of the standard ``contour-improved'' expansion. Applying the technique of conformal mappings for the analytic continuation in the Borel plane, we define a class of improved expansions, which implement both the renormalization-group invariance and the knowledge about the large-order behavior of the series. Detailed numerical studies of specific models for the Adler function indicate that the new expansions have remarkable convergence properties up to high orders. Using these expansions for the determination of the strong coupling from the hadronic width of the tau lepton we obtain, with a conservative estimate of the uncertainty due to the nonperturbative corrections, alpha(s)(M-tau(2)) = 0.3189(-0.0151)(+0.0173), which translates to alpha(s)(M-Z(2)) = 0.1184(-0.0018)(+0.0021). DOI: 10.1103/PhysRevD.87.014008

A hybrid RTS-BP algorithm for improved detection of large-MIMO M-QAM signals

Low-complexity near-optimal detection of large-MIMO signals has attracted recent research. Recently, we proposed a local neighborhood search algorithm, namely reactive tabu search (RTS) algorithm, as well as a factor-graph based belief propagation (BP) algorithm for low-complexity large-MIMO detection. The motivation for the present work arises from the following two observations on the above two algorithms: i) Although RTS achieved close to optimal performance for 4-QAM in large dimensions, significant performance improvement was still possible for higher-order QAM (e.g., 16-, 64-QAM). ii) BP also achieved near-optimal performance for large dimensions, but only for {±1} alphabet. In this paper, we improve the large-MIMO detection performance of higher-order QAM signals by using a hybrid algorithm that employs RTS and BP. In particular, motivated by the observation that when a detection error occurs at the RTS output, the least significant bits (LSB) of the symbols are mostly in error, we propose to first reconstruct and cancel the interference due to bits other than LSBs at the RTS output and feed the interference cancelled received signal to the BP algorithm to improve the reliability of the LSBs. The output of the BP is then fed back to RTS for the next iteration. Simulation results show that the proposed algorithm performs better than the RTS algorithm, and semi-definite relaxation (SDR) and Gaussian tree approximation (GTA) algorithms.