Crystal growth, transport and magnetic properties of rare-earth manganite Pr1-xPbxMnO3

Crystal growth, electrical and magnetic properties are reported for mixed valence manganite Pr1-xPbxMnO3 (x = 0.2, 0.23, and 0.3). The crystals with x = 0.2 and 0.23 are ferromagnetic and insulating, whereas that with x = 0.3 is ferromagnetic below 200 K and shows an insulator-metal transition at 235 K. This composition shows a magnetoresistance of 90% in a field of 5 T. In the paramagnetic region, the temperature dependence of magnetic susceptibility of the crystals follows a Curie-Weiss behavior. The thermal evolution of magnetization in the ferromagnetic phase varies as T-3/2, in accordance with Bloch's law. The spin-stiffness constant D obtained from the Bloch constant is found to increase linearly with x. The magnetization does not reach complete saturation upto a field of 5 T. A possible contribution of the Pr spins to the total magnetic moment is discussed.

4,4′-Bipyridyl complexes of iron: Magnetic, Mössbauer and other spectroscopic studies

4,4prime-Bipyridyl (4,4prime-bipy) complexes of ferrous salts of the Fe(4,4prime-bipy)x(anion)y type (where x or y=1 or 2) and of ferric salts of the Fe(4,4prime-bipy)m(anion)n type (where m=1 or 2 and n=3) have been synthesised. Elemental analyses, i.r. and electronic spectra, magnetic and Mössbauer studies have been performed to characterize the complexes. 4,4prime-Bipy and some anions are inferred to act as bridging ligands. The magnetic moments, electronic and Mössbauer spectra suggest that the complexes are of high spin type with distorted octahedral structures. The value of the isomer shift and quadrupole splitting are discussed in terms of bonding of the ligand and anions.

Magnetic properties of nanostructured ferrimagnetic zinc ferrite

Nanostructured ZnFe2O4 ferrites with different grain sizes were prepared by high energy ball milling for various milling times. Both the average grain size and the root mean square strain were estimated from the x-ray diffraction line broadening. The lattice parameter initially decreases slightly with milling and it increases with further milling. The magnetization is found to increase as the grain size decreases and its large value is attributed to the cation inversion associated with grain size reduction. The Fe-57 Mossbauer spectra were recorded at 300 K and 77 K for the samples with grain sizes of 22 and 11 nm. There is no evidence for the presence of the Fe2+ charge state. At 77 K the Mossbauer spectra consist of a magnetically ordered component along with a doublet due to the superparamagnetic behaviour of small crystalline grains with the superparamagnetic component decreasing with grain size reduction. At 4.2 K the sample with 11 nm grain size displays a magnetically blocked state as revealed by the Mossbauer spectrum. The Mossbauer spectrum of this sample recorded at 10 K in an external magnetic field of 6 T applied parallel to the direction of gamma rays clearly shows ferrimagnetic ordering of the sample. Also, the sample exhibits spin canting with a large canting angle, maybe due to a spin-glass-like surface layer or grain boundary anisotropies in the material.

Lessons from the Sparse Sensor Network Deployment in Rural India

We discuss the key issues in the deployment of sparse sensor networks. The network monitors several environment parameters and is deployed in a semi-arid region for the benefit of small and marginal farmers. We begin by discussing the problems of an existing unreliable 1 sq km sparse network deployed in a village. The proposed solutions are implemented in a new cluster. The new cluster is a reliable 5 sq km network. Our contributions are two fold. Firstly, we describe a. novel methodology to deploy a sparse reliable data gathering sensor network and evaluate the ``safe distance'' or ``reliable'' distance between nodes using propagation models. Secondly, we address the problem of transporting data from rural aggregation servers to urban data centres. This paper tracks our steps in deploying a sensor network in a village,in India, trying to provide better diagnosis for better crop management. Keywords - Rural, Agriculture, CTRS, Sparse.

Optimal Blood Glucose Regulation using Single Network Adaptive Critics

Diabetes is a serious disease during which the body's production and use of insulin is impaired, causing glucose concentration level toincrease in the bloodstream. Regulating blood glucose levels as close to normal as possible, leads to a substantial decrease in long term complications of diabetes. In this paper, an intelligent neural network on-line optimal feedback treatment strategy based on nonlinear optimal control theory is presented for the disease using subcutaneous treatment strategy. A simple mathematical model of the nonlinear dynamics of glucose and insulin interaction in the blood system is considered based on the Bergman's minimal model. A glucose infusion term representing the effect of glucose intake resulting from a meal is introduced into the model equations. The efficiency of the proposed controllers is shown taking random parameters and random initial conditions in presence of physical disturbances like food intake. A comparison study with linear quadratic regulator theory brings Out the advantages of the nonlinear control synthesis approach. Simulation results show that unlike linear optimal control, the proposed on-line continuous infusion strategy never leads to severe hypoglycemia problems.

Evolution of magnetic order in the system LaNi1-xMnxO3 (x < 0.10)

Magnetic susceptibility measurements on dilute solid-solutions LaNi1-xMnxO3 (x < 0.1) have been carried out. With increasing x the magnetic susceptibility behaviour changes from Pauli paramagnetic to Curie-Weiss type. The temperature coefficient of resistance (TCR) changes sign around x = 0.03 but the system seems to be metallic in terms of showing a finite extrapolated conductivity at 0 K even when x = 0.10. The x = 0.10 system shows indications of spin-glass like behaviour.

Synthesis, magnetic and electrical properties of Fe-containing SiO2 nanocomposite

Nanocrystalline Fe powders were synthesized by transmetallation reaction and embedded in silica to form Fe-SiO2 nanocomposite. Thermomagnetic study of the as-prepared Fe sample indicates the presence of Fe3O4 and Fe particles. Oxidation studies of Fe and Fe-SiO2 show an increased thermal stability of Fe-SiO2 nanocomposite over pure Fe. The Fe-SiO2 shows an enhanced oxidation temperature (i.e., 780 K) and a maximum saturation magnetization value of (135 emu/g) with 64 wt.% of Fe content in silica. Electrical and dielectric behaviour of the Fe-SiO2 nanocomposite has been investigated as a function of temperature and frequency. Low frequency ac conductivity and dielectric constants were found to be influenced by desorptions of chemisorbed moisture. High saturation magnetization, thermal stability, frequency-dependent conductivity and low power loss make Fe-silica a promising material for high frequency applications. (C) 2010 Elsevier B.V. All rights reserved.

Reduction in magnetic field induced broadening of the resistive transition in laser‐deposited YBa2Cu3O7−x thin films on MgO

The magnetic field induced broadening of the normal to superconducting resistive transition of YBa2Cu3O7−x thin films laser deposited on (100) MgO substrates for field oriented parallel to the c axis is found to be significantly reduced in comparison with that found previously in single crystals and in films deposited on SrTiO3. This reduction in broadening is associated with a high density of defects which, while causing a slight decrease in Tc and an increase in the zero‐field transition width, seems to provide strong vortex pinning centers that reduce flux creep

Study of magnetic field effect on the specific heat and entropy in DyBa2Cu3O7-x

The change in the specific heat by the application of magnetic field up to 161 for high temperature superconductor system for DyBa2Cu3O7-x by Revaz et al. [23] is examined through the phenomenological Ginzburg-Landau(G-L) theory of anisotropic Type-II superconductors. The observed specific heat anomaly near T-c with magnetic field is explained qualitatively through the expression <Delta C > = (B-a/T-c) t/(1 - t)(alpha Theta(gamma)lambda(2)(m)(0)), which is the anisotropic formulation of the G-L theory in the London limit developed by Kogan and coworkers; relating to the change in specific heat Delta C for the variation of applied magnetic field for different orientations with c-axis. The analysis of this equation explains satisfactorily the specific heat anomaly near T-c and determines the anisotropic ratio gamma as 5.608, which is close to the experimental value 5.3 +/- 0.5given in the paper of Revaz et al. for this system. (C) 2010 Elsevier B.V. All rights reserved.

A comparative study of the magnetic and electrical properties of perovskite oxides and the corresponding two-dimensional oxides of K2NiF4

Electrical and magnetic properties of several oxide systems of K2NiF4 structure have been compared to those of the corresponding perovskites. Members of the La1−xSr1+xCoO4 system are all semiconductors with a high activation energy for conduction unlike La1−xSrxCoO3 (x ≥ 0.3) which is metallic; the latter oxides are ferromagnetic. La0.5Sr1.5CoO4 shows a magnetization of 0.5 μB at 0 K (compared to 1.5 μB of La0.5Sr0.5CoO3), but the high-temperature susceptibilities of the two systems are comparable. In SrO · (La0.5Sr0.5MnO3)n, both magnetization and electrical conductivity increase with the increase in n approaching the value of the perovskite La0.5Sr0.5MnO3. LaSrMn0.5Ni0.5(Co0.5)O4 shows no evidence of long-range ferromagnetic ordering unlike the perovskite LaMn0.5Ni0.5(Co0.5)O3; high-temperature susceptibility behavior of these two insulating systems is, however, similar. LaSr1−xBaxNiO4 exhibits high electrical resistivity with the resistivity increasing proportionately with the magnetic susceptibility (note that LaNiO3 is a Pauli-paramagnetic metal). High-temperature susceptibility of LaSrNiO4 and LaNiO3 are comparable. Susceptibility measurements show no evidence for long-range ordering in LaSrFe1−xNixO4 unlike in LaFe1−xNixO3 (x ≤ 0.35) and the electrical resistivity of the former is considerably higher. Electrical resistivity of Sr2RuO4 is more than an order of magnitude higher than that of SrRuO3. Some generalizations of the properties of two- and three-dimensional oxide systems have emerged from these experimental observations.

Structural and magnetic properties of Sr2Fe1+xMo1-xO6 (-1 <= x <= 0.25)

We have synthesized the solid solution Sr2Fe1+xMo1-xO6 with -1 <= x <= 0.25, the composition x=0 corresponding to the well-known double-perovskite system Sr2FeMoO6. We report structural and magnetic properties of the above system, exhibiting systematic variations across the series. These results restrict the range of models that can explain magnetism in this family of compounds, providing an understanding of the magnetic structure.

Effect of network connectivity on thermal properties of As30Te70-xTlx glasses

Alternating differential scanning calorimetry (ADSC) studies were undertaken to investigate the effect of Tl addition on the thermal properties of As30Te70-xTlx ( 6 <= x <= 22 at%) glasses. These include parameters such as glass-transition temperature (T-g), changes in specific heat capacity (Delta C-p) and relaxation enthalpy (Delta H-NR) at the glass transition. It was found that T-g of the glasses decreased with the addition of Tl, which is in contrast to the dependence of T-g in As - Te glasses on the addition of Al and In. The change in heat capacity Delta C-p through the glass transition was also found to decrease with increasing Tl content. The addition of Tl to the As - Te matrix may lead to a breaking of As - Te chains and the formation of Tl+Te- AsTe2/2 dipoles. There was no significant dependence of the change of relaxation enthalpy, through the glass transition, with composition.

Multiple contour extraction from graylevel images using an artificial neural network

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of ail edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.

Transport and magnetic properties of conducting polyaniline doped with BX3 (X=F, Cl, and Br)

We report transport and magnetic properties of a different class of highly conducting polyaniline, doped with boron trihalides BX3 (X=F, Cl, and Br). In order to understand the transport mechanism we analyze the temperature dependence of resistivity of a large number of samples, made by pelletizing doped polyaniline powder and by doping films of polyaniline. We find that the charge transport in this class of conducting polyaniline is driven by the charging-energy limited transport of charge carriers, in contrast to the quasi-one-dimensional variable range hopping conduction prevalent in conventional proton-doped polyaniline samples. Magnetic susceptibility provides further insight into the unusually high intrinsic conductivity behavior.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.