Synthesis and characterization of Fe- and Co-based ferrite nanoparticles and study of the T-1 and T-2 relaxivity of chitosan-coated particles

In pursuit of newer and more effective contrast agents for magnetic resonance imaging, we report in this article the use of biocompatible chitosan-coated ferrite nanoparticles of different kinds with a view to determine their potential applications as the contrast agents in the field of nuclear magnetic resonance. The single-phase ferrite particles were synthesized by chemical co-precipitation (CoFe2O4 and Fe3O4) and by applying ultrasonic vibration (CoFe2O4 and Co0.8Zn0.2Fe2O4). Although magnetic anisotropy of CoFe2O4 nanoparticle leads to finite coercivity even for nanoensembles, it has been reduced significantly to a minimum level by applying ultrasonic vibration. Fe3O4 synthesized by chemical co-precipitation yielded particles which already possess negligible coercivity and remanence. Substitution of Co by Zn in CoFe2O4 increases the magnetization significantly with a small increase in coercivity and remanence. Particles synthesized by the application of ultrasonic vibration leads to the higher values of T-2 relaxivities than by chemical coprecipitation. We report that the T-2 relaxivities of these particles are of two orders of magnitude higher than corresponding T-1 relaxivities. Thus, these particles are evidently suitable as contrast agent for T-2 weighted MR images.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Predictability of nonstationary time series using wavelet and EMD based ARMA models

Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology. (C) 2013 Elesvier B.V. All rights reserved.

Comparison of OpAmp based and comparator based switched capacitor filter

Comparator based switched capacitor circuits provide an excellent opportunity to design sampled data systems where the virtual ground condition is detected rather than being continuously forced with negative feedback in Opamp based circuits. This work is an application of this concept to design a 1 st order 330 KHz cutoff frequency Lowpass filter operating at 10 MHz sampling frequency in 0.13μm technology and 1.2 V supply voltage. The Comparator Based Switched Capacitor (CBSC) filter is compared with conventional Two stage Miller compensated Operational amplifier based switched capacitor filter. It is shown that CBSC filter relaxes the constraints like speed ,linearity, gain, stability which would otherwise be hard to satisfy in scaled technologies in Opamp based circuits. The designed CBSC based lowpass filter provides significant power savings compared to traditional Opamp based switched capacitor filter.

Self-assembly of discrete metallamacrocycles employing half-sandwich octahedral diruthenium(II) building units and imidazole-based ligands

Equimolar combination of a series of binuclear half-sandwich p-cymene ruthenium(II) building units Ru-2(mu-eta(4)-C2O4)(MeOH)(2)(eta(6)-p-cymene)(2)](OTf)(2) 1a](OTf)(2), Ru-2(mu-eta(4)-N,N'-diphenyloxamidato)( MeOH)(2)(eta(6)-p-cymene)(2)](OTf)(2) 1b](OTf)(2) and Ru-2(mu-eta(4)-C6H2O4)(MeOH)(2)(eta(6)-p-cymene)(2)](OTf)(2) 1c](OTf)(2) separately with imidazole-based ditopic ligands (L-1-L-2) in methanol yielded a series of tetranuclear metallamacrocycles 2-7](OTf)(4), respectively L-1 = 1,4-bis(imidazole-1-yl)benzene; L-2 = 4,4'-bis(imidazole-1-yl)biphenyl; OTf- = O3SCF3-]. Similarly, the reaction of Ru-2(mu-eta(4)-C2O4)(MeOH)(2)(eta(6)-p-cymene)2](OTf)(2) 1a](OTf)(2) with a triazine-based tritopic ligand 1,3,5-tris(imidazole-1-yl) triazine (L3) in 3: 2 M ratio afforded an unexpected tetranuclear macrocycle 8](OTf)(4) instead of an expected trigonal prismatic cage 8a](OTf)(6). All the self-assembled macrocycles 2-8](OTf)(4) were isolated in moderate to high yields and were fully characterized by multinuclear H-1, F-19] NMR, IR and electrospray ionization mass spectrometry (ESI-MS). In addition, X-ray diffraction study on the single crystals of 3](OTf)(4) and 8](OTf)(4) also indicated the formation 2 + 2] self-assembled macrocycles. Despite the possibility of formation of different conformational isomeric macrocycles (syn-and anti) and polymeric product due to free rotation of ligand sites of imidazole linkers, the selective formation of single conformational isomer (anti) as the only product is quite interesting. Furthermore, the photo-and electrochemical properties of these assemblies have been studied using UV/Vis absorption and cyclic voltammetry analysis. (c) 2013 Elsevier B.V. All rights reserved.

Alumina and Silica based Epoxy Nano-composites for Electrical Insulation

Plain epoxy resins or resin impregnated cellulose have found application as electrical insulation in power equipment. In the past, their performance was improved by the use of inorganic oxide fillers of microscopic dimensions. In the recent past nano-particle doped epoxy insulation came into use with a view to further enhance the dielectric properties. This paper reports dielectric investigations into epoxy nano-composites based on a class of metal oxides, Al2O3 and SiO2. In particular, consideration has been given to the partial discharge performance and electrical breakdown under different voltage profiles as a function of the volumetric composition of the nano-particles in epoxy resin.

Glacial mass balance changes in the Karakoram and Himalaya based on CMIP5 multi-model climate projections

The impact of future climate change on the glaciers in the Karakoram and Himalaya (KH) is investigated using CMIP5 multi-model temperature and precipitation projections, and a relationship between glacial accumulation-area ratio and mass balance developed for the region based on the last 30 to 40 years of observational data. We estimate that the current glacial mass balance (year 2000) for the entire KH region is -6.6 +/- 1 Gta(-1), which decreases about sixfold to -35 +/- 2 Gta(-1) by the 2080s under the high emission scenario of RCP8.5. However, under the low emission scenario of RCP2.6 the glacial mass loss only doubles to -12 +/- 2 Gta(-1) by the 2080s. We also find that 10.6 and 27 % of the glaciers could face `eventual disappearance' by the end of the century under RCP2.6 and RCP8.5 respectively, underscoring the threat to water resources under high emission scenarios.

Biodegradable Mg and Mg based alloys for biomedical implants

Mg and its alloys become natural biomaterials as the elemental Mg is found in the human body in abundance and their mechanical properties being akin to the natural bone as well as due to their inherent bioabsorbable/bioresorbable property. This paper discusses the development of new Mg alloys and their corrosion characteristics in detail. The latest advancements in coating of Mg alloys to control their degradation rate are also reviewed along with the future challenges that need to be addressed.

Synthesis and antiproliferative effect of novel 4-thiazolidinone-, pyridine- and piperazine-based conjugates on human leukemic cells

The present work reveals the synthesis and antiproliferative effect of a series of 2, 3 disubstituted 4-thiazolidinone analogues on human leukemic cells. The chemical structures of newly synthesized compounds were confirmed by IR, H-1 NMR, C-13 NMR and mass spectral analysis. Compound methyl 3-methoxy-4-(4-oxo-3-(5-(piperazin-1-yl)pyridin-2-yl)thiazolidin-2-yl)be nzoate (5) displayed potent activity (IC50 9.71, 15.24 and 19.29 mu M) against Nalm6, K562, Jurkat cells. Cell cycle analysis and mitochondrial membrane potential further confirmed that compound 5 is cytotoxic and able to induce cell death. (C) 2014 Elsevier Masson SAS. All rights reserved.

Carbon nanotubes and graphene-based chemical sensors

The chemical sensing behaviour of the carbon nano-tube and graphene-based sensors for detecting various chemical analytes is presented in this article. A focus on detection mechanisms has been provided to assess their relative potential under different environmental conditions. The performance of these two carbon allotropes is compared based on their sensitivity towards various types of electron donating and accepting molecules. Although these carbon materials still have to meet crucial challenges in fabrication and optimization, continued progress in this field may lead to a sensor with superior sensitivity for a wide range of applications.

Give-and-take based peer-to-peer content distribution networks

Content Distribution Networks (CDNs) are widely used to distribute data to large number of users. Traditionally, content is being replicated among a number of surrogate servers, leading to high operational costs. In this context, Peer-to-Peer (P2P) CDNs have emerged as a viable alternative. An issue of concern in P2P networks is that of free riders, i.e., selfish peers who download files and leave without uploading anything in return. Free riding must be discouraged. In this paper, we propose a criterion, the Give-and-Take (G&T) criterion, that disallows free riders. Incorporating the G&T criterion in our model, we study a problem that arises naturally when a new peer enters the system: viz., the problem of downloading a `universe' of segments, scattered among other peers, at low cost. We analyse this hard problem, and characterize the optimal download cost under the G&T criterion. We propose an optimal algorithm, and provide a sub-optimal algorithm that is nearly optimal, but runs much more quickly; this provides an attractive balance between running time and performance. Finally, we compare the performance of our algorithms with that of a few existing P2P downloading strategies in use. We also study the computation time for prescribing the strategy for initial segment and peer selection for the newly arrived peer for various existing and proposed algorithms, and quantify cost-computation time trade-offs.

Stress states in individual Si particles of a cast Al-Si alloy: Micro-Raman analysis and microstructure based modeling

The stress states in Si particles of cast Al-Si based alloys depend on its morphology and the heat treatment given to the alloy. The Si particles fracture less on modification and fracture more in the heat treated condition. An attempt has been made in this work to study the effect of heat treatment and Si modification on the stress states of the particles. Such understanding will be valuable for predicting the ductility of the alloy. The stress states of Si particles are estimated by Raman technique and compared with the microstructure-based FEM simulations. Combination of Electron Back-Scattered Diffraction (EBSD) and frequency shift, polarized micro-Raman technique is applied to determine the stress states in Si particles with (111) orientations. Stress states are measured in the as-received state and under uniaxial compression. The residual stress, the stress in the elastic-plastic regime and the stress which causes fracture of the particles is estimated by Raman technique. FEM study demonstrates that the stress distribution is uniform in modified Si, whereas the unmodified Si shows higher and more complex stress states. The onset of plastic flow is observed at sharp corners of the particles and is followed by localization of strain between particles. Clustering of particles generates more inhomogeneous plastic strain in the matrix. Particle stress estimated by Raman technique is in agreement with FEM calculations. (C) 2014 Elsevier B.V. All rights reserved.

An Optical How Feature and McFIS Based Approach for 3-Dimensional Human Action Recognition

We propose to develop a 3-D optical flow features based human action recognition system. Optical flow based features are employed here since they can capture the apparent movement in object, by design. Moreover, they can represent information hierarchically from local pixel level to global object level. In this work, 3-D optical flow based features a re extracted by combining the 2-1) optical flow based features with the depth flow features obtained from depth camera. In order to develop an action recognition system, we employ a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). The m of McFIS is to find the decision boundary separating different classes based on their respective optical flow based features. McFIS consists of a neuro-fuzzy inference system (cognitive component) and a self-regulatory learning mechanism (meta-cognitive component). During the supervised learning, self-regulatory learning mechanism monitors the knowledge of the current sample with respect to the existing knowledge in the network and controls the learning by deciding on sample deletion, sample learning or sample reserve strategies. The performance of the proposed action recognition system was evaluated on a proprietary data set consisting of eight subjects. The performance evaluation with standard support vector machine classifier and extreme learning machine indicates improved performance of McFIS is recognizing actions based of 3-D optical flow based features.

ZnO quantum dots and graphene based heterostructure for excellent photoelastic and highly sensitive ultraviolet photodetector

Heterostructures comprised of zinc oxide quantum dots (ZnO QDs) and graphene are presented for ultraviolet photodetectors (UV PD). Graphene-ZnO QDs-graphene (G-ZnO QDs-G) based PD demonstrated an excellent UV photoresponse with outstanding photoelastic characteristics when illuminated for several cycles with a periodicity 5 s. PD demonstrated faster detection ability with the response and recovery times of 0.29 s in response to much lower UV illumination. A direct variation in photoresponse is revealed with the bias voltage as well as UV illumination intensity. A drastic reduction in the dark current is noticed due to potential barrier formation between adjacent ZnO QDs and the recombination rate reduces by directly transferring photogenerated charge carriers from ZnO QDs to graphene for enhanced the charge mobility.

High temperature thermoelectric properties of Zr and Hf based transition metal dichalcogenides: A first principles study

We investigate the electronic and thermal transport properties of bulk MX2 compounds (M = Zr, Hf and X = S, Se) by first-principles calculations and semi-classical Boltzmann transport theory. The band structure shows the confinement of heavy and light bands along the out of plane and in-plane directions, respectively. This results in high electrical conductivity (sigma) and large thermopower leading to a high power factor (S-2 sigma) for moderate n-type doping. The phonon dispersion demonstrates low frequency flat acoustical modes, which results in low group velocities (v(g)). Consequently, lowering the lattice thermal conductivity (kappa(latt)) below 2 W/m K. Low kappa(latt) combined with high power factor results in ZT > 0.8 for all the bulk MX2 compounds at high temperature of 1200 K. In particular, the ZT(max) of HfSe2 exceeds 1 at 1400 K. Our results show that Hf/Zr based dichalcogenides are very promising for high temperature thermoelectric application. (C) 2015 AIP Publishing LLC.