Enhanced anti-biofilm activity of facile synthesized silver oxide nanoparticles against K. pneumoniae

Journal of Inorganic and Organometallic Polymers and Materials - The silver oxide nanoparticle was successfully synthesized using floral waste by simple one pot, cost effective method. The complete...     

Catalytic properties of dispersed iron oxides Fe2O3/MO2 (M = Zr,Ce, Ti and Si) for sulfuric acid decomposition reaction: Role of support

Supported iron oxides have been established as an important class of catalyst for high temperature sulfuric acid decomposition. With an objective to elucidate the role of support in modifying the overall catalytic properties of dispersed iron oxide catalysts, a series of supported iron oxide based catalysts, Fe₂O₃ (15 wt%)/MO₂ (M = Zr, Ce, Ti and Si), synthesized by adsorption-equilibrium method, is investigated for sulfuric acid decomposition reaction. The structure of dispersed iron oxide phases largely depended on the nature of the support oxide as revealed by the XRD and Mössbauer studies. α-Fe₂O₃ is found to be present as a major phase on ZrO₂ and CeO₂ support while ε-Fe₂O₃ was the major phase on silica supported iron oxide. On the other hand, presence of mixed oxide Fe₂TiO₅ was revealed over TiO₂ support. Strong dispersed metal oxide-support interactions inhibited the total reduction of the dispersed phase on SiO₂ and TiO₂ as compared to complete reduction of dispersed iron oxide on CeO₂ and ZrO₂ supports during temperature programmed reduction upto 1000 °C. The order of catalytic activity at a temperature of ～750 °C is observed as Fe₂O₃/SiO₂ > Fe₂TiO₅/TiO₂ > Fe₂O₃/ZrO₂ > Fe₂O₃/CeO₂, while at higher temperatures of ～900 °C the SO₂ yield is found to be comparable for all catalysts. A relationship between the rate of sulfate decomposition and catalytic activity is established through detailed TG-DTA investigations of sulfated catalyst and support. Considerable influence of the support oxide on the composition, structure, redox properties, morphology and catalytic activities of the active iron oxide dispersed phase has been observed. Thus, the support oxides operate as a critical component in the complex supported metal oxide catalysts and these findings might influence the design and development of future high temperature sulfuric acid decomposition catalysts.     

View Compensated Compression of Volume Rendered Images for Remote Visualization

Remote visualization of volumetric images has gained importance over the past few years in medical and industrial applications. Volume visualization is a computationally intensive process, often requiring hardware acceleration to achieve a real time viewing experience. One remote visualization model that can accomplish this would transmit rendered images from a server, based on viewpoint requests from a client. For constrained server-client bandwidth, an efficient compression scheme is vital for transmitting high quality rendered images. In this paper, we present a new view compensation scheme that utilizes the geometric relationship between viewpoints to exploit the correlation between successive rendered images. The proposed method obviates motion estimation between rendered images, enabling significant reduction to the complexity of a compressor. Additionally, the view compensation scheme, in conjuction with JPEG2000 performs better than AVC, the state of the art video compression standard.     

A vector quantizer for image restoration

This paper presents a novel technique for image restoration based on nonlinear interpolative vector quantization (NLIVQ). The algorithm performs nonlinear restoration of diffraction-limited images concurrently with quantization. It is trained on image pairs consisting of an original image and its diffraction-limited counterpart. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented that demonstrate improvements in visual quality and peak signal-to-noise ratio of the restored images.     

Selective wakeup for parallel forward engines under variable load towards energy conservation in IP routers

Recent studies have shown that a large amount of energy consumption in the communication medium occurs at the data processing plane. The data plane executes the forwarding decisions in the routers and switches. Through initial studies, the line card was identified as the most granular component of the router and later forward engine, a sub component of line card has been recognized as the most power intensive component of routers. Fundamental techniques like link rate adaption, sleep and wake-up have been imposed to reduce the energy at line cards and forward engines. On the other hand, router's architectures undergo drastic changes like empowering data plane with parallel processing due to the rise of gigabit routers. In this paper, to increase the degree of local autonomy and better energy savings, we have adopted the parallel processing design and imposed a variable amount of traffic on different line cards. The existing parallel forward engines perform load balancing in synchronous manner. In our design, asynchronous behavior is imposed such that every line card could independently decide to wake up or turn off their forward engine based on the traffic parameters. We have done simulations and witnessed increased energy savings (average sleeping time) without compromising the completion of lookup process.     

Monte Carlo calculations for efficiency calibration of a whole-body monitor using BOMAB phantoms of different sizes

Internal contamination due to high-energy photon (HEP) emitters is assessed using a scanning bed whole-body monitor housed in a steel room at the Bhabha Atomic Research Centre (BARC). The monitor consists of a (203 mm diameter × 102 mm thickness) NaI(Tl) detector and is calibrated using a Reference BOMAB phantom representative of an average Indian radiation worker. However, a series of different size physical phantoms are required to account for size variability in workers, which is both expensive and time consuming. Therefore, a theoretical approach based on Monte Carlo techniques has been employed to calibrate the system in scanning geometry with BOMAB phantoms of different sizes characterised by their weight (W) and height (H) for several radionuclides of interest ((131)I, (137)Cs, (60)Co and (40)K). A computer program developed for this purpose generates the detector response and the detection efficiencies (DEs) for the BARC Reference phantom (63 kg/168 cm), ICRP Reference male phantom (70 kg/170 cm) and several of its scaled versions. The results obtained for different size phantoms indicated a decreasing trend of DEs with the increase in W/H values of the phantoms. The computed DEs for uniform distribution of (137)Cs in BOMAB phantom varied from 3.52 × 10(-3) to 2.88 × 10(-3) counts per photon as the W/H values increased from 0.26 to 0.50. The theoretical results obtained for the BARC Reference phantom have been verified with experimental measurements. The Monte Carlo results from this study will be useful for in vivo assessment of HEP emitters in radiation workers of different physiques.     

Investigation of thermoelectric generators connected in different configurations for micro‐grid applications

This research work investigates the power‐current (P‐I) and voltage‐current (V‐I) characteristics of the thermoelectric modules (TEMs) in series‐parallel configurations under homogeneous and heterogeneous temperature difference (ΔT) condition. To study its performance, 5 different series‐parallel combinations were formed using 16 TEMs. The comparisons among the different configurations have been done to determine the optimal series‐parallel configuration. The total load power extracted from 16 individually connected TEMs was 18.2 W, which was placed as a reference load power. The optimal series‐parallel combination for maximizing the load power is square series‐parallel configuration, whose maximum load power is 95.5%, compared to the reference load power. Moreover, in square series‐parallel configuration, the total internal resistance value that remains constant is equal to the internal resistance of a single TEM, and the total open‐circuit voltage increases gradually on adding any number of TEMs. Thus, it produces higher load voltage and higher load current simultaneously, which is recommended to power DC micro‐grid applications. Furthermore, the series, parallel, and square series‐parallel configurations are connected as star to obtain 3 separate DC output to power the same application. The performance of TEMs under various configurations is analyzed, and the obtain results are verified experimentally.     

Spatial distribution of oxygen in coals. Development of a tin labelling reaction and Mössbauer studies

All of the hydroxyl groups in Illinois No. 6 and Rawhide (Wyodak) coals have been converted to their-O-SnBu₃ derivatives by reacting with (n-Bu₃Sn)₂0 in refluxing toluene. The Sn Mössbauer spectra of the coal derivatives show that almost all of the tin is trigonal bipyramidal, which requires the presence nearby of a heteroatom for co-ordination to the tin. If this observed geometry occurs in the parent coal, in spite of the large size of the introduced derivatizing group, then the hydroxyl groups of the coal are paired with another heteroatom and most are hydrogen bonded in the solid.     

Adaptive machine learning algorithm employed statistical signal processing for classification of ECG signal and myoelectric signal

Multidimensional Systems and Signal Processing - In this research paper we present designing and evaluating the electrocardiography (ECG) and Myoelectric signal (EMG) pattern recognition methods...     

Wavelet-based compressed sensing using a Gaussian scale mixture model

While initial compressed sensing (CS) recovery techniques operated under the implicit assumption that the sparse domain coefficients are independently distributed, recent results have indicated that integrating a statistical or structural dependence model of sparse domain coefficients into CS enhances recovery. In this paper, we present a method for exploiting empirical dependences among wavelet coefficients during CS recovery using a Bayes least-square Gaussian-scale-mixture model. The proposed model is successfully incorporated into several recent CS algorithms, including reweighted l(1) minimization (RL1), iteratively reweighted least squares, and iterative hard thresholding. Extensive experiments including comparisons with a state-of-the-art model-based CS method demonstrate that the proposed algorithms are highly effective at reducing reconstruction error and/or the number of measurements required for a desired reconstruction quality.