On the cholesteryl ester hydrolase activity in the microsomal and supernatant fractions of pigeon aorta

Cholesteryl ester hydrolase activity was measured in the microsomal and supernatant fractions of the aorta of atherosclerosis-susceptible White Carneau and atherosclerosis-resistant Show Racer pigeons while on their normal cholesterol-free diets. Enzyme activities from both fractions showed fatty acid specificities for the hydrolysis of different cholesteryl esters in the following decreasing order: Linoleate greater than oleate greater than palmitate. At 9 months of age (the period of lipid accumulation) the microsomal enzyme activity in the Show Racer breed was significantly higher (P less than 0.001) than in the White Carneau breed, while the supernatant enzyme was slightly higher (P less than 0.05) in the White Carneaux at this age. In older birds (3 years of age) these differences in enzyme activities disappeared.     

An optimal distributed algorithm for recognizing mesh-connected networks

In this paper, we consider the problem of recognizing whether a given network is a rectangular mesh. We present an efficient distributed algorithm with an O(N) message and time complexity, where N is the number of nodes in the network. This is an improvement of a previous algorithm presented in Mohan (1990) with a message complexity of O(N log N) and time complexity of O(N^1.6). The proposed algorithm is constructive in nature and also assigns coordinates to the nodes of the network.     

Deep Learning Enabled Object Detection and Tracking Model for Big Data Environment

Recently, big data becomes evitable due to massive increase in the generation of data in real time application. Presently, object detection and tracking applications becomes popular among research communities and finds useful in different applications namely vehicle navigation, augmented reality, surveillance, etc. This paper introduces an effective deep learning based object tracker using Automated Image Annotation with Inception v2 based Faster RCNN (AIA-IFRCNN) model in big data environment. The AIA-IFRCNN model annotates the images by Discriminative Correlation Filter (DCF) with Channel and Spatial Reliability tracker (CSR), named DCF-CSRT model. The AIA-IFRCNN technique employs Faster RCNN for object detection and tracking, which comprises region proposal network (RPN) and Fast R-CNN. In addition, inception v2 model is applied as a shared convolution neural network (CNN) to generate the feature map. Lastly, softmax layer is applied to perform classification task. The effectiveness of the AIA-IFRCNN method undergoes experimentation against a benchmark dataset and the results are assessed under diverse aspects with maximum detection accuracy of 97.77%.     

Biogenic synthesis of biopolymer‐based Ag–Au bimetallic nanoparticle constructs and their anti‐proliferative assessment

This study reports an eco‐friendly‐based method for the preparation of biopolymer Ag–Au nanoparticles (NPs) by using gum kondagogu (GK; Cochlospermum gossypium), as both reducing and protecting agent. The formation of GK‐(Ag–Au) NPs was confirmed by UV‐absorption, fourier transformed infrared (FTIR), atomic force microscopy (AFM), scanning electron microscope (SEM) and transmission electron microscope (TEM). The GK‐(Ag–Au) NPs were of 1–12 nm in size. The anti‐proliferative activity of nanoparticle constructs was assessed by MTT assay, confocal microscopy, flow cytometry and quantitative real‐time polymerase chain reaction (PCR) techniques. Expression studies revealed up‐regulation of p53, caspase‐3, caspase‐9, peroxisome proliferator‐activated receptors (PPAR) PPARa and PPARb, genes and down‐regulation of Bcl‐2 and Bcl‐x(K) genes, in B16F10 cells treated with GK‐(Ag–Au) NPs confirming the anti‐proliferative properties of the nanoparticles.Inspec keywords: nanomedicine, transmission electron microscopy, genetics, cellular biophysics, molecular biophysics, enzymes, nanofabrication, gold, silver, scanning electron microscopy, nanoparticles, Fourier transform infrared spectra, atomic force microscopy, biomedical materialsOther keywords: size 1.0 nm to 12.0 nm, Ag‐Au, anti‐proliferative assessment, eco‐friendly‐based method, anti‐proliferative activity, anti‐proliferative properties, biopolymer‐based Ag–Au bimetallic nanoparticle, Cochlospermum gossypium, gum kondagogu, biopolymer preparation, biogenic synthesis, UV‐absorption, Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, MTT assay, confocal microscopy, flow cytometry, caspase‐3, caspase‐9, peroxisome proliferator‐activated receptors, Bcl‐2 gene, Bcl‐x(K) gene, B16F10 cells     

Analysis and design of single-phase power factor corrector with genetic algorithm and adaptive neuro-fuzzy-based sliding mode controller using DC–DC SEPIC

This paper proposes a methodology for single-phase power factor correction with DC–DC single-ended primary inductance converter (SEPIC) using cascade control strategy which comprises of genetic algorithm-based outer PI controller and an inner current controller which uses an adaptive neuro-fuzzy inference system-based sliding mode controller. DC–DC SEPIC is a fourth-order converter, and in order to reduce the complexity in controller design, reduced-order model of the original higher-order system is obtained by using Type-I Hankel matrix method. The performance of the proposed system is analysed using MATLAB/Simulink-based simulation studies. In order to ensure the robustness of the proposed controller, the performance parameters such as percentage total harmonic distortion, power factor, % voltage regulation, and % efficiency are analysed. From the simulation results, it is inferred that the proposed method provides efficient tracking of output voltage and effective source current shaping for load, line, and set point variations.

     

Fabrication of nanostructure on a polymer film using atomic force microscope

SPM based lithographic techniques have been developed to pattern various substrates such as metals, semiconductors, and organic/polymer films due to its simplicity and high spatial precision nanostructure. Fabrication of nanostructure using polymeric materials is a key technique for the development of nanodevices. Here, we report the fabrication of nanostructures from polyacrylicacid (PAA) and polymethacrylicacid (PMAA) film on a silicon substrate using atomic force microscope (AFM). The formation of the nanopattern from the polymer film was studied using electrostatic nanolithography and the optimization of the conditions for nanopatterning of the polymer film was investigated with respect to the applied potential and translational speed of the AFM tip. The nanostructure of size 28 nm was created using the biased AFM tip on the PMAA film coated on Si(100) substrate and found that this method is a direct and reliable method to produce uniform nanostructures on a polymer film.     

Effect of Natural Fiber Network on Permeability and Tensile Strength of Composites through Vacuum Infusion Process

This investigation is primarily focused to study the effect of fiber network on the permeability in vacuum infusion molding process. The unsaturated permeability of several natural fiber mats with different networks is measured. The experimental permeabilities are fitted by the Kozeny model and contact angle model. The outcome highlighted that the contact angle model shows more precise results as compared to kozeny model. The obtained permeability for the random fiber mats shows higher values than directional fiber mat. Furthermore, the maximum increase in tensile strength is observed in the unidirectional composites and the flow along the fiber direction.     

Effects of Radio Frequency Heating Treatment on Structure Changes of Soy Protein Isolate for Protein Modification

The effects of radio frequency (RF) heating treatments with different final temperatures (70, 80, and 90 °C) and electrode gaps (120, 160, and 200 mm) on the structural characteristics of soy protein isolate (SPI) dispersion were investigated. The results showed that RF heating significantly influenced free sulfhydryl groups and surface hydrophobicity of SPI. Free sulfhydryl groups increased with the increase of final temperature. The hydrophobicity of the RF-heated sample was higher than the original SPI without RF treatment. The highest hydrophobicity of the RF-heated SPI was found with electrode gap of 200 mm at 90 °C. RF heating treatment resulted in the reduction of ultraviolet absorption of SPI indicating the change of three-dimensional positions of soy protein but did not modify the protein primary structure of SPI. The Fourier transform infrared spectroscopy showed that hydration of SPI was decreased by RF heating. The self-reassembly from random coil structure to β-sheet structure suggested that RF heating treatment can change the secondary structure of soy protein to be more orderly.

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Dynamic predictive model for growth of Salmonella enteritidis in egg yolk

ABSTRACT:  Salmonella Enteritidis (SE) contamination of poultry eggs is a major human health concern worldwide. The risk of SE from shell eggs can be significantly reduced through rapid cooling of eggs after they are laid and their storage under safe temperature conditions. Predictive models for the growth of SE in egg yolk under varying ambient temperature conditions (dynamic) were developed. The growth of SE in egg yolk under several isothermal conditions (10, 15, 20, 25, 30, 35, 37, 39, 41, and 43 °C) was determined. The Baranyi model, a primary model, was fitted with growth data for each temperature and corresponding maximum specific growth rates were estimated. Root mean squared error (RMSE) values were less than 0.44 log₁₀ CFU/g and pseudo- R ² values were greater than 0.98 for the primary model fitting. For developing the secondary model, the estimated maximum specific growth rates were then modeled as a function of temperature using the modified Ratkowsky's equation. The RMSE and pseudo- R ² were 0.05/h and 0.99, respectively. A dynamic model was developed by integrating the primary and secondary models and solving it numerically using the 4th-order Runge–Kutta method to predict the growth of SE in egg yolk under varying temperature conditions. The integrated dynamic model was then validated with 4 temperature profiles (varying) such as linear heating, exponential heating, exponential cooling, and sinusoidal temperatures. The predicted values agreed well with the observed growth data with RMSE values less than 0.29 log₁₀ CFU/g. The developed dynamic model can predict the growth SE in egg yolk under varying temperature profiles.     

Transport architecture evolution in UMTS/IMT‐2000 cellular networks

Mobile evolution from the second generation (2G) to the third generation (3G) raises several important questions for operators and manufacturers. How to ensure that the old and current investments can still be utilized in the future? What is the optimum architecture? ATM or IP? Voice or data? There is no single correct answer to these questions, as it all depends on individual cases. In this paper, we discuss the transport architecture evolution for the universal mobile telecommunications system (UMTS)/international mobile telecommunications—year 2000 (IMT‐2000), or 3G cellular networks and interworking aspects between 2G and 3G cellular networks. The interfaces between access nodes in a cellular network and the changes incorporated to support packet data services are described. Emerging services such as mobile data, virtual private networks (VPN) and location aware networking are described. Role of ATM and IP in this new transport architecture is presented. Control and data plane interworking issues between different transport technologies are described. The new ATM standard, ATM adaptation layer type 2 (AAL2) and its applicability for transporting compressed speech in an ATM based cellular network is described. A similar approach in IP, multiplexing in real‐time transport protocol (RTP) payload to transport compressed speech on selective interfaces of 3G network, is introduced. Transport network architecture evolution within four different scenarios is evaluated. Special interest is focused on the protocol stacks and flexible layered solutions that allow smooth migration from one transport technology to another. Copyright © 2000 John Wiley & Sons, Ltd.