Design of a Web Based Underwater Acoustic Communication Testbed and Simulation Platform

Wireless Personal Communications - Underwater Wireless Sensor Networks (UWSNs) are playing a vital role in exploring the unseen underwater (UW) natural resources. However, performance evaluation of...     

Throughput performance of NOMA in WLANs with a CSMA MAC protocol

Wireless Networks - The existing medium access control (MAC) protocols are not able to utilize the full opportunities from power-domain non-orthogonal multiple access (NOMA) technique in wireless...     

Synthesis,characterization and ion exchange properties of zirconium(IV) tungstoiodophosphate,a new cation exchanger

Zirconium(IV) tungstoiodophosphate has been synthesized under a variety of conditions. The most chemically and thermally stable sample is prepared by adding a mixture of aqueous solutions of 0·5 mol L⁻¹ sodium tungstate, potassium iodate and 1 mol L⁻¹ orthophosphoric acid to aqueous solution of 0·1 mol L⁻¹ zirconium(IV) oxychloride. Its ion exchange capacity for Na⁺ and K⁺ was found to be 2·20 and 2·35 meq g⁻¹ dry exchanger, respectively. The material has been characterized on the basis of chemical composition, pH titration, Fourier transform infrared spectroscopy (FTIR) and thermogravimetric analysis. The effect on the exchange capacity of drying the exchanger at different temperatures has been studied. The analytical importance of the material has been established by quantitative separation of Pb²⁺ from other metal ions.     

Method to Characterize the Air Flow and Water Removal Characteristics During Vacuum Dewatering. Part II—Analysis and Characterization

This is part II of a study reported earlier on a method to characterize the air flow and water removal characteristics during vacuum dewatering. This article presents experimental data and analysis of results from the use of a cyclically actuated vacuum dewatering device for removing moisture from wetted porous materials such as paper with the intermittent application of vacuum and accompanying air flow though the material. Results presented include sheet moisture content as a function of residence time and hence water removal rate under a variety of process conditions. Also, experimental results on air flow through the wet porous structure and hence the role and importance of air flow during vacuum dewatering are presented. Vacuum dewatering process conditions include exit solids content between 11 and 20% solid under applied vacuum conditions of 13.5 to 67.7 kPa (4 to 20 in. Hg). Regression analysis indicated that the exit sheet moisture content exhibited a nonlinear relationship with residence time with exit solids reaching a plateau after a certain residence time. Final moisture content correlated linearly with the average overall flow rate of air through the paper sample and the basis weight of the material.     

A finite range failure model

In the present article the characterstics of a finite range failure time distribution, that includes the rectangular distribution as a particular case, are studied. When shape parameter surpass unity then the distribution is IFR otherwise it always remains IFRA. A graphic shape of the distribution is also formed for certain admissible values of the constants.     

Purification and renaturation of recombinant human lymphotoxin (tumour necrosis factor beta) expressed in Escherichia coli as inclusion bodies

High level expression of recombinant human tumour necrosis factor β (rh TNF-β) in Escherichia coli results in the formation of two portions of protein, namely soluble active protein and insoluble protein which is inactive and aggregates in the form of inclusion bodies (IBs). In this study, a procedure for purification and renaturation of rh TNF-β from inclusion bodies has been designed and verified experimentally with a product purity of more than 90% and a recovery of about 30%. The procedure includes washing of IBs with specific wash buffer (Triton X-100/EDTA/lysozyme/PMSF), their solubilization with 8 mol dm^?3 alkaline urea, purification with ion-exchange columns, refolding with renaturation buffer and finally concentration and desalination with an ultrafiltration membrane. The characteristics of the renatured protein were identical with those of purified protein from the soluble fraction as demonstrated by (1) SDS-PAGE, (2) cytotoxic activity on mouse L929 cells, (3) N-terminal amino acid sequence, and (4) gel filtration chromatography.     

Potent and selective bicyclic lactam inhibitors of thrombin: Part 2: P1 modifications

The synthesis and antithrombotic activity of a series of nonpeptide bicyclic thrombin inhibitors is described. We have explored the SAR with modifications to the P1 site. The introduction of arginine mimetics at the P1 site led to potent and selective thrombin inhibitors.     

A novel method for the classification of Alzheimer's disease from normal controls using magnetic resonance imaging

Alzheimer's disease (AD) is the most prevalent form of dementia. Although fewer people, who suffer from AD are correctly and promptly diagnosed, due to a lack of knowledge of its cause and unavailability of treatment, AD is more manageable if the symptoms of mild cognitive impairment (MCI) are in an early stage. In recent years, computer‐aided diagnosis has been widely used for the diagnosis of AD. The main motive of this paper is to improve the classification and prediction accuracy of AD. In this paper, a novel approach is developed to classify MCI, normal control (NC), and AD using structural magnetic resonance imaging (sMRI) from the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset (50 AD, 50 NC, 50 MCI subjects). FreeSurfer is used to process these MRI data and obtain cortical features such as volume, surface area, thickness, white matter (WM), and intrinsic curvature of the brain regions. These features are modified by normalizing each cortical region's features using the absolute maximum value of that region's features from all subjects in each group of MCI, NC, and AD independently. A total of 420 features are obtained. To address the curse of dimensionality, the obtained features are reduced to 30 features using a sequential feature selection technique. Three classifiers, namely the twin support vector machine (TSVM), least squares TSVM (LSTSVM), and robust energy‐based least squares TSVM (RELS‐TSVM), are used to evaluate the classification accuracy from the obtained features. Five‐fold and 10‐fold cross‐validation are used to validate the proposed method. Experimental results show an accuracy of 100% for the studied database. The proposed approach is innovative due to its higher classification accuracy compared to methods in the existing literature.