Biodegradable drag reducing agents and flocculants based on polysaccharides: Materials and applications

Organic and inorganic flocculants are used in treatment of water and industrial effluents. Polymeric flocculants, synthetic as well as natural, because of their natural inertness to PH changes, low dosage, and easy handling, have become very popular in industrial effluent treatment. It has been established in the authors' laboratory that by grafting polyacrylamide branches on rigid backbone of polysaccharides, the dangling grafted chains have easy approachability to contaminants in effluents. Thus grafted polysaccharides are very efficient, shear stable and biodegradable flocculants. They also exhibit turbulent drag reducing characteristics. Among grafted guar gum, xanthan gum, carboxymethyl cellulose, and starch, grafted starch performs the best. Starch consists of amylose (a low molecular weight linear polymer) and amylopectin (a high molecular weight, branched polymer). The grafted amylopectin is found to be the best flocculant for various kinds of industrial effluents, providing credibility to the above‐cited model. In the present paper, the details about grafted polysaccharides as turbulent drag reducers and flocculants are given, along with their applications.     

Effect of Structural Changes Induced by Deletion of 54FLRAPSWF61 Sequence in αB-crystallin on Chaperone Function and Anti-Apoptotic Activity

Previously, we showed that the removal of the 54–61 residues from αB-crystallin (αBΔ54–61) results in a fifty percent reduction in the oligomeric mass and a ten-fold increase in chaperone-like activity. In this study, we investigated the oligomeric organization changes in the deletion mutant contributing to the increased chaperone activity and evaluated the cytoprotection properties of the mutant protein using ARPE-19 cells. Trypsin digestion studies revealed that additional tryptic cleavage sites become susceptible in the deletion mutant than in the wild-type protein, suggesting a different subunit organization in the oligomer of the mutant protein. Static and dynamic light scattering analyses of chaperone–substrate complexes showed that the deletion mutant has more significant interaction with the substrates than wild-type protein, resulting in increased binding of the unfolding proteins. Cytotoxicity studies carried out with ARPE-19 cells showed an enhancement in anti-apoptotic activity in αBΔ54–61 as compared with the wild-type protein. The improved anti-apoptotic activity of the mutant is also supported by reduced caspase activation and normalization of the apoptotic cascade components level in cells treated with the deletion mutant. Our study suggests that altered oligomeric assembly with increased substrate affinity could be the basis for the enhanced chaperone function of the αBΔ54–61 protein.     

Support Vector Machines for Automated Recognition of Obstructive Sleep Apnea Syndrome From ECG Recordings

Obstructive sleep apnea syndrome (OSAS) is associated with cardiovascular morbidity as well as excessive daytime sleepiness and poor quality of life. In this study, we apply a machine learning technique [support vector machines (SVMs)] for automated recognition of OSAS types from their nocturnal ECG recordings. A total of 125 sets of nocturnal ECG recordings acquired from normal subjects (OSAS- ) and subjects with OSAS (OSAS+), each of approximately 8 h in duration, were analyzed. Features extracted from successive wavelet coefficient levels after wavelet decomposition of signals due to heart rate variability (HRV) from RR intervals and ECG-derived respiration (EDR) from R waves of QRS amplitudes were used as inputs to the SVMs to recognize OSAS +/- subjects. Using leave-one-out technique, the maximum accuracy of classification for 83 training sets was found to be 100% for SVMs using a subset of selected combination of HRV and EDR features. Independent test results on 42 subjects showed that it correctly recognized 24 out of 26 OSAS + subjects and 15 out of 16 OSAS - subjects (accuracy = 92.85%; Cohen's kappa value of 0.85). For estimating the relative severity of OSAS, the posterior probabilities of SVM outputs were calculated and compared with respective apnea/hypopnea index. These results suggest superior performance of SVMs in OSAS recognition supported by wavelet-based features of ECG. The results demonstrate considerable potential in applying SVMs in an ECG-based screening device that can aid a sleep specialist in the initial assessment of patients with suspected OSAS.     

Shorting strap tunable single feed dual-band PIFA

RF switches are integrated to the shorting straps of a single feed dual-band planar inverted-F antenna (PIFA) to make a tunable PIFA. The L-band switch yields 0.45-dB insertion loss (IL) and 10-dB isolation bandwidth (BW) of 40% at 1.5 GHz. The tunable PIFA yields 39% impedance BW at 900-MHz band and 7.8% BW at 2000-MHz band. The measured radiation patterns are nearly omni-directional and yield a gain of -7.8 dBi at 652 MHz and 4.3 dBi at 2104 MHz.     

Evaluation of Abrasive Wear Resistance of Al<Subscript>2</Subscript>O<Subscript>3</Subscript>/7075 Composite by Taguchi Experimental Design Technique

Two-body abrasive wear resistance of 7075 Al-alloy reinforced with 20 wt% Al₂O₃ particles has been studied with reference to unreinforced base alloy by design of experimental technique. Taguchi L₉ orthogonal array and analysis of variance techniques considering four factors, i.e., load, size of SiC abrasive particle, velocity and sliding distance, each at three different levels, have been employed. The experimental results reveal that wear resistance of composite is far superior than that of the unreinforced base alloy under any given test condition. In general, the most dominating factor is found to be the size of abrasive particle followed by load for both base alloy and composite. The confirmation tests reveal the accuracy level ±?5.52 and ±?6.06% for base alloy and composite, respectively. Mechanism of abrasive wear and the difference of wear response of base alloy and composite are discussed via characterizations of worn surface and generated wear debris.     

Effect of Austenite Conditioning on Martensitic Transformation in Commercial Grade Interstitial-Free Steel

Metallurgical and Materials Transactions A - Martensite is an important phase for the strengthening of interstitial-free (IF) steel. The as-received sample is soaked in the austenitic temperature...     

Bandwidth allocation for communicating virtual machines in cloud data centers

The Journal of Supercomputing - High-performance computing in a cloud environment may require massive data transfer among some of the virtual machines (VMs). These VMs are deployed in physical...     

Microstructural characterization and wear properties of silver and gold nanoparticle doped K-Mg-Al-Si-O-F glass-ceramics

In ascertaining the effects of silver (Ag) and gold (Au) nanoparticles on crystallization of boro-alumino-silicate system; the K₂O-MgO-Al₂O₃-SiO₂-B₂O₃-F glasses doped with/without 0.2?wt% Ag- and Au- content were melt-quenched at 1550?°C. Doping of nanoparticles considerably increased the glass-transition temperature and softening point but decreased the thermal expansion. A sharp crystallization exotherm in differential scanning calorimetry (DSC) is observed at 750?°C (?±?1?°C) for glass without nanoparticle and that broadened to 800–855?°C when contains nanoparticle. Opaque glass-ceramics were derived from the glasses by controlled heat-treatment at 1050?°C with predominant crystalline phase fluorophlogopite (KMg₃AlSi₃O₁₀F₂) mica. Traces of Ag- and Au- particles were also identified from X-ray diffraction (XRD) technique. The activation energy (E_c) of crystallization (344?±?17?kJ/mol) is decreased to 233 (?±?12) and 307 (?±?15) kJ/mol (Kissinger method) on doping with Ag- and Au- nanoparticles, respectively. Compact microstructure (FESEM) composed of rock like and plate-like mica crystals are developed in base glass-ceramic and that gets restructured to interlocked type morphology in presence of Ag- nanoparticle. Significant microstructural change induced by nanoparticle addition caused the decrease in microhardness (4.31–4.66?GPa) and increase in thermal expansion. Friction and wear testing under reciprocative sliding (using WC-Co ball) exposed that the average coefficient of friction (COF) is 0.60?±?0.2 for all glass-ceramics at 20?N load and 10?Hz frequency. At a lower load of 5?N, the average COF value is increased from 0.69 to 0.92 on use of Au-nanoparticle. A Similar trend was also observed at 10?N load as COF increased from 0.62 to 0.78.     

An ACO-based multi-objective optimization for cooperating VM placement in cloud data center

The Journal of Supercomputing - High-performance computing requires numerous virtual machines (VMs) to meet the demand for services of the end-users. Such computation generates high intra-network...     

Estimating rock properties using sound signal dominant frequencies during diamond core drilling operations

In many engineering applications such as mining,geotechnical and petroleum industries,drilling operation is widely used.The drilling operation produces sound by-product,which could be helpful for preliminary estimation of the rock properties.Nevertheless,determination of rock properties is very difficult by the conventional methods in terms of high accuracy,and thus it is expensive and timeconsuming.In this context,a new technique was developed based on the estimation of rock properties using dominant frequencies from sound pressure level generated during diamond core drilling operations.First,sound pressure level was recorded and sound signals of these sound frequencies were analyzed using fast Fourier transform(FFT).Rock drilling experiments were performed on five different types of rock samples using computer numerical control(CNC)drilling machine BMV 45 T20.Using simple linear regression analysis,mathematical equations were developed for various rock properties,i.e.uniaxial compressive strength,Brazilian tensile strength,density,and dominant frequencies of sound pressure level.The developed models can be utilized at early stage of design to predict rock properties.