QoS-Aware Optical Fog-Assisted Cyber-Physical System in the 5G Ready Heterogeneous Network

Wireless Personal Communications - In recent years, the emergence of Internet of things and cyber-physical system provide a proactive and efficacious solution to enable remote monitoring, machine...     

A 2-D Analytical Modeling of Dual Work Function Metal Gate MOSFET Using High-K Gate Dielectric with Enhanced RF/Analog Performance for Low Power Applications

A 2-dimensional electrostatic potential modeling of fully depleted channel, with high-k based dual work function double gate (DWFDG) MOSFET, has been devel     

Design of a thermal management system for a battery pack in an electric vehicle using Dymola

As the world moves toward more green and efficient means of modes of transport, electric vehicles are the most suitable and ideal choice to fulfill this requirement. Rapid developments in the field of battery technology are the main reason for their progress, but thermal management in such systems has been an area of concern for a long time. The work undertaken is to design and develop a battery management system (BMS) with a specific focus on the thermal behavior of the battery pack with varying vehicle loads as well as environmental conditions. To design an efficient BMS, one needs to model the battery behavior covering the thermal as well as electrical aspects of the battery. Apart from the battery model, a mathematical model of the electrical vehicle to mimic the various road load conditions for battery also needs to be modeled. Depending on the need for cooling based on battery behavior, the cooling circuit is modeled for the battery pack used. The entire study has been carried out using Dymola, a mathematical modeling software.     

Deep autoencoders for feature learning with embeddings for recommendations: a novel recommender system solution

Neural Computing and Applications - We propose “Deep Autoencoders for Feature Learning in Recommender Systems,” a novel discriminative model based on the incorporation of features from...     

An Exemplar Imidazoline Surfactant for Corrosion Inhibitor Studies: Synthesis,Characterization, and Physicochemical Properties

An optimized one-pot recipe has been developed to synthesize a surfactant molecule, referred to as OMID, consisting of an imidazoline head group and aliphatic tail, which is an exemplar corrosion inhibitor for carbon steel in acidic solutions. As evidenced by gas chromatography, ¹H and ¹³C nuclear magnetic resonance, and Fourier-transform infrared data, a high-purity product was achieved without the use of either a solvent or catalyst. Critical micelle concentration values and corrosion inhibition efficiencies ( η %) were determined in aqueous solutions of hydrochloric acid and sulfuric acid using surface tensiometry and linear polarization resistance measurements, respectively. Hydrolysis of the imidazoline head group as a function of pH (0–11) was explored with ultraviolet–visible absorption spectroscopy. In addition, N 1s and C 1s X-ray photoelectron spectroscopy data were acquired from both surface-adsorbed OMID and a multilayer of the imidazoline head group of OMID. These latter data are highly relevant to those attempting to understand OMID inhibition chemistry.     

PDMS microfluidics: A mini review

Polydimethylsiloxane (PDMS) is hailed as one of the foundational materials for microfluidics. Though a silicone-based elastomer of many desirable properties, the emergence of microfluidic fabrication techniques, especially soft lithography, has elevated its status to an exceptional one. In this mini review, we look at the salient aspects that make PDMS so special in achieving such a coveted status in the microfluidics community. A methodical approach is followed to touch upon the application of PDMS in various aspects of microfluidics with the advantages, limitations, and some future directions. © 2020 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48958.     

The HLD Study of Surfactant Partitioning for Oilfield Corrosion Inhibitors

The partitioning of corrosion inhibitor (CI) products is a measure of their potential to protect oilfield pipelines. In this paper the hydrophilic–lipophilic deviation (HLD) model is first used to quantify their partitioning in terms of the characteristic curvature (C _c,act) of a series of anionic (alkoxylated phosphate esters) and cationic (alkoxylated amines, aromatic amines, imidazoline acetates and quaternary amines) actives. This parameter is expressed over a range of pHs within which pipeline corrosion occurs. The HLD model is next used to predict the partitioning of each active from water into toluene at increased salinities. Linear mixing rules are lastly used to predict the characteristic curvature of Product A (C _c,mix) as a function of the C _c,act of a subset of actives.     

Conformation Analysis of GalNAc‐Appended Sugar Amino Acid Foldamers as Glycopeptide Mimics

Sugar amino acid (SAA)‐based foldamers with well‐defined secondary structures were appended with N‐acetylgalactosamine (GalNAc) sugars to access sequence‐defined, multidentate glycoconjugates with full control over number, spacing and position. Conformation analysis of these glycopeptides by extensive NMR spectroscopic studies revealed that the appended GalNAc units had a profound influence on the native conformational behaviour of the SAA foldamers. Whereas the 2,5‐cis glycoconjugate showed a helical structure in water, comprising of two consecutive 16‐membered hydrogen bonds, its 2,5‐trans congener displayed an unprecedented 16/10‐mixed turn structure not seen before in any glycopeptide foldamer.