Grafting vinyl monomers into nylon-6. II. Graft copolymerization of methyl methacrylate onto nylon-6 by hexavalent chromium ion

The feasibility of chromium(VI) to induce graft copolymerization of methyl methacrylate onto nylon-6 was investigated in the presence of nitrogen. The rate of grafting was determined by varying monomer concentration, chromium(VI) concentration, temperature, acidity of the medium, solvents, inorganic salts, and redox system. The graft yield increases significantly by increasing the monomer concentration. The graft yield increases with increase of [Cr(VI)] up to 0.025 mole/liter. With further increase of [Cr(VI)], the graft yield decreases. The increase of acid concentration up to 0.395 mole/liter results the increase in graft yield. Beyond this concentration the graft yield decreases. The graft yield increases with increase in temperature up to 55°C and thereafter it decreases. The graft yield is medium dependent. The graft yield increases with increasing thiourea concentration upto 0.0025 mole/liter but beyond this concentration, the percentage graft yield decreases. A suitable kinetic scheme has been proposed and the rate equation has been evaluated.     

Production of agrochemical from waste polyesters

In this study, agrochemical was produced from waste polyesters. Reactions of waste polyesters [poly (ethylene terephthalate) (PET) and poly (butylene terephthalate) (PBT)] powder with ethylene glycol (EG) in the presence of tetrahydrofurane (THF) using 0.003 mol lead acetate as a catalyst were carried out in a batch reactor at 470 K and at atmospheric pressure conditions. Reactions were undertaken with various particle size ranges from 50 to 512.5 μm, and reaction time from 30 to 70 min for reactions of polyesters. Low molecular weight product of polyester was obtained during this process. In the next stage, hydroxylamine hydrochloride (HAHC), cyclohexylamine (CHA), and potasium hydroxide (KOH) solution were introduced to convert low molecular weight product of polyester into terephthalohydroxamic acid (TPHA) by introduction of HCl (Hydrochloric Acid) as per stoichiometric requirement. TPHA can be used as an agrochemical (insecticide) with appreciable efficiency. To increase the polyester conversion rate, external catalyst (0.003 mol lead acetate) was introduced during the reaction. The product was deposited on the surface of unreacted polyester, which was removed from the surface by introducing dimethyl sulfoxide (DMSO). To accelerate the reaction rate, DMSO, CHA, and THF were introduced during the reaction, which has an industrial significance. Depolymerization of polyester was proportional to the reaction time. Depolymerization of polyester was inversely proportional to the particle size of polyester. Analyses of value‐added product (TPHA) and byproducts [EG and BD (1,4‐butanediol)] as well as polyesters were undertaken. A kinetic model is developed, and experimental data simulated with it, which was consistent with the model. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 2504–2510, 2006     

Design of a password-based authenticated key exchange protocol for SIP

The Session Initiation Protocol (SIP) is a signaling communications protocol, which has been chosen for controlling multimedia communication in 3G mobile networks. In recent years, password-based authenticated key exchange protocols are designed to provide strong authentication for SIP. In this paper, we address this problem in two-party setting where the user and server try to authenticate each other, and establish a session key using a shared password. We aim to propose a secure and anonymous authenticated key exchange protocol, which can achieve security and privacy goal without increasing computation and communication overhead. Through the analysis, we show that the proposed protocol is secure, and has computational and computational overheads comparable to related authentication protocols for SIP using elliptic curve cryptography. The proposed protocol is also provably secure in the random oracle model.     

Bipartite coherent-state quantum key distribution with strong reference pulse

We propose an optical scheme for quantum key distribution in which bits are encoded in relative phases of four bipartite weak coherent states ${|\alpha, \alpha\rangle, |-\alpha, -\alpha\rangle, |-\alpha, \alpha\rangle}$ and ${|\alpha, -\alpha \rangle}$ , with respect to a strong reference pulse. We discuss security of the scheme against eavesdropping strategies like, photon number splitting, photon beam splitting and intercept-resend attacks. It is found that present scheme is more sensitive against these eavesdropping strategies than the two-dimensional non-orthogonal state based protocol and BB84 protocol. Our scheme is very simple, requires only passive optical elements like beam splitters, phase shifters and photon detectors, hence is at the reach of presently available technology.     

Event-triggered control for discrete-time multi-agent average consensus

We consider the average consensus problem for the multi-agent system in the discrete-time domain. Three triggering based control protocols are developed, which dictate the broadcast and control update instants of individual agents to alleviate communication and computational burden. Lyapunov-based design methods prescribe when agents should communicate and update their control so that the network converges to the average of agents' initial states. We start with a static version of the distributed event-triggering law and then generalize it so that it involves an internal auxiliary variable to regulate the threshold dynamically for each agent. The third protocol uses a self-triggering algorithm to avoid continuous listening wherein each agent estimates its next triggering time and broadcasts it to its neighbors at the current triggering time. Numerical simulations are shown to validate the efficacy of the proposed algorithms.     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Studies on microbridges of superconducting YBCO thin film

Critical current densities of the superconducting Y-Ba-Cu-O (YBCO) films have been observed to decrease with the increase of power of microwave radiation. Presence of Josephson type of junctions in the microbridges has been established from the microwave irradiation and magnetic field studies. BCS energy gap parameter (2/kT _c ) has been calculated from thedI/dV characteristics and found to be 3.7 at 13 K.     

An integrated intelligent computing model for the interpretation of EMG based neuromuscular diseases

Intelligent computing system (ICS) and knowledge-based system (KBS) have been widely used in the detection and interpretation of EMG (electromyography) based diseases. Heuristic-based detection methods of EMG parameters for a particular disease have also been reported in the literature but little effort has been made by researchers to combine rule-based reasoning (RBR) and case-based reasoning of KBS, and ANN (artificial neural nets) of ICS. Integrating the methods in KBS and ICS improves the computational and reasoning efficiency of the problem-solving strategy. We have developed an integrated model of CBR and RBR for generating cases, and ANN for matching cases for the interpretation and diagnosis of neuromuscular diseases. We have hierarchically structured the neuromuscular diseases in terms of their physio-pyscho (muscular, cognitive and psychological) parameters and EMG based parameters (amplitude, duration, phase etc.). Cumulative confidence factor is computed at different node from lowest to highest level of hierarchal structure in the process of diagnosis of the neuromuscular diseases. The diseases considered are Duchenne muscular dystrophy, Polymyostits, Endocrine myopathy, Metabolic myopathy, Neuropathy, Poliomyletis and Myasthenia gravis. The basic objective of this work is to develop an integrated model of RBR, CBR and ANN in which RBR is used to hierarchically correlate the sign and symptom of the disease and also to compute cumulative confidence factor (CCF) of the diseases. CBR is used for diagnosing the neuromuscular diseases and to find the relative importance of sign and symptoms of a diseases to other diseases and ANN is used for matching process in CBR.