Sitananda College

West Bengal, India

Sitananda College

West Bengal, India
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Senapati U.,Belda College | Mandal B.,Sitananda College | Bankura K.P.,Tamralipta Mahavidyalaya
Rasayan Journal of Chemistry | Year: 2017

A detailed study of Cu2+ ion affinities of the amino acids namely Glycine (Gly), Alanine (Ala) and Cysteine (Cys) and their Cu2+ complexes have been investigated using density functional theory. Interactions of a Cu2+ ion with oxygen, nitrogen, and sulfur (for cysteine) of the selected amino acids have been optimized. The results show that complex formation reactions are exothermic in both gas and aqueous phase and the neighboring stereochemical nature of Cu2+ ion is more or less same in all amino acids. The computed Cu2+ affinity for both O-Cu2+ and N-Cu2+ interaction in the gas phase is in this order ΔECys>ΔEAla>ΔEGly. In aqueous phase, Cu2+ ion affinity for O-Cu2+ interaction follows the same order as above, whereas in N-Cu2+ interaction it differs as ΔEAla≥ΔECys>ΔEGly. In NCu2+ interaction Zwitterterionic complexes (Cu2+ bind with both nitrogen and carbonyl oxygen atom) have been formed. The optimization energies are estimated to be lower relative to the other interactions and the Cu2+ ion affinities have been predicted more. The results have been well supported by the natural population analysis (NPA) of the atoms and hardness parameters. The charge, energetics, geometrical and electronic properties of the complexes signify that the interaction between the Cu2+ with the carbonyl oxygen and the amino nitrogen of free amino acids is predominantly a covalent interaction in the gas phase and which becomes more ionic in the aqueous phase. © RASĀYAN. All rights reserved.


Mahata G.C.,Sitananda College
International Journal of Industrial and Systems Engineering | Year: 2015

In this article, we develop a model to determine the economic production run length for a deteriorating production system and allowable shortages in fuzzy random environments. Based on the credibility measure of fuzzy event, the economic production quantity model with fuzzy random elapsed time can be transformed into a crisp model when deriving the expected total cost per unit time. The optimal production run length is proved to exist and be unique. Bounds for the optimal production run length are provided. Furthermore, the bisection method searching for the optimal production run length is designed. The relevant applications of the model are outlined. Finally, a numerical example is given to confirm the proposed model. Copyright © 2015 Inderscience Enterprises Ltd.


In this paper, we investigates the learning effect of the unit production time on optimal lot size for the imperfect production process with partial backlogging of shortage quantity in fuzzy random environments. It is assumed that the setup cost, the average holding cost, the backorder cost, the raw material cost and the labour cost are characterized as fuzzy variables and the elapsed time until the machine shifts from “in-control” state to “out-of-control” state is characterized as a fuzzy random variable. As a function of these parameters, the average total cost is also a random fuzzy variable. Based on the credibility measure of fuzzy event, the fuzzy random total cost function is transformed into an equivalent crisp function. We propose an algorithm to determine the optimal solution. Furthermore, the model is illustrated with the help of numerical example. Finally, sensitivity analysis of the optimal solution with respect to major parameters is carried out. © 2014 Springer Science+Business Media New York

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