Stock market investing is undoubtedly challenging. Investors have to deal with random, vague and ambiguity stock price volatility before embarking on investment decision. Due to these weaknesses, the conventional model has several limitations; as a result investors are demanding for a new robust model which is able to represent their real situation to solve the uncertainty issues. In this study we developed a new fuzzy portfolio selection model using semi-variance as a risk measure integrates with investor’s judgment on assets’ future performance. Linear programming approach was used to optimize the portfolio risk and return. Empirical data showed that the model were able to derive a resourceful portfolio compared to the naïve portfolio selection.
Rough neutrosophic multisets are an improved model of generalization pf neutrosophic multisets represented within the Pawlak’s boundary set of information: lower and upper approximation. The concepts of rough neutrosophic multisets can be easily extended to a relation, mainly since a relation is also a set, i.e. a subset of a Cartesian product. This paper establishes an axiomatic definition of rough neutrosophic multisets relation of Cartesian product over a universal set. Some of the operations and properties of rough neutrosophic multisets, such as max, min, the composition of two rough neutrosophic multisets relation and inverse rough neutrosophic multisets relation, are studied with a proven condition. An algorithm of rough neutrosophic multisets relation is also presented as a step followed to obtain the rough neutrosophic multisets relation. Successful analysis using rough neutrosophic multisets relation theory is represented by the illustrative example of expert opinion about automobile popularity. In conclusion, with a specified condition in uncertainty information, rough neutrosophic multiset relations are generalized in terms of the relation properties of a rough fuzzy relation, rough intuitionistic fuzzy relation, and rough neutrosophic relation over universal. Subsequently, their properties could also be examined.
The proper arrangement of amino acids in a protein determines its proper function, which is vital for the cellular metabolism. This indicates that the process of peptide bond formation requires high fidelity. One of the most important processes for this fidelity is kinetic proofreading. As biochemical experiments suggest that kinetic proofreading plays a major role in ensuring the fidelity of protein synthesis, it is not certain whether or not a misacylated tRNA would be corrected by kinetic proofreading during the peptide bond formation. Using 2-layered ONIOM (QM/MM) computational calculations, we studied the behavior of misacylated tRNAs and compared the results with these for cognate aminoacyl-tRNAs during the process of peptide bond formation to investigate the effect of nonnative amino acids on tRNAs. The difference between the behavior of initiator tRNA(i) (met) compared to the one for the elongator tRNAs indicates that only the initiator tRNA(i) (met) specifies the amino acid side chain.