Mediating Role of Optimism Bias and Risk Perception Between Emotional Intelligence and Decision-Making: A Serial Mediation Model.

The commodity market plays a vital role in boosting the economy. Investors make decisions based on market knowledge and ignore cognitive biases. These cognitive biases or judgment errors have a significant effect on investment decisions. Therefore, this study aimed to investigate the effect of emotional intelligence on decision-making. In addition, optimism bias and risk perception are the intervening variables between emotional intelligence and decision-making. So, this study contributes to the body of knowledge by examining the mediating role of optimism bias and risk perception. The data were collected from the respondents of the commodity market and the 370 questionnaires were distributed among the investors, of which 337 respondents gave their feedback. The convenience base sampling technique is used due to the easy access of respondents, time factor, and cost factor. Data entered into the SPSS Statistics Version 26 and PROCESS macro model 6 were used for serial mediation. AMOS was used for the validity and model-fit analysis. The results of this study aligned with the literature that there is a significant effect of emotional intelligence on decision-making. It also observed that optimism bias has a positive effect on decision-making. The finding of this study will be helpful for the brokers, the government, and especially the investors. This study also proposed that future studies on the stock exchange and real estate market comparative analysis can be conducted.

In silico annotation of unreviewed acetylcholinesterase (AChE) in some lepidopteran insect pest species reveals the causes of insecticide resistance.

Lepidoptera is the second most diverse insect order outnumbered only by the Coeleptera. Acetylcholinesterase (AChE) is the major target site for insecticides. Extensive use of insecticides, to inhibit the function of this enzyme, have resulted in the development of insecticide resistance. Complete knowledge of the target proteins is very important to know the cause of resistance. Computational annotation of insect acetylcholinesterase can be helpful for the characterization of this important protein. Acetylcholinesterase of fourteen lepidopteran insect pest species was annotated by using different bioinformatics tools. AChE in all the species was hydrophilic and thermostable. All the species showed lower values for instability index except L. orbonalis, S. exigua and T. absoluta. Highest percentage of Arg, Asp, Asn, Gln and Cys were recorded in P. rapae. High percentage of Cys and Gln might be reason for insecticide resistance development in P. rapae. Phylogenetic analysis revealed the AChE in T. absoluta, L. orbonalis and S. exigua are closely related and emerged from same primary branch. Three functional motifs were predicted in eleven species while only two were found in L. orbonalis, S. exigua and T. absoluta. AChE in eleven species followed secretory pathway and have signal peptides. No signal peptides were predicted for S. exigua, L. orbonalis and T. absoluta and follow non secretory pathway. Arginine methylation and cysteine palmotylation was found in all species except S. exigua, L. orbonalis and T. absoluta. Glycosylphosphatidylinositol (GPI) anchor was predicted in only nine species.