This study compared the performance of the PARTIAL LEAST SQUARES-structural equation modelling (PLS-SEM) and the robust PARTIAL LEAST SQUARES-structural equation modelling (RPLS-SEM) methods through Winsorisation approach The inputs and the outputs used in this model were based on the electricity generation data, derived from the Al-Zawiya Steam Power Plant, Libya. Furthermore, the researchers compared the novel RPLS-SEM approach with the traditional PLS-SEM approach and noted that the novel RPLS-SEM method was more efficient compared to PLS-SEM.

The growth and development of positive psychological approaches in the field of financial resource management have led to transcendental success as a new conceptual basis in the psychology of professions and occupations. This development has fostered a tendency to apply knowledge and skills to achieve financial development and meet job expectations. Moreover, it has the potential to promote the development of ethical financial practices. Certain professions, particularly those with increased responsibilities and accountability, play a significant role in observing the behavior of financial professionals. Deviations from ethical principles in these professions can have serious social consequences. Therefore, the purpose of this study is to investigate the impact of financial pygmalion on the development of financial confidence among financial auditors. The study employs PARTIAL LEAST SQUARES analysis (PLS) and incorporates the opinions of auditors who are members of the auditing organization and private sector auditing firms. The results of this study indicate that financial pygmalion has a positive and significant effect on three dimensions of auditors' financial ethics self-confidence: content understanding of the professional environment, understanding the value of the professional environment, and belonging to the auditors' professional environment. Regenerate response.

People in the society directly and indirectly contribute to air pollution. Therefore, besides being an organizational and governmental responsibility, the participation of individuals in this matter can be significant in air pollution control. Using the developed theory of planning behavior, this study analyzed the behavior of households to decrease air pollution in Kerman City by investigating pollution, vehicles, electricity consumption, green spaces and reused and recycled appliances. The method of this research was quantitative in terms of the nature of data and practical in terms of purpose. The statistical population was all the households living in Kerman City, due to the lack of access to all the households in this research, 384 households were selected from the available sample. The data analysis tool used in this research was structural equations. The results showed that the variable of perceived behavioral control is the main driver of the intention of households to reduce air pollution, followed by the variables of attitude, mental norm, and past behavior had a direct effect on the individual intention of households to reduce air pollution. In order to reduce pollution and increase the health of households and reduce pollutants in this city, it is suggested to use fewer private vehicles and use public vehicles, plant trees and increase green spaces, and cooperate with the government to reduce the production of greenhouse gases.

Iron is an essential element used as supplement in different dosage-forms. Different time and expenditure-consuming methods introduced for detection and determination of elemental ions such as Atomic Absorption Spectroscopy. In this research, two different and routine methods containing ATR-IR and atomic absorption were applied to define the amount of iron in 198 samples containing different concentrations of commercial iron drops and syrups and the output data of the methods was transferred to chemometric model to compare the accuracy and robustness of the methods. By applying this mathematical model, in addition to the confirmation of ATR-IR (a time and energy-saving method) as a replacement of Atomic Absorption Spectroscopy to produce the same results, chemometrical model was used to evaluate the output data in a faster and easier method. At first, ATR-IR spectra data converted to normal matrix by SNV preprocessing approach. Then, a relationship between iron concentrations achieved by AAS and ATR-IR data was established using PLS-LS-SVM. Consequently, model was able to predict ~99% of the samples with low error-values (root mean square-error of cross-validation equal to 0. 98). Y-permutation test performed to confirm that the model was not assessed accidentally. Although, chemometric methods for detection of some heavy metals have been reported in the literature, combination of PLS-LS-SVM with ATR-IR was not cited. In this study a fast and robust method for iron assay was suggested. As a result, ATR-IR can be a suitable method in detection and qualification of iron-content in pharmaceutical dosage forms with less energy-consumption but similar accuracy.

Using the formation constants of 74 charge–transfer complexes in which iodine and iodine monochloride act as acceptors, quantitative structure–property relationships models were developed for predicting these constants for the first time. The procedure was based on reducing a large number of the descriptors based on the variable importance in projection and subsequent selection by stepwise regression and genetic algorithm. The most important variables influencing the charge–transfer interactions were identified and interpreted. Models were obtained by linear methods of multiple linear regression and PARTIAL LEAST SQUARES regression and the nonlinear method of radial basis function–PARTIAL LEAST SQUARES. The best predictions were obtained with the Gaussian radial basis function with s=0.9 and LV=10. The obtained results confirm the capability of the proposed approach to give predictive models for KCT.