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Stock price crash risk is a phenomenon in which stock prices are subject to severe negative and sudden adjustments. So far, different approaches have been proposed to model and predict  the  stock price crash risk, which in most cases have been the main emphasis on the factors affecting it, and often traditional methods have been used for prediction. On the other hand, using  Meta Heuristic Algorithms, has led to a lot of research in the field of finance and accounting. Accordingly, the purpose of this research is to model the Stock price crash risk of listed companies in Tehran Stock Exchange using firefly algorithm and compare the results with multivariate regression as a traditional method. Of the companies listed on the stock exchange, 101 companies have been selected as samples. Initially, 19 independent variables were introduced into the model as input property of the particle accumulation algorithm, which was considered as a feature selection method. Finally, in each of the different criteria for calculating the risk Stock price crash risk, some optimal variables were selected, then using firefly algorithm and multivariate regression, the stock price crash risk was  predicted  and results were compared. To quantify the Stock price crash risk, three criteria for negative skewness, high fluctuations and maximum sigma have been used. Two methods of MSE and MAE have been used to compare the methods. The results show that the ability of meta-meta-heuristic methods to predict the risk Stock price crash risk is not  generally higher than the traditional method of multivariate regression, And the research hypothesis was not approved.

Islamophobia’s occurrence in any particular country has little do with the presence of Muslim; it is possible to be Islamophobic when there are virtually no Muslim around. This because the lack of Muslims is filled by the surplus of Islamophobic representations. This surplus of representations is now increasingly reliant on the internet. There are many studies reporting on Islamophobia on the internet, classifying the negative representations, the targeted acts of aggressive online behaviour (trolling) against Muslims. These studies are basically taxonomies, and they share this feature with general literature on Islamophobia, which is concerned with reporting instances of Islamophobia empirically with little time spent on its theorisation. Such an understanding of Islamophobia implies that it is simply dismissed as being a matter of prejudice, bias, and closed views. A Critical Muslim Studies understanding of Islamophobia developed initially in the collected volume Thinking Through Islamophobia (2010), and then subsequent publications shift the focus away positivism to decolonial discourse theory. Using decolonial discourse theory, this study will how online Islamophobia is not just a distortion of Islam, or hatred of Muslims but rather it main vectors for denying Muslim political consciousness.

Nowadays, organizational intelligence is very important in acquiring necessary information for making suitable decisions and gaining competitive benefits in active environments for generative corporations. So, the present study aims to identify and prioritize organizational intelligent criteria in the production cooperatives of Iran. In methodology,this is an applied (developmental) study objectively and a mixed (quantitative-qualitative) survey regarding the nature of data. The present study is a Grounded theory its nature and methodology in the qualitative section, while it is a descriptive-exploratory study in the quantitative section. The study population consists of experts including the managers of the Ministry of Cooperatives, Labor, and Social Welfare, who were 12 respondents selected using the non-probability purposive and snowball sampling techniques. The dimensions of organizational intelligence, including intelligent enablers, organizational intelligent capabilities, intelligent development contexts, and intelligent governance with 18 criteria were identified using the grounded method. Finally, the cause and effect relationships between the dimensions and criteria were determined by the Analytical Network Process method based on the fuzzy DEMATEL. According to DEMATEL findings, the “intelligent governance” and “intelligent development contexts” dimensions are the cause, while the “intelligent enablers” and “organizational intelligent capabilities” constitute the effect. The “customer relationship management”, “organizational learning”, and “human intelligence” criteria have respectively the most weight and priority in the organizational intelligence of production cooperatives in Iran.