With the accelerated pace of society and increasingly fierce competition across various fields, people’s daily stress continues to increase, and anxiety disorders have gradually become a prominent issue in the field of public mental health. Using the psychology work When Panic Attacks: The New, Drug-Free Anxiety Therapy That Can Change Your Life as an example, this paper explores the application of Relevance Theory in the translation of psychotherapy popular science texts. It summarizes the textual features and translation principles of psychotherapy popular science texts, and analyzes the methods and strategies to achieve optimal relevance between the source text and target text on the lexical and syntactic levels, aiming to provide references for future popular science translation practices.

This study analyzes the potential of making Uzbekistan’s taxation system more inclusive by introducing a tax incentive policy related to zakat (obligatory Islamic alms for the wealthy). Additionally, it explores the establishment of relevant institutions to facilitate zakat collection and distribution. The study employs the method of comparative legal research, combined with exploratory research techniques, to examine taxation and zakat systems in different countries. The study’s findings indicate that incorporating zakat incentives, either in the form of tax credits or deductions, into Uzbekistan’s taxation system can enhance the role of zakat institutions in the country’s economy and reduce tax evasion to some extent. Moreover, it proposes a preliminary model of zakat management for Uzbekistan based on conclusions of the comparative study of various countries and analysis of the national legislation. Finally, the research highlights the necessity of a systematic approach to educate the public about zakat obligations, which is crucial for operation of proposed zakat management model and improving compliance. The study provides essential policy recommendations, including the implementation of zakat tax incentives, enhancing public zakat literacy, and ensuring the efficient operation of zakat institutions. By adopting these measures, the government of Uzbekistan can foster a more equitable and effective taxation system, contributing to socioeconomic development and poverty alleviation.

This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.

The present study attempted to assess the impact of fundamental ratios on the share prices of selected telecommunication companies in India. India has dramatically expanded over the past ten years to become the second-biggest telecoms market worldwide, with 1.17 billion users. The Indian telecom industry has proliferated thanks in part to the government of India’s liberal and reformist policies and strong customer demand. It has become a lucrative investment sector for investors due to its recent and prospective growth. Data on 13 telecom firms indexed in the S&P BSE telecommunication index from 2013 to 2022 were taken from companies’ annual reports, the BSE website (Bombay Stock Exchange), and other secondary sources. Six firm-specific fundamental factors viz. Debt to Equity ratio (D/E), Current ratio (CR), Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to earnings ratio (P/E), Return on equity (ROE), and three country-specific fundamental factors viz. Gross Domestic Product, Inflation rate, and S&P BSE Sensex return were considered. Fixed effect panel regression through Generalized Least Square (GLS) model was performed to find inferences. Debt Equity ratio and Inflation rate were found to impact share price negatively. Conversely, the Total Assets Turnover ratio (ATR), Earnings per share (EPS), Price to Earnings ratio (P/E), and Return on Equity (ROE) positively impacted selected companies’ share prices. The study results will benefit individual & institutional investors in formulating their investment and portfolio diversification strategies for gaining a high effective rate of return on their investments.

The purpose of this study was to assess rural students’ computational thinking abilities. The following proofs were observed: (1) Students’ abstraction affected algorithmic thinking skills; (2) Students’ decomposition influenced algorithmic thinking skills; (3) Students’ abstraction impacted evaluation skills; (4) Students’ algorithmic thinking affected evaluation skills; (5) Students’ abstraction impacted generalization skills; (6) Students’ decomposition impacted generalization skills; (7) Students’ evaluation affected generalization skills. Gender differences were observed in the relationship among the computational thinking factors of junior high school students. This included the abstraction-generalization skills; evaluation-generalization skills; and decomposition-generalization skills relationships, which were moderated by the gender of the students. 258 valid surveys were collected, and they were utilized in the study. Conducting the descriptive, reliability, and validity analyses used SPSS software, and the structural equation modeling (SEM) was also conducted through Smart PLS software to assess the hypothetical relationships. There were gender disparities in the correlation among computational thinking components of the junior high school students’ studying in rural areas. Research has shown that male and female students may have different abstractions, evaluations, and generalizations related to computational thinking, with females being more strongly associated than males in non-programming learning contexts. These results are expected to provide relevant information in subsequent analyses and implement a computational thinking curriculum to overcome the still-existing gender gaps and promote computational thinking skills.