The current examines the influence of Islamic values on smoking behaviors among undergraduate students at Yarmouk University in Irbid, Jordan (N: 334). Tobacco use, in religious and cultural terms, is viewed as abhorrent; it is a significant concern for this population group. The study intends to identify how Islamic values affect the perception of students on smoking and, consequently, their smoking behavior. A self-administered questionnaire assessed sociodemographic data and the past 30 days of cigarette use. Descriptive statistics, such as frequencies and percentages, midpoint and standard deviation, and inferential statistics, such as chi-square tests, t-tests, ANOVA, Pearson correlation, and hierarchical regression, were used to analyze smoking behaviors, Islamic values, and demographic attributes. The study shows that Islamic values have a strong negative attitude towards smoking; students attributed smoking to religion, family and social expectations and perceptions, health and economic implications. Further, the hierarchical regression analysis revealed that cigarette use, hookah and e-cigarette, gender, and attitude towards Islamic values were suitable predictors for cigarette use. This study advances knowledge regarding smoking behaviors from the cultural-religious perspective. It highlights the importance of historically and culturally informed gender-sensitive prevention programs that address smoking-related beliefs, attitudes, and practices. Collaboration with the Ministry of Health and media outlets to integrate Islamic values into public health campaigns can reduce smoking among university students by aligning cultural and religious beliefs with health messaging.

With the advent of the big data era, the amount of various types of data is growing exponentially. Technologies such as big data, cloud computing, and artificial intelligence have achieved unprecedented development speed, and countries, regions, and multiple fields have included big data technology in their key development strategies. Big data technology has been widely applied in various aspects of society and has achieved significant results. Using data to speak, analyze, manage, make decisions, and innovate has become the development direction of various fields in society. Taxation is the main form of China’s fiscal revenue, playing an important role in improving the national economic structure and regulating income distribution, and is the fundamental guarantee for promoting social development. Re examining the tax administration of tax authorities in the context of big data can achieve efficient and reasonable application of big data technology in tax administration, and better serve tax administration. Big data technology has the characteristics of scale, diversity, and speed. The effect of tax big data on tax collection and management is becoming increasingly prominent, gradually forming a new tax collection and management system driven by tax big data. The key research content of this article is how to organically combine big data technology with tax management, how to fully leverage the advantages of big data, and how to solve the problems of insufficient application of big data technology, lack of data security guarantee, and shortage of big data application talents in tax authorities when applying big data to tax management.

To achieve the energy transition and carbon neutrality targets, governments have implemented multiple policies to incentivize electricity suppliers to invest in renewable energy. Considering different government policies, we construct a renewable energy supply chain consisting of electricity suppliers and electricity retailers. We then explore the impact of four policies on electricity suppliers’ renewable energy investments, environmental impacts, and social welfare. We validated the results based on data from Wuxi, Jiangsu Province, China. The results show that government subsidy policies are more effective in promoting electricity suppliers to invest in renewable energy as consumer preferences increase, while no-government policies are the least effective. We also show that electricity suppliers are most profitable under the government subsidy policy and least profitable under the carbon cap-and-trade policy. Besides, our results indicate that social welfare is the worst under the carbon cap-and-trade policy. With the increase in carbon intensity and renewable energy quota, social welfare is the highest under the subsidy policy. However, the social welfare under the renewable energy portfolio standard is optimal when the renewable energy quota is low.

Urbanization process affects global socio-economic development. Originally tied to modernization and industrialization, current urbanization policy is focused on productivity, economic activities, and environmental sustainability. This study examines impact of urbanization in various regions of Kazakhstan, focusing on environmental, social, labor, industrial, and economic indicators. The study aims to assess how different indicators influence urbanization trends in Kazakhstan, particularly regarding environmental emissions and pollution. It delves into regional development patterns and identifies key contributing factors. The research methodology is based on classical economic theories of urbanization and modern interpretations emphasizing sustainability and socio-economic impacts and includes two stages. Shannon entropy measures diversity and uncertainty in urbanization indicators, while cluster analysis identifies regional patterns. Data from 2010 to 2022 for 17 regions forms the basis of analysis. Regions are categorized into groups based on urbanization levels leaders, challenged, stable, and outliers. This classification reveals disparities in urban development and its impacts. Findings stress the importance of integrating environmental and social considerations into urban planning and policies. Targeted interventions based on regional characteristics and urbanization levels are recommended to enhance sustainability and socio-economic outcomes. Tailored urban policies accommodating specific regional needs are crucial. Effective management and policy-making demand a nuanced understanding of these impacts, emphasizing region-specific strategies over a uniform approach.

A new method has been proposed to estimate top heat losses of vertical flat plate liquid/air collectors with double glazing. Empirical relations have been developed for the temperatures of glass covers, thus facilitating the calculation of individual heat transfer coefficients. The values of individual heat transfer coefficients therefore obtained can be used in the proposed analytical equation for the estimation of the top heat loss coefficient of the vertical collector with double glazing. The analytical equation has been developed for collector tilt angle of 60 to 90 degrees, plate temperature of 323 K to 423 K, absorber coating emittance of 0.1 to 0.95, air gap spacing of 20 mm to 50mm between the plate and inner glass cover, air gap spacing of 20 mm to 50mm between glass covers, wind heat transfer coefficient of 5 W/m2K to 30 W/m2K, and ambient temperature of 263K to 313K. The accuracy of the analytical equation has been validated for the said range of variables in comparison to numerical solutions, and the values of the top heat loss coefficient are found to be within 2.5 percent compared to numerical solutions.

An alternative for sustainable management in the cultivation of Capsicum annuum L. has focused on the use of plant growth promoting rhizobacteria (PGPR) and arbuscular mycorrhizal fungi (AMF). This research selected PGPRPGPR and AMF based on their effect on Bell Pepper and Jalapeño bell pepper plants. Five bacterial strains isolated from different localities in the state of Mexico (P61 [Pseudomonas tolaasii], A46 [P. tolaasii], R44 [Bacillus pumilus], BSP1.1 [Paenibacillus sp.] and OLs-Sf5 [Pseudomonas sp.]) and 3 AMF treatments (H1 [consortium isolated from Chile rhizosphere in the state of Puebla], H2 [Rhizophagus intraradices] and H3 [consortium isolated from lemon rhizosphere from the state of Tabasco]). In addition, a fertilized treatment (Steiner solution 25%) and an absolute control were included. Jalapeño bell pepper “Caloro” and Bell Pepper “California Wonder” seedlings were inoculated with AMF at sowing and with CPB 15 days after emergence, and grown under controlled environment chamber conditions. In Jalapeño bell pepper, the best bacterial strain was P61 and the best AMF treatment was H1; in Bell Pepper the best strain was R44 and the best AMF were H3 and H1. These microorganisms increased the growth of jalapeño bell pepper and Bell Pepper seedlings compared to the unfertilized control. Likewise, P61 and R44 positively benefited the photosynthetic capacity of PSII.