This study investigates the effects of two ultraviolet (UV) stabilizers, UV-531 and
UV-783, on the durability, oxidation stability, and dimensional stability of highdensity polyethylene (HDPE) materials. HDPE samples were prepared with varying
additive contents (1% and 2% by weight) for 2 types of UV additives to evaluate
HPDE’s resistance against UV-induced degradation. These results found that
HPDE with UV additives of UV-531 and UV-783 with 1-2 wt.% showed good
longitudinal reversion, oxidation induction time (ISO 11357), and weathering
resistance compared to HPDE without using UV additives. Inherently, we found
that both UV-531 and UV-783, stabilizers improved the oxidation induction time
(OIT) and tensile strength retention after accelerated aging. More importantly, the
UV-531 additive exhibited superior stabilization performance compared to UV783, particularly at 1.0 wt%, showing a 30% increase in OIT and maintaining over
95% tensile strength after UV exposure. The findings demonstrate the effectiveness
of UV-531 as an efficient stabilizer for outdoor HDPE applications requiring longterm durability.

This study explores the changes in the food industry due to the emergence
of cloud kitchens. This research paper will investigate whether cloud kitchens offer
a more sustainable, accessible, and profitable business model compared to
traditional restaurants in emerging markets. This will be determined using a mix of
secondary data and a case study, Bento, an emerging cloud kitchen in Jeddah, Saudi
Arabia. Findings indicate that cloud kitchens enhance Profitability and accessibility,
but they lack Sustainability. These results are interpreted using Porter's cost
leadership strategy, lean start-up theory, and corporate social responsibility
frameworks. Overall, cloud kitchens are an example of a business model that aligns
with the Saudi Vision 2030 goals.

Franchising emerged as a modern business model during the second half of the twentieth century and has since gained considerable scholarly attention due to its growing role in business expansion and economic development. Many franchise systems originate from a simple entrepreneurial idea that later evolves into a structured and replicable business model with the potential for successful imitation. Today, franchising has become an increasingly dynamic and expanding practice within Iran’s business environment.
The aim of this quantitative study is to examine the factors influencing franchisee satisfaction within the franchising process. Data were collected using a standardized questionnaire whose validity was confirmed by academic experts and whose reliability was determined through Cronbach’s alpha (0.092). Inferential analyses were performed using SPSS software to identify the determinants of franchisee satisfaction, including system and service quality, the franchisor’s competitive advantage, franchisee characteristics, and market attractiveness.
The findings indicate that three factors—system and service quality, the franchisor’s competitive advantage, and market attractiveness—have a significant relationship with franchisee satisfaction. Stepwise regression analysis of the four key variables demonstrated that only system and service quality has a statistically significant effect on franchisee satisfaction when assessed simultaneously. Furthermore, regression analyses revealed meaningful relationships among system and service quality, competitive advantage, and market attractiveness, confirming the interdependence of these variables in influencing franchisee satisfaction.

One of the fundamental objectives of companies and profit-oriented organizations is to generate profits in the short term and to maximize shareholder wealth in the long term. Achieving these goals requires effective financial decision-making in areas such as financing strategies, the utilization of internal capital, and external investment opportunities. Effective decisions depend on accurate performance evaluation, which must be carried out using appropriate indicators and criteria. Financial performance indicators have a particularly important position due to their practicality, objectivity, and measurable nature. Among the key financial indicators for companies listed on the stock exchange is stock return (SR), and investors continually search for reliable methods to predict it. Economic Value Added (EVA) is widely recognized as one of the most efficient measures for explaining stock returns quantitatively and is regarded as a leading internal performance indicator.
The present research aims to examine the relationship between EVA and stock return and to compare its explanatory power with that of net profit (NP) in predicting stock return. The analysis was conducted in the context of companies engaged in oil production and listed on the stock exchange. The correlation coefficient between net profit and stock return was found to be 0.07, indicating a stronger explanatory power of net profit in describing changes in stock return. The findings demonstrate that EVA does not show a statistically significant relationship with stock return for the oil production sector within the examined capital market. These results suggest the need to identify more suitable economic indicators for evaluating stock returns in such companies.

The introduction of fuel hydrocarbons and inorganic contaminants such as heavy metals into soil leads to a deterioration of soil quality, potentially impairing its normal functions and posing risks to public health and groundwater resources. This study aims to evaluate key parameters involved in the co-remediation of soil contaminated with diesel and heavy metals using non-ionic surfactants in a soil-washing process. In this experimental investigation, the effects of washing time, agitation speed, surfactant concentration, chelating agent addition, and pH on contaminant removal efficiency were examined.
The results indicated that diesel removal using non-ionic surfactants, specifically Tween 80 and Brij 35, reached approximately 70–80% and 60–65% under optimal conditions, respectively. The incorporation of the chelating agent EDTA significantly increased the removal efficiency of cadmium (Cd) and lead (Pb). These findings suggest that soil washing using a combination of non-ionic surfactants and EDTA is an effective approach for the simultaneous remediation of diesel and heavy metals in contaminated soil, and can therefore be recommended for practical applications in soil decontamination.

The present study aims to examine the relationship between psychological hardiness, emotional intelligence, and work holism among high school teachers. The population under investigation consisted of male and female teachers employed in secondary schools during the 2012–2013 academic year. Using a simple random sampling method, a total of 100 teachers were selected as the research sample.
Data were collected through standardized instruments, including the Kobasa Psychological Hardiness Questionnaire, the Bar-On Emotional Intelligence Inventory (90 items), and the Aghabeigi Workaholism Questionnaire. Descriptive statistics (frequency, percentage, mean, and standard deviation) as well as inferential statistical methods (t-test and regression analysis) were used to analyze the data.
The findings revealed a significant negative relationship between psychological hardiness and work holism, and a significant positive relationship between psychological hardiness and emotional intelligence. Additionally, a significant negative relationship was observed between emotional intelligence and work holism. The results further indicated that there was no significant difference between male and female teachers in terms of psychological hardiness, work holism, or emotional intelligence.

This study presents a selective, sensitive, precise, accurate, and rapid high-performance liquid chromatographic (HPLC) method for the quantification of levofloxacin in human plasma. The analytical procedure was validated in accordance with ICH guidelines. Sample preparation involved a one-step protein precipitation technique to isolate levofloxacin, followed by a simple and fast isocratic separation on a Zorbax SB-CN reversed-phase HPLC column, with fluorescence detection at an excitation wavelength of 290 nm and an emission wavelength of 456 nm.
The method employed a weighted factor of 1/concentration² and demonstrated linearity within the range of 0.3–20.39 µg/mL, with a correlation coefficient greater than 0.998. Recovery, selectivity, linearity, precision, accuracy, and stability were assessed using spiked plasma samples. The overall precision and accuracy values were within 1–7%.
The validated method was successfully applied to human plasma samples for a levofloxacin pharmacokinetic study. Its high analytical throughput, requiring approximately 20 minutes for sample preparation followed by a short chromatographic run time of 12 minutes, highlights its suitability for pharmacological and pharmacokinetic applications involving levofloxacin.

In contemporary economies, e-commerce has become one of the most essential tools for financial transactions in developed markets. As traditional commercial environments are increasingly unable to meet the evolving needs of consumers, organizations have begun to modify marketing strategies to influence customer behavior more effectively. Social networks, due to their unique capabilities in tracking and understanding user preferences, provide a powerful platform through which organizations can employ e-commerce to achieve strategic objectives.
Within social networks, customer influence often occurs through peer recommendations, particularly when potential buyers observe positive experiences from other online consumers. This peer-driven persuasion attracts additional customers and increases the likelihood of online purchases. Recommendation systems in social networks function by leveraging shared information among users, interpersonal connections, and similarities in product preferences and consumer behavior.
The present study introduces the concepts of e-commerce and social networks and examines how they interact to reduce user disengagement within e-commerce platforms embedded in social networks. To analyse the research hypotheses, both descriptive and inferential statistical methods were employed. Descriptive statistics included frequency tables and measures of central tendency, while inferential analysis utilized Pearson’s correlation coefficient as implemented in SPSS Version 17.

Structural loads applied to buildings are generally categorized into two groups: vertical loads and lateral loads. Dead loads, live loads, and snow loads constitute vertical loads, while wind and earthquake loads represent lateral forces. In the case of lightweight or high-rise buildings, wind effects can be particularly critical. The influence of wind on structures depends on wind characteristics, building geometry, and surrounding environmental conditions.
In this study, a linear analysis was performed on 54 steel moment frame models to compare wind load provisions in widely recognized codes, including NBCC-05, ASCE 7-05, and the National Building Code. Additionally, the influence of the number of building stories and the number of bays on structural response to wind loading was examined. Results indicate that the ASCE 7-05 code predicts higher values for the evaluated parameters compared with the other standards. Furthermore, an increase in the number of stories and bays leads to increased column stress ratios, overturning moments, base shear forces, story drift indices, and displacement at the centre of mass, as defined by the governing provisions of this code.