The intermittent flow cold storage heat exchanger is one of the most important components of the pulse tube expansion refrigerator based on the reverse Brayton cycle. In the experimental system, the volume and heat transfer of the helical tube play a decisive role in the stable operation of the whole experimental system. However, there are few studies on heat transfer in a helical tube under helium working medium and intermittent flow conditions. In this paper, a process and method for calculating the volume of a helical tube are proposed based on the gas vessel dynamics model. Subsequently, a three-dimensional simulation model of the helical tube was established to analyze the heat transfer process of cryogenic helium within the tube. The simulations revealed that the temperature of helium in the tube decreases to the wall temperature and does not change when the helical angle exceeds 720°. Moreover, within the mass flow rate range of 1.6 g/s to 3.2 g/s, an increase in the mass flow rate was found to enhance the heat transfer performance of the helical tube. This study provides a reference for the selection and application of a helical tube under intermittent flow conditions and also contributes to the experimental research of inter-wall heat exchanger and pulse tube expansion refrigerators.

Zinc oxide (ZnO) hollow spheres are gaining attention due to their exceptional properties and potential applications in various fields. This study investigates the impact of different zinc precursors Zinc Chloride (ZnCl₂), Zinc Nitrate [Zn(NO₃)₂], and Zinc Acetate [Zn(CH₃COO)₂] on the hydrothermal synthesis of ZnO hollow spheres. A comprehensive set of characterization techniques, including Field Emission Scanning Electron Microscopy (FE-SEM), X-ray Diffraction (XRD), Thermogravimetric analysis (TGA), and Brunauer-Emmett-Teller (BET) analysis, was utilized to assess the structural and morphological features of the synthesized materials. Our findings demonstrate that all samples exhibit a high degree of crystallinity with a wurtzite structure, and crystallite sizes range between 34 to 91 nm. Among the different precursors, ZnO derived from Zinc Nitrate showed markedly higher porosity and a well-defined mesoporous structure than those obtained from Zinc Acetate and Zinc Chloride. This research underscores the significance of precursor selection in optimizing the properties of ZnO hollow spheres, ultimately contributing to advancements in the design and application of ZnO-based nanomaterials.

Corporate social responsibility (CSR) is an important concept of modern economic theory. In the last few decades, it has become an increasingly popular marketing tool used by companies. Consumers too want to see more CSR activities, especially those focused on environmental protection. The petroleum industry produces both toxic and non-toxic waste at almost all stages of production. While petroleum companies satisfy market demand, they also want to meet consumers’ moral and ethical demands. In this light, CSR has become vital for the development of industry. This paper looks at CSR in the petroleum industry, and its effect on customer satisfaction and subsequently toward the customer repurchase intention in Malaysia. The starting point of this paper is the Stakeholder Theory. It then examines CSR endeavors within the oil and gas sector and its link to customer repurchase intentions. It also looks at the established hypotheses between the activities of CSR (Economic Responsibility, Legal Responsibility, Ethical Responsibility, Philanthropic Responsibility), customer satisfaction and repurchase intention. This paper aims to learn about the customer’s sense of fulfilment with the CSR activities, and what could be the reaction base on the customer’s expectation.

Using the Intercultural Competence and Inclusion in Education Scale (ICIES), this study examines variations in intercultural competence and inclusion between mainstream and multiethnic high schools. The sample consisted of 384 high school students, aged 17 to 18, from both rural and urban areas in Western Romania, enrolled in grades 11 and 12. The ICIES demonstrated strong reliability, with a Cronbach’s alpha of 0.721. Exploratory factor analysis revealed three distinct dimensions: Intercultural opportunities and activities, Comfort in diverse settings, and Cultural reflection and values. Independent samples t-tests identified significant differences between mainstream and multiethnic schools across several items, with students in multiethnic schools reporting higher levels of intercultural competence and inclusion. These findings highlight the critical role of multicultural educational settings in fostering students' cultural awareness and inclusive attitudes. This study provides actionable insights for enhancing multicultural education practices and policies, including teacher training programs, inclusive curricula, and extracurricular initiatives that promote intercultural engagement and reduce intergroup biases.

Accurate drug-drug interaction (DDI) prediction is essential to prevent adverse effects, especially with the increased use of multiple medications during the COVID-19 pandemic. Traditional machine learning methods often miss the complex relationships necessary for effective DDI prediction. This study introduces a deep learning-based classification framework to assess adverse effects from interactions between Fluvoxamine and Curcumin. Our model integrates a wide range of drug-related data (e.g., molecular structures, targets, side effects) and synthesizes them into high-level features through a specialized deep neural network (DNN). This approach significantly outperforms traditional classifiers in accuracy, precision, recall, and F1-score. Additionally, our framework enables real-time DDI monitoring, which is particularly valuable in COVID-19 patient care. The model’s success in accurately predicting adverse effects demonstrates the potential of deep learning to enhance drug safety and support personalized medicine, paving the way for safer, data-driven treatment strategies.