This study explores the intricate relationship between emotional cues present in food delivery app reviews, normative ratings, and reader engagement. Utilizing lexicon-based unsupervised machine learning, our aim is to identify eight distinct emotional states within user reviews sourced from the Google Play Store. Our primary goal is to understand how reviewer star ratings impact reader engagement, particularly through thumbs-up reactions. By analyzing the influence of emotional expressions in user-generated content on review scores and subsequent reader engagement, we seek to provide insights into their complex interplay. Our methodology employs advanced machine learning techniques to uncover subtle emotional nuances within user-generated content, offering novel insights into their relationship. The findings reveal an inverse correlation between review length and positive sentiment, emphasizing the importance of concise feedback. Additionally, the study highlights the differential impact of emotional tones on review scores and reader engagement metrics. Surprisingly, user-assigned ratings negatively affect reader engagement, suggesting potential disparities between perceived quality and reader preferences. In summary, this study pioneers the use of advanced machine learning techniques to unravel the complex relationship between emotional cues in customer evaluations, normative ratings, and subsequent reader engagement within the food delivery app context.

In this paper, we modeled and simulated two tandem solar cell structures (a) and (b), in a two-terminal configuration based on inorganic and lead-free absorber materials. The structures are composed of sub-cells already studied in our previous work, where we simulated the impact of defect density and recombination rate at the interfaces, as well as that of the thicknesses of the charge transport and absorber layers, on the photovoltaic performance. We also studied the performance resulting from the use of different materials for the electron and hole transport layers. The two structures studied include a bottom cell based on the perovskite material CsSnI₃ with a band gap energy of 1.3 eV and a thickness of 1.5 µm. The first structure has an upper sub-cell based on the CsSnGeI₃ material with an energy of 1.5 eV, while the second has an upper sub-cell made of Cs₂TiBr₆ with a band gap energy of 1.6 eV. The theoretical model used to evaluate the photocurrent density, current-voltage characteristic, and photovoltaic parameters of the constituent sub-cells and the tandem device was described. Current matching analysis was performed to find the ideal combination of absorber thicknesses that allows the same current density to be shared. An efficiency of 29.8% was obtained with a short circuit current density J_sc = 19.92 mA/cm², an open circuit potential V_oc = 1.46 V and a form factor FF = 91.5% with the first structure (a), for a top absorber thickness of CsSnGeI₃ of 190 nm, while an efficiency of 26.8% with J_sc = 16.74, V_oc = 1.50 V and FF = 91.4% was obtained with the second structure (b), for a top absorber thickness of Cs₂TiBr₆ of 300 nm. The objective of this study is to develop efficient, low-cost, stable and non-toxic tandem devices based on lead-free and inorganic perovskite.

Green cosmetics made from organic ingredients are becoming increasingly popular due to their environmentally friendly nature. However, research on consumer behavior towards green cosmetics is rare, especially in developing countries like Pakistan. Previous studies have primarily focused on female consumers, and little is known about the behavior of male consumers. Therefore, this research aims to investigate the behavior of both male and female consumers towards green cosmetic products and analyze the factors that affect their purchase behavior. This study employs a quantitative approach with deductive reasoning and collects data through a questionnaire from major cities in Pakistan. The study finds that eco-awareness, social influence, price-quality instructions, health consciousness, and the need for uniqueness significantly influence consumer purchase behavior when buying green cosmetics. Interestingly, price sensitivity does not significantly affect consumer purchase behavior as consumers are willing to pay for high-quality green cosmetics. Based on the findings, the study recommends promoting eco-awareness and health consciousness among consumers through educational campaigns and workshops launched by the government and the private sector. Future research can explore factors such as age, gender, and specific generations like millennials and Generation Z, as well as packaging, branding, and product design to promote environmentally friendly and health-conscious products. Additionally, comparative studies between countries can identify universal and region-specific factors, and examining the overall impact of green cosmetic products on the environment can highlight areas for improvement in sustainability.

This research presents an innovative perspective on vocational education by merging the Instructional System Design (ISD) model with Innovation in Thailand Vocational Education and Training (InnoTVET) principles. Targeted at nursing students, the course aims to cultivate entrepreneurial skills while connecting vocational training with healthcare policy development. It aligns with global movements in Education for Sustainable Development (ESD), addressing the increasing demand for nurse entrepreneurs who can devise creative healthcare solutions within established policy frameworks. By employing mastery learning techniques alongside design thinking, the course effectively bridges theoretical concepts with practical applications. The mixed-methods study underlines relevant contribution in students’ entrepreneurial mindsets. Results from t-tests reveal the students’ ability to identify opportunities, engage in innovative thinking, and work within policy frameworks. Findings are supported by qualitative data, which demonstrate enhanced confidence, improved problem-solving capacities, and a deeper understanding of healthcare market dynamics. Although expert evaluation of student projects is scheduled for future iterations, the initial outcomes reinforce the course’s success. The course is structured into seven modules spanning 45 hours, featuring active learning components, five business-oriented assignments, and a final innovation project that integrates the curriculum’s core elements. This design ensures students develop both practical expertise and interdisciplinary insights critical to healthcare innovation. The integration of InnoTVET and ISD principles in nursing education sets a precedent for vocational education reform. This example of a successful nursepreneurship initiative provides a scalable model for enhancing vocational programs in diverse fields, fostering innovation and sustainability.

This study explores the influence of digital technologies, including media, on pre-service teachers’ interactions and engagement patterns. It underscores the significance of promoting digital competence to empower pre-service teachers to navigate the digital world responsibly, make informed decisions, and enhance their digital experiences. The objective is to identify key themes and categories in research studies related to pre-service teachers’ digital competence and skill preparations. Conducting a systematic literature review, we searched databases such as SCOPUS, ScienceDirect, and Taylor & Francis, including forty-three articles in the dataset. Applying qualitative content analysis, we identified four major themes: digital literacy, digital competencies, digital skills, and digital thinking. Within each theme, categories and their frequencies were examined. Preliminary findings reveal a growing prevalence of digital competence and literacy articles between 2019 and 2024. The paper concludes by offering recommendations for further research and implementations, with specific criteria used for article selection detailed in the paper. A digital literacy policy for teacher education preparedness is included.