Lifelong learning (LLL) is progressively recognized as a crucial component of personal and professional development, particularly for adult students. As a heavily populated developing country, China requires profound national education reform to support its economic development and maintain its competitive advantage on the global economic stage. The governmental policy endorses the execution of diverse forms of lifelong learning programs to bolster the national education reform. However, implementing such programs can be challenging for all the stakeholders of the programs, especially for adult students. The weaker foundational knowledge and insufficient online learning abilities of adult students particularly highlight the academic challenges they face. This study explores the academic challenges faced by adult learners in a Chinese vocational college’s LLL program. Focusing on ex-soldiers, unemployed individuals, migrant workers, and new professional farmers (aged 22–44), data were collected from 16 adult students via purposive sampling. Semi-structured interviews and document analysis revealed recurring thematic academic challenges. Additionally, the study found that adult student attributes (highest education level, age) significantly influenced the unique academic challenges they encountered. This research provides practical solutions to improve LLL programs and promote successful lifelong learning experiences for adult students. 

The rapid advancement of artificial intelligence (AI) technology is profoundly transforming the information ecosystem, reshaping the ways in which information is produced, distributed, and consumed. This study explores the impact of AI on the information environment, examining the challenges and opportunities for sustainable development in the age of AI. The research is motivated by the need to address the growing concerns about the reliability and sustainability of the information ecosystem in the face of AI-driven changes. Through a comprehensive analysis of the current AI landscape, including a review of existing literature and case studies, the study diagnoses the social implications of AI-driven changes in information ecosystems. The findings reveal a complex interplay between technological innovation and social responsibility, highlighting the need for collaborative governance strategies to navigate the tensions between the benefits and risks of AI. The study contributes to the growing discourse on AI governance by proposing a multi-stakeholder framework that emphasizes the importance of inclusive participation, transparency, and accountability in shaping the future of information. The research offers actionable insights for policymakers, industry leaders, and civil society organizations seeking to foster a trustworthy and inclusive information environment in the era of AI, while harnessing the potential of AI-driven innovations for sustainable development.

Synthetic membranes play a crucial role in a wide range of separation processes, including dialysis, electrodialysis, ultrafiltration, and pervaporation, with growing interest in synthetic emulsion membranes due to their precision, versatility, and ion exchange capabilities. These membranes enable tailored solutions for specific applications, such as water and gas separation, wastewater treatment, and chemical purification, by leveraging their multi-layered structures and customizable properties. Emulsion membrane technology, particularly in pressure-driven methods like reverse osmosis (RO) and nanofiltration (NF), has shown great potential in overcoming traditional challenges, such as fouling and energy inefficiency, by improving filtration efficiency and selectivity. This review explores the latest advancements in emulsion membrane development, their adaptability to various industrial needs, and their contribution to addressing long-standing limitations in membrane separation technologies. The findings underscore the promise of emulsion membranes in advancing industrial processes and highlight their potential for broader applications in water treatment, environmental management, and other key sectors.

Water pollution has become a serious threat to our ecosystem. Water contamination due to human, commercial, and industrial activities has negatively affected the whole world. Owing to the global demanding challenges of water pollution treatments and achieving sustainability, membrane technology has gained increasing research attention. Although numerous membrane materials have focused, the sustainable water purification membranes are most effective for environmental needs. In this regard sustainable, green, and recyclable polymeric and nanocomposite membranes have been developed. Materials fulfilling sustainable environmental demands usually include wide-ranging polyesters, polyamides, polysulfones, and recyclable/biodegradable petroleum polymers plus non-toxic solvents. Consequently, water purification membranes for nanofiltration, microfiltration, reverse osmosis, ultrafiltration, and related filtration processes have been designed. Sustainable polymer membranes for water purification have been manufactured using facile techniques. The resulting membranes have been tested for desalination, dye removal, ion separation, and antibacterial processes for wastewater. Environmental sustainability studies have also pointed towards desired life cycle assessment results for these water purification membranes. Recycling of water treatment membranes have been performed by three major processes mechanical recycling, chemical recycling, or thermal recycling. Moreover, use of sustainable membranes has caused positive environmental impacts for safe waste water treatment. Importantly, worth of sustainable water purification membranes has been analyzed for the environmentally friendly water purification applications. There is vast scope of developing and investigating water purification membranes using countless sustainable polymers, materials, and nanomaterials. Hence, value of sustainable membranes has been analyzed to meet the global demands and challenges to attain future clean water and ecosystem.

Art studies and activities for older adults have received significantly less attention as a result of prohibitively expensive materials that are unfit for commercial use, and research utilizing digital technology to investigate artistic activities for older adults is extremely limited. The purpose of this article is to analyze and review recent research in these fields to summarize the current trends. The literature review comprised 108 articles from databases that included Scopus, ScienceDirect, and Google Scholar. The papers were subjected to a thorough examination by the VOSviewer program and researchers, who utilized content analysis to classify them into four themes: 1) inclusive design; 2) accessibility; 3) digital art therapy and 4) digital technology environments. Further investigation and development are necessary to propose a novel approach to instructing senior-level art utilizing cutting-edge technologies, which could be enhanced by the findings of this review article.

In the era of artificial intelligence, smart clothing, as a product of the interaction between fashion clothing and intelligent technology, has increasingly attracted the attention and affection of enterprises and consumers. However, to date, there is a lack of focus on the demand of silver-haired population’s consumers for smart clothing. To adapt to the rapidly aging modern society, this paper explores the influencing factors of silver-haired population’s demand for smart clothing and proposes a corresponding consumer-consumption-need theoretical model (CCNTM) to further promote the development of the smart clothing industry. Based on literature and theoretical research, using the technology acceptance model (TAM) and functional-expressive-aesthetic consumer needs model (FEAM) as the foundation, and introducing interactivity and risk perception as new external variables, a consumer-consumption-need theoretical model containing nine variables including perceived usefulness, perceived ease of use, functionality, expressiveness, aesthetics, interactivity, risk perception, purchase attitude, and purchase intention was constructed. A questionnaire survey was conducted among the Chinese silver-haired population aged 55–65 using the Questionnaire Star platform, with a total of 560 questionnaires issued. The results show that the functionality, expressiveness, interactivity, and perceived ease of use of smart clothing significantly positively affect perceived usefulness (P < 0.01); perceived usefulness, perceived ease of use, aesthetics, and interactivity significantly positively affect the purchase attitude of the silver-haired population (P < 0.01); perceived usefulness, aesthetics, interactivity, and purchase attitude significantly positively affect the purchase intention of the silver-haired population (P < 0.01); functionality and expressiveness significantly positively affect perceived ease of use (P < 0.01); risk perception significantly negatively affects purchase attitude (P < 0.01). Through the construction and empirical study of the smart clothing consumer-consumption-need theoretical model, this paper hopes to stimulate the purchasing behavior of silver-haired population’s consumers towards smart clothing and enable them to enjoy the benefits brought by scientific and technological advancements, which to live out their golden years in comfort, also, promote the rapid development of the smart clothing industry.