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.

This study considers the relationship between investment in the manufacturing and processing industries and economic growth in Vietnam. This study applies an autoregressive distributed lag (ARDL) model to reassess the long- and short-term relationships between industrial investment and economic growth from 1998 to 2023. It has been found that in both the long and short term, investments in this sector have a positive and significant effect on economic growth. The results further show that labor negatively affects growth in the long run, but is favorable in the short run. The verdict for the role of exports is that more evidence is required before any conclusive analysis can be conducted. Reinvestment in the manufacturing and processing industries for further economic growth is evident in the foregoing analysis. On the other hand, this research provides insight into the optimization of the utilization of resources and future sustainability by the government.

Development of technologies and innovations encouraged companies to look for and implement innovative solutions in their practice seeking not only to increase the efficiency of activity but also towards sustainability. In this context, the aim of the research is to reveal innovative solutions for the improvement of the warehousing processes towards sustainability in the case of manufacturing companies. The methodological setup consists of two steps. First, a comprehensive literature analysis was conducted seeking to reveal and present a theoretical model based on the conceptual framework on this topic. Then, a semi-structured interview was conducted with 8 managers holding managerial positions in four Lithuanian manufacturing companies. The manufacturing companies were chosen for the research due to their durable experience in the market, which use advanced warehouse management methods in their operations. Main findings showed, that innovative solutions such as Big Data Datasets, smart networks, Drones, Robots, Internet of Things and etc., are important for the efficient warehousing processes. Furthermore, it is also necessary to emphasize the benefits of implementing of innovative solutions in warehousing processes not only in economic terms, but also for solving of social and environmental issues towards sustainability. The novelty of this study lies in its dual objective of filling a theoretical gap and of drawing the attention of companies and policy makers to the importance of innovative solutions implementation in the warehousing process towards sustainability.

Language is fundamental to human communication, allowing individuals to express and exchange ideas, thoughts, and emotions. In early childhood, some children experience communication disorders that impede their ability to articulate words correctly, posing significant challenges to their learning and development. This issue is exacerbated in developing countries, where limited resources and a lack of technological tools hinder access to effective speech therapy. Traditional speech therapy remains vital, but the latest technological advancements have introduced robotic assistants to enhance therapy for communication disorders. Despite their potential, these technologies are often inaccessible in developing regions due to high production costs and a lack of sustainable manufacturing models. For these reasons, this paper presents “FONA,” a robotic assistant that employs rule-based expert systems to provide tactile, auditory, and visual stimuli. FONA supports children aged 3 to 6 in speech therapy by delivering exercises such as syllable production, word formation, and pictographic storytelling of various phonemes. Notably, FONA was successfully tested on children with cochlear implants, reducing the number of sessions required to produce isolated phonemes. The paper also introduces an innovative analysis of the Make To Order (MTO) manufacturing system for producing FONA in developing countries. This analysis explores two key perspectives: collaborative networks and entrepreneurship, offering a sustainable production model. In a pilot experiment, FONA significantly improved children’s attention spans, increasing the period by 17 min. Furthermore, the economic analysis demonstrates that producing FONA through collaborative networks can significantly reduce costs, making it more accessible to institutions in developing countries. The findings suggest that the project is viable for a five-year period, providing a sustainable and effective solution for addressing communication disorders in children.

Based on digital technology, the digital economy has typical characteristics of high efficiency, greenness, intelligence, innovation, strong penetration and so on, which can promote the sporting goods manufacturing industry (SGMI) to realize the goal of green development. This study selects panel data from 30 provinces in China over the period of 2011 to 2022. And the green total factor productivity of the sporting goods manufacturing industry (SGTFP) is used to reflect the green development of SGMI. The level of digital economy development (DIG) and the SGTFP are measured by using the entropy method and the Super-SBM model with undesirable outputs. Based on the method of coupling coordination degree model, the coordinated development degree of DIG and SGTFP is analyzed first. Then, by making use of the fixed effect model, intermediary effect model and spatial Durbin model, the influence of DIG on the green development of SGMI and its mechanism are empirically studied. The results show that DIG, SGTFP and the degree of their coupling and coordination are generally on the rise. The benchmark regression results show that the coefficient of DIG on SGTFP is 0.213; that is, the digital economy can significantly promote the improvement of green development in SGMI. According to the analysis of the spatial Durbin model, the impact of the digital economy on SGTFP has a certain spatial spillover, that is, the development of digital economy in the region will have a certain promoting effect on the green development of SGMI in the surrounding region. The intermediary effect model analyzes the influence mechanism and finds that the digital economy mainly boosts SGTFP through green innovation technology and energy consumption structure.

A precise risk assessment in a production line constitutes a significant item to identify susceptible areas where there is a possibility of product quality degradation. This also applies to the precast concrete production line in Indonesia that has a spun pile product. Based on a risk assessment activity conducted in this study, it is proposed to build a traceability model in order to maintain and even improve the spun pile product quality in Indonesia. The approach used was the Neural Network of the perceptron model for weighing and will result in a defined traceability path in the context of reducing defects and even failed spun pile products. The simulation result showed that the model has been able to detect risky path possibilities to reduce product quality. The accumulation result of high-risk and medium-risk paths in this study showed that closer to product finalization, the risk will be higher. It is evident that when assessing Indicators, the order from the highest accumulation value first is Curing & Demolding and Stressing & Spinning at 29% each, Casting at 14%, Forming & Setting at 14%, and lastly Cutting & Heading at 14%. Regarding the risk assessment for activities, the first position is Curing & Demolding and Stressing & Spinning with 30% each, the second is Casting and Forming & Setting with 15% each, and the third is Cutting & Heading with 10%.