Search Results (390)

This study presents a systematic literature review on the reuse of Arundo donax as a secondary renewable raw material for sustainable construction. Originally classified as a dangerously invasive species by the International Union for Conservation of Nature (IUCN), Arundo donax has recently gained recognition as a non-conventional promising biomass resource, particularly in the context of green innovation and circular economy strategies in light of the European Green Deal and the New European Bauhaus initiatives. This review combines bibliometric mapping and full-text analysis, leading to the selection of 20 peer-reviewed studies, thematically clustered into two main application areas: the development of panels and composites with improved mechanical, thermal, and acoustic performance; and the use of this species in geotechnical or low-tech solutions, such as earth construction and erosion control. While most contributions are recent and technically oriented, this review highlights several critical gaps, such as the lack of standardized testing protocols, the limited number of environmental assessments, and the absence of long-term performance evaluations. Despite these limitations, the considered biomass shows significant potential to support regenerative design strategies for the built environment. Future research should prioritize comparative LCA studies, industrial scalability, and the formulation of guidelines to integrate Arundo donax-based materials into sustainable construction practices. Full article

This qualitative case study explores how preschool teachers enact inclusive pedagogical practices by integrating tangible technologies, low-tech, and no-tech tools within an inquiry-based learning framework. Focusing on teacher decision-making and children’s multimodal engagement, the study examines two questions: (1) How do early childhood teachers use a range of tools to support inclusive, inquiry-driven learning? and (2) How do children engage with these tools to communicate, collaborate, and construct knowledge? Drawing on classroom observations, teacher-created storyboards, child artifacts, and educator reflections, findings illustrate how programmable robots, recycled materials, and hands-on resources support accessibility and creative expression for diverse learners. Children used alternative modalities such as coding, drawing, building, and storytelling to represent their ideas and engage in problem-solving across a range of developmental and linguistic needs. Teachers are positioned as pedagogical designers who scaffold inclusive participation through flexible environments, intentional provocations, and responsive guidance. Rather than treating technology as a standalone innovation, the study emphasizes how its integration, when grounded in play, inquiry, and real-world relevance, can promote equity and engagement. These findings contribute to research on Universal Design for Learning (UDL), early STEM education, and inclusive instructional design in early childhood classrooms. Full article

Background: Neuropathic pain (NP), resulting from damage to the somatosensory nervous system, affects 7–10% of the global population and remains poorly managed despite available therapies. Smoking has been associated with increased pain severity and disease burden, yet its role in neuropathy/NP has not been systematically reviewed. This systematic review synthesizes the existing literature on smoking status and its relationship with neuropathy/NP incidence, prevalence, and severity. Methods: The review was conducted in accordance with PRISMA guidelines and included studies that assessed smoking consumption, dependency, quantity, and cessation in individuals with neuropathy/NP. Summary estimates were stratified by exposure type, and pooled odds ratios and relative risks were calculated. Results: Across 62 studies comprising cohort, case–control, and cross-sectional designs, smoking was consistently associated with greater NP prevalence and pain severity. Smoking dependency was linked to increased incidence, while cessation was associated with reduced risk of NP. Despite considerable heterogeneity and risk of bias, particularly from subjective exposure measurement and inconsistent classification, this relationship remained statistically significant. Conclusions: Findings support the role of smoking as a modifiable risk factor in various etiologies of neuropathy/NP. Cessation may represent a low-cost, low-risk, low-tech adjunctive therapy; however, further robust cessation interventional trials are needed, particularly for less common infectious causes of chronic NP such as leprosy. Full article

This study evaluates the competitiveness and sustainable development prospects of French-speaking African countries by constructing a comprehensive framework integrating the TOPSIS method and adaptive LASSO algorithm. Using multivariate data from sources such as the World Bank, 30 indicators covering core, basic, and auxiliary competitiveness were selected to quantitatively analyze the competitiveness of 26 French-speaking African countries. Results show that their comprehensive competitiveness exhibits spatial patterns of “high in the north and south, low in the east and west” and “high in coastal areas, low in inland areas”. Algeria, Morocco, and six other countries demonstrate high competitiveness, while Central African countries generally show low competitiveness. The adaptive LASSO algorithm identifies three key influencing factors, including the proportion of R&D expenditure to GDP, high-tech exports, and total reserves, as well as five secondary key factors, including the number of patent applications and total number of domestic listed companies, revealing that scientific and technological investment, financial strength, and innovation transformation capabilities are core constraints. Based on these findings, sustainable development strategies are proposed, such as strengthening scientific and technological research and development and innovation transformation, optimizing financial reserves and capital markets, and promoting China–Africa collaborative cooperation, providing decision-making references for competitiveness improvement and regional cooperation of French-speaking African countries under the background of the “Belt and Road Initiative”. Full article

As inevitable outcomes of the digital economy’s low-carbon development, green data centers play a crucial role in environmental impact and underlying mechanisms. This study focuses on green data center establishment as a representative practice, utilizing Chinese A-share listed companies and urban data from 2009 to 2023 to construct a multi-period difference-in-differences model. From a supply chain perspective, we investigate the impact of green data centers on corporate carbon emissions and their mechanisms. The results demonstrate that regional establishment of green data centers significantly promotes corporate carbon emission reduction, with conclusions remaining robust after a series of comprehensive robustness and endogeneity tests. This process primarily operates through two channels: green total factor energy efficiency and green attention. Green data center establishment significantly enhances green total factor energy efficiency and corporate green attention. The more developed the regional digital infrastructure and the higher the computing power development levels, the stronger the incentive effect on corporate carbon reduction. Heterogeneity analysis reveals that green data centers have more significant promoting effects on carbon emission reduction in state-owned enterprises and high-tech enterprises. This research contributes to a deeper understanding of the effects, mechanisms, and regional variations related to green data centers in facilitating corporate carbon emission reduction. Full article

Startups are often praised for their innovative power and dynamic work environments, but are also criticized for workplace cultures that perpetuate traditional masculine norms of competitiveness, workaholism, emotional resilience, and strength. This exploratory study examines the prevalence of Masculinity Contest Culture (MCC) in German startups and related gender dynamics. The Masculinity Contest Culture scale, which assesses masculine norms related to emotional resilience, physical superiority, workaholism, and aggressive competitiveness, was employed to collect data from 101 participants representing various startups. The results indicate an overall low prevalence of MCC, with slightly higher scores for strong commitment to work. Individuals from disparate gender and hierarchical status groups exhibited comparable ratings of the intensity of toxic masculinity. While the presence of female founders and supervisors did not affect MCC scores, male dominance within the work environment had a small but significant amplifying effect. Significant differences were observed based on the prevailing leadership style, indicating that a shared leadership approach is associated with the creation of a more inclusive and less toxic work environment. The results challenge commonly held assumptions about tech startups. In addition, the study highlights the need for further research into the impact of leadership dynamics on startup culture. Full article

The rapid development and adoption of artificial intelligence (AI) technology has sparked debates about its implications for labor markets, yet the micro-level relationship between AI and labor share remains underexplored. Based on the theory of skill-biased technological change, this study aims to examine whether AI technology increases labor share by labor structure upgrading at the enterprise level. Using panel data for China’s listed companies from 2012 to 2022, this study tests this relationship using a two-way fixed effects model. The empirical results reveal that AI technology significantly increases labor share, with labor structure upgrading playing a mediating role in this relationship. Heterogeneity analysis reveals that the influence of AI technology on labor share is stronger for enterprises characterized by low labor market rigidity, high labor market supply, and talent policy support in external environments, as well as among labor-intensive, high-tech, and non-state-owned enterprises. Notably, this study finds that advancements in AI technology have achieved mutually beneficial outcomes of improving labor share and enhancing total factor productivity. Our research findings provide detailed empirical evidence for enterprises to formulate and implement AI strategies. Full article

The advancement of high-tech industries, notably in semiconductor manufacturing, pharmaceuticals, and precision instrumentation, has imposed stringent requirements on cleanroom environments, where strict control of airborne particulates, microbial presence, temperature, and humidity is essential. However, these controlled environments incur significant energy consumption, with air conditioning systems accounting for 40–60% of total usage due to high air circulation rates, intensive treatment demands, and system resistance. In light of global carbon reduction goals and escalating energy costs, improving the energy efficiency of cleanroom heating, ventilation, and air conditioning (HVAC) systems has become a critical research priority. Recent efforts have focused on optimizing airflow distribution, integrating heat recovery technologies, and adopting low-resistance filtration to reduce energy demand while maintaining stringent environmental standards. Concurrently, artificial intelligence (AI) methods, such as machine learning, deep learning, and adaptive control, are being employed to enable intelligent, energy-efficient system operations. This review systematically examines current energy-saving technologies and strategies in cleanroom HVAC systems, assesses their real-world performance, and highlights emerging trends. The objective is to provide a scientific basis for the green design, operation, and retrofit of cleanrooms, thereby supporting the industry’s transition toward low-carbon, sustainable development. Full article

This study evaluates the accuracy of a low-cost wearable system for the continuous monitoring of vital signs, including heart rate, blood oxygen saturation (Sp${\mathrm{O}}_2$), blood pressure trend (BPT), and body temperature. The prototype was built using the nRF52840 microcontroller, which integrates photoplethysmography and infrared sensors. The heart rate and Sp${\mathrm{O}}_2$ data were collected under three body positions (Rest, Sitting, and Standing), while all measurements were performed using both anatomical configurations: BPT-Finger and BPT-Earlobe. Results were compared against validated commercial devices: UT-100 for heart rate and Sp${\mathrm{O}}_2$, G-TECH LA800 for blood pressure, and G-TECH THGTSC3 for body temperature. Ten participants were monitored over a ten-day period. Bland–Altman analysis revealed clinically acceptable agreement thresholds of ±5 mmHg for blood pressure, ±5–10 bpm for heart rate, ±4% for Sp${\mathrm{O}}_2$, and ±0.5 °C for temperature. Both wearable configurations demonstrated clinically acceptable agreement across all vital signs. The BPT-Earlobe configuration exhibited superior stability and lower variability in the Rest and Sitting positions, likely due to reduced motion artifacts. Conversely, the BPT-Finger configuration showed higher Sp${\mathrm{O}}_2$ accuracy in the Standing position, with narrower limits of agreement. These findings highlight the importance of sensor placement in maintaining measurement consistency across physiological conditions. With an estimated cost of only ~USD 130—compared to ~USD 590 for the commercial alternatives—the proposed system presents a cost-effective, scalable, and accessible solution for decentralized health monitoring, particularly in underserved or remote environments. Full article

The middle reaches of the Yangtze River are important bases for high-tech, advanced manufacturing, and modern service industries in China, as well as a demonstration area for the coordination of economic and ecological construction, which plays an important role in the ecosystem carbon cycle. With the steady progress of social and economic development and urbanization, the supply capacity of ecosystem services has sharply decreased, and the carbon cycle mechanism has changed, further reducing the sustainability of regional ecosystem services. In this study, carbon storage in the middle reaches of the Yangtze River was estimated from 2000 to 2020 based on the InVEST model, and the temporal and spatial evolution characteristics of carbon storage in the middle reaches of the Yangtze River were summarized using the coefficient of variation and spatial autocorrelation. The coupled InVEST-PLUS model was used to simulate the carbon storage characteristics of the middle reaches of the Yangtze River under natural development, ecological protection, cultivated land protection, and urban development scenarios in 2035. The results show the following: (1) The main land-use types in the middle reaches of the Yangtze River are cultivated and forest land, and the land-use types in the study area show the characteristics of “two increases and four decreases” in the past 20 years. (2) The carbon storage level in the middle reaches of the Yangtze River has decreased by 83.65 × 10⁶ t in the past 20 years (approximately 1.16%). The coefficient of variation showed that the carbon storage level in the middle reaches of the Yangtze River was high, with the fluctuating area accounting for 8.79% of the total area. The results of local spatial autocorrelation show that the high-value areas of carbon storage are mainly distributed in the west and southeast of the study area, and the low-value areas are mainly distributed in the middle of the study area, exhibiting characteristics of “high values surrounding low values” in space. (3) The simulation results of carbon storage in the middle reaches of the Yangtze River in 2035 showed that the ecological protection scenario was better than the other scenarios in terms of the mean level, functional performance, and patch presentation. Full article

The increasing prevalence of sedentary lifestyles poses significant global health challenges, including obesity, diabetes, musculoskeletal disorders, and cardiovascular issues. This paper presents the design and development of a universal smart chair system aimed at mitigating the adverse effects of prolonged sitting. The proposed solution integrates a pressure sensor, vibration motors, an LED strip, and Bluetooth Low-Energy (BLE) communication into a modular and adaptable design. Powered by an STM32WB55CGU6 microcontroller and a rechargeable lithium-ion battery system, the smart chair monitors sitting duration and the user’s posture, and provides alerts through tactile, visual, and auditory notifications. A complementary mobile application allows users to customize sitting time thresholds, monitor activity, and assess battery status. Designed for universal compatibility, the system can be adapted to various chair types. Technical and functional testing demonstrated reliable performance, with the chair operating for over eight workdays on a single charge. The smart chair offers an innovative, cost-effective approach to improving workplace ergonomics and health outcomes, with potential for further enhancements such as posture monitoring. A pilot study with 83 students at VILNIUS TECH showed that the smart chair detected correct posture with 94.78% accuracy, and 97.59% of users responded to alerts by adjusting their posture within an average of 3.27 s. Full article

Lithium, a critical element for clean energy and modern technologies, plays an indispensable role in advancing renewable energy storage, electric vehicles, and high-tech industries. The rapidly growing demand for lithium, along with its limited global production, has led to concerns about the sustainability of current extraction and processing technologies for efficient lithium recovery. This comprehensive review explores global trends in lithium processing, focusing on spodumene beneficiation and extraction techniques. While highlighting well-established conventional processes, such as dense media separation (DMS), flotation, high-temperature roasting, and acid or alkali treatment, it underscores the environmental and economic challenges of these processes, particularly when applied to low-grade lithium ores, which are increasingly being targeted to meet lithium demand. Innovative methods, such as microwave irradiation, are also explored for their potential to improve process efficiency, reduce energy consumption, and minimize environmental impact, offering promising pathways to overcome the limitations of traditional lithium recovery techniques. A significant contribution of this review is its focus on the largely untapped lithium resources of Kazakhstan, presenting geological insights and the potential for sustainable development. By addressing knowledge gaps and integrating technological, eco-friendly, and regional development perspectives, this study provides valuable insights for advancing lithium processing toward more sustainable and circular practices aligned with global climate and resource efficiency goals. Full article

The digital transformation of enterprises constitutes a crucial element of modernization processes in the countries of the European Union, supporting the achievement of sustainable development goals through increased innovation, economic efficiency and the development of high-tech sectors and knowledge-intensive services. In empirical analyses, multidimensional statistical analysis methods were applied, with particular emphasis on linear ordering, classification methods and regression analysis. Ten monitoring indicators adopted by the European Union constitute the basis for assessing the digital transformation advancement of enterprises. The study classified EU countries into three groups according to the level of digital transformation: low, medium and high. Based on the employment structure in high-tech manufacturing, medium–high-tech manufacturing and knowledge-intensive services, four distinct types of employment structures were identified. A positive relationship was found between the level of digital transformation and the share of employment in knowledge-intensive services, while no significant relationship was observed for the other sectors. The study shows that the EU countries are clearly differentiated both in terms of the level of digital transformation of enterprises and the structure of employment in high-tech manufacturing, medium–high-tech manufacturing and knowledge-intensive services. A higher level of digital transformation supports the growth of employment in knowledge-intensive services, while its impact on high-tech and medium–high-tech manufacturing remains limited. Full article

This paper examines the firm-level carbon intensity of 83 constituent stocks in the Hang Seng Index, constructs two distinct indexes from the 20 firms with the highest and lowest carbon intensities, and analyzes the connectedness of their annualized daily volatilities with four key external factors over the past 15 years. Our findings reveal that low-carbon stocks—often represented by high-tech and financial firms—tend to exhibit higher volatility, reflecting their more dynamic business environments and greater sensitivity to changes in revenue and profitability. In contrast, high-carbon companies, such as those in the utilities and energy sectors, display more stable demand patterns and are generally less exposed to abrupt market shocks. We also find that oil price shocks result in greater volatility spillovers for low-carbon stocks. Among external influences, the U.S. stock market and Treasury yield exert the most significant spillover effects, while crude oil prices and the U.S. dollar–Chinese yuan exchange rate act as net volatility recipients. Full article

The sustainable management of organic waste is a global priority due to its environmental impact and the increasing pressure on urban and rural systems, particularly in regions with limited technological infrastructure. This study introduces and validates a comprehensive methodology based on Digital Twins (DTs) to optimize production and service systems in organic waste management. The methodology includes contextual and propositional phases and is built on a modular three-layer architecture (physical, cloud, and virtual) that enables real-time monitoring, simulation, and feedback. It was validated through a field implementation in a composting facility in Cajamarca, Colombia. The results showed a 10% increase in composting efficiency and a monthly gain of 1200 kg of compost. A statistical analysis confirmed a significant increase in process efficiency (p < 0.001) and a reduction in performance variability (p < 0.01). The return on investment reached 18,957.6% using low-cost technology. These findings demonstrate the viability and adaptability of the proposed methodology for low-tech environments and support its potential for scaling in circular economy applications across waste management and agriculture. Full article