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The global interest in environmental issues and sustainable energy has propelled extensive research in photovoltaic (PV) technologies. Brazil has emerged as one of the top ten solar energy producers and flexible PV suppliers in the world. In this context, organic photovoltaic cells (OPVs) have garnered attention due to their flexibility and ability to integrate into various surfaces, albeit facing challenges regarding lifespan and efficiency compared to silicon cells. This review examines the current state of research on OPVs and thin-film solar technologies, employing the systematic literature review methodology Proknow-C. The review includes an analysis of raw materials such as conductive polymers, fabrication processes including film deposition and encapsulation, and technological advancements that enhance the efficiency and stability of OPVs. Utilizing the Proknow-C methodology, a bibliographic portfolio was constructed to identify the current state of research in this field. Of 268 papers from major scientific databases, only 30 were deemed relevant to the theme, highlighting a significant research gap. This paper is a valuable resource for researchers, providing an updated overview and a foundation for future investigations in organic photovoltaics. The results emphasize the importance of materials such as conductive polymers and donor–acceptor molecules and the role of nanotechnology in advancing OPVs. Innovations in manufacturing techniques, such as inkjet and blade coating-based printing techniques, are shown to increase efficiency by providing precise control over film thickness and uniformity and reducing costs through lower material waste. Overall, this review highlights the necessity of further exploration and collaboration within the scientific community to address the challenges and propel advancements in organic photovoltaic cells. These advancements are crucial for transitioning to cleaner energy sources, reinforcing the ongoing significance of thin-film technologies in energy innovation. [ABSTRACT FROM AUTHOR]

This review aims to summarize the recent advancements and prevailing challenges within the realm of hydrogen storage and transportation, thereby providing guidance and impetus for future research and practical applications in this domain. Through a systematic selection and analysis of the latest literature, this study highlights the strengths, limitations, and technological progress of various hydrogen storage methods, including compressed gaseous hydrogen, cryogenic liquid hydrogen, organic liquid hydrogen, and solid material hydrogen storage, as well as the feasibility, efficiency, and infrastructure requirements of different transportation modes such as pipeline, road, and seaborne transportation. The findings reveal that challenges such as low storage density, high costs, and inadequate infrastructure persist despite progress in high-pressure storage and cryogenic liquefaction. This review also underscores the potential of emerging technologies and innovative concepts, including metal–organic frameworks, nanomaterials, and underground storage, along with the potential synergies with renewable energy integration and hydrogen production facilities. In conclusion, interdisciplinary collaboration, policy support, and ongoing research are essential in harnessing hydrogen's full potential as a clean energy carrier. This review concludes that research in hydrogen storage and transportation is vital to global energy transformation and climate change mitigation. [ABSTRACT FROM AUTHOR]

This paper explores an interesting approach to wind energy technology, focusing on a novel type of drag-driven vertical-axis wind turbines (VAWTs). Studied geometries employ rotor-shaped cross-sections, presenting a distinctive approach to harnessing wind energy efficiently. The rotor-shaped cross-section geometries are examined for their aerodynamic efficiency, showcasing the meticulous engineering behind this innovation. The drag-driven turbine shapes are analyzed for their ability to maximize energy extraction in a variety of wind conditions. A significant aspect of these turbines is their adaptability for diverse applications. This article discusses the feasibility and advantages of utilizing these VAWTs in fence configurations, offering an innovative integration of renewable energy generation with physical infrastructure. The scalability of the turbines is highlighted, enabling their deployment as a fence around residential properties or as separators between highway lanes and as energy-generating structures atop buildings. The scientific findings presented in this article contribute valuable insights into the technological advancements of rotor-shaped VAWTs and their potential impact on decentralized wind energy generation. The scalable and versatile nature of these turbines opens up new possibilities for sustainable energy solutions in both urban and residential settings, marking a significant step forward in the field of renewable energy research and technology. In particular, it was shown that among the proposed rotor geometries, the five-blade rotor was characterized by the highest efficiency and, working in a palisade configuration with a spacing of 10 mm to 20 mm, produced higher average values of the torque coefficient than the corresponding Savonius turbine. [ABSTRACT FROM AUTHOR]

This review explores the extensive applications of plants in areas of biomimetics and bioinspiration, highlighting their role in developing sustainable solutions across various fields such as medicine, materials science, and environmental technology. Plants not only serve essential ecological functions but also provide a rich source of inspiration for innovations in green nanotechnology, biomedicine, and architecture. In the past decade, the focus has shifted towards utilizing plant-based and vegetal waste materials in creating eco-friendly and cost-effective materials with remarkable properties. These materials are employed in making advancements in drug delivery, environmental remediation, and the production of renewable energy. Specifically, the review discusses the use of (nano)bionic plants capable of detecting explosives and environmental contaminants, underscoring their potential in improving quality of life and even in lifesaving applications. The work also refers to the architectural inspirations drawn from the plant world to develop novel design concepts that are both functional and aesthetic. It elaborates on how engineered plants and vegetal waste have been transformed into value-added materials through innovative applications, especially highlighting their roles in wastewater treatment and as electronic components. Moreover, the integration of plants in the synthesis of biocompatible materials for medical applications such as tissue engineering scaffolds and artificial muscles demonstrates their versatility and capacity to replace more traditional synthetic materials, aligning with global sustainability goals. This paper provides a comprehensive overview of the current and potential uses of living plants in technological advancements, advocating for a deeper exploration of vegetal materials to address pressing environmental and technological challenges. [ABSTRACT FROM AUTHOR]

Regional green energy technological innovation is an important means to alleviate economic–environmental contradictions. The purpose of this study was to explore the mechanisms of green finance, financial technology, and regional green energy technological innovation. In this study, we constructed dual machine learning models, spatial econometric models, and panel threshold effect models to investigate the effects of green finance and financial technology on regional green energy technological innovation, using panel data from 266 cities nationwide from 2009 to 2021. The research findings are as follows: (1) Both green finance and financial technology significantly promote regional green energy technological innovation. (2) Based on a spatial weight matrix embedded in economic geography, both green finance and financial technology generate positive spatial spillover effects on regional green energy technological innovation. (3) The interaction between green finance and financial technology significantly contributes to regional green energy technological innovation. Financial technology can strengthen the positive local and neighboring effects of green finance on regional green energy technological innovation. (4) Based on the threshold effect of financial technology, green finance cannot significantly promote regional green energy technological innovation when financial technology is in an underdeveloped stage. With the advancement of financial technology, green finance continues to have a positive impact on regional green energy technological innovation. Based on this analysis and our conclusions, we propose practical policy recommendations that can provide a more sustainable approach to green energy technology innovation. [ABSTRACT FROM AUTHOR]

The proposed general theory of scientific variability for technological evolution explains one of the drivers of technological change for economic progress in human society. Variability is the predisposition of the elements in systems to assume different values over time and space. In biology, the variability is basic to explaining differences and development in organisms. In economics of technical change, the effects of variability within research fields on evolutionary dynamics of related technologies are unknown. In a broad analogy with the principles of biology, suggested theoretical framework here can clarify a basic driver of technological evolution: the variability within research fields can explain the dynamics of scientific development and technological evolution. The study sees whether statistical evidence supports the hypothesis that the rate of growth of scientific and technological fields can be explained by the level of variability within scientific fields. The validation is based on emerging research fields in quantum technologies: quantum imaging, quantum meteorology, quantum sensing, and quantum optics. Statistical evidence seems in general to support the hypothesis stated that the rate of growth can be explained by the level of scientific variability within research fields, measured with the relative entropy (indicating the dispersion of scientific topics in a research field underlying a specific technology). Nonparametric correlation with Spearman's rho shows a positive coefficient of 0.80 between entropy measures and rates of growth between scientific and technological fields. The linear model of the relation between rate of growth and scientific variability reveals a coefficient of regression equal to 1.63 (R2 = 0.60). The findings here suggest a general law that variability within research fields positively drives scientific development and technological evolution. In particular, a higher variability within research fields can support a high rate of growth in scientific development and technological evolution. The proposed general theory of scientific variability is especially relevant in turbulent environments of technology-based competition to clarify a basic determinant of technological development to design strategies of technological forecasting and management of promising innovations. [ABSTRACT FROM AUTHOR]

With the rapid advancement of urban intelligence, there is an increasingly urgent demand for technological innovation in traffic management. License plate recognition technology can achieve high accuracy under ideal conditions but faces significant challenges in complex traffic environments and adverse weather conditions. To address these challenges, we propose the enhanced attention network and decoding for license plate recognition model (EAND-LPRM). This model leverages an encoder to extract features from image sequences and employs a self-attention mechanism to focus on critical feature information, enhancing its capability to handle complex traffic scenarios such as rainy weather and license plate distortion. We have curated and utilized publicly available datasets that closely reflect real-world scenarios, ensuring transparency and reproducibility. Experimental evaluations conducted on these datasets, which include various complex scenarios, demonstrate that the EAND-LPRM model achieves an accuracy of 94%, representing a 6% improvement over traditional license plate recognition algorithms. The main contributions of this research include the development of a novel attention-mechanism-based architecture, comprehensive evaluation on multiple datasets, and substantial performance improvements under diverse and challenging conditions. This study provides a practical solution for automatic license plate recognition systems in dynamic and unpredictable environments. [ABSTRACT FROM AUTHOR]

This paper investigates the complex relationship between technology, religion, and sacrifice, positing this last term as a pivotal concept for understanding the evolution and impact of technological advancements. Through a detailed examination of various cultural and religious frameworks, it explores how artificial intelligence and other modern technologies both challenge and redefine traditional notions of the sacred and the profane. By analyzing historical and contemporary practices, the study highlights the paradoxical role of sacrifice in the digital age, serving as both a metaphor for the loss inherent in technological progress and a foundational principle that shapes the ethical landscapes of innovation. [ABSTRACT FROM AUTHOR]

Carbon emission intensity is an important index reflecting an entity's low-carbon competitiveness. This paper presents an extended logarithmic mean divisia index (LMDI) model to dissect carbon intensity within China's civil aviation from 1998 to 2019, revealing a significant reduction in CO2 emissions per air transport revenue. It attributes this decrease to technological advancements, optimized fleet structures, and improved operational efficiencies, highlighting the impact of larger, more efficient aircraft and enhanced load factors. The study also explores economic factors influencing carbon efficiency, suggesting a comprehensive approach encompassing technological innovation and strategic operational improvements for sustainable aviation development. [ABSTRACT FROM AUTHOR]

This study explores the impact of digital transformation on Korean society by analyzing Korean social media data, focusing on the societal and economic effects triggered by advancements in digital technology. Utilizing text mining techniques and semantic network analysis, we extracted key terms and their relationships from online news and blogs, identifying major themes related to digital transformation. Our analysis, based on data collected from major Korean portals using various related search terms, provides deep insights into how digital evolution influences individuals, businesses, and government sectors. The findings offer a comprehensive view of the technological and social trends emerging from digital transformation, including its policy, economic, and educational implications. This research not only sheds light on the understanding and strategic approaches to digital transformation in Korea but also demonstrates the potential of social media data in analyzing the societal impact of technological advancements, offering valuable resources for future research in effectively navigating the era of digital change. [ABSTRACT FROM AUTHOR]

Sustainable rural development forms a robust foundation for economic and social sustainability. Moreover, the digital economy acts as a catalyst for advancing rural sustainable development by altering the distribution of production factors. Thus, this study concentrates on 30 provinces in China, constructing an evaluation index system for both the digital economy and rural sustainable development. The study employs various methods and models to analyze the spatiotemporal changes and driving factors affecting the coupling and coordination between these two aspects. The research findings are as follows: the coupling and coordination levels among provinces in China have been on the rise year by year. By 2022, the coupling and coordination levels of most provinces range between 0.5 and 0.6. Regional disparities are the primary determinant of the poor overall coupling and coordination level in China. In 2022, the coupling and coordination level in the eastern region is 0.6663, compared to 0.5420 in the central region and 0.5087 in the western region. Factors such as urbanization, industrial structure transformation, technological innovation, higher education, economic development, and government support significantly influence the coupling and coordination level. Nevertheless, their effects vary across regions, with a more pronounced impact in the eastern region than in the central and western regions. Therefore, this paper proposes policy recommendations, including infrastructure optimization, rural digitization promotion, regional resource allocation enhancement, cross-regional development mechanism exploration, and differentiated development strategy implementation. [ABSTRACT FROM AUTHOR]

Scientific and technological innovation and ecological progress are important forces for China's high-quality development. Nevertheless, the current body of research seldom explores the mutual dependence and evolutionary patterns of the two regional systems when considering both historical and future perspectives. This paper aims to enhance the current theoretical research framework by focusing on the coastal region of China. It analyzes and predicts the co-evolution and space–time distribution process of two systems by constructing a coupled model and a gray prediction model. The results show the following: (1) the coupling and coordinated development level of the two coastal systems has basically reached the stage of good coupling and coordinated development, and the level has increased, but the gap has gradually increased, and Jiangsu and Guangdong have reached the leading level; (2) the spatial distribution in coastal areas is uneven, showing a convex spatial pattern of "high in the middle and low at both ends"; (3) during the forecast period, the overall coupling and coordination level of the two systems will continue to improve, but individual cities still cannot jump out of the development state of slow development processes. With the aim of fostering the harmonious growth of both systems at both regional and national levels, this paper proposes practical recommendations concerning the establishment of a sustainable interaction mechanism, the evolution of the industrial structure towards ecological sustainability, and the economic contribution to scientific and technological innovation. Furthermore, this article serves as a valuable reference for advancing the sustainable development of other nations. [ABSTRACT FROM AUTHOR]

From powering our homes to driving our economies, energy lies at the heart of humanity's complex challenges in the modern era. This paper reviews the evolution of smart energy systems, examining their technological advancements and societal implications while proposing a future design framework emphasizing four key pillars: holistic resource optimization, adaptive intelligence, environmental harmony, and human-centered design. While they offer numerous benefits, such as enhanced energy efficiency and reduced carbon emissions, smart energy systems also face challenges. These include cybersecurity risks, the complexity of integrating diverse energy sources seamlessly, high upfront costs, and potential compatibility issues arising from evolving technologies. Overcoming these challenges will be crucial for unleashing the full potential of smart energy systems and facilitating their global adoption. Abundant opportunities for further research and development exist in this domain, awaiting exploration and advancement. [ABSTRACT FROM AUTHOR]

This study introduces a new automated system that blends multi-satellite information and citizen science data for reliable and timely observations of lake and river ice in under-observed northern regions. The system leverages the Google Earth Engine resources to facilitate the analysis and visualization of ice conditions. The adopted approach utilizes a combination of moderate and high-resolution optical data, along with radar observations. The results demonstrate the system's capability to accurately detect and monitor river ice, particularly during key periods, such as the freeze-up and the breakup. The integration citizen science data showed added values in the validation of remote sensing products, as well as filling gaps whenever satellite observations cannot be collected due to cloud obstruction. Moreover, it was shown that citizen science data can be converted to valuable quantitative information, such as the case of ice thickness, which is very useful when combined with ice extent derived from remote sensing. In this study, citizen science data were employed for the quantitative assessment of the remote sensing product. Obtained results showed a good agreement between the product and observed river status, with a Critical Success Index of 0.82. Notably, the system has shown effectiveness in capturing the spatial and temporal evolution of snow and ice conditions, as evidenced by its application in analyzing specific ice jam events in 2023. The study concludes that the developed system marks a significant advancement in river ice monitoring, combining technological innovation with community engagement. [ABSTRACT FROM AUTHOR]

Energy storage systems are essential in modern energy infrastructure, addressing efficiency, power quality, and reliability challenges in DC/AC power systems. Recognized for their indispensable role in ensuring grid stability and seamless integration with renewable energy sources. These storage systems prove crucial for aircraft, shipboard systems, and electric vehicles, addressing peak load demands economically while enhancing overall system reliability and efficiency. Recent advancements and research have focused on high-power storage technologies, including supercapacitors, superconducting magnetic energy storage, and flywheels, characterized by high-power density and rapid response, ideally suited for applications requiring rapid charging and discharging. Hybrid energy storage systems and multiple energy storage devices represent enhanced flexibility and resilience, making them increasingly attractive for diverse applications, including critical loads. This paper provides a comprehensive overview of recent technological advancements in high-power storage devices, including lithium-ion batteries, recognized for their high energy density. In addition, a summary of hybrid energy storage system applications in microgrids and scenarios involving critical and pulse loads is provided. The research further discusses power, energy, cost, life, and performance technologies. [ABSTRACT FROM AUTHOR]

Chinese traditional fermented seasonings, essential to the culinary heritage of China, are produced through fermentation, resulting in a diverse range of unique flavors and aromas. The microorganisms involved in fermentation play significant roles in shaping the quality of these traditional fermented seasonings. The production of traditional fermented seasonings is affected by various biological and abiotic factors, presenting challenges concerning product quality and safety. This review investigates the impact of bioaugmentation technology on key Chinese traditional fermented seasonings, such as vinegar, soy sauce, sufu, doubanjiang, dajiang, and douchi. Additionally, the challenges and constraints linked to the implementation of bioaugmentation technology are discussed. The potential of bioaugmentation is highlighted by its ability to shorten the fermentation time, optimize raw material utilization, improve nutritional value, and enhance the quality parameters of these seasonings. This paper demonstrates an interesting convergence of traditional culinary heritage and contemporary technological advancements. [ABSTRACT FROM AUTHOR]

This review focuses on the complex connections between machine learning, mechatronics, and stretch forming, offering valuable insights that can lay the groundwork for future research. It provides an overview of the origins and fundamentals of these fields, emphasizes notable progress, and explores the influence of these fields on society and industry. Also highlighted is the progress of robotics research and particularities in the field of sheet metal forming and its various applications. This review paper focuses on presenting the latest technological advancements and the integrations of these fields from their beginnings to the present days, providing insights into future research directions. [ABSTRACT FROM AUTHOR]

In agriculture, the intricate relationship between innovation, productivity, and entrepreneurship is underexplored. Despite the widely recognized role of innovation in driving productivity, concrete indicators and comprehensive farm-level studies are lacking. This research aims to unravel this complexity by exploring the impact of innovation, specifically in agricultural entrepreneurship, on transformative changes in farm productivity. The work presented in this manuscript explores how farm-level data derived from the Farm Business Survey (FBS) for the period between 2003 and 2014 is used to identify innovators and to assesses changes in productivity, technical efficiency, and economic efficiency. Therefore, it aims to contribute to comprehensively exploring the role of innovation, particularly within the context of entrepreneurship in agriculture, and its influence on driving transformative changes in farm productivity. Results reveal significant productivity variation and a moderate overall improvement. Furthermore, investment in human resources, particularly managerial input, significantly enhances farm productivity across various models, indicating experienced managers utilize technology effectively. Notably, management and human capital innovation drive positive productivity changes in the UK cereal sector for the period 2003–2014, surpassing technological advancements. Efficient farmers leverage experience to benefit from operational scale changes, emphasizing the importance of accumulated knowledge. Hence, policy interventions should recognize these nuances; while promoting vocational training aids technology adoption, it may not spur management innovation. Thus, strategies must balance various aspects to effectively foster innovation in agriculture, considering both technological and managerial advancements for sustained productivity growth. The study advocates for a departure from the 'bigger is better' mentality, proposing educational programs and support services to encourage informed decision-making. This forward-looking approach aims to inform future policies and enhance understanding of the intricate dynamics between agricultural innovation, productivity, and entrepreneurship. [ABSTRACT FROM AUTHOR]

Patents as proxy for technological trends is well noted. The rapid increase of patents in China, however, has aroused debates on its technological progress: 'few original innovations' are produced in advanced areas, and true 'breakthroughs' are disproportionate to the quantity of the applications. As different technological fields contributions vary to technological progress, a nuanced understanding towards technological composition is in need to help reveal China's strength in technological innovation. This research takes the Yangtze River Delta (YRD), one of China's most inventive city-regions, as an epitome to examine the issue via three steps: (1) valid patent inventions applied from 2010 to 2018 are sorted to capture the concentration and colocation features of 35 technological fields defined by the World Intellectual Property Organization (WIPO); (2) four types (intensive, extensive, distinctive, and supportive) of technologies exemplifying technology intensity and interactivity are identified by the cross-classification method and further analyzed by spatial autocorrelation; (3) how urban factors relate to innovation of these four types of technologies are explored. This research unveils a mixed but polarized structure of technological composition in the YRD where the spatial concentration of technologies is as analogous to the nation's but colocation is not; though quite a few technologies fall into the intensive (usually high-tech) category which assumes to be more likely to breed 'breakthroughs', their numbers are limited and far less than extensive (usually labor intensive) or supportive. Knowledge exchange is frequent in core inventive cities where economic performance measured by GDP is most eminently linked to patent inventions of categorized technologies, the exception is intensive technology for which the significance of university students overrides other factors. [ABSTRACT FROM AUTHOR]

The Industry 5.0 paradigm has a human-centered vision of the industrial scenario and foresees a close collaboration between humans and robots. Industrial manufacturing environments must be easily adaptable to different task requirements, possibly taking into account the ergonomics and production line flexibility. Therefore, external sensing infrastructures such as cameras and motion capture systems may not be sufficient or suitable as they limit the shop floor reconfigurability and increase setup costs. In this paper, we present the technological advancements leading to the realization of ProxySKIN, a skin-like sensory system based on networks of distributed proximity sensors and tactile sensors. This technology is designed to cover large areas of the robot body and to provide a comprehensive perception of the surrounding space. ProxySKIN architecture is built on top of CySkin, a flexible artificial skin conceived to provide robots with the sense of touch, and arrays of Time-of-Flight (ToF) sensors. We provide a characterization of the arrays of proximity sensors and we motivate the design choices that lead to ProxySKIN, analyzing the effects of light interference on a ToF, due to the activity of other sensing devices. The obtained results show that a large number of proximity sensors can be embedded in our distributed sensing architecture and incorporated onto the body of a robotic platform, opening new scenarios for complex applications. [ABSTRACT FROM AUTHOR]

Federated learning (FL) is a machine learning (ML) technique that enables collaborative model training without sharing raw data, making it ideal for Internet of Things (IoT) applications where data are distributed across devices and privacy is a concern. Wireless Sensor Networks (WSNs) play a crucial role in IoT systems by collecting data from the physical environment. This paper presents a comprehensive survey of the integration of FL, IoT, and WSNs. It covers FL basics, strategies, and types and discusses the integration of FL, IoT, and WSNs in various domains. The paper addresses challenges related to heterogeneity in FL and summarizes state-of-the-art research in this area. It also explores security and privacy considerations and performance evaluation methodologies. The paper outlines the latest achievements and potential research directions in FL, IoT, and WSNs and emphasizes the significance of the surveyed topics within the context of current technological advancements. [ABSTRACT FROM AUTHOR]

In recent years, significant advancements in the field of machine learning have influenced the domain of image restoration. While these technological advancements present prospects for improving the quality of images, they also present difficulties, particularly the proliferation of manipulated or counterfeit multimedia information on the internet. The objective of this paper is to provide a comprehensive review of existing inpainting algorithms and forgery detections, with a specific emphasis on techniques that are designed for the purpose of removing objects from digital images. In this study, we will examine various techniques encompassing conventional texture synthesis methods as well as those based on neural networks. Furthermore, we will present the artifacts frequently introduced by the inpainting procedure and assess the state-of-the-art technology for detecting such modifications. Lastly, we shall look at the available datasets and how the methods compare with each other. Having covered all the above, the outcome of this study is to provide a comprehensive perspective on the abilities and constraints of detecting object removal via the inpainting procedure in images. [ABSTRACT FROM AUTHOR]

This research provides a comprehensive analysis of the dynamic interplay between agent-based modeling (ABM) and artificial intelligence (AI) through a meticulous bibliometric study. This study reveals a substantial increase in scholarly interest, particularly post-2006, peaking in 2021 and 2022, indicating a contemporary surge in research on the synergy between AI and ABM. Temporal trends and fluctuations prompt questions about influencing factors, potentially linked to technological advancements or shifts in research focus. The sustained increase in citations per document per year underscores the field's impact, with the 2021 peak suggesting cumulative influence. Reference Publication Year Spectroscopy (RPYS) reveals historical patterns, and the recent decline prompts exploration into shifts in research focus. Lotka's law is reflected in the author's contributions, supported by Pareto analysis. Journal diversity signals extensive exploration of AI applications in ABM. Identifying impactful journals and clustering them per Bradford's Law provides insights for researchers. Global scientific production dominance and regional collaboration maps emphasize the worldwide landscape. Despite acknowledging limitations, such as citation lag and interdisciplinary challenges, our study offers a global perspective with implications for future research and as a resource in the evolving AI and ABM landscape. [ABSTRACT FROM AUTHOR]

The pandemic caused by COVID-19 impacted the entire world, but technological progress led to the appearance of new and innovative emerging technologies (ETs). These technologies proved to have a wide potential for use as support in education, but being a new technology, certain complications arose when it came to their application in the educational model. Nowadays, there are many digital technologies, so it is necessary to identify those that can be used in today's education. Digital technologies have been implemented in all types of sectors, one of them being education, and the use of these technologies translates into significant improvements in educational processes and learning outcomes. Despite this, there is currently little research on the use of ETs as a support in the academic process. This research uses systematic mapping (SM) of the last 5 years, together with the Unified Theory of Acceptance and Use of Technology (UTAUT) model to identify the use and acceptance of ETs in higher education. For the SM, a keyword search string was used in three scientific databases (Scopus, Web of Science, and IEEE Xplore). To apply the UTAUT, a survey was conducted with 120 students on the acceptance of ETs as support in higher education. The results obtained indicate that ETs provide some optimization of educational processes, with greater immersion and application of knowledge when using technologies such as augmented reality, virtual reality, and mobile learning. Likewise, ETs can motivate students, allowing them to reach new academic and professional achievements. [ABSTRACT FROM AUTHOR]

Building construction accounts for a significant proportion of global greenhouse gas emissions, raw material extraction, and waste production. Applying circular economy (CE) principles in the building construction industry would considerably reduce these values. However, uptake by the industry is relatively slow, which is largely attributed to sectoral barriers, including limitations in knowledge and experience. This review paper aims to assess and contribute to diminishing these obstacles by offering a comprehensive review of circular material usage principles and strategies within the construction sector. Opportunities and facilitators of change are also presented, including innovations and emerging technologies in recycling, digitization, robotic systems, novel materials, and processing. Finally, four case studies demonstrate the application of circular theory via a novel block system, recycled aggregate, modular kitchen reuse, and an energy efficiency retrofit. The conclusions show that future efforts should prioritize the development of strong regulatory frameworks, awareness initiatives, and international cooperation. In this regard, the integration of technological advancements, such as AI, robotics, and blockchain, is essential for optimizing waste management efficiency. Furthermore, education on circular practices plays a critical role. Through global collaboration, standardizing circular construction approaches can promote a more sustainable and resilient building construction industry. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries (LIBs) are a widely used energy storage technology as they possess high energy density and are characterized by the reversible intercalation/deintercalation of Li ions between electrodes. The rapid development of LIBs has led to increased production efficiency and lower costs for manufacturers, resulting in a growing demand for batteries and their application across various industries, particularly in different types of vehicles. In order to meet the demand for LIBs while minimizing climate-impacting emissions, the reuse, recycling, and repurposing of LIBs is a critical step toward achieving a sustainable battery economy. This paper provides a comprehensive review of lithium-ion battery recycling, covering topics such as current recycling technologies, technological advancements, policy gaps, design strategies, funding for pilot projects, and a comprehensive strategy for battery recycling. Additionally, this paper emphasizes the challenges associated with developing LIB recycling and the opportunities arising from these challenges, such as the potential for innovation and the creation of a more sustainable and circular economy. The environmental implications of LIB recycling are also evaluated with methodologies able to provide a sustainability analysis of the selected technology. This paper aims to enhance the comprehension of these trade-offs and encourage discussion on determining the "best" recycling route when targets are in conflict. [ABSTRACT FROM AUTHOR]

With the significant role that Unmanned Surface Vessels (USVs) could play in industry, the military and the transformation of ocean engineering, a growing research interest in USVs is attracted to their innovation, new technology and automation. Yet, there has been no comprehensive review grounded in bibliometric analysis, which concentrates on the most recent technological advancements and developments in USVs. To provide deeper insight into the relevant research trends, this study employs a bibliometric analysis to examine the basic features of the literature from 2000 to 2023, and identifies the key research hotspots and modeling techniques by reviewing their current statuses and the recent efforts made in these areas. Based on the analysis of the temporal and spatial trends, disciplines and journals' distribution, institutions, authors and citations, the publications relating to the new technology of USVs are assessed based on their keywords and the term analysis in the literature; six future research directions are proposed, including enhanced intelligence and autonomy, highly integrated sensor systems and multi-modal task execution, extended endurance and resilience, satellite communication and interconnectivity, eco-friendly and sustainable practices and safety and defense. The scientific literature is reviewed in a systematic way using a comparative analysis of existing tools, and the results greatly contribute to understanding the overall situation of new technology in USVs. This paper is enlightening to students, international scholars and institutions, as it can facilitate partnerships between industry and academia to allow for concerted efforts to be made in the domain of USVs. [ABSTRACT FROM AUTHOR]

Bio-mechatronics is an interdisciplinary scientific field that emphasizes the integration of biology and mechatronics to discover innovative solutions for numerous biomedical applications. The broad application spectrum of bio-mechatronics consists of minimally invasive surgeries, rehabilitation, development of prosthetics, and soft wearables to find engineering solutions for the human body. Fiber-optic-based sensors have recently become an indispensable part of bio-mechatronics systems, which are essential for position detection and control, monitoring measurements, compliance control, and various feedback applications. As a result, significant advancements have been introduced for designing and developing fiber-optic-based sensors in the past decade. This review discusses recent technological advancements in fiber-optical sensors, which have been potentially adapted for numerous bio-mechatronic applications. It also encompasses fundamental principles, different types of fiber-optical sensors based on recent development strategies, and characterizations of fiber Bragg gratings, optical fiber force myography, polymer optical fibers, optical tactile sensors, and Fabry–Perot interferometric applications. Hence, robust knowledge can be obtained regarding the technological enhancements in fiber-optical sensors for bio-mechatronics-based interdisciplinary developments. Therefore, this review offers a comprehensive exploration of recent technological advances in fiber-optical sensors for bio-mechatronics. It provides insights into their potential to revolutionize biomedical and bio-mechatronics applications, ultimately contributing to improved patient outcomes and healthcare innovation. [ABSTRACT FROM AUTHOR]

Due to a growing number of environmental issues, including global warming, water scarcity, and fossil fuel depletion, the topic of modern materials in energy is becoming crucial for our civilization. The technological advancements that have been observed bring many innovations that significantly impact how energy can be generated, stored, and distributed. Moreover, new opportunities have emerged in energy and materials engineering due to the increasing computational capability of current data processing systems. Methods that are highly demanding, time-consuming, and difficult to apply may now be considered when developing complete and sophisticated models in many areas of science and technology. Combining computational methods and AI algorithms allows for multi-threaded analyses solving advanced and interdisciplinary problems. Therefore, knowledge and experience in this subject, as well as the investigation of new, more efficient, and environmentally friendly solutions, currently represent one of the main directions of scientific research. The Special Issue "Advances in Materials: Modelling Challenges and Technological Progress for Green Engineering and Sustainable Development" aims to bring together research on material advances, focusing on modelling challenges and technological progress (mainly for green engineering and sustainable development). Original research studies, review articles, and short communications are welcome, especially those focusing on (but not limited to) artificial intelligence, other computational methods, and state-of-the-art technological concepts related to the listed keywords within energy and materials engineering. [ABSTRACT FROM AUTHOR]

There is still a significant gap between most high-tech fields in China and developed countries, and the relationship between the economic resilience of innovation systems and the innovation capability of the high-tech industry has received attention. Using data from 30 provinces in China, this study adopts the fuzzy-set qualitative comparative analysis approach to analyze the relationship between economic resilience and high-tech industry innovation capability, and the findings are as follows: (1) Technological talents and economic development are necessary conditions for explaining the high innovation capability of high-tech industries. (2) The combination of economic resilience and different factors constitutes the equivalent configuration of two high innovation capabilities and four low innovation capabilities. (3) Under high-intensity technological competition between governments, the increased agglomeration of technological talents, and high-quality economic development, the strengthening of economic resilience is conducive to enhancing the innovation capability of high-tech industries. (4) Under low-intensity technological competition between governments, a well-developed technology market, and increased agglomeration of technological talents, the strengthening of economic resilience is adverse to enhancing the innovation capability of high-tech industries. The main contribution of this study is to clarify the configuration mechanism of economic resilience that acts on the innovation capability of the high-tech industry and reveal the complex interaction between economic resilience and multiple factors. [ABSTRACT FROM AUTHOR]

New innovations within spine surgery continue to propel the field forward. These technologies improve surgeons' understanding of their patients and allow them to optimize treatment planning both in the operating room and clinic. Additionally, changes in the implants and surgeon practice habits continue to evolve secondary to emerging biomaterials and device design. With ongoing advancements, patients can expect enhanced preoperative decision-making, improved patient outcomes, and better intraoperative execution. Additionally, these changes may decrease many of the most common complications following spine surgery in order to reduce morbidity, mortality, and the need for reoperation. This article reviews some of these technological advancements and how they are projected to impact the field. As the field continues to advance, it is vital that practitioners remain knowledgeable of these changes in order to provide the most effective treatment possible. [ABSTRACT FROM AUTHOR]

Immersive technologies are revolutionary technological advancements that offer users unparalleled experiences of immersion in a virtual or mixed world of virtual and real elements. In such technology, user privacy, security, and anonymity are paramount, as users often share private and sensitive information. Therefore, user authentication is a critical requirement in these environments. This paper presents a systematic literature review of recently published research papers on immersive technology-based user authentication mechanisms. After conducting the literature search in September 2023 using Scopus, the selection process identified 36 research publications that were further analyzed. The analysis revealed three major types of authentications related to immersive technologies, consistent with previous works: knowledge-based, biometric, and multi-factor methods. The reviewed papers are categorized according to these groups, and the methods used are scrutinized. To the best of our knowledge, this systematic literature review is the first that provides a comprehensive consolidation of immersive technologies for user authentication in virtual, augmented, and mixed reality. [ABSTRACT FROM AUTHOR]

The rapid economic growth of China has caused significant adverse effects on the environment. Meanwhile, technological innovation, a fundamental driver of economic development and social progress, plays a pivotal role in mitigating haze pollution. This study comprehensively examines the influence of technological innovation on haze pollution in the Yangtze River urban agglomeration, using the STIRPAT model and analyzing research data from 2004 to 2020. Additionally, the study investigates the specific moderating role of urban spatial structure in the relationship between technological innovation and haze pollution. The findings reveal that technological innovation in the middle reaches of the Yangtze River urban agglomeration can effectively curtail haze pollution, and its impact extends to surrounding areas through spillover effect. The polycentric urban spatial structure significantly enhances the haze-reducing effect of technological innovation in the region. Notably, in cities with a strong level of environmental regulation, the urban spatial structure plays a substantial role in augmenting the haze-reducing impact of technological innovation. The policy implications of this research underscore the importance of continuous improvement in technological innovation within the middle reaches of the Yangtze River urban agglomeration. To address haze pollution in future development, the adoption of a polycentric development strategy and the establishment of sound environmental governance policies are recommended. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) technology and devices represent an exciting field in computer science that is rapidly emerging worldwide. The demand for automation and efficiency has also been a contributing factor to the advancements in this technology. The proliferation of IoT devices coincides with advancements in wireless networking technologies, driven by the enhanced connectivity of the internet. Today, nearly any everyday object can be connected to the network, reflecting the growing demand for automation and efficiency. This paper reviews the emergence of IoT devices, analyzed their common applications, and explored the future prospects in this promising field of computer science. The examined applications encompass healthcare, agriculture, and smart cities. Although IoT technology exhibits similar deployment trends, this paper will explore different fields to discern the subtle nuances that exist among them. To comprehend the future of IoT, it is essential to comprehend the driving forces behind its advancements in various industries. By gaining a better understanding of the emergence of IoT devices, readers will develop insights into the factors that have propelled their growth and the conditions that led to technological advancements. Given the rapid pace at which IoT technology is advancing, this paper provides researchers with a deeper understanding of the factors that have brought us to this point and the ongoing efforts that are actively shaping the future of IoT. By offering a comprehensive analysis of the current landscape and potential future developments, this paper serves as a valuable resource to researchers seeking to contribute to and navigate the ever-evolving IoT ecosystem. [ABSTRACT FROM AUTHOR]

An anticipated challenge for the offshore wind industry is the legally standardized decommissioning of offshore wind infrastructure after the expiration of the respective approval period. To meet the energy and climate targets set by, e.g., the German Federal Government, this challenge must be mastered in the context of sustainability. Potential concepts are (i) the deconstruction of offshore infrastructure without replacement, (ii) the continued operation of the plants, (iii) partially or even completely replacing them with newer, modernized plants (re-powering). Re-powering could also be a combination of existing infrastructures with other innovative technologies, such as hydrogen. In this work, the three concepts are analyzed along with their risks and additional factors, such as feasibility, cost-effectiveness, predictability of technological progress, and, planning security, are discussed. A quantitative risk and resilience analysis is conceptually demonstrated for the specific risk of extreme weather and wave conditions caused by climate change. Synthetic wave height data are generated and the corresponding load changes are applied to example offshore wind farms. The three end-of-life options are compared using resilience indicators that serve as exemplary measures for the energy output, which serves as the key performance indicator. [ABSTRACT FROM AUTHOR]

Innovation is the main driving force to promote national technological progress. It is of great significance to explore the optimal path to improve innovation efficiency by using the qualitative method and neural network prediction model to promote the high-quality development of the national economy. This study focuses on high-tech industries in the eastern, central and western regions of China; a factor-dependent research framework for innovation efficiency improvement in high-tech industries is constructed in China. The fuzzy-set qualitative comparative analysis method (QCA) is used to explore multiple paths to enhance the innovation efficiency of China's high-tech industries. Then, a GA-PSO-BP neural network is used to construct an optimization model for the enhancement path of technological innovation efficiency, which clarifies the optimal path for the enhancement of innovation efficiency of high-tech industries in the eastern, central and western regions of China. Finally, innovation management strategies for high-tech industries are presented with regional features. The study finds that none of the individual conditions are necessary to promote the innovation efficiency of China's high-tech industries, and only the linkage effect of the factors can achieve the goal of improving the innovation efficiency level of China's high-tech industries. There are four configuration paths to improve the innovation efficiency of China's high-tech industries, which are: "Multinational company (MNC) innovation—economic development—government support"; "MNC innovation—government support"; "economic development—government support"; and "economic development". The characteristics of regional heterogeneity make differences in the optimal paths of innovation efficiency improvement in high-tech industries in eastern, central and western regions of China. [ABSTRACT FROM AUTHOR]

Improving the digital economy and environmental governance efficiency are important methods for current high-quality economic development. Based on the panel data of 11 cities in Zhejiang, on the eastern coast of China, fine particulate matter smaller than a 2.5 μm (PM2.5) environmental efficiency (PMEE) was measured by the undesirable output Slack-Based Measure-Data Envelopment Analysis (SBM-DEA) model. The fixed effect regression model, the divergences in the difference model and other empirical methods were obtained to test the driving mechanism of social-economic factors on the PMEE. The results showed that: (1) the concentration of PM2.5 was continually decreasing, and environmental quality experienced a continuous improvement in Zhejiang province in the observation period, although cities such as Hangzhou, Jiaxing and Shaoxing have relatively severe PM2.5 pollution. (2) The total average value of PMEE in Zhejiang was 0.6430 over the observation period, while there was still a lot of room for improvement when compared to the production frontier. Additionally, PMEE in each city showed a fluctuating growth trend. Cities with a higher PMEE were mainly Zhoushan, Hangzhou and Ningbo. (3) The level of the digital economy had a positive role in promoting the PMEE, which was statistically significant. The level of pollution control and technological innovation also had a significantly positive effect. However, the ratio of the industrial output value to the gross domestic product (GDP) presented a negative effect on the PMEE. In the future, it is suggested that the development of the urban digital economy should be accelerated in an all-around way to improve the efficiency of government pollution control and to improve the technical efficiency of PM2.5 via innovative technological progress. [ABSTRACT FROM AUTHOR]

Cyber threats are projected to cause USD 10.5 trillion in damage to the global economy in 2025. Comprehending the level of threat is core to adjusting cyber posture at the personal, organizational, and national levels. However, representing the threat level with a single score is a daunting task if the scores are generated from big and complex data sources such as social media. This paper harnesses the modern technological advancements in artificial intelligence (AI) and natural language processing (NLP) to comprehend the contextual information of social media posts related to cyber-attacks and electronic warfare. Then, using keyword-based index generation techniques, a single index is generated at the country level. Utilizing a convolutional neural network (CNN), the innovative process automatically detects any anomalies within the countrywide threat index and explains the root causes. The entire process was validated with live Twitter feeds from 14 October 2022 to 27 December 2022. During these 75 days, AI-based language detection, translation, and sentiment analysis comprehended 15,983 tweets in 47 different languages (while most of the existing works only work in one language). Finally, 75 daily cyber threat indexes with anomalies were generated for China, Australia, Russia, Ukraine, Iran, and India. Using this intelligence, strategic decision makers can adjust their cyber preparedness for mitigating the detrimental damages afflicted by cyber criminals. [ABSTRACT FROM AUTHOR]

In network management, network measuring is crucial. Accurate network measurements can increase network utilization, network management, and the ability to find network problems promptly. With extensive technological advancements, the difficulty for network measurement is not just the growth in users and traffic but also the increasingly difficult technical problems brought on by the network's design becoming more complicated. In recent years, network feature measurement issues have been extensively solved by the use of ML approaches, which are ideally suited to thorough data analysis and the investigation of complicated network behavior. However, there is yet no favored learning model that can best address the network measurement issue. The problems that ML applications in the field of network measurement must overcome are discussed in this study, along with an analysis of the current characteristics of ML algorithms in network measurement. Finally, network measurement techniques that have been used as ML techniques are examined, and potential advancements in the field are explored and examined. [ABSTRACT FROM AUTHOR]

To achieve carbon neutrality and improve emission reduction efficiency, capturing carbon dioxide from the air on a large scale and promoting the application and innovation of carbon capture technology (CCUS) are the most important goals. This study undertakes an annual and comprehensive evaluation of the policy and the technological innovation efficiency (TIE) of 10 listed companies in China using the DEA model and the Malmquist index analysis method. The number of relevant laws and policies is significant, but they are not well coordinated. The static evaluation results indicate that the complete factor production rate is low, generally lower than 0.9, and the technical innovation efficiency is weak, mainly because of technological backwardness. The dynamic evaluation results indicate that the changes in total factor productivity (TFP) each year are primarily affected by changes in technological progress. This suggests that most domestic enterprises are still exploring technological innovation (TI) and operational business models. Finally, this study proposes measures to improve the TIE of carbon capture technology enterprises in China, including giving full play to the role of the government, expanding effective investment, and improving innovational ability. [ABSTRACT FROM AUTHOR]

In the realm of the emergence and spread of infectious diseases with pandemic potential throughout the history, plenty of pandemics (and epidemics), from the plague to AIDS (1981) and SARS (in 2003) to the bunch of COVID variants, have tormented mankind. Though plenty of technological innovations are overwhelmingly progressing to curb them—a significant number of such pandemics astounded the world, impacting billions of lives and posing uncovered challenges to healthcare organizations and clinical pathologists globally. In view of addressing these limitations, a critically exhaustive review is performed to signify the prospective role of technological advancements and highlight the implicit problems associated with rendering best quality lifesaving treatments to the patient community. The proposed review work is conducted in two parts. Part 1 is essentially focused upon discussion of advanced technologies akin to artificial intelligence, Big Data, block chain technology, open-source technology, cloud computing, etc. Research works governing applicability of these technologies in solving many uncovered healthcare issues prominently faced by doctors and surgeons in the fields of cardiology, medicine, neurology, orthopaedics, paediatrics, gynaecology, psychiatry, plastic surgery, etc., as well as their role in curtailing the spread of numerous infectious, pathological, neurotic maladies is thrown light off. Boundary conditions and implicitly associated challenges substantiated by remedies coupled with future directions are presented at the end. [ABSTRACT FROM AUTHOR]

Vehicular edge networks (VENs) connect vehicles to share data and infotainment content collaboratively to improve network performance. Due to technological advancements, data growth is accelerating, making it difficult to always connect mobile devices and locations. For vehicle-to-vehicle (V2V) communication, vehicles are equipped with onboard units (OBU) and roadside units (RSU). Through back-haul, all user-uploaded data is cached in the cloud server's main database. Caching stores and delivers database data on demand. Pre-caching the data on the upcoming predicted server, closest to the user, before receiving the request will improve the system's performance. OBUs, RSUs, and base stations (BS) cache data in VENs to fulfill user requests rapidly. Pre-caching reduces data retrieval costs and times. Due to storage and computing expenses, complete data cannot be stored on a single device for vehicle caching. We reduce content delivery delays by using the cuckoo search optimization algorithm with cooperative content caching. Cooperation among end users in terms of data sharing with neighbors will positively affect delivery delays. The proposed model considers cooperative content caching based on popularity and accurate vehicle position prediction using K-means clustering. Performance is measured by caching cost, delivery cost, response time, and cache hit ratio. Regarding parameters, the new algorithm outperforms the alternative. [ABSTRACT FROM AUTHOR]

Electrical power distribution is the most important division in the power supply chain. However, its sustainability in terms of efficiency is very important for the growth of every country. This main objective of the paper is to assess the productivity dynamics of this process using the data envelopment analysis (DEA) methodology to analyse the effectiveness of the electricity distribution regions (EDRs) over a period of 7 years. The paper adapts the biennial Malmquist productivity index by infusing it with the slacks-based measure (SBM) to assess the productivity dynamics of EDRs in Ghana. Productivity dynamics were assessed by decomposing the SBM-BMPI productivity scores into the efficiency, technology, and scale change. It was discovered that the productivity of EDRs in Ghana progressed by 16.23% per annum over the sample period. Productivity was driven mainly by technological change and not the efficiency changes and scale changes. [ABSTRACT FROM AUTHOR]

China's economic development is characterized by openness, and trade and investment are important engines for promoting economic development. China's economy is now in a transitional period, during which excessive carbon emission reduction would inevitably hinder economic development. In this context, improving carbon emission efficiency is an effective way to achieve sustainable development. This paper deals with the relationships among foreign direct investment, technological innovation and carbon emission efficiency. Our research findings include the following. First, carbon efficiency shows regional differences. East China has the highest mean value of carbon emission efficiency, followed by central China and west China over the sample period. Second, FDI exerts both direct and indirect impacts on carbon emission efficiency through technological innovation, which confirms the intermediate effect of technological innovation. Finally, sub-sample analysis indicates that the impact of FDI and technological innovation on carbon emission efficiency show regional heterogeneity. According to these findings, we offer policy recommendations as follows. The government should stimulate independent innovation, promote technological progress in renewable energy and green energy, and attract environmentally friendly foreign investment to improve carbon emission efficiency and boost green development. [ABSTRACT FROM AUTHOR]

The construction industry has experienced phenomenal growth because of technological advancements in the past couple of decades. Prefabrication constitutes a sizeable share of this industry and is being adopted all over the world. The method of casting construction elements in a controlled environment and assembling them on-site has revolutionised the industry. Research on various aspects of the technology is ongoing around the world, and an impressive number of articles have been published. However, the prefab technology, materials used, and terminology have varied across locations, which may have hindered the method's wider acceptability. By evaluating technical articles published between 1991 and 2022, this report analyses the present body of knowledge regarding prefab technology, its evolution, sustainability, and stakeholder views. This technology effectively contributes around 40% in time saving, 27% in cost reduction, 30% in reduced carbon emissions, and 84% in on-site wastage reduction. It also increases quality, gives a dependable alternative for meeting mass construction targets, is energy efficient, and provides environmentally conscious options. This paper contributes to the body of knowledge by providing a snapshot of the prefab industry spanning three decades, detailing a wide range of factors affecting the industry. [ABSTRACT FROM AUTHOR]

To achieve the harmonious development of economic growth and the environment, nations must pay more attention to wastewater treatment and boost efficiency using green technology. This study applies the Malmquist-DEA model to assess the efficiency of green technology innovation in 19 Chinese wastewater treatment companies between 2017 and 2020. In addition, focus is placed on the core wastewater treatment technology of the companies with excellent performance, indicating how wastewater treatment companies may improve their green technology. The results of the study indicate that, first, the overall effectiveness of green technology innovation in companies follows a rising and then decreasing trend. In 2020, wastewater treatment companies' green technology innovation efficiency was around 17.4 percent lower than in 2017. Improving technical progress is the key to boosting the total factor productivity of wastewater treatment companies. Second, based on the Tobit regression, the shareholding ratio of companies has a positive influence on the technical efficiency of companies. Therefore, China should increase innovation capacity and productivity, adopt current sewage treatment technology from overseas, and thus gradually achieve clean sewage utilization and ecological environment management. [ABSTRACT FROM AUTHOR]

Increasing total factor productivity is the key to promoting high-quality economic development. This paper starts with land supply as an institutional source factor and discusses the impact of the regional differentiation of land supply on total factor productivity in China. Based on the panel data of 273 cities in China from 2003 to 2017, this paper measures total factor productivity (TFP) using the DEA-Malmquist index, decomposes it into technical progress (TE), pure technical efficiency (PE) and scale efficiency (SE), and analyzes the effect of the regional differentiation of land supply on TFP using the spatial Durbin model and mediating model. This study finds the following: (1) At the national level, the tilting of land supply to the central and western regions leads to a contradiction between land supply and demand, which hinders TFP by suppressing TE, PE and SE. (2) At the regional level, the reduction in land supply in the eastern region expands the technological substitution rate, induces the substitution effect of enterprise innovation, and thus promotes TE, but inhibits PE and SE under the resource constraint and congestion effect, which hinders the improvement of TFP. The estimates for the central and western regions are generally consistent with the national results; again, as land supply increases, this hinders TFP by suppressing TE, PE and SE. (3) In terms of the mechanism of influence, the decrease in land supply in the eastern region promotes TE and TFP by promoting urban innovation and inhibiting SE through productive services agglomeration; the increase in land supply in the central and western regions hinders TE and TFP by inhibiting urban innovation, and hinders SE through manufacturing agglomeration. The conclusion of this paper has great significance for deepening the structural reform of land supply and promoting high-quality economic development. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a complex neurodegenerative disease with a multitude of disease variations including motor and non-motor symptoms. Quality of life and symptom management may be improved with physical activity. Due to technological advancement, development of small new wearable devices recently emerged and allowed objective measurement of walking activity in daily life. This review was specifically designed to synthesize literature on objective walking activity measurements using wearable devices of patients with PD. Inclusion criteria included patients with a diagnosis of PD and exclusion criteria included studies using animal models or mixed syndromes. Participants were not required to undergo any type of intervention and the studies must have reported at least one output that quantifies daily walking activity. Three databases were systematically searched with no limitation on publication date. Twenty-six studies were eligible and included in the systematic review. The most frequently used device was the ActiGraph GT3X which was used in 10 studies. Duration of monitoring presented a range from 8 h to one year. Nevertheless, 11 studies measured walking activity during a 7-day period. On-body sensor wearing location differed throughout the included studies showing eight positions, with the waist, ankle, and wrist being the most frequently used locations. The main procedures consisted of measurement of walking hours during a 2-day period or more, equipped with a triaxial accelerometer at the dominant hip or ankle. It is also important for further research to take care of different factors such as the population, their pathology, the period, and the environment. [ABSTRACT FROM AUTHOR]

This review summarizes the most recent advances from technological and physico-chemical perspectives to improve several remaining issues in polymeric materials' additive manufacturing (AM). Without a doubt, AM is experimenting with significant progress due to technological innovations that are currently advancing. In this context, the state-of-the-art considers both research areas as working separately and contributing to developing the different AM technologies. First, AM techniques' advantages and current limitations are analyzed and discussed. A detailed overview of the efforts made to improve the two most extensively employed techniques, i.e., material extrusion and VAT-photopolymerization, is presented. Aspects such as the part size, the possibility of producing parts in a continuous process, the improvement of the fabrication time, the reduction of the use of supports, and the fabrication of components using more than one material are analyzed. The last part of this review complements these technological advances with a general overview of the innovations made from a material perspective. The use of reinforced polymers, the preparation of adapted high-temperature materials, or even the fabrication of metallic and ceramic parts using polymers as supports are considered. Finally, the use of smart materials that enable the fabrication of shape-changing 3D objects and sustainable materials will also be explored. [ABSTRACT FROM AUTHOR]

Green finance integrates the concept of environmental governance into the financial industry, which is conducive to sustainable development. Applying the mediating effect model, this paper investigates the effect of green finance on urban haze pollution and explores the mediating role of technological innovation of enterprises between them. Based on a sample of 639 enterprises in China over 2016–2019, a significantly negative effect of green finance on urban haze pollution is found. An increase of one standard deviation in green finance decreases PM2.5 concentration by 8.8 μg/m3, ceteris paribus. Further, green finance may improve environmental quality by promoting technological innovation. Considering the heterogeneity of enterprise ownership, this mediating effect exists in non-state-owned enterprises, while it cannot be observed in state-owned enterprises. This study proposes a new solution for pollution: using green financial tools to promote environmentally friendly technological progress. [ABSTRACT FROM AUTHOR]