Search Results (4,628)

Using waste biomass as a raw material for the combined production of electricity and heat offers corresponding energy, economic, environmental and resource efficiency benefits. The study examines both the performance of a system for combined energy production based on the Organic Rankine Cycle (ORC) utilizing wood biomass and the market interest in its deployment within Bulgaria. Its objective is to propose a technically and economically viable solution for the recovery of waste biomass through the combined production of electricity and heat while simultaneously assessing the readiness of industrial and municipal sectors to adopt such systems. The cogeneration plant incorporates an ORC module enhanced with three additional economizers that capture residual heat from flue gases. Operating on 2 t/h of biomass, the system delivers 1156 kW of electric power and 3660 kW of thermal energy, recovering an additional 2664 kW of heat. The overall energy efficiency reaches 85%, with projected annual revenues exceeding EUR 600,000 and a reduction in carbon dioxide emissions of over 5800 t/yr. These indicators can be achieved through optimal installation and operation. When operating at a reduced load, however, the specific fuel consumption increases and the overall efficiency of the installation decreases. The marketing survey results indicate that 75% of respondents express interest in adopting such technologies, contingent upon the availability of financial incentives. The strongest demand is observed for systems with capacities up to 1000 kW. However, significant barriers remain, including high initial investment costs and uneven access to raw materials. The findings confirm that the developed system offers a technologically robust, environmentally efficient and market-relevant solution, aligned with the goals of energy independence, sustainability and the transition to a low-carbon economy. Full article

Monitoring water quality is crucial for achieving clean water and sanitation goals, particularly in remote areas. The project “Morbidity vs. Water Quality for Human Consumption in Tonosí: A Pilot Study” aimed to enhance water quality assessments in Panama using advanced analytical techniques to assess volatile organic compounds, heavy metals, and microbiological pathogens. To support this, the Technical Unit for Water Quality (UTECH) was established, featuring a novel mobile laboratory with cutting-edge technology for accurate testing, minimal chemical reagent use, reduced waste generation, and equipped with a solar-powered battery system. The aim of this paper is to explore the design, deployment, and impact of the UTECH. Furthermore, this study presents results from three sampling points in Tonosí, where several parameters exceeded regulatory limits, demonstrating the capabilities of the UTECH and highlighting the need for ongoing monitoring and intervention. The study also assesses the environmental, social, and economic impacts of the UTECH in alignment with the Sustainable Development Goals and national initiatives. Finally, a SWOT analysis illustrates the UTECH’s potential to improve water quality assessments in Panama while identifying areas for sustainable growth. The study showcases the successful integration of advanced mobile laboratory technologies into water quality monitoring, contributing to sustainable development in Panama and offering a replicable model for similar initiatives in other regions. Full article

This study investigates the relationship between the dynamic capabilities of university administration and students’ awareness of artificial intelligence (AI) tools within a higher education context. Drawing on data from 139 students at the College of Education, Sultan Qaboos University, the research employed two validated instruments, one measuring the dynamic capabilities of university administration and another assessing students’ awareness and perception of AI tool use. Understanding this relationship is critical, as universities increasingly face pressure to guide responsible and effective AI use among students. Findings reveal significant correlations between the university administration’s dynamic capabilities, particularly technological agility, and students’ engagement with AI tools. Notably, technological dynamic capabilities within the administration significantly predicted two specific dimensions of student awareness: effectiveness of using AI tools and perceived faculty members’ efficiency in AI. These results highlight the critical role of institutional leadership in promoting equitable and sustainable integration of AI in education. The study contributes to the broader discourse on AI for sustainable development by illustrating how institutional strategies can enhance innovation, inclusion, and student readiness in support of SDG 4. Full article

This paper measures the post-treatment effects of Central Bank Digital Currencies (CBDCs) on mobile money and outstanding loans from commercial banks as a percentage of the GDP in Nigeria and the Bahamas, respectively, from the perspective of financial inclusion. The literature on the topic has primarily focused on the technological specifications of CBDCs and their potential future implementation. This article addresses a gap in the empirical literature by examining the effects of CBDCs. To this end, a Synthetic Control Method (SCM) is applied to the Bahamas (SandDollar) and Nigeria (eNaira) to construct a counterfactual scenario and assess the impact of CBDCs on mobile money and commercial bank loans. Nigeria’s mobile money transactions as a percentage of the GDP increased significantly compared to the synthetic control group, suggesting a notable positive effect of the eNaira. Conversely, in the Bahamas, actual performance fell below the synthetic control, implying that SandDollar may have contributed to a decline in outstanding loans. These results suggest that CBDCs could pose a “deposit substitution risk” for commercial banks. However, they may also enhance the performance of other Fintech tools, as observed in the case of mobile money. As CBDC implementations worldwide remain in their early stages, their long-term effects require further analysis. Full article

Ultrafine bubbles (UFBs) represent an emerging technology with unique physicochemical properties. This study investigated the effects of air-filled UFBs infused in drinking water on gut microbiota composition and the associated health markers in Sprague Dawley rats over a 12-week period. Using a two-phase design, UFB concentration was increased from 1.7 × 10⁶ to 6.5 × 10⁹ UFBs/mL at week 7 to assess dose-dependent effects. Administration of UFBs in drinking water induced significant shifts in gut microbiome populations, characterized by increased Bacteroidetes (+122% weeks 8–12) and decreased Firmicutes (−43% weeks 8–12) compared to controls. These microbial shifts coincided with enhanced short-chain fatty acid production (butyrate +56.0%, p ≤ 0.001; valerate +63.1%, p ≤ 0.01) and reduced inflammatory markers (TNF-α −84.0%, p ≤ 0.05; IL-1β −41.0%, p ≤ 0.05; IL-10 −69.8%, p ≤ 0.05). UFB effects demonstrated systematic concentration-dependent threshold responses, with 85.7% of parameters exhibiting directional reversals between low (1.7 × 10⁶ UFBs/mL) and high (6.5 × 10⁹ UFBs/mL) concentration phases rather than linear dose–response relationships. The systematic nature of these threshold effects, with 71.4% of parameters achieving statistical significance (p ≤ 0.05), indicates concentration-dependent biological mechanisms rather than random effects on gut biology. Despite current metagenomic techniques identifying only 25% of the total gut microbiome, the observed changes in characterized species and metabolites demonstrate UFB technology’s therapeutic potential for conditions requiring microbiome modulation, providing new insights into UFB influence on complex biological systems. Full article

Male infertility is a multifactorial condition often associated with disruptions in sperm metabolism and mitochondrial function, yet traditional semen analysis provides limited insight into these molecular mechanisms. Understanding sperm bioenergetics and metabolic dysfunctions is crucial for improving the diagnosis and treatment of conditions such as asthenozoospermia and azoospermia. This systematic review synthesizes recent literature, focusing on advanced tools and techniques—including omics technologies, advanced imaging, spectroscopy, and functional assays—that enable comprehensive molecular assessment of sperm metabolism and development. The reviewed studies highlight the effectiveness of metabolomics, proteomics, and transcriptomics in identifying metabolic biomarkers linked to male infertility. Non-invasive imaging modalities such as Raman and magnetic resonance spectroscopy offer real-time metabolic profiling, while the seminal microbiome is increasingly recognized for its role in modulating sperm metabolic health. Despite these advances, challenges remain in clinical validation and implementation of these techniques in routine infertility diagnostics. Integrating molecular metabolic assessments with conventional semen analysis promises enhanced diagnostic precision and personalized therapeutic approaches, ultimately improving reproductive outcomes. Continued research is needed to standardize biomarkers and validate clinical utility. Furthermore, these metabolic tools hold significant potential to elucidate the underlying causes of previously misunderstood and unexplained infertility cases, offering new avenues for diagnosis and treatment. Full article

This exploratory case study investigates the implementation and educational impact of a Virtual Reality (VR)- and Augmented Reality (AR)-based assistive technology developed to support learners with dyslexia. The intervention, delivered via mobile devices and VR headsets, incorporated gamified and interactive content aimed at enhancing cognitive skills such as attention, inhibition, narrative memory, and phonological awareness. Two in-depth case studies were conducted with primary school students formally diagnosed with dyslexia. Cognitive performance was assessed using the NEPSY-II neuropsychological battery, and user experience was evaluated using the Technology Acceptance Model (TAM). The results showed positive trends in executive function and language-related skills, as well as high motivation and satisfaction. While these findings suggest promising benefits of immersive educational technologies in dyslexia intervention, conclusions regarding efficacy cannot be drawn due to the limited sample size. Further research with larger and controlled designs is needed to validate these initial observations. Full article

Efficient planning of train crew rosters is a key factor in ensuring operational reliability and promoting long-term sustainability in railway transport, both economically and socially. This article presents a systematic approach to developing a crew rostering model in passenger rail transport, with a focus on the operational setting of the train crew depot in Česká Třebová, a city in the Czech Republic. The seven-step methodology includes identifying available train shifts, defining scheduling constraints, creating roster variants, and calculating personnel and time requirements for each option. The proposed roster reduced staffing needs by two employees, increased the average shift duration to 9 h and 42 min, and decreased non-productive time by 384 h annually. These improvements enhance sustainability by optimizing human resource use, lowering unnecessary energy consumption, and improving employees’ work–life balance. The model also provides a quantitative assessment of operational feasibility and economic efficiency. Compared to existing rosters, the proposed model offers clear advantages and remains applicable even in settings with limited technological support. The findings show that a well-designed rostering system can contribute not only to cost savings and personnel stabilization, but also to broader objectives in sustainable public transport, supporting resilient and resource-efficient rail operations. Full article

Digestate valorization is essential for sustainable waste management and circular economy strategies, yet large-scale adoption faces technical, economic, and environmental challenges. Beyond waste-to-energy conversion, digestate is a valuable soil amendment, enhancing soil structure and reducing reliance on synthetic fertilizers. However, its agronomic benefits depend on feedstock characteristics, treatment processes, and application methods. This study reviews digestate composition, treatment technologies, regulatory frameworks, and environmental impact assessment through Life Cycle Assessment. It analyzes the influence of functional unit selection and system boundary definitions on Life Cycle Assessment outcomes and the effects of feedstock selection, pretreatment, and post-processing on its environmental footprint and fertilization efficiency. A review of 28 JCR-indexed articles (2018–present) analyzed LCA studies on digestate, focusing on methodologies, system boundaries, and impact categories. The findings indicate that Life Cycle Assessment methodologies vary widely, complicating direct comparisons. Transportation distances, nutrient stability, and post-processing strategies significantly impact greenhouse gas emissions and nutrient retention efficiency. Techniques like solid–liquid separation and composting enhance digestate stability and agronomic performance. Digestate remains a promising alternative to synthetic fertilizers despite market uncertainty and regulatory inconsistencies. Standardized Life Cycle Assessment methodologies and policy incentives are needed to promote its adoption as a sustainable soil amendment within circular economy frameworks. Full article

Vehicle-to-everything (V2X) communication is a fundamental technology in the development of intelligent transportation systems, encompassing vehicle-to-vehicle (V2V), infrastructure (V2I), and pedestrian (V2P) communications. This technology enables connected and autonomous vehicles (CAVs) to interact with their surroundings, significantly enhancing road safety, traffic efficiency, and driving comfort. However, as V2X communication becomes more widespread, it becomes a prime target for adversarial and persistent cyberattacks, posing significant threats to the security and privacy of CAVs. These challenges are compounded by the dynamic nature of vehicular networks and the stringent requirements for real-time data processing and decision-making. Much research is on using novel technologies such as machine learning, blockchain, and cryptography to secure V2X communications. Our survey highlights the security challenges faced by V2X communications and assesses current ML and blockchain-based solutions, revealing significant gaps and opportunities for improvement. Specifically, our survey focuses on studies integrating ML, blockchain, and multi-access edge computing (MEC) for low latency, robust, and dynamic security in V2X networks. Based on our findings, we outline a conceptual framework that synergizes ML, blockchain, and MEC to address some of the identified security challenges. This integrated framework demonstrates the potential for real-time anomaly detection, decentralized data sharing, and enhanced system scalability. The survey concludes by identifying future research directions and outlining the remaining challenges for securing V2X communications in the face of evolving threats. Full article

The efficiency of electric motors is highly dependent on their operating temperature, with lower temperatures contributing to enhanced performance, reliability, and extended service life. This study presents a comprehensive review of state-of-the-art cooling technologies and evaluates their impact on the thermal behavior of a commercial motor–generator system in high-demand applications. A baseline model of a permanent magnet synchronous motor (PMSM) was developed using MotorCAD 2023^® software, which was supported by reverse engineering techniques to accurately replicate the motor’s physical and thermal characteristics. Subsequently, multiple cooling strategies were simulated under consistent operating conditions to assess their effectiveness. These strategies include conventional axial water jackets as well as advanced oil-based methods such as shaft cooling and direct oil spray to the windings. The integration of these systems in hybrid configurations was also explored to maximize thermal efficiency. Simulation results reveal that hybrid cooling significantly reduces the temperature of critical components such as stator windings and permanent magnets. This reduction in thermal stress improves current efficiency, power output, and torque capacity, enabling reliable motor operation across a broader range of speeds and under sustained high-load conditions. The findings highlight the effectiveness of hybrid cooling systems in optimizing both thermal management and operational performance of electric machines. Full article

Contactless vital sign monitoring has emerged as a transformative healthcare technology, enabling the assessment of vital signs without physical contact with the human body. This review comprehensively reviews the rapidly evolving landscape of this field, with particular emphasis on multi-modal sensing approaches and multi-task learning paradigms. We systematically categorize and analyze existing technologies based on sensing modalities (vision-based, radar-based, thermal imaging, and ambient sensing), integration strategies, and application domains. The paper examines how artificial intelligence has revolutionized this domain, transitioning from early single-modality, single-parameter approaches to sophisticated systems that combine complementary sensing technologies and simultaneously extract multiple vital sign parameters. We discuss the theoretical foundations and practical implementations of multi-modal fusion, analyzing signal-level, feature-level, decision-level, and deep learning approaches to sensor integration. Similarly, we explore multi-task learning frameworks that leverage the inherent relationships between vital sign parameters to enhance measurement accuracy and efficiency. The review also critically addresses persisting technical challenges, clinical limitations, and ethical considerations, including environmental robustness, cross-subject variability, sensor fusion complexities, and privacy concerns. Finally, we outline promising future directions, from emerging sensing technologies and advanced fusion architectures to novel application domains and privacy-preserving methodologies. This review provides a holistic perspective on contactless vital sign monitoring, serving as a reference for researchers and practitioners in this rapidly advancing field. Full article

With the acceleration of the pace of life, increased stress levels, and changes in lifestyle factors such as diet and exercise, the incidence of diseases such as cancer and immunodeficiency has been on the rise, which is closely associated with the impaired antioxidant capacity of the body. Polypeptides and polysaccharides derived from edible fungi demonstrate significant strong antioxidant activity and immunomodulatory effects. Auricularia auricula, the second most cultivated mushroom in China, is not only nutritionally rich but also offers considerable health benefits. In particular, its polysaccharides have been widely recognized for their immunomodulatory activities, while its abundant protein content holds great promise as a raw material for developing immunomodulatory peptides. To meet the demand for high-value utilization of Auricularia auricula resources, this study developed a key technology for the stepwise extraction of polypeptides (AAPP1) and polysaccharides (AAPS3) using a composite enzymatic hydrolysis process. Their antioxidant and immunomodulatory effects were assessed using cyclophosphamide (CTX)-induced immune-suppressed mice. The results showed that both AAPP1 and AAPS3 significantly reversed CTX-induced decreases in thymus and spleen indices (p < 0.05); upregulated serum levels of cytokines (e.g., IL-4, TNF-α) and immunoglobulins (e.g., IgA, IgG); enhanced the activities of hepatic antioxidant enzymes SOD and CAT (p < 0.05); and reduced the content of MDA, a marker of oxidative damage. Intestinal microbiota analysis revealed that these compounds restored CTX-induced reductions in microbial α-diversity, increased the abundance of beneficial bacteria (Paramuribaculum, Prevotella; p < 0.05), decreased the proportion of pro-inflammatory Duncaniella, and reshaped the balance of the Bacteroidota/Firmicutes phyla. This study represents the first instance of synergistic extraction of polypeptides and polysaccharides from Auricularia auricula using a single process. It demonstrates their immune-enhancing effects through multiple mechanisms, including “antioxidation-immune organ repair-intestinal microbiota regulation.” The findings offer a theoretical and technical foundation for the deep processing of Auricularia auricula and the development of functional foods. Full article

Advances in neuroscience have improved the understanding of cognitive, emotional, and social processes involved in learning. Simultaneously, technologies such as artificial intelligence, augmented reality, and gamification are transforming educational practices. However, their integration into formal education remains limited and often misapplied. This study aims to evaluate the impact of technology-supported neuroeducational models on student learning and well-being. A systematic review was conducted using PubMed, the Web of Science, ScienceDirect, and LILACS, including open-access studies published between 2020 and 2025. Selection and methodological assessment followed PRISMA 2020 guidelines. Out of 386 identified articles, 22 met the inclusion criteria. Most studies showed that neuroeducational interventions incorporating interactive and adaptive technologies enhanced academic performance, intrinsic motivation, emotional self-regulation, and psychological well-being in various educational contexts. Technology-supported neuroeducational models are effective in fostering both cognitive and emotional development. The findings support integrating neuroscience and educational technology into teaching practices and teacher training, promoting personalized, inclusive, and evidence-based education. Full article

The highway and bridge industry is facing persistent challenges related to the high turnover of technical personnel, which poses risks to the continuity and sustainability of infrastructure development. Although Geographic Information System (GIS) training has increasingly been advocated as a strategy to stabilize the workforce, its practical application remains relatively limited across China. Drawing on the Conservation of Resources (COR) theory, this study examines whether GIS training is associated with lower turnover intention among technical staff, potentially through enhanced perceptions of career growth and reduced work-related anxiety. Based on 412 valid responses—primarily from technical personnel employed by major infrastructure enterprises such as regional subsidiaries of the China Communications Construction Group (CCCG) and China State Construction Engineering Corporation (CSCEC)—the study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the proposed relationships. The findings indicate that GIS training is negatively associated with turnover intention, with career growth partially mediating this association. Additionally, work anxiety moderates the relationship, such that the link between GIS training and turnover intention appears weaker under higher levels of anxiety. This research contributes to bridging the gap between training practices and theoretical understanding, offering insights to inform workforce retention strategies in technology-intensive industries. Full article