Search Results (2,633)

Modern scientific knowledge management systems increasingly demand methods capable of flexible modeling and dynamic analytics. This paper presents an approach to modeling for the needs of research knowledge base systems. The presented method integrates extensible XML-based data modeling with advanced analytical tools. The approach enables the structured definition of domain models characterized by hierarchical nesting, historical tracking, and semantic versioning. The presented analytical engine, based on this approach, uses XPath navigation to support dynamic pivot-table aggregations over complex, nested data. The underlying modeling is particularly useful for handling temporal data. It is suitable for broader contexts, resulting in flexible data structures, multi-version record management, interoperability with Linked Open Data (LOD) standards, and FAIR-compliant workflows. The results demonstrate that combining model-centric extensibility, semantic interoperability, and user-driven analytics provides a scalable and adaptable foundation for building information management systems across diverse institutional and organizational settings. A use case for a university knowledge database is presented, and acceptance of the system by users is discussed. Full article

Comprehensive healthcare seeks to uphold the right to health by providing patient-centred care in both personal and work environments. However, the unequal distribution of healthcare services significantly restricts access in remote or underserved areas—a challenge that is particularly critical in mental health care within low-income countries. On average, there is only one psychiatrist for every 200,000 people, which severely limits early diagnosis and continuous monitoring in patients’ daily environments. In response to these challenges, this research explores the feasibility of implementing an information system that integrates cloud computing with an intelligent Facial Expression Recognition (FER) module to enable psychologists to remotely and periodically monitor patients’ emotional states. This approach enhances comprehensive clinical assessments, supporting early detection, ongoing management, and personalised treatment in mental health care. This applied research follows a descriptive and developmental approach, aiming to design, implement, and evaluate an intelligent cloud-based solution that enables remote monitoring of patients’ emotional states through Facial Expression Recognition (FER). The methodology integrates principles of user-centred design, software engineering best practices, and machine learning model development, ensuring a robust and scalable solution aligned with clinical and technological requirements. The development process followed the Software Development Life Cycle (SDLC) and included functional, performance, and integration testing. To assess overall system quality, we defined an evaluation framework based on ISO/IEC 25010 quality characteristics: functional suitability, performance efficiency, usability, and security. The intelligent FER model achieved strong validation results, with a loss of 0.1378 and an accuracy of 96%, as confirmed by the confusion matrix and associated performance metrics. Full article

The integration of electric vehicles (EVs) into smart grids (SGs) is reshaping both energy systems and mobility infrastructures. This review presents a comprehensive and cross-disciplinary synthesis of current technologies, methodologies, and challenges associated with EV–SG interaction. Unlike prior reviews that address these aspects in isolation, this work uniquely connects three critical pillars: (i) the evolution of energy storage technologies, including lithium-ion, second-life, and hybrid systems; (ii) optimisation and predictive control techniques using artificial intelligence (AI) for real-time energy management and vehicle-to-grid (V2G) coordination; and (iii) cybersecurity risks and post-quantum solutions required to safeguard increasingly decentralised and data-intensive grid environments. The novelty of this review lies in its integrated perspective, highlighting how emerging innovations, such as federated AI models, blockchain-secured V2G transactions, digital twin simulations, and quantum-safe cryptography, are converging to overcome existing limitations in scalability, resilience, and interoperability. Furthermore, we identify underexplored research gaps, such as standardisation of bidirectional communication protocols, regulatory inertia in V2G market participation, and the lack of unified privacy-preserving data architectures. By mapping current advancements and outlining a strategic research roadmap, this article provides a forward-looking foundation for the development of secure, flexible, and grid-responsive EV ecosystems. The findings support policymakers, engineers, and researchers in advancing the technical and regulatory landscape necessary to scale EV–SG integration within sustainable smart cities. Full article

Urban flooding presents increasingly complex challenges exacerbated by climate change, rapid urbanization, and aging infrastructure. This investigation combines planning theories and socio-hydrological modelling to create a planning-adaptable urban flood management strategy. The case study of Chiba Prefecture, Japan, demonstrates this approach in depth. By applying the Social-Ecological-Technological Systems (SETS) framework in combination with planning theories, the study has identified the relationship between the conventional engineered methods and the newly introduced environmentally friendly (nature-based) solutions. Our findings, which are based on content analysis of 23 official statutory planning documents, indicate that there is a significant focus on the conservation of ecosystems and green infrastructure balanced with issues of emergency planning and community engagement. One of the points that the results highlight is integrating the ecological, social and technological aspects in order to create flood management policies that are both robust and fair. This integrated approach offers a robust framework for mitigating flood risks while promoting sustainable urban development and long-term community resilience. Full article

This systematic review examines the methodologies and applications of integrated risk indicators in positron emission tomography (PET) radiopharmaceutical production, focusing on occupational, technological, and environmental risks. Conducted in accordance with PRISMA 2020 guidelines and utilizing the Ryyan software 2023 for article screening, the review synthesizes findings from 70 studies published between 2020 and 2025 in English and Spanish, including articles, conference papers, and reviews. The review was registered on PROSPERO (CRD420251078221). Key disciplines contributing to risk assessment frameworks include environmental science, occupational health and safety, civil engineering, mining engineering, maritime safety, financial/economic risk, and systems engineering. Predominant risk assessment methods identified are probabilistic modeling (e.g., Monte Carlo simulations), machine learning (e.g., neural networks), multi-criteria decision-making (e.g., AHP and TOPSIS), and failure mode and effects analysis (FMEA), each offering strengths, such as uncertainty quantification and systematic hazard identification, alongside limitations like data dependency and subjectivity. The review explores how frameworks from other industries can be adapted to address PET-specific risks, such as radiation exposure to workers, equipment failure, and waste management, and how studies integrate these factors into unified risk indicators using weighted scoring, probabilistic methods, and fuzzy logic. Gaps in the literature include limited stakeholder engagement, lack of standardized frameworks, insufficient real-time monitoring, and under-represented environmental risks. Future research directions propose developing PET-specific tools, integrating AI and IoT for real-time data, establishing standardized frameworks, and expanding environmental assessments to enhance risk management in PET radiopharmaceutical production. This review highlights the interdisciplinary nature of risk assessment and the critical need for comprehensive, tailored approaches to ensure safety and sustainability in this field. Full article

The aging population in Europe and other developed regions is accelerating the demand for adaptable domestic environments that support independent living and care at home. In this context, ontologies offer a promising approach to represent and manage knowledge about built environments, smart technologies, and user needs—especially within Ambient Assisted Living (AAL) systems. This paper presents a systematic literature review examining the role of ontologies in the reconfiguration of domestic living spaces, with a focus on their application in design processes and decision support systems. Following the PRISMA methodology, 14 relevant works published between 2000 and 2025 were identified and analyzed. The review explores key aspects such as ontology conceptualization, reuse, engineering methodologies, integration with CAD systems, and validation practices. The results show that research on this topic is fragmented yet growing, with the first contribution dated 2005 and peaks in 2016, 2018, and 2024. Most works (11) were conference papers, with Europe leading the contributions, particularly Italy. Half of the reviewed ontologies were developed “from scratch”, while the rest relied on conceptualizations such as BIM. Ontology reuse was inconsistent: only 50% of works reused existing models (e.g., SAREF, SOSA, BOT, ifcOWL), and few adopted Ontology Design Patterns. While 11 works followed ontology engineering methodologies—mostly custom or established methods such as Methontology or NeOn—stakeholder collaboration was reported in less than 36% of cases. Validation practices were weak: only six studies presented use cases or demonstrators. Integration with CAD systems remains at a prototypical stage, primarily through semantic enrichment and SWRL-based reasoning layers. Remaining gaps include poor ontology accessibility (few provide URLs or W3IDs), limited FAIR compliance, and scarce modeling of end-user needs, despite their relevance for AAL solutions. The review highlights opportunities for collaborative, human-centered ontology development aligned with architectural and medical standards to enable scalable, interoperable, and user-driven reconfiguration of domestic environments. Full article

The complex pathological mechanisms of atherosclerosis (AS) involve lipid metabolism disorders, inflammatory responses, and plaque instability, resulting in significant challenges to effective clinical management. Current therapeutic approaches, such as statins and stent implantation, suffer from issues including single-target action, notable side effects, and the risk of restenosis. Nanoparticle-based drug delivery systems have demonstrated considerable promise by enabling the codelivery of multiple agents directly to atherosclerotic lesions, thereby improving therapeutic efficacy and minimizing systemic toxicity. Among various nanomaterials, organic nanoparticles have recently emerged as a research hotspot in the field of AS treatment due to their excellent biocompatibility, degradability, and potential for targeted modification. This review systematically summarizes the recent advances and emerging trends in the application of organic nanoparticles for AS treatment, employing bibliometric analysis to delineate research frontiers. We employed bibliometric tools to analyze 1999 articles on organic nanocarriers for AS therapy indexed in the Web of Science Core Collection. The analysis included co-occurrence and clustering techniques to explore influential keywords and key contributors. Temporal analysis was applied to identify emerging research hotspots and track the evolution of this field. The literature reveals three major current focal areas: (1) the development of engineered biomimetic organic nanoparticles; (2) the design of multifunctional polymer-based organic nanocarriers; and (3) the innovation of organic-coated stents. This article not only provides a comprehensive overview of cutting-edge organic nanotechnologies for AS therapy, but also critically discusses the challenges in clinical translation, offering insights into future directions for the development of safe, effective, and personalized nanomedicine strategies against AS. Full article

Achieving the full potential of wind energy in the global renewable transition depends critically on enhancing the performance and reliability of polymer composite components. This review synthesizes recent advances from 2022 to 2025, including the development of next-generation hybrid composites and the application of high-fidelity computational methods—finite element analysis (FEA), computational fluid dynamics (CFD), and fluid–structure interaction (FSI)—to optimize structural integrity and aerodynamic performance. It also explores the transformative role of artificial intelligence (AI) in structural health monitoring (SHM) and the integration of Internet of Things (IoT) systems, which are becoming essential for predictive maintenance and lifecycle management. Special focus is given to harsh offshore environments, where polymer composites must withstand extreme wind and wave conditions. This review further addresses the growing importance of circular economy strategies for managing end-of-life composite blades. While innovations such as the geometric redesign of floating platforms and the aerodynamic refinement of blade components have yielded substantial gains—achieving up to a 30% mass reduction in PLA prototypes—more conservative optimizations of internal geometry configurations in GFRP blades provide only around 7% mass reduction. Nevertheless, persistent challenges related to polymer composite degradation and fatigue under severe weather conditions are driving the adoption of real-time hybrid predictive models. A bibliometric analysis of over 1000 publications confirms more than 25 percent annual growth in research across these interconnected areas. This review serves as a comprehensive reference for engineers and researchers, identifying three strategic frontiers that will shape the future of wind turbine blade technology: advanced composite materials, integrated computational modeling, and scalable recycling solutions. Full article

Two-component systems (TCSs) are ubiquitous in bacteria and are central to their ability to sense and respond to diverse environmental and intracellular cues. Classically composed of a sensor histidine kinase and a cognate response regulator, TCSs control processes ranging from metabolism and development to virulence and antibiotic resistance. In addition to their biological roles, TCSs are garnering attention in synthetic biology and antimicrobial drug development. While canonical architectures have been extensively studied, increasing evidence highlights the remarkable diversity in their organization and regulation. Despite substantial progress, key questions remain regarding the prevalence and physiological relevance of non-canonical TCSs, the mechanisms ensuring signal fidelity, and the potential for engineering these systems. This review explores non-typical TCSs, focusing on their varied transcriptional regulation, alternative response regulator activities, varied control by phosphorylation, and negative control mechanisms. We discuss how bacteria manage signaling specificity among numerous TCSs through cross-talk, hierarchical interactions, and phosphorelay systems and how these features shape adaptive responses. By synthesizing current understanding and highlighting still existing knowledge gaps, this review offers a novel perspective on TCS diversity, indicating directions for future research and potential translational applications in biotechnology and medicine. Full article

Biofilms constitute a significant challenge in the therapy of infectious diseases, offering remarkable resistance to both pharmacological treatments and immunological elimination. This resilience is orchestrated through the regulation of extracellular polymeric molecules, metabolic dormancy, and quorum sensing, enabling biofilms to persist in both clinical and industrial environments. The resulting resistance exacerbates chronic infections and contributes to mounting economic burdens. This review examines the molecular and structural complexities that drive biofilm persistence and critically outlines the limitations of conventional diagnostic and therapeutic approaches. We emphasize advanced technologies such as super-resolution microscopy, microfluidics, and AI-driven modeling that are reshaping our understanding of biofilm dynamics and heterogeneity. Further, we highlight recent progress in biofilm-targeted therapies, including CRISPR-Cas-modified bacteriophages, quorum-sensing antagonists, enzyme-functionalized nanocarriers, and intelligent drug-delivery systems responsive to biofilm-specific cues. We also explore the utility of in vivo and ex vivo models that replicate clinical biofilm complexity and promote translational applicability. Finally, we discuss emerging interventions grounded in synthetic biology, such as engineered probiotic gene circuits and self-regulating microbial consortia, which offer innovative alternatives to conventional antimicrobials. Collectively, these interdisciplinary strategies mark a paradigm shift from reactive antibiotic therapy to precision-guided biofilm management. By integrating cutting-edge technologies with systems biology principles, this review proposes a comprehensive framework for disrupting biofilm architecture and redefining infection treatment in the post-antibiotic era. Full article

Building-Integrated Photovoltaics (BIPV) is a transformative approach to sustainable energy, which integrates photovoltaic systems as integral elements of building structures, such as facades, roofs, and windows. This bibliometric review aims to comprehensively analyze the evolution, trends, and challenges in BIPV research by referencing more than 10,000 publications indexed in Scopus. Key findings highlight the growing importance of cross-disciplinary collaboration in engineering, architecture, and environmental science to improve BIPV efficiency, aesthetic integration, and economic viability. Despite substantial progress, challenges remain, including high initial costs, regulatory limitations, and the need for innovative materials and energy storage solutions. Emerging trends underscore the potential of BIPV in urban planning and sustainability initiatives, supported by increased collaboration and international adoption in regions with supportive policies. This review identifies research gaps in cost-effective production, adaptive materials, and integrated energy management solutions, which offer future pathways for BIPV innovation. This review serves as a reference for academics, practitioners, and policymakers aiming to advance the adoption of BIPV, contributing to global efforts towards energy sustainability and low-carbon urban development. Full article

Buildings are among the most significant sources of energy consumption worldwide. Unfortunately, many are inefficient in terms of energy use, leading to high operational expenses. With modern technologies such as IoT sensors, smart meters, secure real-time communication, and advanced mathematical algorithms for data processing integrated into an efficient energy management platform, traditional buildings can be transformed into smart structures. In this context, a platform called “Building Energy Efficiency in Totality” (BENEFIT), which incorporates the smart building energy management (SBEM) concept, has been designed, developed, integrated, and tested as an innovative tool for monitoring and optimally controlling energy consumption. The platform is based on open-source software, enabling rapid and straightforward development of comprehensive solutions that address all aspects of the SBEM concept. The BENEFIT architecture allows the management of a wide range of devices within the building, including energy generation units, heating, ventilation, and air conditioning systems, indoor lighting, environmental sensors, surveillance cameras, and others. BENEFIT has been implemented and tested in a building belonging to the Faculty of Electrical Engineering at the Technical University of Iasi, Romania. The analysis of the results after one year of integrating the BENEFIT platform has resulted in a plan focused on measures to reduce energy consumption and improve the building’s performance and efficiency. The implementation of two measures (upgrading window insulation and improving lighting) resulted in a 12.14% reduction in total energy consumption. Full article

This paper explores the potential for engineer-to-order (ETO) companies to capitalise financially on their modular product architectures by sharing them with their suppliers. Few scholars have studied product architectures being shared across buyers (ETO companies) and suppliers. While the topic’s relevance has previously been demonstrated, scholars tend to leave out details on how the shared elements of architectures, respectively, benefit the company and with what financial effect. The study aims to develop a framework for describing a shared architecture and to test it in a case study of an ETO company and two of its tier-one suppliers. The framework is built on existing research and the case work of this paper. The study identifies three key aspects of a shared product architecture: a common system decomposition, modules and interfaces that are financially driven by interorganisational alignment of key design characteristics, and a series of coordinated activities that are consistent and mutually beneficial for both organisations. The results show that the ETO company saw 10–35% cost saving on supplier scope after developing the shared architecture. The study contributes to the literature on product architectures and provides insights for ETO companies aiming to enhance financial performance through modular architectures. Full article

Organs-on-Chips (OoC) technology has begun to be considered a pragmatic tool for drug evaluation, offering researchers an opportunity to move beyond the less physiologically relevant animal models. OoCs are microfluidic structures that imitate the functionalities of individual human organs, serving as mimicry tools for drug response and reproducibility studies. On the one hand, companies producing OoCs find managing and analyzing the large amounts of data generated challenging. This is where artificial intelligence (AI) can be deployed to address such problems. This paper will present the state-of-the-art of current OoC technology and AI, discussing the benefits and threats of combining these approaches. AI can be applied to optimize the process of OoC fabrication and operation, as well as for the big data analysis of OoC devices. By combining these technologies, scientists gain a powerful tool for drug development that is more efficient and accurate. However, processing the vast datasets generated by OoC systems often requires specialized AI expertise and computational resources. Despite the numerous possible benefits of amalgamating OoC technology with AI, several challenges and limitations need to be addressed. The large datasets generated by OoC systems can be difficult to process and analyze, which is a task that may require specialized AI expertise. Additionally, limitations of OoC systems include issues with reproducibility, as the devices are sensitive to perturbations in experimental conditions. Furthermore, the development and implementation of AI algorithms require significant computational resources and expertise, which may not be readily available to all research institutions. To overcome these challenges, interdisciplinary collaboration between biologists, engineers, data scientists, and AI experts is essential. Continued advancements in both OoC technology and AI will likely lead to more robust and versatile platforms for biomedical research and drug development, ultimately contributing to the advancement of personalized medicine and the reduction of reliance on animal testing. Full article

The development of dynamic missions of small satellites requires the development of efficient, compact, and reliable propulsion systems (PSs). This paper investigates a propellant storage and supply system (PSSS), utilizing alternative solid-state propellants in the form of wire. To establish the background to the suggested solutions implemented in the proposed system, two types of comparative analysis were performed. The first one compared different types of propellant management system designs while the second juxtaposes a variety of propellants. It is shown that the solid-state systems for small satellite operations are advantageous, while the selection of propellants should be focused on safe operations and operational requirements. The principle of operation and structural design of the proposed wire-based solid-state propellant management system are discussed, including the assessment of its engineering realization. The strategies to mitigate the potential problems with the system’s operations such as propellant unwanted deposition and corrosive effects are suggested. An example of using the proposed system is provided, which considers a deep space dynamic mission case. The proposed PSSS architecture is dedicated to increasing the energy efficiency, resilience to environmental factors, and suitability for small satellite platforms, including that of the CubeSat format. Full article