Search Results (7,694)

This article examines the global efforts to govern and regulate Artificial Intelligence (AI) in response to its rapid development and growing influence across many parts of society. It explores how governance takes place at multiple levels, including international bodies, national governments, industries, companies, and communities. The study draws on a wide range of official documents, policy reports, and international agreements to build a timeline of key regulatory and standardization milestones. It also analyzes the challenges of coordinating across different legal systems, economic priorities, and cultural views. The findings show that while some progress has been made through soft-law frameworks and regional partnerships, deep divisions remain. These include unclear responsibilities, uneven enforcement, and risks of regulatory gaps. The article argues that effective AI governance requires stronger international cooperation, fair and inclusive participation, and awareness of power imbalances that shape policy decisions. Competing global and commercial interests can create obstacles to building systems that prioritize the public good. The conclusion highlights that future governance models must be flexible enough to adapt to fast-changing technologies, yet consistent enough to protect rights and promote trust. Addressing these tensions is critical for building a more just and accountable future of AI. Full article

Under the combined effects of climate change, overexploitation, and intense grazing, temperate steppe in northern China is experiencing increasing deterioration, which is typified by a shift from structural degradation to functional disruption. Accurately tracking steppe degradation using remote sensing technology has emerged as a crucial scientific concern. Prior research failed to integrate ecosystem structure and function and lacked reference baselines, relying only on individual indicators to quantify degradation. To resolve these gaps, this study established a novel degradation evaluation index system integrating ecosystem structure and function, incorporating vegetation community distribution and proportions of degradation-indicator species to define reference states and quantify degradation severity. Analyzed spatiotemporal evolution and drivers across the temperate typical steppe (2013–2022). Key findings reveal (1) non-degraded and slightly degraded areas dominated (75.57% mean coverage), showing an overall fluctuating improvement trend; (2) minimal transitions between degradation levels, with stable conditions prevailing (59.52% unchanged area), indicating progressive degradation reversal; and (3) natural factors predominated as degradation drivers. The integrated structural–functional framework enables more sensitive detection of early degradation signals, thereby informing more effective steppe restoration management. Full article

Microorganisms exhibit metabolic versatility, which enables their multifaceted application, including in pollutant detoxification, waste recycling, and environmental restoration. Agricultural processing generates substantial byproducts rich in carbon, nitrogen, and sulfur, which require proper handling to mitigate ecological challenges and reduce carbon footprints. The generation of recalcitrant keratinous biomass and its slow degradation in the environment have prompted technological interventions for sustainable solutions. Fundamentally, chemical, thermal and mechanical processing methods have been utilized in managing keratinous waste. These approaches are not only energy-intensive but also yield low-quality products and exacerbate environmental challenges. Multidimensional research on the microbial-assisted conversion of keratinous waste into valuable products, which aligns with circular economy principles, is underway. The biodegradation of keratinous resources has predominantly employed culturable single microbial strains; however, few studies have recently investigated microbial consortia as a promising strategy. The use of microbial consortia leverages the high cultural stability and complementary metabolic pathways of microbes to achieve excellent keratin biodegradation. Therefore, this study examined the latest advancements in transforming keratinous waste into high-quality protein hydrolysates using microbial strains. It detailed various types of microbial consortia and their roles in the valorization of keratinous biomass, while highlighting some knowledge gaps for future studies. The study also explored the role of ancillary microbial enzymes in facilitating the conversion of keratinous biomass into value-added products. Full article

State Departments of Transportation (DOTs) face challenges with traditional bridge inspections that are time-consuming, inconsistent, and paper-based. This study focused on an existing research gap regarding automated methods that streamline the bridge inspection process, prioritize maintenance effectively, and allocate resources efficiently. Thus, this paper introduces a digitalized bridge inspection framework by integrating Building Information Modeling (BIM) and Business Intelligence (BI) to enable near-real-time monitoring and digital documentation. This study adopts a Design Science Research (DSR) methodology, a recognized paradigm for developing and evaluating the innovative SmartBridge to address pressing bridge inspection problems. The method involved designing an Autodesk Revit-based plugin for data synchronization, element-specific comments, and interactive dashboards, demonstrated through an illustrative 3D bridge model. An illustrative example of the digitalized bridge inspection with the proposed framework is provided. The results show that SmartBridge streamlines data collection, reduces manual documentation, and enhances decision-making compared to conventional methods. This paper contributes to this body of knowledge by combining BIM and BI for digital visualization and predictive analytics in bridge inspections. The proposed framework has high potential for hybridizing digital technologies into bridge infrastructure engineering and management to assist transportation agencies in establishing a safer and efficient bridge inspection approach. Full article

Cannabidiol (CBD) and its derivatives show interesting therapeutic potential, including antioxidant, anti-inflammatory, and anticancer properties; however, their clinical translation remains a complex task due to physicochemical restrictions such as low water solubility, high lipophilicity, and instability under light, oxygen, and high temperatures. Polymeric encapsulation has emerged as a promising strategy to overcome these challenges, offering protection against environmental degradation, improved bioavailability, and controlled release. Natural and synthetic polymers, both biocompatible and biodegradable, provide versatile matrices for CBD delivery, enabling nanoparticle formation, targeted transport, and enhanced pharmacokinetics. This review highlights the structural characteristics of CBD, its interaction mechanisms with polymeric matrices such as hydrogels, electrospun nanofibers, biodegradable microparticles, thin films, and lipid-polymer hybrid systems, and the principal encapsulation techniques, such as emulsion solvent evaporation, electrospinning, and supercritical fluid technologies, that facilitate stability and scalability. Furthermore, material characterization approaches, including microscopy, thermal, and degradation analyses, are discussed as tools for optimizing encapsulation systems. While notable advances have been made, key challenges remain in achieving reproducible large-scale production, ensuring regulatory compliance, and designing smart polymeric carriers personalized for specific therapeutic contexts. By addressing these gaps, polymer-based encapsulation may unlock new opportunities for CBD in pharmaceutical, nutraceutical, and therapeutic applications, providing a guide for future innovation and translation into effective patient-centered products. Full article

Structured-light 3D reconstruction is an active measurement technique that extracts spatial geometric information of objects by projecting fringe patterns and analyzing their distortions. It has been widely applied in industrial inspection, cultural heritage digitization, virtual reality, and other related fields. This review presents a comprehensive analysis of mainstream fringe-based reconstruction methods, including Fringe Projection Profilometry (FPP) for diffuse surfaces and Phase Measuring Deflectometry (PMD) for specular surfaces. While existing reviews typically focus on individual techniques or specific applications, they often lack a systematic comparison between these two major approaches. In particular, the influence of different projection schemes such as Digital Light Processing (DLP) and MEMS scanning mirror–based laser scanning on system performance has not yet been fully clarified. To fill this gap, the review analyzes and compares FPP and PMD with respect to measurement principles, system implementation, calibration and modeling strategies, error control mechanisms, and integration with deep learning methods. Special focus is placed on the potential of MEMS projection technology in achieving lightweight and high-dynamic-range measurement scenarios, as well as the emerging role of deep learning in enhancing phase retrieval and 3D reconstruction accuracy. This review concludes by identifying key technical challenges and offering insights into future research directions in system modeling, intelligent reconstruction, and comprehensive performance evaluation. Full article

In a significant transition from classical theories of efficient markets and perfectly rational investors, the recent literature has increasingly acknowledged the importance of the human element and external market conditions in decision-making. However, the application of adaptive market frameworks in the property sector remains underexplored. This gap is particularly pronounced in the commercial property market, where structural inefficiencies, such as information asymmetry and illiquidity, amplify decision-making complexity. Given that investor rationality tends to diminish as uncertainty and complexity increase, this study explored how private commercial property investors adapt their strategies amid heightened uncertainty. The perspectives of seven experienced property experts were thematically analysed to highlight recurring patterns, which were then integrated into a conceptual mind map. The findings reveal that while economic fundamentals are the constant drivers of capital allocation decisions, investors process these signals through the lens of adaptive behaviour based on intuition, experience, risk perceptions, and herding. This relationship becomes more pronounced under conditions of heightened uncertainty, where investors seek to supplement available information with sentiment due to weaker signals and declining confidence in fundamentals. Sustainable investing and technology integration also emerged as core considerations, but interest among private investors is subdued due to ambiguous value propositions regarding the long-term economic benefits of a green premium. These findings offer practical insights into how external market conditions influence property investment decisions and provide a platform for operational models of investment decision-making that integrate adaptive behaviour. Full article

Transportation networks are critical lifelines in national infrastructure but are increasingly exposed to risks arising from climate variability, cyber threats, aging assets, and limited resources. This paper presents a scoping review of 58 peer-reviewed studies published between 2015 and 2025 that examine the role of Artificial Intelligence (AI) in strengthening infrastructure resilience, with transportation systems adopted as the strategic case. The review classifies applications along five dimensions: technological approach, infrastructure sector, transportation linkage, resilience/security aspect, and key research gaps. Findings show that AI, machine learning (ML), and the Internet of Things (IoT) dominate current applications, particularly in predictive maintenance, intelligent monitoring, early-warning systems, and optimization. These applications extend beyond transport to energy, water, and agri-food systems that indirectly sustain transport resilience. Persistent challenges include affordability, data scarcity, infrastructural limitations, and limited real-world validation, especially in Sub-Saharan African contexts. The paper synthesizes cross-sector pathways through which AI enhances transport resilience and outlines practical implications for policymakers and practitioners. A targeted research agenda is also proposed to address methodological gaps, enhance deployment in resource-constrained settings, and promote hybrid and explainable AI for trust and scalability. Full article

Battery Electric Vehicles (BEVs) technology is rapidly emerging as the cornerstone of sustainable transportation, driven by advancements in battery technology, power electronics, and modern drivetrains. This paper presents a comprehensive review of current and next-generation BEV powertrain architectures, focusing on five key subsystems: battery energy storage system, electric propulsion motors, energy management systems, power electronic converters, and charging infrastructure. The review traces the evolution of battery technology from conventional lithium-ion to solid-state chemistries and highlights the critical role of battery management systems in ensuring optimal state of charge, health, and safety. Recent innovations by leading automakers are examined, showcasing advancements in cell formats, motor designs, and thermal management for enhanced range and performance. The role of power electronics and the integration of AI-driven strategies for vehicle control and vehicle-to-grid (V2G) are analyzed. Finally, the paper identifies ongoing research gaps in system integration, standardization, and advanced BMS solutions. This review provides a comprehensive roadmap for innovation, aiming to guide researchers and industry stakeholders in accelerating the adoption and sustainable advancement of BEV technologies. Full article

Background/Objectives:Hydrogels are highly hydrated, biocompatible polymer networks increasingly investigated as drug-delivery systems (DDS) for analgesics. Their ability to modulate local release, prolong drug residence time, and reduce systemic toxicity positions them as promising platforms in perioperative, chronic, and localized pain settings. This scoping review aimed to systematically map clinical applications, efficacy, and safety of hydrogel-based DDS for analgesics, while also documenting non-DDS uses where the matrix itself contributes to pain modulation through physical mechanisms. Methods: Following PRISMA-ScR guidance, PubMed, Embase, and Cochrane databases were searched without publication date restrictions. Only peer-reviewed clinical studies were included; preclinical studies and non-journal literature were excluded. Screening and selection were performed in duplicate. Data extracted included drug class, hydrogel technology, clinical setting, outcomes, and safety. Protocol was registered with Open Science Framework. Results: A total of 26 clinical studies evaluating hydrogel formulations as DDS for analgesics were included. Most were randomized controlled trials, spanning 1996–2024. Local anesthetics were the most frequent drug class, followed by opioids, corticosteroids, Non-Steroidal Anti-Inflammatory Drugs (NSAIDs), and neuromodulators. Application sites were predominantly topical/transdermal and perioperative/incisional. Across the DDS cohort, most of the studies reported improved analgesic outcomes, including reduced pain scores and lower rescue medication use; neutral or unclear results were rare. Safety reporting was limited, but tolerability was generally favorable. Additionally, 38 non-DDS studies demonstrated pain reduction through hydrogel-mediated cooling, lubrication, or barrier effects, particularly in burns, ocular surface disorders, and discogenic pain. Conclusions: Hydrogel-based DDS for analgesics show consistent clinical signals of benefit across diverse contexts, aligning with their mechanistic rationale. While current evidence supports their role as effective, well-tolerated platforms, translational gaps remain, particularly for hybrid nanotechnology systems and standardized safety reporting. Non-DDS applications confirm the intrinsic analgesic potential of hydrogel matrices, underscoring their relevance in multimodal pain management strategies. Full article

Background: Urban disasters expose persistent gaps in the operational picture and timely decision-making for response teams, which require user-centred systems that connect analysis to action. This study proposes and formatively validates an integrated framework that couples digital twins and augmented reality for humanitarian logistics. Methods: A mixed methods design combined a structured literature synthesis with a practitioner survey across architecture, engineering, planning, BIM, and construction to assess perceived value and adoption conditions. Results: Findings indicate that practitioners prioritised digital twins for enhancing situational awareness (71.4%) and augmented reality for providing real-time information overlays (64.3%). A majority judged that integrating these technologies would yield substantial improvements in disaster response (67.9%), despite implementation challenges. Conclusions: The framework links live state estimation and short-horizon simulation to role-specific, in-scene AR cues, with the aim of reducing decision latency and improving coordination. Adoption depends primarily on human and organisational factors, including user accessibility, preparation needs, and clear governance. These results suggest a viable pathway to operationalise the bridge between analysis and field action and outline priorities for pilot evaluation. Full article

Against the backdrop of global agricultural transformation, rural China faces the critical challenge of reconciling economic development with environmental conservation and social well-being. This study, grounded in the rural revitalization strategy, investigates the internal mechanisms, level measurement, and sustainable development paths of rural industrial integration based on the “Triple Integration of Production, Livelihood and Ecology” (PLE) philosophy. Firstly, we discussed the suitability and the mechanisms of this philosophy on China’s rural industrial integration. Secondly, based on a textual corpus extracted from academic journals and policy documents, we employed an LDA topic model to cluster the themes and construct an evaluation indicator system comprising 29 indicators. Then, utilizing data from the China Statistical Yearbook and the China Rural Statistical Yearbook (2013–2022), we measured the level of China’s rural industrial integration using the entropy method. The composite integration index displays a continuous upward trend over 2013–2022, accelerating markedly after the 2015 stimulus policy, yet a temporary erosion of “production–livelihood–ecology” synergy occurred in 2020 owing to an exogenous shock. Lastly, combining the system dynamics model, we simulated over the period 2023–2030 the three sustainable development scenarios: green ecological development priority, livelihood standard development priority and production level development priority. Research has shown that (1) the “Triple Synergy of Production, Livelihood and Ecology” philosophy and China’s rural industrial integration are endogenously unified, and they form a two-way mutual mechanism with the common goal of sustainable development. (2) China’s rural industrial integration under this philosophy is characterized by production-dominated development and driven mainly by processing innovation and service investment, but can be constrained by ecological fragility and external shocks. (3) System dynamics simulations reveal that the production-development priority scenario (Scenario 3) is the most effective pathway, suggesting that the production system is a vital engine driving the sustainable development of China’s rural industrial integration, with digitalization and technological innovation significantly improving integration efficiency. In the future, efforts should focus on transitioning towards a people-centered model by restructuring cooperative equity for farmer ownership, building community-based digital commons to bridge capability gaps, and creating market mechanisms to monetize and reward conservation practices. Full article

Wetting behavior of molten metals on solid substrates is a critical phenomenon influencing numerous industrial applications, including welding, anti-corrosion coatings, and metal additive manufacturing (AM). In particular, molten metal jetting (MMJ), an emerging AM technology, requires that the molten metal remain pinned at the nozzle exit. Thus, each new metal requires a specific nozzle material to ensure consistent droplet ejection and deposition, making it important to rapidly identify the appropriate wetting combinations. However, traditional measurements of wetting angles require expensive equipment and only allow one combination of materials to be investigated at a time which can be time consuming. This work introduces a rapid screening method based on sessile droplet experiments to evaluate wetting profiles across multiple metal–substrate combinations simultaneously. This study investigates the wetting interactions of molten Al alloy (Al4008), Cu, and Sn on various ceramic and metal substrates to identify optimal material combinations for MMJ nozzle designs. Results demonstrate that Al4008 achieves wetting on ceramic substrates such as AlN, TiO₂, and SiC, with varying mechanisms including chemical reactions and weak surface interactions. Additionally, theoretical predictions regarding miscibility gaps and melting point differences were verified for Cu and Sn on refractory metals like Mo and W. Findings from this study contribute to the establishment of a materials compatibility library, enabling the selection of wetting/non-wetting combinations for stable MMJ operation. This resource not only advances MMJ technologies but also provides valuable insights for broader applications such as welding, coating, and printed electronics. Full article

Background: The digitalization of medical services is promoted as a solution for improving access, quality, and efficiency within healthcare systems. In this context, the study investigates the extent to which digitalization in Romania meets the current needs of patients through a convergent analysis of user perceptions and managerial perspectives. Based on the specialized literature, the research tests two hypotheses: (H1) the implementation of digital technologies significantly contributes to improving the quality of medical services and operational efficiency; (H2) digitalization has a positive impact on patient satisfaction by facilitating access to care and improving communication with medical personnel. Methods: The study adopted methodology is cross-sectional and mixed, including an online mixed-methods questionnaire for patients, distributed between 6 and 14 May 2025, and a qualitative questionnaire with open-ended questions distributed via e-mail to managers from public hospitals through The Administration of Hospitals and Medical Services of Bucharest, between 3 and 24 March 2025. Results: In total, 125 patients and 15 hospital managers participated in the study. Statistical analysis (χ², ordinal regression) and data triangulation highlight a predominantly positive, yet heterogeneous, patient perception of digitalization, with Hypothesis H1 only partially supported (weak, inconsistent, and in some cases negative associations between technology use and perceived service quality). By contrast, H2 was robustly validated, with patient satisfaction strongly linked to tangible benefits, particularly easier access and online appointment scheduling. However, use remains limited to administrative functions, while advanced technologies such as telemedicine or electronic health records are poorly adopted. From an institutional perspective, hospitals predominantly use IT systems for internal purposes, without real patient access to their own data, no interoperability between medical units, and marginal implementation of telemedicine. This reveals a significant gap between user perception and organizational realities, emphasizing the lack of a patient-oriented digital infrastructure. Conclusions: The results highlight the potential of digitalization to enhance patient experience and service efficiency, while also pointing out structural limitations that hinder the full realization of this potential. Patient satisfaction is strongly associated with tangible benefits, particularly easier access and online scheduling, whereas the effect on perceived quality is weaker and sometimes inconsistent. There are significant disparities in digitalization levels between healthcare providers, perceived by patients as public–private differences, and gaps among public hospitals are also confirmed by managerial data. These findings suggest that a successful digital transformation of the medical system in Romania must address both technological infrastructure gaps and organizational barriers, within a coordinated national strategy that ensures interoperability, patient-centered design, and sustainable implementation. Full article

Healthcare 5.0 represents the next evolution in intelligent and interconnected healthcare systems, leveraging emerging technologies such as Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) to enhance patient care and automation. While Intrusion Detection Systems (IDSs) are a critical component for securing these environments, the current literature lacks a systematic analysis that jointly evaluates the effectiveness of AI models, the suitability of datasets, and the role of Explainable Artificial Intelligence (XAI) in the Healthcare 5.0 landscape. To fill this gap, this survey provides a comprehensive review of IDSs for Healthcare 5.0, analyzing state-of-the-art approaches and available datasets. Furthermore, a practical case study is presented, demonstrating that the fusion of network and biomedical features significantly improves threat detection, with physiological signals proving crucial for identifying complex attacks like spoofing. The primary contribution is therefore an integrated analysis that bridges the gap between cybersecurity theory and clinical practice, offering a guide for researchers and practitioners aiming to develop more secure, transparent, and patient-centric systems. Full article