Search Results (3,991)

The convergence of Large Language Models (LLMs) with the Internet of Things (IoT) is driving a transformative shift toward a continuous, context-aware smart healthcare ecosystem. Due to its novelty, existing research in this domain remains fragmented, leaving a critical gap in unified frameworks that synthesize domain applications, functional AI deployment roles, network architectures, and security boundaries. Following PRISMA 2020 guidelines, this paper presents a systematic literature review and quantitative analysis evaluating a selected corpus of 61 peer-reviewed and 14 preprint papers in this domain. Methodologically, we assess a novel hybrid article discovery strategy, finding that an AI-powered prompt-based literature search strategy achieves higher precision than traditional keyword-based Boolean queries (86% vs. 42%) on the evaluated search sample, which may reduce screening workloads. We found that the major limitation of AI-based literature search is non-determinism, which is also an inherent property of LLM-powered applications. To address this, we propose methodological guidelines for using an AI-assisted hybrid literature search strategy. Based on the selected literature, we establish a multi-layer taxonomy organizing the IoT-LLM advances in the healthcare domain across four pillars: application domain, LLM role, IoT device type, and architectural deployment pattern. Quantitative synthesis reveals a heavy research concentration in remote patient monitoring and personal health management (representing 59% of the corpus combined), primarily driven by the data accessibility of wearable sensors (64%). Cross-tabulation uncovers a distinct capability–constraint spectrum: cloud-based deployments lean on heavyweight state-of-the-art models (mainly GPT-family models) for complex semantic reasoning, whereas edge, federated, and blockchain-based hybrid systems leverage localized models (BERT and LLaMA families). Patient data privacy and reduced communication overhead were among the main reasons for choosing localized models. Crucially, our assessment reveals a pervasive neglect of LLM-specific vulnerabilities such as prompt injection and jailbreak attacks and a tendency to treat regulatory frameworks (e.g., HIPAA, GDPR) as design features rather than empirically validated compliance metrics. Finally, we propose an actionable future research agenda prioritizing multi-device system orchestration, emergency care integration, privacy-preserving LLMs, and deployment-scale clinical validation. Full article

Marine pollution in the Philippine archipelago poses increasing threats to biodiversity, ecosystem services, and human health due to rapid urbanization, population growth, and inadequate waste management. As a core region of the Coral Triangle, the Philippines is particularly vulnerable to pollutants transported across interconnected marine ecosystems. This review synthesizes current knowledge on the occurrence, sources, analytical approaches, risk assessment, and knowledge gaps associated with conventional and emerging major marine pollutants, including oil, heavy metals, polycyclic aromatic hydrocarbons, persistent organic pollutants, pharmaceuticals and personal care products, per- and polyfluoroalkyl substances, plastics, and additional stressors such as nutrients, pathogens, and shipping-related contaminants. Available evidence indicates widespread contamination of coastal waters, sediments, and marine biota, with pollution hotspots commonly associated with urbanized coastlines, river systems, industrial zones, shipping routes, aquaculture areas, and tourism centers. Emerging pollutants such as plastics and microplastics are increasingly detected even in remote environments, highlighting limitations in current monitoring and management frameworks. However, significant gaps remain in long-term monitoring, standardized methodologies, human health risk assessment, and interdisciplinary integration. This review emphasizes the need for harmonized monitoring programs, improved waste management infrastructure, strengthened regulatory enforcement, expanded analytical capacity, and integrated science-based policies to support sustainable marine management and ocean governance in the Philippines. Full article

Wildfire risks are increasing due to climate change, which poses a challenge to conventional firefighting strategies. In the wildland–urban interface (WUI), people and their infrastructure are increasingly vulnerable to fire. Strategic planting of low-flammable vegetation as green firebreaks has emerged to support wildfire management in the WUI. However, under extreme heat and drought, even low-flammability plants become fuel, contributing to fire spread and intensity. This paper presents a conceptual design framework for irrigated green firebreaks (iGFBs), which does not seek fine detail, or transferability, but rather it provides the initial concept for integrating vegetation design with supplemental irrigation to maintain fuel moisture and enhance fire-regulating ecosystem services. The framework is structured around landscape contexts, priority ecosystem services, integrated design solutions, and implementation considerations. A case study in Noosa Shire, Queensland, Australia, demonstrates how urban water reuse, including greywater and rainwater, can provide the needed irrigation in a WUI landscape. The iGFB concept highlights the potential to reduce fire intensity and slow fire spread while delivering co-benefits such as localised cooling and enhanced biodiversity. While the framework is site-responsive, its underlying principles are transferable to other WUI settings. Further research is required to evaluate the effectiveness of iGFBs under different fire and climate scenarios. Full article

Cardiovascular diseases remain the leading cause of global mortality, yet conventional diagnostics are episodic and clinic-centered, missing the dynamic physiological events that unfold between encounters. Wearable devices offer continuous, real-world monitoring and, together with artificial intelligence, digital biomarkers, and telecardiology, increasingly support a shift toward predictive, preventive, personalized, and participatory (P4) cardiovascular care. This narrative review synthesizes the contemporary evidence base for wearable cardiovascular technology and organizes it around the four pillars of P4 medicine, with the explicit aim of distinguishing what is clinically proven from what remains aspirational. The wearable ecosystem now spans consumer smartwatches, medical-grade ECG patches, smart textiles, and emerging soft bioelectronics, generating an expanding repertoire of digital biomarkers. Evidence is strongest where validation is most mature: atrial fibrillation screening, supported by large-scale studies, and structured heart-failure telemonitoring, associated with reductions in heart-failure hospitalization of 18–32% in structured programs. For acute coronary syndrome triage, cuffless blood pressure, cardiac rehabilitation, and AI-derived prognostic markers, the supporting evidence is growing but rests largely on analytical and early clinical validation rather than on demonstrated improvements in hard cardiovascular outcomes. Across all four pillars, translation is constrained by accuracy variability across demographic subgroups, regulatory fragmentation, data privacy concerns, interoperability deficits, and inequitable access for elderly, low-income, and low- and middle-income populations. Realizing the P4 promise will require harmonized validation standards, demographic-stratified accuracy reporting, equitable access strategies, and a clinical infrastructure capable of converting continuous wearable data into actionable decisions. Full article

Trace element contamination in Amazonian freshwater ecosystems threatens riverine food security. This study evaluated two post-harvest treatments—ethylenediaminetetraacetic acid (EDTA) and Lactobacillus fermentum—to assess cadmium (Cd) and lead (Pb) variations in edible muscle of four Amazonian fish species (Cichla monoculus, Pimelodus jivaro, Platynematichthys notatus, and Serrasalmus rhombeus). Concentrations were determined using ICP-OES. Platynematichthys notatus exhibited the highest baseline bioaccumulation, whereas C. monoculus showed the lowest. Although main treatment effects should be considered exploratory, distinct species-dependent trends emerged. EDTA achieved the highest Cd reduction in P. notatus (49.78%), while L. fermentum demonstrated notable Cd and Pb reductions in C. monoculus, P. notatus, and S. rhombeus. Conversely, relative concentration increases occurred in P. jivaro under both treatments, reflecting matrix-related effects. These findings suggest that post-harvest efficiency depends on fish species and metal type. Probiotic post-harvest processing represents a promising strategy for reducing dietary exposure to Cd and Pb in Amazonian fisheries, though optimizing operational parameters for community-level applications remains necessary. Full article

The accelerating contamination of global ecosystems by heavy metal ions, per- and polyfluoroalkyl substances (PFASs), microplastics and nanoplastics (MNPs), and emerging contaminants demands sensing technologies that are rapid, sensitive, selective, and field-deployable. Quantum dots (QDs) have emerged as leading candidates for environmental sensing; however, their performance is often interpreted empirically rather than through a unified understanding of the underlying excitonic physics. This narrative review presents a mechanistically integrated framework for QD-based environmental sensing, establishing the exciton, the spatially confined electron–hole quasiparticle, as the primary signal carrier in the most analytically powerful QD sensing modalities. A critical distinction is drawn between three categories of signal-generating processes: genuine excitonic transduction (photoinduced electron transfer, trap-state modulation, FRET, charge-transfer exciton formation, and binding energy modulation); non-excitonic optical phenomena, including the inner filter effect and light scattering, which are frequently misattributed as excitonic responses; and partially excitonic processes such as certain electrochemiluminescence pathways. Exciton fundamentals, confinement effects, and the influence of defects, dopants, and surface states are examined across carbon, chalcogenide, perovskite, and III–V QD families. A Defect–Exciton Energy Map is introduced as a rational design tool linking defect characteristics to excitonic response regime and sensing modality. Application of the mechanistic framework to heavy metal ions, PFASs, microplastics, and emerging contaminants demonstrates that sensing performance differences are mechanistically predictable from excitonic parameters rather than being arbitrary outcomes of materials choice. Benchmarking against competing platforms identifies conditions under which QD sensors offer genuine advantages. The roles of density functional theory, molecular dynamics, and machine learning in enabling rational sensor design are assessed. Key challenges, including stability, real-sample validation, standardisation, and toxicity, and future directions, including QD/two-dimensional material heterostructures and circular economy carbon QD platforms, are identified. Full article

Kidney transplant monitoring and early identification of graft dysfunction are central needs for long-term graft survival. Although kidney biopsy represents the gold standard in diagnostic procedures, its invasiveness may limit frequent longitudinal evaluation, highlighting the necessity of non-invasive diagnostic tools. Urine has emerged over the years as an easily obtainable source of cellular and molecular components derived from transplanted kidneys. Particularly, exfoliated cells and extracellular vesicles (EVs) represent complementary and interconnected markers able to reflect tissue injury, inflammatory signals, immune cell infiltration, and regenerative processes occurring in the graft. Also, recent advances in transcriptomics, proteomics, metabolomics, and single-cell technologies have expanded the diagnostic and mechanistic value of urinary liquid biopsy, enabling the identification of disease-specific molecular signatures associated with rejection, delayed graft function, fibrosis, and graft loss. This review discusses the emerging concept of an integrated urinary cell–EV ecosystem and highlights how integrated multi-omic approaches may transform non-invasive graft surveillance and advance precision medicine in kidney transplantation. Full article

The rapid digital transformation of the sports industry in Saudi Arabia under Vision 2030 has reshaped how football fans engage with sporting events through modern infrastructure, international competitions, and expanding digital media ecosystems. While sport participation and spectatorship have been associated with positive well-being outcomes, limited empirical evidence exists regarding how digitally enabled sports investments relate to football fans’ mental health. This study examines the associations between three dimensions of perceived sports industry investment, hosting international football events (HIFE), football infrastructure investment (FII), and digital platforms and broadcasting investment (DP&BI), and self-reported symptoms of depression, anxiety, and stress among 550 Saudi football fans. Data was analysed using partial least squares structural equation modelling (PLS-SEM). The findings indicate that HIFE was significantly associated with lower levels of depression, anxiety, and stress. FII was significantly associated with lower depression and anxiety, but not with stress. DP&BI was significantly associated with lower depression and anxiety, while its association with stress was non-significant. The results highlight the role of emerging digital sports ecosystems in supporting psychological well-being and demonstrate that different forms of sports investment contribute unequally to mental health outcomes. This study contributes to the literature on digital transformation in sport by illustrating how investments in digital platforms, broadcasting technologies, and digitally enhanced fan experiences are associated with mental health outcomes among football supporters. Practical implications are provided for policymakers and sport organisations seeking to leverage digital and physical sports investments to promote societal well-being within the framework of Saudi Vision 2030. Full article

This study develops a modular framework for the diagnostic application of microfoundational theory to examine how individual-level actions aggregate into macro-level technological capabilities and operational performance in innovation intermediaries within emerging economies. Grounded in Coleman’s bathtub model and the Viable System Model, we dissect three interdependent modules to diagnose systemic issues within institutional voids. Methodologically, we conduct a qualitative critical case study of a centenary Brazilian Research and Technology Organization, utilizing semi-structured interviews across three distinct organizational levels—senior executives, unit heads, and research leads—triangulated with eleven institutional management documents (2019–2024) through categorical content analysis. Theoretically, this research aims to establish a conceptual taxonomy that synthesizes Coleman’s micro–macro link, potentially serving as an analytical baseline for future cross-context evaluations of innovation intermediaries while exploring how meso–micro actions co-evolve with ecosystem-level environments. Practically, this study seeks to offer actionable governance levers for managers and policymakers, illustrating how the strategic deployment of dedicated internationalization units to buffer external complexity and the targeted cultivation of soft competencies in senior research leads may help overcome collaborative network isolation within late-development settings. Full article

Direct-to-cell (D2C) non-terrestrial networks (NTNs) based on 5G technology are emerging as a key complement to terrestrial cellular networks, extending connectivity to underserved and remote areas while enabling integration with existing mobile ecosystems. As these systems begin operating in frequency bands already used by terrestrial International Mobile Telecommunications (IMT) networks, coexistence becomes critical. This paper presents a victim-centric methodology for evaluating D2C interference into terrestrial 5G networks in the 694/698 MHz-2.7 GHz regulatory study range. Seven downlink carrier cases and four uplink carrier cases between 734 and 2620 MHz are evaluated. For a prescribed external interference-to-noise ratio, the external contribution is referenced to receiver thermal noise, while terrestrial intra-network interference remains part of the baseline and interfered signal-to-interference-plus-noise ratio (SINR). The resulting throughput loss is translated into candidate power-flux-density (PFD) and equivalent-power-flux-density (EPFD) protection levels. A reference non-geostationary-satellite-orbit (NGSO) system is used only to motivate the assumed receiver-exposure fractions; the numerical network results are therefore conditional on those exposure assumptions. The same external interference level produces approximately three times greater network throughput loss at base stations than at user equipment, so direction-specific protection levels are required. For downlink protection, the tested 3 dB noise-rise case gives candidate PFD levels from −109.23 to −98.17 dB(W/(m²·MHz)); for opposite-direction cross-border uplink protection, I/N = −6 dB gives candidate EPFD levels from −138.23 to −130.18 dB(W/(m²·MHz)) for non-AAS base stations. The approximately 11 dB offset for AAS cases results from the maximum-gain normalization used in EPFD and should not be interpreted as evidence of greater satellite exposure. These values are tested candidate levels rather than estimates of an exact 5% crossing point. Full article

While Artificial Intelligence (AI) has transformed materials discovery, the primary bottleneck to technological impact remains the transition from lab-scale synthesis to robust, industrial-scale manufacturing. Most promising materials perish in this depth, which is referred as the “valley of death”. The current review consolidates and critically evaluates the emerging ecosystem of AI-driven strategies and frameworks designed specifically to bridge this “lab-to-fab” gap. The review shifts our attention from property prediction to the engineering-driven problems of manufacturability. Furthermore, the review discusses the main obstacles to scaling the production of materials, such as reproducibility, process optimization in the context of uncertainty, and techno-economic viability, as well as the AI approaches being developed to overcome them. This includes Natural Language Processing (NLP) for method extraction, graph neural networks for reaction modeling, reinforcement learning for process control, Bayesian optimization for definition of process windows, and integrated AI–Techno-Economic Analysis (TEA) frameworks. Equally importantly, the review examines the principal failure modes that constrain practical deployment, including out-of-distribution generalization, incomplete and non-transferable literature-derived data, simulator-to-plant mismatch, uncertainty miscalibration, and the continued need for expert oversight. The article concludes with a forward-looking roadmap for the future of AI in chemical and materials engineering. The proposed conclusion is defined by a paradigm shift from simply finding new materials to creating viable, economical, and scalable pathways to produce them, thereby enabling a new era of synthesis-aware materials innovation. Full article

The growing accumulation of microplastics in marine ecosystems, coupled with the presence of emerging contaminants such as pharmaceuticals, represents an environmental problem that has received little attention to date. The present study evaluates the potential of microplastics to act as transport vectors for pharmaceuticals through their adsorption onto two plastic polymers widely used today: polyethylene terephthalate (PET) and medium-density polyethylene (MDPE) in seawater. As a control, the same experiments were conducted in ultrapure water (Milli-Q). Both plastics were exposed to a mixture of 29 pharmaceuticals belonging to different therapeutic classes over a 28-day period, with sampling conducted at various time intervals. The identification, quantification, and characterization of the compounds were performed using ultra-high-performance liquid chromatography coupled with mass spectrometry detection. Statistical analysis was performed using R-Studio software. Outcomes reveal that the type of polymer significantly influences adsorption, with MDPE being more efficient than PET. In contrast, the type of water and the therapeutic class of the drugs were not identified as determining factors. Furthermore, a positive, albeit moderate, correlation was observed between the hydrophobicity of the pharmaceutical and its adsorption efficiency on MDPE. These findings suggest that hydrophobic interactions play a key role in the adsorption of drugs onto microplastics, providing a solid foundation for future research, such as predictive models or mitigation strategies in aquatic ecosystems. Full article

The supply chain ecosystem (SCE) operating within an urban environment is characterised by continuous interactions among manufacturing, logistics, service, information, and energy flows across multiple smart city manufacturing-service clusters (SCMSCs). Within the SCE, intelligent production buildings (IPBs) emerge as multifunctional multistorey production-service infrastructures developed under conditions of limited urban land availability and increasing demand for localised manufacturing and service integration. These buildings operate under heterogeneous and dynamically changing energy-demand conditions, substantially complicating energy consumption management. This study develops a knowledge-driven coordination approach for the energy consumption management of IPBs operating within SCMSCs from the perspective of the urban SCE. IPBs are conceptualised as distributed environments with finite building-level power supply system capacity, where manufacturing, logistics, service, and digital processes dynamically compete for shared energy resources. A hierarchical representation of the SCMSC energy environment is proposed, capturing distributed interactions and heterogeneous electricity-demand profiles across interconnected clusters. An information-analytical system integrating monitoring, data acquisition, analysis, ML-based demand prediction, planning, and decision-support functions is developed to support predictive electricity-demand coordination. The proposed framework combines IoT-enabled monitoring with digital-twin-supported synchronisation of energy states for distributed coordination among IPBs. The proposed approach is evaluated through scenario-based analysis of an IPB operating within an urban manufacturing-service environment. The results indicate the potential of knowledge-driven coordination to improve energy-capacity utilisation, mitigate peak-load formation, and enhance operational stability within SCMSCs. Full article

The global deterioration of water quality caused by industrial, agricultural, and domestic pollutants poses significant threats to aquatic ecosystems and human health. The significance of this study lies in addressing a critical gap in the remediation of emerging contaminants by evaluating biochar-based adsorption under environmentally relevant hydrochemical conditions. Four activated biocarbons—A-ac-NiO-ext-1:1, A-ac-Fe₃O₄-NiO-ext-1:1, A-ac-Fe₃O₄-1:2, and A-ac-Alg—synthesized from apple pomace were investigated. Their adsorption performance was evaluated under four salinity conditions (M0–M3; total dissolved solids: 0–6123 mg/L), at temperatures of 298, 318, and 338 K, and over three consecutive adsorption–desorption cycles. DBP concentrations were determined by GC–MS. The maximum adsorption capacity, 6.25 mg DBP/g, was achieved by A-ac-Fe₃O₄-1:2 at 338 K under M3. Salinity effects were material-dependent: A-ac-NiO-ext-1:1 exhibited decreased adsorption with increasing ionic strength, whereas A-ac-Fe₃O₄-1:2 showed enhanced adsorption, potentially due to salting-out effects. A-ac-Fe₃O₄-NiO-ext-1:1 maintained stable performance across salinity conditions, while A-ac-Alg exhibited a nonlinear response. The main novelty of this study was the systematic comparative evaluation of four differently functionalized apple pomace-derived activated biochars, integrating the effects of salinity, temperature, thermodynamics, and cyclic reusability within a unified experimental framework. Full article

Ports are progressively evolving from traditional logistics nodes into integrated energy ecosystems, characterised by increasing electrification of maritime and land-based operations, the deployment of renewable energy sources, and the emergence of new and highly variable energy demand profiles. In this context, the main challenge is not only the availability of renewable energy but also the capacity of port energy systems to provide sufficient electrical power, flexibility, and resilience under increasing operational constraints. These issues are particularly relevant in Mediterranean ports, where limited grid capacity, infrastructure constraints, load variability, and interactions with surrounding urban areas strongly influence energy planning strategies. This paper proposes an integrated framework for the development of sustainable port energy hubs based on renewable generation, energy storage, green hydrogen systems, port microgrids, and intelligent energy management strategies (EMS). The main novelty lies in the integration of these energy vectors within a unified framework that explicitly accounts for the specific operational and infrastructure constraints of Mediterranean ports. The proposed approach aims to optimise the interaction between energy production, distribution, storage, and consumption, with particular attention to the role of hydrogen as a long-duration energy storage vector and as an energy carrier for selected port logistics applications. Through a data-driven Port Energy Baseline Assessment (PEBA), port operational characteristics are translated into quantified energy demand and power requirements, providing the basis for power adequacy assessment and the evaluation of alternative transition pathways. An illustrative application to a representative Mediterranean port, characterized by a peak electricity demand of 42 MW, illustrates how the framework quantifies power requirements, assesses power adequacy under infrastructure constraints, and compares alternative transition pathways based on renewable generation, battery storage, and hydrogen. Full article