Search Results (1,669)

Subdiffusion on graphs is often modeled by time-fractional diffusion equations; yet, its structural and dynamical consequences remain unclear. We show that subdiffusive transport on graphs is a memory-driven process generated by a random time change that compresses operational time, produces long-tailed waiting times, and breaks Markovianity while preserving linearity and mass conservation. While the subordination representation and complete monotonicity properties of the Mittag-Leffler function are classical, we develop a graph-based synthesis in which Mittag-Leffler dynamics admit an exact convex, mass-preserving representation as a superposition of Laplacian semigroups evaluated at rescaled times. This perspective reveals fractional diffusion as ordinary diffusion acting across multiple intrinsic time scales and enables new structural and dynamical interpretations of graphs. This framework uncovers heterogeneous, vertex-dependent memory effects and induces transport biases absent in classical diffusion, including algebraic relaxation, degree-dependent waiting times, and early-time asymmetries between sources and neighbors. These features define a subdiffusive geometry on graphs, enabling the recovery of global shortest paths, in contrast to the graph exploration of diffusive geometry, while simultaneously favoring high-degree regions. Finally, we show that time-fractional diffusion can be interpreted as a singular limit of multi-rate diffusion, in an appropriate asymptotic sense. Full article

A capacitive micromachined ultrasonic transducer (CMUT) was engineered and functionalized with either zeolitic imidazolate framework-8 (ZIF-8) dispersed in an AZ1512HS photoresist matrix or with graphene oxide (GOx) to operate as a gravimetric sensor for organic vapors. The sensor response was investigated under controlled humidity conditions during pulsed exposure to acetone, ethyl methyl ketone, isopropanol, kerosene, and diesel vapors. The impedance of the device was monitored by observing and tracking the resonance frequency shift as well as the resistance maximum shift, giving us the possibility to track two response parameters simultaneously. Different combinations of shifts in the sensor resonance frequency and the resistance maximum values were observed for the ZIF-8 functionalized device when exposed to the selected vapors, ranging from 12.4 kHz for ethyl methyl ketone to 2.4 kHz for diesel, and from 580 Ω for acetone to 20 Ω for isopropanol. Sensors functionalized with GOx did not demonstrate any significant response to either ethyl methyl ketone or isopropanol in the frequency domain. GOx-functionalized sensors were used for relative humidity monitoring in test gases. Besides the conventional response of the produced gravimetric sensing system, we also observed a strong relationship between the humidity of the gas mixture and the strength of the interaction of target gases with the functional film of the sensor. The results highlight the multidimensional nature of the sensor response and demonstrate how humidity influences the interaction between vapor molecules and the functional coating. This paper focuses on the characterization of the coupled behavior of resonance frequency and resistance shifts under controlled operating conditions. The presented experimental setup provides a basis for future concentration-dependent investigations and functional material comparisons in CMUT-based gravimetric sensing systems and provides a necessary foundation for accurate interpretation of future concentration-resolved measurements. Full article

To address the challenges of complex wiring, limited external power supply, and difficult maintenance in temperature monitoring during the construction of mass concrete, this study proposes a formwork-integrated self-powered temperature monitoring system based on hydration heat recovery. The system incorporates temperature sensing, thermal energy harvesting, energy storage and management, and wireless data transmission. Its heat-transfer performance, power-generation capability, and operational reliability are evaluated through experimental testing and seasonal condition analysis. The results show that interface optimization can substantially improve heat-transfer efficiency, enabling stable power generation and system operation even under low temperature-gradient conditions. The system exhibits a considerable energy surplus in summer and autumn, satisfies monitoring demands in spring, and is capable of achieving energy-neutral operation even in winter. Without requiring embedment within the concrete or reliance on an external power supply, the proposed system offers a convenient and efficient new solution for temperature monitoring during construction. Full article

As wildfires intensify globally due to climate change, accurate wildfire danger forecasting systems have become essential for effective disaster management and early warning. Fuel Moisture Content (FMC), defined as the ratio of water mass to dry fuel mass, plays a critical role in determining ignition probability and fire spread dynamics. This study conducts a comparative analysis of five major national wildfire danger rating systems: the National Fire Danger Rating System (NFDRS, USA), Canadian Forest Fire Danger Rating System (CFFDRS), European Forest Fire Information System (EFFIS), Australian Fire Danger Rating System (AFDRS), and the Korean Forest Fire Danger Rating System (KFDRS). Using a multi-criteria comparative framework, the systems were evaluated based on fuel classification structure, input variables, modeling approach, and spatiotemporal prediction resolution. The results reveal substantial disparities in spatial resolution (100 m to district-level), temporal resolution (hourly vs. daily), and fuel moisture modeling approaches (physics-based, index-based, and hybrid systems). Specifically, NFDRS and AFDRS provide high-frequency forecasting with hourly temporal resolution, operating at spatial resolutions of 1 km and 100 m, respectively, and incorporating dynamic fuel moisture modeling. In contrast, CFFDRS and KFDRS primarily rely on daily index-based predictions. Furthermore, while many global systems increasingly leverage remote sensing and machine learning for real-time FMC estimation, South Korea’s KFDRS remains predominantly empirical and weather-driven. The analysis identifies critical limitations in the KFDRS, including coarse spatial resolution (district-level), limited integration of Live Fuel Moisture Content (LFMC) modeling, and the lack of AI-augmented hybrid approaches. Accordingly, this study proposes a phased three-stage policy roadmap (2026–2035), emphasizing sensor-network expansion, AI–physics fusion modeling, and high-resolution (10 m) FMC mapping to enhance forecasting accuracy in complex terrains. These findings provide strategic insights for improving wildfire risk management and supporting the transition from reactive response to predictive wildfire forecasting under increasing climate variability. Full article

Dynamic response measurements support bridge monitoring and structural assessment because they are obtainable under operational loading and are sensitive to changes in stiffness, boundary conditions, and mass distribution. This article presents a structured scoping review of dynamic-response-based bridge monitoring and assessment. It covers damage-sensitive indicators, stiffness/capacity proxy inference, interpretation under operational and extreme loading, sensing with acquisition (contact, and indirect/drive-by), and data processing, machine learning and digital-twin integration for decision support. Evidence was identified through targeted searches in Scopus and The Lens with duplicate resolution in Zotero. The cited studies are compiled into a traceable evidence inventory linked to method families and decision objectives. The synthesis shows that global modal properties enable change screening but are highly confounded by environmental/operational variability. Localization and state characterization typically require denser or higher-fidelity sensing and signal conditioning. Finally, capacity-related inference using calibrated conversion models or machine learning (ML) surrogates remains context-bounded and validation-dependent. This review provides an end-to-end pipeline, evidence-maturity rubric, and conservative failure-mode checks with escalation logic that tie SHM outputs to inspection and analysis rather than direct condition declarations for bridge owners. This review is intentionally scoped and does not claim PRISMA-style comprehensiveness. Full article

Flexible conductive hydrogels hold great promise in wearable electronics and biomonitoring applications, yet their practical use is constrained by issues such as poor low-temperature tolerance, susceptibility to dehydration, and limited multifunctional sensing capabilities. This study successfully synthesized a dual-conductive lithium-ion and calcium-ion hydrogel based on acrylamide/gelatin via a simplified low-temperature one-pot polymerization method. At 60 °C, mixing acrylamide, gelatin, lithium chloride, and calcium chloride within 40 min constructed a network structure featuring covalent bonds, ionic bonds, and hydrogen bonds. The resulting material exhibited exceptional extensibility with a break elongation of 1408.5% and tensile strength of 134.2 kPa while maintaining strong adhesion to nine different substrates. It retained flexibility at −20 °C and demonstrated minimal mass loss (3% of initial value) after 10 days of aging. As a sensor, this hydrogel reliably responds to pressure, temperature, large-amplitude body movements, and subtle physiological signals like pulse and vocal cord vibrations. In animal simulation monitoring, its electrical resistance signals increased linearly with model body weight and remained stable between −20 °C and 20 °C. These results demonstrate the hydrogel’s broad application potential in wearable sensing, ecological monitoring, and smart agriculture. Full article

The progressive decline in functional β-cell mass in Type 2 Diabetes (T2D) is increasingly recognized not as a simple apoptotic loss, but as a complex erosion of cellular identity termed “dedifferentiation.” Central to this phenotypic shift is the metabolo-epigenetic axis, where mitochondria act as the primary sensing hub, transducing nutrient flux into biochemical signals that govern the chromatin landscape. This review synthesizes current evidence on how mitochondrial metabolites—including Acetyl-CoA, α-ketoglutarate, and NAD+—serve as obligatory co-factors for the epigenetic machinery. We explore how chronic metabolic stress triggers a “Systemic epigenetic destabilization,” leading to the loss of lineage-specific markers and the formation of persistent “metabolic scars.” Furthermore, we discuss the clinical implications of these changes, specifically regarding the phenomenon of metabolic memory and the molecular limits of β-cell reversibility. By integrating foundational transcriptional studies with emerging epigenomic data, we propose that targeting the mitochondrial–epigenetic axis offers a strategic window for re-differentiating failing β-cells and restoring glycemic homeostasis. Full article

Molecularly imprinted polymers (MIPs) are widely employed for selective adsorption of target molecules in sensing and separation applications. The architecture of MIP films can influence adsorption behavior, interfacial stability, and reusability, yet systematic investigations of these effects are limited. This study aimed to evaluate how different polypyrrole (PPy) MIP film architectures affect the adsorption, stability, and regeneration characteristics of geraniol-imprinted layers on gold electrodes. Geraniol-imprinted and non-imprinted PPy films were electropolymerized onto quartz crystal microbalance (QCM) substrates. Two film architectures were compared: (i) a single-layer geraniol-imprinted PPy film, and (ii) a double-layer film consisting of a non-imprinted PPy underlayer followed by a geraniol-imprinted layer. Film characterization was performed using cyclic voltammetry (CV) and electrochemical quartz crystal microbalance (EQCM) measurements. Adsorption–desorption cycles were conducted to assess mass uptake, signal stability, and regeneration performance. EQCM analysis revealed that the double-layer architecture exhibited enhanced frequency signal stability during repeated adsorption–desorption cycles compared to single-layer films, suggesting a stabilizing effect of the underlying non-imprinted PPy layer at the electrode interface. Geraniol-imprinted films demonstrated significantly higher mass uptake than non-imprinted controls, confirming the sensitivity provided by molecular imprinting. Single-layer films showed more variability in signal response and less consistent regeneration performance. The architecture of MIP films significantly affects adsorption behavior, stability, and regeneration on electrode surfaces. Incorporating a non-imprinted PPy underlayer can improve signal reproducibility and enhance the robustness of MIP-based sensing interfaces. These findings provide guidance for the rational design of MIP coatings for electrochemical sensors and QCM-active platforms. Full article

Herein, an electrochemical sensor is reported for the first time based on an ordered macro–microporous composite derived from metal–organic frameworks (MOFs) for the highly sensitive detection of auramine O (AO), a Group 2B carcinogen. The hierarchical pore architecture, integrating an ordered macroporous network with a microporous ZIF-8 framework, enables the uniform dispersion of a high density of catalytically active sites. The interconnected macroporous channels facilitate efficient mass transport and rapid removal of reaction byproducts, effectively preventing pore blockage and ensuring stable sensing performance during repeated measurements. Owing to these structural advantages, the proposed sensor exhibits outstanding analytical performance toward AO detection, with a sensitivity of 0.4843 μA μM⁻¹, a detection limit of 0.168 μM (S/N = 3), and a wide linear range from 0.5 to 50 μM. Moreover, the sensor demonstrates excellent selectivity and reproducibility, maintaining reliable responses even in the presence of 100-fold excess common food constituents such as tartrazine and glucose. Real sample analysis further confirms its high accuracy and operational stability. Overall, the electrochemical sensor based on silver nanoparticle-decorated ordered macro–microporous ZIF-8 synthesized via in situ reduction shows great potential as a portable and on-site tool for rapid AO detection in food. More broadly, ordered macro–microporous MOF-derived materials represent a promising platform for advanced electrochemical sensor applications. Full article

Electric-propulsion (EP) orbit raising from geosynchronous transfer orbit (GTO) to geostationary Earth orbit (GEO) requires long-duration, continuously steered low thrust, for which small pointing deviations may accumulate over time, and practical execution is constrained by spacecraft attitude and momentum management. This study develops a cross-layer command-to-execution framework that couples mission-level thrust-command generation with smooth trajectory planning of an EP vectoring arm. At the orbit layer, an engineering-oriented mission-level transfer model with dominant J₂ secular correction is used to construct a time-tagged sequence of thrust magnitude and direction commands for the GTO–GEO transfer. At the execution layer, a 4-DOF revolute arm is modeled using Denavit–Hartenberg kinematics, and the desired thrust directions are mapped to feasible joint trajectories through a direction-only inverse-kinematics formulation cast as a constrained nonlinear least-squares problem with cross/dot residuals, smoothness regularization, and warm-start propagation. In numerical simulation, the GTO–GEO transfer is completed in approximately 278 days with Δv ≈ 3665 m/s, corresponding to a propellant consumption of 175 kg (spacecraft mass from 1800 kg to 1625 kg). The planned joint trajectories remain smooth over the full horizon, with maximum inter-sample variations of 1.84° and 1.04° for the major and minor motion groups, respectively. The numerical geometric thrust-direction tracking error in the kinematic mapping remains at the millidegree level, with a mean of 7.39 × 10⁻⁴° and a P95 of 0.00101°. The results demonstrate that the proposed cross-layer interface can generate executable, low-bandwidth joint commands while preserving high geometric consistency with the desired thrust directions in the numerical kinematic mapping sense, thereby providing a practical basis for implementation-oriented studies of EP orbit transfer with vectoring manipulators. Full article

Maritime Autonomous Surface Ships (MASS) are progressing from proof-of-concept to engineering test and initial application phases due to advancements in intelligent sensing, automatic control, and communication technologies. However, numerous studies have shown that the improvement of automation level does not linearly reduce human factor risks. Instead, it exhibits more complex evolutionary characteristics at the medium automation level. In particular, MASS Level 2 (MASS L2) features a “system-dominated, human-supervised” operational mode, and its human factor risks have become one of the key factors restricting the safe operation, large-scale application and sustainable long-term deployment of autonomous ships. This study employs a systematic literature review to analyze 89 core articles (2020–2025) and summarizes the theoretical basis, risk characteristics, and evolutionary trends of human factor risk research in MASS L2. The review results indicate that the current research consensus has gradually shifted from the traditional “human error”-centered explanatory paradigm to a systematic understanding of “information mismatches, opacity, and coupling failures in the human-machine-shore collaborative system”. Typical human factor risks in MASS L2 are mainly manifested as the degradation of supervisory cognition and situation awareness, imbalance in trust in automation, vulnerability in mode switching and takeover, skill degradation, and structural risks in ship-shore collaboration. Based on these findings, this study constructs a classification system and a comprehensive analysis framework for human factor risks in MASS L2, reveals the interaction relationships and dynamic evolution mechanisms among different risk types from a system-level perspective, and further discusses the limitations of existing research in terms of methods, data, and engineering applicability. Finally, considering the development trends of autonomous ship technology, this study proposes future research directions in human factor theoretical modeling, dynamic risk assessment, system design, and operation management. This study aims to provide a systematic knowledge framework for human factor risk research in MASS L2 and offer references for the safety design, safety management, and development of higher-level automation of autonomous ships, while supporting the sustainable and safe advancement of the global intelligent shipping industry. Full article

This study investigated the antibiofilm and anti-quorum-sensing (QS) potential of endophyte extracts isolated from medicinal plants and their validation against Pseudomonas aeruginosa. Endophytes were isolated from the plants using the serial dilution method, and the extracts produced by these endophytes were screened for antimicrobial and biofilm-inhibition activity using assays. The efficient extract was biochemically characterized, followed by validation of its secondary metabolite content. Furthermore, QS-regulatory gene expression levels and microscopy were used to confirm inhibition of biofilm formation. A total of 12 cultures, including 8 bacterial and 4 fungal, were isolated and screened, demonstrating efficient antimicrobial activity (zone of inhibition of 18.8 mm) and 64.3% antibiofilm activity. The efficient endophyte isolated from Paederia foetida was identified as Bacillus xiamenensis MM07 by 16S rRNA gene sequencing. MM07 extract analyses by biochemical and Fourier transform infrared methods revealed the presence of diverse biomolecules. A dose-dependent inhibition was observed, achieving up to 83.5, 60.3, 73.2, 82.7, 83.2, and 15.1 in biofilm formation and exopolysaccharide, violacein, pyocyanin, protease, and alginate production, along with 63.2% swimming ability at 30 µg/mL, respectively. Gas chromatography-mass spectrometry analyses validated the presence of major secondary metabolites, including 3,3-dimethyl-4-methylamino-butan-2-one, 6-amino-2-methyl-, 1-iodo-2-methylundecane, and hexadecanoic acid, with the potential to inhibit biofilm and QS activity. Quantitative real-time polymerase chain reaction of QS regulatory genes (lasI, lasR, rhlI, and rhlR) and microscopy analysis confirmed the anti-QS properties, evidenced by a 40.3% decline in gene expression and biofilm inhibition by MM07 extract. These findings highlight the potential of novel B. xiamenensis MM07 endophyte from P. foetida as a sustainable source of biomolecules for combating biofilm-associated infections. Full article

Continuous monitoring of sitting posture is crucial for ergonomic assessment and fatigue prevention, yet many existing approaches rely on vision-based systems or single-modality sensing that are limited in capturing spatial and temporal biomechanical dynamics. This paper presents a multimodal smart-skin sensing system for spatial and temporal ergonomic fatigue analysis in sitting postures. The proposed platform integrates 42 distributed pressure, temperature, and vibration sensors arranged in 14 trimodal sensing nodes embedded across anatomical seating and back regions to enable real-time multimodal acquisition of human–chair interaction patterns. The study introduces an analytical framework combining anatomical heatmap visualization, temporal evolution analysis, delta pressure mapping, fatigue intensity estimation, and hotspot detection to characterize dynamic pressure redistribution during prolonged sitting. Experimental evaluations were conducted using a biomechanical mannequin and a single human participant with identical anthropometric characteristics (165 cm height and 62 kg body mass) across nine seated conditions, including neutral sitting, reclining, leaning, periodic shifting, and vibration-induced motion. Each posture condition was recorded as a time-series session and segmented into temporal phases to analyze fatigue evolution during prolonged sitting. Statistical analysis of pressure redistribution dynamics indicates significantly higher pressure drift in human measurements compared with the mechanically stable mannequin baseline (p < 0.001). The proposed framework provides a scalable sensing approach for ergonomic monitoring, intelligent seating systems, and human–machine interface applications. Full article

The fluorescence properties of organic molecules are largely determined by molecular architecture, π-conjugation, and electronic substituent effects. In this study, three novel pyrene-chromone Schiff base derivatives were designed and synthesized to investigate substituent-driven modulation of photophysical behavior. The compounds were obtained via condensation of 1-aminopyrene with three different chromone-based aldehydes and fully characterized by FT-IR, ¹H-NMR, and mass spectrometry. The molecular design involves a donor-π-acceptor architecture: pyrene donates electrons, while the chromene moiety accepts them, enabling charge transfer upon excitation. UV-Vis and fluorescence spectroscopy revealed intense absorption in the 430–440 nm range and tunable emission in the 540–565 nm region, corresponding to large Stokes shifts (107–125 nm). Substituent effects significantly influenced optical band gaps and emission intensities, with the nitro-substituted derivative exhibiting a reduced band gap and pronounced fluorescence quenching due to enhanced intramolecular charge transfer. Concentration-dependent absorption studies demonstrated linear Beer–Lambert behavior, indicating the absence of aggregation within the investigated range. These results establish clear structure–property relationships in pyrene-chromene Schiff bases and highlight their potential as promising candidates for optoelectronic and fluorescence-based sensing applications. Full article

Background/Objectives: Acute exercise remodels many interconnected biochemical pathways in metabolically active tissues. This remodeling involves the activation of the energy-sensing AMP-activated protein kinase (AMPK) to maintain cellular energy homeostasis. Critical energy reserves of glycogen, primarily stored in liver and skeletal muscle and known to interact with AMPK, are utilized to help meet increased energy demands with exercise. However, the breadth of metabolic pathways regulated by acute exercise and AMPK’s interactive roles with glycogen remain incompletely understood. This study therefore aimed to map mouse liver and skeletal muscle metabolite responses to continuous acute exercise and disruption of AMPK-glycogen interactions. Methods: Liquid chromatography–mass spectrometry-based untargeted metabolomics was used to measure the relative abundance of liver and gastrocnemius muscle metabolites at rest and following an acute bout of continuous treadmill running in wild type (WT) and AMPK transgenic mice with double knock-in (DKI) mutations in the β subunit carbohydrate binding module that mediates glycogen binding. Results: Over 200 total metabolites were identified/annotated across liver and skeletal muscle, including 45 metabolites responsive to exercise (p < 0.05; FDR < 0.1). Exercise-regulated metabolites included known metabolic pathways and metabolites never associated or with only emerging evidence related to exercise (e.g., ergothioneine) and/or AMPK-glycogen interactions (N6,N6,N6-trimethyl-L-lysine, a precursor of L-carnitine). Conclusions: Liver and skeletal muscle metabolomic profiles displayed shifts between WT and DKI mice at rest, with shifts also detected following a continuous acute exercise bout. An interaction effect was also observed in skeletal muscle, suggesting differential muscle metabolite responses to acute exercise in DKI mice that may contribute to their functional impairments in metabolic control and exercise capacity versus WT. Collectively, these findings expand the molecular landscape of acute exercise and reveal liver and muscle metabolites underlying exercise-induced metabolic responses. Full article