Search Results (8,945)

Flapping-wing micro air vehicles (FWMAVs) have gained increasing attention due to their manoeuvrability, low acoustic signature, and suitability for confined or cluttered environments. Despite considerable progress, existing reviews treat actuation mechanisms and mechanical transmissions in isolation, leaving a gap in the comparative assessment of pulley-based and alternative flapping systems. This study provides a comprehensive and quantitative synthesis of the literature on FWMAV mechanical architectures, with particular emphasis on pulley-driven transmissions used in platforms such as the Nano Hummingbird and the Robotic Hummingbird. A structured review methodology was applied, incorporating a systematic database search, extraction of performance parameters, and cross-platform comparison of flapping frequency, lift generation, power consumption, lift-to-weight ratio, and material choices. The analysis identifies consistent scaling trends across motor-driven, piezoelectric, and hybrid actuation families and highlights the efficiency and stroke-amplification advantages of pulley-based mechanisms for centimetre-scale hovering MAVs. The review also identifies unresolved challenges, including durability of transmission materials, standardisation of performance metrics, and the need for high-fidelity aerodynamic characterisation. Overall, this work offers an integrated framework for understanding the trade-offs among actuation and transmission strategies and provides a roadmap to guide future research and the practical development of next-generation FWMAVs. Full article

Precise modeling of narrow gorges is challenging due to extreme confinement, hindering visibility and accessibility. These environments often render Global Navigation Satellite Systems (GNSS)-based positioning unfeasible, a difficulty compounded by water and dense vegetation. Consequently, multi-technique data fusion is required. This study proposes a robust methodology to generate high-resolution 3D models of such complex environments by integrating multiple aerial (e.g., Unmanned Aerial Vehicles, UAVs) and terrestrial techniques. A multi-sensor approach combined UAV-Light Detection and Ranging (LiDAR) and UAV-photogrammetry for external areas with Terrestrial laser scanning (TLS), Mobile Mapping System (MMS), and Spherical Photogrammetry (SP) for the canyon floor. Furthermore, the representativeness of these 3D models was analyzed against standard Digital Terrain Models (DTMs) for determining water height levels during flood events. A one-dimensional hydraulic (1DH) model compared the 3D mesh approach with the traditional 2.5D perspective in a challenging, narrow canyon prone to flooding. Our results show that traditional 2.5D DTMs significantly over- or underestimate water levels in narrow sections—failing to account for overhangs and vertical wall irregularities—whereas high-resolution 3D meshes provide a more realistic representation of hydraulic behavior. This work demonstrates that multi-sensor data fusion is essential for accurate flood risk management and infrastructure planning in complex fluvial environments. Full article

Waste tire rubber–soil mixtures feature low density, high energy dissipation, and low shear modulus, which are widely used in geotechnical engineering for vibration attenuation. In this study, the evolution of the small-strain stiffness characteristics of clay-rubber mixture (CRM) is investigated; a resonance column test was carried out to determine the small-strain stiffness characteristics of CRM samples with different confining pressures (${\sigma }_3$), rubber particle contents (${\mathrm{C}}_{\mathrm{rubber}}$), and rubber particle sizes (${\mathrm{D}}_{\mathrm{rubber}}$). The test results indicate that ${\sigma }_3$ can promote the dynamic shear modulus (G) of CRM and restrain the damping ratio (D). The rubber particles have a great influence on both G and D. Under the same conditions, G decreases significantly with the increase in ${\mathrm{C}}_{\mathrm{rubber}}$ and increases slightly with the increase in ${\mathrm{D}}_{\mathrm{rubber}}$, which indicates that rubber particles inhibit the development of G. D increases with the increase in ${\mathrm{C}}_{\mathrm{rubber}}$ and ${\mathrm{D}}_{\mathrm{rubber}}$. The results show that the contact area between clay particles and rubber particles increases with the increase in ${\mathrm{C}}_{\mathrm{rubber}}$, resulting in the decreases in G and D. The G–γ curves are analyzed by using the Hardin–Drnevich equation. Based on the fitting results, the maximum dynamic shear modulus ($G_{\max }$) is obtained. Therefore, the evolution of $G_{\max }$ with ${\sigma }_3$, ${\mathrm{C}}_{\mathrm{rubber}}$, and ${\mathrm{D}}_{\mathrm{rubber}}$ are analyzed, and an equation for the $G_{\max }$ of CRM considering the effects of ${\sigma }_3$, ${\mathrm{C}}_{\mathrm{rubber}}$, and ${\mathrm{D}}_{\mathrm{rubber}}$ is proposed. In addition, the D–γ curves can be well described by an empirical equation. Full article

Flatland metasurfaces provide a fundamentally distinct approach to optical gas sensing by confining light–matter interaction to planar, subwavelength interfaces, where resonant energy storage and near-field enhancement replace extended optical path lengths. This review presents a physics-driven perspective on metasurface-enabled gas sensing, focusing on how gaseous analytes perturb the complex eigenmodes of engineered planar resonators. Diverse sensing modalities, including enhanced molecular absorption, refractive index-induced resonance shifts, loss modulation, polarization conversion, and chemo-optical transduction, are unified within a common perturbative framework that links sensitivity to mode confinement, quality factor, and analyte overlap. The analysis highlights fundamental trade-offs imposed by material dispersion, intrinsic loss, and radiation balance across plasmonic, dielectric, polaritonic, and hybrid metasurface platforms operating from the visible to the terahertz regime. Attention is given to the limits of chemical selectivity in flatland architectures and to the role of functional materials, multimodal transduction, and computational inference in addressing these constraints. System-level considerations, including thermal stability, fabrication tolerance, and integration with detectors and electronics, are identified as critical determinants of real-world performance. By consolidating disparate approaches within a unified flatland framework, this review provides physical insight and design guidance for the development of compact, integrable, and application-specific optical gas sensing systems. Full article

Quantum walks (QWs) represent pillars of quantum dynamics and information processing. They provide a powerful framework for simulating quantum transport, designing search algorithms, and enabling universal quantum computation. Several physical platforms have been employed for their implementation, such as trapped atoms and ions, nuclear magnetic resonance systems, and photonic quantum architectures either in bulk optics or waveguide structures and fiber loop networks. Here we focus on the most promising and versatile approach, which is photonic integrated circuits. In this work, we review how the employment of this versatile experimental platform has allowed exploring several phenomena related to QW-based protocols, such as evolution in the presence of different kinds of noise. In this landscape, to the best of our knowledge, few examples report on the introduction of absorbing centers and their effects on the coherence of the dynamics. Here we present and discuss the results related to the absorbing boundaries in QWs, obtained through theoretical simulations and experiments conducted with the universal photonic quantum processors realized by QuiX Quantum. We analyze how localized absorption along one lattice edge affects the walker dynamics, depending on both the leakage probability and the initial injection site. Our results suggest that the presence of controlled losses modifies interference patterns and coherence without fully destroying quantum features and providing an effective resource for engineering on-chip QWs and simulating open quantum systems. Full article

Primary cutaneous lymphomas (PCLs) are a heterogeneous group of extranodal T- and B-cell neoplasms confined to the skin at diagnosis, characterised by distinct biological drivers, clinical behaviour, and therapeutic challenges compared with systemic lymphomas. Over the past decade, advances in genomic profiling, single-cell and spatial transcriptomics, and tumour microenvironment analysis have substantially refined the understanding of PCL pathogenesis, highlighting immune evasion, clonal heterogeneity, and compartment-specific disease dynamics as key determinants of outcome and treatment response. These insights have coincided with a rapidly evolving therapeutic landscape that includes immunomodulatory agents, targeted therapies, and ADCs, while also exposing persistent limitations related to diagnostic delay, response heterogeneity, resistance, and lack of validated predictive biomarkers. In this review, we provide a dermatology-focused synthesis of primary cutaneous lymphomas, integrating contemporary classification and clinicopathologic features with molecular pathogenesis and tumour microenvironmental insights of direct clinical relevance. We discuss current diagnostic and staging approaches, critically appraise established and emerging therapeutic strategies in cutaneous T- and B-cell lymphomas, and highlight unresolved clinical challenges and unmet needs, including biomarker integration, longitudinal disease monitoring, and translation of molecular advances into routine practice. Full article

Purpose: The aim of this narrative review is to update current knowledge on Moyamoya vasculopathy (MMV) by addressing key diagnostic debates—including laterality; genetic subtypes; regional epidemiology; and features distinguishing Moyamoya Disease (MMD), Moyamoya Syndrome (MMS) and their mimics. Methods: Key and representative studies were identified through PubMed/MEDLINE and Scopus, focusing on publications from 2014–2025 while also considering earlier seminal works. Results: MMD typically presents with bilateral steno-occlusion of the terminal internal carotid arteries (ICAs) and proximal middle and anterior cerebral arteries (MCAs/ACAs) due to concentric vascular thickening, accompanied by characteristic ‘puff-of-smoke’ collaterals, whereas MMS shows a similar but more often unilateral pattern with fewer collaterals, influenced by the underlying condition. However, this distinction often fails to reflect the full clinical and radiological variability of the Moyamoya spectrum. Atypical moyamoya-like patterns, often confined to M1 or A1 segments, further complicate diagnosis. Clinical manifestations ranged from asymptomatic cases to ischemic or hemorrhagic strokes, and occasionally seizures. Diagnosis relied on multimodal imaging (DSA, MRA, CTA), but genetic mutations, contributing to radiological variability, often complicate differentiation between MMD, MMS, and mimics. Management is pattern-specific: MMS and atypical forms are generally managed conservatively, whereas MMD frequently requires surgical revascularization, particularly in children and symptomatic adults. Nevertheless, variability within diagnostic categories limits the applicability of rigid treatment protocols. Conclusions: Current diagnostic algorithms remain limited. Integrating advanced imaging findings with clinical, genetic, and epidemiological data is essential to define the full disease spectrum, improve diagnostic accuracy, and inform patient management and outcome assessment. Full article

Electrochemical energy storage is pivotal in constructing new-type power systems. However, the large-scale deployment of energy storage stations poses severe safety challenges, particularly the risk of deflagration. The coupling of combustible accumulation within battery systems and the confined structure of storage units can trigger cascading thermal runaway and deflagration accidents. Existing research still falls short in systematically analyzing the deflagration risks and process evolution mechanisms in energy storage stations. To address this gap, this study develops a probabilistic risk assessment model that enables analysis of risk propagation through the integration of fault tree analysis (FTA) with a static fuzzy Bayesian network (BN). The proposed approach delineates the complete risk evolution pathway from battery thermal runaway to deflagration in a confined space. Diagnostic reasoning identifies a dominant risk escalation path initiated by internal short circuits, leading to thermal runaway, flammable gas release, and pressure accumulation due to inadequate pressure relief. Sensitivity analysis highlights gases ejected during thermal runaway (C22) and lack of pressure relief devices or insufficient venting area (C31) as the most influential risk drivers. This study thus offers a practical, model-based framework for enhancing targeted risk prevention and safety resilience in electrochemical energy storage station infrastructure. Full article

Telemedicine has the potential to substantially improve the care of children and adolescents with chronic respiratory diseases, including asthma, cystic fibrosis, bronchiectasis, and chronic respiratory failure. Digital health interventions—such as remote monitoring, virtual consultations, adherence-support tools, and educational platforms—can enhance disease control, continuity of care, and access to specialized services. Despite these opportunities, the implementation of telemedicine in pediatric respiratory care remains fragmented and uneven across healthcare systems. A central barrier to progress is the marked heterogeneity of outcome measures used to evaluate telemedicine interventions. Inconsistent definitions, variable endpoints, and limited follow-up reduce comparability across studies, hinder evidence synthesis, and impede translation into clinical guidelines, reimbursement models, and policy decisions. Consequently, telemedicine is often confined to isolated pilot projects rather than embedded within standard care pathways. This narrative review issues a Call to Action for the coordinated implementation and harmonization of telemedicine in pediatric chronic respiratory diseases. We advocate for the urgent development and adoption of a Core Outcome Set (COS) to standardize outcome measurement across clinical trials and real-world evaluations. In addition, we highlight the importance of integrating implementation science, economic evaluation, ethical oversight, and equity considerations into telemedicine research and deployment. Addressing regulatory fragmentation, ensuring interoperability, and aligning accreditation with reimbursement and Health Technology Assessment requirements are essential for sustainable scale-up. Finally, we emphasize the need for international collaboration among clinicians, researchers, policymakers, payers, technology developers, and patient advocacy groups to accelerate learning and promote equitable, evidence-based digital care models. Through coordinated action, telemedicine can evolve from a promising innovation into a reliable and accessible standard of care for children with chronic respiratory diseases. Full article

High-water-content dredged slurry from port dredging requires geotechnical improvement via drainage and consolidation. The small-strain dynamic properties (shear stiffness, damping characteristics) of reconstituted and consolidated clays are critical to the dynamic response and serviceability of overlying infrastructure. This study uses resonant column tests to investigate how initial water content affects the small-strain dynamic behaviour of reconstituted Ningbo soft clay, focusing on the evolution of the dynamic shear modulus ($G$) and damping ratio ($\lambda$) under different initial water contents and confining pressures. The test results indicate that the initial water content exerts a pronounced effect on the maximum small-strain shear modulus ($G_{\mathrm{m}\mathrm{a}\mathrm{x}}$) and on the strain-dependent degradation pattern of $G$. $G_{\mathrm{m}\mathrm{a}\mathrm{x}}$ increases with decreasing water content, and confining pressure exerts a more pronounced enhancing effect on $G_{\mathrm{m}\mathrm{a}\mathrm{x}}$ under low water content conditions. For specimens with different initial water contents, the maximum shear modulus normalised by confining pressure $(G_{\mathrm{m}\mathrm{a}\mathrm{x}}/{({\sigma }_0^{\mathrm{\text{'}}}/P_a)}^n)$exhibits a consistent, material-specific functional relationship with void ratio ($e$) within the investigated ranges. By contrast, initial water content exerts limited effects on the normalised $G/G_{\mathrm{m}\mathrm{a}\mathrm{x}}–\gamma$ and $\lambda –\gamma$ curves in the tested small-strain range. On this basis, an empirical model for small-strain shear modulus incorporating initial water content effects is proposed to guide dynamic soil parameter selection for geotechnical design under the tested conditions. Full article

Constrained by the low grade and poor floatability of the run-of-mine ore, the beneficiation of porphyry-type copper–molybdenum sulfide ores generates large quantities of molybdenum tailings, leading to significant environmental risks and resource losses and necessitating urgent recovery and reutilization. In this study, a representative sample of molybdenum tailings with a Mo grade of 0.354% was investigated to analyze its process mineralogy. The results show that molybdenite predominantly exists as fine, flaky particles intimately intergrown with quartz, pyrite, and aluminosilicate minerals, exhibiting an extremely low degree of liberation and an overall ultrafine particle size. Laboratory flotation tests show that the flotation kinetics conform to a first-order model; however, a considerable amount of molybdenum remains in the tailings, indicating that the mineralization process needs to be intensified. Through structural optimization and confined-space design, a vortex-based mineralization reactor was developed. Computational fluid dynamics simulations demonstrate that the mineralizer can generate flow fields with high turbulence intensity and dissipation rates and can induce high-energy, small-scale micro-vortices. On this basis, a semi-industrial rougher flotation system was established by coupling the developed mineralizer with a flotation column. Under optimized operating conditions, namely a feed pressure of 0.06 MPa and an impeller frequency of 20 Hz, single-stage treatment of the tailings produced molybdenum concentrates with a grade of 1.90% and a recovery of 81.29%, while the Mo grade of the tailings was reduced to 0.08%. The results are markedly superior to those obtained using a conventional laboratory flotation cell, demonstrating a substantial enhancement in mineralization efficiency and molybdenum recovery. The proposed approach, therefore, provides a practical reference for the flotation recovery of molybdenum tailings as well as other micro-fine, low-grade metal tailings. Full article

With the continuous advancement of the “dual-carbon” strategy, the penetration of renewable energy sources such as wind and photovoltaic (PV) power has steadily increased, imposing more stringent requirements on the safe and stable operation of modern power systems. As the core components of these systems, critical electrical devices operate under harsh conditions characterized by high voltage, strong electromagnetic interference (EMI), and confined high-temperature environments. Their operating status directly affects the reliability of the power supply, and any fault may trigger cascading failures, resulting in significant economic losses. To address the issues of low inspection efficiency, limited fault-identification accuracy, and unstable data transmission in strong-EMI environments, this study proposes an intelligent inspection system for power equipment based on multi-technology integration. The system incorporates a redundant dual-mode wireless transmission architecture combining Wireless Fidelity (Wi-Fi) and Fourth Generation (4G) cellular communication, ensuring reliable data transfer through adaptive link switching and anti-interference optimization. A You Only Look Once version 8 (YOLOv8) object-detection algorithm integrated with Open Source Computer Vision (OpenCV) techniques enables precise visual fault identification. Furthermore, a multi-source data-fusion strategy enhances diagnostic accuracy, while a dedicated monitoring scheme is developed for the water-cooling subsystem to simultaneously assess cooling performance and fault conditions. Experimental validation demonstrates that the proposed system achieves a fault-diagnosis accuracy exceeding 95.5%, effectively meeting the requirements of intelligent inspection in modern power systems and providing robust technical support for the operation and maintenance of critical electrical equipment. Full article

Aboveground storage tanks are used to store various fluids and chemicals for many industrial purposes. According to API standard 653, the structural integrity of these tanks must be regularly assessed. The U.S. EPA requires each operator to have a Spill Prevention, Control and Countermeasure Plan (SPCC) for aboveground storage containers. The accepted practice for inspection of these tanks, particularly the tank bottoms, requires removing the tank from service, emptying the tank, and interior entry for direct inspection of the structure. The required inspection operations are hazardous due to the chemicals themselves as well as the requirement to operate within confined spaces. An inspection from outside the tank would have significant cost and time benefits and would provide a large reduction in the risks faced by inspection personnel. Guided wave (GW) testing is a promising candidate for screening of storage tank walls and bottoms from the tank exterior due to the ability of GWs to propagate over long distances from a fixed probe location. The lowest-order transverse-motion guided wave modes (e.g., torsional vibrations in pipes) are a good choice for long-range inspection because this mode is not dispersive; therefore, the wave packets do not spread out in time. A common weakness of guided wave inspection is the complexity of report generation in the presence of multiple geometry features in the structure, such as welds, welded plate corners, attachments and so on. In some cases, these features cause generation of non-relevant indications caused by mode conversion. Another significant challenge in applying GW testing is development of probes with high-enough signal amplitudes and relatively small footprints to allow them to be mounted on short tank bottom extensions. In this paper, a new generation of magnetostrictive transducers will be presented. The transducers are based on the reversed Wiedemann effect and can generate shear horizontal mode guided waves over a wide frequency range (20–150 kHz) with SNRs in excess of 50 dB. The recently developed SwRI MST 8 × 8 probe contains an array of eight pairs of individual magnetostrictive transducers (MsTs). The data acquisition hardware allows acquisition using Full Matrix Capture (FMC) and analysis software reporting of anomalies based on Total Focusing Method (TFM) image reconstruction. This novel inspection package allows generation of reports that map out corrosion locations and provide estimates of defect widths. Case studies of this technology on actual storage tank walls and bottoms will be presented together with validation of processing methods on mockups with known anomalies and geometry features. Full article

With the increasing depletion of shallow resources, marine-based mineral resources in coastal and continental shelf areas are poised to become a new frontier for resource development. However, ions in brine solutions undergo complex water-rock interactions with rocks, affecting the engineering stability of marine-based rock masses. This study addresses engineering safety concerns arising from the long-term coupled effects of brine erosion and confining pressure on rocks during seabed mineral resource extraction. Using red sandstone as the research subject, it investigates the evolution of its mechanical properties under complex brine-erosion conditions. Experiments involved immersing red sandstone specimens in simulated seabed brine solutions for erosion cycles of 14, 21, and 35 days. Triaxial compression tests were conducted under confining pressures of 5 MPa, 10 MPa, and 15 MPa to systematically analyze the effects of erosion duration and confining pressure on rock strength, deformation, energy characteristics, and failure modes. Results indicate that brine erosion significantly reduces the strength and elastic modulus of red sandstone, but the effect is not simply linear. Instead, it follows a trend of initial slight strengthening followed by significant deterioration. During short-term erosion (21 days), some mechanical parameters slightly recovered, potentially due to temporary filling of fractures by brine ions. After long-term erosion (35 days), all mechanical properties markedly declined. This study aims to reveal the triaxial mechanical properties and energy evolution patterns of red sandstone under multi-ionic brine erosion, providing crucial experimental evidence for designing safe isolation layers and evaluating long-term stability in seabed mining. Full article

Autonomous drone navigation in confined tubular environments remains a major challenge due to the constraining geometry of the conduits, the proximity of the walls, and the perceptual limitations inherent to such scenarios. We propose a reinforcement learning (RL) approach enabling a drone to navigate unknown three-dimensional tubes without any prior knowledge of their geometry, relying solely on local observations from a Light Detection and Ranging (LiDAR) sensor and a conditional visual detection of the tube center. In contrast, the Pure Pursuit algorithm, used as a deterministic baseline, benefits from explicit access to the centerline, creating an information asymmetry designed to assess the ability of RL to compensate for the absence of a geometric model. The agent is trained through a progressive curriculum learning strategy that gradually exposes it to increasingly curved geometries, where the tube center frequently disappears from the visual field. A turning-negotiation mechanism, based on the combination of direct visibility, directional memory, and LiDAR symmetry cues, proves essential for ensuring stable navigation under such partial observability conditions. Experiments show that the Proximal Policy Optimization (PPO) policy acquires robust and generalizable behavior, consistently outperforming the deterministic controller despite its limited access to geometric information. Validation in a high-fidelity three-dimensional environment further confirms the transferability of the learned behavior to continuous physical dynamics. In particular, this work introduces an explicit formulation of the turn negotiation problem in tubular navigation, coupled with a reward design and evaluation metrics that make turn-handling behavior measurable and analyzable. This explicit focus on turn negotiation distinguishes our approach from prior learning-based and heuristic methods. The proposed approach thus provides a complete framework for autonomous navigation in unknown tubular environments and opens perspectives for industrial, underground, or medical applications where progressing through narrow and weakly perceptive conduits represents a central challenge. Full article