Search Results (881)

This paper introduces a hybrid two-stage registration framework for reconstructing three-dimensional (3D) kidney anatomy from macroscopic slices, using CT-derived models as the geometric reference standard. The approach addresses the data-scarcity and high-distortion challenges typical of macroscopic imaging, where fully learning-based registration (e.g., VoxelMorph) often fails to generalize due to limited training diversity and large nonrigid deformations that exceed the capture range of unconstrained convolutional filters. In the proposed pipeline, the Optimal Cross-section Matching (OCM) algorithm first performs constrained global alignment—translation, rotation, and uniform scaling—to establish anatomically consistent slice initialization. Next, a lightweight deep-learning refinement network, inspired by VoxelMorph, predicts residual local deformations between consecutive slices. The core novelty of this architecture lies in its hierarchical decomposition of the registration manifold: the OCM acts as a deterministic geometric anchor that neutralizes high-amplitude variance, thereby constraining the learning task to a low-dimensional residual manifold. This hybrid OCM + DL design integrates explicit geometric priors with the flexible learning capacity of neural networks, ensuring stable optimization and plausible deformation fields even with few training examples. Experiments on an original dataset of 40 kidneys demonstrated that the OCM + DL method achieved the highest registration accuracy across all evaluated metrics: NCC = 0.91, SSIM = 0.81, Dice = 0.90, IoU = 0.81, HD95 = 1.9 mm, and volumetric agreement ${\mathrm{DC}}_{\mathrm{Vol}}$ = 0.89. Compared to single-stage baselines, this represents an average improvement of approximately 17% over DL-only and 14% over OCM-only, validating the synergistic contribution of the proposed hybrid strategy over standalone iterative or data-driven methods. The pipeline maintains physical calibration via Hough-based grid detection and employs Bézier-based contour smoothing for robust meshing and volume estimation. Although validated on kidney data, the proposed framework generalizes to other soft-tissue organs reconstructed from optical or photographic cross-sections. By decoupling interpretable global optimization from data-efficient deep refinement, the method advances the precision, reproducibility, and anatomical realism of multimodal 3D reconstructions for surgical planning, morphological assessment, and medical education. Full article

Recently, continuous improvements in aircraft manoeuvrability and fuel consumption reduction have led researchers to investigate additional wing configurations based on morphing concepts. Morphing is also a potential solution for noise level reduction and may therefore represent an additional benefit. The advantages of morph-type schemes over traditional control surfaces during specific manoeuvres become a key parameter in the preliminary design stage. In this work, three types of airfoil morphing applied to a typical basic wing are considered and analysed: leading-edge morphing, trailing-edge morphing, and rib twist. The aerodynamic performance of each configuration is evaluated through a numerical procedure combining a panel method and a vortex lattice method. Drag reduction in morphed versus conventional wings under identical flight conditions is quantified, allowing the identification of the most efficient configuration. The analyses consider both roll manoeuvres and high-lift flight phases by evaluating changes in design parameters—such as chord-wise hinge positions, span-wise morph distribution, and morphing angles—which are compared and discussed. For the rolling manoeuvre, increasing the span-wise morphing region improves drag reduction, but not by more than 5%. When shifting the hinge position from 60% to 80% of the chord, similar drag reduction levels can be achieved, although the required morph angle differs under the same conditions. The effect of different drag components is also assessed, showing that the induced drag component is predominant for low aspect ratio wings, whereas parasite drag becomes significant at higher aspect ratios. Optimal geometrical configurations are presented and discussed for both manoeuvres. For the rolling, hinge positions yielding typical rolling moment coefficients (i.e., −0.05, −0.06, and −0.08) lie between 65% and 75% of the chord, with span-wise morphing ranges 40% < y_rib < 60% producing drag reduction up to 40% compared with a conventional wing. For the high-lift conditions, configurations between 65% < x_hinge < 80% and 50% < y_rib < 90% allow a drag reduction which can go up to 60%. Another beneficial effect is also observed for the yawing moment coefficient C_n with a reduction of more than 20% for larger aileron surfaces. Full article

Adaptive winglets improve aerodynamic efficiency by enabling geometry adjustments tailored to flight conditions. In this study, an engineering-oriented optimization framework is developed and applied to numerical aerodynamic evaluations based on the wing–winglet configuration of a KC-135 aircraft, under representative takeoff, climb, and cruise conditions. A Plackett–Burman design is employed to screen the 10 kinds of winglet geometric parameters, from which the dominant variables affecting drag are identified. Subsequently, response surface methodology is used to construct surrogate models and determine optimal parameter combinations for each flight phase, thereby defining a feasible morphing envelope for adaptive winglet operation. The results indicate that a coupled morphing of winglet height and cant angle constitutes the most effective morphing mode. Across the takeoff, climb, and cruise phases, the optimal morphing envelope involves a continuous transition from Height = 0.20b/2 and Cant angle = 86.3° at takeoff, to Height = 0.192b/2 and Cant angle = 8.2° during climb, and finally approaching the baseline configuration (Height = 0.135b/2, Cant angle = 20°) at cruise, while achieving a maximum drag reduction efficiency improvement of up to 8.8% at the climb phase. Full article

Long-term ecological data are rare but are highly desirable for assessing responses to ongoing environmental change. To assess temporal trends in abundance over time and establish a baseline for future comparison, we monitored a plethodontid salamander community for ten years. From 2014 to 2023, we sampled forest plots at Wooster Memorial Park (OH, USA) using a regular and standardized monitoring scheme. Of nine salamander species detected, four were common enough to permit statistical analysis. Three species (Eurycea bislineata, Plethodon cinereus and P. electromorphus) had no statistically significant abundance trends over time. The slimy salamander (P. glutinosus), however, showed a statistically significant decline in abundance. We also report on ecological differences between P. cinereus and P. electromorphus, which occur in sympatry at this site. Specifically, we document significant microhabitat differences between these species, which are suggestive of competition avoidance. Additional data are presented on color morph frequency, body size, sexual dimorphism, frequency of hybridization, mate choices, and phenology of surface activity. As global environmental change accelerates, such baseline information is essential to track organismal responses. We also provide a brief review of other long-term field studies in plethodontid salamanders. Full article

Unsteady atmospheric disturbances significantly compromise the stability of ornithopters, necessitating advanced turbulence-mitigation strategies. In contrast, natural flyers display remarkable aerodynamic adaptability through dynamic flow-control mechanisms such as covert feathers, enabling stability across unsteady flow regimes. Drawing inspiration from this biological phenomenon, this study presents the modeling and hybrid control of a kestrel-based ornithopter equipped with a Nature-Inspired Flow Control Device (NFCD) that replicates the adaptive feather deployment mechanism observed in kestrels. A reduced-order multibody bond-graph model (BGM) of the full ornithopter is developed, incorporating the main body, propulsion system, rigid wings, and the NFCD subsystem. The model captures key fluid-structure-interaction (FSI) effects between morphing feathers and surrounding airflow. A Linear Quadratic Regulator (LQR) ensures optimal performance under nominal gust conditions (≤3 m/s), while an H₂ controller activates during high-intensity gusts (≥4 m/s) to enhance disturbance rejection through electromechanical feather actuation. A gain-scheduled transition is employed in the intermediate gust range (3–4 m/s) to ensure a smooth transition between controllers. Simulations indicate up to 70% reduction in gust-induced oscillations and 32% gust-mitigation efficiency, achieved through feather actuation in the NFCD combined with hybrid control, stabilizing the ornithopter in less than 1.4 s under higher gust conditions. The close correspondence between simulated responses and previously reported findings validates the proposed approach. Overall, by merging biomimetic aerodynamics, nature-inspired flow control, and advanced control design, the LQR-H₂ governed NFCD provides a promising pathway toward gust-tolerant ornithopters capable of resilient and stable flight in unsteady atmospheric environments. Full article

Stimuli-responsive hydrogels are an emerging class of smart materials with immense potential across biomedical engineering, soft robotics, environmental systems, and advanced manufacturing. In this review, we present an in-depth exploration of their material design, classification, fabrication strategies, and real-world applications. We examine how a wide range of external stimuli—such as temperature, pH, moisture, ions, electricity, magnetism, redox conditions, and light—interact with polymer composition and crosslinking chemistry to shape the responsive behavior of hydrogels. Special attention is given to the growing field of 4D printing, where time-dependent shape and property changes enable dynamic, programmable systems. Unlike existing reviews that often treat materials, stimuli, or applications in isolation, this work introduces a multidimensional comparative framework that connects stimulus-response behavior with fabrication techniques and end-use domains. We also highlight key challenges that limit practical deployment—including mechanical fragility, slow actuation, and scale-up difficulties—and outline engineering solutions such as hybrid material design, anisotropic structuring, and multi-stimuli integration. Our aim is to offer a forward-looking perspective that bridges material innovation with functional design, serving as a resource for researchers and engineers working to develop next-generation adaptive systems. Full article

This paper presents a 3-Bridge LLC resonant converter featuring wide output voltage gain characteristics and a novel control method. To achieve operation within a narrower frequency control range, the proposed converter introduces one additional operational mode compared to the previously suggested 3-bridge topology. The converter is configured to have five distinct operation modes, controlled by the switching patterns of the main switches, to enable wide-range output voltage regulation. In each mode, frequency modulation is employed for output voltage control. Furthermore, a morphing control strategy is utilized to ensure stable output voltage regulation during mode transitions. The validity and practical applicability of the proposed 3-bridge LLC resonant converter with five operation modes are verified through experimental results from a 6 kW prototype. Full article

Designing high-speed aircraft for wide-speed-range operation remains a major aerodynamic challenge. This study investigates the unsteady aerodynamics of a continuously morphing airfoil from transonic to hypersonic regimes. A smooth morphing trajectory is constructed among transonic, supersonic, and hypersonic baseline shapes, and analyzed via high-fidelity unsteady Reynolds-averaged Navier–Stokes (URANS) simulations with a radial basis function (RBF) dynamic mesh. Two processes are examined: pure geometric morphing at fixed Mach numbers (Ma), and morphing coupled with flight acceleration. Key findings reveal two distinct adaptation features: (1) Transonic flow is highly sensitive to morphing (28.8% drop in lift-to-drag ratio), while supersonic flow is robust (<5% variation). (2) During coupled acceleration, the flow transitions smoothly—the shock evolves from a detached bow wave to an attached oblique structure, and the adaptive airfoil maintains a lift-to-drag ratio above 4 across Ma = 0.8–6. Additionally, wake vorticity transitions from organized shear layers to multi-scale clusters. These results elucidate the flow physics mechanism of continuous morphing and provide a framework for designing adaptive wide-speed-range aircraft. Full article

This study develops an explainable reinforcement learning (RL) control framework for hybrid ventilation in Mediterranean office buildings to enhance thermal comfort, energy efficiency, and long-term climate resilience. A working environment was created Using EnergyPlus to represent an office test cell equipped with natural ventilation and air conditioning. The RL controller, based on Proximal Policy Optimization (PPO), was trained exclusively on present-day Typical Meteorological Year (TMY) data from Beirut and subsequently evaluated, without retraining, under future 2050 and 2080 climate projections (SSP1-2.6 and SSP5-8.5) generated using the Belcher morphing technique, in order to quantify robustness under projected climate stressors. Results showed that the RL control achieved consistent, though moderate, annual HVAC energy reductions (6–9%), and a reduction in indoor overheating degree (IOD) by about 35.66% compared to rule-based control, while maintaining comfort and increasing natural ventilation hours. The Climate Change Overheating Resistivity (CCOR) improved by 24.32%, demonstrating the controller’s resilience under warming conditions. Explainability was achieved through Kernel SHAP, which revealed physically coherent feature influences consistent with thermal comfort logic. The findings confirmed that physics-informed RL can autonomously learn and sustain effective ventilation control, remaining transparent, reliable, and robust under future climates. This framework establishes a foundation for adaptive and interpretable RL-based hybrid ventilation control, enabling long-lived office buildings in Mediterranean climates to reduce cooling energy demand and mitigate overheating risks under future climate change. Full article

The MATα_HMGbox and HMG-box_ROX1-like domains of the MAT1-1-1 and MAT1-2-1 proteins, respectively, play essential roles in DNA binding and the subsequent regulation of gene transcription, controlling Ophiocordyceps sinensis sexual reproduction. Alternative splicing, differential occurrence and transcription of the MAT1-1-1 and MAT1-2-1 genes have been demonstrated in Hirsutella sinensis (GC-biased Genotype #1 of the 17 O. sinensis genotypes), suggesting self-sterility under heterothallic or hybrid outcrossing. In this study, the MATα_HMGbox domains of MAT1-1-1 proteins in wild-type Cordyceps sinensis isolates were shown to cluster into 5 clades in the Bayesian clustering tree and belong to diverse stereostructure morphs under 19 AlphaFold codes. The HMG-box_ROX1-like domains of MAT1-2-1 proteins, on the other hand, were shown to cluster into 2 branched Bayesian clades and belong to stereostructure morphs under 25 AlphaFold codes. Correlation analysis revealed that 1–3 amino acid substitutions in the DNA-binding domains of the mating proteins resulted in altered hydrophobicity and secondary and tertiary structures of the DNA-binding domains of the proteins, especially altered stereostructures of the hydrophobic cores formed by 3 critical α- helices within the functional domains of the proteins. Fungal origin analysis revealed possible heterospecific fungal sources of mating proteins with stereostructure variations in wild-type C. sinensis isolates, suggesting that alterations in DNA binding function and the subsequent regulation of mating-related gene transcription are involved in ensuring the accuracy and genetic diversity of heterothallic and hybrid reproduction of O. sinensis during the lifecycle of the C. sinensis insect–fungal complex. Full article

The evolution of modern warfare and civil exploration requires platforms that can operate seamlessly across the air–water interface. The folding-wing Hybrid Air and Underwater Vehicle (FUD) has emerged as a transformative solution, combining the high-speed cruising capabilities of fixed-wing aircraft with the stealth characteristics of underwater navigation. This review thoroughly analyzes the advancements and challenges in folding-wing FUD technology. The discussion is framed around four interconnected pillars: the overall design driven by morphing technology, adaptation of the propulsion system, multi-phase dynamic modeling and control, and experimental verification. The paper systematically compares existing technical pathways, including lateral and longitudinal folding mechanisms, as well as dual-use and hybrid propulsion strategies. The analysis indicates that, although significant progress has been made with prototypes demonstrating the ability to transition between air and water, core challenges persist. These challenges include underwater endurance, structural reliability under impact loads, and effective integration of the power system. Additionally, this paper explores promising application scenarios in both military and civilian domains, discussing future development trends that focus on intelligence, integration, and clustering. This review not only consolidates the current state of technology but also emphasizes the necessity for interdisciplinary approaches. By combining advanced materials, computational intelligence, and robust control systems, we can overcome existing barriers to progress. In conclusion, FUD technology is moving from conceptual validation to practical engineering applications, positioning itself to become a crucial asset in future cross-domain operations. Full article

This paper presents a unified aerodynamic design and optimization framework for morphing Blended-Wing-Body (BWB) Unmanned Aerial Vehicles (UAVs) operating in subsonic and near-transonic regimes. The proposed framework integrates parametric CAD modeling, Computational Fluid Dynamics (CFD), and surrogate-based optimization using Response Surface Methodology (RSM) to establish a generalized approach for geometry-driven aerodynamic design under multi-Mach conditions. The study integrates classical aerodynamic principles with modern surrogate-based optimization to show that adaptive morphing geometries can maintain efficiency across varied flight conditions, establishing a scalable and physically grounded framework that advances real-time, high-performance aerodynamic adaptation for next-generation BWB UAVs. The methodology formulates the optimization problem as drag minimization under constant lift and wetted-area constraints, enabling systematic sensitivity analysis of key geometric parameters, including sweep, taper, and twist across varying flow regimes. Theoretical trends are established, showing that geometric twist and taper dominate lift variations at low Mach numbers, whereas sweep angle becomes increasingly significant as compressibility effects intensify. To validate the framework, a representative BWB UAV was optimized at Mach 0.2, 0.4, and 0.8 using a parametric ANSYS Workbench environment. Results demonstrated up to a 56% improvement in lift-to-drag ratio relative to an equivalent conventional UAV and confirmed the theoretical predictions regarding the Mach-dependent aerodynamic sensitivities. The framework provides a reusable foundation for conceptual design and optimization of morphing aircraft, offering practical guidelines for multi-regime performance enhancement and early-stage design integration. Full article

Traditional wheeled ground robots offer high energy efficiency and excellent mobility on flat terrain but are constrained by their fixed structures, making it difficult to overcome obstacles or adapt to complex environments. To address these limitations, this paper presents a morphing wheeled land–air robot (MW-LAR) that integrates ground locomotion and quadrotor flight. By incorporating foldable arms and variable-diameter wheels, the MW-LAR can not only switch between ground and flight modes, but also achieve transitions between wheeled and legged locomotion in the ground mode. The foldable arms support seamless aerial-to-ground transitions and in-flight morphing, while the variable-diameter wheels facilitate efficient obstacle traversal on the ground. Benefiting from the design of foldable arms, two complementary landing approaches, namely direct quadrotor landing and ground-mode landing, are implemented to explore different aerial-to-ground transition modes and to improve landing safety and switching efficiency. Experimental results demonstrate that the MW-LAR achieves stable and energy-efficient performance across multiple locomotion modes and complex environments, highlighting its potential for integrated land–air mobility applications. Full article

To improve the continuous chordwise bending performance of morphing wings, this study proposes a rigid–flexible coupled wing rib structure and its control strategy. Initially, the optimal rigid–flexible hybrid configuration was optimized via the mean camber line parameterization and genetic algorithm. For the flexible segment, topology optimization was conducted using the load path method, followed by subspace-based shape–size alternating optimization; bionic “longbow” curved beams and ‘S’-shaped substructures were adopted to enhance deformability. Biomimetic pneumatic muscles were used as actuators, and a fuzzy-adjusted PI sliding mode controller was designed to address the issue that traditional PI sliding mode controllers cannot achieve precise control under non-optimal parameters or when there is a significant difference in deformation targets. Experimental results show that when the flexible rib deflects by 15°, the three-rib wing box achieves a 30° deflection, with stresses within the allowable limit of 7075Al-T6 (540 MPa) and a deformation error of only 7.6%. For the 15° downward bending control, the adjustment time is 6.06 s, the steady-state error is 0.19°, and the overshoot is 1.8%. This study verifies the feasibility of the proposed rigid–flexible coupled structure and fuzzy PI-SMC, providing a technical reference for morphing aircraft. Full article

Transonic shock buffet, characterized by large-amplitude self-sustained shock oscillations arising from shock wave/boundary layer interactions, poses significant challenges to aircraft handling quality and structural integrity. Conventional control strategies for buffet suppression typically require prior knowledge of unstable steady-state solutions or time-averaged flow fields and are only applicable to fixed-flow conditions, rendering them inadequate for realistic flight scenarios involving time-varying parameters. This study proposes a data-driven adaptive control framework for transonic buffet suppression utilizing localized morphing skin as the actuation mechanism. The control system employs a Multi-Layer Perceptron neural network that dynamically adjusts the local skin height based on lift coefficient feedback, with the target lift coefficient determined through a moving average method. Numerical simulations on the NACA0012 airfoil demonstrate that the optimal actuator configuration—a skin length of 0.2c with maximum deformation positioned at 0.65c—achieves effective buffet suppression with minimal settling time. Beyond this baseline case, the proposed method exhibits robust performance across different flow conditions. Furthermore, the controller successfully suppresses buffet under time-varying flow conditions, including simultaneous variations in Mach number and angle of attack. These results demonstrate the potential of the proposed framework for practical aerospace applications. Full article