Search Results (2,797)

One of the engineering applications inspired by nature is bio-inspired wings. The aerodynamic properties and autorotation characteristics of samara wing models have been studied extensively using both experimental and numerical methods. However, the three-dimensional flow behavior and angle of attack interaction around a natural samara wing are not yet fully understood. This study investigates the flow behavior around a samara wing model, with the aim of underlying physics and qualitatively analyzing the flow field, as well as the aerodynamic forces and stresses. Since the samara wing and the flow around it are three-dimensional, the difficulty of experimental investigation was taken into account, and the numerical analysis was performed using Computational Fluid Dynamics techniques. The results obtained from the numerical solution of the governing equations for three-dimensional turbulent flow were verified with experimental data. The calculations were performed by varying the angle of attack of the model wing between 0 and 50 degrees at 10-degree intervals. Depending on the angle of attack, the velocity field around the wing, surface pressure, and stress distributions, vortex structures formed on the wing and streamlines were analyzed, and the results were presented. This study and its results on this model may lead to the development and optimization of the model and its use in turbines or air vehicles. Full article

Today, microfluidics has become a revolutionary field of engineering due to its wide range of applications, including lab-on-a-chip devices, microscale biochemical reactors, drug delivery systems, and disease diagnostics. Efficient fluid mixing has been a significant challenge in these systems due to the dominance of laminar flow and low-Reynolds number conditions, where mixing relies primarily on slow molecular diffusion. It is very difficult to achieve rapid mixing and homogeneous mixing within a limited length. In this study, a bioinspired passive micromixer is developed based on the cristae architecture of mitochondria, which is known for maximizing surface area and transport efficiency in biological systems. The micromixer incorporates cristae-like microstructures within a straight microchannel to produce continuous flow deflection, stretching, and folding, thereby promoting chaotic advection without relying on external energy sources. It also includes mitochondrial granules, such as micropillars, within the channel to disrupt streamline flow. Thus, a numerical investigation was conducted to design four different micromixer geometries: conventional T-channel, and T-channels with a single, double and triple matrix of cristae. The analysis was performed in COMSOL Multiphysics, in which “Laminar flow” and “Transport of diluted species” physics were used, and a stationary study was executed. Simulations were conducted at different Reynolds numbers (Re = 0.1–100) to observe the feasibility of the proposed designs. For analysis, the mixing index and concentration profiles at the outlet and along the length were also examined. The results showed that the high cristae density channel performed well, achieving a mixing index of 95.85% at Re = 0.1 and 85.84% at Re = 100, proving that the proposed mitochondria-inspired cristae Mito-mixer delivers efficient mixing over a broad Reynolds-number range while maintaining a compact, length-efficient design. Full article

Event cameras are bio-inspired vision sensors offering low latency, low power consumption, and high dynamic range, capturing motion with microsecond-level precision via a per-event triggering mechanism. Despite these advantages, the inherent sparsity and lack of color in event data hinder direct analysis, necessitating advanced deep learning approaches. To achieve low-latency and high-precision motion segmentation for indoor robotic applications, this paper introduces a dual-branch decoupled CNN framework. Specifically, Principal Component Analysis (PCA) is utilized to project 3D event point clouds into 2D motion trend maps, capturing local motion priors while suppressing ambiguity in structured environments. Concurrently, an Event Leaky Integration (ELI) model, inspired by biological membrane potentials, is designed to enhance the structural representation of sparse events. Within this framework, separate branches respectively perform motion validation and shape extraction and are fused via a Spatial Gated Fusion (SGF) module to suppress static background interference. It is demonstrated experimentally that with an input window of only 10 ms, the proposed method achieves a 77% average mIoU across five indoor test scenarios from the EV-IMO dataset with an inference latency of 10 ms per frame. Compared to state-of-the-art methods like MSRNN and GCN, which required 30–300 ms event slices, our framework achieves a favorable trade-off between computational efficiency and segmentation accuracy, maintaining competitive performance under ultra-short time windows for indoor event-based motion processing. Full article

Ulcerative colitis (UC) is a chronic inflammatory disorder of the colon characterized by dysregulated mucosal immunity and progressive epithelial injury. Upadacitinib (UPA), a selective Janus kinase 1 (JAK1) inhibitor, has demonstrated clinical efficacy in UC, but its therapeutic application is often constrained by adverse effects arising from systemic drug exposure. This underscores the need for advanced, site-specific delivery systems that enhance local efficacy while minimizing systemic toxicity. Here, we developed a colon-targeted natural lipid nanoparticle formulation of UPA (UPA-nLNP) to improve therapeutic performance and safety. UPA-nLNP was prepared by thin-film hydration using digalactosyldiacylglycerol (DGDG), monogalactosyldiacylglycerol (MGDG), and phosphatidic acid (PA), mimicking the lipid composition of ginger-derived exosomal particles, and was characterized for particle size, surface charge, and encapsulation efficiency. The formulation exhibited excellent mucus-penetrating capability and was evaluated in a dextran sulfate sodium (DSS)-induced acute colitis model in C57BL/6 mice following oral administration (5 mg/kg). Pharmacokinetic analysis demonstrated increased colonic accumulation with reduced systemic exposure compared to free UPA. Treatment with UPA-nLNP improved body weight recovery, reduced disease biomarkers, and suppressed key proinflammatory cytokines in the colon, with no evidence of systemic toxicity. This innovative strategy holds strong potential to enhance the clinical utility of JAK1 inhibitors by providing a safer and more effective therapeutic approach for ulcerative colitis. Full article

The biomechanics of frog jumping has been a subject of significant interest in both biology and engineering, driven by the high efficiency of their movement. This study presents the dynamic simulation of a frog’s complete jump cycle, from take-off to landing and re-stabilization, to advance the development of bio-inspired jumping robots for irregular terrains. As a primary contribution, and unlike previous studies that focus exclusively on the propulsion phase, this work addresses all stages, using direct servomotor actuation without mechanical energy storage. Biological joint kinematics were mathematically characterized using Cubic Smoothing Splines. By empirically tuning the smoothing parameter (p), the trajectories achieved the continuous differentiability required for electromechanical actuation. These curves were implemented into a 3D multibody simulation (Altair Inspire), where a PID-based tracking framework managed the mechanically nonlinear multibody dynamics governing the jump (arising from contact forces, impacts, and time-varying inertial effects) to ensure stabilization during the complex landing phase. Validating the model against previous studies, the simulation successfully achieved a maximum horizontal jump distance of 24.12 cm (4.02 body lengths) and a peak velocity of 1.45 m/s. The kinematic fidelity of the model was mathematically validated, yielding a maximum Normalized Root Mean Square Error (NRMSE) of 4.121% relative to biological reference trajectories. Furthermore, the robustness of the landing and re-stabilization phases was demonstrated through a continuous double jump covering a total distance of 45.83 cm. Finally, a dynamic scaling analysis was performed to evaluate the feasibility of implementing real motors. Ultimately, this study establishes a mathematically robust framework for replicating frog-inspired jumping dynamics, contributing a transferable methodology for the design and control of articulated bio-inspired robotic systems. Full article

Flexible heat exchangers with intricate three-dimensional (3D) geometries exhibit superior mechanical and thermal performance compared with traditional two-dimensional (2D) designs. Their ability to offer greater design freedom and unique functionalities makes them particularly attractive for wearable medical devices. This study investigates flexible heat exchanger technologies in three main directions: (i) miniaturisation, (ii) integration of physical and mathematical models, and (iii) enhanced adaptability through heterogeneous design integration. Through a combination of literature review, mathematical modelling, and experimental analysis, the thermal efficiency of several configurations is compared, including basic thermoplastic polyurethane (TPU) tubes and 3D bio-inspired TPU tubes with aluminium-finned structures. The findings establish a foundation for the development of next-generation flexible wearable medical cooling devices with improved thermal management capabilities and practical applicability in industrial design. Furthermore, the outcomes of this research will directly support the development of improved wearable cooling devices within a UK-based medical device SME, Paxman Scalp Coolers, facilitating the translation of advanced heat exchanger designs into clinically relevant and commercially viable solutions. Full article

Flapping-wing drones (FWDs), owing to their compact size and operation in cluttered and unsteady airflow environments, encounter significant aerodynamic and stability challenges. Studies of avian flight reveal that falcons and other raptors actively deflect their covert feathers to mitigate gusts and maintain stable flight. Drawing inspiration from this mechanism, this study presents a peregrine falcon-inspired Active Flow Control Unit (AFCU) integrated with a Deep Deterministic Policy Gradient (DDPG)-based deep reinforcement learning (DRL) controller for real-time disturbance attenuation. The AFCU employs mechanical covert feathers (MCFs) that actuate to dissipate gust loads during high wind conditions. A reduced-order bond graph model that encapsulates the nonlinear interaction between the primary wing and the feather-based active flow control surfaces is created which is used as a dynamic training environment for the DDPG agent. Utilizing closed-loop interactions, the successfully obtained learned policy produces optimal actuator forces to reduce feather-displacement error and aerodynamic load variations. The designed controller stabilizes the internally unstable open-loop AFCU, attaining near-zero steady-state error and settling times under 1.6 s for gust magnitudes ranging from 12.5 to 20 m/s. Simulations further illustrate a reduction of up to 50% in gust-induced loads compared to traditional approaches. This integration of bio-inspired design with learning-based active flow control offers a viable avenue for the development of highly adaptive and gust-resilient flapping-wing aerial systems. Full article

Innovation in the field of bioinspired therapeutic anticoagulants, as an alternative to heparin and its derivatives, is increasingly focused toward the discovery of new molecules from natural sources. Inspired by the compelling observation that marine organisms possess a wide array of acidic polysaccharides (APs) within their extracellular matrix (ECM) with promising anticoagulant potential, this study investigates AP topographic distribution, content, and bioactivity in the body of seven phylogenetically distant Mediterranean sponge species. Tissue architecture was evidenced by Alcian Blue histological staining whereas biochemical analyses were carried out on APs purified from papain-digested tissue extracts using anion-exchange chromatography. Four polysaccharide fractions were obtained and assessed for hexuronic acid content. The two most abundant ones, up to 98% of the total, were characterized by electrophoretic analyses, and assessed in vitro for inhibitory activity on blood coagulation. Histology evidenced a heterogeneous distribution of APs within the sponge’s ECM, along with marked interspecific variability in both concentration and electrophoretic profiles. Neither Tethya aurantium nor Crambe crambe showed any significant in vitro effects on coagulation, whereas the other species exhibited a strong inhibitory effect on both activated partial thromboplastin time (aPTT) and thrombin time (TT), comparable to standard heparin (Hep). Concerning aPTT, both I. retidermata and H. communis reached the endpoint of 300 s at 5 µgUA/mL, whereas S. spinosulus, O. lobularis, A. aerophoba reached it at 10 µgUA/mL. With reference to TT, A. aerophoba, I. retidermata, S. spinosulus and H. communis had comparable effects on coagulation time with respect to Hep (endpoint at 5 µgUA/mL), whereas O. lobularis was less effective (endpoint at 100 µgUA/mL). These findings show that Porifera, one of the most basal Metazoa, have an ECM rich in APs with anticoagulant properties towards both intrinsic and common pathways of coagulation, consistent with known inhibitory mechanisms reported for certain marine sulfated polysaccharides derived from other invertebrate taxa. These molecules, obtainable through sustainable blue technology, represent compelling candidates for bioinspired next-generation anticoagulant therapeutics, with broader applications in regenerative medicine and tissue engineering. Full article

Background: Crocodilians rarely develop cancer despite long lifespans and continuous exposure to environmental carcinogens, suggesting robust natural anti-tumor defense mechanisms. Methods: We investigated the anti-cancer activity of sera derived from the phylogenetically related species—alligators, crocodiles, and chickens, and studied their underlying immune mechanisms. The anti-tumor activity of alligator serum was tested in murine models of melanoma and lymphoma. Results: Alligator serum (AS) and its (NH₄)₂SO₄-precipitated fraction (ASa) showed rapid and potent cytotoxicity toward multiple murine and human cancer cell lines while sparing non-malignant human cells. Importantly, ASa attenuated melanoma and lymphoma tumor growth in mice. Electrophysiological analyses in PN71 cancer cells treated with ASa revealed rapid membrane depolarization and formation of high-conductance pores consistent with Complement-mediated membrane attack complex (MAC) activity. Proteomic analyses identified the Complement component C5 as a major protein enriched in active fractions, implicating the Complement system in cancer cell killing. Based on phylogenetic similarity of C5, crocodile and chicken sera exhibit alligator-like comparable anti-cancer activity. Mechanistic studies in chicken serum showed that the anti-cancer activity depends on Ca²⁺ and Mg²⁺ ions, terminal Complement components (C5–C8), and IgM antibodies that initiate Complement activation. Immunodepletion of IgM from CSa significantly reduced cytotoxicity, whereas purified chicken IgM activated human Complement to induce cancer cell death. Conclusions: These findings identify a conserved IgM–Complement immune mechanism capable of selectively targeting malignant cells. The evolutionary conservation and cross-species functionality of this pathway highlight its potential as a bio-inspired strategy for developing novel Complement-based cancer immunotherapies. Full article

The selective harvesting of leaves from flexible-stem crops remains a major challenge in agricultural mechanization due to stem compliance, heterogeneous petiole strength, and unstable tool–crop interaction. To address these issues, a bio-inspired ring-cutting and compliant clamping harvesting mechanism is proposed for low-damage selective harvesting under complex terrain conditions. Inspired by the adaptive attachment behavior of octopus suckers, a flexible compliant clamping interface combined with a ring-shaped sliding cutting structure was developed to stabilize flexible stems during harvesting. A coupled kinematic–force analytical model was established to characterize the interaction between tool motion, stem feeding, and cutting behavior. In addition, a sliding cutting mechanics model was introduced to analyze the relationship between cutting force and sliding angle. Dynamic multibody simulations were performed using ADAMS to verify the motion feasibility and trajectory stability of the proposed harvesting mechanism. Bench-scale experiments were conducted using mulberry branches as a representative flexible-stem crop, and a response surface methodology based on a Box–Behnken experimental design was applied to optimize key operational parameters. The optimal parameter combination included a chain linear speed of 0.18 m·s⁻¹, a feeding speed of 0.30 m·s⁻¹, and an installation angle of 36°. Under these conditions, the missed harvest rate was reduced to 9.2–9.8%, demonstrating improved harvesting stability compared with conventional rigid cutting mechanisms. The results indicate that integrating compliant stabilization with sliding cutting provides an effective engineering strategy for selective harvesting of flexible-stem crops in complex agricultural environments. Full article

Automatic modulation recognition (AMR) is increasingly relevant to communication-sensing front ends in robotic and human–robot collaborative systems, where reliable spectrum awareness and adaptive wireless reception are desired. However, existing methods often degrade sharply at low signal-to-noise ratios (SNRs), and large language models (LLMs) are not natively compatible with continuous I/Q signals due to the inherent modality gap. We propose BioLAMR, a GPT-2 adaptation framework for AMR inspired by the auditory system’s parallel time–frequency processing and cortical hierarchy. The framework combines bio-inspired dual-domain feature extraction with parameter-efficient LLM adaptation. BioLAMR includes three components. First, a lightweight dual-domain fusion (LDDF) module extracts complementary time- and frequency-domain features and fuses them through channel and spatial attention. Second, a convolutional embedding module converts continuous I/Q signals into GPT-2-compatible sequences without discrete tokenization. Third, a hierarchical fine-tuning strategy updates only 8.9% of parameters to preserve pretrained knowledge while adapting to modulation recognition. Experiments on the RadioML2016.10a and RadioML2016.10b benchmarks show that BioLAMR achieves overall accuracies of 64.99% and 67.43%, outperforming the strongest competing method by 2.60 and 2.47 percentage points, respectively. Under low-SNR conditions, it reaches 36.78% and 38.14%, the best results among the compared methods. Ablation studies verify the contribution of each component. These results demonstrate that combining dual-domain signal modeling with parameter-efficient GPT-2 adaptation is an effective route to robust AMR in challenging wireless environments. Full article

Collaborative operation of heterogeneous UAV swarms in dense urban environments remains challenging because right-of-way allocation is often rigid, frequent replanning consumes considerable onboard computation, and paths obtained by purely mathematical optimization may not be easy to execute under real dynamic constraints. This paper presents a physics-informed, event-triggered path planning and control framework, termed Physics-Informed SSA-MPC. Its global search layer is built on the Sparrow Search Algorithm (SSA), whose search mechanism originates from sparrow foraging and anti-predatory behaviors. On this basis, the method combines an event-triggered Stackelberg game for airspace coordination, a physically constrained SSA for global path generation, and an event-triggered MPC for local replanning. Battery State of Health (SoH) is incorporated into the adaptive search process, while Lévy-flight updates are limited by the maximum available acceleration to avoid infeasible path mutations. Local replanning is activated only when predicted safety ellipsoids overlap or tracking errors exceed prescribed thresholds, which helps reduce redundant computation. Simulations in a digital twin of Lujiazui, Shanghai, show that the proposed method shortens path length by 3.3% to 14.9%, reduces obstacle-avoidance latency to 45 ms, and achieves a 100% engineering feasibility rate. Full article

The development of More Electric Aircraft (MEA) necessitates that Electro-Hydrostatic Actuator (EHA) controllers achieve exceptional power density within rigorously constrained volumes. However, the compact layout design of these controllers constitutes a challenging NP-hard problem, characterized by strong multi-physics coupling—such as electromagnetic, thermal, and structural fields—and complex nonlinear constraints. Traditional meta-heuristic algorithms frequently suffer from premature convergence and struggle to balance global exploration with local exploitation. To address these challenges, the core contribution of this paper is the proposal of a novel Fractional-Order Anteater Foraging Optimization Algorithm (AFO), which is successfully applied to an established EHA controller layout optimization model. At the algorithmic level, by incorporating the Grünwald–Letnikov fractional derivative, the algorithm exploits the inherent memory property of fractional calculus to dynamically adjust the search step size and direction based on historical evolutionary information, thereby preventing stagnation in local optima. At the engineering application level, a high-fidelity mathematical model of the EHA controller is established, comprising 11 design variables and 10 critical physical constraints, including parasitic inductance minimization, thermal radiation efficiency, and electromagnetic interference (EMI) isolation. Extensive validation against the CEC2005 and CEC2022 benchmark functions demonstrates the superior convergence accuracy and stability of the AFO algorithm. In a specific EHA case study, the proposed method reduced the controller volume by 33.9% while strictly satisfying all multi-physics constraints, compared to traditional methods. Furthermore, a physical prototype was fabricated based on the optimized layout, and experimental tests confirmed its stable operation and excellent thermal performance. The results validate the efficacy of incorporating fractional calculus into bio-inspired algorithms to solve complex, high-dimensional engineering optimization problems. Full article

In-pipe robots must navigate narrow, curved passages where rigid mechanisms often require bulky steering units. Soft crawlers offer better compliance but typically rely on multiple actuators or reconfigurable contacts to achieve multi-directional motion. Drawing inspiration from biological soft crawlers that exploit directional friction and coordinated anchor–slip patterns, this study focuses on locomotion principles observed in caterpillars, water boatmen, and whirligig beetles. Based on these bioinspired concepts, we present a tendon-driven soft in-pipe robot that combines continuum bending–twisting deformation with modular anisotropic friction pads (AFPs), enabling three locomotion modes using only two motors. AFP inclination, curvature, and ridge geometry were optimized through friction tests, constant-curvature modeling, and finite element analysis to enhance directional adhesion on flat and curved surfaces. A deformation-based locomotion framework was developed to couple tendon actuation with friction orientation, achieving longitudinal crawling, transverse translation, in-place rotation, and smooth transitions via programmed twisting. Driving experiments demonstrated repeatable anchor–slip locomotion with average speeds of 28.6 mm/s, 15.7 mm/s, and 11.5°/s for the three modes. Pipe tests in straight, curved, and T-junction sections further validated stable contact and reliable gait transitions. These findings highlight the potential of friction-programmed continuum robots as compact, bioinspired platforms for advanced in-pipe inspection and diagnostic tasks. Full article