Search Results (124)

Module-level free-space optical interconnects require actuators to combine both large stroke and high stability. To address this core trade-off that plagues traditional folded-beam actuators, we have developed a millimeter-scale MEMS electromagnetic actuator integrating a Differential Motion Rejection (DMR) unit with a rigid frame. Its performance was systematically evaluated through magnetic–structural coupling modeling, finite element simulation, and experiments. The actuator achieved millimeter-scale stroke under sinusoidal drive, with a primary resonant frequency of approximately 31 Hz. The introduction of the DMR and frame proved highly effective: the out-of-plane displacement at resonance was reduced by about 97%, the static Z-direction stiffness increased by over 50 times, and the displacement crosstalk decreased to 0.265%. Optical testing yielded a stable deflection angle of approximately ±21°. These results demonstrate that this design successfully combines large stroke with high stability, significantly suppressing out-of-plane parasitic motion and crosstalk, making it suitable for module-level optical interconnect systems with stringent space and stability requirements. Full article

Accurately modeling and representing the collective dynamics of large-scale robotic systems remains one of the fundamental challenges in swarm robotics. Within the context of agricultural robotics, swarm-based coordination schemes enable scalable and adaptive control of multi-robot teams performing tasks such as crop monitoring and autonomous field maintenance. This paper introduces a cohesive Potential Linked Nodes (PLNs) framework, an adjustable formation structure that employs Artificial Potential Fields (APFs), and virtual node–link interactions to regulate swarm cohesion and coordinated motion (CM). The proposed model governs swarm formation, modulates structural integrity, and enhances responsiveness to external perturbations. The PLN framework facilitates swarm stability, maintaining high cohesion and adaptability while the system’s tunable parameters enable online adjustment of inter-agent coupling strength and formation rigidity. Comprehensive simulation experiments were conducted to assess the performance of the model under multiple swarm conditions, including static aggregation and dynamic flocking behavior using differential-drive mobile robots. Additional tests within a simulated cropping environment were performed to evaluate the framework’s stability and cohesiveness under agricultural constraints. Swarm cohesion and formation stability were quantitatively analyzed using density-based and inter-robot distance metrics. The experimental results demonstrate that the PLN model effectively maintains formation integrity and cohesive stability throughout all scenarios. Full article

This work proposes an analysis of the capability of three deep learning models—the feedforward neural network (FFNN), long short-term memory (LSTM) network, and physics-informed neural network (PINN)—to identify the parameters of a flexible fixed-wing aircraft using in-flight data. These neural networks, composed of multiple hidden layers, are evaluated for their ability to perform system identification and to capture the nonlinear and dynamic behavior of the aircraft. The FNN and LSTM models are compared to assess the impact of temporal dependency learning on parameter estimation, while the PINN integrates prior knowledge of the system’s governing of ordinary differential equations (ODEs) to enhance physical consistency in the identification process. The objective is to exploit the generalization capability of neural network-based models while preserving the accurate estimation of the physical parameters that characterize the analyzed system. The neural networks are evaluated for their ability to perform system identification and capture the nonlinear behavior of the aircraft. The results show that the FFNN achieved the best overall performance, with average Theil’s inequality coefficient (TIC) values of 0.162 during training and 0.386 during testing, efficiently modeling the input-output relationships but tending to fit high-frequency measurement noise. The LSTM network demonstrated superior noise robustness due to its temporal filtering capability, producing smoother predictions with average TIC values of 0.398 (training) and 0.408 (testing), albeit with some amplitude underestimation. The PINN, while successfully integrating physical constraints through pretraining with target aerodynamic derivatives, showed more complex convergence, with average TIC values of 0.243 (training) and 0.475 (testing), and its estimated aerodynamic coefficients differed significantly from the conventional values. All three architectures effectively captured the coupled rigid-body and flexible dynamics when trained with distributed wing sensor data, demonstrating that neural network-based approaches can model aeroelastic phenomena without requiring explicit high-fidelity flexible-body models. This study provides a comparative framework for selecting appropriate neural network architectures based on the specific requirements of aircraft system identification tasks. Full article

Chronic lymphocytic leukemia (CLL) has systemic effects that extend beyond malignant lymphocytes, potentially altering the structure and function of circulating red blood cells (RBCs). In this study, atomic force microscopy (AFM) was combined with complementary calorimetric analysis to investigate the membrane ultrastructure, nanomechanical characteristics, and thermodynamic behavior of RBCs from untreated CLL patients and those receiving targeted therapies (Obinutuzumab/Venetoclax or Ibrutinib). RBCs from untreated patients exhibited pronounced reduction in membrane roughness, increased stiffness and adhesion forces, and altered thermal unfolding of cytoskeletal and membrane proteins, indicative of impaired structural flexibility and stability. Treatment with Obinutuzumab/Venetoclax partially restored surface topography, but stiffness and adhesion forces remained elevated, suggesting persistent cytoskeletal rigidity. The obscured spectrin and Band 2–4 thermal transitions and the elevated total enthalpy change revealed by differential scanning calorimetry indicated a modified conformation or binding state of membrane proteins. In contrast, Ibrutinib therapy produced near-normal nanomechanical and thermal characteristics, reflecting a more comprehensive restoration of RBC integrity. These findings demonstrate that CLL and its therapies distinctly influence erythrocyte morphology and mechanics, underscoring the systemic impact of the disease. The strong correspondence between AFM and calorimetric data highlights the potential of integrated biophysical approaches to detect subtle RBC alterations and to serve as complementary indicators for therapeutic monitoring. Full article

This study examines the structural evolution of Knowledge Innovation Networks (KINs) and Technology Innovation Networks (TINs) across Chinese cities (2015–2024). Using SCI/SSCI co-authorship and prefecture-level patent data, we construct dual-layer networks and assess their resilience through metrics such as average clustering coefficient, path length, global efficiency, and largest-component ratio. Our framework clarifies how network structure, spatial proximity, and urban hierarchy jointly shape innovation dynamics and opportunity distribution. Three main findings emerge. First, KINs have moved toward polycentricity yet remain hierarchically rigid, with persistent core–periphery gaps despite improved connectivity in tier 2–4 cities. TINs show greater cross-tier adaptability, creating new innovation gateways while intensifying intra-tier polarization. Second, under simulated disruptions, KINs are vulnerable to targeted attacks and exhibit path-dependent degradation, whereas TINs maintain efficiency until a critical threshold, then collapse abruptly. Third, MRQAP analysis reveals that economic and geographic proximity facilitate collaboration in KIN but constrain linkages in TINs, with spatial proximity exerting a stronger influence on knowledge flows. These results demonstrate how innovation networks mediate urban–rural interactions, affect spatial inequality, and shape regional resilience. We argue for differentiated policies that strengthen core–periphery connectivity while mitigating proximity-induced lock-in, fostering more inclusive, resilient, and sustainable urban innovation systems. Full article

This study investigates the substitution of fossil-based isocyanates with bio-based alternatives in polyurethane resin (PU) coatings and polyurethane dispersion (PUD) coatings, focusing on mechanical and thermal performance. The coatings were formulated using bio-based pentamethylene diisocyanate (PDI) and a range of fossil-based hexamethylene diisocyanate (HDI) trimers, combined with either a polyester polyol or a polyacrylate polyol. Differential-scanning calorimetry analysis revealed that PDI-based coatings exhibit higher reactivity during crosslinking, resulting in higher glass transition temperatures. Thermogravimetric analysis showed lower thermal stability compared to HDI-based polyurethanes, indicating increased rigidity but reduced thermal resilience. Mechanical testing of the coatings on wood showed superior microhardness, scratch resistance, and wear resistance for PDI-based coatings, particularly when combined with polyester polyols. Microscopic surface evaluation and roughness analysis confirmed smoother morphologies and lower crack densities in PDI-polyester coatings. Gloss and water contact angle measurements further demonstrated improved surface uniformity and hydrophobicity for PDI-based coatings. The FTIR spectroscopy validated the chemical integrity and more intense hydrogen bonding for PDI-based coatings. The post-wear spectra indicated chemical oxidation and surface rearrangements in PDI-based systems and mechanical degradation with chain scission for HDI-based coatings. Overall, the study highlights that bio-based PDI trimers can effectively replace fossil-based HDI trimers in PU and PUD coatings without compromising mechanical performance, especially when paired with polyester polyols. These findings support the development of more sustainable polyurethane coatings with enhanced durability and environmental compatibility. Full article

This paper examines the generic case of nonlinear mechanical oscillation under the influence of Hertzian-type restoring forces, a model relevant to phenomena involving elastic contact. The study addresses the complexity of strongly nonlinear systems by focusing on the differential equation governing the oscillation of a rigid sphere interacting with an elastic half-space, which includes a full series expansion to account for large deformations. Since no closed-form solution exists for the amplitude-dependent oscillation period, a new approximate analytical approach is introduced. This method preserves the system’s dominant Hertzian scaling while incorporating higher-order corrections through an averaged factor. For amplitudes where the deformation is less than or equal to the sphere’s radius, this approximation is nearly identical to the numerical solution. For larger amplitudes, the accuracy is further enhanced by introducing a semi-empirical linear adjustment to the relative error. This framework provides a reliable analytical description of the system’s behavior, offering a useful tool for theoretical studies and comparison with numerical results. Full article

The AASHTO Manual for Assessing Safety Hardware (MASH) replaced the NCHRP Report 350 in 2009, becoming the new standard for evaluating safety hardware devices, including concrete bridge parapets; all new permanent installations of bridge rails on the National Highway System must be compliant with the 2016 MASH requirements after 31 December 2019, as agreed by the FHWA and AASHTO. However, due to the complexity of vehicular impact events, there are several different methods for estimating vehicular impact force on the parapets. They can be grouped into three main categories: theoretical, numerical and measurement methods. This paper presents a practical method based on analytical concepts for providing impact force estimates that can help bridge owners to evaluate the structural capacity of bridge parapets at a fraction of the cost of full-scale crash tests and finite element numerical simulations. This approach was developed based on fundamental dynamic principles and refined dynamic analysis of vehicle rigid-body motions during multi-phased impact events. Principles of impulse and momentum were first applied to determine both linear and angular velocities of a vehicle immediately after the initial impact; then coupled differential equations of motion were derived and solved to describe the vehicle’s plane-motion during the subsequent stage, which includes both translational and rotational movements. The proposed method was shown to be capable of providing reasonably accurate force estimates with significantly less demand for time and effort compared to other complex methods. These estimates can help infrastructure owners to make informed and sustainable decisions for bridge projects, which include selecting the most efficient bridge design alternatives, in a cost-effective and timely manner. Recommendations for future studies were also discussed. Full article

We present Stereo-GS, a real-time system for online 3D Gaussian Splatting (3DGS) that reconstructs photorealistic 3D scenes from streaming stereo pairs. Unlike prior offline 3DGS methods that require dense multi-view input or precomputed depth, Stereo-GS estimates metrically accurate depth maps directly from rectified stereo geometry, enabling progressive, globally consistent reconstruction. The frontend combines a stereo implementation of DROID-SLAM for robust tracking and keyframe selection with FoundationStereo, a generalizable stereo network that needs no scene-specific fine-tuning. A two-stage filtering pipeline improves depth reliability by removing outliers using a variance-based refinement filter followed by a multi-view consistency check. In the backend, we selectively initialize new Gaussians in under-represented regions flagged by low PSNR during rendering and continuously optimize them via differentiable rendering. To maintain global coherence with minimal overhead, we apply a lightweight rigid alignment after periodic bundle adjustment. On EuRoC and TartanAir, Stereo-GS attains state-of-the-art performance, improving average PSNR by 0.22 dB and 2.45 dB over the best baseline, respectively. Together with superior visual quality, these results show that Stereo-GS delivers high-fidelity, geometrically accurate 3D reconstructions suitable for real-time robotics, navigation, and immersive AR/VR applications. Full article

Human airways maintain homeostasis through intricate cellular interactomes combining secretome-mediated signalling and mechanotransduction feedback loops. This review presents the first unified map of bidirectional mechanobiology–secretome interactions between airway epithelial cells (AECs), smooth muscle cells (ASMCs), and chondrocytes. We unify a novel three-component regulatory architecture: epithelium functioning as environmental activators, smooth muscle as mechanical actuators, and cartilage as calcium-dependent regulators. Critical mechanotransduction pathways, particularly YAP/TAZ signalling and TRPV4 channels, directly couple matrix stiffness to cytokine release, creating a closed-loop feedback system. During development, ASM-driven FGF-10 signalling and peristaltic contractions orchestrate cartilage formation and epithelial differentiation through mechanically guided morphogenesis. In disease states, these homeostatic circuits become pathologically dysregulated; asthma and COPD exhibit feed-forward stiffness traps where increased matrix rigidity triggers YAP/TAZ-mediated hypercontractility, perpetuating further remodelling. Aberrant mechanotransduction drives smooth muscle hyperplasia, cartilage degradation, and epithelial dysfunction through sustained inflammatory cascades. This system-level understanding of airway cellular networks provides mechanistic frameworks for targeted therapeutic interventions and tissue engineering strategies that incorporate essential mechanobiological signalling requirements. Full article

Buildings crossing active faults often suffer severe damage due to fault dislocation during direct-type urban earthquakes. This study employs physical model tests to systematically investigate the dynamic response mechanisms of the integrated “surface rupture zone–overburden–foundation–superstructure” system subjected to bedrock dislocation. A testing apparatus capable of simulating reverse faults with adjustable dip angles (45° and 70°) was developed. Using both sand and clay as representative overburden materials, the experiments simulated the processes of surface rupture evolution, foundation deformation, and structural response under varying fault dislocation magnitudes. Results indicate that the fault rupture pattern is governed by the bedrock dislocation magnitude, soil type, and fault dip angle. The failure process can be categorized into three distinct stages: initial rupture, rupture propagation, and rupture penetration. The severity and progression of structural damage are primarily determined by the building’s location relative to the fault trace. Structures located entirely on the hanging wall exhibited tilting angles that remained below the specified code limit throughout the dislocation process, demonstrating behavior dominated by rigid-body translation. In contrast, buildings crossing the fault exceeded this limit even at low dislocation levels, developing significant tilt and strain concentration due to differential foundation settlement. The most severe damage occurred in high-angle dip sand sites, where the maximum structural tilt reached 5.5°. This research elucidates the phased evolution of seismic damage in straddle-fault structures, providing experimental evidence and theoretical support for the seismic design of buildings in near-fault regions. The principal theoretical and methodological contributions are (1) developing a systematic “fault–soil–structure” testing methodology that reveals the propagation of fault dislocation through the system; (2) clarifying the distinct failure mechanisms between straddle-fault and hanging-wall structures, providing a quantitative basis for targeted seismic design; and (3) quantifying the controlling influence of fault dip angle and soil type combinations on structural damage severity, identifying high-angle dip sand sites as the most critical scenario. Full article

The static stability of an elastic, incompressible nanorod subjected to an extensional force is analyzed. The force is applied to a rigid rod that is welded to the free end of the nanorod. The material behavior of the nanorod is described using a two-phase local/nonlocal stress-driven model. Mathematically, the problem is formulated as a system of nonlinear differential equations suitable for nonlinear analysis. For the analysis, the Liapunov–Schmidt method is employed. Depending on a geometric parameter (the length of the rigid rod) and nonlocal parameters (the small length-scale parameter and the phase parameter), the buckling load and post-buckling behavior of the nanorod are determined. The results show that the nonlocal effect increases the buckling load, indicating a stiffening effect. An increase in the length of the rigid rod decreases the buckling load. Regarding the post-buckling behavior, it is shown that both supercritical and subcritical bifurcations can occur, depending on the values of the geometric and nonlocal parameters. The occurrence of a subcritical bifurcation, which is highly undesirable in real-world constructions, is a novel effect not observed in the classical Bernoulli–Euler theory. Full article

Regional agricultural carbon balance studies are crucial for promoting coordinated development and achieving carbon neutrality. This research quantifies agricultural carbon emissions and sinks across 190 counties in the Beijing–Tianjin–Hebei (BTH) region from 2013 to 2022. The methodology involved the carbon emission factor approach and crop productivity models to assess the agricultural carbon balance. Furthermore, this study employed the carbon load model and the carbon output technical elasticity model to analyze the per-unit contribution of agricultural products and the carbon implications of augmented agricultural output. The findings reveal the following: (1) Total agricultural carbon emissions followed a fluctuating, inverted “U”-shaped trajectory, peaking in 2015. Emission reductions were primarily driven by decreases in agricultural energy consumption and land utilization, followed by crop cultivation. Conversely, agricultural net carbon sequestration and the carbon offset ratio show a fluctuating upward trend. (2) The agricultural carbon balance exhibits a distinct north–south differentiation. There has been a year-on-year reduction in carbon deficit counties, while the spatial aggregation of the carbon balance has become increasingly pronounced over time. (3) The marginal contribution of the agricultural carbon balance across the five primary agricultural zones positively correlates with the scale of agriculture and the prevailing crop cultivation regimes. Specifically, the Central Hebei Plain agricultural zone demonstrated the highest contribution, while the Daming agricultural zone exhibited the lowest. (4) Driven by the synergistic effect of internal and external factors, the BTH region has optimized its production elements. This has led to an elevated agricultural carbon balance and reduced inter-regional disparities. The region’s agricultural carbon balance demonstrates a favorable trajectory, suggesting sustainability under a low-carbon development paradigm. This study offers sustainability recommendations based on four pillars: establishing rigid production systems, enhancing compensation and trading mechanisms, optimizing industrial structures and integration strategies, and reinforcing regional coordination and incentive frameworks. Full article

This study provides a comprehensive quantitative comparison of three structurally distinct epoxy prepolymers—cycloaliphatic, novolac, and bis-aromatic (BADGE)—cured with a single hardener, methyl nadic anhydride (MNA), and catalyzed by 1-methylimidazole under strictly identical stoichiometric and thermal conditions. Each formulation was optimized in terms of epoxy/anhydride ratio and catalyst concentration to ensure meaningful cross-comparison under representative cure conditions. A multi-technique approach combining differential scanning calorimetry (DSC), dynamic rheometry, and thermogravimetric analysis (TGA) was employed to jointly assess cure kinetics, network build-up, and long-term thermal stability. DSC analyses provided reaction enthalpies and glass transition temperatures (Tg) ranging from 145 °C (BADGE-MNA) to 253 °C (cycloaliphatic ECy-MNA) after stabilization of the curing reaction under the chosen thermal protocol, enabling experimental fine-tuning of stoichiometry beyond the theoretical 1:1 ratio. Isothermal rheology revealed gel times of approximately 14 s for novolac, 16 s for BADGE, and 20 s for the cycloaliphatic system at 200 °C, defining a clear hierarchy of reactivity (Novolac > BADGE > ECy). Post-cure thermomechanical performance and thermal aging resistance (100 h at 250 °C) were assessed via rheometry and TGA under both dynamic and isothermal conditions. They demonstrated that the novolac-based resin retained approximately 93.7% of its initial mass, confirming its outstanding thermo-oxidative stability. The three systems exhibited distinct trade-offs between reactivity and thermal resistance: the novolac resin showed superior thermal endurance but, owing to its highly aromatic and rigid structure, limited flowability, while the cycloaliphatic resin exhibited greater molecular mobility and longer pot life but reduced stability. Overall, this work provides a comprehensive and quantitatively consistent benchmark, consolidating stoichiometric control, DSC and rheological reactivity, Tg evolution, thermomechanical stability, and degradation behavior within a single unified experimental framework. The results offer reliable reference data for modeling, formulation, and possible use of epoxy–anhydride thermosets at temperatures above 200 °C. Full article

This study investigates the mechanical, thermal, electrical, and microstructural properties of polyamide 66 (PA66) composites reinforced with waste-derived micro–nano NiCr (80/20) powders. Composites containing 2, 5, and 8 wt% NiCr were prepared using thermokinetic mixing and compression molding, followed by characterization via tensile testing, Shore D hardness, Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), and thermal/electrical conductivity measurements. Results showed a progressive increase in tensile modulus, tensile strength, hardness, and thermal conductivity with increasing NiCr content, reaching maximum values at 8 wt% filler. However, elongation at break decreased, indicating reduced ductility due to restricted polymer chain mobility. DSC and FTIR analyses revealed that low NiCr loadings promoted nucleation and crystallinity, while higher contents disrupted crystalline domains. Electrical conductivity exhibited a slight upward trend, remaining sub-percolative up to 8 wt% NiCr; conductivity modulation is modest at high filler loadings. SEM–EDS confirmed uniform dispersion at low–moderate contents and agglomeration at higher levels. The use of industrial waste NiCr powder not only enhanced material performance but also contributed to sustainable materials engineering by valorizing by-products from the coatings industry. These findings suggest that NiCr/PA66 composites have potential applications in automotive, electronics, and thermal management systems requiring improved mechanical rigidity and heat dissipation. Full article