Search Results (53)

Hydrogenated amorphous silicon (a-Si:H) is a mature thin-film technology for large-area devices and thin-film sensors, and its low-temperature growth via Plasma-Enhanced Chemical Vapor Deposition (PECVD) makes it particularly suitable for biomedical flexible and wearable platforms. However, the reliable integration of a-Si:H sensors on polymer substrates requires a quantitative assessment of their electrical stability under mechanical stress, since bending-induced variations may affect sensor accuracy. In this work, we provide a quantitative, direction-dependent evaluation of the static-bending robustness of both single-doped a-Si:H layers and complete p-i-n junction stacks on polyimide (Kapton^®), thereby linking material-level strain sensitivity to device-level functionality. First, n- and p-doped a-Si:H layers were deposited on 50 µm thick Kapton^® and then structured as two-terminal thin-film resistors to enable resistivity extraction under bending conditions. Electrical measurements were performed on multiple samples, with the current path oriented either parallel (longitudinal) or perpendicular (transverse) to the bending axis, and resistance profiles were determined as a function of bending radius. While n-type layers exhibited limited and mostly gradual variations, p-type layers showed a stronger sensitivity to mechanical stress, with a critical-radius behavior under transverse bending and a more progressive evolution in the longitudinal one. This directional response identifies a practical bending condition under which doped layers, particularly p-type films, are more susceptible to strain-induced degradation. Subsequently, a linear array of a-Si:H p-i-n sensors was fabricated on Kapton^® substrates with two different thicknesses (25 and 50 µm thick) and characterized under identical bending conditions. Despite the increased strain sensitivity observed in the single-layers, the p-i-n diodes preserved their rectifying behavior down to the smallest radius tested. Indeed, across the investigated radii, the reverse current at −0.5 V remained consistent, confirming stable junction operation under bending. Only minor differences, related to substrate thickness, were observed in the reverse current and in the high-injection regime. Overall, these results demonstrate the mechanical robustness of stacked a-Si:H junctions on polyimide and support their use as sensors for wearable biosensing architectures. By establishing a quantitative, orientation-aware stability benchmark under static bending, this study supports the design of reliable a-Si:H flexible sensor platforms for curved and wearable surfaces. Full article

To address complex connections in prefabricated concrete structures, a novel joint connecting a prefabricated concrete-filled steel tubular column and a composite beam is proposed. Pseudo-static tests on six scaled specimens and ABAQUS finite element analyses were conducted to investigate seismic mechanisms, focusing on slab effects and beam-bottom configurations. Experimental results show the joints exhibit plump hysteretic curves. The composite beams displayed distinct shear-dominated failure, while the stiffened column remained intact. With an average ductility coefficient of 2.84 and an ultimate equivalent viscous damping coefficient of 0.207, the specimens demonstrated excellent deformation and energy dissipation capabilities. The slab’s flange effect significantly enhanced negative bearing capacity, causing mechanical asymmetry. Comparatively, the steel plate beam bottom configuration offered superior stiffness and stability over the reinforcement beam bottom configuration. Sensitivity analysis revealed that bearing capacity is highly sensitive to beam parameters (e.g., longitudinal rebar strength, connector length) but less sensitive to column parameters. Notably, the bearing capacity of the beam bottom configuration using reinforcement increases significantly with concrete strength and reinforcement ratio, whereas the beam bottom configuration using a steel plate shows marked insensitivity to these factors. These findings clarify the load transfer mechanism and support the seismic design of prefabricated structures. Full article

This study employs computational fluid dynamics (CFD) to investigate the aerodynamic performance and static stability of hybrid wing aircraft, considering the interference of counter-rotating embedded propellers. Extensive numerical verification has been carried out, including comparisons with NASA’s high-lift propeller (HLP) data. Three configurations—no propeller, counter-rotating inboard-upwash (CNIU) and counter-rotating outboard-upwash (CNOU) are defined to analyze the aerodynamic force/moment characteristics and flow field structures over a range of angles of attack from −6° to 26°, in conjunction with crosswind velocities of 0, 5, 10, and 15 m/s. The propeller-induced slipstream alters the aircraft’s fundamental performance by modifying wing pressure distributions and vortex systems. Specifically, the CNIU configuration increases the low-pressure areas on both the fuselage and outer wing upper surfaces, enhancing the lift-to-drag ratio by 28.4% at low angles of attack. In contrast, the CNOU configuration improves longitudinal steady-static margin by 27.4% under typical conditions and demonstrates superior lateral static stability under 10 m/s leftward crosswind conditions. For engineering applications in the aerodynamic design of such aircraft, the CNIU configuration is recommended for high cruise efficiency, whereas the CNOU configuration is preferred for flight stability. Full article

Wind-induced response poses a significant challenge to the stability of extra-large-span heavy steel box girders during synchronous lifting operations. This study adopted a method combining numerical simulation with on-site monitoring to investigate the aerodynamic characteristics the beam during the overall hoisting process of the Xiaotun Bridge. A high-fidelity finite element model was established using Midas NFX 2024 R1, and fluid–structure interaction (FSI) analysis was conducted, utilizing the RANS k-ε turbulence model to simulate stochastic wind fields. The results show that during the lifting stage from 3 m to 25 m, the maximum horizontal displacement of the steel box girder rapidly increases at wind angles of 90° and 60°, and the peak displacement is reached at 25 m. Under a strong breeze at a 90° wind angle and 25 m lifting height, the maximum lateral displacement was 42.88 mm based on FSI analysis, which is approximately 50% higher than the 28.58 mm obtained from linear static analysis. Subsequently, during the 25 m to 45 m lifting stage, the displacement gradually decreases and exhibits a linear correlation with lifting height. Concurrently, the maximum stress of the lifting lug of the steel box girder increases rapidly in the 3–25 m lifting stage, reaches the maximum at 25 m, and gradually stabilizes in the 25–45 m lifting stage. The lug stress under the same critical condition reached 190.80 MPa in FSI analysis, compared with 123.83 MPa in static analysis, highlighting a significant dynamic amplification. Furthermore, the detrimental coupling effect between mechanical vibrations from the lifting platform and wind loads was quantified; the anti-overturning stability coefficient was reduced by 10.48% under longitudinal vibration compared with lateral vibration, and a further reduction of up to 39.33% was caused by their synergy with wind excitation. Field monitoring validated the numerical model, with stress discrepancies below 9.7%. Based on these findings, a critical on-site wind speed threshold of 9.38 m/s was proposed, and integrated control methods were implemented to ensure construction safety. During on-site lifting, lifting lug stresses were monitored in real time, and if the predefined threshold was exceeded, contingency measures were immediately activated to ensure a controlled termination. Full article

Background/Objectives: Glioblastoma (GBM) exhibits heterogeneous, nonlinear invasion patterns that challenge conventional modeling and radiomic prediction. Most deep learning approaches describe the morphology but rarely capture the dynamical stability of tumor evolution. We propose an AI framework that approximates a latent attractor landscape of GBM morphodynamics—stable basins in a continuous manifold that are consistent with reproducible morphologic regimes. Methods: Multimodal MRI scans from BraTS 2020 (n = 494) were standardized and embedded with a 3D autoencoder to obtain 128-D latent representations. Unsupervised clustering identified latent basins (“attractors”). A neural ordinary differential equation (neural-ODE) approximated latent dynamics. All dynamics were inferred from cross-sectional population variability rather than longitudinal follow-up, serving as a proof-of-concept approximation of morphologic continuity. Voxel-level perturbation quantified local morphodynamic sensitivity, and proof-of-concept control was explored by adding small inputs to the neural-ODE using both a deterministic controller and a reinforcement learning agent based on soft actor–critic (SAC). Survival analyses (Kaplan–Meier, log-rank, ridge-regularized Cox) assessed associations with outcomes. Results: The learned latent manifold was smooth and clinically organized. Three dominant attractor basins were identified with significant survival stratification (χ² = 31.8, p = 1.3 × 10⁻⁷) in the static model. Dynamic attractor basins derived from neural-ODE endpoints showed modest and non-significant survival differences, confirming that these dynamic labels primarily encode the morphodynamic structure rather than fixed prognostic strata. Dynamic basins inferred from neural-ODE flows were not independently prognostic, indicating that the inferred morphodynamic field captures geometric organization rather than additional clinical risk information. The latent stability index showed a weak but borderline significant negative association with survival (ρ = −0.13 [−0.26, −0.01]; p = 0.0499). In multivariable Cox models, age remained the dominant covariate (HR = 1.30 [1.16–1.45]; p = 5 × 10⁻⁶), with overall C-indices of 0.61–0.64. Voxel-level sensitivity maps highlighted enhancing rims and peri-necrotic interfaces as influential regions. In simulation, deterministic control redirected trajectories toward lower-risk basins (≈57% success; ≈96% terminal distance reduction), while a soft actor–critic (SAC) agent produced smoother trajectories and modest additional reductions in terminal distance, albeit without matching the deterministic controller’s success rate. The learned attractor classes were internally consistent and clinically distinct. Conclusions: Learning a latent attractor landscape links generative AI, dynamical systems theory, and clinical outcomes in GBM. Although limited by the cross-sectional nature of BraTS and modest prognostic gains beyond age, these results provide a mechanistic, controllable framework for tumor morphology in which inferred dynamic attractor-like flows describe latent organization rather than a clinically predictive temporal model, motivating prospective radiogenomic validation and adaptive therapy studies. Full article

Background: Glioblastoma (GBM) is among the most aggressive and morphologically heterogeneous brain tumors. Beyond static imaging biomarkers, its structural organization can be viewed as a nonlinear dynamical system. Characterizing morphodynamic attractors within such a system may reveal latent stability patterns of morphological change and potential indicators of morphodynamic organization. Methods: We analyzed 494 subjects from the multi-institutional BraTS 2020 dataset using a fully automated computational pipeline. Each multimodal MRI volume was encoded into a 16-dimensional latent space using a 3D convolutional autoencoder. Synthetic morphological trajectories, generated through bidirectional growth–shrinkage transformations of tumor masks, enabled training of a contraction-regularized Neural Ordinary Differential Equation (Neural ODE) to model continuous-time latent morphodynamics. Morphological complexity was quantified using fractal dimension (DF), and local dynamical stability was measured via a Lyapunov-like exponent (λ). Robustness analyses assessed the stability of DF–λ regimes under multi-scale perturbations, synthetic-order reversal (directionality; sign-aware comparison) and stochastic noise, including cross-generator generalization against a time-shuffled negative control. Results: The DF–λ morphodynamic phase map revealed three characteristic regimes: (1) stable morphodynamics (λ < 0), associated with compact, smoother boundaries; (2) metastable dynamics (λ ≈ 0), reflecting weakly stable or transitional behavior; and (3) unstable or chaotic dynamics (λ > 0), associated with divergent latent trajectories. Latent-space flow fields exhibited contraction-induced attractor-like basins and smoothly diverging directions. Kernel-density estimation of DF–λ distributions revealed a prominent population cluster within the metastable regime, characterized by moderate-to-high geometric irregularity (DF ≈ 1.85–2.00) and near-neutral dynamical stability (λ ≈ −0.02 to +0.01). Exploratory clinical overlays showed that fractal dimension exhibited a modest negative association with survival, whereas λ did not correlate with clinical outcome, suggesting that the two descriptors capture complementary and clinically distinct aspects of tumor morphology. Conclusions: Glioblastoma morphology can be represented as a continuous dynamical process within a learned latent manifold. Combining Neural ODE–based dynamics, fractal morphometry, and Lyapunov stability provides a principled framework for dynamic radiomics, offering interpretable morphodynamic descriptors that bridge fractal geometry, nonlinear dynamics, and deep learning. Because BraTS is cross-sectional and the synthetic step index does not represent biological time, any clinical interpretation is hypothesis-generating; validation in longitudinal and covariate-rich cohorts is required before prognostic or treatment-monitoring use. The resulting DF–λ morphodynamic map provides a hypothesis-generating morphodynamic representation that should be evaluated in covariate-rich and longitudinal cohorts before any prognostic or treatment-monitoring use. Full article

Flapping-wing micro-air vehicles (FWMAVs) exhibit unique aerodynamic characteristics that differ fundamentally from other aircraft, yet little is known about their dynamic stability derivatives. This study aims to identify pitch-rate stability derivatives of an in-house prototype, CKopter-1, to advance the modeling and control of bio-inspired flight. Experiments were conducted using a robotic-arm fan-array system that enabled prescribed pitching motions under controlled inflow. Aerodynamic forces and moments were measured with a six-axis load cell, while vehicle kinematics were captured using motion tracking and synchronized during post-processing. Tests consisted of quasi-static cycles and dynamic cycles at pitch rates of 35°/s, 58.8°/s, and 68.4°/s. The results revealed static instability below an angle of attack of 33°, a trim condition near 58.5°, and positive stability up to 72.5°. Dynamic cases showed clear pitch-rate effects in the longitudinal components, from which the derivatives were extracted. A comparison with previous studies confirmed comparable magnitudes, with systematic differences attributable to wing dihedral and tail length. This study demonstrates that the fan-array robotic-arm method enables stability derivative identification even beyond feasible flight regimes, providing valuable parameters for future flight dynamics modeling and control of FWMAVs. Full article

To address the issues of high labor intensity, high missed harvest rates, and high damage rates associated with traditional subsurface crop harvesters, this paper takes carrots as the research object and designs an automatic row-following device based on collaborative perception and intelligent control. Firstly, the physical characteristic parameters and planting agronomic requirements of carrots in a harvest period were systematically measured and analyzed, and a collaborative control architecture with ‘lateral row-following and longitudinal profiling’ as the core was established. The architecture was composed of a lateral detection mechanism and a ridge surface floating detection mechanism. Building on this, this paper designed a control system with a STC12C5A60S2 single-chip microcomputer as the control core and a fusion fuzzy PID algorithm. By collaboratively driving the lateral and vertical stepper motors, the system achieved a precise control of the digging device’s position and posture, significantly improving the response speed and control stability under complex ridge conditions. Through the simulation of SolidWorks (2019) and RecurDyn (2023), the structural reliability and dynamic profiling effect of key components were validated from both static and dynamic perspectives, respectively. The parameter optimization results based on the response surface method show that the lateral motor speed and the forward speed are the dominant factors affecting the lateral accuracy and the vertical accuracy, respectively. Under the optimal parameter combination, the mean lateral deviation of the device measured in the field test was 1.118 cm, and the standard deviation was 0.257 cm. The mean vertical deviation is 0.986 cm, and the standard deviation is 0.016 cm. This study provides a feasible technical solution for the mechanized agronomic operation of carrots and other subsurface crops. Full article

When drilling inclined and horizontal sections, a significant part of the drill string is in a compressed state which leads to a loss of stability and longitudinal bending. Modeling of the stress–strain state (SSS) of the drill string (DS), including prediction of its stability loss, is carried out using modern software packages; the basis of the software’s mathematical apparatus and algorithms is represented by deterministic statically defined formulae and equations. At the same time, a number of factors such as the friction of the drill string against the borehole wall, the presence of tool joints, drill string dynamic operating conditions, and the uncertainty of the position of the borehole in space cast doubt on the accuracy of the calculations and the reliability of the predictive models. This paper attempts to refine the actual behavior of the drill string in critical and post-critical conditions. To study the influence of dynamic conditions in the well on changes in the SSS of the DS due to its buckling, the following initial data were used: a drill pipe with an outer diameter of 88.9 mm and tool joints causing pipe deflection under gravitational acceleration of 9.81 m/s² placed in a horizontal wellbore with a diameter of 152.4 mm; axial vibrations with an amplitude of variable force of 15–80 kN and a frequency of 1–35 Hz; lateral vibrations with an amplitude of variable impact of 0.5–1.5 g and a frequency of 1–35 Hz; and an increasing axial load of up to 500 kN. A series of experiments are conducted with or without friction of the drill string against the wellbore walls. The results of computational experiments indicate a stabilizing effect of friction forces. It should be noted that the distance between tool joints and their diametrical ratio to the borehole, taking into account gravitational acceleration, has a stabilizing effect due to the formation of additional contact force and bending stresses. It was established that drill string vibrations may either provide a stabilizing effect or lead to a loss of stability, depending on the combination of their frequency and vibration type, as well as the amplitude of variable loading. In the experiments without friction, the range of critical loads under vibration varied from 85 to >500 kN, compared to 268 kN as obtained in the reference experiment without vibrations. In the presence of friction, the range was 150 to >500 kN, while in the reference experiment without vibrations, no buckling was observed. Based on the results of this study, it is proposed to monitor the deformation rate of the string during loading as a criterion for identifying buckling in the DS stress–strain state monitoring system. Full article

Exploring the dynamic mechanisms of household poverty alleviation is crucial for achieving sustainable poverty reduction and preventing relapse into poverty. However, existing research is often constrained by a static perspective, failing to integrate poverty states with transition processes, and lacking the methodological tools to decipher the nonlinear heterogeneity and spatial dependence inherent in household pathways. This study addresses three critical questions: How can we conceptualize and quantify the dynamic trajectories of household poverty alleviation? What are the key mechanisms that drive households from poverty to stable sustainability? And how do these pathways vary across different spatial contexts? Our analysis, based on an explainable machine learning framework applied to longitudinal data from 107,637 households, yields several key findings. First, household pathways are strongly predicted by their initial typology. Those with heavy burdens and limited labor capacity ($S_{I-4}$) predominantly remained in unstable states (62.5%), while households with human capital advantages ($S_{I-3}$, $S_{I-6}$) achieved stable poverty alleviation directly at rates of 84.9% and 100%, respectively. Second, the transition from instability to stability follows discernible bridging mechanisms, where pathways reliant on skill upgrading prove more decisive for long-term stability than those dependent solely on short-term subsidies. Third, pathways are intrinsically shaped by spatial context, creating a geography of opportunity and risk—from policy compensation in mountainous areas, to resource-institutional synergy in agricultural plains, and labor-market stabilization in mining and peri-urban regions. In conclusion, sustainable poverty alleviation hinges on interventions precisely aligned with both initial household profiles and regional contexts. The central policy implication is to move beyond one-size-fits-all approaches by balancing protective safety nets with capacity-building investments, thereby creating equitable development pathways across diverse geographies. Full article

Research on morphing aircraft that can change geometry to achieve the desired performance and stability under different flight conditions has been ongoing for many years. This study provides a conceptual-level, preliminary analysis of the impact of symmetrically changing the wing sweep angle on aircraft performance and stability. The T-37B-like aircraft is selected as a base to compare the results with T-37B’s known data. The T-37B-like aircraft is modeled in both Digital DATCOM and Open VSP software. Changes in aircraft performance and stability are demonstrated for changes in the wing sweep angle between −10° and 40°. When 0° and 40° wing sweep configurations are compared, it is observed that the 40° wing sweep configuration performs better in terms of climb and range, but worse in terms of takeoff distance, glide, approach, and radius of turn. In terms of static stability, it has a positive effect on longitudinal stability. While it does not significantly affect lateral stability overall, it contributes positively to stability around the roll axis. Changing the symmetrical wing sweep angle is expected to improve certain performance and stability parameters while degrading others. A symmetrical variable-sweep wing offers advantages by adjusting to the optimal sweep angle for each flight phase. Thus, benefits can be fully utilized, and drawbacks minimized. However, it entails design, mechanical, weight, and financial costs. Therefore, whether the performance and stability benefits outweigh these costs must be evaluated on an aircraft-specific basis. Full article

In this work we present the shape optimization of a 2000 L water tank placed behind the rear axle of a forestry skidder. The main criterion is the static stability of the vehicle. The purpose of the research is to decrease the impact of the tank on stability of the vehicle. The stability is determined in the form of distances of vectors of a stability triangle and a gravity vector. The tank is divided into small elements and their impact on stability is evaluated independently. Then, the gravity vector, placed in the center of gravity of the vehicle with the tank, combines the gravities of the vehicle and the tank composed of as many elements as required for the desired volume. The Python 3.13 programming language is used to implement the solution. The results for various shapes of the tank are displayed in the form of heatmaps. A slope angle of 20 degrees is used for the analysis. The results show that the longitudinal or lateral stability can be improved by shape modifications of the tank. The most interesting output is the final shape of the tank that improves terrain accessibility of the vehicle. The optimization method is universal and can also be used for different vehicles, tank placements and also auxiliary devices added in general positions. Full article

The central buckle is essential for maintaining longitudinal stability in suspension bridges. However, conventional steel buckles are often excessively stiff, leading to stress concentration and insufficient durability. Moreover, they tend to perform poorly under fatigue loading conditions. This study proposes a novel flexible central buckle system based on a Carbon Fiber-Reinforced Polymer (CFRP) to address these limitations. This study proposes a novel flexible central buckle system based on Carbon Fiber-Reinforced Polymer (CFRP) to address these limitations. Taking the long-span Shiziyang Suspension Bridge as a case study, a finite element model is developed to investigate the effects of CFRP central buckles with eight different stiffness levels on the static and dynamic responses of the bridge. The results indicate that a CFRP central buckle with a low elastic modulus achieves comparable displacement control performance to that of traditional steel buckles, while inducing significantly lower internal forces, demonstrating strong potential as a substitute. Based on this finding, a coordinated control strategy combining the CFRP central buckle with end-span restraining devices is proposed. This integrated system reduces midspan displacement and central buckle internal force by 61.1% and 49.8%, respectively. Considering both performance and cost-efficiency, a low-modulus CFRP material such as T300 is recommended. The proposed approach offers a new and effective solution for longitudinal control in ultra-long-span suspension bridges. Full article

In the context of global population aging, identifying reliable, objective tools to assess physical function and postural stability in older adults is increasingly important to mitigate fall risk. This study presents a non-contact platform that uses a Microsoft Azure Kinect depth camera to evaluate functional performance related to lower-limb muscular capacity and static balance through self-selected depth squats and four progressively challenging stances (feet apart, feet together, semitandem, and tandem). By applying markerless motion capture algorithms, the system provides key biomechanical parameters such as center of mass displacement, knee angles, and sway trajectories. A comparison of older and younger individuals showed that the older group tended to perform shallower squats and exhibit greater mediolateral and anteroposterior sway, aligning with age-related declines in strength and postural control. Longitudinal tracking also illustrated how performance varied following a fall, indicating potential for ongoing risk assessment. Notably, in 30 s balance trials, the first 10 s often captured meaningful differences in stability, suggesting that short-duration stance tests can reliably detect early signs of imbalance. These findings highlight the feasibility of low-cost, user-friendly depth-camera technologies to complement traditional clinical measures and guide targeted fall-prevention strategies in older populations. Full article

This study examines a single-span beam crossing without longitudinal deformation compensators during diesel fuel pumping. In addition to static forces, namely, the weight of the pipeline and the transported product, the analysis considers vertical components of inertial forces acting on the oil product and the pipeline itself. These forces are directed perpendicularly to the abscissa axis connecting the endpoints of the crossing. The inertial effects cause significant vertical oscillations of the pipeline, which have not been sufficiently addressed in previous research. This work aims to study these oscillations to determine the displacements of points along the pipeline axis, the magnitudes of the inertial forces, and the resulting bending moments at the crossing. A classical Fourier series method is applied to solve the formulated boundary value problem. The results show that oscillations occur in the vertical plane, are symmetrical relative to the center of the span, and are undamped. The maximum vertical displacement reaches approximately 57 mm at the midpoint of the crossing, and the oscillation period is around 0.415 s. Inertial force distribution and bending moments are also symmetric about the center. A detailed analysis with small time steps confirmed that the oscillations are strictly periodic, exhibiting equal displacements in the upward and downward directions. The results highlight that fatigue loads arise during the operation of such crossings, which is important for assessing the strength and stability of oil pipeline structures under real operating conditions. Full article