Search Results (8,871)

Accurate multi-modal traffic demand forecasting is key to optimizing intelligent transportation systems (ITSs). To overcome the shortcomings of existing methods in capturing dynamic high-order correlations between heterogeneous spatial units and decoupling intra- and inter-mode dependencies at multiple time scales, this paper proposes a Dynamic Multi-Relation Learning with Multi-Scale Hypergraph Transformer method (MST-Hype Trans). The model integrates three novel modules. Firstly, the Multi-Scale Temporal Hypergraph Convolutional Network (MSTHCN) achieves collaborative decoupling and captures periodic and cross-modal temporal interactions of transportation demand at multiple granularities, such as time, day, and week, by constructing a multi-scale temporal hypergraph. Secondly, the Dynamic Multi-Relationship Spatial Hypergraph Network (DMRSHN) innovatively integrates geographic proximity, passenger flow similarity, and transportation connectivity to construct structural hyperedges and combines KNN and K-means algorithms to generate dynamic hyperedges, thereby accurately modeling the high-order spatial correlations of dynamic evolution between heterogeneous nodes. Finally, the Conditional Meta Attention Gated Fusion Network (CMAGFN), as a lightweight meta network, introduces a gate control mechanism based on multi-head cross-attention. It can dynamically generate node features based on real-time traffic context and adaptively calibrate the fusion weights of multi-source information, achieving optimal prediction decisions for scene perception. Experiments on three real-world datasets (NYC-Taxi, -Bike, and -Subway) demonstrate that MST-Hyper Trans achieves an average reduction of 7.6% in RMSE and 9.2% in MAE across all modes compared to the strongest baseline, while maintaining interpretability of spatiotemporal interactions. This study not only provides good model interpretability but also offers a reliable solution for multi-modal traffic collaborative management. Full article

The Wuding chicken, a renowned indigenous breed in Yunnan Province, is prized for its superior meat quality; however, its economic potential is limited by pronounced broodiness and suboptimal egg production. Central to alleviating these constraints is the precise regulation of ovarian granulosa cell (GC) proliferation and steroidogenic processes that dictate follicular development and laying performance. While Estrogen Receptor 2 (ESR2) is a known transcription factor implicated in follicular maturation, its spatiotemporal dynamics within the hypothalamic-pituitary-ovarian (HPO) axis and its specific regulatory mechanisms in Wuding chicken remain elusive. This study characterizes ESR2 expression across the HPO axis during the laying and broody periods and functionally validates its role in GCs. We observed that ESR2 expression was significantly higher throughout the HPO axis during the laying period compared to the broody period, with the most pronounced differential expression occurring in the ovary. Notably, subcellular localization analysis revealed that ESR2 is distributed in both the nucleus and the cytoplasm, indicating involvement in both nuclear transcriptional regulation and cytoplasmic signaling. Functional assays indicate that ESR2 modulates the expression of genes associated with GC proliferation, steroidogenesis, and apoptosis, potentially via the PI3K/AKT/mTOR signaling pathway. Our findings indicate that this process involves a synergistic interplay between genomic and potential non-genomic actions. Specifically, ESR2 overexpression upregulates the expression of key signaling components and steroidogenic genes, including CYP19A1, STAR, PTGS2, and FSHR, while its cytoplasmic localization suggests a potential for non-genomic interactions. Together, these coordinated mechanisms may maintain GC functional homeostasis and support follicular development. Collectively, these results suggest that ESR2 plays an important role in maintaining GC homeostasis and follicular development and may involve both genomic and non-genomic modes of action, highlighting its potential relevance for future studies on reproductive performance in indigenous poultry breeds. Full article

DC–DC converters have become a key component in the structure of renewable energy systems, where an interface to increase and regulate the output voltage is required. This paper presents a modular non-isolated topology that achieves high voltage gain through interconnected switched-inductor cells. For the proposed converter, the design rules for sizing the energy storage elements for n number of cells are obtained, considering continuous, discontinuous, and boundary operation modes. Therefore, design equations are provided to support the precise selection of passive components according to voltage and power specifications. A nonlinear dynamic model is developed, and a model-based control scheme with inner current and outer voltage loops ensures robust regulation and fast transient response. Experimental validation on a 200 W prototype confirms theoretical predictions under steady-state and real-life dynamic conditions. Full article

Cooperative operations in which a UAV advances ahead of a UGV to conduct forward reconnaissance are critical in disaster relief and urban inspection missions. Prevalent air–ground coordination methods operate under the assumption of ideal communication or treat connectivity as a secondary objective. However, obstacle occlusion, such as high-rise buildings in urban areas and mountainous terrain, results in Non-Line-of-Sight (NLOS) conditions, disrupting communication between the two platforms. To address these challenges, this paper introduces a cooperative control framework based on dynamically varying modulation matrices for both the UAV and the UGV. By evaluating and mapping occlusion risks in real time, the cooperative motions of the UAV and UGV are adaptively adjusted to maintain Line-of-Sight (LOS). An LOS assessment function is designed and mapped to the eigenvalues of the modulation matrices, enabling smooth and adaptive coordination under changing environmental conditions while avoiding the limitations of traditional discrete mode-switching strategies. Theoretical analysis and simulation results confirm that the proposed approach not only ensures stable LOS connectivity but also enhances trajectory smoothness, adaptability, and computational efficiency. Full article

To investigate the dynamic behavior of smart composite structures with embedded heat sources over a wide temperature range, this study employed thermoplastic polypropylene as the matrix, combined with glass/carbon fiber prepregs and Ni80Cr20 alloy heating wires, and fabricated functional laminated specimens with integrated heating elements via a prepreg molding process. Using a self-developed variable-temperature cantilever beam vibration testing system, the evolution of natural frequencies and damping ratios from room temperature to 140 °C was systematically examined. Results indicate that temperature-induced thermal softening of the polypropylene matrix reduces the effective bending stiffness of the composites, leading to a decline in natural frequencies across all modes. For example, the first-order natural frequency of the sample decreased from approximately 30.8 Hz at room temperature to about 28.3 Hz at 140 °C, representing a reduction of approximately 8.12%. The second-order reduction reached about 8.99%, and the third-order reduction was approximately 9.65%. Carbon fiber-reinforced specimens exhibited relatively smaller frequency reductions due to the high modulus of the fibers. Concurrently, elevated temperatures enhance molecular chain mobility and interfacial viscoelastic dissipation at the fiber–matrix interface, causing a sharp increase in damping ratios at high temperatures (>100 °C). For instance, the damping ratio of the first-order mode increased significantly from approximately 1.02% at room temperature to about 2.9% at 140 °C. By comparatively analyzing carbon fiber and glass fiber systems, the study elucidated the distinct mechanisms underlying the “fiber-dominated” stiffness retention effect and the “resin/interface-dominated” damping dissipation effect under thermal influence. These findings provide critical experimental data and theoretical references for the active thermal regulation of structural performance in thermoplastic composite structures with integrated heat sources, thereby mitigating damage caused by external disturbances. Full article

A hybrid graphene-VO₂ reconfigurable terahertz metamaterial absorber is proposed for broadband radar cross-section (RCS) reduction and high-performance sensing. The designed structure leverages the phase transition property of VO₂ and the electrostatic tunability of graphene to achieve dynamic switching between ultra-broadband and narrowband absorption states. When VO₂ is in the metallic state and graphene is unbiased, the absorber exhibits over 90% absorption across 0.82~3.50 THz, corresponding to a relative bandwidth of 124%. In the narrowband mode, with VO₂ in the insulating state and graphene biased (E_f = 1 eV), a sharp absorption peak exceeding 60% is achieved at 1.48 THz. The symmetrical design ensures polarization insensitivity and wide-angle stability. Applications in broadband RCS reduction higher than 10 dB and refractive index sensing with a sensitivity of 24.86 GHz/RIU are demonstrated, surpassing conventional terahertz sensors. This work provides a promising platform for adaptive terahertz stealth and sensing systems. Full article

To address the existing problems of frequent manual tray handling, poor continuity, and insufficient coordination in fully automatic transplanters, this study designed an integrated multi-layer tray-handling and dual-claw coordinated seedling pick-and-throw mechanism. Through continuous tray conveying and multi-layer tray-handling mechanisms, automatic replacement of multiple seedling trays was achieved. A dual-claw coordinated seedling picking and planting mechanism was designed, and the seedling picking trajectory was optimized based on path planning and RecurDyn kinematic simulation. Six-segment and seven-segment S-shaped acceleration and deceleration motion control curves and planning strategies that can be switched according to the target displacement and dynamic parameters were proposed, and a PLC-based software and hardware control system was constructed. The simulation and experimental results show that the dual-module parallel motion mode is more efficient and has a smoother trajectory than the serial mode. The average positioning absolute error of tray conveying is 1.09 mm, the average horizontal and vertical positioning absolute errors of seedling picking are 1.07 mm and 1.09 mm, respectively, and the horizontal and vertical positioning absolute errors of seedling planting are 1.50 mm and 1.51 mm, respectively. The success rate of seedling picking is 97.01%, the success rate of seedling planting is 96.39%, and the qualified rate of planting is 96%. The experimental results meet the actual operation requirements. This study provides a theoretical basis and technical support for the high-efficiency coordinated operation of fully automatic transplanters. Full article

Limited by the material response characteristics and structural design, the development of dynamically tunable terahertz absorbers with multi-functional properties remains a major challenge. In this study, a dual-tunable terahertz absorber based on the synergistic integration of strontium titanate (STO) and Dirac semimetal (BDS) is proposed. By utilizing the temperature-sensitive dielectric constant of STO and the electrically tunable conductivity of BDS, the device can realize on-demand switching between a broadband absorption mode (absorptivity >90% in the 1.347~2.1271 THz band) and a dual-narrowband absorption mode under external field excitation. Notably, the centrosymmetric cross-patterned structure on the top layer ensures the polarization insensitivity of the device, and this single structure can also serve as a high-sensitivity temperature sensor. Simulation results verify that the device exhibits stable performance under different incident angles and environmental variations. This study constructs a compact multi-functional device platform integrating dynamic absorption regulation and in situ sensing, which provides a new technical route for the development of intelligent terahertz systems in the fields of terahertz imaging, communication, detection and other related areas. Full article

The dynamic response of a supercritical composite shaft is inherently nonlinear and constitutes a critical aspect of its structural and operational design. In this work, a flexible composite shaft operating in an ultra-supercritical turbine regime is idealized as a cantilever beam. A combined experimental, numerical, and analytical framework is employed to characterize the nonlinear flexural response of the CFRP cantilever subjected to high-frequency external base excitation. The governing equations of motion are formulated by incorporating inertia-related nonlinear effects. Despite excitation in the vicinity of the third flexural mode, the system response is predominantly governed by the first bending mode, indicating strong nonresonant modal coupling. As the excitation amplitude is increased from 0.8 g to 2.8 g, the modulation sidebands around the third-mode frequency space out from 1.8 Hz to 4.1 Hz, while the amplitude of the induced nonresonant response associated with the first mode decreases monotonically from 2.2 g to 0.02 g. This intermodal energy transfer between widely separated modes is attributed to the presence of cubic nonlinearities inherent to the laminated composite material. Full article

The stabilization of rock mass vibrations in underground excavations presents a critical engineering challenge due to the interplay of viscoelastic dynamics, impulsive shocks from blasting or rock bursts, and time-varying delays induced by wave propagation and sensor–actuator networks. In this paper, an integral sliding mode control scheme is developed for a Kelvin–Voigt type hyperbolic system subject to such impulsive effects and time-varying delays. To preserve sliding surface continuity under impulsive disturbances, the impulse information is explicitly incorporated into the design of the integral sliding function. The resulting sliding mode dynamics, which include discrete state jumps, are analyzed using a piecewise Lyapunov functional combined with inequality techniques; sufficient conditions are derived to guarantee asymptotic stability. Moreover, a sliding mode control law is synthesized to ensure that the system trajectories reach and remain on the sliding manifold from the initial time onward, despite parameter uncertainties and external disturbances. Numerical simulations with parameters reflecting realistic mining scenarios verify the effectiveness of the proposed control strategy, demonstrating its potential for practical rock mass vibration stabilization in geotechnical engineering. Full article

Hopper scales are critical dynamic metering equipment in industrial production, yet their metrological performance is often compromised by wear on weighing units over long-term service. This study proposes a wear state assessment method based on the evolution of vibration features. Focusing on the rocker-column weighing unit, we analyzed the mechanism by which geometric changes in the spherical indenter—caused by fretting wear—alter the system’s constraint state. A global-to-local coupled Discrete Element Method and Finite Element Method (DEM–FEM) model was constructed to account for material-structure interactions, alongside a dynamic simulation model considering wear evolution. The simulation accuracy was validated through a dedicated experimental platform. The results indicate that as spherical wear intensifies, the low-frequency swaying of the indenter is suppressed, causing the system’s vibration mode to transition from a flexible, swaying-dominated state to a high-frequency, rigid-impact-dominated state. In the frequency domain, this manifests as energy migration, characterized by attenuation of the low-frequency main peak and an elevation of the high-frequency broadband noise floor. Crucially, as a key innovation for wear diagnosis, this study reveals the directional sensitivity of statistical indicators. While the Root Mean Square (RMS) exhibits a non-monotonic V-shaped trend, the Kurtosis and Margin factors of the tangential vibration demonstrate superior monotonic sensitivity. Under severe wear conditions, these two indicators increase by 14 and 11 times, respectively. These findings provide highly effective diagnostic criteria and hold significant engineering application value for the predictive maintenance of industrial dynamic weighing systems. Full article

Iterative self-training of language models presents a promising avenue for realizing self-improving Artificial Intelligence systems; however, this process is often hindered by the fundamental challenge of “Model Collapse.” Existing research indicates that models undergo catastrophic performance degradation and diversity collapse when recursively trained on their own increasingly homogenized synthetic data. Although some data selection-based approaches attempt to mitigate this issue by enhancing diversity, they predominantly rely on static strategies, lacking a feedback mechanism capable of adapting in real-time to the dynamic evolution of the model state and data distribution. To address this limitation, we propose a dynamic data selection framework titled “DCES” (dynamic center-edge sampling). We conducted extensive experiments on iterative self-training tasks across multiple model architectures. The results demonstrate that our system significantly outperforms baselines in terms of Perplexity (PPL) and loss across various models and test sets. Simultaneously, the framework effectively mitigates the degradation of Expected Calibration Error (ECE) and entropy metrics, successfully preventing mode collapse. Our findings highlight that an adaptive system capable of intelligent data curation based on training feedback is pivotal for maintaining the dynamic balance of data distributions and achieving sustainable AI self-evolution. This work provides a systematic methodology for realizing this goal. Full article

To address the degradation of angle tracking performance in steer-by-wire (SBW) systems caused by external disturbances and parameter uncertainties, this paper proposes a composite control strategy integrating adaptive sliding mode control (ASMC) and a peak-suppression extended state observer (PSESO). Firstly, a novel sliding mode reaching law is designed, which incorporates a dynamic adaptive gain function to achieve real-time adjustment of the control gain. This approach accelerates the reaching speed while effectively mitigating chattering. Secondly, to enhance the disturbance rejection capability of the system, a PSESO is developed to estimate the lumped disturbance in the SBW system in real time. By dynamically adjusting the observer bandwidth, the peak phenomenon in state estimation is suppressed, thereby avoiding saturation of the control signal. The disturbance estimate from the PSESO is then fed forward as a compensation term into the adaptive sliding mode (ASM) controller, forming a composite ASMC+PSESO controller that enables active compensation and suppression of disturbances. Finally, the proposed composite control strategy is validated through both simulations and experiments. Experimental results demonstrate that under sinusoidal signal tracking conditions, the proposed method reduces the maximum tracking error, the mean absolute error, and the integral absolute error by 64.4%, 74.2%, and 73.1%, respectively, compared to traditional sliding mode control (TSMC). These results fully underscore its superiority in angle tracking control and disturbance rejection for SBW systems. Full article

Retrieval-time augmentation can correct hard test samples but may also introduce harmful interference when retrieved neighbors are unreliable. We propose TDI-SF (trustworthy dynamic inference via similarity-gated strict fallback), a safety-oriented dynamic inference strategy that intervenes only when needed and falls back to a frozen baseline when retrieval quality is insufficient. Uncertainty-gated selective retrieval triggers on a hard subset, defined by high entropy or low margin predictions ($q=0.3$), and similarity-gated fusion weights neighbor evidence by maximum similarity with a strict fallback threshold (alpha-mode=maxsim, min_maxsim). We evaluate on ImageNet-100 (ResNet-50) and CICIDS2017 (MLP) and report overall accuracy, hard-subset accuracy, calibration, negative flips, and risk–coverage behavior alongside efficiency. Comprehensive evaluation under both clean and degraded retrieval conditions demonstrates the value of each component. On ImageNet-100, TDI-SF improves hard-subset accuracy by 0.92% and overall accuracy by 0.30%, applying retrieval to only 32.6% of samples with 1.38 ms overhead per triggered sample. On CICIDS2017, the same mechanism yields +1.30% hard-subset gains with only 0.43 ms/hard overhead. These results show a simple, auditable recipe for safer retrieval-augmented inference across heterogeneous domains. Full article

Based on the electron cyclotron maser instability, gyrotrons are capable of generating high-power electromagnetic vortex waves. In conventional axisymmetric configurations, the electron beam typically lifts the azimuthal degeneracy between co-rotating and counter-rotating modes, leading to a state of intense mutual suppression. This study elucidates a fundamental transition from such competitive dynamics to a stable cooperative coexistence, driven by symmetry-breaking perturbations. Using a time-dependent self-consistent interaction theory, we investigate the intermodal dynamics of the counter-rotating ${\mathrm{T}\mathrm{E}}_{6,2}$ mode pair in a terahertz gyrotron. Our results reveal that the azimuthal intermodal phase beating dictates a reciprocal energy exchange that ensures single-mode dominance. However, electron beam misalignment introduces a significant azimuthal non-uniformity in the coupling strength. This non-uniformity effectively neutralizes the competitive disparity between the two modes. At a critical offset, the system undergoes a “territorial division,” where the orthogonal vortex modes spatially segregate by dominating distinct azimuthal segments of the annular beam. This spatial segregation eliminates nonlinear cross-suppression, allowing for the stable coexistence of both rotational states. These findings offer a new perspective on multi-mode interactions in non-ideal systems and establish a robust theoretical framework for the active manipulation of vortex waves in high-performance THz radiation sources. Full article