Search Results (1,701)

Millimeter-wave (mmWave) technology is essential for meeting the reliable connectivity and high-capacity demands of autonomous driving applications. Vehicle-to-infrastructure (V2I) networks have been modeled and analyzed based on stochastic geometry (SG) in many studies. However, most studies focus only on two-dimensional (2D) antenna models and disregard a key characteristic of V2I networks, i.e., the rapid mobility of vehicles. In this work, a three-dimensional (3D) coverage and connectivity analysis framework is proposed for mmWave V2I downlink transmission based on SG. First, a realistic 3D system model is developed, which includes 3D transmission channel, blockage, and antenna array models. Then, exact expressions for the coverage probability, connectivity probability, and effective throughput of a typical vehicle are derived. Finally, the theoretical analysis is validated through simulation results, which also reveal that an optimal density of roadside units (RSUs) that maximizes spectral efficiency exists and that disregarding the effect of the vertical beam of a 3D antenna array can lead to inaccurate evaluations. Moreover, appropriately setting system parameters can mitigate the negative impact of high vehicular mobility on connectivity performance. Full article

Lithium niobate on insulator (LNOI) has emerged as a promising platform for compact, low-loss phase modulators. The extant LNOI studies evaluate device performance almost exclusively through the Pockels effect, treating piezoelectric–photoelastic strain and thermo-optic drift as decoupled channels. Crucially, both mechanisms directly perturb the phase bias of a fiber-optic gyroscope (FOG), rendering them indispensable in sensing-oriented design. This work establishes a unified multiphysics model of an X-cut TFLN ridge phase modulator that self-consistently couples the electro-optic, piezoelectric–photoelastic, thermo-optic, and pyroelectric channels. The contributions of the four mechanisms are quantitatively decomposed under realistic FOG operating conditions, and the slab thickness, ridge-top width, and electrode gap are systematically optimized to balance modulation efficiency against environmental robustness. The co-optimization of the ridge geometry and electrode gap design maintains the EO overlap factor near 0.55, while reducing the half-wave voltage requirement. This results in a half-wave voltage length of V_πL = 1.65 V·cm at a 4.4 μm electrode gap. The optimized geometry and electrode gap (4.4 μm) are essentially temperature-independent: extracted from the Pockels modulation slope, V_πL remains stable at ≈1.65 V·cm (push–pull single-pass; within ~0.3%) across 25~85 °C. Furthermore, an externally imposed substrate temperature rise of 60 K (the upper end of the 25~85 °C FOG operating range) induces a mode-field-weighted thermal residual corresponding to approximately 27% of the Pockels modulation depth at an applied voltage of 5 V. The present study demonstrates that the DC-coupled operation of TFLN sensor-grade modulators is viable across the full FOG temperature range, without dedicated active temperature stabilization, and the residual thermal-bias offset is absorbed by the FOG’s standard closed-loop servo electronics. The results of the study provide quantitative design guidelines for high-performance, environmentally stable TFLN phase modulators in compact FOG systems. Full article

In the context of global climate warming, sea surface temperature (SST) rise and sea level (SL) rise are projected to amplify typhoon-related marine dynamic disaster risks. These are idealized sensitivity experiments designed to isolate the individual effects of SST warming and SL rise, not full climate projections. This study investigates Super Typhoon Doksuri (2023) using the WRF-SWAN-ROMS coupled model, with sensitivity experiments designed for SST (+0.8 °C, +2.0 °C, +3.5 °C) and SL rise (+0.4 m, +0.6 m, +0.8 m) scenarios referenced to IPCC AR6 projections. Results indicate that SST rise enhances typhoon intensity by approximately 16% at +3.5 °C, elevates mean wave height by 25.0%, and increases extreme significant wave height by 24.0%, with the extreme wave height sensitivity approximately 2.75 times that of the mean. Storm surge exhibits a nonlinear response, with the extreme surge sensitivity approximately 13.2 times that of the mean. SL rise has relatively minor effects on open sea areas but affects coastal regions notably, expanding the inundation area by approximately 47% under the 0.8 m scenario. The Taiwan Strait channeling effect amplifies wave heights and surges on the right side of the track. Comparative analysis suggests that SST indirectly amplifies disasters by enhancing typhoon intensity, while SL rise directly constrains nearshore dynamics through static water level elevation. These findings offer process-based insights into the contrasting physical mechanisms through which SST rise and SL rise affect coastal hazards in semi-enclosed regions and may inform future ensemble-based climate impact assessments. Full article

The spatial organization of microscale fillers is critical for macroscopic performance, yet precise control over their distribution and orientation remains a major challenge in direct ink writing. Here, we present an acoustofluidic capillary nozzle that integrates acoustic manipulation into direct ink writing, enabling programmable in situ assembly of functional fillers during extrusion. By coupling a piezoelectric transducer with a commercial glass capillary, stable acoustic standing waves are established within the flow channel, driving suspended filler particles toward pressure nodes via acoustic radiation forces. Simulations and experiments systematically investigate how capillary geometry and material properties influence acoustic energy distribution and particle assembly behavior. In particular, rectangular capillaries generate stable multi-node standing waves, inducing periodic alignment of nickel-coated carbon fibers into ordered conductive bundles. This acoustically programmed microstructure reduces the percolation threshold from 8 wt% to 2 wt% and enhances electrical conductivity by up to 32.1-fold at identical filler contents. Meanwhile, the composites exhibit pronounced anisotropic conductivity and maintain excellent mechanical flexibility, with stable electromechanical performance under 16% bending strain and cyclic loading. This work demonstrates a simple and scalable acoustofluidic nozzle platform for programmable microstructure engineering in direct ink writing, offering new opportunities for fabricating high-performance multifunctional composites. Full article

Aiming at the technical bottleneck that traditional porous structures can hardly achieve mechanical load-bearing and acoustic regulation simultaneously, this study designs and fabricates three implicit surface porous structures (Gyroid, Diamond, Lidinoid) based on the bionic principle of trabecular bone. Experimental characterization and numerical analysis of their mechano-acoustic coupling performance are systematically carried out. Selective Laser Melting (SLM) technology is employed to realize the integrated forming of 316L bionic structures. Quasi-static compression experiments and finite element simulations are conducted to reveal the progressive deformation mechanism and energy absorption characteristics of different topological configurations. The results indicate that the Diamond structure exhibits the optimal comprehensive performance in terms of load-bearing capacity, specific energy absorption and isotropy. On this basis, the sound absorption and sound insulation performances of the structures are evaluated via an acoustic impedance tube test. The results show that the Diamond structure possesses a remarkably higher sound absorption coefficient and sound insulation value in the high-frequency range than other configurations, demonstrating excellent acoustic energy dissipation and sound wave isolation capability. The research indicates that the synergistic optimization of mechanical and acoustic performances can be achieved by regulating the Triply Periodic Minimal Surface (TPMS) topological configuration. Benefiting from its efficient stress transfer paths and intricate sound wave propagation channels, the Diamond structure realizes the coupling of high load-bearing capacity, superior energy absorption and favorable acoustic performance. This work provides a theoretical basis and technical support for the design of bionic porous structures in multifunctional scenarios such as bone implants and protective noise reduction. Full article

Laser remote sensing based on wavefront sensors shows great potential for detecting minute vibrations. However, due to their high detection sensitivity, wavefront sensors are highly susceptible to interference from environmental noise and instrument-induced noise, which significantly compromises the quality of the acquired vibration signals and the accuracy of the detection. In this study, over 60,000 vibration signal data samples were collected under various amplitude and frequency conditions using a laser remote sensing seismic wave detection system. By applying a physics-aware dual-channel decoupled network (PRISM) to perform noise reduction on the vibration signals, we achieved improvements in signal quality under multiple real-world noise environments. The average signal-to-noise ratio improved by 12.16 dB, and the signal distortion ratio improved by 6.35 dB, successfully preserving faint vibration signals within the noise. Full article

Cloud detection is a fundamental task in atmospheric science and satellite remote sensing. While numerous algorithms utilizing multiple visible and infrared channels have been developed, the absence of visible light at night forces most current methods to rely on multi-channel thermal infrared (TIR) observations. Consequently, detection accuracy is significantly reduced due to the minimal thermal contrast between low clouds and the ground. Furthermore, distinguishing clouds under strictly moonless conditions remains a critical challenge. Leveraging the low-light observation capability of the Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS/DNB), this study proposes a single-channel cloud detection algorithm. Based on the physical scattering of ground-based artificial lights by clouds, the algorithm integrates a feature-engineering layer with a Random Forest machine learning model. This moonlight-independent approach can rapidly determine cloudy conditions, offering a novel method for high-precision nighttime cloud detection. Validation experiments using a single fixed radar site in Longmen, China, with 97 rigorously synchronized satellite-radar sample pairs, demonstrate that the proposed algorithm achieves an overall accuracy of 86.6% (95% CI: 78.4–92.0%) against millimeter-wave cloud radar observations. While strictly reliant on stable artificial ground lights—making it primarily applicable to urban and artificially lit regions—this method provides a valuable supplementary tool for nighttime monitoring. Full article

Physical inactivity and household financial fragility are often studied separately, yet households may respond to health and financial shocks through interrelated behavioral, health, and financial processes. This study examines whether physical activity, health capital, and household financial resilience are dynamically associated in China. Using five waves of the China Family Panel Studies, we construct a household-wave panel and multidimensional indices of health capital and financial resilience. We apply lagged household fixed-effects models, dynamic mediation analysis, and panel vector autoregression with impulse response functions and forecast error variance decomposition. The results indicate that physical activity is positively associated with subsequent health capital, health capital positively predicts subsequent household financial resilience, and financial resilience has a smaller but statistically significant association with later physical activity. The mediation results are consistent with health capital serving as a partial transmission channel between physical activity and financial resilience. The PVAR results show persistent cross-variable responses, suggesting modest dynamic interdependence among the three components rather than definitive causal evidence of a strong self-reinforcing system. Heterogeneity analyses suggest that these associations are more pronounced among low-income, older-head, and chronic-risk households. These findings extend health-capital and household finance research by showing that health behavior and financial resilience can be examined as jointly evolving household-level processes. The results suggest that integrated approaches to physical activity promotion and household financial protection may be worth further policy experimentation and evaluation, especially for vulnerable households. Full article

This paper investigates the tracking control problem for a class of networked nonlinear systems in a non-ideal communication environment, where both internal communication constraints (delays and packet dropouts) and external random deception attacks are taken into account. From a symmetry perspective, the backward and forward channels constitute a paired sensing–actuation structure, and channel-dependent imperfections may destroy their functional coordination. To compensate for the resulting sensing–actuation mismatch, a data-driven sliding-mode predictive tracking control scheme is developed without relying on an explicit system model. First, an equivalent dynamic linearization is adopted to represent the input–output behavior using a data-dependent incremental model. Then, using delayed measurements together with historical input–output data, an online estimator is constructed to update the pseudo partial derivative (PPD). Based on the estimated PPD, a multi-step predictor is further designed to generate the predicted outputs, and a data-driven sliding-mode predictive tracking controller is proposed by imposing a discrete reaching law on the predicted outputs. Rigorous analysis is provided to ensure the stability of the closed-loop system and to guarantee that the tracking error remains bounded, together with an explicit bound that reveals the influence of the delay horizon, estimation mismatch, and attack amplitudes. Finally, numerical simulations under square-wave and sinusoidal references validate the effectiveness and robustness of the proposed approach. Full article

We present a review on the application of the mathematical models for research on social processes, social structures, and actors in social systems. The scope of the review is not restricted to the classical applications of mathematics such as theory of probability, statistics, stochastic processes, differential equations, and game theory. We also discuss applications of the theory of networks for social network analysis and the numerical research on dynamics of social systems. The number of these applications has increased very fast in recent years. Special attention is given to the results from the area of sociophysics, where mathematical methodology is used to analyze social systems in cooperation with the models and concepts of physics. Another special topic in his review is connected to the results from econophysics, where the mathematical methodology and theories and methods of physics are used in the studies on the dynamics of economic systems. In addition, we give several examples for the application of mathematical methods to social systems: (a) application of difference equations to model the flow of substances in channels of networks; (b) analytical solution of nonlinear equations connected to the model of waves of popularity; (c) numerical results of the waves of popularity in a model that accounts for the change in the opinion of the supporters of the ideas for positive or negative popularity of a person, material item, or a piece of information (idea, theory, ideology, etc.) In the last case, we illustrate the effectiveness of the numerical analysis to discover new effects on the studied social system. The review ends with a large list of references. These references can be used as a guide of the way of new researchers to the large field of mathematical social dynamics. Full article

Conventional settlement monitoring techniques are inadequate for seawall construction environments due to severe physical impacts, the absence of terrestrial communication networks, and highly dynamic disturbances. This research proposes a multi-source fusion settlement monitoring system designed specifically for the construction phase to overcome these constraints. An integrated inclinometer–magnetoresistive sensing unit is the central component of this system. The unit achieves physical isolation from the severe impact loads of rock backfilling, guarantees protection in high-salinity and high-humidity environments, and accommodates the large deformations typical of soft foundations by utilizing a structural design that includes a rigid channel steel sheath, anti-corrosion sealing, and flexible joints. In terms of computation, a cascaded attitude fusion framework is developed that combines a Multiplicative Extended Kalman Filter (MEKF) with Quaternion Estimator (QUEST) initialization. High-precision displacement inversion via quaternion rotation is made possible by the introduction of an adaptive mechanism based on the Mahalanobis distance that precisely detects and suppresses transient acceleration disturbances induced by construction machinery and waves. Additionally, data transmission issues in remote offshore areas are resolved by combining solar power and BeiDou short-message communication technologies. This adaptive technique minimizes attitude estimate errors in dynamic situations by approximately 84.56%, as demonstrated by experimental and field validation. The system was deployed as a 165 m array comprising 49 sensing units and monitored continuously for 458 days, achieving a normalized RMSE of 9.44–11.02% compared to reference settlement tubes and capturing a maximum settlement of 1.7 m in the core high-fill section. These results confirm the system’s high monitoring accuracy and resilience in harsh construction conditions. Full article

As wireless networks evolve from 5G toward 6G, the complexity of the electromagnetic environment increases sharply. Spectrum usage expands significantly into millimetre-wave (mmWave) and terahertz (THz) high-frequency bands. Network node density and mobility increase markedly. Moreover, communication-sensing-computation functions are deeply integrated. Accurate, real-time, full-band Electromagnetic Spectrum Maps (ESMs) have become a core infrastructure for 6G spectrum situational awareness, Dynamic Spectrum Access (DSA), interference coordination, and Integrated Sensing and Communication (ISAC). However, while a growing body of recent work extends radio mapping to multi-band and temporal domains, the predominant focus of existing Radio Map research remains the two-dimensional spatial power distribution at a single fixed frequency—essentially a degenerate special case of ESM after the frequency and time dimensions are collapsed—and no existing survey unifies 3D spatial construction, time-varying prediction, and full 6G system integration under a shared 4D formalism. This paper focuses on the three core research dimensions of ESMs, i.e., 3D spatial ESM construction, dynamic time-varying ESM modelling and prediction, and ESM integration with 6G systems. Under a unified four-dimensional ESM framework (space × frequency × time × power), we clarify the hierarchical relationships among ESM/SEM/REM/Radio Map/Channel Knowledge Maps (CKMs). Then, we systematically review 3D ESM construction, dynamic ESM modelling and prediction, and the integration of ESM with CKM/Digital Twin Networks (DTNs)/ISAC. Finally, we identify five, core open problems that constrain the development of the field to provide a systematic reference for 6G intelligent spectrum management research. Full article

Current terahertz (THz) metasurfaces are often constrained by fixed operational states, lacking the flexibility to switch dynamically between transmission and reflection modes. To address this limitation, we propose a tunable coded metasurface based on the photo-adjustable conductivity of silicon, enabling seamless mode switching and versatile wavefront manipulation. By leveraging the photo-induced dielectric-to-metallic transition, the device functions as a high-efficiency transmission-type polarization converter under zero pump fluence, transforming incident X-polarized waves into Y-polarized waves across a broad frequency range of 0.85–1.5 THz, with a polarization conversion ratio (PCR) exceeding 99%. Upon excitation by 800 nm near-infrared laser pulses, the metasurface transitions to reflection mode, where it simultaneously achieves linear polarization conversion and generates dual-channel orbital angular momentum (OAM) beams through a phase-coding strategy integrated with Fourier convolution. Furthermore, by employing the Gerchberg–Saxton (GS) algorithm to optimize the phase profile, holographic reconstruction is realized in the far field. This design integrates diverse manipulation capabilities into a single, dynamically controllable platform, offering a promising technological approach for THz information processing and integrated photonic systems. Full article

Fujian Province is located in the southeast coastal region of Mainland China and belongs to the Cathaysia Block (CB). Since the Neoproterozoic, this region has experienced multi-stage tectonic activities, which have formed extensive metallogenic belts, such as the Wuyishan and Nanling metallogenic belts. To clarify deep geodynamic processes and deep metallogenic mechanisms, we determine a high-resolution three-dimensional (3-D) velocity model of the crust and upper mantle beneath the Fujian region. Two datasets are collected for the tomographic inversion. One dataset includes 70,330 P-wave and 87,057 S-wave arrival times from 6206 local earthquakes. The other dataset includes 13,714 P-wave relative travel-time residuals from 812 teleseismic events. Our tomography reveals significant low-velocity (low-V) anomalies in the upper mantle down to 500 km depth, which may represent hot ad wet upwelling flows from the mantle transition zone. We also find some low-V and high-Vp/Vs anomalies in the crust beneath major faults and the coastal area of Fujian, which are interpreted as magmatic channels. Combining with previous geological, geochemical, and geophysical results, we consider that the subduction of the Paleo-Pacific Plate in the Late Mesozoic played a crucial role in the formation of ore deposits. We propose a geodynamic model of the deep mineralization in Fujian, in which upwelling mantle flow underplated the crust and intruded into the crust along fault zones. This geodynamic model also has certain significance for the deep mineralization mechanisms of the CB and the Lower Yangtze Block. Full article

Accurate segmentation of ship targets in high-resolution remote sensing images is crucial for maritime monitoring, traffic management and naval security. However, existing methods struggle to simultaneously address extreme scale variations in ships and severe complex background interference, leading to unsatisfactory accuracy and generalization in scenarios with shoreline occlusion and ocean wave noise. To tackle this challenge, we first construct a large-scale, high-quality multi-scale ship dataset containing 69,407 professionally annotated samples. Then, we propose ShipMS-BSNet, a multi-scale feature fusion network based on nnU-Net. At the encoder, the Multi-Scale Receptive Field Enhancement (MSRF) module captures multi-scale contextual information, while the Background Suppression Channel Attention (BSCA) module suppresses invalid background responses via learnable negative bias. At the decoder, dynamic upsampling restores spatial details, and a final Multi-Scale Refinement (MSR) module optimizes target boundaries. Extensive experiments on our self-built dataset and the public HRSC2016 dataset show that our method outperforms mainstream approaches. On the self-built dataset, it achieves 0.879 precision, 0.875 Recall, 0.868 F1-score and 0.761 IoU, validating its strong robustness for multi-scale ship segmentation in complex marine environments. Full article