Search Results (1,317)

Lightning discharges over the Tibetan Plateau are monitored by ground-based networks that locate radiation sources from their low-frequency radio emissions. This study uses the Qinghai Datong network in the northeastern Tibetan Plateau, which records the 50 kHz to 2.5 MHz band over a small area to locate lightning in three dimensions. In such networks, the accuracy of three-dimensional location depends critically on the consistency of the signals recorded across stations, which is progressively degraded by aging analog front-ends and by complex electromagnetic noise. To address this, we propose a phase-preserving denoising scheme, termed WZ, that suppresses both broadband and narrowband noise while keeping the relative timing between stations essentially unchanged, so that the arrival times used for location are preserved. The improvement is illustrated with both simulations and real data. In Monte Carlo simulations, WZ improves the signal-to-noise ratio by 10 dB and reduces the time-of-arrival error to 0.3 μs. Applied to two intracloud flashes of contrasting morphology, WZ recovers substantially more radiation sources and more continuous discharge channels than conventional filtering, at no cost to fit quality, allowing, for example, the downward development of the channel to be tracked quantitatively. The method requires no change to the existing hardware and can be applied to archived data, making it a practical way to improve both current and historical records from long-running low-frequency lightning networks. Full article

Noise mitigation on urban rail transit lines in service is often constrained by the need to maintain uninterrupted operation and avoid large-scale demolition or reconstruction. Using Kunming Metro Line 4 as an engineering case study, this study combined onboard field measurements with data-driven analysis to characterize passenger-compartment noise and identify its principal determinants. A green noise-mitigation framework integrating source control, transmission-path control, and green operational management was developed, and its benefits were quantified across four dimensions: acoustic-environment improvement, human-health protection, low-carbon energy savings, and enhanced operation and maintenance efficiency. Passenger-compartment noise levels predominantly ranged from 78 to 82 dB(A). SHapley Additive exPlanations (SHAP) analysis identified train operating speed and track gradient as the two dominant factors, with relative importance values of 35.03% and 27.56%, respectively. Engineering implementation of the framework reduced peak noise levels in curved sections by 3–8 dB(A). The results further showed that noise-pollution mitigation and carbon-emission reduction share common sources and intervention pathways. The scenario-based assessment indicated that, under the specified parameter assumptions, the relevant measures could collectively achieve an estimated annual carbon emission reduction of approximately 3353.20 tCO₂. These findings provide a practical and scientific basis for green noise mitigation and coordinated pollution and carbon reduction on urban rail transit lines in service. Full article

This paper develops a rolling wavelet-denoised Tail-Event driven NETwork (RWD–TENET) framework to examine time-varying tail-risk spillovers between cryptocurrencies and global stock indices. Within each rolling historical window, the framework filters high-frequency disturbances from asset returns and then applies TENET to construct directional tail-risk networks, thereby avoiding look-ahead bias. Using daily data for eight representative cryptocurrencies and seventeen global stock indices from 10 October 2018 to 24 November 2025, we compare networks estimated from raw and denoised returns. Controlled simulations and empirical results indicate that RWD reduces noise-induced distortions while largely preserving extreme-event information and the main temporal structure of asset returns. Consequently, the denoised networks are sparser but exhibit greater edge concentration, stronger average transmission, and higher global efficiency. Dynamic connectedness varies substantially over time and rises sharply during major episodes of financial stress, revealing pronounced cross-market tail-risk contagion. At the group level, global stock indices generally act as risk receivers, whereas cryptocurrencies display stronger risk-emitting behavior, particularly during stress episodes. At the asset level, both risk reception and emission are concentrated in a small number of systemically important nodes, although their roles vary across market states. These findings suggest that RWD–TENET provides a robust and interpretable framework for identifying economically meaningful tail-risk transmission channels and systemic roles in interconnected crypto-equity systems. Full article

Despite the rapid proliferation of unmanned aerial vehicles (UAVs) across industrial, agricultural, and scientific domains, their deployment remains constrained by limited endurance, aerodynamic inefficiency, and acoustic emissions, all mediated by a shared onboard energy budget. Existing biomimetic UAV reviews have generally treated aerodynamics, structures, sensing, control, and energy systems as parallel topics rather than as interacting components of a unified aerial architecture. Drawing primarily on literature published between 2015 and June 2026 and identified through searches of Web of Science, Scopus, and Google Scholar, this review addresses this gap by examining bio-inspired technologies across six principal domains: aeroacoustic and passive flow control, aerodynamic efficiency, multifunctional structural composites, neuromorphic sensing and control, ionic energy storage, and energy harvesting. Its principal contribution is a cross-domain synergy analysis identifying five performance couplings and one structural enabling architecture through which these domains interact physically and functionally. Representative examples include serration-based propeller geometries that can simultaneously reduce noise and power demand; morphing wing surfaces that serve as both aerodynamic structures and triboelectric harvesting substrates; and neuromorphic spiking neural networks that have been reported, in specific event-vision inference benchmarks, to reduce inference energy by three to four orders of magnitude relative to embedded graphics processing unit (GPU)-based implementations. Mechanical harvesting outputs nonetheless remain orders of magnitude below propulsion requirements and are thus positioned as supplementary. Four systemic barriers (unquantified mass–energy balance, undocumented durability, aeroelastic co-design gaps, and heterogeneous metrics) are evaluated, and the resulting synthesis indicates that advancing bio-inspired UAVs requires a transition from structural imitation to functional, system-level biomimetics. Full article

Nominal launch-power profiles can lose quality-of-transmission (QoT) margin when span and equipment parameters vary. We study this effect using C-band GNPy 2.14.1 simulations that recompute amplified-spontaneous-emission (ASE) noise and Gaussian-noise (GN)-model nonlinear interference under perturbations. Ten runs use 384 training scenarios and 1024 intensified-stress scenarios with scalar and spectral multipliers of 1.25 and 1.50. In paired within-GNPy comparisons, a finite-sample 5% lower-tail-mean selector, defined as the mean of the 20 worst training utilities, improves fifth-percentile minimum-channel generalized signal-to-noise-ratio (GSNR) margin over nominal optimization by 0.247 dB, with a 95% confidence-interval half-width of 0.014 dB. After normalization to the nominal total launch power, the gain remains 0.179 dB (half-width 0.017 dB), suggesting that spectral shape is a major contributor to the paired difference in this comparison. The gain lies between 0.245 and 0.248 dB when the training-tail fraction varies from 1% to 10%; relaxing the per-channel ceiling from 3.0 to 3.5 dBm removes almost all active bounds while retaining a 0.246 dB gain. Selected profiles mainly raise the low-frequency edge, and the benefit appears near the modeled reach boundary rather than on high-margin metro links. Erbium-doped fiber amplifier noise figure, gain ripple, and reconfigurable optical add-drop multiplexer equalization lead the sensitivity ranking. Reduced Manakov checks preserve power ordering while exposing model offsets. The results describe the specified GNPy configuration, finite search, and synthetic perturbation laws; field-calibrated performance remains to be established. Full article

Air travel induces substantial landside traffic through the movement of passengers, employees, suppliers, and cargo between airports and their surrounding regions. While this airport-induced landside traffic has received growing attention within airport sustainability research, its associated external costs remain insufficiently quantified. This study develops a modular model to estimate traffic volumes and associated external costs of airport-induced landside traffic. It accounts for key behavioral and operational parameters, including modal split, trip distances, occupancy rates, and trip frequencies, differentiated across user groups and transport modes. The model is applied to Germany as a case study using national mobility statistics, airport data, and external cost factors from European transport studies. The assessment covers greenhouse gas emissions, air pollution, accidents, noise, habitat damage, and upstream fuel supply impacts. Results indicate that airport-induced landside traffic generated external costs of approximately EUR 1.43 billion in Germany in 2019, with passengers and airport employees accounting for the largest shares. Accident costs and greenhouse gas emissions dominate the overall impacts. Sensitivity analyses further show that moderate behavioral changes, such as modal shifts toward public transport and increased vehicle occupancy, can significantly reduce external costs. The findings highlight the importance of integrating landside access into environmental assessments and sustainable airport planning. Full article

We report on electric field measurements recorded onboard the China Seismo-Electromagnetic Satellite (CSES). In this study, we emphasize the whistler and transmitter very low frequency (VLF) radiations recorded in the frequency range between 1.8 kHz and 25 kHz. The electric field detector (EFD) instrument onboard the CSES works as a double probe instrument and allows access to the three electric components of VLF waves. Three frequencies were selected, two related to whistler hiss (i.e., 2.5 kHz channel) and chorus (i.e., 5 kHz channel) radiations and one to the NAA ground-based transmitter signal (i.e., 24 kHz). We investigate the corresponding power spectral density variations, from which we derive the Stokes intensity I and normalized q linear polarization components. This leads us to study their statistical fluctuations and to emphasize the behaviors of natural whistler hiss and chorus radiations and man-made transmitter emissions. The Stokes intensities of the natural whistler and NAA transmitter radiations are estimated, respectively, to be about 1 mV² m⁻² Hz⁻¹ and 0.05 mV² m⁻² Hz⁻¹. The correlation coefficients of the Stokes intensity polarizations are in the order of 98% powerfully coupled, contrary to the Stokes normalized linear polarizations, which are found to be relatively paired, i.e., less than 60%. The signal-to-noise ratio is estimated considering three intensity levels (i.e., high, medium, low). This analysis leads us to characterize the Stokes normalized linear components of VLF radio waves and to show different behaviors of the polarization when considering the Northern and Southern Hemispheres. The regions of enhanced whistler Stokes intensities of whistler hiss and chorus emissions are confined to the sub-auroral regions in both hemispheres, particularly at geomagnetically ranges linked to the NAA transmitter station and its conjugate region in the Southern Hemisphere. In this investigation, we point out the Stokes polarization parameters, which are essential for the characterization of whistler VLF radio waves, particularly when considering the CSES mission objectives and commitments. Full article

Airports are complex infrastructure systems with important environmental, operational, and social impacts that require integrated sustainability governance. Although numerous international regulations, environmental management standards, certification schemes, and policy initiatives have been developed to support airport sustainability, existing research has largely examined these mechanisms independently, resulting in fragmented approaches to sustainability planning and implementation. This study develops an Integrated Airport Sustainability Policy Framework through a qualitative conceptual methodology based on a systematic literature review, guided by PRISMA-ScR principles, and comparative policy analysis. Peer-reviewed literature was systematically analyzed alongside international regulatory and policy documents, including guidance and standards published by the International Civil Aviation Organization (ICAO), the International Organization for Standardization (ISO), Airports Council International (ACI) Airport Carbon Accreditation (ACA), the European Commission, the Federal Aviation Administration (FAA), and the United Nations (UN). The thematic synthesis identified four connected dimensions that consistently underpin sustainable airport governance: environmental management and emissions reduction, operational and energy efficiency, community and social sustainability, and governance, collaboration, and compliance. These dimensions were integrated into a scalable conceptual framework that consolidates existing sustainability mechanisms into an integrated governance structure adaptable to airports with various operational characteristics and regulatory contexts. The proposed framework addressed the fragmentation of existing policy approaches and proposes a structured basis for integrating environmental, operational, social, and governance aspects into airport decision-making. As a conceptual model developed through secondary evidence synthesis, the framework is intended to support future research and policy development and requires empirical validation through application across airports of different sizes and geographical contexts. Full article

The counter-diabatic shortcut to adiabaticity (CDSTA) has been explored in implementing qudit quantum Fourier transforms (QFTs) via stimulated Raman adiabatic passage (STIRAP) to suppress non-adiabatic leakage. While direct CD driving may introduce unwanted global microwave couplings, seeking an approach without explicit CD fields is highly desirable. By employing rotating-frame absorption, we implement an all-optical CDSTA strategy to synthesize the QFT. Direct CD driving (STIRSAP) removes the adiabatic time floor of STIRAP and sets the acceleration upper bound; the all-optical scheme reproduces this acceleration with a peak-amplitude overhead below $5\%$ in the working regime while eliminating the microwave coupling. The quartit encoding further reduces the integrated energy by a factor of 3 relative to the two-qubit decomposition. Extending to open quantum systems, the all-optical strategy shows improved robustness against amplitude noise and spontaneous emission. Full article

Real-time tissue identification during laser-guided surgery is a critical unmet need for collateral damage avoidance and margin delineation. Laser-Induced Breakdown Spectroscopy (LIBS) is compatible with pulsed laser surgical systems and offers rapid, label-free elemental analysis. This study presents a machine learning pipeline classifying five ex vivo bovine tissue classes, plus one synthetic null-signal control class, from LIBS spectra, designed to control specimen-level data leakage and class imbalance bias. Key contributions are (i) a ‘peak max over baseline’ aggregation strategy suppressing shot noise while preserving emission peaks; (ii) a repeated, group-based cross-validation protocol (GroupShuffleSplit, N = 10) enforcing specimen-level separation; and (iii) a comparison of 30 configurations (10 classifiers × 3 pipelines). Extra Trees with normalization reached the highest weighted F1-score (0.934 ± 0.118); excluding the synthetic control, five-class scores fall to 0.875–0.915 and the ranking changes, so these are the reference figures for biological tissue discrimination. Support Vector Machines were less accurate but more consistent (0.917 ± 0.069). Acquisition takes approximately 3 s per point; inference is sub-millisecond. With five source animals, the best configuration chosen on the same outer splits, and inner tuning that was not group-aware, these estimates are an exploratory step toward real-time guided surgery. Full article

Managing vehicle speeds in rural-to-urban transition zones—where two-lane roads traverse small population centres—remains a critical challenge for road safety engineering. While various traffic calming measures (TCMs) are employed to enforce speed limits, empirical evidence comparing their relative effectiveness in sequential applications is often limited. This study presents a field analysis conducted on the BI-2604 road in Gordexola (Spain). Using radar counters at 24 sequential control points, a dataset of 23,021 valid vehicle passages was analysed to evaluate seven distinct calming configurations. The results indicate that, within this corridor, purely visual countermeasures were associated with high non-compliance: standard crosswalks (paint only) recorded a non-compliance rate of 92.9%, while the Speed Monitoring Display (SMD) registered a 72.1% violation rate. Regarding physical measures, a safety–compliance paradox was identified. Speed humps located in 50 km/h zones achieved the highest statistical compliance (41.7% violation). However, raised crosswalks in 30 km/h zones, despite registering higher non-compliance (63.6%), achieved the lowest mean speeds (approximately 34 km/h; V85 ≈ 45 km/h), a range that the previous literature associates with lower pedestrian injury risk. The findings suggest that, within the investigated corridor, physical vertical deflection was associated with lower speeds than the analysed visual/signalling measures, although it remains an imperfect solution that generates significant negative externalities (noise, emissions, and discomfort) and fails to guarantee strict legal adherence to 30 km/h limits. These limitations highlight the urgent need for alternative solutions, setting the stage for future research on optimised perceptual countermeasures. Full article

We report a timing and spectral study of the 2024 outburst of the Be/X-ray binary pulsar 2S 1553-542 using NuSTAR and NICER observations. From the NuSTAR light curve, we measure a pulse period of $9.285022\pm 0.000001$ s. The energy-resolved pulse profiles are dominated by a single peak and show a wing-like structure most clearly in the 12–22 keV band. The pulsed fraction remains above 60% and increases with energy. The phase-averaged NuSTAR spectrum is described by an absorbed blackbody plus cutoff power-law continuum, together with an iron emission line and a cyclotron absorption feature. Using the cyclabs model, we obtain a cyclotron energy of $E_{\mathrm{cyc}}\simeq 24.1$ keV, corresponding to a magnetic field strength of $B\sim 3\times {10}^{12}$ G. Phase-resolved spectroscopy shows that the continuum and cyclotron-line parameters vary with pulse phase, and that the line becomes poorly constrained around the pulse-wing phase. We also searched the short NICER GTIs for transient mHz variability using wavelet analysis and a CEEMDAN-based Hilbert–Huang transform. Localized excesses near ∼10 mHz and ∼20 mHz are found, but the short exposures, COI effects, red-noise fluctuations, and the lack of a well-constrained Fourier peak limit their significance. We therefore treat them as candidate mHz variability rather than firm mHz QPO detections. Full article

Financial markets in emerging economies exhibit fractal long-memory dynamics ($H=0.93$ on CBOE VIX; $H=0.81$ on JSE realised volatility) and extreme non-Gaussianity (kurtosis $=51.6$) that together invalidate conventional Gaussian-emission regime models. This paper introduces SARDINE (Stochastic Adaptive Regime Detection via Integrated Neuro-Fuzzy Estimation), a continuous-time framework that embeds Takagi-Sugeno-Kang (TSK) fuzzy membership weights directly inside a stochastic differential equation integrator, governing the geometry of stochastic uncertainty at each integration step. Three formal results underpin the architecture: a Lyapunov-style diffusion stability bound, a regime-adaptive noise attenuation guarantee, and an asymmetric cost advantage condition. Evaluated on 17 JSE Top40 securities ($N=2778$ daily observations, 2015–2026; 537-day held-out test), SARDINE achieves FAR $=0.143$, FNR $=0.195$, and a 1.33-day early-warning lead time, reducing the asymmetric cost by 32% relative to GMM. Against 14 baselines including Neural SDE, PatchTST, and Mamba, the fuzzy-gated diffusion reduces false alarms by 54–63%. A fractional Brownian motion ablation ($H\in \{0.44,0.50,0.93\}$, $B=200$ replicates) reveals that long-memory information should be embedded in the input representation rather than the noise driver; $H=0.50$ is recommended for operational deployment. Full article

This study presents a novel approach in millimeter wave (MMW) imaging by demonstrating the first experimental implementation of an imaging system that integrates optical up-conversion within a glow discharge detector (GDD) plasma alongside a phase-sensitive lock-in camera. In this novel approach, incident MMW radiation, modulated with an ON–OFF signal, strikes the GDD, which functions as an up-conversion sensor, transforming the MMW signal into ON–OFF-modulated near-infrared (NIR) optical emissions. This upconverted light is then captured by the lock-in camera, which synchronously demodulates the optical signal at each pixel. By simultaneously receiving the upconverted optical emissions and the original reference signal used to modulate the MMW radiation, the camera achieves synchronous demodulation of the incoming light at each pixel. This advanced configuration enables the direct extraction of amplitude and phase information with pixel-level synchronous demodulation, while actively and effectively increasing the SNR and eliminates the uncorrelated background plasma emissions. The proposed optical up-conversion system effectively addresses existing limitations, offering a unique combination of advantages. By inheriting the fundamental benefits of GDD, such as cost-efficiency per unit, simplified electronic design, and robust resistance to high radiation levels, the system demonstrates enhanced noise suppression and increased sensitivity. Validation experiments utilizing LED modulation verify an optical acquisition time of approximately 100 ms per scan position (pixel dwell time), representing a significant improvement of several orders of magnitude over conventional optical acquisition approaches. In the present proof-of-concept implementation, complete image formation additionally includes the mechanical scanning time required for image reconstruction. Ultimately, this work establishes an improved paradigm for MMW imaging, advancing the development of compact, rapid, and cost-effective imaging systems for advanced non-ionizing imaging applications. Full article

The larvae of wood-boring insects often cause damage to wooden buildings, furniture, and objects of cultural heritage. A fundamental practical challenge in assessment and conservation is reliably distinguishing between active and inactive infestations—a distinction that conventional visual inspection methods cannot always resolve with confidence. We present a selection of experiments for the implementation of acoustic emission (AE) measurement methods for these inspections, spanning from highly controlled laboratory settings to practical field tests. An overview explains the physical principles of structure-borne sound emission by feeding larvae and the AE sensors and other instrumentation used (AMSY-6 stationary system and the single-channel Insect Activity Detection System, IADS). Laboratory experiments with standardized small specimens containing single larvae of Hylotrupes bajulus are described in detail, examining the influence of temperature, sensor coupling method, and sensor-to-larva distance on detection reliability. Verification experiments on large structural timber with unknown infestation levels demonstrated the practical applicability of the method and enabled qualitative localization of larval activity. Field applications in historic buildings, churches, and cultural heritage objects are presented and discussed. The results confirm that AE sensors can reliably detect larval activity of H. bajulus in standardized specimens at signal-to-noise ratios clearly distinguishable from negative controls. Sensor sensitivity decreases significantly with distance, with reliable detection up to approximately 30 cm under the tested conditions. Although interpretive expertise in wood biology, infestation assessment, and conservation expertise remains essential, the results indicate that AE sensors can indeed be used to detect larval activity inside wood in a non-destructive way in a broad range of field and laboratory applications and across a range of conditions. Full article