Search Results (667)

Ultrasonic inspection of welded steel components remains challenging due to weld-scale material gradients, local anisotropy, attenuation, and aperture limitations. These factors severely distort both the first-arrival wavefield and the late-arriving scattered wavefield. To address this, this study presents a numerical proof of concept for three-dimensional cross-weld virtual-array coda-wave tomography (VACWT). The “virtual array” utilizes a synthetic aperture created by re-indexing sequential source–receiver records from two opposing line scans into midpoint–angle–depth coordinates. This approach enables line-based data acquisition to achieve multi-angle volumetric coverage without requiring a two-dimensional matrix array. A parameterized welded-solid benchmark model was developed, incorporating effective longitudinal and shear wave velocities, attenuation, and out-of-plane tilt fields. Four defect scenarios were evaluated: a cylindrical void, a lack-of-fusion ribbon, a porosity cluster, and an interference case. For each source–receiver path, four observables were extracted from the synthetic records: first-arrival travel time perturbations, coda wave stretching, coda decorrelation, and late-window energy ratios. These observables were then coupled into a volumetric inverse problem to separate smooth slowness variations, distributed scattering strength, and compact defect occupancy. Under the current simulation conditions, VACWT achieved smaller recovered support volumes and higher volumetric overlap compared to the delay-and-sum total focusing method (DAS-TFM), background-corrected TFM, and reverse time migration (RTM). In the interference case, applying a fixed defect-free calibration threshold yielded a centroid error of 0.48 mm, a volumetric intersection over union (IoU) of 0.856, and a false-positive volume fraction of 0.0%. While these findings serve as benchmark results rather than generalized experimental validation, the study demonstrates that late scattered wave observables provide valuable constraints for volumetric support recovery in a controlled welded-solid model. Future experimental verification on welded steel specimens with known defects remains necessary. Full article

Against the backdrop of global energy transition and the widespread adoption of Hydrogen-Blended Natural Gas (HBNG), the safety of urban gas pipeline networks faces severe challenges. This paper systematically reviews the research progress of numerical simulation in the field of natural gas pipeline safety, focusing on its core supporting roles throughout the “Leakage–Dispersion–Evolution–Consequence” disaster chain. First, it analyzes the kinetic modeling of high-pressure leakage holes and property corrections based on real gas equations of state, elaborating on the numerical characterization of HBNG multi-component transport. Second, it compares the dispersion mechanisms and environmental coupling modeling methods in typical scenarios such as buried porous media, confined spaces in utility tunnels, underwater environments, and urban building clusters. Third, it reviews leakage monitoring technologies based on physical field simulation and data-driven approaches (e.g., Convolutional Neural Network, Long Short-Term Memory), emphasizing the value of numerical simulation in constructing digital twin training sets. Furthermore, it explores the dynamic evolution of explosion flame–shock wave interactions and the evaluation models for secondary disaster consequences. Finally, the current research status of grid-based risk pre-warning and emergency response strategies is summarized. In conclusion, numerical simulation is not only a robust method for precisely quantifying and characterizing complex physical mechanisms but also a critical technological foundation for building smart and resilient energy cities. Future research should focus on the deep coupling of multi-physics fields, physics-informed learning, and the development of system-level integrated defense systems. Full article

Population-based evidence on sleep quality in Kazakhstan remains limited. This study describes sleep quality as a multidimensional construct among adults in Kazakhstan using data collected during the first national survey wave after the adoption of a single national time zone. The survey was designed as a national post-transition baseline assessment and not as an evaluation of the causal impact of the time-zone reform. Associations with socio-demographic, behavioural, clinical, and regional factors were examined. We conducted a nationally representative cross-sectional survey of adults aged 18–69 years in Kazakhstan from May to October 2025 using a multistage stratified cluster design. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI). Poor sleep quality was defined as a global PSQI score > 5. Complete PSQI data were available for 5872 participants. Descriptive analyses examined the global PSQI score and the seven component scores. Survey-weighted multivariable logistic regression was used to identify factors independently associated with poor sleep quality. The weighted prevalence of poor sleep quality was 28.1%, and the weighted mean global PSQI score was 4.43. The greatest component burden was attributable to sleep latency (mean 0.87), subjective sleep quality (0.82), and sleep disturbances (0.80), whereas use of sleep medication contributed minimally (0.11). Poor sleep quality was more common among women, older adults, urban residents, and participants with diabetes, current smoking, heavy episodic drinking, and depressive symptoms. In the adjusted model, female sex (aOR 1.37, 95% CI 1.19–1.57), age 55 years or older versus 18–24 years (1.98, 1.53–2.55), diabetes (1.47, 1.22–1.78), current smoking (1.28, 1.10–1.50), heavy episodic drinking (1.43, 1.16–1.76), and depressive symptoms (4.26, 3.52–5.15) were independently associated with higher odds of poor sleep quality. Rural residence was inversely associated with the outcome (0.71, 0.61–0.84). Compared with the North, higher odds were observed in the Central region (2.00, 1.46–2.74), East (1.94, 1.48–2.53), West (1.48, 1.17–1.88), and Almaty city (2.18, 1.72–2.76). Poor sleep quality is common among adults in Kazakhstan and is characterized primarily by difficulties with sleep initiation, perceived sleep quality, and nocturnal disturbances. The findings provide national post-transition baseline evidence and suggest that sleep health surveillance in Kazakhstan should prioritize demographic, mental health, behavioural, and regional inequalities while avoiding causal interpretation of the time-zone reform itself. Full article

The rapid development of Internet of Things technologies has accelerated the deployment of smart home systems. However, perception solutions based on visual sensors remain constrained by illumination sensitivity, occlusion, and privacy concerns. Frequency-modulated continuous-wave (FMCW) millimeter-wave radar provides a promising alternative because it operates independently of lighting conditions, is robust to environmental changes, and preserves user privacy. To address multiple-extended-target tracking in cluttered indoor environments, this paper proposes a high-accuracy tracking algorithm that combines an improved Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, an optimized Nearest-Neighbor Data Association (NNDA) scheme, and an Extended Kalman Filter (EKF). The improved DBSCAN algorithm introduces spatial-extent constraints, velocity-consistency checks, and candidate-cluster validation to cluster raw radar point clouds and convert extended targets into representative point targets with little additional computational cost. The optimized NNDA scheme then integrates clustering information into the association process, improving the matching accuracy between existing tracks and current measurements. Finally, the EKF estimates the state of each target from the associated measurements. Real-world experiments show that the proposed algorithm achieves tracking errors below 0.4 m in typical motion scenarios, maintains continuous tracking in two-person crossing scenarios, and reaches 93.3% counting accuracy in five-person scenarios. These results outperform the tracking system based on the commercial Texas Instruments (TI) IWR6843ISK millimeter-wave radar evaluation board. The proposed method offers a reliable and privacy-preserving sensing solution for smart homes, elderly care, and intelligent building applications. Full article

Presently, video communities such as YouTube, bilibili and TikTok have emerged as core fields for information dissemination and public opinion generation. Their embedded user dynamic interaction data support research on public cognitive behavior and content dissemination laws. This study used web crawling technology to construct a complete dataset including 367 video metadata and 2.39 million comment records from Luo Xiang Speaks on Criminal Law—a prominent legal popularization account on the bilibili platform—and systematically explored the temporal evolution patterns of comment interactions in video communities. By establishing a four-dimensional feature system alongside the k-means++ clustering algorithm, this study successfully identified three distinct comment growth patterns (p < 0.001): the burst–decay, the multi-wave oscillation, and the delayed peak. The results of non-parametric tests showed that these three patterns have significant differences in core features (e.g., peak delay time, skewness) and are systematically related to user grade structure, content interaction depth, and release timing. In addition, the user interaction networks of different videos demonstrate significant structural heterogeneity and disassortative mixing, characterized by a highly active minority dominating the discourse, while peripheral nodes gravitate toward high-profile hubs. These findings offer researchers deeper insights into the micro-mechanisms of information dissemination. Full article

Background: Changes in the rearfoot calcaneal position affect the foot “arch structure” during the stance phase of gait and hence influence reactions in the plantar fascia thickness and stiffness during weight bearing. However, previous research has focused on the non-weight-bearing assessment of plantar fascia thickness (PFT) and stiffness (PFS) and has not linked these measurements to rearfoot position. Methods: This study aims to investigate if a change in the weight-bearing rearfoot position influences the PFT and PFS. A linear actuator-driven 3D-printed platform was utilised to reliably move the rearfoot through a range of frontal (F (4,12) = 19,585.8, p = 0.00) and sagittal plane angles (F (2,6) = 11,751.32, p = 0.00) whilst weight bearing. An ultrasound probe capable of shear wave elastography was incorporated into the platform for the closed-chain weight-bearing assessment of the PF. The PFT and PFS were collected for 13 (26 feet) participants (11 male, two female; age 35.62 ± 15.04; BMI: 30.31± 6.22 Kg/m²) from a convenience sample who met the inclusion criteria. Results: The data were subject to appropriate statistical, collective and cluster analysis. Individual participant data analysis showed a strong nonlinear correlation between PFT and PFS in the relaxed calcaneal position. The rearfoot sagittal plane cluster demonstrated an auxetic property in 54.3% of the group, where both the PFT and PFS increased. The frontal plane cluster demonstrated an auxetic property in 76% of the group, where the PFT increased as the PFS increased. Conclusions: The results suggest that the PF does have a specific response to changes in the rearfoot position for individuals, which, in some, can show an auxetic property. Full article

Structural health monitoring (SHM) of additively manufactured (AM) small and complex components is investigated using a sensor-based signal processing and machine-learning framework. Guided-wave responses acquired from piezoelectric transducers are analyzed to evaluate the performance of sweep-sine and pulse excitation signals, as well as the influence of infill patterns, part geometry, and defect type on system reliability. Test specimens, including dogbone structures and a simulated rocket-nozzle component, were fabricated using AM, and nonstationary guided-wave signals were recorded and processed. Time–frequency signal representations (scalograms) were generated using the Continuous Wavelet Transform (CWT). Convolutional Neural Networks (CNNs) and Gaussian Mixture Models (GMMs) were employed for supervised classification and unsupervised clustering, respectively. Sweep-sine excitation consistently yielded higher classification accuracy, with CNN analysis achieving near-perfect performance and GMM clustering demonstrating improved group separability. In contrast, pulse excitation revealed transient signal features associated with wave interactions, including reflections, mode conversion, and scattering, highlighting its potential for complementary signal-based diagnostics. Importantly, the proposed hybrid supervised–unsupervised learning framework enables the quantification of previously unseen intermediate load states, demonstrating strong adaptability and generalizability beyond the conditions represented in the training data. Full article

Historic stone-built heritage is continually exposed to environmental stressors that promote material degradation and surface alteration, often in spatially heterogeneous ways. Rapid, non-destructive diagnostic tools capable of capturing both spectral and spatial information are therefore essential to support preventive conservation strategies. In this study, short-wave infrared hyperspectral imaging (SWIR-HSI), combined with chemometric analysis, three-dimensional (3D) visualisation, and complementary spectroscopic techniques, is investigated as an integrated framework for assessing the conservation state of historical stonework. A field campaign was conducted at the 15th- to 17th-century San Emeterio and San Celedonio Church (Larrabetzu, Spain), a sandstone structure exposed to environmental pollution and adverse conditions. SWIR hyperspectral images (1000–2500 nm) were acquired in situ and analysed using Principal Component Analysis (PCA) and K-Means clustering to explore spectral variability and segment the façade into spectrally homogeneous regions. The resulting chemometric outputs were projected onto a photogrammetry-based 3D RGB model, enabling volumetric visualisation of material heterogeneity and surface alteration patterns. To support the interpretation of hyperspectral features, selected regions were further analysed using X-ray fluorescence (XRF) and Raman spectroscopy. The proposed 3D-SWIR approach enhances the interpretability of hyperspectral data by embedding it within its architectural context and linking spectral variability to underlying physicochemical processes. This integrated methodology demonstrates strong potential as a non-destructive diagnostic and decision-support tool for assessing, monitoring, and conserving cultural heritage stone structures. Full article

The governance of land use carbon emissions is pivotal to achieving the goals of carbon peak and carbon neutrality. Rural revitalization significantly shapes the spatiotemporal patterns and evolutionary dynamics of land use carbon emissions, yet this relationship has received inadequate attention in existing literature. This study employs a combination of decoupling models, the Boston Matrix, spatial analysis, and interpretable machine learning models to conduct an empirical analysis of 124 regions in western China. The findings reveal diversified spatiotemporal evolution trends in rural revitalization land use carbon emissions. The decoupling relationship between rural revitalization and carbon emissions demonstrates a polarized nature, with over half of the assessed regions experiencing negative decoupling effects. The role of impact factors in decoupling relationships is characterized by a mixed nature, hierarchical intensity, nonlinear pathways, spatial heterogeneity and autocorrelation. The pathways of factor effects display nonlinear forms such as wave-like, inverted U-shaped, and U-shaped patterns, with the nature and intensity of effects dynamically shifting between “threshold mutations” and “inflection reversals” as factors evolve. The spatiotemporal evolution patterns, decoupling relationships, and SHAP values all exhibit significant spatial autocorrelation and form “spatial clusters” of various shapes. The decoupling of rural revitalization and carbon emissions in western China constitutes a complex systemic endeavor, necessitating comprehensive analysis from multiple dimensions—encompassing spatiotemporal evolution patterns, decoupling relationship, nonlinear mechanisms, and spatial effects—followed by the formulation of differentiated and precision-targeted governance strategies. Full article

A significant fraction of the HF waves is absorbed by the lowest ionospheric layer, the D-region. This region is perturbed by solar flares, which notably cause fast increases in the Sun’s X-ray flux. We present here a new chemistry model, the “Lower Ionosphere Region–Absorption and Chemistry Modelling” (LIR-ACheM), to study the D-region behaviour. It is based on the Mitra–Rowe scheme and takes into account four distinct sources (EUV, Lyman-$\alpha$, X-rays and cosmic rays) and seven species (electrons, $N{O}^{+}$, $O_2^{+}$, $O_4^{+}$, positive cluster ions, $O_2^{-}$ and other negative ions). It thus offers a compromise between accuracy and computing time. The D-region’s sluggishness and its recovery time after a flare are analysed, highlighting the importance of detachment at low altitudes and soft X-ray fluxes above 80 km. Full article

In the fields of cell engineering, bio-fabrication, and targeted therapy, achieving high-precision manipulation of microparticles and cells remains a technical challenge. Although acoustic tweezers based on surface acoustic waves (SAWs) offer a promising solution, the structural complexity of conventional SAW devices has limited their practical applications. This work proposes a symmetric interdigitated transducer (IDT)-based acoustic tweezers device featuring a simple structure and high flexibility for modulating acoustic pressure field patterns and enabling particle manipulation. Theoretical investigations into the particle manipulation mechanism of the proposed device were conducted using the finite element method. A detachable polymethyl methacrylate (PMMA) assembly chamber was also designed. The effectiveness of the device was validated through dynamic and reconfigurable manipulation experiments using fluorescent polystyrene microspheres. Experimental results demonstrate that the proposed device can rapidly and precisely modulate SAW to achieve array-based manipulation of particle clusters, forming corresponding array patterns. Compared with conventional sorting methods, this device offers advantages including low cost, high precision, ease of operation, and good biocompatibility, making it suitable for large-scale manipulation of microparticles and biological cells. This technology has the potential to expand the application landscape of SAW and may emerge as a cutting-edge approach for directed cell assembly and culture. Full article

Todos Santos Bay, Mexico, features several wave-focusing areas driven by its complex bathymetry, making it an ideal real-world test case for wave energy converter (WEC) park optimization. This study quantifies the influence of submarine cable costs and bathymetry-dependent mooring costs on the proposed park layout (hereafter the star-layout) and the levelized cost of energy (LCOE) of a 10-device WEC park, using a multi-state operational wave climatology of $N=179$ representative sea states from a 2008–2018 SNL-SWAN hindcast (covering 97.20% of the annual time). A binary genetic algorithm combined with K-means clustering analysis was used to minimize LCOE under three cost scenarios: baseline, cable-only, and cable plus bathymetry-dependent mooring. Both infrastructure cost components contribute substantially: cable costs add 52.2% to the baseline LCOE, and bathymetry-dependent mooring costs add a further 16.0% at this site, with cable approximately three times more impactful. These quantitative magnitudes are conditioned on the moderate depth-gradient setting of Todos Santos Bay; the qualitative cost-component hierarchy is expected to generalize, but the relative weights will depend on the bathymetric and wave-climate characteristics of each candidate site. The mooring contribution is nontrivial both economically and spatially (the centroid of the park shifts by approximately 151 m between the cable-only and cable-plus-depth scenarios). K-means clustering identified 2–4 layout families per scenario (K $=4\to 3\to 2$ as cost components are added), indicating that infrastructure constraints reduce the viable solution space. These results support the central hypothesis of this work: WEC park optimization studies that adopt flat-bathymetry simplifications, the prevailing assumption in much of the prior literature, risk substantial underestimation of LCOE at sites with nontrivial depth variation. We recommend that bathymetry-dependent mooring costs be included alongside cable costs in any early-stage techno-economic assessment of WEC parks at sites with complex bathymetry. Full article

In next-generation wireless communication systems, spectrum efficiency can be realized through the integration of hybrid beamforming (HBF) and non-orthogonal multiple access (NOMA). To maximize the synergy between these two technologies, it is essential to accurately cluster users within beams. Most existing studies on clustering overlook practical constraints and assume perfect channel state information (CSI). However, obtaining full CSI is impractical in realistic environments due to high feedback overhead and potential CSI errors. To address these challenges, this paper adopts an opportunistic beamforming (OBF) framework based on a partial CSI environment. The OBF facilitates channel estimation and HBF precoder design using only signal-to-interference-plus-noise ratio (SINR) feedback. Subsequently, clustering and power allocation (PA) are performed utilizing the feedback SINR from OBF without requiring additional feedback information. While conventional NOMA focuses on maximizing either throughput or fairness, this paper proposes a scheme that selects users with high SINR to maximize system throughput while minimizing the throughput disparity among users to enhance fairness. Furthermore, a power allocation method that satisfies the minimum successive interference cancellation (SIC) power requirement is employed to ensure stable decoding. Simulation results demonstrate that the proposed clustering scheme enhances the sum-rate compared to conventional SINR-based clustering methods while maintaining fairness. Consequently, this study suggests a promising approach to improving NOMA performance in practical partial CSI environments. Full article

The reaction dynamics of weakly-bound nuclear systems at near-barrier energies is a compelling topic in nuclear physics. This review summarizes decades of experimental work by the Nuclear Reaction Group at the China Institute of Atomic Energy. Using transfer reactions with the distorted wave born approximation and asymptotic normalization coefficient analyses, we confirm the first excited neutron halo (¹³C) on the $\beta$-stability line and identified new halo states in ¹²B. Total reaction cross-section measurements revealed proton halo nuclei ${}^{27}\mathrm{P}$ and ${}^{29}\mathrm{S}$, with core enlargement observed in ${}^{27}\mathrm{P}$ and ${}^{28}\mathrm{P}$. We established conditions for halo formation and delineated the proton halo existence region. In two-proton emission studies, we observed ${}^2\mathrm{He}$ cluster emission from highly excited ${}^{17,18}\mathrm{Ne}$ and ${}^{28,29}\mathrm{S}$, with ${}^{29}\mathrm{S}$ being the second such case internationally. In $\beta$-delayed decay, we discovered $\beta$2p emission in ${}^{22}\mathrm{Si}$ and determined its mass, observing isospin-symmetry breaking in ${}^{20}\mathrm{Mg}$, ${}^{22}\mathrm{Si}$, and ${}^{27}\mathrm{S}$. Decay schemes for ${}^{27}\mathrm{S}$ and ${}^{26}\mathrm{P}$ addressed the ${}^{26}\mathrm{Al}$ abundance problem. For nuclear interactions, we investigated the ${}^6\mathrm{He}$ optical potential, finding the dispersion relation inapplicable for ${}^6\mathrm{He}$ + ${}^{209}\mathrm{Bi}$, and developed notch and Bayesian methods to constrain uncertainties. For unstable nuclei, the proton drip-line systems ⁸B and ¹⁷F have been intensively studied via complete kinematics measurements of the ⁸B + ¹²⁰Sn and ¹⁷F + ⁵⁸Ni reactions, respectively. The results show that elastic breakup dominates for proton-halo ${}^8\mathrm{B}$, while inelastic breakup prevails for ${}^{17}\mathrm{F}$, with proton-rich nuclei exhibiting lower breakup probabilities than neutron-halo nuclei due to Coulomb effects. Fusion studies revealed sub-barrier enhancement in ${}^{17}\mathrm{F}$ + ${}^{58}\mathrm{Ni}$ from continuum couplings. We propose direct fusion–evaporation measurements with deflection systems integrated with breakup detection to disentangle complete and incomplete fusion channels. Full article

SARS-CoV-2, the causative agent of COVID-19, emerged in late 2019 and rapidly developed into a global health crisis. In this study, we analysed 173,194 SARS-CoV-2 genomes from the GISAID database to explore the intra-continental dynamics and distribution of variants across Africa between 2020 and 2024. We have identified 1377 distinct lineages, which were classified by clade to assess associations with infection and mortality rate. So, we conducted a Shannon entropy analysis to confirm the diversity and we applied a Correspondence Analysis (CA). Our findings revealed that one of the deadliest in Africa during the Delta wave, lineage AY.45 predominated in the South Africa cluster, whereas AY.34.1 drove transmission in the Atlantic West Africa cluster, underscoring regional heterogeneity. Furthermore, early in the pandemic, men exhibited a 39% higher risk of infection compared to women (aOR: 1.39, 95% CI [1.34–1.45]), particularly in association with clade G. By contrast, later stages were dominated by clade GRA, which disproportionately affected the elderly (≥70 years; aOR: 1.39, 95% CI [1.33–1.45]) and children (0–9 years; aOR: 1.26, 95% CI [1.20–1.33]). Our analysis highlighted that the pandemic on the African continent unfolded as a mosaic of epidemics shaped by diverse variants and regional epidemiological contexts. These findings emphasize the importance of genomic surveillance to capture local epidemic signatures and inform region-specific public health strategies. Full article