This study assesses the stability of the Bei'an-Hei'he Highway (BHH), located near the southern limit of latitudinal permafrost in the Xiao Xing'anling Mountains, Northeast China, where permafrost degradation is intensifying under combined climatic and anthropogenic influences. Freeze-thaw-induced ground deformation and related periglacial hazards remain poorly quantified, limiting regional infrastructure resilience. We developed an integrated framework that fuses multi-source InSAR (ALOS, Sentinel-1, ALOS-2), unmanned aerial vehicle (UAV) photogrammetry, electrical resistivity tomography (ERT), and theoretical modeling to characterize cumulative deformation, evaluate present stability, and project future dynamics. Results reveal long-term deformation rates from -35 to +40 mm/yr within a 1-km buffer on each side of the BHH, with seasonal amplitudes up to 11 mm. Sentinel-1, with its 12-day revisit cycle, demonstrated superior capability for monitoring the Xing'an permafrost. Deformation patterns were primarily controlled by air temperature, while precipitation and the topographic wetness index enhanced spatial heterogeneity through thermo-hydrological coupling. Wavelet analysis identified a 334-day deformation cycle, lagging climate forcing by similar to 107 days due to the insulating effects of peat. Early-warning analysis classified 4.99 % of the highway length as high-risk (subsidence 10.91 mm/yr). The InSAR-based landslide prediction model achieved high accuracy (Area Under the Receiver Operating Characteristic (ROC) Curve, or AUC = 0.9486), validated through field surveys of subsidence, cracking, and slow-moving failures. The proposed 'past-present-future' framework demonstrates the potential of multi-sensor integration for permafrost monitoring and provides a transferable approach for assessing infrastructure stability in cold regions.

Canopy reflectance (CR) models describe the transfer and interaction of radiation from the soil background to the canopy layer and play a vital role in the retrieval of biophysical variables. However, few efforts have focused on estimating soil background scattering operators, resulting in uncertainties in CR modelling, especially over sloping terrain. This study developed a canopy reflectance model for simulating CR over sloping terrain, which combines the general spectral vector (GSV) model, the PROSPECT model, and 4SAIL model coupled with topography (GSV-PROSAILT). The canopy reflectance simulated by GSV-PROSAILT was validated against two datasets: discrete anisotropic radiative transfer (DART) simulations and remote sensing observations. A comparison with DART simulations under various conditions revealed that the GSV-PROSAILT model captures terrain-induced CR distortion with high accuracy (red band: coefficient of determination $\lpar {\rm R 2} \rpar = 0.731$(R2)=0.731, root-mean-square error (RMSE) = 0.007; near infrared (NIR) band: $\rm R2 = 0.8319$R2=0.8319, RMSE = 0.0098). The results of remote sensing observation verification revealed that the GSV-PROSAILT model can be successfully used in CR modelling. These validations confirmed the performance of GSV-PROSAILT in soil and canopy reflectance modelling over sloping terrain, indicating that it can provide a potential tool for biophysical variable retrieval over mountainous areas.

Liquefaction hazard analysis is crucial in earthquake-prone regions as it magnifies structural damage. In this study, standard penetration test (SPT) and shear wave velocity (Vs) data of Chittagong City have been used to assess the liquefaction resistance of soils using artificial neural network (ANN). For a scenario of 7.5 magnitude (Mw) earthquake in Chittagong City, estimating the liquefaction-resistance involves utilizing peak horizontal ground acceleration (PGA) values of 0.15 and 0.28 g. Then, liquefaction potential index (LPI) is determined to assess the severity of liquefaction. In most boreholes, the LPI values are generally higher, with slightly elevated values in SPT data compared to Vs data. The current study suggests that the Valley Alluvium, Beach and Dune Sand may experience extreme liquefaction with LPI values ranges from 9.55 to 55.03 and 0 to 37.17 for SPT and Vs respectively, under a PGA of 0.15 g. Furthermore, LPI values ranges from 25.55 to 71.45 and 9.55 to 54.39 for SPT and Vs correspondingly. The liquefaction hazard map can be utilized to protect public safety, infrastructure, and to create a more resilient Chittagong City.

Ground subsidence resulting from underground coal mining poses significant challenges to urban safety, infrastructure stability, and environmental protection, particularly in regions extending beneath water bodies. This study investigates subsidence patterns in the Kozlu coal basin by integrating Interferometric Synthetic Aperture Radar (InSAR), numerical modelling, and machine learning techniques. The Kozlu coal basin, located in Zonguldak, Turkey, serves as a critical example, where extensive mining activities have led to complex deformation patterns. InSAR effectively captures terrestrial subsidence but is limited in underwater regions. Numerical modelling provides insights into geological behaviour but requires extensive input data. Machine learning, specifically Gaussian Process Regression (GPR), bridges this gap by predicting subsidence in unobservable underwater zones with high accuracy. The integrated approach reveals consistent deformation trends across terrestrial and marine environments, offering practical tools for risk mitigation and resource management. These findings underscore the importance of interdisciplinary methods in addressing complex geological challenges and pave the way for future advancements in subsidence monitoring and prediction.

In this study, the effect of near-field and far-field ground motions on the seismic response of the soil pile system is investigated. The forward directivity effect, which includes a large velocity pulse at the beginning of the velocity time history of the ground motion is the most damaging phenomenon observed in near-field ground motions. To investigate the effect of near-field and far-field ground motions on the seismic response of a soil-pile system, a three-dimensional model consisting of the two-layer soil, liquefiable sand layer over dense sand, and the pile is utilized. Modeling is conducted in FLAC 3D software. The P2P Sand constitutive model is selected for sandy soil. Three fault-normal near-field and three far-field ground motion records were applied to the model. The numerical results show that near field velocity pulses have a considerable effect on the system behavior and sudden huge displacement demands were observed. Also, during the near-field ground motions, the exceeded pore water pressure coefficient (Ru) increases so that liquefaction occurs in the upper loose sand layer. Due to the pulse-like ground motions, a pulse-like relative displacement is created in response to the pile. Meanwhile the relative displacement response of the pile is entirely different due to the energy distribution during the far-field ground motions.

The soil strength of soft clay is influenced by strain rate effect. Models considering strain rate effect always ignore the impact of loading rate on pore pressure and have poor applicability to 3D engineering problems. Based on the classic inelastic core boundary surface model, a logarithmic rate function representing the strain rate effect of soft soil was introduced to the hardening law. A new parameter H was added to adjust the plastic modulus while another new parameter mu is introduced to account for the strain rate effect. A rate-effect boundary surface constitutive model suitable for saturated clay was subsequently proposed. Combined with the implicit integral numerical algorithm and stress-permeability coupling analysis, the innovative model was implemented in the finite element software and validated by comparing with the results of triaxial tests. By analysing the rate-effect of 11 types of soft soil, a formula to calculate the rate parameter was derived. The developed model was used to calculate the undrained vertical bearing capacity and sliding resistance of a movable subsea mudmat. The mudmat frictional coefficient from soil undrained to partial drained and finally undrained state was obtained and compared with those from the Modified Cam-Clay model. Identical results were obtained without considering the rate effect. When considering the strain rate effect on the improvement of soil strength, the friction resistance coefficient initially decreases and then increases with the decrease of the sliding speed, eventually stabilising after reaching the limit value. The rate-effect on the friction resistance coefficient is most prominent under undrained conditions with high sliding speeds. The soil strain rate effect is suggested to be considered in the design of the subsea mudmat avoid underestimating the friction resistance.

Fragile fruits, which are prone to mechanical damage and microbial infection, necessitate protective materials that possess both cushioning and antimicrobial properties. In this study, we present a novel genipin-crosslinked chitosan/gelatin aerogel (CS/GEL/GNP) synthesized through direct mixing and free-drying techniques. The mechanical properties and cushioning capacities of the CS/GEL/GNP aerogel were thoroughly characterized, alongside an evaluation of its antimicrobial efficacy. The composite aerogel demonstrated remarkable compressibility and shape recovery characteristics. In a transportation simulation test, the aerogel effectively protected strawberries from mechanical damage. Furthermore, the composite aerogel exhibited enhanced antimicrobial activities against Escherichia coli, Staphylococcus aureus and Botrytis cinerea in vitro. The quality of strawberries was successfully maintained at ambient temperature when packaged with the CS/GEL/GNP. Notably, the aerogel could be completely degraded in the soil within 21 days and is nontoxic to cells. Consequently, the dual-functional CS/GEL/GNP aerogel presents a promising option for packaging materials aimed at protecting delicate fruits.

Atmospheric aerosols are known to alter the Earth's radiative balance and influence climate. However, accurately quantifying the magnitude of aerosol-induced radiative forcing remains challenging. We characterize optical properties of biomass-burning (BB) and non-biomass-burning (NB) aerosols and quantify BB aerosol radiative forcing at two AERONET (AErosol RObotic NETwork) sites in Huancayo (Peru) and La Paz (Bolivia) during 2015-2021. From AERONET data, we derive aerosol optical depth (AOD), & Aring;ngstr & ouml;m exponent (AE), single-scattering albedo (SSA), and asymmetry parameter (ASY). We then employ the SBDART model to calculate aerosol radiative forcing (ARF) on monthly and multiannual timescales. BB aerosols peak in September (AOD: 0.230 at Huancayo; 0.235 at La Paz), while NB aerosols reach maxima in September at Huancayo (0.109) and November at La Paz (0.104). AE values exceeding unity for BB aerosols indicate fine-mode dominance. Huancayo exhibited the highest BB ARF in November: +16.4 W m-2 at the top of the atmosphere (TOA), -18.6 W m-2 at the surface (BOA), and +35.1 W m-2 within the atmospheric column (ATM). This was driven by elevated AOD and high scattering efficiency. At La Paz, where SSA data was only available for September, BBARF values were also significant (+15.16 at TOA, -17.52 at BOA, and +32.73 W m-2 within the ATM). This result underscores the importance of quantifying the ARF, particularly over South America where data is scarce.

Reclaimed coastal areas are highly susceptible to uneven subsidence caused by the consolidation of soft marine deposits, which can induce differential settlement, structural deterioration, and systemic risks to urban infrastructure. Further, engineering activities, such as construction and loadings, exacerbate subsidence, impacting infrastructure stability. Therefore, monitoring the integrity and vulnerability of linear urban infrastructure after construction on reclaimed land is critical for understanding settlement dynamics, ensuring safe and reliable operation and minimizing cascading hazards. Subsequently, in the present study, to monitor deformation of the linear infrastructure constructed over decades-old reclaimed land in Mokpo city, South Korea (where 70% of urban and port infrastructure is built on reclaimed land), we analyzed 79 Sentinel-1A SLC ascending-orbit datasets (2017-2023) using the Persistent Scatterer Interferometry (PSInSAR) technique to quantify vertical land motion (VLM). Results reveal settlement rates ranging from -12.36 to 4.44 mm/year, with an average of -1.50 mm/year across 1869 persistent scatterers located along major roads and railways. To interpret the underlying causes of this deformation, Casagrande plasticity analysis of subsurface materials revealed that deep marine clays beneath the reclaimed zones have low permeability and high compressibility, leading to slow pore-pressure dissipation and prolonged consolidation under sustained loading. This geotechnical behavior accounts for the persistent and spatially variable subsidence observed through PSInSAR. Spatial pattern analysis using Anselin Local Moran's I further identified statistically significant clusters and outliers of VLM, delineating critical infrastructure segments where concentrated settlement poses heightened risks to transportation stability. A hyperbolic settlement model was also applied to anticipate nonlinear consolidation trends at vulnerable sites, predicting persistent subsidence through 2030. Proxy-based validation, integrating long-term groundwater variations, lithostratigraphy, effective shear-wave velocity (Vs30), and geomorphological conditions, exhibited the reliability of the InSAR-derived deformation fields. The findings highlight that Mokpo's decades-old reclamation fills remain geotechnically unstable, highlighting the urgent need for proactive monitoring, targeted soil improvement, structural reinforcement, and integrated InSAR-GNSS monitoring frameworks to ensure the structural integrity of road and railway infrastructure and to support sustainable urban development in reclaimed coastal cities worldwide.

This study presents a novel micromorphic continuum model for sand-gravel mixtures with low gravel contents, which explicitly accounts for the influences of the particle size distribution, gravel content, and fabric anisotropy. This model is rigorously formulated based on the principle of macro-microscopic energy conservation and Hamilton's variational principle, incorporating a systematic analysis of the kinematics of coarse and fine particles as well as macro-microscopic deformation differentials. Dispersion equations for plane waves are derived to elucidate wave propagation mechanisms. The results demonstrate that the model effectively captures normal dispersion characteristics and size-dependent effects on wave propagation in these mixtures. In long-wavelength regimes, wave velocities are governed by macroscopic properties, whereas decreasing wavelengths induce interparticle scattering and multiple reflections, attenuating velocities or inhibiting waves, especially when wavelengths approach interparticle spacing. The particle size, porosity, and stiffness ratio primarily influence the macroscopic average stiffness, exhibiting consistent effects on dispersion characteristics across all wavelength domains. In contrast, the particle size ratio and gravel content simultaneously influence both macroscopic mechanical properties and microstructural organization, leading to opposing trends across different wavelength ranges. Model validation against experiments confirms its exceptional predictive ability regarding wave propagation characteristics, including relationships between lowpass threshold frequency, porosity, wave velocity, and coarse particle content. This study provides a theoretical foundation for understanding wave propagation in sand-gravel mixtures and their engineering applications.