Buried pipelines are essential for the safe and efficient transportation of energy products such as oil, gas, and various chemical fluids. However, these pipelines are highly vulnerable to ground movements caused by geohazards such as seismic faults, landslide, liquefaction-induced lateral spreading, and soil creep, which can result in potential pipeline failures such as leaks or explosions. Response prediction of buried pipelines under such movements is critical for ensuring structural integrity, mitigating environmental risks, and avoiding costly disruptions. As such, this study adopts a Physics-Informed Neural Networks (PINNs) approach, integrated with a transfer learning technique, to predict structural response (e.g., strain) of both unreinforced and reinforced steel pipes subjected to Permanent Ground Displacement (PGD). The PINN method offers a meshless, simulation-free alternative to traditional numerical methods such as Finite Element Method (FEM) and Finite Difference Method (FDM), while eliminating the need for training data, unlike conventional machine learning approaches. The analyses can provide useful information for in-service pipe integrity assessment and reinforcement, if needed. The accuracy of the predicted results is verified against Finite Element (FE) and Finite Difference (FD) methods, showcasing the capability of PINNs in accurately predicting displacement and strain fields in pipelines under geohazard-induced ground movement.

Biogrouting has been proposed for improving mechanical properties of soils and rocks, whose performance greatly depends on the location of biocement at pore-scale. To enhance the performance of biogrouting, many strategies were proposed, including the addition of assistants, controlling curing moisture degree, and flocculation of bacteria. Clay is one such assistant which has been proven to be effective, with an assumption of increasing active biocement, i.e. those located between soil particles. In this work, we employed microfluidics to directly observe whether clay minerals can certainly control the location of precipitates and how they function. First of all, the capacity of bentonite and kaolin for adsorbing bacteria were investigated. Then, the location of CaCO3 crystals with and without clay minerals were visually observed using microfluidics. Pore-filling ratios and CaCO3 ratios, which are closely related to permeability and strength of biocemented soils, were quantitatively analyzed from collected images. Finally, the effects of bentonite and kaolin and their dosages on the location of biocement were comprehensively discussed. The results demonstrated that the performance of bentonite and kaolin on adsorbing bacteria and regulating biocement location is distinct due to differences in the morphologies of clays. These findings can help us to improve biogrouting performance on soil stabilization and propose new strategies in various practical applications, such as CO2 sequestration, heavy metal remediation, and oil recovery enhancement, all with a foundational understanding of their mechanisms.

Surface soil moisture (SSM) is a key limiting factor for vegetation growth in alpine meadow on the Qinghai-Tibetan Plateau (QTP). Patches with various sizes and types may cause the redistribution of SSM by changing soil hydrological processes, and then trigger or accelerate alpine grassland degradation. Therefore, it is vital to understand the effects of patchiness on SSM at multi-scales to provide a reference for alpine grassland restoration. However, there is a lack of direct observational evidence concerning the role of the size and type of patches on SSM, and little is known about the effects of patches pattern on SSM at plot scale. Here, we first measured SSM of typical patches with different sizes and types at patch scale and investigated their patterns and SSM spatial distribution through unmanned aerial vehicle (UAV)-mounted multi-type cameras at plot scale. We then analyzed the role of the size and type of patchiness on SSM at both patch and plot scales. Results showed that: (1) in situ measured SSM of typical patches was significantly different (P < 0.01), original vegetation patch (OV) had the highest SSM, followed by isolate vegetation patch (IV), small bare patch (SP), medium bare patch (MP) and large bare patch (LP); (2) the proposed method based on UAV images was able to estimate SSM (0-40 cm) with a satisfactory accuracy (R-2 = 0.89, P < 0.001); (3) all landscape indices of OV, with the exception of patch density, were positively correlated with SSM at plot scale, while most of the landscape indices of LP and IV showed negative correlations (P < 0.05). Our results indicated that patchiness intensified the spatial heterogeneity of SSM and potentially accelerated the alpine meadow degradation. Preventing the development of OV into IV and the expansion of LP is a critical task for alpine meadow management and restoration.

This study conducted load-bearing capacity tests to quantitatively analyze the impact of permafrost degradation on the vertical load-bearing capacity of railway bridge pile foundations. Meanwhile, a prediction model vertical load-bearing capacity for pile foundations considering permafrost degradation was developed and validated through these tests. The findings indicate that the permafrost degradation significantly influences both the failure patterns of the pile foundation and the surrounding soil. With the aggravation of permafrost degradation, damage to the pile foundation and the surrounding soil becomes more pronounced. Furthermore, permafrost degradation aggravates, both the vertical ultimate bearing capacity and maximum side friction resistance of pile foundations exhibit a significant downward trend. Under unfrozen soil conditions, the vertical ultimate bearing capacity of pile foundations is reduced to 20.1 % compared to when the permafrost thickness 160 cm, while the maximum side friction resistance drops to 13.2 %. However, permafrost degradation has minimal impact on the maximum end bearing capacity of pile foundations. Nevertheless, as permafrost degradation aggravates, the proportion of the maximum end bearing capacity attributed to pile foundations increases. Moreover, the rebound rate of pile foundations decreases with decreasing permafrost thickness. Finally, the results confirm that the proposed prediction model can demonstrates a satisfactory level of accuracy in forecasting the impact of permafrost degradation on the vertical load-bearing capacity of pile foundations.

The pedunculate oak (Quercus robur L.) is a major tree species in Europe, but it has faced recent growth decline and dieback events in some areas resulting in economic and ecosystem losses. In the southeastern edge of its natural distribution in eastern Romania, rising temperatures since the 1980s, when a shift towards warmer and more arid conditions occurred, increased evaporative demand and triggered growth decline. We analyzed the adaptive potential of six oak stands (333 individual trees) with ages ranging between 97 and 233 years, located in three wet and three dry sites. Results showed unstable climate-growth correlations with a breakpoint after 1985 when climate warming intensified. Wet soil conditions from early spring to summer enhanced growth; on the contrary, a high evaporative demand linked to warmer conditions and greater potential evapotranspiration reduced growth, particularly in wet sites. After 1985, drought stress induced a reduction in latewood width in dry sites. The relationship between growth and summer-autumn drought intensified during the last decades in all sites. Warmer spring conditions negatively affected oak growth, particularly latewood production. Wet sites had lower resilience indices, and we also noted a post-1985 progressive reduction of growth resilience. Slow-growing trees from dry sites showed growth decline, which could be an early-warning signal of impending dieback and tree death. In contrast, fast-growing trees from wet sites showed sustained relative growth improvement, which was attributed to tree age and size effects. After 1985, the pedunculate oak is more vulnerable to drought damage in dry sites near the southeastern distribution limit in response to hotter winter-spring droughts.

Calculation and prediction of the uplift capacity of squeezed branch piles (SBP) are still immature. This study develops a method to predict the load-displacement relationship and ultimate capacity of SBP under pullup load by using a hyperbolic model to describe the nonlinear load transfer between pile-soil and plate-soil. The uplift bearing behaviors of SBP are analyzed through six sets of indoor model tests in homogeneous soils. The results, along with field tests of single-plate piles in layered soils and the indoor tests, confirm the high accuracy of the theoretical prediction method. The effects of three factors, including the pile side soil damage ratio (Rf), the horizontal earth pressure coefficient (k) and the damage angles of the soil under plate (psi), on the prediction results are analyzed. The results show that these factors significantly affect the second half of the loaddisplacement curve of SBP. Furthermore, as the Rf rises, the anticipated ultimate uplift capacity of SBP decreases linearly; as the k rises, it increases linearly; and as the psi rises, it increases nonlinearly.

Cotton aphid (Aphis gossypii Glover) is a harmful pest that affects cotton crops in Xinjiang, China. Afidopyropen is a new type of insecticide that exerts a strong control effect on piercing-sucking pests. In this work, Highperformance liquid chromatography (HPLC) was used to assess afidopyropen residues on different cotton parts following foliar spraying and root application. The effects of agent retention on physiological indices of cotton aphids and preventive effects were investigated. The results showed that different application methods had a strong influence on afidopyropen residues, most of which were in cotton roots, with fewer in stems and leaves. Enzyme activity analysis showed that the carboxylesterase activity of A. gossypii was significantly increased under different application methods. Foliar spraying and root application (hydroponics) of afidopyropen had rapid, potent effects against A. gossypii, while root application (soil cultivation) did not have a significant effect, but had a positive effect by day 14. Elucidation of the effects of the two application methods to the physiological indices and control of A. gossypii provide a theoretical basis for the development and promotion of integrated water-pharmaceutical technologies for afidopyropen spraying and drip irrigation in cotton fields in Xinjiang and elsewhere.

A series of finite element analyses, conducted on the basis of modified triaxial tests incorporating radial drainage, were carried out to investigate the lateral deformation and stress state characteristics of prefabricated vertical drain (PVD) unit cells under vacuum preloading. The analyses revealed that the inward horizontal strain of the unit cell increases approximately linearly with the vacuum pressure (Pv) but decreases non-linearly with an increase in the initial vertical effective stress (sigma ' v0). The variations in the effective stress ratio, corresponding to the median excess pore water pressure during vacuum preloading of the PVD unit cell, were elucidated in relation to the Pv and sigma ' v0 using the simulation data. Relationships were established between the normalized horizontal strain and normalized effective stress ratio, as well as between the normalized stress ratio and a composite index parameter that quantitatively captures the effects of vacuum pressure, initial effective stress, and subsoil consolidation characteristics. These relationships facilitate the prediction of lateral deformation in PVD-improved grounds subjected to vacuum preloading, utilizing fundamental preloading conditions and soil properties. Finally, the proposed methodology was applied to analyze two field case histories, and its validity was confirmed by the close correspondence between the predicted and measured lateral deformation.

This study presents a method for remediating soils contaminated by organic pollutants through the selective blocking of pores. This technique is based on the use of yield stress fluids, specifically concentrated biopolymer solutions, which, due to their distinctive rheological properties, preferentially flow through high-conductance flow paths. Following the injection of yield stress fluid, its presence redirects subsequent water flow towards the pores that are typically unswept during standard waterflooding. Laboratory experiments at the pore scale were conducted to validate this method and confirm previous findings from core-flooding experiments. Aqueous xanthan gum solutions were used as microscopic blocking agents in well-characterized micromodels exhibiting microscopic heterogeneities in pore size. The impact of polymer concentration, soil wettability and operating conditions (injection pressure and flow rate) on the residual pollutant saturation following treatment was analyzed, enabling the optimization of the remediation strategy. The use of xanthan gum as a blocking agent led to a significant improvement in pollutant removal compared to conventional waterflooding, delivering consistently better results across all cases studied. The method demonstrated strong performance in water-wet medium, with the average polymer concentration yielding the highest efficiency in pollutant removal.

The wheat powdery mildew (WPM) is one of the most severe crop diseases worldwide, affecting wheat growth and causing yield losses. The WPM was a bottom-up disease that caused the loss of cell integrity, leaf wilting, and canopy structure damage with these symptoms altering the crop's functional traits (CFT) and canopy spectra. The unmanned aerial vehicle (UAV)-based hyperspectral analysis became a mainstream method for WPM detection. However, the CFT changes experienced by infected wheats, the relationship between CFT and canopy spectra, and their role in WPM detection remained unclear, which might blur the understanding for the WPM infection. Therefore, this study aimed to propose a new method that considered the role of CFT for detecting WPM and estimating disease severity. The UAV hyperspectral data used in this study were collected from the Plant Protection Institute's research demonstration base, Xinxiang city, China, covering a broad range of WPM severity (0-85 %) from 2022 to 2024. The potential of eight CFT [leaf structure parameter (N), leaf area index (LAI), chlorophyll a + b content (Cab), carotenoids (Car), Car/Cab, anthocyanins (Ant), canopy chlorophyll content (CCC) and average leaf angle (Deg)] obtained from a hybrid method combining a radiative transfer model and random forest (RF) and fifty-five narrow-band hyperspectral indices (NHI) was explored in WPM detection. Results indicated that N, Cab, Ant, Car, LAI, and CCC showed a decreasing trend with increasing disease severity, while Deg and Car/Cab exhibited the opposite pattern. There were marked differences between healthy samples and the two higher infection levels (moderate and severe infection) for Cab, Car, LAI, Deg, CCC, and Car/Cab. N and Ant only showed significant differences between the healthy samples and the highest infection level (severe infection). As Cab, Car, and Ant decreased, the spectral reflectance in the visible light region increased. The decrease in N and LAI was accompanied by a reduction in reflectance across the entire spectral range and the near-infrared area, which was exactly the opposite of Deg. The introduction of CFT greatly improved the accuracy of the WPM severity estimation model with R2 of 0.92. Features related to photosynthesis, pigment content, and canopy structure played a decisive role in estimating WPM severity. Also, results found that the feature importance showed a remarkable interchange as increasing disease levels. Using features that described canopy structure changes, such as optimized soil adjusted vegetation index, LAI, visible atmospherically resistant indices, and CCC, the mild infection stage of this disease was most easily distinguished from healthy samples. In contrast, most severe impacts of WPM were best characterized by features related to photosynthesis (e.g., photochemical reflectance index 515) and pigment content (e.g., normalized phaeophytinization index). This study help deepen the understanding of symptoms and spectral responses caused by WPM infection.