The lateral cyclic bearing characteristics of pile foundations in coastal soft soil treated by vacuum preloading method (VPM) are not well understood. To investigate, static lateral cyclic loading tests were conducted to assess the impact of treatment durations and sealing conditions on pile performance. Results indicated that vacuum preloading significantly improved soil properties, with undrained shear strength (S-u) increasing by up to 36.5 times, especially in shallow layers. Longer treatment durations boosted the ultimate lateral bearing capacity by up to 125%, although the effect decreased with depth, suggesting an optimal duration. Sealing conditions had minimal impact on capacity but affected S-u distribution and pile behaviour. Analysis of p-y curves revealed that longer durations improved soil resistance in shallow layers, while shorter durations provided consistent resistance across depths. Sealed conditions enhanced displacement capacity. The API specification predicted soil resistance accurately for lateral displacements under 0.1D but showed errors for larger displacements. These findings emphasise the need for optimising VPM parameters to enhance pile-soil interaction and lateral cyclic performance. The study offers guidance for applying VPM in soft soil foundation engineering and balancing performance with cost efficiency.

The southern regions of China are rich in ion-adsorbed rare earth mineral resources, primarily distributed in ecologically fragile red soil hilly areas. Recent decades of mining activities have caused severe environmental damage, exacerbating ecological security (ES) risks due to the inherent fragility of the red soil hilly terrain. However, the mechanisms through which multiple interacting factors influence the ES of rare earth mining areas (REMA) remain unclear, and an effective methodological framework to evaluate these interactions dynamically is still lacking. To address these challenges, this study develops an innovative dynamic ES evaluation and earlywarning simulation framework, integrating Variable Weight (VW) theory and the Bayesian Network (BN) model. This framework enhances cross-stage comparability and adapts to evolving ecological conditions while leveraging the BN model's diagnostic inference capabilities for precise ES predictions. A case study was conducted in the Lingbei REMA. The main findings of the study are as follows: (1) From 2000 to 2020, the overall ES of the mining area exhibited a dynamic trend of deterioration, followed by improvement, and ultimately stabilization. (2) Scenario S27 (high vegetation health status and high per capita green space coverage) significantly reduces the probability of the ES reaching the extreme warning level. (3) The evaluation and simulation framework developed in this study provides a more accurate representation of the ES level distribution and its variations, with probabilistic predictions of ES demonstrating high accuracy. This study is of great significance for improving regional ES, supporting the optimization of ecological restoration strategies under multi-objective scenarios, and promoting the coordinated development of nature and resource utilization.

This study evaluated the usability and effectiveness of robotic platforms working together with foresters in the wild on forest inventory tasks using LiDAR scanning. Emphasis was on the Universal Access principle, ensuring that robotic solutions are not only effective but also environmentally responsible and accessible for diverse users. Three robotic platforms were tested: Boston Dynamics Spot, AgileX Scout, and Bunker Mini. Spot's quadrupedal locomotion struggled in dense undergrowth, leading to frequent mobility failures and a System Usability Scale (SUS) score of 78 +/- 10. Its short, battery life and complex recovery processes further limited its suitability for forest operations without substantial modifications. In contrast, the wheeled AgileX Scout and tracked Bunker Mini demonstrated superior usability, each achieving a high SUS score of 88 +/- 5. However, environmental impact varied: Scout's wheeled design caused minimal disturbance, whereas Bunker Mini's tracks occasionally damaged young vegetation, highlighting the importance of gentle interaction with natural ecosystems in robotic forestry. All platforms enhanced worker safety, reduced physical effort, and improved LiDAR workflows by eliminating the need for human presence during scans. Additionally, the study engaged forest engineering students, equipping them with hands-on experience in emerging robotic technologies and fostering discussions on their responsible integration into forestry practices. This study lays a crucial foundation for the integration of Artificial Intelligence (AI) into forest robotics, enabling future advancements in autonomous perception, decision-making, and adaptive navigation. By systematically evaluating robotic platforms in real-world forest environments, this research provides valuable empirical data that will inform AI-driven enhancements, such as machine learning-based terrain adaptation, intelligent path planning, and autonomous fault recovery. Furthermore, the study holds high value for the international research community, serving as a benchmark for future developments in forestry robotics and AI applications. Moving forward, future research will build on these findings to explore adaptive remote operation, AI-powered terrain-aware navigation, and sustainable deployment strategies, ensuring that robotic solutions enhance both operational efficiency and ecological responsibility in forest management worldwide.

Compared with the water-base drilling fluid, oil-based drilling fluid has always been one of the important technical guarantees in high temperature deep well, high-inclination directional well and all kinds of complex seismic exploration. With 5#white oil selected and taken as continuous phase, emulsifying agent, organic soil, tackifier, fluid loss agent, lime, other treatment agents and dosages are optimized and the optimal formula of oil-base drilling fluid is determined. This new type environmentally-friendly oil-base drilling fluid possesses good rheological properties, suspension capability, high temperature stability, stronger anti-pollution ability and common emulsion-breaking voltage of more than 2000 V. During the field application, this fluid possesses regular borehole diameter, good lubricity, stable borehole, simple preparation process, easy site maintenance and good reservoir protection features. Furthermore, it can solve complex formation, water expansion of clay shale, poor lubrication & drag reduction effect, poor reservoir protection effect and other technically-difficult problems.

To address the low utilization rate of construction waste soil and the environmental impact of traditional cement solidification, this study investigates the effect of desulfurized gypsum and silica fume in synergy with cement for construction waste soil. The effects of solidifying material dosage, liquid-to-solid ratio, and mixing ratio on mechanical properties were analyzed. Optimal performance was achieved with the dosage of solidifying material was 20%, the liquid-to-solid ratio was 0.2, and the mixing ratio of desulfurized gypsum, silica fume, and cement was 2:1:1, meeting the requirements of the technical specification for application of road solidified soil (T/CECS 737-2020). This formulation is referred to as FS-C type solidified soil. A self-fabricated carbonation device was employed to assess carbonation methods, time, and curing age on the mechanical properties of solidified soil. Carbonation for 6 h post-molding significantly enhanced strength, while carbonation in a loose state led to strength reduction. SEM analysis revealed a denser microstructure in carbonated samples due to calcium carbonate and silica gel formation. Compared to traditional cement solidification, FS-C type solidified soil reduces cement consumption by 15%, decreases CO2 emissions by 299.25 g/m(3), and sequesters 85 g/m(3) of CO2. These findings highlight the potential of FS-C type solidified soil as an environmentally friendly alternative for construction applications.

In recent years, some cities have adopted a new type of tunnel termed quasi-rectangular tunnel (QRT). Compared with the common double-line single-circle tunnel, the QRT has a smaller cross- and narrower spacing. Existing researches about QRTs mainly focus on their mechanical properties, with a lack of research on the influence of vibration and resulting noise on the surrounding environment. The vibration and structure-borne noise in the building along the subway line are adverse to human health when trains pass through the QRT. In this paper, the characteristics of vibration generated by train operation in the QRT and the propagation law in the soil are analyzed based on the finite element method-infinite element method (FEM-IEM) model. Combined with the monitoring data, vibration and indoor secondary structure-borne noise and their annoyance degrees in a 7-storey residential building 18m away from the line are also predicted and evaluated. Results show that during the ground vibration, indoor vibration and structure-borne noise of buildings along the line are mainly concentrated in the frequency band around 40Hz. The vibration and structure-borne noise of the first floor all exceed the night limit specified by an industry standard. The annoyance caused by vibration on the first floor is 0.96, which makes people feel very annoyed, while the annoyance caused by noise is 0.251, which makes people feel slightly annoyed. The research results highlight the effects of railway-induced vibrations in QRT on the building along the subway line, emphasizing their importance in the development of rail transit with QRT. The estimated vibration and noise levels, along with the degrees of annoyance, can be effectively utilized during the design and construction processes of both QRT and buildings to mitigate negative impacts on human comfort and health.

Electrical resistivity tests can potentially be applied in loess damage testing under combined freeze-thaw cycle (FTC) and earthquake conditions, which is crucial for preventing and controlling loess landslides. However, two challenges involving loess electrical resistivity measurements and damage characterization should be addressed. To achieve loess spatial resistivity measurements in extreme environments with low-uncertainty, a novel, multichannel, four-point method utilizing flexible electrodes is proposed. For loess damage characterization, a novel fusion algorithm is developed that integrates the electrical conductivity model with a data-driven process to eliminate the influence of moisture content and temperature on resistivity. To validate this approach, loess resistivity tests and damage characterizations were conducted using a combination of FTCs and earthquakes. The results indicate that the proposed method addresses the challenge of continuous measurement, ensuring that the discrepancy between the calculated and CT test results remains within an acceptable range, where the relative error ranged from 0 to 0.15. In addition, in the top and bottom areas, where considerable soil moisture exists, the calculation error associated with the previous empirical model was reduced considerably, with the relative error primarily ranging from 0.04 to 0.44.

Regulations on chemicals aim to protect public health and the environment. However, owing to the nature of this chemical, it is difficult to determine its impact pathway. Thus, it is difficult to investigate the damage caused by chemicals. However, it is essential to evaluate the costs and benefits of chemicals to establish reasonable chemical regulations. Therefore, this study analyzes the benefits of strengthening the regulation of chemical substances in Korea using the conditional valuation method. In particular, this study evaluated the public benefit of the chemical regulation of arsenic, which is a carcinogen. Data were collected from 1000 households in Korea, and a one-and-one-half-bound dichotomous choice spike model was used. The results show that the average annual willingness to pay for additional income tax payments over 10 years to reduce the incidence of arsenic-related diseases is 4314 Korean won (3.67 USD), with 57.5% of households refusing to pay. Additional analysis indicates that females are more willing to pay, and a higher education level, knowledge of arsenic, and experience in using arsenic-free products and hand sanitizers lead to a higher willingness to pay. The results of this study can be used to establish an efficient level of arsenic regulations and determine their effect on the related market.

The pressuremeter test is a widely used in-situ test method in geotechnical engineering for determining ground properties. It is applicable to all types of soil and weak rocks, it records soil deformation under loading conditions. This paper presents a literature review on the application of the pressuremeter test in evaluating the behavior of foundations under load. It explores the methods used to interpret pressuremeter test data in various soil types, reviews the different analytical models employed, and focuses on approaches for assessing the behavior of foundations using pressuremeter test results. The achievements and limitations of each method are presented and discussed. Despite the extensive literature on the applications, interpretation, and development of the pressuremeter test, its use in evaluating the behavior of foundations under load remains limited. This work seeks to address this research gap by identifying challenges in utilizing pressuremeter test data for such analyses and providing recommendations for future research. This work aims to encourage further investigation into the potential of pressuremeter tests for advancing the understanding of foundation behavior under loading conditions.

Global demand for ecosystem services like food and clean water is increasing, and it is crucial to economically value these services for the purposes of environmental conservation, land-use planning, and the implementation of green taxes. Focusing on a monoculture wheat agroecosystem, the economic value of ecosystem services and environmental damage from different farm management types is here compared with natural ecosystems in a semi-arid region in Iran during the 2019-2020 agricultural year. Using field survey data collected from 203 wheat farms with varying management practices, we estimated the economic value of six ecosystem services, along with three environmental damages. The net value of provisioning/regulating services less environmental disservices in wheat agroecosystems was highest for farms with a conservation management system, followed (in rank order) by intensive, traditional, organic, and industrial management types. Wheat agroecosystems recorded net values of 41.94% to 66.92% below those of natural ecosystems in the region. The findings show that converting natural ecosystems into wheat agroecosystems increases the value of provisioning services (food and forage) but also substantially increases environmental costs. These costs rose linearly with the value of increases in provisioning services.