The aerosol scattering phase function (ASPF), a crucial element of aerosol optical properties, is pivotal for radiative forcing calculations and aerosol remote sensing detection. Current detection methods for the ASPF include multi-sensor detection, single-sensor rotational detection and imaging detection. However, these methods face challenges in achieving high-resolution full-angle measurement, particularly for small forward (i.e., less than 10 degrees) or backward (i.e., more than 170 degrees) scattering angles in open path. In this work, a full-angle ASPF detection system based on the multi-field-of-view Scheimpflug lidar technique has been proposed and demonstrated. A 450 nm continuous-wave semiconductor laser was utilized as the light source and four CMOS image sensors were employed as detectors. To detect the full-angle ASPF, four receiving units capture angular scattering signals across different angle ranges, namely 0 degrees-20 degrees, 10 degrees-96 degrees, 84 degrees-170 degrees, 160 degrees-180 degrees, respectively. The influence of the relative illumination and angular response of the used image sensors have been corrected, and a signal stitching algorithm was developed to obtain a complete 0-180 degrees angular scattering signal. Atmospheric measurements have been conducted by employing the full-angle ASPF detection system in open path. The experimental results of the ASPF have been compared with the AERONET data from the Socheongcho station and simulated ASPF based on the typical aerosol models in mainland China, showing excellent agreement. The promising results demonstrated in this work have shown a great potential for detecting the full-angle ASPF in open path.

The presence of frozen volatiles (especially H2O ice) has been proposed in the permanently shadowed regions (PSRs) near the poles of the Moon, based on various remote measurements including the visible and near-infrared (VNIR) spectroscopy. Compared with the middle- and low-latitude areas, the VNIR spectral signals in the PSRs are noisy due to poor solar illumination. Coupled with the lunar regolith coverage and mixing effects, the available VNIR spectral characteristics for the identification of H2O ice in the PSRs are limited. Deep learning models, as emerging techniques in lunar exploration, are able to learn spectral features and patterns, and discover complex spectral patterns and nonlinear relationships from large datasets, enabling them applicable on lunar hyperspectral remote sensing data and H2O-ice identification task. Here we present H2O ice identification results by a deep learning-based model named one-dimensional convolutional autoencoder. During the model application, there are intrinsic differences between the remote sensing spectra obtained by the orbital spectrometers and the laboratory spectra acquired by state-of-the-art instruments. To address the challenges of limited training data and the difficulty of matching laboratory and remote sensing spectra, we introduce self-supervised learning method to achieve pixel-level identification and mapping of H2O ice in the lunar south polar region. Our model is applied to the level 2 reflectance data of Moon Mineralogy Mapper. The spectra of the identified H2O ice-bearing pixels were extracted to perform dual validation using spectral angle mapping and peak clustering methods, further confirming the identification of most pixels containing H2O ice. The spectral characteristics of H2O ice in the lunar south polar region related to the crystal structure, grain size, and mixing effect of H2O ice are also discussed. H2O ice in the lunar south polar region tends to exist in the form of smaller particles (similar to 70 mu m in size), while the weak/absent 2-mu m absorption indicate the existence of unusually large particles. Crystalline ice is the main phase responsible for the identified spectra of ice-bearing surface however the possibility of amorphous H2O ice beneath optically sensed depth cannot be ruled out.

Root-knot nematodes (RKN) severely reduce watermelon yields worldwide, despite its nutraceutical value. This study investigated the effects of rock dust (RD) and poultry manure (PM) amendments, applied singly or in combination, on RKN suppression and watermelon fruit yield enhancement. A two-trial field experiment was conducted utilizing a randomized complete block design with three replicates. The treatments included RD and PM each applied at 0, 2.5, or 5 t/ha and combined applications of RD and PM at 2.5 or 5 t/ha each. At 60-66 days post-inoculation, root galling and RKN population density were assessed alongside root-shoot weight. The results indicated that root galling in watermelons was reduced by 60-85 % and 67-89 % in the combined RD- and PMtreated plots across the 1st and 2nd trials, respectively, in contrast to the control plots. Likewise, the RKN population was suppressed by 94-99 % in treated plots in both trials, differing from the control plots. Notably, watermelon fruit yield was significantly higher (p < 0.05) in combined RD and PM treated plots, ranging from 24.7 to 33.7 t/ha and 34.6-46.5 t/ha in the 1st and 2nd trials, respectively, compared to control plots with 13.5 t/ha in the 1st trial compared to and 20.9 t/ha yield in the 2nd trial. In conclusion, our study indicates that coapplication of RD and PM effectively reduced RKN damage and enhanced watermelon fruit yield, providing a sustainable strategy for watermelon production.

Internal erosion induces alterations in the initial microstructure of soils, simultaneously affecting physical, hydraulic, and mechanical properties. The initial soil composition plays a crucial role in governing the initiation and progression of seepage-induced suffusion. This study employs the controlled variable method to develop granular soil models with varying particle size ratios, initial fine particle contents, and coarse particle shapes. Seepage suffusion simulations coupled with microstructural analyses are conducted using the CFD-DEM approach. Results demonstrate that particle size ratio, fine particle content, and coarse particle shape exert distinct influences on cumulative erosion mass, fine particle distribution, contact fabric, and mechanical redundancy at both macroscopic and microscopic scales. This numerical investigation advances the fundamental understanding of internal erosion mechanisms and informs the development of micro-mechanical constitutive models. Furthermore, for binary granular media composed of coarse and fine particles, careful control of the particle size ratio and fine content is recommended when utilizing gap-graded soils in embankment and dam construction to improve structural resilience and resistance to internal erosion.

The frequent occurrence of earthquakes worldwide has rendered highway slope protection projects highly vulnerable to damage from seismic events and their secondary disasters. This severely hampers the smooth implementation of post-disaster rescue and recovery efforts. To address this challenge, this study proposes a comprehensive method for assessing seismic losses in slope protection projects, incorporating factors such as topography and elevation to enhance its universality. The method categorizes seismic losses into two main components: damage to protection structures and costs associated with landslide and rockfall clearance and transportation. This study estimates the cost range for common protection structures and clearance methods under general conditions based on widely recognized quota data in China. It establishes criteria for classifying the damage states of protection structures and provides loss ratio values based on real-world seismic examples and expert experience, constructing a model for assessing damage losses. Additionally, by summarizing the geometric characteristics of soil and rock accumulations on road surfaces, a method for estimating landslide volumes is proposed, considering the dynamic impact of slope gradients on clearance and transportation volumes, and a corresponding cost assessment model for clearance and transportation is developed. The feasibility and reliability of the proposed method are verified through two case studies. The results demonstrate that the method is easy to implement and provides a scientific basis for improving relevant standards and practices. It also offers an efficient and scientific tool for loss assessment to industry practitioners.

Seasonal freezing and thawing significantly influence the migration and distribution of soil hydrothermal salts. Understanding the dynamics of hydrothermal salt forces in canal foundation soils is crucial for effective canal disease control and optimization. However, the impact on rectangular canals remains poorly understood. Therefore, field-scale studies on water-heat-salt-force-displacement monitoring were conducted for the canal. The study analyzed the changes and interaction mechanisms of water-heat-salt-force in the soil beneath the canal, along with the damage mechanisms and preventive measures. The results indicate that the most rapid changes in temperature, moisture, and salt occur in the subsoil on the canal side, with the greatest depth of freezing. Heat transfer efficiency provides an intuitive explanation for the sensitivity of ground temperature at the junction of the canal wall and subsoil to air temperature fluctuations, as well as the minimal moisture migration in this region under the subcooling effect. The temperature-moisture curve suggests that current waterheat-force and water-heat-salt-force models exhibit a delay in accurately predicting water migration within the subsoil. Rectangular canals are more susceptible to damage under peak freezing conditions, requiring a combined approach of freezing restraint and frost-heaving force to mitigate damage. These findings offer valuable insights for canal design, maintenance, and further research.

This paper deals with the contribution of the soil-structure interaction (SSI) effects to the seismic analysis of cultural heritage buildings. This issue is addressed by considering, as a case study, the Mosque-Cathedral of Cordoba (Spain). This study is focussed on the Abd al-Rahman I sector, which is the most ancient part, that dates from the 8th century. The building is a UNESCO World Heritage Site and it is located in a moderate seismic hazard zone. It is built on soft alluvial strata, which amplifies the SSI. Since invasive tests are not allowed in heritage buildings, in this work a non-destructive test campaign has been performed for the characterisation of the structure and the soil. Ambient vibration tests have been used to calibrate a refined 3D macro-mechanical-based finite element model. The soil parameters have been obtained through an in situ geotechnical campaign, that has included geophysical tests. The SSI has been accounted for by following the direct method. Nonlinear static and dynamic time-history analyses have been carried out to assess the seismic behaviour. The results showed that the performance of the building, if the SSI is accounted for, is reduced by up to 20 % and 13 % in the direction of the arcades and in the perpendicular direction, respectively. Also, if the SSI is taken into account, the damage increased. This study showed that considering the SSI is important to properly assess the seismic behaviour of masonry buildings on soft strata. Finally, it should be highlighted that special attention should be paid to the SSI, which is normally omitted in this type of studies, to obtain a reliable dynamic identification of the built heritage.

Zn2+ play an important role in maintaining the normal functioning of living organisms, and excessive or insufficient levels can cause serious health problems. Zn2+ play a vital role in maintaining normal biological functions, and abnormal levels Zn2+ may lead to a range of severe health issues. Therefore, real-time and accurate detection of Zn2+ is critically important. Given the widespread presence of Zn2+ in living organisms and external environments, developing probes suitable for multi-scenario Zn2+ detection is of significant practical value. In this study, a novel probe SSD was synthesized using salicylaldehyde as the precursor, enabling ultra-sensitive Zn2+ detection with a detection limit as low as 9.1 nM. The probe SSD was successfully applied to the detection of Zn2+ in water, soil, and food samples. In addition, an SSD-based Zn2+ smartphone detection platform was developed, which can quickly detect the content of Zn2+ in actual samples. Moreover, due to its excellent optical properties and low toxicity, SSD was able to detect both intracellular and extracellular Zn2+. Most importantly, probe SSD demonstrated the capability to monitor real-time changes in Zn2+ concentrations during cellular oxidative damage, providing valuable insights for research on related physiological diseases.

Open-ended pipe piles (OEPPs) are widely used in offshore foundations, yet accurately predicting their driving responses remains challenging due to soil plug complexities. Existing pile driving analysis models inadequately characterize the effects of soil plug, potentially leading to driving problems such as hammer refusal, pile running, and structural damage. This paper proposes an effective soil plug (ESP) model for OEPP driving analysis. The ESP model considers the effective range of soil plug, which exerts internal resistance that increases exponentially with depth while the beyond of effective range contributes only mass inertia. It also accounts for the relative slippage at the pile-soil plug interface. A differential iterative method is developed to solve the ESP model. Subsequently, investigations including the model validation and parameter analysis are conducted. Model validations against existing models and field measurements confirms the reliability of the ESP model. Parameters sensitivity analysis reveals the importance of soil plug length and distribution type of internal resistance on the pile dynamic responses. In addition, if soil plug slippage occurs, the displacement peak of soil plug increases with depth rather than one-dimensional wave attenuation. Furthermore, contrary to previous assumptions of continuous slippage, the soil plug experiences a discontinuous jump-sliding mode under long-duration impact loading. These findings provide theoretical basis for OEPP driving simulation and interpretations of high-strain dynamic test.

This paper establishes a novel full-process numerical simulation framework for analyzing the 3D seismic response of mountain tunnels induced by active faults. The framework employs a two-step approach to achieve wavefield transmission through equivalent seismic load: first, a highly efficient and accurate FMIBEM (Fast multipole indirect boundary element method) is used for large-scale 3D numerical simulations at the regional scale to generate broadband ground motions (1-5 Hz) for specific sites; subsequently, using the FEM (Finite element method), a refined simulation of the plastic deformation of surrounding rock and the elastoplastic behavior of the tunnel structure was conducted at the engineering scale. The accuracy of the framework has been validated. To further demonstrate its effectiveness, the framework is applied to analyze the impact of different fault movement mechanisms on the damage to mountain tunnels based on a scenario earthquake (Mw 6.7). By introducing tunnel structure damage classification and corresponding damage indicators, the structural damage levels of tunnels subjected to active fault movements are quantitatively evaluated. The findings demonstrate that the framework successfully simulates the entire process, from fault rupture and terrain amplification to the seismic response of tunnel structures. Furthermore, the severity of tunnel damage caused by different fault types is ranked as follows: reverse fault > normal fault > strike-slip fault.