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.

Ambient seismic noise and microseismicity analyses are increasingly applied for the monitoring of landslides and natural hazards. These methodologies can offer a valuable monitoring tool also for glacial and periglacial bodies, to understand the internal processes driven by external modifications in air temperature and rainfall/snowfall regimes and to forecast possible melting-related hazards in the light of climate change adaptation. We applied the methods to an almost continuous year of data recorded by a network of four passive seismic stations deployed in the frontal portion of the Gran Sometta rock glacier (Aosta Valley, NW Italian Alps). The spectral analysis of ambient seismic noise revealed frequency peaks related to stratigraphic resonances inside the rock glacier. Although the resonance frequency related to the bedrock interface was constant over time, a second higher resonance frequency was identified as the effect of variations in the active layer thickness driven by external air temperature modifications at the daily and seasonal scales. Ambient seismic noise cross-correlation highlighted coherent shear wave velocity modifications inside the periglacial body. The microseismicity dataset extracted from the continuous ambient noise recordings was analyzed and clustered to further investigate the ongoing internal processes and gain insight into their source mechanism and location. The first cluster of events was found to be likely related to the basal movements of the rock glacier and to falls and slides of the debris material. The second cluster was possibly related to shallow ice and rock fracturing processes. The validation of the seismic results through simple models of the rock glacier physical and mechanical layering, the internal thermal regime and the surface displacements allowed for a comprehensive understanding of the rock glacier's reaction to the external conditions.

In this study, a high-confining pressure and real-time large-displacement shearing-flow setup was developed. The test setup can be used to analyze the injection pressure conditions that increase the hydro-shearing permeability and injection-induced seismicity during hot dry rock geothermal extraction. For optimizing injection strategies and improving engineering safety, real-time permeability, deformation, and energy release characteristics of fractured granite samples driven by injected water pressure under different critical sliding conditions were evaluated. The results indicated that: (1) A low injection water pressure induced intermittent small-deformation stick-slip behavior in fractures, and a high injection pressure primarily caused continuous high-speed large-deformation sliding in fractures. The optimal injection water pressure range was defined for enhancing hydraulic shear permeability and preventing large injection-induced earthquakes. (2) Under the same experimental conditions, fracture sliding was deemed as the major factor that enhanced the hydraulic shear-permeability enhancement and the maximum permeability increased by 36.54 and 41.59 times, respectively, in above two slip modes. (3) Based on the real-time transient evolution of water pressure during fracture sliding, the variation coefficients of slip rate, permeability, and water pressure were fitted, and the results were different from those measured under quasi-static conditions. (4) The maximum and minimum shear strength criteria for injection-induced fracture sliding were also determined (m = 0.6665 and m = 0.1645, respectively, m is friction coefficient). Using the 3D (three-dimensional) fracture surface scanning technology, the weakening effect of injection pressure on fracture surface damage characteristics was determined, which provided evidence for the geological markers of fault sliding mode and sliding nature transitions under the fluid influence. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

The city of A & iuml;n T & eacute;mouchent, located in northwest Algeria at the westernmost part of the Lower Cheliff Basin, has experienced several moderate earthquakes, the most significant of which occurred on 22 December 1999 (Mw 5.7, 25 fatalities, severe damage). In this study, ambient noise measurements from 62 sites were analyzed using the horizontal-to-vertical spectral ratio (HVSR) method to estimate fundamental frequency (f0) and amplitude (A0). The inversion of HVSR curves provided sedimentary layer thickness and shear wave velocity (Vs) estimates. Additionally, four spatial autocorrelation (SPAC) array measurements refined the Rayleigh wave dispersion curves, improving Vs profiles (150-1350 m/s) and sediment thickness estimates (up to 390 m in the industrial zone). Vs30 and vulnerability index maps were developed to classify soil types and assess liquefaction potential within the city.

Installing strong ground motion measuring devices in existing structures is significant for earthquake engineering and building safety to monitor whether the structures can be damaged or not. This study determined with different spectral ratio methods the dominant vibration period and amplification characteristics of both the structure and the ground from earthquake and noise records and compared the results. For this purpose, online- monitored accelerometer devices were placed on the top floor of a 5-story public building that was improved in 2008, on the ground where it was built, and on the rock approximately 1 km away from this building. MASW measurement was taken to determine the ground class of the area where the accelerometer device was installed on the ground right next to the building. Many earthquake records of different distances and magnitudes were obtained by the fixed devices located in the building, on the ground, and the rock. Spectral ratio methods were applied to the recorded earthquakes according to the reference station method and horizontal/vertical ratio methods according to the single station method. In addition to the analyses applied to the earthquake records, noise measurements were taken at night on the building floors and ground, and these measurements were evaluated according to the horizontal/vertical spectral ratio method and floor spectral ratio methods. As a result of all the analyses, the amplifications, dominant frequencies, and damping ratio of the building and the ground were determined, and the interference status of the building and the ground was examined. As a result, it was observed that the dominant frequency of the building, the spectral ratio amplification, and the damping ratio values of the building were approximately the same by using different spectral ratio methods for earthquake and noise data. In addition, there was a slight increase in the building's dominant period as a result of earthquakes that occurred at different times.

The Narrow-Angle Cameras (NACs) onboard the Lunar Reconnaissance Orbiter Camera (LROC) capture lunar images that play a crucial role in current lunar exploration missions. Among these images, those of the Moon's permanently shadowed regions (PSRs) are highly noisy, obscuring the lunar topographic features within these areas. While significant advancements have been made in denoising techniques based on deep learning, the direct acquisition of paired clean and noisy images from the PSRs of the Moon is costly, making dataset acquisition expensive and hindering network training. To address this issue, we employ a physical noise model based on the imaging principles of the LROC NACs to generate noisy pairs of images for the Moon's PSRs, simulating realistic lunar imagery. Furthermore, inspired by the ideas of full-scale skip connections and self-attention models (Transformers), we propose a denoising method based on deep information convolutional neural networks. Using a dataset synthesized through the physical noise model, we conduct a comparative analysis between the proposed method and existing state-of-the-art denoising approaches. The experimental results demonstrate that the proposed method can effectively recover topographic features obscured by noise, achieving the highest quantitative metrics and superior visual results.

The Tibetan Plateau, a critical region influencing both local and global atmospheric circulation, climate dynamics, hydrology and terrestrial ecosystems, is undergoing climate-driven changes, including glacial retreat, permafrost thaw and groundwater changes. Despite its importance, implementing continuous and systematic observations has been challenging due to the area's high altitude and extreme climate conditions. In this context, seismic interferometry emerges as a cost-effective method for the continuous monitoring of subsurface structural changes driven by environmental factors and internal geophysical processes. We investigate subsurface evolution using four years of seismic data from nine stations on the northeastern Tibetan Plateau, by applying coda wave interferometry across multiple frequency bands. Our findings highlight seismic velocity changes within the frequency bands 5-10, 0.77-1.54, and 0.25-0.51 Hz, revealing depth-dependent seasonal and long-term changes. Near-surface and deeper strata exhibit similar seasonal patterns, with velocities increasing in winter and decreasing in summer driven by changes in hydrological processes, while intermediate ice-water phase strata show contrasting behaviour due to thermal elastic strain. Long-term trends suggest that the upper subsurface layer is affected by melting water and precipitation originating from Kunlun Mountains, whereas deeper layer reflect groundwater level variations influenced by climate change and human activities. This study provides insights into the environmental evolution of the Tibetan Plateau and its impact on managing local groundwater resources.

The permanently shadowed regions (PSRs) of the Moon are located at the Moon's polar regions that are permanently in shadow due to their inability to receive direct sunlight. Images of these areas are usually dark and significantly affected by noise, obscuring the lunar terrain information. Although image denoising has made considerable progress, there is still limited study on images denoising of lunar PSRs. The main challenge lies in the fact that images of PSRs are characterized by low contrast, complex noise type, and uneven illumination. The existing deep learning-based methods exhibit poor physical interpretability and cannot effectively remove complex noise. Therefore, this study introduces a novel denoising method by using combination of physical noise models and deep Learning. Specially, the physical noise model is used to simulate the noise of lunar PSRs according to the imaging principles of the lunar reconnaissance orbiter camera narrow angle camera. The improved deep learning model, which incorporates full-scale skip connections and Transformer is used to denoise the images. The proposed method is tested in 297 PRSs images with latitudes below -70 degrees and compared with state-of-the-art methods. Experimental results demonstrate that the proposed method outperforms existing methods in restoring terrain details and provides better quantitative and visual outcomes. This approach has the potential to improve the clarity of lunar PSR images and support future lunar exploration.

The S-wave velocity (Vs) is a valuable parameter for assessing the mechanical properties of subsurface materials for geotechnical purposes. Seismic surface wave methods have become prominent for estimating near-surface Vs models. Researchers have proposed methods based on passive seismic signals as efficient alternatives to enhance depth of investigation, lateral resolution and reduce field effort. This study presents the Multichannel Analysis of Surface Waves (MASW) utilizing Common Virtual Source Gathers (CVSGs) derived from seismic ambient noise cross-correlations, based on Ambient Noise Seismic Interferometry concepts. The method is applied to passive data acquired with an array of receivers at the Paranoa earth dam in Brasilia, Brazil, to construct a pseudo-2D Vs image of the massif for interpretation. Our findings showcase the adopted processing flow and combination of methods as an effective approach for near-surface Vs estimation, demonstrating its usability also for large earth dam embankments.

The Pohang Basin sustained the most extensive seismic damage in the history of instrumental recording in Korea due to the 2017 Mw 5.5 earthquake. The pattern of damage shows marked differences from a radial distribution, suggesting important contributions by local site effects. Our understanding of these site effects and their role in generating seismic damage within the study area remains incomplete, which indicates the need for a thorough exploration of subsurface information, including the thickness of soil to bedrock and basin geometry, in the Pohang Basin. We measured the depth to bedrock in the Pohang Basin using dense ambient noise measurements conducted at 698 sites. We propose a model of basin geometry based on depths and dominant frequencies derived from the horizontal-to-vertical spectral ratio (HVSR) of microtremor at 698 sites. Most microseismic measurements exhibit one or more clear HVSR peak(s), implying one or more strong impedance contrast(s), which are presumed to represent the interface between the basement and overlying basin-fill sediments at each measurement site. The ambient seismic noise induces resonance at frequencies as low as 0.32 Hz. The relationship between resonance frequency and bedrock depth was derived using data from 27 boreholes to convert the dominant frequencies measured at stations adjacent to the boreholes into corresponding depths to the strong impedance contrast. The relationship was then applied to the dominant frequencies to estimate the depth to bedrock over the whole study area. Maps of resonance frequency and the corresponding depth to bedrock for the study area show that the greatest depths to bedrock are in the coastal area. The maps also reveal lower fundamental frequencies in the area west of the Gokgang Fault. The results indicate a more complex basin structure than previously proposed based on a limited number of direct borehole observations and surface geology. The maps and associated profiles across different parts of the study area show pronounced changes in bedrock depth near inferred blind faults proposed in previous studies, suggesting that maps of bedrock depth based on the HVSR method can be used to infer previously unknown features, including concealed or blind faults that are not observed at the surface.