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Monitoring and determining the development of frozen walls is a critical aspect of ensuring safe tunnel construction during freezing periods. Traditional temperature measurements for estimating freezing front expansion are constrained due to the limited number of measurement points and their fixed distribution. Here we introduce an innovative non-destructive detection method to investigate freezing wall expansion behind tunnel shield segments. First, dielectric properties of frozen and unfrozen clay and sandy soil were measured through laboratory experiments. Second, a freezing front model was established using a combination of numerical simulations and laboratory experiments. A 600 MHz radar was employed for detection and identification. Results indicate substantial differences in the dielectric constants of frozen and unfrozen soil, which can be employed as a convincing parameter for GPR to distinguish between them. Detection results demonstrate that GPR possesses the capability to determine the development pattern and approximate location of the frozen front behind shield tunnel segments. This method exhibits significant potential as an efficient and rapid means of detecting freezing wall expansion in tunnel engineering. Highlights: The difference in dielectric properties of frozen & unfrozen soils depends on the unfrozen water content. The electromagnetic responses of freezing front were studied by numerical simulation and indoor experiment. The accuracy of detection results from ground-penetrating radar was verified by conventional thermal methods. A fast and non-destructive method for determining the development of freezing fronts behind shield tunnel segments was proposed. [ABSTRACT FROM AUTHOR]

Microservice architecture is a new technology for deploying large-scale applications and services in the cloud. But multivariate time series data with anomalies are increasingly generated in the cloud. Effectively diagnosing the runtime system anomalies is necessary to ensure the quality of service of microservice systems. Typical anomaly detection methods are effective in data quality and computing reliability of cloud computing. However, they all focus on one-class anomaly detection, which may not perform on practical microservice frameworks with diverse types of anomalies. Furthermore, locating the root cause of anomalies to eliminate after detection is essential. To address these issues, we propose an effective parallel convolutional anomaly multi-classification model (PCAC) based on an attention mechanism for fault diagnosis in microservice system. We first construct a parallel convolutional structure that allows subnetworks to extract features independently. Then, channel and spatial attention mechanisms are applied in the parallel convolutional layers to mitigate the loss of feature representation. Finally, causal inference based on the anomalous graph is used to locate the fault in the microservice system. The experimental results clearly show that the proposed model achieves the highest F1 scores on six public microservice datasets, improved by 37.9% in average macro-F1 and 4.4% in average micro-F1 scores respectively, outperforming eight state-of-the-art methods. [ABSTRACT FROM AUTHOR]

In recent years, urban road collapse incidents have been occurring with increasing frequency, particularly in populous cities. To mitigate road collapses, geophysical prospecting plays a crucial role in urban road inspections. Ground Penetrating Radar (GPR), a non-destructive technology, is extensively employed for detecting urban road damage, with manual interpretation of GPR images typically used to identify buried objects. Nonetheless, manual interpretation methods are not only inefficient but also subjective, as they rely on the interpreter's experience, thereby affecting the interpreting reliability. This study investigates the distribution and causes of road collapses and develops a deep learning-based intelligent recognition model using GPR detection images of urban roads in cities of the South China as original samples. The finding reveal that road collapses are concentrated in the months of July and August, mainly caused by pipe leakage and rainfall. Common anomalies in urban road GPR detection comprise seven types of target objects, including cavity, pipeline, etc., with standard GPR images acquired through outdoor field experiments. Utilizing GPR forward simulation and image augmentation methods to expand the sample size, as well as generating anchor box dimensions through clustering analysis, have all been proven to effectively improve the model's performance. The urban road GPR image intelligent recognition model, based on the YOLOv4 algorithm, achieves a detection accuracy of up to 85%, proving effective in GPR detection of urban roads in cities of North China. This research offers valuable insights for the future application of deep learning-based image recognition algorithms in urban road GPR detection. [ABSTRACT FROM AUTHOR]

The JUpiter ICy moons Explorer (JUICE) of ESA was launched on 14 April 2023 and will arrive at Jupiter and its moons in July 2031. In this review article, we describe how JUICE will investigate the interior of the three icy Galilean moons, Ganymede, Callisto and Europa, during its Jupiter orbital tour and the final orbital phase around Ganymede. Detailed geophysical observations about the interior of the moons can only be performed from close distances to the moons, and best estimates of signatures of the interior, such as an induced magnetic field, tides and rotation variations, and radar reflections, will be obtained during flybys of the moons with altitudes of about 1000 km or less and during the Ganymede orbital phase at an average altitude of 490 km. The 9-month long orbital phase around Ganymede, the first of its kind around another moon than our Moon, will allow an unprecedented and detailed insight into the moon's interior, from the central regions where a magnetic field is generated to the internal ocean and outer ice shell. Multiple flybys of Callisto will clarify the differences in evolution compared to Ganymede and will provide key constraints on the origin and evolution of the Jupiter system. JUICE will visit Europa only during two close flybys and the geophysical investigations will focus on selected areas of the ice shell. A prime goal of JUICE is the characterisation of the ice shell and ocean of the Galilean moons, and we here specifically emphasise the synergistic aspects of the different geophysical investigations, showing how different instruments will work together to probe the hydrosphere. We also describe how synergies between JUICE instruments will contribute to the assessment of the deep interior of the moons, their internal differentiation, dynamics and evolution. In situ measurements and remote sensing observations will support the geophysical instruments to achieve these goals, but will also, together with subsurface radar sounding, provide information about tectonics, potential plumes, and the composition of the surface, which will help understanding the composition of the interior, the structure of the ice shell, and exchange processes between ocean, ice and surface. Accurate tracking of the JUICE spacecraft all along the mission will strongly improve our knowledge of the changing orbital motions of the moons and will provide additional insight into the dissipative processes in the Jupiter system. Finally, we present an overview of how the geophysical investigations will be performed and describe the operational synergies and challenges. [ABSTRACT FROM AUTHOR]

The site of LuneryRosieres la-Terre-des-Sablons (Lunery, Cher, France) comprises early evidence of human occupation in mid-latitudes in Western Europe. It demonstrates hominin presence in the Loire River Basin during the Early Pleistocene at the transition between an interglacial stage and the beginning of the following glacial stage. Three archaeological levels sandwiched and associated with two diamicton levels deposited on the downcutting river floor indicate repeated temporary occupations. Lithic material yields evidence of simple and more complex core technologies on local Jurassic siliceous rocks and Oligocene millstone. Hominins availed of natural stone morphologies to produce flakes with limited preparation. Some cores show centripetal management and a partially prepared striking platform. The mean ESR age of 1175 ka ± 98 ka obtained on fluvial sediments overlying the archaeological levels could correspond to the transition between marine isotopic stages (MIS) 37 and 36, during the normal Cobb Mountain subchron, and in particular at the beginning of MIS 36. The Lunery site shows that hominins were capable of adapting to early glacial environmental conditions and adopting appropriate strategies for settling in mid-latitude zones. These areas cannot be considered as inhospitable at that time as Lunery lies at some distance from the forming ice cap. [ABSTRACT FROM AUTHOR]

The quality of asphalt pavement (HMA) is often assessed by its dielectric permittivity, e.g., using ground-penetrating radar technology. The mostly employed relationships were developed for dry HMA pavement as follows: Complex Refractive Index Model (CRIM), Bottcher, Rayleigh, and Al-Qadi–Lahouar–Leng models (so-called ALL model), while the relationships for the estimation of wet HMA properties are empiric and not consistent with those for dry HMA mixtures. The article presents the results of the development and analysis of novel relationships between the values of dielectric permittivity and the mechanical characteristics of wet asphalt. It is shown that the new relationships are the general consistent cases of the expressions previously developed for dry HMA. The new expressions for the Rayleigh and ALL models are shown providing close estimates for the value of moisture content in the range of porosity and degree of water saturation: 0–0.12 and 0–1, respectively, and in the wide range of aggregate specific gravity (2.5–2.9), the binder content (0.04–0.08), the dielectric permittivity of aggregate (6–11), and the maximum specific gravity (2.5–2.9). Since the ALL model is an implicit function, in which the dielectric permittivity variable cannot be extracted, the direct problem (to calculate the dielectric constant value from density/specific gravity and porosity value) can be solved numerically while the inverse problem can be solved algebraically. The newly developed expression for the Rayleigh model (for wet asphalt) can be used for the estimation of dielectric permittivity based on expected values of porosity and density, and vice versa, and hence it is simpler for using. [ABSTRACT FROM AUTHOR]

This study aims to develop a damage-detection algorithm based on the electromagnetic wave properties inside a reinforced concrete structure. The proposed method involves employing two algorithms based on data measured using ground-penetrating radar—a common electromagnetic wave method in civil engineering. The possible defect area was identified based on the energy dissipated by the damage in the frequency-wavenumber domain, with the damage localized using the calculated relative permittivity of the measurements. The proposed method was verified through a finite difference time-domain-based numerical analysis and a testing slab with artificial damage. As a result of verification, the proposed method quickly identified the presence of damage inside the concrete, especially for honeycomb-like defects located at the top of the rebar. This study has practical significance in scanning structures over a large area more quickly than other non-destructive testing methods, such as ultrasonic methods. [ABSTRACT FROM AUTHOR]

It is unclear how high concentrations of copper affect the structure and function of roots in the process of controlling root entanglement in containers although copper pruning technology has been widely applied. One-year-old glossy privet (Ligustrum lucidum) seedlings were treated with latex carrier (T1), 100 g L− 1 Cu(OH)2 in combination with latex (T2), and a control (T0) without latex and Cu(OH)2. The roots were classified into seven classes according to diameter and six root orders by branching order. There were 6 root orders under the T2, one more than that under the T1 and T0. The length sum of the first to fourth root orders under the T2 was 52.4% and 132.0% higher than that under the T1 and T0. The T1 treatment significantly increased the length of the finest roots less than 0.50 mm in diameter, especially the roots less than 0.25 mm in diameter. No root circling was observed under the T2 treatment where the length of the tap root decreased and root volume increased. The T2 treatment significantly improved the plant height (+ 62.2% and + 24.1%), maximum net photosynthetic rate (+ 70.5% and + 63.8%), leaf area (+ 4.10% and + 37.6%), and total leaf number (+ 143.0% and + 66.9%) compared to the T0 and the T1. Latex treatment enhanced the growth of the lateral roots by increasing humidity and temperature in the containers but could not control root circling, whose improvement mechanism was different from that of copper. [ABSTRACT FROM AUTHOR]

The need for reconstruction of the distribution of physical properties like dielectric permittivity and electrical conductivity of shallow subsurface sedimentary architecture leads to the development of an optimum strategy of GPR data inversion. In this paper, we present finite difference frequency domain (FDFD) full waveform inversion (FWI) method to get high-resolution subsurface model using GPR data. FWI is an optimization technique which involves in search of the minima between recorded and predicted data. The inversion process includes the quasi-Newton method and simultaneous frequency sampling strategy of irregular sampling. The Hessian term in quasi-Newton algorithm is approximated using preconditioned-LBFGS consideration and the search directions are also optimized after following the Wolfe conditions. At the end of each iteration during inversion, permittivity and conductivity models were updated and became ready to be the initial model for the next iteration. The goals of this research were to develop a robust framework for sedimentary-GPR data inversion and to evaluate the efficacy of the novel grid strategy introduced by Layek and Sengupta (2021) proposed for FWI. This paper presents a comparative analysis between conventional and newly proposed technique from Layek and Sengupta (2021), supported by numerical experiments conducted through our own MATLAB programming. Numerical tests conducted on a benchmark from previously published article, established the fact that new grid formulation produces a faster converging rate and required less computation time. This approach demonstrates remarkable efficacy when applied to a comprehensive sedimentary model comprising a lossy medium. [ABSTRACT FROM AUTHOR]

In this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model have been used. The task is to independently predict characteristic parameters of a buried object of diverse radii allocated at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable data structures (raw B-scans, extracted features, consecutive A-scans) with respect to computational cost and accuracy of surrogates. The usage of raw B-scan data and the applications for processing steps on B-scan profiles in the context of object characterization incur high computational cost so it can be a challenging issue. The proposed surrogate model referred to as the deep regression network (DRN) is utilized for time frequency spectrogram (TFS) of consecutive A-scans. DRN is developed with the main aim being computationally efficient (about 13 times acceleration) compared to conventional network models using B-scan images (2D data). DRN with TFS is favorably benchmarked to the state-of-the-art regression techniques. The experimental results obtained for the proposed model and second-best model, CNN-1D show mean absolute and relative error rates of 3.6 mm, 11.8 mm and 4.7%, 11.6% respectively. For the sake of supplementary verification under realistic scenarios, it is also applied for scenarios involving noisy data. Furthermore, the proposed surrogate modeling approach is validated using measurement data, which is indicative of suitability of the approach to handle physical measurements as data sources. [ABSTRACT FROM AUTHOR]

The occurrence of subsurface karst caves can cause the development of superficial depressions which, in turn, may pose a construction hazard. Identifying such a substratum requires integrated non-invasive measurement methods. The main objective of the study was to demonstrate the effectiveness of the non-invasive ERT, TLS, and GPR survey techniques in identifying the karst floor and determining the direction of discontinuities around the cave. The paper analyzes the limitations of the methods used in the study of heterogeneous media. These limitations are related to the methodology and measurement conditions, data processing, and interpretation in the context of the resolution and depth range. The study was conducted using the example of the Jaskinia pod Świecami cave, formed in the Sarmatianal calcarenites in Poland. The research confirmed its complex karst-anthropogenic genesis. The cave was formed as a result of the infiltration of rainwater and the dissolution of limestone by groundwater, while the paleokarst forms that are characteristic of it and of the surrounding caves and occur in their vicinity, i.e., narrow ridges called "karst candles", were formed as a result of water circulation during the local permafrost degradation in the middle Pleistocene. However, these forms were modified in the Upper Pleistocene and Holocene, as indicated by ERT images. [ABSTRACT FROM AUTHOR]

Purpose: The land-lake interface is a unique zone where terrestrial and aquatic ecosystems meet, forming part of the Earth's most geochemically and biologically active zones. The unique characteristics of this interface are yet to be properly understood due to the inherently high spatiotemporal variability of subsurface properties, which are difficult to capture with the traditional soil sampling methods. Geophysical methods offer non-invasive techniques to capture variabilities in soil properties at a high resolution across various spatiotemporal scales. Methods: We combined electromagnetic induction (EMI), electrical resistivity tomography (ERT), and ground penetrating radar (GPR) with data from soil cores and in situ sensors to investigate hydrostratigraphic heterogeneities across land-lake interfaces along the western basin of Lake Erie. Results: EMI revealed high spatial heterogeneities in ECa distribution across the land-lake interfaces, with higher values in the wetland and transition zones compared to the upland zone. Soil ECa maps matched soil maps from a public database with the hydric soil units delineated as high conductivity zones (ECa > 40 mS/m). ERT and GPR showed vertical variation in soil properties with clear stratigraphic boundaries, and correlation of ERT profiles with lithologs from piezometers revealed the stratigraphic units of silt–clay and till sequence down to 3.5 m depth which are consistent with the surficial geology of the study area. Conclusions: These results validate the use of multiple geophysical methods for extrapolating soil properties and mapping stratigraphic structures at land-lake interfaces, thereby providing the missing information required to improve the earth system model (ESM) of coastal interfaces. [ABSTRACT FROM AUTHOR]

Detecting and determining the development of the frozen wall is a vital component of artificial freezing engineering. The electromagnetic parameters of frozen soil play a critical role in the fast and accurate identification using high-frequency electromagnetic waves. This study investigated the impacts of various factors on the dielectric properties of artificial frozen soil through laboratory experiments. The dielectric properties and evolutionary characteristics of sand were measured under different conditions, including temperature, probing frequency, initial moisture content, and salt content. The experimental results obtained characteristic curves of the relative dielectric constant of frozen sand in the frequency range of 300–2000 MHz under various conditions. Quantitative analysis was conducted to examine the differences in the dielectric properties of frozen sand. The analysis indicated that, under low-temperature and salt-free conditions, a reflection coefficient above 0.464 can be utilized to identify frozen/unfrozen sand. Furthermore, ground penetrating radar (GPR) is capable of effectively detecting and differentiating between salt-containing unfrozen soil and frozen soil. This study provides a solid theoretical framework for the quantitative identification of freezing front and frozen wall development. Additionally, the research findings have substantial theoretical implications for defect detection in frozen walls and the quantitative inversion of temperature fields in frozen soil. [ABSTRACT FROM AUTHOR]

This paper presents the current state of conservation of historic roof churches located in the Żuławy of Gdańsk (Poland). It also describes the architecture of these temples, the region itself and old carpentry techniques for constructing roof trusses. Interdisciplinary tests were carried out in six churches. The geometry of the load bearing structures, the moisture content and the carpentry technique were specified. The field survey also included visual inspections and non-destructive testing of timber structural elements of the roof constructions. The ground penetrating radar and ultrasonic testing methods were used to assess the structure and extent of the damage to the timber elements. The interdisciplinary research presented in this article is important in the planning of historic buildings conservation works and it might be applied to other timber structures. [ABSTRACT FROM AUTHOR]

Ground penetrating radar (GPR) systems are effective sensors for discovering various types of objects buried underground, such as military mines, metal objects, and pieces of underground infrastructures. A GPR system can be manually operated by a human or can be an integral part of a host platform. The host platform may be semi- or fully autonomous and may operate in different environments such as land vehicles or more recently air-borne drones. One challenge for the fully or semi-autonomous host platforms in particular is to find an efficient search procedure that would reduce the operation time and optimize resource utilization. Most of the current approaches are based on pre-defined search patterns which, for large and sparse areas, could mean unnecessary waste of time and resources. In this paper, we introduce a method that combines a coarse and therefore relatively low cost initial search pattern with a Reinforcement Learning (RL) driven efficient navigation path for eventual target detection, by exploiting the signal processing pipeline of the onboard GPR. We illustrate the applicability of the method using a well-known, high fidelity GPR simulation environment and a novel RL framework. Our results suggest that combination of a coarse navigation scheme and an RL-based training procedure based on GPR scan returns can lead to a more efficient target discovery procedure for host platforms. [ABSTRACT FROM AUTHOR]

Since 2021, a new surge in discrete aurora detections at Mars has been observed by the Emirates Mars Ultraviolet Spectrometer (EMUS) onboard the Emirates Mars Mission (EMM) Hope Orbiter as EMUS started to regularly obtain synoptic auroral images with a high sensitivity. Here we report on a fortuitous conjunction between EMM and Mars Express (MEX) using far ultraviolet (FUV) imaging of discrete aurora by EMM EMUS, in situ measurements of suprathermal electrons by the MEX Analyzer of Space Plasma and Energetic Atoms Electron Spectrometer (ELS), and topside radar sounding of the nightside ionosphere by the MEX Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS). In this event, EMM EMUS imaged a clear discrete aurora signature around moderately strong crustal magnetic fields on the nightside near the dusk terminator, 11 min before which MEX MARSIS measured a prominent local enhancement of the peak electron density in the nightside ionosphere and MEX ELS observed an in situ enhancement of suprathermal electrons at the corresponding location. A remarkable geographic agreement is found between the enhancements of the aurora, ionosphere, and suprathermal electrons, suggesting that the enhanced ionization and auroral emission are caused concurrently by precipitating suprathermal electrons. Subsequent images indicate that the discrete aurora slightly changed its shape in 15 min and mostly disappeared in a few hours. The MEX MARSIS measurements of the auroral ionosphere display overlapping ionospheric and surface echoes indicative of horizontal gradients of the peak electron density. Analysis of the overlapping echoes implies that the auroral ionosphere and electron precipitation could be highly structured with horizontal spatial scales on the order of several tens of km. MEX MARSIS also observed a non-auroral ionospheric enhancement with a wider spatial extent than the local auroral enhancement, suggesting alternative sources of the enhanced nightside ionosphere such as plasma transport. The comparison between the ionospheric structures measured by MEX MARSIS, suprathermal electron flux measured by MEX ELS, and discrete auroral emission imaged by EMM EMUS underscores the complexity of the auroral and non-auroral nightside ionospheres. This motivates further investigations of their sources, transport, and connections to the magnetotail dynamics of Mars. [ABSTRACT FROM AUTHOR]

Timely and accurate detection and identification of cavities under urban roads is the key to road safety. Due to the inability to obtain accurate migration velocity and the difficulty of achieving complete convergence of diffraction signals of the cavity disease, traditional migration methods struggle to accurately identify and locate the subgrade cavity. This paper proposes a GPR image migration processing (TUFK method) based on 2D undecimated wavelet transform and the F–K method in accordance with the high-precision imaging of the subgrade cavity. The finite-difference forward models of subgrade cavity without and with noise are established, and the model test of cavity detection by GPR is carried out in the laboratory. Through the fine extraction and migration processing of the weak diffraction signals from the cavity, the optimal velocity required for migration is analyzed, and the TUFK method is applied to the migration process of GPR data acquired for the purpose of cavity detection. Furthermore, the proposed method is applied to the processing of GPR data acquired in the field with a cavity below the roadbed. The results show that the TUFK method can accurately extract the diffraction signals from the cavity and achieve the fine convergence of cavity diffraction signals whether in noiseless or noisy environments. Compared with the traditional Kirchhoff and F–K migration methods, this method can effectively obtain accurate migration velocity and the migration results can reflect the actual position and shape of the cavity. This study can provide a new idea and effective method for the imaging of subgrade cavity. [ABSTRACT FROM AUTHOR]

The Florida Everglades are a vast subtropical wetland that historically spanned over 1,000,000 hectares, but much of the Everglades has changed in the last 100 years due to anthropogenic activity. Collier County, situated in southwest FL and bordering the Gulf of Mexico, was subject to alteration in the form of logging, road building, and canal digging. These actions disrupted the natural sheet flow of water and had large environmental impacts on the region, impacts which are slowly being addressed by Everglades restoration efforts. The aim of this work was to observe environmental change at a cypress swamp forest in Collier County within the Big Cypress National Preserve. Using sediment core data including charcoal analysis, loss on ignition, and peat humification, as well as remote sensing techniques, this project uses a novel approach to assess local environmental conditions in the modern era for the region. While this analysis was based on a single core located at the study site, additional ground-penetrating radar profiles at the study site showed a consistent, laterally continuous distribution of subsurface interfaces, therefore suggesting that the core is representative of the conditions at this specific location. Historical records and contemporary data are used to evaluate environmental change over time, and satellite imagery is used to quantify vegetation health. Environmental change related to anthropogenic activity is noted, and evidence of progress from restoration efforts is observed from the last two decades in our study's data. [ABSTRACT FROM AUTHOR]

The use of geophysical techniques can contribute considerably to the advancement and optimization of subsurface surveys, due to the low costs and time effectiveness. Ground penetrating radar (GPR) has great potential to rapidly and non-invasively evaluate soil in sites affected by the Fundão dam collapse, Southeastern Brazil. The objective of this work was to investigate the thickness of the iron ore tailing layer deposited in a stretch of the Gualaxo do Norte River, besides identifying the most efficient electromagnetic frequency for analysis of this type of material. Three antennas (200, 400 and 900 MHz) were used for GPR surveys in three transects. The radargrams were processed with filtering and gain techniques, aiming to improve the signal quality. We could detect three ground reflection zones with different electromagnetic properties, representing, sequentially, the topsoil, the tailing layer, and the C horizon of the original soil, separated by two reflectors representing the boundaries layers. The tailing layer presented an average thickness of approximately 1 m. 200 MHz presented the best results, whose signal reached the greatest penetration depth and detected the entire tailing layer thickness, besides the others layers present. Using field control points, we could observe that the depths obtained with radargrams had 93% of concordance with the actual depths, which is very satisfactory. The results indicate that the 200 MHz antenna is a better option in surveys involving stratification on Technosols constituted by tailings and GPR should be more explored in the evaluation of soil and sediments. [ABSTRACT FROM AUTHOR]

This communication uses Matlab Simulink to present an end-to-end model of a continuous-wave ground penetrating radar. The modelling of a radar system, the target and its location, and the soil environment with related incident signal attenuation and reflection are all included in this model. By maintaining the target at a variable depth, isolation between the antennas, soil composition, and target simulations are performed for a selected operating frequency. The simulation results are verified by conducting experiments with a prototype ground-penetrating radar. Experiments involving two distinct target sizes maintained at varying depths in two different types of soil have been carried out for validation, and the outcomes of the simulations have been compared. This validation demonstrates that the proposed model closely approximates the physical design. The proposed model demonstrates how the number of design and development iterations and time needed to physically realize a continuous wave ground-penetrating radar can be decreased. [ABSTRACT FROM AUTHOR]

Star dunes are the tallest dunes on Earth and are amongst the larger and more spectacular aeolian landforms. Although they are widespread in modern sandy deserts, star dunes are rarely recognised in the rock record probably due to a lack of suitable sedimentary models. This paper presents a new sedimentary model for the structure of a star dune at Erg Chebbi in Morocco (Sahara Desert) on the basis of ground-penetrating radar (GPR) surveys. Individual sedimentary structures in star dunes are similar to those in linear or barchanoid dunes, likely leading to misidentification in the rock record. However, the suite of features described in this paper will permit identification of star dunes in future studies of the rock record. Optically stimulated luminescence (OSL) dating shows that accumulation of the Erg Chebbi star dune post-dates the end of the African Humid Period (AHP). At the base of the dune, there is an ~ 8000-year hiatus in the record. Since then, the dune has grown rapidly to create a 100 m high dune within the past 1000 years and is migrating towards the west. Changes in the cross-strata support the idea that star dune construction was accompanied by a change in the wind directions. [ABSTRACT FROM AUTHOR]

Training samples for deep learning networks are typically obtained through various field experiments, which require significant manpower, resource and time consumption. However, it is possible to utilize simulated data to augment the training samples. In this paper, by comparing the actual experimental model with the simulated model generated by the gprMax [1] forward simulation method, the feasibility of obtaining simulated samples through gprMax simulation is validated. Subsequently, the samples generated by gprMax forward simulation are used for training the network to detect objects in existing real samples. At the same time, aiming at the detection and intelligent recognition of road sub-surface defects, the Swin-YOLOX algorithm is introduced, and the excellence of the detection network, which is improved by augmenting the simulated samples with real samples, is further verified. By comparing the prediction performance of the object detection models, it is observed that the model trained with mixed samples achieved a recall of 94.74% and a mean average precision (mAP) of 97.71%, surpassing the model trained only on real samples by 12.95% and 15.64%, respectively. The feasibility and excellence of training the model with mixed samples are confirmed. The potential of using a fusion of simulated and existing real samples instead of repeatedly acquiring new real samples by field experiment is demonstrated by this study, thereby improving detection efficiency, saving resources, and providing a new approach to the problem of multiple interpretations in ground penetrating radar (GPR) data. [ABSTRACT FROM AUTHOR]

Ultrasonic time-of-flight diffraction (TOFD) technique is a means of defect detection adopting the diffracted longitudinal waves from flaw tips. However, the dead zone is induced by the coupling between tip-diffracted longitudinal wave and lateral wave or longitudinal back-wall wave. In this paper, the methods for reducing dead zone are reviewed from parameter optimization, alternative TOFD techniques and signal processing techniques. The principles, effects and influencing factors of different methods are analyzed and compared in sequence. Finally, the future challenges focus on the multiple overlapped signals (N ≥ 3) from shallow subsurface defects in thin plates and the change of dead zone induced by irregular structure. [ABSTRACT FROM AUTHOR]

The generation and use of 3D images and visualizations through remote sensing, Building Information Modeling, and Augmented Reality technologies, have come to play a significant role in construction engineering practice. Although these technologies are promising, their potential can be misjudged when potential end-users are unaware of key assumptions that were made by developers. Realistic expectations require insights into the ways in which these technologies transform input collected into 3D visualizations and how these visualizations are possibly used on construction sites. This study's objective is hence to explore the form of technological mediation that the generation and use of 3D images and visualizations provide between a human and objects, or aspects of these objects, that would otherwise be largely imperceptible to professionals in construction practice. We show that algorithms pre- and post-process data through their technological selectivities, which function as mediators. Double mediations of augmented and engaged relationships play a dominant role in the use of 3D images and visualizations and enhance the situational awareness of professionals in construction practice. This is the first study that applies this perspective to increase the understanding of the mediating role of 3D images and visualizations in construction practice. [ABSTRACT FROM AUTHOR]

The electrical resistivity, i.e. electrical resistivity tomography (ERT) and direct current-resistivity sounding (DC-ERS), and ground penetrating radar (GPR) methods were deployed to assess a gully erosion site in Bacoco area of Calabar, Nigeria. The study aims to assess the mechanism and dynamics of the gully erosion conditions in the area based on shallow lithostratigraphic evaluations. The results revealed good contrast in the operative properties (i.e. electrical resistivity and dielectric permittivity) between competent and weak zones along the profiles close to the gully head. The joint interpretations provided reliable shallow subsurface models and lithologies that consist predominantly of lateritic top cover and sands. However, the ERT model delineates the contrast between lithologies and demarcates the weak zones from the relatively competent zones, in contrast to the responses generated by the GPR technique. This joint interpretation approach minimizes the uncertainty due to the non-uniqueness problems common to the geophysical technique. Also, the geophysical interpretations were constrained using lithologic information from the gully walls and one-dimensional (1-D) DC-ERS inverted model to provide additional validity. Our findings suggest the influence of structural control on gully formation and demonstrate its contribution to the complex interactions with other drivers, such as seepages through porous media and high-energy runoff due to intense rainfall. The rapid, non-invasive and environmentally friendly characteristics of ERT and GPR techniques favour their applicability in assessing shallow subsurface environmental problems. [ABSTRACT FROM AUTHOR]

This study presents a novel method for optimizing parameters in urban flood models, aiming to address the tedious and complex issues associated with parameter optimization. First, a coupled one-dimensional pipe network runoff model and a two-dimensional surface runoff model were integrated to construct an interpretable urban flood model. Next, a principle for dividing urban hydrological response units was introduced, incorporating surface attribute features. The K-means algorithm was used to explore the clustering patterns of the uncertain parameters in the model, and an artificial neural network (ANN) was employed to identify the sensitive parameters. Finally, a genetic algorithm (GA) was used to calibrate the parameter thresholds of the sub-catchment units in different urban land-use zones within the flood model. The results demonstrate that the parameter optimization method based on K-means-ANN-GA achieved an average Nash-Sutcliffe efficiency coefficient (NSE) of 0.81. Compared to the ANN-GA and K-means-deep neural networks (DNN) methods, the proposed method better characterizes the runoff generation and flow processes. This study demonstrates the significant potential of combining machine learning techniques with physical knowledge in parameter optimization research for flood models. [ABSTRACT FROM AUTHOR]

Chinese lunar landing mission Chang'E-4 reached the far side of the Moon in January 2019 and has been providing unprecedented Lunar Penetrating Radar data able to explore the lunar subsurface down to more than 40 m (with its more resolutive high frequency band). Data are periodically released to the scientific community in raw PDS4 format. Here we provide different versions of the radar dataset after editing (i.e. pre-processing), partial, and full processing in order to provide a complete ready-to-use dataset to end-users (data collected since 4th January 2019 until 27th March 2023) which can be directly exploited for analysis, interpretation, inversion, as well as integration with imagery or other information. In particular, we implemented an efficient and objective way to remove duplicated traces representing more than 90% of original data, as well as a processing flow able to retain all the original data information, while avoiding redundancies. The provided datasets can be implemented with future data releases and straightforwardly exploited for any future analysis. [ABSTRACT FROM AUTHOR]

Recently, global urbanization and industrialization have resulted in excessive groundwater exploitation, and the occurrence and damage of land subsidence to human life and property are increasing accordingly. The present study assessed the impact of tunnel excavation on the groundwater system and potential land subsidence in a Korean metropolitan area. A numerical model was established to predict groundwater level variations with tunnel excavation, and the mechanisms and cases of land subsidence worldwide were reviewed. The established model adequately represented the groundwater system in the study area. The tunnel excavation decreased the groundwater level along the tunnel line, and significant groundwater drawdown primarily occurred up to 6.1 m at locations with high permeability, leading to the temporary development of a large depression cone. The study area has favorable conditions for land subsidence, and curved tunnel excavation may induce ground disturbance, resulting in groundwater inflow and soil loss in the region. In addition, the risk of land subsidence is expected to persist owing to the lag time caused by the creep phenomenon, even though the groundwater level recovers. Efforts to effectively reduce land subsidence damage in urban areas are crucial, requiring measures such as controlling land subsidence occurrence and implementing prevention measures through early recognition, including artificial recharge of groundwater, underground cavity observation with ground penetrating radar, land subsidence observation with a borehole extensometer, and groundwater level monitoring systems. [ABSTRACT FROM AUTHOR]

Rock blasting and other geological disasters occur frequently in the TBM construction of deeply buried tunnels and seriously threaten construction safety and progress. Therefore, it is extremely important to conduct scientific research for effective prevention and control of rockbursts in construction. Based on a large number of field rockburst data, this study analyses the influence of rockburst on construction safety and efficiency by using statistical theory and summarizes the temporal and spatial characteristics of rockburst time, location and influence range. Using these results, combined with the characteristics of the TBM structure and construction method, classification prevention and control objectives, theoretical criteria and prevention and control technology of rock bursts are proposed. A theoretical system of classified prevention and control of rockburst is constructed, which is cooperatively controlled by microseismic monitoring, TBM equipment, TBM excavation and support measures. The system is verified to provide practical protection, demonstrating that this report provides an important reference for the prevention and control of rock bursts in ultradeep tunnels. [ABSTRACT FROM AUTHOR]

To effectively delineate the spatial distribution of oil contaminant plumes, geophysical methods indirectly measure the physical properties of the subsurface and can provide spatial information and images on a large scale, as opposed to traditional direct methods such as borehole drilling, sampling, and chemical analysis, which are time-consuming and costly. However, interpreting geophysical responses over non-aqueous phase liquid (NAPL)–contaminated sites is not straightforward due to inconsistent responses from biodegraded oil contaminants. In this study, we performed multi-geophysical surveys including seismic refraction, ground-penetrating radar, electrical resistivity tomography (ERT), and induced polarization (IP) surveys, to locate NAPL-contaminated zones in a clay-rich site. To reduce ambiguity in discriminating between oil contaminants and clay layers, we first figure out the geological structure of the site by interpreting geophysical data incorporating with borehole data. The ERT data highlighted the heavily contaminated regions in the unsaturated zone but were less distinctive below groundwater levels. Conversely, IP responses revealed potential hotspots within the clay layers, extending beneath the groundwater. Considering the 3D geological model, NAPL-contaminated zones are properly delineated through interpretation of ERT and IP data together with borehole data, and the contaminant source zone was properly estimated within the site. [ABSTRACT FROM AUTHOR]

A geophysical Bayesian inversion problem may target the posterior distribution of geological or hydrogeological parameters given geophysical data. To account for the scatter in the petrophysical relationship linking the target parameters to the geophysical properties, this study treats the intermediate geophysical properties as latent (unobservable) variables. To perform inversion in such a latent variable model, the intractable likelihood function of the (hydro)geological parameters given the geophysical data needs to be estimated. This can be achieved by approximation with a Gaussian probability density function based on local linearization of the geophysical forward operator, thereby, accounting for the noise in the petrophysical relationship by a corresponding addition to the data covariance matrix. The new approximate method is compared against the general correlated pseudo-marginal method, which estimates the likelihood by Monte Carlo averaging over samples of the latent variable. First, the performances of the two methods are tested on a synthetic test example, in which a multivariate Gaussian porosity field is inferred using crosshole ground-penetrating radar first-arrival travel times. For this example with rather small petrophysical uncertainty, the two methods provide near-identical estimates, while an inversion that ignores petrophysical uncertainty leads to biased estimates. The results of a sensitivity analysis are then used to suggest that the linearized Gaussian approach, while attractive due to its relative computational speed, suffers from a decreasing accuracy with increasing scatter in the petrophysical relationship. The computationally more expensive correlated pseudo-marginal method performs very well even for settings with high petrophysical uncertainty. [ABSTRACT FROM AUTHOR]

New approaches to studying and monitoring of on palsa mires the Kola Peninsula are considered. Because of the observed signs of permafrost degradation in frost heave mounds (palsa), such objects can serve as markers of significant climate anomalies and shifts taking place in the Arctic zone. The analysis of the occurrence of palsa mires on the Kola Peninsula showed the existence of four separate morphometric and climatic clusters. The obtained results demonstrated the potential of a set of methods for determining the dynamics of permafrost in the palsa and for monitoring the related transformation of the mire ecosystem. [ABSTRACT FROM AUTHOR]

Benchmarking the amplitudes of ground penetrating radar (GPR) signals has received little attention in the past, likely because different research groups have used their own GPR data acquired for different projects individually. To facilitate the integration of GPR data for machine learning and change detection through building a functional fingerprinting database, the amplitude attributes must be harmonized across different systems. This would make GPR more useful as an evaluation tool for material states in civil engineering applications. A simple and straightforward method using a metal plate reflector is proposed to convert the amplitudes between different instruments. The method was successful in concrete diagnosis with machine learning. Future work will consider more variables, such as concrete with different rebar diameters at different depths, and fuse multi-frequency data to expedite machine learning. [ABSTRACT FROM AUTHOR]

The Ground Penetrating Radar method is used to study a three-layered model of the surrounding rock–void–lining interface with regard to variation in the void thickness and in the electromagnetic properties of the void filler. The numerical modeling uses the method of finite differences in the time domain. The numerical modeling data are compared with the results of the physical simulation implemented using SIR-3000 GPR with the Model 52600 antenna having the working frequency of 2.6 GHz (S-band). It is found that the size of the void behind concrete lining and the electromagnetic properties of a material filling the void have influence on the accuracy of ranging to the lower boundary of the void and to the discontinuity in the form of a steel bolt located immediately behind the void in surrounding rock mass. [ABSTRACT FROM AUTHOR]

Ground Penetrating Radar (GPR) is one of the most used devices for road structural damages detection. However, due to the different roadbed conditions and various disturbances in the nearby environment during detection, there are great difficulties in interpreting detection images, which also hinders automatic detection based on deep learning. In this work, we design a GPR image denoising method based on Cyclegan. We select the most suitable generator and add different attention mechanisms. After denoising the natural GPR road detection image, using the Yolo (You Only Look Once) to test the accuracy of the original image and the denoised image after adding different attention mechanisms. The detection accuracy is improved by 30%. The results of the detection network and the evaluation of the denoised images by GPR image interpreters indicate that the method has the following advantages: lower requirements for training data sets, a wide range of data sources, low cost, good denoising effect, and automatic detection of GPR images. It is of great help to the automatic detection of GPR images. [ABSTRACT FROM AUTHOR]

The dimension of the void area in pavement is crucial to its structural safety. However, there is no effective method to measure its geometric parameters. To address this issue, a void size extraction algorithm based on the continuous wavelet transform (CWT) method was proposed using ground-penetrating radar (GPR) signal. Firstly, the finite-difference time-domain (FDTD) method was used to investigate the GPR response of void areas with different shapes, sizes, and depths. Next, the GPR signal was processed using the CWT method, and a 3D image based on the CWT result was used to visualize the void area. Based on the differences between the void and normal pavement in the time and frequency domains, the signal with maximum energy from the CWT time–frequency result was extracted and combined to reconstruct the new B-scan image, where void areas have energy concentration phenomenon. Based on this, width and depth of void detection algorithm was proposed to recognize the void area. Finally, the detection algorithm was verified both in numerical model and physical lab model. The results indicated that the CWT time–frequency energy spectrum can be used to enhance the void feature, and the 3D CWT image can clearly visualize the void area with a highlighted energy area. After fully testing and validating in numerical and lab models, our proposed method achieved high accuracy in void width and depth detection, providing a precise method for estimating void dimension in pavement. This method can guide DOT departments to carry out pre-maintenance, thereby ensuring pavement safety. [ABSTRACT FROM AUTHOR]

The epikarst together with its soil stocks (subcutaneous structure) are crucial to the fact that they may contribute to the canopy growth and can significantly influence the ecological restoration and organic carbon sequestration. Geophysical techniques especially, the ground penetrating radar (GPR) are advantageous for such investigations. However, the complicated karst environment due to numerous influencing factors (i.e., the forest, epikarst slope, peak-cluster depression, soil humidity, high voltage power lines) can significantly influence the exploration with GPR. In the past, such applications were limited to local scales without considering the aforementioned factors together. Hence, the present study analyses the influences of these factors on the performance and reliability of GPR results considering the central Guizhou plateau of south-west China as a case study. These site-specific findings are summarized into a GPR application potential zonation map at the catchment scale. The zones were rated as low, moderate and high potential degree regions, each reflecting results reliability which can be considered as a cost-effective feasibility reference for the future GPR applications in complex karst terrain characterization, as well as the areas having similar karstic conditions. [ABSTRACT FROM AUTHOR]

The production of crops secure the human food supply, but climate change is bringing new challenges. Dynamic plant growth and corresponding environmental data are required to uncover phenotypic crop responses to the changing environment. There are many datasets on above-ground organs of crops, but roots and the surrounding soil are rarely the subject of longer term studies. Here, we present what we believe to be the first comprehensive collection of root and soil data, obtained at two minirhizotron facilities located close together that have the same local climate but differ in soil type. Both facilities have 7m-long horizontal tubes at several depths that were used for crosshole ground-penetrating radar and minirhizotron camera systems. Soil sensors provide observations at a high temporal and spatial resolution. The ongoing measurements cover five years of maize and wheat trials, including drought stress treatments and crop mixtures. We make the processed data available for use in investigating the processes within the soil–plant continuum and the root images to develop and compare image analysis methods. [ABSTRACT FROM AUTHOR]

An integrated geophysical survey using land magnetic and ground penetrating radar (GPR) methods was conducted to investigate the archaeological findings and ancient cultural relics at an undiscovered 100 m × 60 m in Tal-Baltus in El-Sadat city, Menofia Governorate, Egypt. The study area at Tal-Baltus was chosen among several archaeological hills in the Menofia governorate due to its archaeological significance in the Greco-Roman history of Egypt. The total area was first surveyed using the magnetic method, and then two small promising sites within this area were selected for the GPR survey. The obtained magnetic results showed the presence of remarkably high anomalies with different shapes of irregular geometry. Therefore, they are interpreted as ruins of old storage rooms related to an ancient harbor-shaped structure. Besides, numerous scattered pillars and column heads were also delineated and matched with remains of granite blocks in abundance in the study area, taking the same trend as the delineated magnetic anomalies. In addition, the GPR results highlighted several hyperbolas with variable amplitudes and sizes, which have been interpreted as the shallow foundation of a potential ancient harbor made of limestone. The comprehensive interpretation of the integrated magnetic and GPR surveys strongly suggests that the study area may be a part of an ancient harbor in addition to some other ancillary room-shaped structures used for cargo storage purposes and scattered portions of walls and pillars dating back to the Greco-Roman era. [ABSTRACT FROM AUTHOR]

Lacustrine beach ridges are often used to reconstruct past lake levels. However, the sedimentary architecture involved in their sedimentary evolution remains unclear, particularly for embayed beaches. To better understand the sedimentary processes, the sedimentary architecture and geomorphology of an embayed beach on the southern of Qinghai Lake were investigated using ground penetrating radar (GPR), trenches, and modern beach observation. The embayed beach's deposits are composed of three major sedimentary facies: washover deposition, fair-weather swash deposition, and lagoonal deposition. According to the variations in sedimentary facies, the formation of the embayed beach can be divided into two stages: lake-level highstand and lake-level lowstand. During lake-level highstand stage, geomorphic changes primarily occur in the cross-shore direction. A single beach ridge with washover lobes and sheets developed along the entire embayed beach. During lake-level lowstand stage, the sediments are mainly transported alongshore within the embayed beach. The northern end shows progradational complex deposits including beach ridge, lagoon and beach system, while only a beach ridge is present at the southern end. Hydrodynamic changes in two stages lead to the heterogeneity of sediment distribution, reflected in the morphology and the sedimentary architecture. The interaction of topography and hydrodynamics controls the formation and evolution of the embayed beach. This study improves the understanding of the sedimentary processes involved in embayed beaches. [ABSTRACT FROM AUTHOR]

This paper describes scientific research conducted to highlight the potential of an integrated GPR-UAV system in engineering-geological applications. The analysis focused on the stability of a natural scree slope in the Germanasca Valley, in the western Italian Alps. As a consequence of its steep shape and the related geological hazard, the study used different remote sensed methodologies such as UAV photogrammetry and geophysics survey by a GPR-drone integrated system. Furthermore, conventional in-situ surveys led to the collection of geological and geomorphological data. The use of the UAV-mounted GPR allowed us to investigate the bedrock depth under the detrital slope deposit, using a non-invasive technique able to conduct surveys on inaccessible areas prone to hazardous conditions for operators. The collected evidence and the results of the analysis highlighted the stability of the slope with Factors of Safety, verified in static conditions (i.e., natural static condition and static condition with snow cover), slightly above the stability limit value of 1. On the contrary, the dynamic loading conditions (i.e., seismic action applied) showed a Factor of Safety below the stability limit value. The UAV-mounted GPR represented an essential contribution to the surveys allowing the definition of the interface debris deposit-bedrock, which are useful to design the slope model and to evaluate the scree slope stability in different conditions. [ABSTRACT FROM AUTHOR]

The German TanDEM-X mission's primary goal is to create a highly accurate and global digital elevation model (DEM) with global accuracies of at least 10 m absolute height error (linear 90% error). This paper provides one-of-a-kind accuracy assessment of the TanDEM-X global DEM. The assessment of the TanDEM-X DEMs over Nallamala Area, Andhra Pradesh is presented through a comparison with SRTM and TanDEM-X DEMs. TanDEM-X has a finer effective spatial (i.e., horizontal) resolution than SRTM, according to analysis, visualization, and elevation scatterplots. As a first step, digital elevation models are compared to the conventional method of GCP (ground control point) elevation. Then, any two DEMs are compared using a computational method such as R programing, which is a statistical technique that selects point locations with equal distance. TanDEM-X lower elevations indicate that the radar signal penetrates deeper. DEMs with differences allowed the identification of issues related to the production methods of the DEMs. A systematic difference in elevations between TanDEM-X 12 and 30 m, and SRTM was observed. The results show a high level of detail and consistency for TanDEM-X data, indicate that the effective horizontal resolution of SRTM is coarser than the nominal 12 and 30 m. These DEMs are then delineated in QSWAT model for stream network generation. QSWAT is a tool used for the validation of digital elevation models (DEMs) in hydrological modeling. It allows for the comparison of the topographic features of the DEM with field survey data to identify discrepancies and improve model accuracy. [ABSTRACT FROM AUTHOR]

Introduction: The DaVinci Xi Robotic Surgical System (Xi) long cannula (Intuitive Surgical Company, Sunnyvale, CA) provides five additional centimeters of distal length compared to the standard Xi trocar. The extra length allows the cannula to traverse prohibitively thick body wall tissue. Our aims are to quantitatively model the consequences of not preserving the rotational centerpoint of motion (RCM) at the muscular abdominal wall. This is an essential tenet in robotic surgery; it is violated with shallow placement of the long trocar. This leads to unchecked, unnoticed blunt widening of port sites by the robotic arm, increasing hernia risk. Methods: We begin with an exploration of the schematic of the Xi robotic arm as patented by Intuitive (U.S. Patent #5931832). We trigonometrically model the lateral displacement of the abdominal wall at the trocar site with respect to vertical trocar shallowness, instrument tip depth, and instrument tip lateral motion from neutral midline. Results: The rigid parallelogram movement structure of the Xi preserves the RCM at the thick black marker printed on every Xi cannula. By limitation of design, both long and standard trocars must have this marker at the exact same distance from their proximal end. The value ranges of our model parameters (presuming a reasonable maximum orientation angle of 45° from midline) are: trocar shallowness [1 cm, 7 cm]; instrument tip depth [0 cm, 20 cm]; instrument tip lateral movement [0.0 cm, 14.1 cm]. Abdominal wall displacement increased proportionally as each instrument tip parameter reached its maximum deviation from the orthogonal midline as described in the plot figure. Maximal wall displacement at maximal shallowness was approximately 7.0 cm. Conclusion: Robotic surgery revolutionizes modern operation, particularly within bariatrics. However, the current Xi arm design disallows a true long trocar to be used safely without compromising the RCM, thereby risking hernia development. [ABSTRACT FROM AUTHOR]

The Galileo mission to Jupiter revealed that Europa is an ocean world. The Galileo magnetometer experiment in particular provided strong evidence for a salty subsurface ocean beneath the ice shell, likely in contact with the rocky core. Within the ice shell and ocean, a number of tectonic and geodynamic processes may operate today or have operated at some point in the past, including solid ice convection, diapirism, subsumption, and interstitial lake formation. The science objectives of the Europa Clipper mission include the characterization of Europa's interior; confirmation of the presence of a subsurface ocean; identification of constraints on the depth to this ocean, and on its salinity and thickness; and determination of processes of material exchange between the surface, ice shell, and ocean. Three broad categories of investigation are planned to interrogate different aspects of the subsurface structure and properties of the ice shell and ocean: magnetic induction, subsurface radar sounding, and tidal deformation. These investigations are supplemented by several auxiliary measurements. Alone, each of these investigations will reveal unique information. Together, the synergy between these investigations will expose the secrets of the Europan interior in unprecedented detail, an essential step in evaluating the habitability of this ocean world. [ABSTRACT FROM AUTHOR]

The Guizhou Province is located in karst mountainous area, so it is very important for the future layout and planning of the city to study the underground geological structure of the city based on seismic detection technology. In this paper, taking the underground active fault detection in the Liupanshui City, Guizhou Province, China as an example, a set of appropriate evaluation techniques for the accurate spatial location, structural characteristics and latest activities of the fault suit for mountainous area are proposed. Through pre-stack noise suppression, amplitude fidelity and consistency processing, and multiple iterative analysis of velocity residual statics, the resolution of the geological structure of the underground rock has been significantly improved. Based on the detailed interpretation of the shallow seismic data and the regional geological analysis, it is concluded that the main fault strike of the Weining – Shuicheng section of the Weining - Shuicheng fault is NW, mainly normal fault, the dip direction is mainly southwest, partly northeast and the dip angle is 60-70°. The strata of the two fault plates are strongly compressed and broken, and the limestone and dolomite are generally recrystallized, and calcite veins and masses can be seen. [ABSTRACT FROM AUTHOR]

Recently, various techniques have been implemented to investigate the cavity beneath the pavement using ground-penetrating radar (GPR) data. These techniques usually focus on the determination of the height of the cavity and the depth at which it is located, which play a vital role in the agencies' decision-making on the appropriate rehabilitation method for the pavement. Image processing, a relatively advanced technique that utilizes the image generated from the GPR data, has been used for this purpose. However, it is still time-consuming and yields low accuracy. As a solution, this study proposes a machine learning (ML)-based method to estimate cavity properties, such as depth and height, from GPR images with high precision in a significantly reduced time. In this study, a deep convolutional generative adversarial networks-based hyperbolic fitting algorithm, called GAN–cavity, was developed based on the Pix2Pix model to identify multi-shape signature segmentation from the GPR data. The GAN–cavity was trained and tested using 1920 and 480 images, respectively, and the model performed well with an average F1–score of 83.1 per cent. Consequently, an extreme gradient boosting (XGBoost) algorithm was used to predict the cavity depth and height based on the GAN–cavity results. Moreover, the developed model (XGB–cavity classifier) can classify the cavity's height into three classes: small, medium, and large. The XGBoost model XGB–cavity regressor used 341 and 87 cavities for training and testing, respectively, yielding regression scores (R2) and root mean squared error (RMSE) of 0.88 and 3.28 cm in cavity depth prediction, respectively. By applying the support vector machine synthetic minority oversampling technique (SVM–SMOTE) algorithm to overcome the data imbalance, the XGB–cavity classifier model obtained a high accuracy of 0.89 with precision–avg, recall–avg, and F1–score–avg of 0.83, 0.83, and 0.83, respectively. Based on the results, the proposed method (GAN–XGB–cavity) of combining the GAN–cavity and XGB–cavity can successfully identify and fit multi-shape segmentation for depth estimation and height classification of cavities. [ABSTRACT FROM AUTHOR]

Gravity and magnetic survey have been carried out in parts of the Kamrup district of Assam and the West Khasi Hills district of Meghalaya. The objective of the survey is to delineate the subsurface geological structure and identify the mineralization potential zone. Regional-residual separation, radially averaged power spectrum, Euler's depth solutions and 2D-depth model maps mainly have been analyzed for interpretation. High Bouguer anomalies were observed over exposed Assam–Meghalaya gneissic complex (AMGC) rocks whereas low anomalies were observed over quaternary sediments. The general trend of the gravity and magnetic contours are in the NE–SW direction which is also the trend of geological formations, i.e., AMGC and older metamorphic group rocks. Based on Bouguer contours several inferred contact/lineament/faults have been identified. These contact/lineament/faults are very well validated with Euler's depth solutions and total horizontal gradient of gravity anomaly. Significant high magnetic anomalies have been observed over older metamorphic group rocks and the Assam–Meghalaya gneissic complex. After the correlation with the physical properties of rock samples, geology and interpretation of gravity and magnetic maps, a potential zone has been identified for detailed investigation from a mineralization point of view. [ABSTRACT FROM AUTHOR]

Shallow-seismic full-waveform inversion (FWI) provides an effective way for the accurate reconstruction of near-surface models. The common 2D shallow-seismic FWI inverts either individual Rayleigh or Love waves, and the joint FWI of Rayleigh and Love waves can further improve the reliability of the result. Conventionally, FWI is formulated as a single-objective inverse problem and is solved with deterministic optimization algorithms. It suffers from a relatively high level of ill-posedness and high computational cost, which are two of the main problems that FWI faces. Recently, a random-objective waveform inversion (ROWI) method is proposed to mitigate these problems. ROWI reformulates waveform inversion as a multi-objective inverse problem and solves it with a stochastic optimization algorithm. The multi-objective framework and the stochastic nature provide ROWI relatively high freedom in searching for the optimal model and therefore improve its robustness against the poor initial model. In this paper, we perform a comprehensive comparison between the performance of shallow-seismic FWI and ROWI for the reconstruction of near-surface models. We compare their performance in the scenario of individual inversion of Rayleigh wave, individual inversion of Love wave, and joint inversion of both wave types. Besides, we also compare their effectiveness when using good and poor initial models. Synthetic examples of a highly heterogeneous model show that ROWI is more efficient and more robust than FWI in both individual and joint inversions. The individual ROWI of Love wave can reconstruct the model more efficiently than Rayleigh wave if a good initial model is available, and the other way around if a poor initial model is provided. The joint inversion, in both FWI and ROWI, outperforms the individual inversion of a single wave type. In both individual and joint inversions, ROWI is more efficient in reducing model error and more robust against the poor initial model than FWI. We also compare the performance of ROWI and FWI by using field data sets acquired in Rheinstetten, Germany. The results show that when a good initial model is available, both FWI and ROWI can nicely reconstruct the main structure of the subsurface model. The validity of the reconstructed model is proved by comparing it to a migrated ground-penetrating radar profile. ROWI can consistently reconstruct the model to a good level even when using a poor initial model, while the individual and joint FWIs fail to work when the initial model is poor. It confirms the relatively higher efficiency and robustness of ROWI than FWI in the reconstruction of near-surface models. [ABSTRACT FROM AUTHOR]

In order to achieve a rapid and accurate identification of soil stratification information and accelerate the development of smart agriculture, this paper conducted soil stratification experiments on agricultural soils in the Mollisols area of Northeast China using Ground Penetrating Radar (GPR) and obtained different types of soil with frequencies of 500 MHz, 250 MHz, and 100 MHz antennas. The soil profile data were obtained for 500 MHz, 250 MHz, and 100 MHz antennas, and the dielectric properties of each type of soil were analyzed. In the image processing procedure, wavelet analysis was first used to decompose the pre-processed radar signal and reconstruct the high-frequency information to obtain the reconstructed signal containing the stratification information. Secondly, the reconstructed signal is taken as an envelope to enhance the stratification information. The Hilbert transform is applied to the envelope signal to find the time-domain variation of the instantaneous frequency and determine the time-domain location of the stratification. Finally, the dielectric constant of each soil horizon is used to obtain the propagation velocity of the electromagnetic wave at the corresponding position to obtain the stratification position of each soil horizon. The research results show that the 500 MHz radar antenna can accurately delineate Ap/Ah, horizon and the absolute accuracy of the stratification is within 5 cm. The effect on the soil stratification below the tillage horizon is not apparent, and the absolute accuracy of the 250 MHz and 100 MHz radar antennas on the stratification is within 9 cm. The overwhelming majority of the overall calculation errors are kept to within 15%. Based on the three central frequency antennas, the soil horizon detection rate reaches 93.3%, which can achieve accurate stratification of soil profiles within 1 m. The experimental and image processing methods used are practical and feasible; however, the GPR will show a missed detection for soil horizons with only slight differences in dielectric properties. Overall, this study can quickly and accurately determine the information of each soil stratification, ultimately providing technical support for acquiring soil configuration information and developing smart agriculture. [ABSTRACT FROM AUTHOR]

The karstification process causes mineral dissolution and mechanical removal of carbonate rocks, creating multiscale secondary porosity that greatly affects the development of karst reservoirs. The carbonate rock weathering is mainly nucleated from fractures and bedding planes and spreads out for large areas, forming a ghost-rock karst system divided by different weathering intensities. Locally, where the hydrodynamic conditions are high total removal of the weathered rock lead to the rise of the cave network and eventually the collapse or subsidence of dolines and other karst landforms. This case study presents the use of 2D and 3D GPR data to map karst levels and features in depth of a karst system in the semiarid region of NE Brazil. Synthetic GPR data and direct observation on doline crack walls support the division of karst units into ghost-rock, alterite, and residual soil zones, marked by low-amplitude reflections, and fresh to slightly weathered bedrock, indicated by vertical high-amplitude GPR zones. High-resolution aerial images and digital elevation model provide the surface geometry and distribution of karst landforms, controlled by an orthogonal weathering/fracture system identified in the GPR profiles and time slices. In addition, the karst system was vertically divided into four zones and the area of occurrence of karst units in each zone was estimated. Pore space was then calculated for each zone, assuming porosities to the filling material. We analyzed the estimated pore space distribution compared with a gas-bearing karst reservoir in China. [ABSTRACT FROM AUTHOR]