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Boundary recognition visually delineates the horizontal extent of subsurface anomalies, providing a foundational basis for interpreting gravity data. Compared to gravity observations, gravity gradient data offers the benefits of multiple components and the enhancement of shortwave information in graphical representations. In our study, we investigated the delineation of geological structure boundaries in the lunar Oceanus Procellarum region using gravity gradient techniques. First, based on the observations from the Gravity Recovery and Interior Laboratory (GRAIL) mission, we obtained high-precision synthetic full tensor values of the gravity gradient as our primary research data. Moreover, to reduce curvature errors during large-scale terrain forward modeling, we applied the spherical prism of tesseroid to eliminate the effects of near-surface topography. Grounded on the Bouguer anomalies of gravity gradient, four distinct boundary recognition methods have been employed to explore the geological structure of the lunar Oceanus Procellarum region. It includes the Theta map method, the directional Theta map method, the combination of total horizontal derivative and the modulus of full tensor gravity gradient, and the improved edge detection method based on the Theta map method.The common feature of these methods is the utilization of the multi-component data combination from gravity gradient tensors, which can enhance the accuracy of edge detection. From the investigation results presented in the paper, we have found the following: 1) The improved edge detection method, based on the Theta map principle, enables better identification of the center of subsurface anomaly bodies during boundary recognition, utilizing a consistent single color in graphic displays. 2) According to the results of boundary recognition, numerous strip anomalies exist in the Oceanus Procellarum area that show less correlation with topographic relief. One possible explanation for these graphical anomalies of gravity gradient is that they serve as channels for the upwelling of mantle material during lunar evolution. [ABSTRACT FROM AUTHOR]

The increasing role of unmanned aerial vehicle (UAV) swarms in modern warfare poses a significant challenge to ground and air defense systems. Considering complex terrain environments and multi-sensor resources including radar and photoelectric systems constraints, a novel multi-sensor dynamic scheduling algorithm is proposed in this paper. Firstly, a transmission model with Fresnel zone under complex terrain and sensor models for radar/photoelectric systems are established. Considering the constraints of 6 factors, such as pitch angle, array scanning angle and threat levels, a detection model is developed subsequently. Secondly, to meet the real-time requirements of ground and air defense systems, a fast calculation method for Fresnel zone clearance using adaptive buffer is achieved. Thirdly, an improved Hungarian algorithm is proposed to solve the combinatorial optimization problem of sensor scheduling. Finally, simulation experiments are conducted to evaluate the algorithm performance under different conditions. The results demonstrate that the proposed approach significantly reduces the sensor switching rate while achieving a high sensor-UAV matching rate and high-threat matching rate. Furthermore, the simulation results verify the effectiveness of the proposed algorithm when applied to multi-sensor scheduling for defending UAV swarms. • Modern militaries need advanced sensor scheduling solutions to defend UAV. • Considering the Fresnel zone under complex terrain is crucial. • Adaptive buffer enables rapid calculation of Fresnel zone clearance. • Multiple sensor constraints make scheduling problems realistic. • Improved algorithm effectively enhances matching rates while reducing switching. [ABSTRACT FROM AUTHOR]

• This paper identified the innovation networks and innovation environment as the core components of the regional innovation system. • A two-region, three-sector New Economic Geography model is developed by integrating the digital economy, innovation cooperation, R&D elements flow, and innovation output into a unified framework. • Digital economy promotes innovation output through promoting intra-regional and inter-regional cooperation and attracting the flow of R&D elements personnel and capital. • Underdeveloped cities benefit more from digital economy, while large central cities function as conduits and generate spillover effects to interconnected regions. This paper explored the paradigm shift in spatial innovation dynamics driven by the rapid emergence of the digital economy (DIGE) through the lens of the regional innovation system (RIS). By integrating DIGE, RIS, and innovation output into a unified analytical framework, this study examined the impact and mechanisms of DIGE on innovation output across 330 Chinese cities from 2011 to 2020. Results show that DIGE development significantly contributes to innovation output. This contribution is mediated by DIGE's strengthening of the RIS, primarily through its facilitation of integration into innovation networks and enhancement of the innovation environment. Regional heterogeneities are evident in the innovation-promoting influence of DIGE, with less developed cities, cities with underdeveloped infrastructure, and smaller cities benefiting more significantly. While the direct impact of DIGE on large central cities is subtle, their pivotal positions enable them to radiate and disseminate innovation spillovers to connected cities through extensive cooperative networks. This study underscored the potential of leveraging DIGE, especially in disadvantaged regions, to cultivate robust and synergistic RIS and act as catalysts for augmented innovation output. [Display omitted] [ABSTRACT FROM AUTHOR]

When legged robots perform complex tasks in unstructured environments, falls are inevitable due to unknown external disturbances. However, current research mainly focuses on the locomotion control of legged robots without falling. This paper proposes a comprehensive decision-making and control framework to address the falling over of quadruped robots. First, a capturability-based fall prediction algorithm is derived for planar single-contact and 3D multi-contact locomotion with a predefined gait sequence. For safe fall control, a novel contact-implicit trajectory optimization method is proposed to generate both state and input trajectories and contact mode sequences. Specifically, incorporating uncertainty into the system and terrain models enables mitigating the non-smoothness of contact dynamics while improving the robustness of the resulting trajectories. Furthermore, a model-free deep reinforcement learning-based approach is presented to achieve fall recovery after the robot completes a fall. Experimental results demonstrate that the proposed fall prediction algorithm accurately predicts robot falls with up to 95% accuracy approximately 395ms in advance. Compared to classical locomotion controllers, which often struggle to maintain balance under significant pushes or terrain perturbations, the presented framework can autonomously switch to the fall controller approximately 0.06s after the perturbation, effectively preventing falls or achieving recovery with a threefold reduction in touchdown impact velocity. These findings highlight the effectiveness of the proposed framework in enhancing the stability and safety of legged robots in unstructured environments. • The proposed fall prediction approach exhibits significantly enhanced reliability and flexibility. • The proposed controller can autonomously generate contact sequences, reducing damage from falls. • The designed reinforcement learning-method improves efficiency and robustness in fall recovery. [ABSTRACT FROM AUTHOR]

This paper introduces an implementation of different GIS tools into Streamlit application: FCNN Terrain Classification, Earth Engine Dataset Parsing, and GIS Timelapse Animations. This toolkit is integrated with terrain multi-classification models using Fully Convolutional Neural Networks (FCNNs) for imagery data into Streamlit microservices. The proposed methodology involves labeled and unlabeled data collection from ESA WorldCover and Sentinel-2 MSI on the Google Earth Engine, compressing datasets into TFRecords format with 9 diverse terrain types, and handling Google Cloud training computations. The experimental results demonstrate the effectiveness of the CNN-based approach, achieving a tolerable from 60% up to 80% accuracy of the model and robust classification performance. The simplicity and efficiency of the proposed method make it suitable for real-world tasks requiring reliable and fast GIS analytics. [ABSTRACT FROM AUTHOR]

Terrain is a vital element in construction of virtual scene in the digital era. Despite considerable progress has been made in Generative Adversarial Network (GAN) based terrain modeling methods, their quality and controllability still cannot meet up the requirements of many emerging industries. The present work proposes a novel disentangled generative model, named as StyleTerrain, for achieving controllable high-quality terrain generation. It introduces disentangled representation learning into GAN-based terrain modeling methods for the first time. The model has been evaluated quantitatively. The results show a significantly short perceptual path length and the effectiveness of the disentanglement mechanism in controllable terrain generation, indicating that latent space disentanglement is a promising future direction for achieving generation controllability in GAN-based terrain modeling methods. [Display omitted] • Disentanglement is introduced into GAN-based terrain modeling for the first time. • StyleTerrain achieves superior generation quality and controllability. • Disentanglement is promising in future development of GAN-based terrain modeling. [ABSTRACT FROM AUTHOR]

The mobility of vehicles in off-road environments is critical for many applications. Predicting the tire-soil interaction is a challenge, especially in non-linear deformable terrain. This paper presents an overview of the bibliographic references on tires–deformable soil interactions after the 2000's, identifying the gaps in the literature. The capabilities and challenges of different modeling frameworks used for mobility (i.e., empirical, semi-empirical, and physics-based) are discussed; special emphasis is given to continuum-based frameworks. A summary of terrain material models used to approximate the behavior of coarse and fine-grained soils is provided with practices used to characterize such materials. A review of tire models for deformable soil navigation and the tire-soil interfaces is provided. Strategies to validate all these models are presented. Finally, the application of these studies for assessing the sensitivity concerning input parameters (e.g., velocity, inflation pressure, and normal load), multi-pass, multi-layered soils, wet soils, and fully integrated multi-body vehicle models are discussed. The final contribution of this review paper is a summary table that synthesizes the extensive bibliographic review. Overall, this work highlights a lack of physics-based trafficability studies in wet and plastic deformable soils. Moreover, studies on contact adhesion, stone picking, multipass, and cornering also need improvement. [ABSTRACT FROM AUTHOR]

• A methodology for seafloor topography mapping is proposed. • Data used are satellite gravity anomaly, shipborne gravity anomarly, and shipborne depth. • The accuracy of the seafloor depth determination is better than the available depth models. Seafloor topography mapping has a vital role in territorial management, geological investigation, natural hazard research, and marine construction; therefore, improving the accuracy of seafloor topography mapping is essential. The main objective of this research is to assess the possibility of improving the accuracy of seafloor topographic mapping for the central sea area of Vietnam and its surroundings based on the combination of satellite-derived gravity anomaly data and shipborne data. Firstly, the best satellite-derived gravity anomaly model for the study area is determined by comparing its gravity with the shipborne gravity anomaly. Then, the systematic deviation in the satellite-derived gravity anomaly is eliminated and fitted. Then, the substance density contrast (SDC) between the seabed and the seawater is derived. Subsequently, the seafloor depth was computed using the Gravity Geological method. In the next step, the computed depth is fitted with the shipborne depth to improve the accuracy and reduce the systematic deviation. The result shows that the best satellite-derived gravity anomaly model for the study area is the DTU17GRAV, with an accuracy of ± 5.06 mGal. The most suitable SDC in the study area is 1.40 g/cm3. The final seafloor topographic map with 1′×1′ grid is obtained with the root mean square deviation (RMSD) of ± 83.96 m, which is lower than that of the global terrain model of GEBCO 2022 (RMSD = ±152.88 m). Therefore, it is concluded that the combination of satellite-derived gravity anomaly and shipborne data can significantly improve the accuracy of seafloor mapping for complex topographic areas. The results of this research are helpful for seabed applications and territorial management in the region. [ABSTRACT FROM AUTHOR]

We present a novel proposal for modeling complex dynamic terrains that offers real-time rendering, dynamic updates and physical interaction of entities simultaneously. We can capture any feature from landscapes including tunnels, overhangs and caves, and we can conduct a total destruction of the terrain. Our approach is based on a Constructive Solid Geometry tree, where a set of spheres are subtracted from a base Digital Elevation Model. Erosions on terrain are easily and efficiently carried out with a spherical sculpting tool with pixel-perfect accuracy. Real-time rendering performance is achieved by applying a one-direction CPU–GPU communication strategy and using the standard depth and stencil buffer functionalities provided by any graphics processor. • Real-time rendering using the standard depth and stencil buffers. • Real-time dynamic updates and physical interaction on complex dynamic terrains. • Erosions with a spherical sculpting tool with pixel-perfect accuracy. • The model easily captures tunnels, overhangs and terrain erosion. [ABSTRACT FROM AUTHOR]

• Dynamic factor characterizes vehicle potential that can be created by powertrain. • Approach adds the conjoint effect of the engine, transmission, and driveline. • Includes power distribution among the wheels caused by driveline configuration. • Design factors assess effects on vehicle performance and power utilization. Vehicle terrain mobility characteristics, provided by the powertrain and running gear, are realized in dynamic interactions between the wheels and terrain. Approaches to modeling and simulation of vehicle-terrain interaction and mobility characteristics as well as engineering approaches to design powertrain sub-systems together pre-determine a vehicle's technical success or failure before it touches the ground. This article develops a vehicle mobility design technique, applicable to both manned and unmanned platforms, concerned with powertrain power conversion and realization in tire-terrain interactions. The modeling component is based on multi-drive-wheel vehicle longitudinal dynamics combined with terramechanics and powertrain characteristics. The approach advances the conventional dynamic factor by introducing the conjoint effect of the engine, transmission, and driveline system on vehicle traction and acceleration performance in terrain conditions where circumferential wheel forces and tire slippages may differ from each other. The vehicle design component of the proposed technique introduces drivetrain, driveline, and powertrain design factors that assess the influence of the drivetrain and driveline systems on traction, acceleration performance, power conversion, and realization at the wheels. The vehicle-design-for-mobility technique is completed by examining indices of mobility margins and performance. An analysis of several 8x8 armored personal carriers and 4x4 off-road vehicles illustrates the proposed technique. [ABSTRACT FROM AUTHOR]

This paper constructs the economic model to consider the economy in cities from the waste management perspective. Specifically, we analyze the link between migration, natural capital, and waste management by applying the new economic geography model. We show the results; the population distribution pattern in the long run varies depending on the congestion effect of natural capital and waste management's technological level. In particular, a full agglomeration equilibrium realizes in the long run for higher technological levels of waste management (lower congestion effects), an interior asymmetric equilibrium does for intermediate technological levels (intermediate congestion effects), and the symmetric dispersion equilibrium realizes for the lower technological levels (higher congestion effects). [ABSTRACT FROM AUTHOR]

To study the morphological characteristics of the largest canyons in the Southern and Central Basins of Lake Baikal, we analysed a digital relief model based on high-resolution multibeam bathymetric surveying. We evaluate the role of tectonic, lithological and climatic controlling factors in the formation and evolution of canyons. Tectonic activity and seismicity act as a catalyst for canyon formation and for the development of sublacustrine gravity flows and turbidity currents, and alter the morphological appearance of already existing canyons. The influence of tectonics on the formation of the Baikal canyons is particularly noticeable on the western slope of Lake Baikal, where canyons are mainly located along faults and follow their directions. Gravity flows and turbidity currents become more important during earthquakes and periods of lower lake level. When canyon heads are located close to river mouths, riverine processes have a significant impact on the evolution of the canyon. The topography of the original surface and the lithology of the substrate also play a significant role in the evolution of canyons and in shaping the canyon morphology. During periods of lower lake level (during Pleistocene glacial periods) riverine processes were responsible for initiating the formation of many canyons in Lake Baikal. The canyons developed under the complex influence of the factors considered. One or another factor could be dominant at different stages of their evolution, while the role of the other factors became secondary. These roles could interchange over time. The Baikal canyons show a great deal of resemblance to canyons in marine environments, in terms of morphological characteristics as well as of canyon-forming processes. We propose a morphogenetic classification of the underwater valleys and canyons of Lake Baikal. [ABSTRACT FROM AUTHOR]

A perpendicular jet impingement on a granular bed covering uneven terrain causes complex particle erosion and diffusion behaviours. Such a situation is most likely to occur at a plume-regolith interaction in planetary exploration missions. A plume due to a retrorocket impinges on regolith over a planetary surface in a soft-landing sequence. In this study, we focus on the understanding of basic terrain effects and investigate numerically a subsonic jet impingement on the granular bed covering a rectangular hump using a two-way coupled fluid-particle interaction method. Moreover, the experiments are conducted to determine the suitable numerical parameters: turbulence parameters, friction coefficient of particles, and coefficient of restitution. Both particle erosion and diffusion behaviours are numerically investigated at several hump positions and heights, and consequently the hump position strongly influence the particle diffusion and erosion behaviours. Erosion due to the bearing capacity failure continues to occur from the initial elapsed time in the case of the jet impingement around the hump close to a jet axis. This is because the gas interaction with the hump leads to the velocity reduction of a diffusion gas velocity, and it is lower than a particle velocity in most of the regions. Additionally, the deposited particles in a cavity formed by the close hump are difficult to be diffused because the particles stagnate by the downward impinging jet flow. • The particles in a cavity are difficult to be diffused if a jet covers the cavity. • The particle erosion and diffusion behaviours are influence by a hump position. • The deposited particles are upwardly diffused by a hump. [ABSTRACT FROM AUTHOR]

• Terrace erosion is impacted by the dispersive nature of soils. • Gully and pipe erosion deviate the attention for sedimentation. • Sedimentation was a magnitude larger than erosion. • Leaving plastic sheets on fields increases geomorphic processes. Abandonment of agricultural terraces is one of the main drivers of erosion processes and land degradation in semiarid environments. Soil erosion is a complex process and it is difficult to capture erosion rates including the different phases of the erosion process, depending on the spatio-temporal scale of observation. In this work erosion processes were studied in a small abandoned cascade terraced system in SE Spain regarding its sedimentation rate. Here agriculture practices included plastic covers and the activities were abandoned 18 years before the field study. The objectives were to determine erosion and sedimentation rates in the system and explore the relationships between erosion vulnerability and soil physicochemical properties of the parent material. The methodological approach included the study of erosion features such as rilling, gullying, and piping. A budget per terrace was estimated, using dGPS surface height measurements, drone images and derived terrain modeling, detailed sampling, and GIS techniques; and the determination of material properties such as structural stability, slaking, bulk density, soil organic matter, pH, electrical conductivity, gypsum, carbonate content, and SAR. The results show that gullying and piping result in high detachment rates (5.5–38.9 ton Ha−1 ·yr−1), but deposition was found to be at least as important or larger than detachment for several terraces (31.7–130.4 ton Ha−1 yr−1). Even though not a full exploration of all components of the sediment budget could be done, the 'on terrace' sedimentation rates were high. This means that just mapping gullying or erosional features as indicators for degradation rates can be misleading. Additional information on temporary sedimentation is also crucial to get reliable erosion models, especially at finer spatial scales. Furthermore, this also demonstrates that leveling and abandonment of fields on dispersive substrates accelerates land degradation and that leaving the plastic on the fields also has negative environmental impacts concerning erosion. [ABSTRACT FROM AUTHOR]

Satellite-based precipitation products (SPPs), such as the NOAA Climate Prediction Center (CPC) Morphing technique (CMORPH), have greatly extended our ability to monitor global precipitation. However, their performance over complex terrain remains highly uncertain. To improve accuracy, CPC has recently upgraded its operational SPP to the second generation CMORPH–CMORPH2. In addition to such efforts, the reliability of SPPs can be further enhanced by developing robust uncertainty estimates. This study employs a censored, shifted gamma distribution (CSGD)-based error modeling framework to develop error models for both CMORPH2 and its predecessor, CMORPH1, at a 6-hourly scale over Northern California—a typical complex terrain region that challenges most SPPs. Using the Stage IV reference precipitation, the relative improvements of CMORPH2 over CMORPH1 are quantified by comparing their CSGD-derived error statistics. The comparison shows that CMORPH2 outperforms CMORPH1 by reducing the overall bias and detection errors, and by better capturing the orographic gradients of precipitation over the Coast Ranges and Sierra Nevada. Validation results show that the trained error models can appropriately represent the bias and random errors; however, the models for both CMORPH2 and CMORPH1 show reduced skills in the high-altitude Sierra Nevada. With high-resolution regional climate simulations, the uncertainty estimates are further improved by incorporating them as covariates. The simulated precipitation shows substantial improvement of the uncertainty estimates over most areas, including the challenging high-altitude Sierra Nevada. Following precipitation, the simulated integrated water vapor transport (IVT) and convective available potential energy (CAPE) also offer modest improvements, mainly along the coast. Independent verification further demonstrates the robustness of the uncertainty estimates during heavy precipitation events. As NOAA is currently reprocessing CMORPH2 to produce an updated global precipitation record from 1991 onward, this error modeling framework holds potential for broader applications in quantifying the uncertainty of CMORPH2 for estimating orographic precipitation over extended periods and locations. • We developed parametric models for CMORPH uncertainty estimates in complex terrain. • The second-generation CMORPH exhibits superior performance over its predecessor. • The uncertainty estimates of CMORPH are reliable even in heavy precipitation events. • WRF simulations improve the uncertainty estimates for orographic precipitation. [ABSTRACT FROM AUTHOR]

Disaster relief presents many unique logistics challenges, including damaged transportation infrastructure, multiple conflicting goals, and secondary disasters caused by spontaneous disaster relief. The delivery and distribution of humanitarian relief materials faced by nonprofit organizations (NPOs) poses a critical challenge due to the highly unpredictable nature of disasters, conflicting missions, and the need to navigate government regulations in disaster management. In this paper, we propose a novel multi-objective disaster relief modeling system for NPOs, considering (1) prioritization (providing medical services to seriously injured victims), (2) effectiveness (degree of satisfaction), (3) efficiency (operational costs), and (4) equity (cost of maintaining order). To incorporate the practical constraints of disaster relief operations, we include factors such as road damage, transportation capacity limitations, and route flow saturation as part of the model formulation. We then utilize fuzzy multi-objective programming to optimize the proposed disaster relief model, considering two relief distribution schemes: a common NPOs' spontaneous relief scheme and a newly designed traffic control scheme with government regulation. Based on the real-world scenario of the 2008 Wenchuan earthquake, we demonstrate that the designed traffic control scheme exhibited remarkable improvement among the NPOs' four objectives compared to the spontaneous relief scheme. Moreover, in the process of solving fuzzy multi-objective programming problems, artificial intelligence technology is employed to handle the fuzziness in multi-objective and automatically adjust parameters, making the solution results better and in line with practical situations. And we also validate the proposed model can be solved in polynomial time, meeting the engineering practice requirements, and can be easily extend to most disaster relief distribution scenarios. [Display omitted] • Fuzzy multi-objective programming model for humanitarian relief materials' delivery and distribution was built. • Prioritization, effectiveness, efficiency and equity were considered as the NPOs objectives. • Roadway capacity is considered as a constraint condition. • The NPOs' spontaneous relief scheme and traffic control scheme were discussed specially. • Delivery and distribution of humanitarian relief materials was analyzed based on 2008 Wenchuan earthquake. [ABSTRACT FROM AUTHOR]

• The determinants of smart roadway retrofitting on injury severity are examined in hazardous and non-hazardous terrain. • Random parameters logit models with heterogeneity in the means and variances are established. • Temporally unconstrained parameters model is more suitable compared to partially temporally constrained parameters model. • Road safety policies are suggested to be designed and implemented based on terrain and road development level. The advancement of intelligent road systems in developing countries poses unique challenges in identifying risk factors and implementing safety strategies. The variability of factors affecting crash injury severity leads to different risks across levels of roadway smartness, especially in hazardous terrains, complicating the adaptation of smart technologies. Therefore, this study investigates the temporal instability of factors affecting injury severities in crashes across various terrains, with a focus on the evolution of road smartness. Crash data from selected complex terrain regions in Shaanxi Province during smart road adaptation were used, and categorized into periods before, during, and after smart road implementations. A series of mixed logit models were employed to account for unobserved heterogeneity in mean and variance, and likelihood ratio tests were conducted to assess the spatio-temporal instability of model parameters across different topographic settings and smart processes. Moreover, a comparison between partially constrained and unconstrained temporal modeling approaches was made. The findings reveal significant differences in injury severity determinants across terrain conditions as roadway intelligence progressed. On the other hand, certain factors like pavement damage, truck and pedestrian involvement were identified that had relatively stable effects on crash injury severities. Out-of-sample predictions further emphasize the need for modeling across terrain and roadway development stages. These insights are crucial for developing tailored safety measures for smart road retrofitting in different terrain conditions, thereby supporting the transition towards smarter road systems in developing regions. [ABSTRACT FROM AUTHOR]

Downward shortwave radiation (DSR) is the main energy source for the Earth's system and a dominant component of the radiation budget. Although many algorithms have been proposed for estimating DSR, most models only consider either the radiative effects of terrain or atmosphere, and no research has considered the conditions of clouds on the mountainside. In this paper, a high-resolution Mountain Radiative Transfer model with Clouds (MRTC) is proposed to characterize the cloud-terrain coupling effects on DSR under different surface positions relative to the clouds. To operate the MRTC, a look-up table is employed to obtain initial radiative parameters. The comparison with Monte-Carlo based radiative transfer indicates that MRTC can be applied to conditions of clouds on the mountainside. And the reliability of MRTC under conditions when clouds are above mountains is also validated against in-situ measurements, with an RMSE of 149.9 W / m 2 , a bias of 28.3 W / m 2 , and an R 2 of 0.74. By using more accurate cloud cover data extracted from All-Sky images, the accuracy of MRTC has improved, with the RMSE decreasing to 115.8 W / m 2 , and the R 2 increasing to 0.8. This suggests that the uncertainty in satellite cloud products significantly contributes to errors in DSR estimations. MRTC is expected to more accurately represent cloud-terrain coupling effects on DSR, and improve the accuracy of DSR estimation over rugged terrain under cloudy skies. • A high-resolution mountain radiative transfer model with clouds (MRTC) is proposed. • The coupling effects of clouds and terrain on DSR are fully considered. • The first time the conditions of clouds on the mountainside are handled in DSR estimation. • Validation against a 3D radiative transfer model and in-situ measurements shows good agreement. • Uncertainty in cloud products and the complex 3D cloud structures significantly affect the accuracy of estimation. [ABSTRACT FROM AUTHOR]

• Use of SoLIM-generated soil data in the SWAT model produces reliable results. • Forested areas resulted in higher output uncertainty compared to grasslands and paddy fields. • Higher slope introduces increased uncertainty in the hydrological processes. • Uncertainty patterns differ during flood and non-flood seasons simulated with SWAT. • Evaporation, Φ d , and K sat are key contributors to uncertainty in the SWAT simulation. Hydrological models are essential tools for understanding natural processes, yet they often encounter with uncertainties due to limited input data and simplified assumptions. Soil data is a crucial input parameter for hydrological models, but it faces cartographic challenges due to lack of standardized soil mapping methods. To explore the applicability of soil datasets derived from the Third Law of Geography in hydrological models, the Soil Landscape Inference Model (SoLIM) based on this principle is used to generate a soil dataset. This dataset is then utilized as input data for a semi-distributed hydrological model (Soil and Water Assessment Tool, SWAT) to assess the impact of soil dataset uncertainty on performance of the hydrological model. This study, utilized the Fengyu River Watershed in Yunnan Province, China as an example, showed that: 1) Although the integration of SoLIM-generated soil data into the SWAT model introduces sensitivity in sediment yield, the overall results remain reliable. This suggests that soil datasets based on the Third Law of Geography can serve as input for semi-distributed hydrological models. 2) Uncertainty introduced by SoLIM-generated soil data affects parameters such as evaporation, total porosity of the soil layer (Φ d), and groundwater infiltration coefficient (K sat). These variations influence the sensitivity of SWAT's predictions regarding streamflow and water quality. 3) Factors influencing model outcomes include steeper slopes in certain areas, which enhance streamflow velocity and flow rates, resulting in more dynamic and non-linear responses. Additionally, soil water dynamics exhibit higher temporal and spatial variability in forests compared to pasture and rice paddy fields, where vegetation tends to be more uniform, maintaining stable soil water loss pathways and reducing uncertainty in streamflow predictions. The study provides a foundation for studies addressing the difficulties in acquiring high-precision soil datasets for such models. [ABSTRACT FROM AUTHOR]

• A method for modeling agricultural unstructured terrain was proposed. • The color information and FLANN were incorporated to optimize the SURF. • Achieve fast and accurate image feature extraction and matching. • The constructed agricultural unstructured terrain point cloud was optimized. The global terrain model is the cornerstone and crucial background data towards acquiring autonomous tractors in an agricultural unstructured environment. However, there are severe perspective distortions, variable local feature changes, affine deformations between images, and a lack of manually labeled features during the data-matching process of terrain modeling. In this paper, a feature fusion-based optimization method for modeling agricultural unstructured terrain was proposed on the basis of Unmanned Aerial Vehicle (UAV) oblique photography technology. Firstly, the color information of the image and the Fast library for Approximate Nearest Neighbors (FLANN) were incorporated to optimize the Speed Up Robust Feature (SURF). Secondly, the optimized SURF feature was combined with the Maximally Stable Extremal Regions (MSER) to achieve the fast and accurate feature extraction and matching between the affine deformation images. Finally, the agricultural unstructured terrain was constructed and optimized by adopting the bilateral filtering algorithm. The experimental results indicated that the algorithm proposed in this paper had better matching effect and matching efficiency in the data matching process, which in turn achieved the fast and accurate construction of the global 3D model of agricultural unstructured terrain. [ABSTRACT FROM AUTHOR]

• A semi-empirical terramechanics approach for complex terrain profiles is presented. • The approach is an extension of the semi-empirical models. • The terrain can be defined using an arbitrary heightfield. • The method can capture complex terrain geometries and gaps in the contact patch. • Comparison to the least square plane method highlight proposed approach's strengths. Dynamic simulations of various types of off-road vehicles, from planetary rovers to agricultural equipment, have long relied on well-established semi-empirical terramechanics models. While these models do have drawbacks and reliability issues that have been addressed by numerous works in the decades since the models were first introduced, semi-empirical approaches remain one of the few ways to simulate realistic wheel-soil interaction in real-time. One of their drawbacks is their assumption that the terrain is a flat plane. The models work by integrating normal and shear stresses along the wheel-terrain contact patch. The normal stress at each point along the contact patch is determined using an equation that computes soil pressure based on semi-empirical parameters, the dimensions of the wheel and the sinkage, which is determined based on the distance between the point and the plane that defines the terrain. Other works simplify the rough terrain contact problem by defining an equivalent contact plane at each time step in order to continue to be able to use semi-empirical models - modified to work with slanted planes - to compute the interaction forces. In this work, we propose a new, modified version of the semi-empirical model in which interaction forces for a wheel travelling on rough terrain can be computed without the need to use an equivalent contact plane. To highlight the advantages of our proposed approach, we compare our simulation results to the results of simulations using an existing approach for modelling a wheel travelling over rough terrain using traditional semi-empirical models. [ABSTRACT FROM AUTHOR]

• Equipped with the principle of wiring cost minimization, a hybrid computational model consisting of a deep convolution neural network and a self-organizing map is constructed to simulate human VTC. • A central feature of the model is the biological constraint of neurons' lateral wiring span, which significantly shapes the morphology of the topographical structure in the model. • The topographical structure of both fine-scale category-selective regions and large-scale abstract functional maps is largely replicated in the model. • Categorical selectivity and view-invariant representations of the category-selective regions are generally reserved in the model. Our minds represent miscellaneous objects in the physical world metaphorically in an abstract and complex high-dimensional object space, which is implemented in a two-dimensional surface of the ventral temporal cortex (VTC) with topologically organized object selectivity. Here we investigated principles guiding the topographical organization of object selectivities in the VTC by constructing a hybrid Self-Organizing Map (SOM) model that harnesses a biologically inspired algorithm of wiring cost minimization and adheres to the constraints of the lateral wiring span of human VTC neurons. In a series of in silico experiments with functional brain neuroimaging and neurophysiological single-unit data from humans and non-human primates, the VTC-SOM predicted the topographical structure of fine-scale category-selective regions (face-, tool-, body-, and place-selective regions) and the boundary in large-scale abstract functional maps (animate vs. inanimate, real-word small-size vs. big-size, central vs. peripheral), with no significant loss in functionality (e.g., categorical selectivity and view-invariant representations). In addition, when the same principle was applied to V1 orientation preferences, a pinwheel-like topology emerged, suggesting the model's broad applicability. In summary, our study illustrates that the simple principle of wiring cost minimization, coupled with the appropriate biological constraint of lateral wiring span, is able to implement the high-dimensional object space in a two-dimensional cortical surface. [ABSTRACT FROM AUTHOR]

192 coupled wind and fire CFD simulations were performed using ANSYS Fluent to study the wind and fire interaction in an open car park. The natural ventilation was insufficient for removal of smoke and heat for the majority of investigated fires. Blockage effect was observed for wind directions parallel to the open walls, which resulted in reduced smoke removal and higher smoke temperatures. With known probabilities of all the investigated wind speed and directions, we have estimated the percentage of time in which fire outcomes are acceptable. This value was coined as the car park operational uptime, and was 84.9 %–92.8 % in relation to the fire with HRR = 1.4 MW; 36.5 %–56.1 % at 4.0 MW; 34.1 %–54.4 % at 6.0 MW and 12.13–25.5 % at 8.8 MW. In 6.22 % of wind cases, the velocity inside the car park exceeded 3.0 m/s, which could potentially contribute to the growth of the fire. Limitations of the study include the assumed wind probability distribution relevant to the Warsaw region, the single location of the fire used in the assessment and the implicit modelling of topography and architecture through an introduced wind profile and terrain roughness model. • Qualitative method of natural smoke control assessment of operational uptime is proposed. • Operational uptime of natural smoke control ranged from 84.9 % to 92.8 % for 1.40 MW design fire. • Operational uptime of natural smoke control ranged from 12.1 % to 25.5 % for 8.80 MW design fire. • Wind perpendicular to open facades yielded the best results. • Wind parallel to open facades caused smoke entrapment in the car park and the worst outcomes. [ABSTRACT FROM AUTHOR]

Accurate large-area Digital Terrain Models (DTMs) are crucial for many science applications. Spaceborne Synthetic Aperture Radar (SAR) platforms are often used to create these DTMs as they provide an effective tool to collect surface elevations across a wide extent. However, SAR-derived digital elevation models (DEMs) cannot accurately measure ground elevations in the presence of forests. This work demonstrates an approach to estimate terrain elevations from 12 m TanDEM-X by using a convolutional neural network (CNN) trained with ground elevations from ICESat-2 – a spaceborne laser altimeter. This approach demonstrated the ability to estimate terrain elevations from TanDEM-X DEMs for the greater North Carolina area. The CNN estimated terrain saw an improvement in RMSE from 11.28 m to 4.42 m within the entire area of interest, and a focused improvement in RMSE from 12.78 m to 4.95 m in forested areas when compared to ICESat-2. The CNN model outperformed linear, random forest, and gradient boosted regression models using comparable model inputs. This work combines 12-m TanDEM-X data with ICESat-2 profiles, resulting in a new DTM product with accuracy approaching that of reference elevations obtained from satellite laser altimetry in the southeastern United States. • Investigates use of CNN to create DTM with TanDEM-X and ICESat-2 in North Carolina. • CNN outperformed linear, random forest, and gradient boosted regression models tested. • CNN reduced RMSE from 11.28 m to 4.42 m with convolutional neural network. • Establishes possible framework for creating global DTMs. [ABSTRACT FROM AUTHOR]

• A software application was developed to simulate sprinkler water distribution on undulating hilly terrain. • A water application rate conversion from flat to hilly terrain was deduced by the principle of water volume conservation. • An indoor experimental platform was set up to replicate the sprinkler arrangement on a hill, devoid of plant canopy. The hilly terrain modifies the droplet landing positions in comparison to flat ground, complicating the prediction of sprinkler water distribution on such uneven regions. Utilizing a digital elevation model combined with droplet dynamics and evaporation models, droplet landing positions were calculated on both flat and uneven terrains. From the droplet landing positions and the corresponding water application rates on flat terrain, the water application rate on hilly terrains was deduced using the principle of water volume conservation. Subsequently, a software application was developed to assist in this prediction. Using the radial water distribution data from an individual sprinkler under various operating pressures and the elevation data of a hill, the software predicts the water distribution for either an individual sprinkler or an entire solid-set sprinkler irrigation system on the hill. This allows for the calculation of the average water application rate (h ¯) and distribution uniformity (UCS) for combined sprinklers. The simulated water application rate on hilly terrains was validated using an experimental platform that replicates the sprinkler arrangement on a hill, devoid of plant canopy. Our findings indicate that the simulated water application rate for a sprinkler on hilly terrain aligns closely with the observed values, achieving a confidence coefficient (c) of 0.96. The developed software reliably predicts sprinkler water distribution on hilly terrains with significant accuracy for the conditions studied. We compared the UCS of the flat, hilly slope, and homogeneous slope terrains and found that the hilly slope better reflects the uneven water distribution owing to the undulating characteristics of the hilly terrain. [ABSTRACT FROM AUTHOR]

Filtered Geomorphic Reference Models (FGRMs), extracted from High-Pass Filters based on the Fast Fourier Transform (HPF-FFT), provide a semi-automated and objective detection of a wide range of geoforms and geomorphic situations (flat areas, slopes, depressions, or valley bottoms). The method is sensitive enough to reveal numerous inflection points that enable the identification of subtle changes in relief polarity, resulting in accurate representations of real land depressions. The effectiveness of this method has been demonstrated in lunar landscapes, utilizing altimetry extracted from high-precision Planetary Digital Elevation Models (PDEMs) to construct crater inventories with well-defined FGRMs. However, when analysing lunar environments with closely-spaced geomorphic features, the FGRMs display blurring and generalization effects, reducing their capability to identify all existing crater depressions. This limitation controls the ability of FGRMs, to generate reliable crater inventories. This study examines such effects in three experiments. Using Synthetic Digital Relief Models (SDRMs) constructed by means of a MATLAB script two experiments are performed. In Experiment_1 different scenarios of proximity between aligned craters are analysed. The marks, or footprints, formed by craters of identical size and shape (i.e., circular bowl-shaped depressions with central peaks) are considered, resulting in simplified PDEMs. Various scenarios of crater centre separation (proximity) and the presence of internal features within craters are also analysed. Experiment_2 validates the method with different proximities, locations and crater sizes. Experiment_3 validates the approach in a sampled area of LRO lunar PDEM corresponding to Zelinskiy crater (Mare Ingenii area). To address these blurring effects, a hybrid methodology is employed, generating FGRMs extracted from HPF-FFT, in conjunction with other GIS and remote sensing tools, such as singular point zoning, aspect-slope zoning, and edge-limits zoning. As a result, the correspondence between the FGRMs and the synthetic forms is examined, aiding the comprehension of the graphical response provided by filtering in these cratered areas. The methodology demonstrates that FGRMs derived from HPF-FFT are sensitive to capturing connections between shapes as soon as the crater features start to merge, while blurring becomes evident when the craters are located at a proximity of <20 model units. Additionally, the results highlight the method's utility in accurately locating crater footprints and morphologically characterizing inner crater features, even when crater centres are closely spaced. This approach effectively mitigates blurring effects and enables the precise localization of crater marks and their internal features. The validations carried out in complex relief and high precise DEMs provide a use in real situation. [Display omitted] • SDRMs of nearby craters at different proximity distances are generated using a MATLAB script. • FGRs of craters extracted from FFT filtering yield inaccurate inventories due to blurring effects. • Different scenarios of crater proximity are designed to evaluate the answer provided by filtering. • Combined use of FFT filtering, GIS and remote sensing tools is sensitive to blurring. • The morphological characterisation of simulated craters improving crater inventories. [ABSTRACT FROM AUTHOR]

Autonomous safe landing of UAVs is an important and challenging task in unknown environments, as almost no prior scene information can be leveraged for navigation. Most existing methods cannot address this issue completely, due to terrain uncertainty and system complexity. In this paper, we present a novel and complete framework for UAVs landing, which is built on point cloud in coarse-to-fine manner. Besides, our framework is designed with modularity and has four modules: point cloud preprocessing, coarse landing site selection, fine terrain evaluation, and landing optimal model. Specifically, a composite preprocessing scheme is applied to simultaneously filter noise, generate 3D Octo-map and plan the path on the raw point cloud. To balance the accuracy and real-time of the landing system, only promising coarse landing locations are automatically selected by adopting the proposed multi-stage process in grid-map. Based on the result of coarse stage, a fine-grained 3D validation is modeled by multiple terrain factors, which can further improve landing safety. Finally, a novel landing optimal model fuses terrain condition, fuel consumption, and second landing validation to determine the final landing sites during descent. Extensive experiments have been successfully conducted on different real-world and unknown environments, verifying that our method can select safe landing sites for UAVs robustly. Additionally, the system is further evaluated under normal, emergency, and rescue situations respectively to highlight different landing requirements. • A UAVs landing framework is proposed using a coarse-to-fine manner. • We use the multi-stage process to select coarse landing locations automatically. • A fine-grained terrain evaluation is introduced considering multiple factors. • An optimal model is designed to determine the final landing sites. [ABSTRACT FROM AUTHOR]

Neural networks (NNs) have demonstrated the potential to recover finer textural details from lower-resolution images by superresolution (SR). Given similar grid-based data structures, some researchers have transferred image SR methods to digital elevation models (DEMs). These efforts have yielded better results than traditional spatial interpolation methods. However, terrain data present inherently different characteristics and practical meanings compared with natural images. This makes it unsuitable for existing SR methods on perceptually visual features of images to be directly adopted for extracting terrain features. In this paper, we argue that the problem lies in the lack of explicit terrain feature modeling and thus propose a terrain feature-aware superresolution model (TfaSR) to guide DEM SR towards the extraction and optimization of terrain features. Specifically, a deep residual module and a deformable convolution module are integrated to extract deep and adaptive terrain features, respectively. In addition, explicit terrain feature-aware optimization is proposed to focus on local terrain feature refinement during training. Extensive experiments show that TfaSR achieves state-of-the-art performance in terrain feature preservation during DEM SR. Specifically, compared with the traditional bicubic interpolation method and existing neural network methods (SRGAN, SRResNet, and SRCNN), the RMSE of our results is improved by 1.1% to 23.8% when recovering the DEM from 120 m to 30 m, by 4.9% to 22.7% when recovering the DEM from 60 m to 30 m, and by 7.8% to 53.7% when recovering the DEM from 30 m to 10 m. The source code that has been developed is shared on Figshare (https://doi.org/10.6084/m9.figshare.19597201). [ABSTRACT FROM AUTHOR]

Ground-Based Synthetic Aperture Radar (GB-SAR) enables to monitor a scene in a distance up to a few km and with an accuracy of around one mm. It is mainly used for landslide monitoring but also used to monitor man-made structures such as bridges and dams. Due to the particular distance-dependent imaging concept and related geometric distortion effects, the interpretation of the SAR images can be difficult, especially in the case of complex man-made structures. The geocoding of the SAR data enables to project the 2D SAR image on a 3D digital elevation model (DEM) or a 3D terrain model and highly improves the interpretation of the observed deformation. It also allows to fuse SAR-based observations with other data sources. The purpose of this paper is to present a new algorithm to geocode GB-SAR data in complex scenarios. The method introduces two new components, a Bayesian statistical approach and a ray-tracing algorithm. The first one uses an a priori function on the received intensity to improve the geocoding in case of strong layover, while the latter considers areas in the radar shadow to be excluded from geocoding. Moreover, ray-tracing provides the starting point for the analysis of signals with multiple reflections which are also discussed in this paper. Our algorithm is applied to and evaluated with two case studies. The first one demonstrates the improved geocoding of GB-SAR data on the Linach dam in the Black Forest in Germany, which is characterized by a rather complex architecture. The second case study shows the application of the method at the Enguri dam in Georgia, which is characterized by its large dimensions and a dam height over 270 m. [ABSTRACT FROM AUTHOR]

Geographic information and topographical understanding are crucial for effective field environmental monitoring and autonomous navigation. Unfortunately, implementing this knowledge is often difficult due to unsolved problems such as understanding disorganized and unstructured mountainous regions. Traditional three-dimensional (3D) scene understanding methods from 3D point clouds or fused data are energy-consuming and unsuitable for a resource-constrained unmanned aerial vehicle (UAV) with limited computation, memory, and energy. This study proposes a methodology to understand unstructured gorges and reconstruct them in 3D environments from a low-cost monocular camera. The new approach assigns mountain texture projections to clusters and reshapes surfaces of unstructured mountains to follow geometric constraints regarding position and orientation. The relative relationships between surfaces and vanishing points are then analyzed to understand and reconstruct amorphous gorge scenes. This method is practical and efficient for navigating amorphous gorges based on understanding unstructured mountains. Fortunately, this method requires no prior training and is robust to color and illumination. We compared the percentage of incorrectly classified pixels with the ground truth. Experimental results have demonstrated that our approach can successfully understand amorphous gorges, meeting the requirements for autonomous flying in mountainous environments. • A method is presented to understand amorphous gorge scenes and generate a topographic map. • The algorithm can reconstruct unstructured mountains without prior training. • The approach is robust against changes in illumination and color without camera's parameters. [ABSTRACT FROM AUTHOR]

• A new 3DJG-CT wake model suitable for complex terrain wind farm is proposed. • The topology anisotropy effect on wake development over complex terrain is revealed. • Two phases of field experiment are conducted using LiDARs. • The good performance of 3DJG-CT model is verified by the field measured data. • The correlation between wake development and background flow field is quantified. The topology anisotropy of complex terrain has a tremendous impact on the wake characteristics in real complex terrain wind farm. To efficiently and precisely evaluate the terrain effect on the wake development, a new three-dimensional Jensen-Gaussian wake model for complex terrain (3DJG-CT) was proposed with two improved assumptions and combined with the CFD simulation, building upon the 3DJG-U wake model. The wake centerline is determined by the velocity components (u x , u y , u z) extracted from the CFD simulation results of the background flow field, which also provide the local wind velocity U local (x , y , z) to replace the inflow wind shear model in our earlier 3DJG model. Two phases of field measurement were conducted to reveal the impact of the topology anisotropy on the 3D wake characteristics. By comparing the predictions of the 3DJG-CT model and previous models with the field measurement data, the results show that the 3DJG-CT wake model has good performance in wake profile prediction. Due to the dominant impact of the hill-blocking effect compared to the momentum mixing effect, the downstream wake deficits may be larger than the upstream wake deficits on the leeward slope, which is opposite to the situation in flat terrain. In the windward slope scenario, the wind speed at hub height at downstream distances of 5.5D and 7D is 6.64%% and 8.27% higher than the upstream inflow velocity at hub height, because of the positive coupling effect of the wind speed-up effect and the momentum mixing effect. Better quantification of the wake effect in complex terrain can be supplied in this study. [ABSTRACT FROM AUTHOR]

Posttraumatic Stress Disorder (PTSD) is highly co-morbid with chronic pain conditions. When present, PTSD significantly worsens chronic pain outcomes. Likewise, pain contributes to a more severe PTSD as evidenced by greater disability, more frequent use of harmful opioid analgesics and increased pain severity. The biomechanism behind this comorbidity is incompletely understood, however recent work strongly supports the widely-accepted role of expectation, in the entanglement of chronic pain and trauma symptoms. This work has shown that those with trauma have a maladaptive brain response while expecting stress and pain, whereas those with chronic pain may have a notable impairment in brain response while expecting pain relief. This dynamical expectation model of the interaction between neural systems underlying expectation of pain onset (traumatic stress) and pain offset (chronic pain) is biologically viable and may provide a biomechanistic insight into pain-trauma comorbidity. These predictive mechanisms work through interoceptive pathways in the brain critically the insula cortex. Here we highlight how the neural expectation-related mechanisms augment the existing models of pain and trauma to better understand the dynamics of pain and trauma comorbidity. These ideas will point to targeted complementary clinical approaches, based on mechanistically separable neural biophenotypes for the entanglement of chronic pain and trauma symptoms. [ABSTRACT FROM AUTHOR]

Surface relief in forms of extrusions and intrusions as the substantial feature of early fatigue damage is one of the most important phenomena studied in metal fatigue. The most common surface relief models in bulk metals are agreed to be correlated with the formation of typical dislocation patterns as persistent slip bands (PSBs), while little is known about the fundamental mechanisms at submicron and even nanometer scales where dislocation pattern formation is fully inhibited. Here, as exampled with thin Au films, the underlying fatigue damage mechanism at small scales is investigated through the quantitative characterization of fatigue damages. Continuous generation and migration of vacancies is found to be crucial for the shape of extrusion/intrusions and kinetics of their growth at submicron and even nanometer scales. Due to the degraded dislocation interaction and intensified vacancy diffusion, the delayed vacancy accumulation in the small-scale metal interior suppresses the extrusion and interface void formation in thinner films, which finally leads to the superior ability to support tremendous surface relief and strong fatigue resistance. The finding of the vacancy-dominated fatigue mechanism at small scales extends our understanding of the metal fatigue mechanisms down to the submicron and even nanometer scales and suggests a novel interface engineering strategy by vacancy behavior modulation for fatigue-tolerance material design. [Display omitted] [ABSTRACT FROM AUTHOR]

The purpose of this study is to explore the application of numerical simulation methods in determining the design wind speed for large-span bridges situated in mountainous terrain. Compared to isolated mountains, the simulation of continuous mountain is more complex and often requires a larger computational domain. This implies that excessively high terrain model resolution can compromise computational resources. However, existing studies lack insights into selecting the optimal size of terrain extent, terrain model resolution, as well as the form of truncation curve. In this study, the impacts of terrain model resolution and size of terrain extent are discussed. In addition, the results from various transitional sections are compared against field measurement data. The results show that the UBTS transitional section form with the terrain resolution of 300 m and a diameter of 30 km of the mountain terrain can yield a reasonable simulation result at the bridge site. Furthermore, the research adopts the Xingkang bridge as a case study to outline the steps of determine the design wind speed for mountain bridges. The findings of this research offer valuable guidance for an appropriate numerical method in the practical engineering applications in determining the design wind speed for bridges in mountainous areas. • The terrain model with a horizontal geometry resolution of 300 m is adequate to get a reasonable result. • The adoption of the terrain model with a diameter of 30 km could yield a reasonable result. • The transitional form of UBTS models shows the best performance compared with the field measurements data. • The process of the determining the design wind speed of mountain bridge is illustrated. [ABSTRACT FROM AUTHOR]

[Display omitted] • Artificial neural networks provide better results than traditional methods in assessing geodiversity. • Artificial neural networks in geodiversity assessment take into account correlations between analysis criteria. • Artificial neural networks in geodiversity assessment enable the ranking of criteria quality. Probably for the second time, supervised classification (SC) using artificial intelligence – artificial neural networks (ANN) – was applied for the morphodiversity rating of the landscape, and in the Pieniny Mountains and adjacent areas, it was undoubtedly used for the first time. Vector and raster data describing the landscape characteristics in hexagonal grid cells with a size of 200 m (small diagonal) were utilized. Since high values of variables indicate high rating scores, in the traditional bonitation procedure (Aggregating Rating Method; AR), standardized values of variables are summed. However, supervised classification can associate individual bonitation degrees with classes, considering the interdependence between variables to a greater extent and allowing for the elimination of less informative variables. As choosing patterns for multiple classes seemed less credible, only two classes were defined: morphodiverse and non-morphodiverse. Subsequently, in several variants with different subsets of variables, activation functions of neuron in output layers assigned to the morphodiverse class were discretized into 2 and 5 categories, resulting in 2- and 5-class rating sets. The results of the 2-class ratings were positively verified using the Terrain Relief model (TR) reflecting the potential morphodiversity, while the results of the 5-class ratings were verified by comparison with the boundaries of the Pieniny National Park and Poprad Landscape Park. It was observed that high rating scores appear in mountainous areas or where rocks are present, indicating protected areas, excluding those with gentle landscapes and without klippen The latter areas were protected not for morphodiversity but for biodiversity. Due to the high variability of ratings obtained using SC-ANN and the AR methods, clustering was performed to facilitate their comparison. It was found that in the SC-ANN approach, areas where ratings are uncertain are significantly smaller than in the AR approach. This observation was confirmed by comparison with the TR model. This suggests that the SC-ANN metod operate more efficiently, allowing for a better assessment of the values of abiotic landscape components and, consequently, better protection of environmentally valuable areas. A significant advantage of the SC-ANN methods was the identification and elimination of variables carrying little information. This revealed the most valuable, informative variables, subsequently used for calculations. Their frequencies ranged from 16 to 25 %, and only in one case did they reach 60 % of the original variable count. The three best variables: the presence of klippen, slope steepness, and elevation, were repeated among different sets of informative features. The conducted research allows recommending the SC-ANN method for assessing morphodiversity. [ABSTRACT FROM AUTHOR]

The Mesozoic syn-rift sediments of the Bredasdorp Sub-basin were deposited during the structural inversion of the orogenic Cape Fold Belt (CFB), a crucial time during the break-up of Gondwana. The Late Jurassic to Early Cretaceous non-marine to marine sediments of the Bredasdorp Sub-basin were studied to infer their composition, parent-rock lithologies, tectonic settings and their dynamic response to tectonic perturbations. The knowledge on the provenance terrains in the Bredasdorp Sub-basin is poorly understood and therefore this research shed light on these provenance terrains. Petrographic quantitative analysis revealed that the mineralogical composition of the sediments comprises mainly of litho-quartzose and feldspatho-litho-quartzose sediments. Modal petrographic data indicates a recycled orogen provenance on QFL plots suggesting the occurrence of a collisional provenance terrain. This setting can be interpreted as the reactivation of the CFB structures eroding the Bokkeveld Group (and younger Karoo Supergroup) and the Table Mountain Group metasediments (and Pre-Cape sediments). The shedding of these sediments in the Bredasdorp Sub-basin were coeval with the deposition of the D-V, V-BUSM and BUSM-1AT1 'informal' sequences. Furthermore, an evolving recycled provenance from sedimentaclastic (un-dissected) to basementaclastic (dissected) sediments are proposed and could be a defining characteristic to the enigmatic offshore Jurassic-Cretaceous stratigraphic nomenclature. During the deposition of the D-V Sequence, a spatial variation in provenance due to intrabasinal uplifted fault blocks (possibly reactivated shear zones) occurred between the erosion of the Bokkeveld Group (and Karoo Supergroup) and the Table Mountain Group (TMG) metasediments. The deposition of the V-BUSM Sequence showed a similar compositional trend within their provenance terrain but showed a stronger correlation to an increased quartz and feldspar content. This is possibly due to the erosion of the dominant TMG, which was further supported by the occurrence of distinct type 3 polycrystalline quartz. The deposition of the BUSM-1AT1 sequence saw an increase in plutonic lithic fragments and feldspar content, indicative of an igneous source, which was attributed to the erosion of the proximal Cape Granite Suite. This distinction is crucial in creating a unifying stratigraphic nomenclature for the Jurassic-Cretaceous sequences of South Africa. A dynamic recycled orogen is envisaged for the Bredasdorp Sub-basin and therefore the use of these type of dynamic models should be incorporated in provenance models especially if there is a well-documented geological setting. • Syn-rift deposits in the Bredasdorp sub-basin were deposited during structural inversion of the Cape Fold Belt (CFB). • Sediments were classified as litho-Quartzose and feldspatho-litho-Quartzose sandstones. • An evolving recycled provenance from sedimentaclastic (undissected) to basementaclastic (dissected) sediments is proposed for the Bredasdorp Sub-basin, offshore South Africa. • Recycled provenance models and terrains can still be evaluated through petrographic data. [ABSTRACT FROM AUTHOR]

• The performance of 2D LiDAR SLAM in simulated orchards is evaluated. • Three typical algorithms Hector, GMapping, and Cartographer are investigated. • A scalable terrain simulation model is built with adjustable roughness. • Evaluation metrics are localization/mapping errors and CPU/memory usage. • Adaptability to terrain roughness, LiDAR model, and orchard size is evaluated. Accurate localization is a prerequisite for developing autonomous mobile orchard robots. Simultaneous localization and mapping (SLAM) is an efficient technique for localizing robots in global navigation satellite system (GNSS)-denied scenarios. Light detection and ranging (LiDAR) is one of the most crucial sensors used for environment perception. Two-dimensional (2D) LiDAR SLAM has been successfully applied in various indoor scenes to construct flat maps and estimate robot trajectories. In this paper, the performances of three representative 2D LiDAR SLAM algorithms, namely, Hector, GMapping, and Cartographer, in semi-structured orchard environments simulated in Gazebo are analysed. A hierarchical terrain modelling method is proposed to generate scalable orchard terrain with adjustable roughness. The adaptability of the three algorithms to terrain roughness, LiDAR, and orchard size is evaluated in terms of the localization error, mapping error, CPU usage, and memory usage. The experimental results show that Cartographer has the highest location and mapping accuracy, followed by GMapping and Hector. However, Hector requires the least computational resources, followed by Cartographer and GMapping. In a 50 m × 50 m orchard with an elevation difference of 15 cm, Cartographer achieved a localization error of 8.14 cm and a mapping error of 8.43 cm at a 4 cm map resolution. In addition, Hector has the highest requirements for the maximum range and field-of-view (FOV) of LiDAR, and GMapping is most susceptible to severe uneven terrain conditions and has the worst scalability for large-scale orchards. [ABSTRACT FROM AUTHOR]

Intra-articular (IA) glucocorticoids (GC) are commonly used for clinical management of both osteoarthritis and rheumatoid arthritis, but their efficacy is limited by the relatively short duration of action and associated side effects. To provide sustained efficacy and to improve the safety of GCs, we previously developed a N -(2-hydroxypropyl)methacrylamide (HPMA) copolymer-based dexamethasone (Dex) prodrug. Serendipitously, we discovered that, by increasing the Dex content of the prodrug to unusually high levels, the aqueous solution of the polymeric prodrug becomes thermoresponsive, transitioning from a free-flowing liquid at 4 °C to a hydrogel at 30 °C or greater. Upon IA injection, the prodrug solution forms a hydrogel (ProGel-Dex) that is retained in the joint for more than 1 month, where it undergoes gradual dissolution, releasing the water-soluble polymeric prodrug. The released prodrug is swiftly internalized and intracellularly processed by phagocytic synoviocytes to release free Dex, resulting in sustained amelioration of joint inflammation and pain in rodent models of inflammatory arthritis and osteoarthritis. The low molecular weight (6.8 kDa) of the ProGel-Dex ensures rapid renal clearance once it escapes the joint, limiting systemic GC exposure and risk of potential off-target side effects. The present study illustrates the translational potential of ProGel-Dex as a potent opioid-sparing, locally delivered adjuvant analgesic for sustained clinical management of arthritis pain and inflammation. Importantly, the observed thermoresponsive properties of the prodrug establishes ProGel as a platform technology for the local delivery of a broad spectrum of therapeutic agents to treat a diverse array of pathological conditions. [Display omitted] • HPMA copolymer-based dexamethasone prodrug demonstrates thermoresponsive properties. • The thermoresponsive prodrug (ProGel-Dex) can be intraarticularly administered. • ProGel-Dex forms hydrogel and remains in the joint for more than one month. • ProGel-Dex provides sustained pain relief in three models of arthritis. • ProGel-Dex does not have any measurable glucocorticoid side effects. [ABSTRACT FROM AUTHOR]

• A framework for dynamic simulation of vehicle-terrain systems is discussed. • We develop and implement a cone index-based (CI) model for dynamics simulation. • CI model does not show oscillations and reaches the steady state smoothly. • We compare the CI model to the existing Wong-Reece models. • Methods qualitatively agree in transient states and maximum tractive effort. Simulation of wheel-ground and vehicle-ground interactions is very important in many applications. Achieving accuracy and efficiency is challenging for both soft and hard terrains. This is not only because of the simulation and numerical challenges, but also due to the questionable nature of the existing terrain models. For example, the most widely used terramechanics model is not a representative constitutive relation for a full range of dynamic conditions and applications, but rather a parametrization of steady state conditions. In general, the selection and development of the proper constitutive model and the parametrization of the ground properties are very challenging. Here, we present a unified framework for general wheel-ground interaction which can be used with different terramechanics models. The framework is based on a complementarity formulation and also uses the concept of kinematic constitutive relations, beside the other known concepts for modelling and parametrizing the soil properties. The framework makes it possible to consider the appropriate modelling of the terrain for a broad range of dynamic behaviours and simulation conditions. We will illustrate the material with several examples for off-road conditions. [ABSTRACT FROM AUTHOR]

• An overview of the spectrum of vehicle mobility terramechanics models is presented. • A literature review of macro-scale vehicle mobility terramechanics models is presented. • The requirements for NG-NRMM macro-scale terramechanics models are presented. • A prototype software tool which satisfies the NG-NRMM requirements is presented. The US army along with NATO member and partner nations' militaries need an accurate software tool for predicting ground vehicle mobility (such as speed-made-good and fuel-consumption) on world-wide terrains where military vehicles may be required to operate. Currently, the NATO Reference Mobility Model (NRMM) is the only NATO recognized tool for assessing ground vehicle mobility. NRMM was developed from the 1960s to the 1980s and relies on steady-state empirical formulas which may not be accurate for new military ground vehicles. A NATO research task group (RTG-248) was established from 2016 to 2018 to develop the NG-NRMM (next-generation NRMM) software tool requirements and an NG-NRMM prototype which uses high-fidelity "simple" or "complex" terramechanics models for the terrain/soil along with modern 3D multibody dynamics software tools for modeling the vehicle. NG-NRMM Complex Terramechanics (CT) models are those that utilize full 3D soil models capable of predicting the 3D soil reaction forces on the vehicle surfaces (including tires, tracks, legs, and under body) and the 3D flow and deformation of the soil including both elastic and plastic deformation under any 3D loading condition. In Part 1 of this paper, an overview of the full spectrum of terramechanics models from the highest fidelity to the lowest fidelity is presented along with a literature review of CT ground vehicle mobility models. [ABSTRACT FROM AUTHOR]

This article examines the use of the Grob G 115E simulator (GO simulator) in Air Force elementary flight training, its technical features, and their impact on various areas of training. Questions about the use of the GO simulator will be answered through expert interviews and a user experience survey for flight instructors. In this way, the usefulness of the simulator was investigated. According to the results obtained, the GO simulator and simulator training in general are an invaluable part of flight training. The realistic cockpit environment and avionics of the GO simulator, combined with precise terrain modeling and good maneuverability, create a high-performance entity capable of meeting the requirements of basic flight training. According to the user experience of flight instructors, the simulator is excellent in its function and, above all, easy to use and reliable. [ABSTRACT FROM AUTHOR]

The real-time rendering of large-scale terrain scenes has been a challenge and is a popular research topic in the fields of 3D games and virtual reality. To fully utilize GPU features, this paper proposes a real-time rendering algorithm for large-scale regular grid terrain based on GPU Tessellation. The CPU processes a coarse-grained quadtree to generate terrain patches and then passes the patches to the GPU after view culling. Then, the GPU refines the terrain by using GPU Tessellation and displacement mapping. The most important advantage of our method is that during the tessellation stage, a new rule that the distance, screen space projection error and variance of the height, as the standard of terrain roughness, is designed. During the tessellation stage, the distance, screen space projection error and variance of the height, as the standard of terrain roughness, are considered. The experimental results show that our algorithm can greatly reduce the CPU processing time and main memory space requirement, and fully utilize the new features of the GPU; In conclusion, the proposed approach can render large-scale terrain with high-precision in real-time. [ABSTRACT FROM AUTHOR]

We show a fractal surface generation method that, unlike other methods, generates both random and deterministic fractals that model natural and architectural elements. The method starts with a succession of sets of sites, which determine, by means of a metric, a succession of Voronoi tessellations of the region where the fractal is defined. For each element of the tessellation sequence we define a tessellation function which depends on each tile. This generates a succession of tessellation functions that will be the parameter of the same seed function. Finally, the fractal is generated by a weighted sum of the seed function evaluated on each value of the succession of parameters. If the sites used to generate the Voronoi tessellation are random, natural elements such as mountains, craters, lakes, etc. are generated; if they are deterministic, architectural and decorative elements are generated. In addition, the designers can control the morphology of the generated fractal by simply varying the metric. • Procedural method, easy to implement, which gives designers a wide range of control. • Based on the sum of functions over a succession of Voronoi tessellation. • The Voronoi tessellation can be random or deterministic. • The method generates random and deterministic fractal surfaces indistinctly. [ABSTRACT FROM AUTHOR]

Flow direction algorithms have important application in attracting geomorphic features and topographic attributes, which serve as inputs for some hydrological and topographical models. Evaluating flow direction algorithms is of great significance and often conducted on synthetic surfaces instead of real digital elevation models for free of approximation errors. However, most widely-used synthetic surfaces are too simplified to represent complex topographical relief of real-world terrains. For this, this work applies a complex synthetic surface of modified Himmelblau's function (HF) to simulate sophisticated terrains encountered in real landscapes. HF surface is spatially smooth and continuous with four hilltops and one valley, where plan curvatures are clustered mainly from −0.1 to 0.1. In addition, a slope line-based discretization numerical (SLDN) approach is designed for obtaining numerical solution to theoretical total contributing area (TCA) on synthetic surfaces of non-integrable slope lines (e.g. HF surface). TCAs estimated by several flow direction algorithms are compared with SLDN-derived TCA quantitatively. Results indicate that the largest and smallest mean size errors are obtained by Random eight-node (Rho8) (i.e. 82.6 %) and Freeman multiple flow direction (FMFD) (i.e. 17.9 %), while the largest and smallest mean extent errors by Eight drainage directions (D8) (i.e. 128.2 %) and Eight drainage directions, least transversal deviation (D8-LTD) (i.e.55.4 %). Most mean errors are larger than 20.0 %, which may not be satisfactory in practice. This work can provide a reference for flow direction algorithms application in digital terrain analysis, and therefore improve accuracy of hydrological, geological and geomorphological models. [Display omitted] • Characteristics of the complex HF surface are comprehensively investigated. • An SLDN approach is used to obtain theoretical TCAs on complex synthetic surfaces. • D8-LTD and FMFD are respectively the best SFD and MFD algorithms on HF surface. [ABSTRACT FROM AUTHOR]

[Display omitted] The Na V 1.8 channel, mainly found in the peripheral nervous system, is recognized as one of the key factors in chronic pain. The molecule VX-150 was initially promising in targeting this channel, but the phase II trials of VX-150 did not show expected pain relief results. By analyzing the interaction mode of VX-150 and Na V 1.8, we developed two series with a total of 19 molecules and examined their binding affinity to Na V 1.8 in vitro and analgesic effect in vivo. One compound, named 2j , stood out with notable activity against the Na V 1.8 channel and showed effective pain relief in models of chronic inflammatory pain and neuropathic pain. Our research points to 2j as a strong contender for developing safer pain-relief treatments. [ABSTRACT FROM AUTHOR]

A novel and efficient approach for modeling irregular domain boundaries and enforcing complex land-based constraints in wind farm layout optimization is presented. The presented method can be used to enforce constraints and represent complex domains for which an analytical expression is not available. The developed approach uses support vector domain description to obtain an analytical expression of the domain from data points sampled from the various regions for wind turbine placements. Such an analytical, continuous, differentiable description can then be used for wind farm layout optimization using gradient based and non-gradient based optimization algorithms. The applicability of the method was demonstrated on a wind farm layout optimization problem where several regions of the terrain were restricted. The method was shown to accurately and efficiently model regular, irregular, convex, non-convex and discontinuous domains/regions using only scattered data sampled from the domains. An efficient method for terrain modeling and interpolation is also presented. The proposed interpolation method uses quadtree decomposition to decompose the large interpolation problem into several smaller interpolation problems thereby reducing the complexity of the interpolation. The framework developed (libSVDD) is also made publicly available. • An efficient method for modeling complex terrain boundaries is presented. • The method is validated on regular, irregular, convex, non-convex and disconnected boundaries. • Optimization is performed to demonstrated the use of the method in wind farm layout design. • Efficient terrain interpolation and modeling approach using decomposition is presented. • The developed methods have been released for public use. [ABSTRACT FROM AUTHOR]

• Discrete element soil model with surface friction, cohesion and rolling resistance. • Strength measured using triaxial test and cone penetrometer on numerical soils. • The relevant space of frictional and frictional-cohesive soils can be represented. • Simulation of rut formation from a heavy vehicle with different loads and soil strengths. • Particle-based terrain models are valid for studying soil response from heavy vehicles. This paper addresses the challenges of creating realistic models of soil for simulations of heavy vehicles on weak terrain. We modelled dense soils using the discrete element method with variable parameters for surface friction, normal cohesion, and rolling resistance. To find out what type of soils can be represented, we measured the internal friction and bulk cohesion of over 100 different virtual samples. To test the model, we simulated rut formation from a heavy vehicle with different loads and soil strengths. We conclude that the relevant space of dense frictional and frictional-cohesive soils can be represented and that the model is applicable for simulation of large deformations induced by heavy vehicles on weak terrain. [ABSTRACT FROM AUTHOR]

• Smoothed-Particle Hydrodynamics technique for soil modelling. • Finite Element Analysis for tire modelling. • Moist soil modelling using two-phase interaction and water pressurization. • Calibration of soil by pressure-sinkage and shear-strength tests. • Effect of moisture on shear, sinkage characteristics and tire cornering stiffness. This paper focuses on predicting and analyzing the tire-moist terrain interaction. The moist terrain (sand) is modelled using Smoothed-Particle Hydrodynamics (SPH) technique. The SPH basic interpolation technique is described, and the necessary interpolation equations are implemented. The soil is modelled using the hydrodynamic elastic-plastic material, while the water is modelled using Murnaghan equation of state. The numerical interaction between both materials is defined using Darcy's law. The soil moisturizing technique consists of layering water particles on top of sand particles and pressurizing the water into the sand. The moisturizing technique is examined using the direct shear-strength test, and validated against physical measurement carried out in a laboratory under similar soil conditions and bulk density. Finally, the results and the effect of moisture content on tire-moist terrain interaction are discussed and investigated using a previously modelled and validated off-road truck tire size 315/80R22.5. [ABSTRACT FROM AUTHOR]

• 3D models are retrieved with respect to the reliefs impressed on their surface. • A new benchmark of 3D models with geometric reliefs derived from 11 real textures. • Analysis of the retrieval performance of methods that participated to SHREC2020. • An extensive comparison of eight methods and twenty runs. • These methods are based on features or transfer learning. This paper presents the methods that have participated in the SHREC'20 contest on retrieval of surface patches with similar geometric reliefs and the analysis of their performance over the benchmark created for this challenge. The goal of the context is to verify the possibility of retrieving 3D models only based on the reliefs that are present on their surface and to compare methods that are suitable for this task. This problem is related to many real world applications, such as the classification of cultural heritage goods or the analysis of different materials. To address this challenge, it is necessary to characterize the local "geometric pattern" information, possibly forgetting model size and bending. Seven groups participated in this contest and twenty runs were submitted for evaluation. The performances of the methods reveal that good results are achieved with a number of techniques that use different approaches. [ABSTRACT FROM AUTHOR]