Search Results (156)

This work presents a solving method for problems of Ambrosetti-Prodi type involving p-Laplacian and p-pseudo-Laplacian operators by using adequate variational methods. A variant of the mountain pass theorem, together with a kind of Palais-Smale condition, is involved in order to obtain and characterize solutions for some mathematical physics issues. Applications of these results for solving some physical chemical problems evolved from the need to model real phenomena are displayed. Solutions for Dirichlet problems containing these two operators applied for modeling critical micellar concentration, as well as the volume fraction of liquid mixtures, have been drawn. Full article

This study aims to reveal the impact mechanisms of five typical topographic habitats in the Sanjiangyuan region (sunny slope, depression, shady slope, mountain pass, and transitional zone) on the characteristics and functions of rhizosphere soil fungal communities of Kengyilia thoroldiana, and to elucidate the association patterns between these communities and soil physicochemical factors. The species composition, diversity, molecular co-occurrence network, and FUNGuild function of microbial communities were investigated based on high-throughput sequencing technology. By combining the Mantel test and RDA analysis, the key habitat factors affecting the structure of the soil fungal community in the rhizosphere zone of Kengyilia thoroldiana were explored. The results showed that: ① The composition of the soil fungal community in the rhizosphere of Kengyilia thoroldiana in five topographical habitats showed significant differentiation characteristics: the number of OTUs in H2 (depression) and H5 (transitional zone) habitats was the highest (336 and 326, respectively). Habitats H2 showed a significant increase in the abundance of Ascomycota and Mortierellomycota and a significant decrease in the abundance of Basidiomycota compared to the other topographical habitats. ② The diversity and aggregation degree of the soil fungal community in the rhizosphere of Kengyilia thoroldiana in five topographical habitats showed differences. ③ Cluster analysis showed that the rhizosphere soil fungi in five topographical habitats of Kengyilia thoroldiana could be divided into two groups, with H2, H4 (mountain pass), and H5 habitats as one group (group 1) and H1 and H3 (shady slope) as one group (group 2). ④ The characteristics of the Kengyilia thoroldiana community and the physical and chemical properties of rhizosphere soil in five topographical habitats were significantly different, and the height, coverage, biomass, and soil nutrient content were the highest in H2 and H5 habitats, while lower in H1 and H3 habitats, with significant differences (p < 0.05). ⑤ Redundancy analysis showed that soil water content was the main driving factor to change the structure and function of the soil fungal community in the rhizosphere of Kengyilia thoroldiana in five topographic habitats in the Sanjiangyuan region. This study demonstrated that topographic habitats affected the species composition, functional pattern, and ecosystem service efficiency of the Kengyilia thoroldiana rhizosphere fungal community by mediating soil environmental heterogeneity, which provides microbial mechanistic insights for alpine meadow ecosystem protection. Full article

Rockfalls on railways are considered a natural disaster under the topic of landslides. It is an event that varies regionally due to landforms and climate. In addition to traffic density, the Karabük–Yenice railway line also passes through mountainous areas, river crossings, and experiences heavy seasonal rainfall. These conditions necessitate the implementation of proactive measures to mitigate risks such as rockfalls, tree collapses, landslides, and other geohazards that threaten the railway line. Undetected environmental events pose a significant threat to railway operational safety. The study aims to provide early detection of environmental phenomena using vibrations emitted through fiber optic cables. This study presents a real-time hazard detection system that integrates Distributed Acoustic Sensing (DAS) with a hybrid ensemble learning model. Using fiber optic cables and the Luna OBR-4600 interrogator, the system captures environmental vibrations along a 6 km railway corridor in Karabük, Türkiye. CatBoosting, Support Vector Machine (SVM), LightGBM, Decision Tree, XGBoost, Random Forest (RF), and Gradient Boosting Classifier (GBC) algorithms were used to detect the incoming signals. However, the Voting Classifier hybrid model was developed using SVM, RF, XGBoost, and GBC algorithms. The signaling system on the railway line provides critical information for safety by detecting environmental factors. Major natural disasters such as rockfalls, tree falls, and landslides cause high-intensity vibrations due to environmental factors, and these vibrations can be detected through fiber cables. In this study, a hybrid model was developed with the Voting Classifier method to accurately detect and classify vibrations. The model leverages an ensemble of classification algorithms to accurately categorize various environmental disturbances. The system has proven its effectiveness under real-world conditions by successfully detecting environmental events such as rockfalls, landslides, and falling trees with 98% success for Precision, Recall, F1 score, and accuracy. Full article

In order to evaluate spatial pollution patterns of the Shaying River and assess human health risk, thirty-three sampling points were established in different reaches of the upper, middle, and lower reaches of the Shaying River. According to the difference in human activities and land use types, the sampling points were artificially divided into three areas: mountainous area, urban area, and agricultural area. Water samples and sediments were collected at each sampling site, and the physicochemical parameters of the water at each site were measured simultaneously. The nutrient content of water samples and the heavy metal content of sediments were measured in the laboratory. The water pollution status of the Shaying River, as well as the status of heavy metal pollution and its associated risk to human health, were assessed and analyzed using the Water Quality Index (WQI) method, principal component analysis (PCA) method, potential ecological risk index method, and health risk assessment method, respectively. The results of the Water Quality Index indicated that the water quality of the Shaying River was moderate, with the reaches in the urban area being more polluted, the agricultural area being the second most polluted, and the mountainous area being in better condition. The results of the principal component analysis showed that soluble ions, organic matter, and nutrients were the main factors contributing to water pollution in the Shaying River, and there was significant variability in the factors contributing to water pollution in different regions, with human activities being the main cause of this variation. The results of a potential ecological risk assessment of heavy metals in sediments showed that heavy metal pollution in the water bodies of the Shaying River was serious and had significant spatial variability. Mountain reaches were the most polluted, followed by agricultural reaches, and urban reaches were the least polluted. The results of the health risk assessment showed that non-carcinogenic risks of heavy metals in different reaches of the Shaying River were within acceptable limits, while carcinogenic risks in agricultural areas exceeded thresholds. Among them, agricultural areas had the highest health risk, with Cr being the most carcinogenic heavy metal and Pb and Cr being the most non-carcinogenic heavy metals. The assessment also found that children’s carcinogenic risk was 8.4 times higher than adult males and 7.3 times higher than adult females. This study involves the typical diverse areas where the Shaying River passes, in order to provide data support and a theoretical basis for environmental protection of the Shaying River Basin. Full article

This paper is devoted to a class of general nonlocal fourth-order elliptic equation with concave–convex nonlinearities. First, using the $Z_2$-mountain pass theorem in critical point theory, we obtain the existence of infinitely many large energy solutions. Then, using the dual fountain theorem, we prove that the equation has infinitely many negative energy solutions, whose energy converges at 0. Our results extend and complement existing findings in the literature. Full article

The distribution of suitable habitats for medicinal plants is affected by climate, soil, land use, and other factors. Arnebiae Radix, an important traditional Chinese medicinal resource in Xinjiang, includes Arnebia euchroma (Royle) I. M. Johnst. and Arnebia guttata Bunge and is at risk of over-exploitation. This study predicted suitable planting areas by integrating habitat and phytochemical suitability using the MaxEnt model and ArcGIS. The AUC values for A. euchroma and A. guttata were 0.977 and 0.952, with TSS values of 0.829 and 0.725, respectively, validating the high accuracy of the prediction model. Under the current scenario, the areas of suitable habitats for A. euchroma and A. guttata were 108,914 and 176,445 km², mainly distributed along the main mountains in Xinjiang. Under future climate scenarios, the suitable habitat area of A. euchroma increased by 11–18%, except in the ssp126-2090s scenario, while the suitable habitat area of A. guttata area decreased by 3–18%. Both species were influenced by land use/land cover and soil available nitrogen content; additionally, A. euchroma was affected by the precipitation in the driest month, and A. guttata by the mean diurnal range. The content of secondary metabolites was positively correlated with habitat suitability, with soil factors contributing 35.25% to the total secondary metabolite content. Their suitable habitats predominantly occur in grasslands (42–82%). As habitat and phytochemical suitability distributions aligned, the eastern and western sides of the northern Kunlun Mountain Pass emerged as key areas for cultivation. This research can provide a scientific foundation for selecting optimal planting regions for the two Arnebia species. Full article

The Gobi Wall is a 321 km-long structure made of earth, stone, and wood, located in the Gobi highland desert of Mongolia. It is the least understood section of the medieval wall system that extends from China into Mongolia. This study aims to determine its builders, purpose, and chronology. Additionally, we seek to better understand the ecological implications of constructing such an extensive system of walls, trenches, garrisons, and fortresses in the remote and harsh environment of the Gobi Desert. Our field expedition combined remote sensing, pedestrian surveys, and targeted excavations at key sites. The results indicate that the garrison walls and main long wall were primarily constructed using rammed earth, with wood and stone reinforcements. Excavations of garrisons uncovered evidence of long-term occupation, including artifacts spanning from 2nd c. BCE to 19th c. CE. According to our findings, the main construction and usage phase of the wall and its associated structures occurred throughout the Xi Xia dynasty (1038–1227 CE), a period characterized by advanced frontier defense systems and significant geopolitical shifts. This study challenges the perception of such structures as being purely defensive, revealing the Gobi Wall’s multifunctional role as an imperial tool for demarcating boundaries, managing populations and resources, and consolidating territorial control. Furthermore, our spatial and ecological analysis demonstrates that the distribution of local resources, such as water and wood, was critical in determining the route of the wall and the placement of associated garrisons and forts. Other geographic factors, including the location of mountain passes and the spread of sand dunes, were strategically utilized to enhance the effectiveness of the wall system. The results of this study reshape our understanding of medieval Inner Asian imperial infrastructure and its lasting impact on geopolitical landscapes. By integrating historical and archeological evidence with geographical analysis of the locations of garrisons and fortifications, we underscore the Xi Xia kingdom’s strategic emphasis on regulating trade, securing transportation routes, and monitoring frontier movement. Full article

Traffic contributes nearly 25% of global greenhouse gas emissions. For designing new traffic routes and decision-making processes, it is essential to incorporate integral life cycle assessments (LCAs) to ensure sustainable solutions and to achieve the UN Sustainable Development Goals (SDGs). This study compares two fictitious routes: a typical Austrian mountain pass road (Route A) with a 3% gradient and a new route (Route B) featuring a 1000 m tunnel, reducing distance and inclines. The LCA analyzes Route B’s lifecycle, from material supply to 100-year tunnel usage, comparing it against a traffic LCA of Route A’s operational emissions. The tunnel assessment considers the New Austrian Tunneling Method, local materials, and typical geology. Traffic effects are analyzed using Austrian vehicle stock data, following EN 17472 and EN 15804 standards. The results, based on Global Warming Potential, indicate that Route B’s construction, maintenance, and utilization generate lower environmental impacts than Route A’s traffic emissions. The tunnel offers overall environmental savings, with its construction and maintenance impacts offset within approximately 10 years. Traffic usage is identified as the primary long-term emission source. This research highlights the significance of integral LCAs in creating a sustainable built environment and supporting a decision-making process in transport infrastructure construction. Full article

Tunnels are commonly found in small and enclosed environments on highways, roads, or city streets. They are constructed to pass through mountains or beneath crowded urban areas. To prevent accidents in these confined environments, lane changes, slow driving, or speeding are prohibited on single- or multi-lane one-way roads. We developed a foreground detection algorithm based on the K-nearest neighbor (KNN) and Gaussian mixture model and 400 collected images. The KNN was used to gather the first 200 image data, which were processed to remove differences and estimate a high-quality background. Once the background was obtained, new images were extracted without the background image to extract the vehicle’s foreground. The background image was processed using Canny edge detection and the Hough transform to calculate road lines. At the same time, the oriented FAST and rotated BRIEF (ORB) algorithm was employed to track vehicles in the foreground image and determine positions and lane deviations. This method enables the calculation of traffic flow and abnormal movements. We accelerated image processing using xfOpenCV on the PYNQ-Z2 and FPGA Xilinx platforms. The developed algorithm does not require pre-labeled training models and can be used during the daytime to automatically collect the required footage. For real-time monitoring, the proposed algorithm increases the computation speed ten times compared with YOLO-v2-tiny. Additionally, it uses less than 1% of YOLO’s storage space. The proposed algorithm operates stably on the PYNQ-Z2 platform with existing surveillance cameras, without additional hardware setup. These advantages make the system more appropriate for smart traffic management than the existing framework. Full article

In this paper, we have investigated the existence of normalized solutions for a class of fractional Kirchhoff equations involving nonlinearity and critical nonlinearity. The nonlinearity satisfies $L^2$-supercritical conditions. We transform the problem into an extremal problem within the framework of Lagrange multipliers by utilizing the energy functional of the equation in the fractional Sobolev space and applying the mass constraint condition (i.e., for given $m>0,$${\int }_{{\mathbb{R}}^N}{|u|}^{2}dx=m^2$). We introduced a new set and proved that it is a natural constraint. The proof is based on a constrained minimization method and some characterizations of the mountain pass levels are given in order to prove the existence of ground state normalized solutions. Full article

In the present paper, we discuss a Schrödinger–Kirchhoff equation involving the $p\left(x\right)$-Laplacian in the entire space ${\mathbb{R}}^N$. The primary focus of this article is on subcritical and critical nonlinearities. We deduce the existence of solutions by employing the mountain pass theorem in two distinct scenarios. Firstly, we discuss the equation when the potential function satisfies a weaker condition in the subcritical case. Secondly, we address the lack of compactness in the critical case without utilizing the concentration compactness principle. Full article

Oil pipelines are susceptible to significant hydraulic erosion from mountain torrents during the flood season when passing through the mountain valley area, which can lead to soil erosion on the pipe surface and expose the pipeline. Accordingly, this study centers on investigating the critical issue of the failure mechanism caused by flash flood erosion in the exposed section of oil pipelines. Both indoor testing and numerical simulation research methods are employed to analyze the flow field distribution characteristics of flash floods in proximity to an exposed pipeline. This study explores the patterns of soil loss around pipelines of varying pipe diameters, levels of exposure, and pipe flow angles. In addition, the spatial and temporal evolution mechanism of pipelines overhang development under the action of flash floods was elucidated. The experimental observations indicate that as the pipe diameter increases, the failure rate of the soil surrounding the pipe accelerates, while the erosion effect on the soil around the executives becomes more pronounced. Additionally, a larger pipe flow angle leads to a reduced soil loss in the downstream direction of the pipe. During flash flood events, the scouring action on the soil surrounding the pipe leads to rapid compression of the flow field around the pipe, while the vortex at the pipe’s bottom exacerbates soil corrosion. Additionally, the maximum pressure exerted on pipeline surfaces at pipeline flow angles of 30°, 60°, and 90° is 14,382 Pa, 16,146 Pa, and 17,974 Pa, respectively. The research results offer valuable insights into pipeline, soil, and water conservation projects in mountain valley regions. Full article

Virtual Reality (VR) has emerged as an effective technology for the dissemination of geographical knowledge due to its visual, interactive, and dynamic nature. This technology allows for adequate valorization of the territorial attributes of marginal mountain areas undergoing tertiarization processes, as it provides suggestive experiences of approach, discovery, and interpretation. All of this should result in the fortification of the conservation process against the expansion of new uses that impact the inherited landscape. In this work, the aim was to design a VR experience for the interpretation of mountains that can be used by public and private entities as a strategy for differentiation in the context of positioning for territorial development. The study area covers the mountain pass of Leitariegos and the Cueto Arbás massif (a mountain in the west of Asturias and León, Northwestern Spain), which make up a geographical unit with ecological, aesthetic, ethnographic, and historical importance. Using a VR tool, we sought to enhance the identification and interpretation of the keys that lead to the initiation and consolidation of the patrimonialization process, uncovering the processes and agents through their practices, the vectors around which the process pivots, and the conflicts in the competition for land use. Full article

Three-dimensional site modeling is an important aspect of Building Information Modeling (BIM), especially in mountainous areas. Accurate site modeling is essential for efficient construction planning and resource allocation. A key issue in site modeling is how to accurately calculate the shape of side-slopes. It involves three sub-problems: geometric representation of side-slopes, determination of fill/cut types, and intersection of side-slopes surface with the terrain surface. To address this, a two-stage method for constructing side-slope models adaptive to terrain is proposed. In the first stage, a marching algorithm along polylines is used to calculate the intersection points of the site boundary polylines with the terrain surface. These intersection points are used to segment the boundary polylines. A rule-based approach is then applied to automatically determine the fill/cut type for each segment. Subsequently, the equations of the side-slopes passing through each segment are derived using geometric principles. In the second stage, a marching algorithm along the plane is used to trace the intersection lines of side-slopes with the terrain. Finally, the side-slopes are rendered with precision by integrating the equations of each segment with the determined intersection lines. The effectiveness of the method is verified through illustrative examples. Algorithm efficiency analysis and 3D modeling illustrations have demonstrated that this method not only boasts accuracy and swift computation but also excels in the level of automation achieved in the modeling process. Full article

Grasslands are one of the most abundant and biodiverse ecosystems in the world. However, in southern European countries, the abandonment of traditional management activities, such as extensive grazing, has caused many semi-natural grasslands to be invaded by shrubs. Therefore, there is a need to characterize semi-natural grasslands to determine their aboveground primary production and livestock-carrying capacity. Nevertheless, current methods lack a realistic identification of vegetation assemblages where grassland biophysical parameters can be accurately retrieved by the inversion of turbid-medium radiative transfer models (RTMs) in fine-grained landscapes. To this end, in this study we proposed a novel framework in which multiple endmember spectral mixture analysis (MESMA) was implemented to realistically identify grassland-dominated pixels from Sentinel-2 imagery in heterogeneous mountain landscapes. Then, the inversion of PROSAIL RTM (coupled PROSPECT and SAIL leaf and canopy models) was implemented separately for retrieving grassland biophysical parameters, including the leaf area index (LAI), fractional vegetation cover (FCOVER), and aboveground biomass (AGB), from grassland-dominated Sentinel-2 pixels while accounting for non-vegetated areas at the subpixel level. The study region was the southern slope of the Cantabrian Mountains (Spain), with a high spatial variability of fine-grained land covers. The MESMA grassland fraction image had a high accuracy based on validation results using centimetric resolution aerial orthophotographs (R² = 0.74, and RMSE = 0.18). The validation with field reference data from several mountain passes of the southern slope of the Cantabrian Mountains featured a high accuracy for LAI (R² = 0.74, and RMSE = 0.56 m²·m⁻²), FCOVER (R² = 0.78 and RMSE = 0.07), and AGB (R² = 0.67, and RMSE = 43.44 g·m⁻²). This study provides a reliable method to accurately identify and estimate grassland biophysical variables in highly diverse landscapes at a regional scale, with important implications for the management and conservation of threatened semi-natural grasslands. Future studies should investigate the PROSAIL inversion over the endmember signatures and subpixel fractions depicted by MESMA to adequately address the parametrization of the underlying background reflectance by using prior information and should also explore the scalability of this approach to other heterogeneous landscapes. Full article