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Commercial vehicles frequently experience lateral interferences, such as crosswinds or side slopes, during extreme maneuvers like emergency steering and high-speed driving due to their high centroid. These interferences reduce vehicle stability and increase the risk of rollover. Therefore, this study takes a bus as the carrier and designs an anti-rollover control strategy based on mixed-sensitivity and robust $H_{\infty }$ controller. Specifically, a 7-DOF vehicle dynamics model is introduced, and the factors influencing vehicle rollover are analyzed. Based on this, to minimize excessive intervention in the vehicle’s dynamic characteristics, the lateral velocity, roll angle, and roll rate are recorded at the vehicle’s rollover threshold as desired values. The lateral load transfer rate (LTR) is chosen as the evaluation index, and the required additional yaw moment is determined and distributed to the wheels for anti-rollover control. Furthermore, to verify the effectiveness of the proposed anti-rollover control strategy, a co-simulation platform based on MATLAB/Simulink and TruckSim is developed. Various dynamic lateral interferences (side winds with different changing trends and wind speeds) are introduced, and the fishhook and J-turn maneuvers are selected to analyze and compare the proposed control strategy with a fuzzy logic algorithm. The results indicate that the maximum LTR of the vehicle is reduced by 0.11. Additionally, the lateral acceleration and yaw rate in the steady state are reduced by more than 1.8 m/s² and 15°, respectively, enhancing the vehicle’s lateral stability. Full article

With the advancement of technology, unmanned ground vehicles (UGVs) have shown increasing application value in various tasks, such as food delivery and cleaning. A key capability of UGVs is obstacle detection, which is essential for avoiding collisions during movement. Current mainstream methods use point cloud information from onboard sensors, such as light detection and ranging (LiDAR) and depth cameras, for obstacle perception. However, the substantial volume of point clouds generated by these sensors, coupled with the presence of noise, poses significant challenges for efficient obstacle detection. Therefore, this paper presents a fast obstacle detection algorithm designed to ensure the safe operation of UGVs. Building on multi-sensor point cloud fusion, an efficient ground segmentation algorithm based on multi-plane fitting and plane combination is proposed in order to prevent them from being considered as obstacles. Additionally, instead of point cloud clustering, a vertical projection method is used to count the distribution of the potential obstacle points through converting the point cloud to a 2D polar coordinate system. Points in the fan-shaped area with a density lower than a certain threshold will be considered as noise. To verify the effectiveness of the proposed algorithm, a cleaning UGV equipped with one LiDAR sensor and four depth cameras is used to test the performance of obstacle detection in various environments. Several experiments have demonstrated the effectiveness and real-time capability of the proposed algorithm. The experimental results show that the proposed algorithm achieves an over 90% detection rate within a 20 m sensing area and has an average processing time of just 14.1 ms per frame. Full article

Jet pumps are widely used in petrochemical processes, nuclear cooling, and wastewater treatment due to their simple structure, high reliability, and stable performance under extreme conditions. However, when transporting solid-laden two-phase flows, they face severe erosion problems, leading to reduced efficiency, malfunctions, or even failure. Therefore, optimizing jet pump performance and extending its service life is crucial. In this study, an experimental platform was established to conduct experiments on wall erosion in jet pumps. The CFD-DEM method was used to simulate the solid–liquid two-phase flow in the jet pump, comparing six erosion models for predicting erosion rates. The Grey Wolf Optimization algorithm was applied to calibrate model coefficients. The results indicate that the Neilson erosion model shows the best consistency with the experimental results. The inlet flow rate significantly influenced the erosion rates, while the flow rate ratio had a smaller effect. The particle concentration exhibited a nonlinear relationship with erosion, with diminishing impact beyond a certain threshold. As the factors varied, the erosion distribution tended to be uniform, but high erosion areas remained locally concentrated, indicating intensified localized erosion. Full article

Quantum entanglement as a non-local correlation between particles is critical to the transmission of quantum information in quantum networks (QNs); the key challenge lies in establishing long-distance entanglement transmission between distant targets. This issue aligns with percolation theory, and as a result, an entanglement distribution scheme called “Classical Entanglement Percolation” (CEP) has been proposed. While this scheme provides an effective framework, “Quantum Entanglement Percolation” (QEP) indicates a lower percolation threshold through quantum preprocessing strategies, which will modify the network topology. Meanwhile, an emerging statistical theory known as “Concurrence Percolation” reveals the unique advantages of quantum networks, enabling entanglement transmission under lower conditions. It fundamentally belongs to a different universality class from classical percolation. Although these studies have made significant theoretical advancements, most are based on an idealized pure state network model. In practical applications, quantum states are often affected by thermal noise, resulting in mixed states. When these mixed states meet specific conditions, they can be transformed into pure states through quantum operations and further converted into singlets with a certain probability, thereby facilitating entanglement percolation in mixed state networks. This finding greatly broadens the application prospects of quantum networks. This review offers a comprehensive overview of the fundamental theories of quantum percolation and the latest cutting-edge research developments. Full article

The Constellation Observing System for Meteorology, Ionosphere, and Climate 2 (COSMIC-2) collects data covering latitudes primarily between 40 degrees north and south, providing abundant data for tropical cyclone (TC) research. The radio occultation data provide valuable information on the boundary layer. However, quality control of the data within the boundary layer remains a challenging issue. The aim of this study is to obtain a more accurate COSMIC-2 radio occultation (RO) dataset through quality control (QC) and use this dataset to validate warm core structures and explore the planetary boundary layer (PBL) structures of TCs. In this study, COSMIC-2 data are used to analyze the distribution of the relative local spectral width (LSW) and the confidence parameter characterizing the random error of the bending angle. An LSW less than 20% is set as a data QC threshold, and the warm core and PBL composite structures of TCs at three intensities in the Northwest Pacific Ocean are investigated. We reproduce the warm core intensity and warm core height characteristics of TCs. In the radial direction of the typhoon eyewall, the impact height of the PBL increases from 3.45 km to 4 km, with the tropopause ranging from 160 hPa to 100 hPa. At the bottom of the troposphere, the variations in the positive and negative bias between the RO-detected and background field bending angles correspond well to the PBL heights, and the variations in the positive bias between the RO-detected and background field refractivity reach 14%. This research provides an effective QC method and reveals that the bending angle is sensitive to the PBL height. Full article

The complex topography of deep sea presents numerous challenges for the accurate exploration of sub-bottom profiles. These include real-time tracking of seafloor reflectors, acquisition and storage of deep-sea long-term reflection data, and splicing of successive profiles. Based on the actual survey data of deep sea, we have developed automatic positioning and noise suppression algorithms, namely the double-difference threshold of proximity points. Furthermore, we have created automatic algorithms, namely content expansion and group data moving, based on extremum in seafloor’s depth. These have been designed to automatically suppress the random noise and effectively splice the sub-bottom profile data in deep water. The aforementioned processing techniques facilitate the enhancement of the quality of deep-water sub-bottom profile data, thereby enabling the provision of a comprehensive and successively long profile for interpretation in the context of deep-water sub-bottom profile data. Full article

The steel ball, as a key rolling element in mechanical equipment, directly affects the performance and service life of the bearing through its surface quality. Traditional methods for detecting surface defects on steel balls often face challenges in efficiency and stability. They struggle with three-dimensional surfaces and are easily affected by noise interference. This paper proposes a defect detection method for the steel ball surface based on Axial Cone mirror expansion and Improved Image Difference (ACID). The axial cone mirror unfolds the entire surface of the steel ball, allowing complete surface images to be obtained with just two captures. This simplifies the acquisition process and increases efficiency. The improved image difference method, combined with adaptive thresholding and adjacent frame difference techniques, effectively reduces noise interference. It enhances both the accuracy and robustness of defect detection. Frequent threshold adjustments and unstable detection, common in traditional methods, are avoided. Experimental results demonstrate that the ACID-based detection method surpasses traditional methods in terms of efficiency and accuracy. The improved method significantly reduces the missed detection rate. For example, the detection rates for cluster, scratch, and stain have increased from 86%, 80%, and 84% to 98%, 96%, and 98%, respectively. Moreover, the improved method reduces noise interference, avoids frequent threshold adjustments, simplifies the operation process, and shows higher stability and robustness in complex background conditions. Full article

Additive manufacturing of advanced materials has become widespread, encompassing a range of materials including thermoplastics, metals, and ceramics. For the ceramics, the complete production process typically involves indirect additive manufacturing, where the green ceramic part undergoes debinding and sintering to achieve its final mechanical and thermal properties. To avoid unnecessary energy-intensive steps, it is crucial to assess the internal integrity of the ceramic in its green stage. This study aims to investigate the use of active thermography for defect detection. The approach is to examine detectability using two benchmarks: the first focuses on the detectability threshold, and the second on typical defects encountered in 3D printing. For the first benchmark, reflection and transmission modes are tested with and without a camera angle to minimize reflection. The second benchmark will then be assessed using the most effective configurations identified. All defects larger than 1.2 mm were detectable across the benchmarks. The method can successfully detect defects, with transmission mode being more suitable since it does not require a camera angle adjustment to avoid reflections. However, the method struggles to detect typical 3D-printing defects because the minimum defect size is 0.6 mm, which is the size of the nozzle. Full article

In the context of armed conflicts, regions often face infrastructure destruction and economic difficulties. The development of tourism can be a key factor in recovery and economic growth. Geospatial platforms for interactive charitable tourism offer a promising solution for attracting tourists and stimulating the development of affected regions. The aim of this study is to assess the effectiveness of geospatial platforms for interactive charitable tourism as a tool for attracting tourists and promoting the recovery and development of regions affected by armed conflicts. This study employed regression and correlation analysis methods. The analysis revealed significant positive correlations for all variables. The correlation coefficient for audience reach was 0.75, for the effectiveness of attracting donations—0.8, for the economic impact on the region—0.9, for user interaction with the platform—0.85, for platform sustainability—0.78, and for social impact—0.92. The t-statistic values exceeded the critical thresholds, and the p-values were below 0.05, confirming the statistical significance of the results. The coefficient of determination was 0.91, indicating a high explanatory power of the model. For the four obtained clusters, approaches to the development and use of geospatial platforms were justified. For regions of Cluster 1 with high audience reach (0.75) and moderate effectiveness of attracting donations (0.8), it is recommended to use technologies to improve connectivity and effectively promote their strengths. For regions of Cluster 2 with high sustainability and high tourism potential (high social impact = 0.92), it is necessary to include advanced geospatial solutions to increase visitor engagement and optimize recovery strategies, building on existing strengths to attract more tourists and stimulate sustainable development. For regions of Cluster 3, significant investments are required both in geospatial platforms and in tourism infrastructure to benefit from high tourism potential (economic impact on the region = 0.9). Strategic development and targeted marketing should be a priority to attract tourists and stimulate economic growth. Regions of Cluster 4 with low sustainability and tourism potential (low user interaction with the platform = 0.85 and platform sustainability = 0.78) require comprehensive support, as they are in a crisis situation. Full article

The rapid desorption of gas in coal is an important cause of gas over-limit and outbursts. In order to explain the causes of coal and gas outbursts induced by vibration, this paper studies the gas desorption experiments of tectonic coal with different particle sizes and different adsorption equilibrium pressures under 0~50 Hz vibration. High-pressure mercury intrusion experiments were used to measure the changes in pore volume and specific surface area of tectonic coal before and after vibration, revealing the control of pore structure changes on the initial desorption capacity of gas. Additionally, from the perspective of energy transformation during coal and gas outbursts, the effect of vibration on the process of coal and gas outbursts in tectonic coal was analyzed. The results showed that tectonic coal has strong initial desorption capacity, desorbing 29.58% to 54.51% of the ultimate desorption volume within 10 min. Vibration with frequencies of 0~50 Hz increased both the gas desorption ratios and desorption volume as the frequency increased. The initial desorption rate also increased with the vibration frequency, and vibration can enhance the initial desorption capacity of tectonic coal and delay the attenuation of desorption rate. Vibration affected the changes in the initial gas desorption rate and desorption rate attenuation coefficient by increasing the pore volume and specific surface area, with the changes in macropores and mesopores primarily affecting the initial desorption rate and 0~10 min desorption ratios, while the changes in micropores and minipores mainly influenced the attenuation rate of the desorption rate. Vibration increased the free gas expansion energy of tectonic coal as the frequency increased. During the incubation and triggering processes of coal and gas outbursts, vibration has been observed to accelerate the fragmentation and destabilisation of the coal body, while simultaneously increasing the gas expansion energy to a point where it reaches the threshold energy necessary for coal transportation, thus inducing and triggering the coal and gas protrusion. The study results elucidate, from an energy perspective, the underlying mechanisms that facilitate the occurrence of coal and gas outbursts, providing theoretical guidance for coal and gas outburst prevention and mine safety production. Full article

This study analyzes recloser operation in the South Korean distribution system to propose effective operational strategies for improving safety and efficiency. This research is based on actual data, such as recloser operation data and fault statistics provided by the Ministry of the Interior and Safety and the Korea Electric Power Corporation, without the use of simulation tools or experiments. Key operational elements, such as reclosure counts, sequence settings, and high-current interruption features, were analyzed. First, an analysis of reclosure counts revealed that over 73% of faults were cleared after the first reclosure, and when the second reclosure was included, more than 90% were successfully restored. This finding suggests that reducing the number of reclosures from the standard three to one or two would not significantly impact fault restoration performance while simultaneously reducing arc generation, thereby improving safety. Additionally, a review of recloser sequence settings highlighted the fact that the traditional 2F2D (two fast, two delayed) sequence often led to frequent instantaneous tripping, increasing the risk of arc generation. The 1F1D (one fast, one delayed) sequence, which applies a delayed trip after an initial fast trip, offers a better fault-clearing performance and reduces the risk of arc generation. Lastly, an analysis of the high-current interruption feature suggested that enabling this function for faults with low reclosing success rates, particularly in cases of short-circuit faults, and setting an immediate trip threshold for fault currents exceeding 3 kA would enhance both safety and efficiency. This operational strategy was implemented in the South Korean distribution system over a three-year period, starting in 2021. While there was a 2.1% decrease in reclosure success rates, this strategy demonstrated that similar success levels could be maintained while reducing the number of reclosures, thus mitigating equipment damage risks and improving safety measures. The refined recloser operation plan derived from this study is expected to enhance the overall stability and reliability of distribution systems. Full article

During the process of mining underground coal, the coal emits a large amount of methane into the mining space, which may lead to methane accumulation and exceed explosion safety limits When the methane encounters a fire source, a methane explosion may occur. The forceful impact caused by a methane explosion in an underground roadway can cause serious damage to the roadway structures and even lead to the collapse of the ventilation system. At the same time, the explosion impact may result in the death of workers and cause physical injury to the surviving workers. Therefore, it is necessary to study the damage effect and injury range of methane explosions. On the basis of the damage criteria and damage characteristics of methane explosions, according to the overpressure distribution of shock waves in the propagation process of a methane explosion, the explosion hazard range is divided into four ranges (from inside to outside): death range, serious injury range, minor injury range, and safety range. Four injury degrees of shock wave overpressure to personal body (slight, medium, serious injury, death), and seven damage degrees of overpressure to structures are also analyzed. The thresholds of their damage (destruction) are determined. On this basis, an experimental system and numerical simulation are constructed to measure damage characteristics, the overpressure value, and the range distance of a methane explosion with different initial explosion intensities. According to the experimental and numerical results, the attenuation formula of a methane explosion shock wave in the propagation process is derived. The research results show that the overpressure and impulse of shock waves are selected as the damage criteria for comprehensive evaluation, and the overpressure criterion is suitable of determining the injury (failure) range over long distances. The four injury ranges are in line with the actual situation and are reasonable. The injury degree also conforms to the medical results, which can be used to guide the injury degree of mine methane explosions. The injury range caused by methane explosions with different initial explosion intensities is reasonable and is basically consistent with the on-site situation. The derived attenuation formula and calculated safety distance are in good agreement with the experimental and numerical results. The research results can provide guidance and help in the escape, rescue, and protection of coal mine underground person. Full article

Bone micromorphometric parameters are generally analyzed with micro CT to reveal two- and three-dimensional structures. These parameters are generally used for new bone formation studies such as tissue engineering and biomaterials studies. Different threshold methods are used for the image segmentation of bone micromorphometric parameters. However, these different threshold methods provide different results for the bones analyzed. This study aimed to compare thresholding methods to evaluate bone micromorphometric parameters in the mouse bone. A dataset containing 15 mouse tibia was used to analyze the different thresholding methods for bone micromorphometric parameter analysis. These threshold methods were used to analyze the mouse tibia (n = 15) with thresholded bones. The threshold methods and the analysis were used directly from CTAn (Bruker Micro-CT). The results were compared between the threshold methods, which included bone volume, trabecular number, connectivity, trabecular separation, and other parameters. There was agreement to some extent for all bone micromorphometric analyses using the different thresholding methods. The results showed that the thresholding method showed good agreement for connectivity and trabecular thickness, but the other parameters showed limited agreement. The evaluation of threshold methods allows for the comparison of image segmentation and the quantification of mouse tibia micromorphometric parameters. This study may enable the analysis of bone micromorphometric parameters using the relatively close threshold method in image segmentation across different research groups. Full article

Quinoa is an annual pseudocereal highly adapted to extreme environments and has become, at this point in time, an extremely popular food due to its exceptional and high nutritional quality. This study aims to investigate the association of quinoa salt tolerance at an early developmental stage with its grain nutritional value under the effect of severe climatic hurdles. The current findings revealed a significant variability between genotypes in salt response attributes at the first development stage, where genotypes Amarilla Sacaca (thereafter, A. Sacaca) and QQ57 exhibited high salt tolerance thresholds with a low salt sensitivity index (SI), and a high capacity for Na⁺ sequestration into vacuoles. A significant positive association was detected between salt tolerance degree and yield parameters, saponins (SAPs), and minerals contents, where genotype A. Sacaca exhibited the highest SAP content with 3.84 mg.g⁻¹ and the highest amounts of K, Ca, P, and Fe. The analysis of fatty acid composition demonstrated a high significant negative correlation between crude fat content and salt SI, and between yield parameters. Despite its low harvest index (HI) and low seed oil content, the salt-tolerant genotype A. Sacaca showed a high nutritional quality for seed oil according to its lowest ω6/ω3 ratio (5.6/1) and lowest level of atherogenicity index (AI). The genotype 115R, defined as the most sensitive to salt stress, exhibited a high seed oil quality due to its low lipid peroxidation susceptibility as reflected by its oxidative susceptibility and peroxidizability indexes. The significance of this study includes the identification of valuable quinoa genotypes showing high efficiency in growth and yield under severe stress accompanied by a high nutritional value satisfying the market requirements for healthy, nutritious, and safe food products. Full article

Due to the hydraulic sorting effect in the hydraulic filling process, a fine-grained aggregate layer dominated by silty fine sand with uneven distribution is easily formed in reclamation projects, which triggers issues with the bearing capacity and nonuniform settlement of calcareous sand foundations. In this study, a series of one-dimensional compression tests were conducted to investigate the effect of different fines contents (f_c) on the compression behavior of calcareous sand. The results show that at the same relative density (medium-density, D_r = 50%), the addition of fine particles leads to a reduction in the initial void ratio (for f_c ≤ 40%). Furthermore, while the compressibility of the soil samples increases with the rising of fines content, it begins to decrease with further addition of fine particles beyond a threshold value of fines content (f_c-th). Additionally, particle crushing contributes to the compressive deformation of calcareous sand, and the particle relative breakage of calcareous sand increases at the initial stage of adding fine particles. Moreover, a comparison of the compression test results between calcareous silty sand (f_c = 10%) and clean sand reveals that the addition of fine particles accentuates the compressibility differences among calcareous sands with different relative densities. These findings provide valuable insights for addressing the challenges posed by fine-grained layers in calcareous sand foundations. Full article