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Rock avalanche disasters in alpine and gorge regions are frequent and large in scale and cause severe damage. The movement of a rock avalanche is complex and has not been fully studied. The deposits of a rock avalanche can provide valuable insights into its movement process, which is crucial in understanding the rock fragmentation mechanism and predicting disaster-affected areas. Taking the Wangjiapo rock avalanche in Yunnan Province of China as an example, the size, shape and distribution characteristics of the deposit were analyzed based on field surveys, unmanned aerial vehicle (UAV) photography and image recognition technology. Initially, 3062 deposited rock blocks were manually measured in the field. Subsequently, the Particles/Pores and Cracks Analysis System (PCAS) was employed to identify 11,357 rock blocks with an area greater than 0.1 m2 from UAV orthophotos. By comparing the characteristics of the rock blocks obtained through image recognition and manual measurement, the statistical analysis of UAV aerial imagery combined with PACS proved feasible in studying the Wangjiapo rock avalanche. The results showed that the rock block movement was accompanied by fragmentation and sorting processes; furthermore, the roundness increased with the migration distance. Small blocks were more prevalent at the foot of the slope, while irregularly shaped, large blocks dominated in source areas. The movement of huge blocks was characterized by significant potential energy-driven features and inertia advantages, allowing them to travel farther than smaller blocks, and they tended to be concentrated in the central area of the deposit. Additionally, affected by the cementation degree of breccia and the topography, the blocks in the eastern and western deposit areas exhibited different fragmentation and deposition characteristics.

High-speed precision planters are subject to high-speed (12~16 km/h) operation due to terrain undulation caused by mechanical vibration and sensor measurement errors caused by the sowing depth monitoring system’s accuracy reduction problems. Thus, this study investigates multi-sensor data fusion technology based on the sowing depth monitoring systems of high-speed precision planters. Firstly, a sowing depth monitoring model comprising laser, ultrasonic, and angle sensors as the multi-sensor monitoring unit is established. Secondly, these three single sensors are filtered using the Kalman filter. Finally, a multi-sensor data fusion algorithm for optimising four key parameters in the extended Kalman filter (EKF) using an improved sparrow search algorithm (ISSA) is proposed. Subsequently, the filtered data from the three single sensors are integrated to address the issues of mechanical vibration interference and sensor measurement errors. In order to ascertain the superiority of the ISSA-EKF, the ISSA-EKF and SSA-EKF are simulated, and their values are compared with the original monitoring value of the sensor and the filtered sowing depth value. The simulation test demonstrates that the ISSA-EKF-based sowing depth monitoring algorithm for high-speed precision planters, with a mean absolute error (MAE) of 0.083 cm, root mean square error (RMSE) of 0.103 cm, and correlation coefficient (R) of 0.979 achieves high-precision monitoring. This is evidenced by a significant improvement in accuracy when compared with the original monitoring value of the sensor, the filtered value, and the SSA-EKF. The results of a field test demonstrate that the ISSA-EKF-based sowing depth monitoring system for high-speed precision planters enhances the precision and reliability of the monitoring system when compared with the three single-sensor monitoring values. The average MAE and RMSE are reduced by 0.071 cm and 0.075 cm, respectively, while the average R is improved by 0.036. This study offers a theoretical foundation for the advancement of sowing depth monitoring systems for high-speed precision planters.

Bayesian model updating has received considerable attention and has been extensively used in structural damage detection. It provides a rigorous statistical framework for realizing structural system identification and characterizing uncertainties associated with modeling and measurements. The Markov Chain Monte Carlo (MCMC) is a promising tool for inferring the posterior distribution of model parameters to avoid the intractable evaluation of multi-dimensional integration. However, the efficacy of most MCMC techniques suffers from the curse of parameter dimension, which restricts the application of Bayesian model updating to the damage detection of large-scale systems. In addition, there are several MCMC techniques that require users to properly choose application-specific models, based on the understanding of algorithm mechanisms and limitations. As seen in the literature, there is a lack of comprehensive work that investigates the performances of various MCMC algorithms in their application of structural damage detection. In this study, the Differential Evolutionary Adaptive Metropolis (DREAM), a multi-chain MCMC, is explored and adapted to Bayesian model updating. This paper illustrates how DREAM is used for model updating with many uncertainty parameters (i.e., 40 parameters). Furthermore, the study provides a tutorial to users who may be less experienced with Bayesian model updating and MCMC. Two advanced single-chain MCMC algorithms, namely, the Delayed Rejection Adaptive Metropolis (DRAM) and Transitional Markov Chain Monte Carlo (TMCMC), and DREAM are elaborately introduced to allow practitioners to understand better the concepts and practical implementations. Their performances in model updating and damage detection are compared through three different engineering applications with increased complexity, e.g., a forty-story shear building, a two-span continuous steel beam, and a large-scale steel pedestrian bridge.

In recent years, urban floods have occurred frequently in China. Therefore, there is an urgent need to strengthen urban flood resilience. This paper proposed a hybrid multi-criteria group decision-making method to assess urban flood resilience based on heterogeneous data, group decision-making methodologies, the pressure-state–response model, and social–economic–natural complex ecosystem theory (PSR-SENCE model). A qualitative and quantitative indicator system is formulated using the PSR-SENCE model. Additionally, a new weighting method for indicators, called the synthesis weighting-group analytic hierarchy process (SW-GAHP), is proposed by considering both intrapersonal consistency and interpersonal consistency of decision-makers. Furthermore, an extensional group decision-making technology (EGDMT) based on heterogeneous data is proposed to evaluate qualitative indicators. The flexible parameterized mapping function (FPMF) is introduced for the evaluation of quantitative indicators. The normal cloud model is employed to handle various uncertainties associated with heterogeneous data. The evaluations for Beijing from 2017 to 2021 reveal a consistent annual improvement in urban flood resilience, with a 14.1% increase. Subsequently, optimization recommendations are presented not only for favorable indicators such as regional economic status, drainability, and public transportation service capacity but also for unfavorable indicators like flood risk and population density. This provides a theoretical foundation and a guide for making decisions about the improvement of urban flood resilience. Finally, our proposed method shows superiority and robustness through comparative and sensitivity analyses.

Face recognition is a widely used computer vision, which plays an increasingly important role in user authentication systems, security systems, and consumer electronics. The models for most current applications are based on high-definition digital cameras. In this paper, we focus on digital images derived from historical motion picture films. Historical motion picture films often have poorer resolution than modern digital imagery, making face detection a more challenging task. To approach this problem, we first propose a trunk–branch concatenated multi-task cascaded convolutional neural network (TB-MTCNN), which efficiently extracts facial features from blurry historical films by combining the trunk with branch networks and employing various sizes of kernels to enrich the multi-scale receptive field. Next, we build a deep neural network-integrated object-tracking algorithm to compensate for failed recognition over one or more video frames. The framework combines simple online and real-time tracking with deep data association (Deep SORT), and TB-MTCNN with the residual neural network (ResNet) model. Finally, a state-of-the-art image restoration method is employed to reduce the effect of noise and blurriness. The experimental results show that our proposed joint face recognition and tracking network can significantly reduce missed recognition in historical motion picture film frames.

The hydrochemical characteristics of watersheds are influenced by many factors, with chemical weathering and human activities exerting the most substantial influence. Performing a quantitative evaluation of the factors contributing to the chemical weathering of rocks is of significant scientific importance. This research zeroes in on the Qingtang River basin to elaborate on the hydrochemical characteristic, explore the origins of ions, and quantify the influence of anthropogenic discharges amidst cation interferences, thus improving the accuracy of chemical weathering rate estimations. The samples encompassed surface water, groundwater, and water from dripping in karst caves. The findings indicate that human-induced alterations significantly influence hydrogeochemical dynamics, although chemical weathering of rocks in their natural state is the controlling factor. The mean contributions of cations from atmospheric deposition, human inputs, carbonate weathering, and silicate weathering were 17.56%, 21.05%, 51.77%, and 9.54%, respectively. The chemical weathering rate for carbonate rocks was 62.4 t·km−2·a−1, which increased by 27.87% due to the influence of exogenous acids. The anthropogenic impact is predominantly evident in two aspects: (1) the alteration of hydrochemical processes within the watershed through direct input of ions, and (2) the acceleration of rock weathering rates in the watershed due to the exogenous acids.

In response to the analysis of the functional status of forearm blood vessels, this paper fully considers the orientation of the vascular skeleton and the geometric characteristics of blood vessels and proposes a blood vessel width calculation algorithm based on the radius estimation of the tangent circle (RETC) in forearm near-infrared images. First, the initial infrared image obtained by the infrared camera is preprocessed by image cropping, contrast stretching, denoising, enhancement, and initial segmentation. Second, the Zhang–Suen refinement algorithm is used to extract the vascular skeleton. Third, the Canny edge detection method is used to perform vascular edge detection. Finally, a RETC algorithm is developed to calculate the vessel width. This paper evaluates the accuracy of the proposed RETC algorithm, and experimental results show that the mean absolute error between the vessel width obtained by our algorithm and the reference vessel width is as low as 0.36, with a variance of only 0.10, which can be significantly reduced compared to traditional calculation measurements.

Natural gas hydrate (NGH) is considered as a type of clean energy to replace coal and oil. During exploitation, permeability is one of the key parameters controlling production efficiency, reservoir stability, and greenhouse gas sequestration. Limited by experimental and numerical simulation tools, in current research, the directionality of permeability is usually ignored. In this work, a DEM–CFD coupling simulation method is developed to compute the anisotropic permeability. The sedimentary process of reservoir sediments is reconstructed, enabling the acquisition of numerical models that possess pore structures consistent with the actual fabric characteristics. The fluid transport process in various directions can be simulated with a finite element method. Taking the natural gas hydrate reservoir in the Shenhu area of the South China Sea as an example, the proposed method is validated and applied to explore the effect of compaction stress on permeability anisotropy. With the increase in compaction stress, the permeability anisotropy exhibited a rapid initial increase, followed by a sustained stabilization. The primary cause is the rearrangement of sediment particles. The non-spherical particles are driven to align in a predominantly horizontal orientation, thereby enhancing anisotropy. The proposed method provides a tool for the efficient exploitation of hydrate resources.

Amorphous alloy fiber has the advantages of high tensile strength and high corrosion resistance compared with steel fiber, but its interfacial bonding with cement matrix is poor and requires surface modification treatment. In this study, the surface modification of amorphous alloy fiber was carried out by using silane coupling agent KH-550 solution, and its effect on the mechanical properties of ultra-high-performance concrete was investigated. The results showed that the amorphous alloy fibers modified with 15% concentration silane coupling agent KH-550 solution can effectively improve the mechanical properties of the ultra-high-performance concrete, where the interfacial bond strength with the cement matrix reached 3.29 MPa and the roughness reached 3.85. The compressive strength, flexural strength, tensile strength, and peak stress of the ultra-high-performance concrete mixed with modified amorphous alloy fibers could reach up to 133.6 MPa, 25.5 MPa, 8.32 MPa, and 114.26 MPa, respectively, which were 2.9%, 6.3%, 10.9%, and 4.3% higher than those of the ultra-high-performance concrete with unmodified amorphous alloy fibers. As the surface of the fiber was modified, its properties changed and the bonding effect with the cement matrix was better, which in turn improved the mechanical properties of the ultra-high-performance concrete.

Wave energy has a high energy density and strong predictability, presenting encouraging prospects for development. So far, there are dozens of different wave energy devices (WECs), but the mechanism that ultimately converts wave energy into electrical energy in these devices has always been the focus of research by scholars from various countries. The energy conversion mechanism in wave energy devices is called PTO (power take-off). According to different working principles, PTOs can be classified into the linear motor type, hydraulic type, and mechanical type. Hydraulic PTOs are characterized by their high efficiency, low cost, and simple installation. They are widely used in the energy conversion links of various wave energy devices. However, apart from experimental methods, there is currently almost no concise numerical method to predict and evaluate the power generation performance of hydraulic PTO. Therefore, based on the working principle of hydraulic PTO, this paper proposes a numerical method to simulate the performance of a hydraulic PTO using MATLAB(2018b) Simulink®. Using a point-absorption wave energy device as a carrier, a float hydraulic system power-generation numerical model is built. The method is validated by comparison with previous experimental results. The predicted power generation and conversion efficiency of the point-absorption wave energy device under different regular and irregular wave conditions are compared. Key factors affecting the power generation performance of the device were investigated, providing insight for the subsequent optimal design of the device, which is of great significance to the development and utilization of wave energy resources.

The stink bug, Riptortus pedestris (Fabricius) (Hemiptera: Alydidae), is a highly destructive pest that significantly damages legume crops in East and South Asia. Neonicotinoid insecticides containing thiamethoxam are widely used to control R. pedestris in soybean fields. However, the current knowledge on the impact of different thiamethoxam concentrations on R. pedestris growth and reproduction is lacking and insufficient. The present study investigated the effects of thiamethoxam on the biological traits of R. pedestris after treatment with LC10 (19.8 mg/L), LC20 (31.6 mg/L), LC30 (44.2 mg/L), LC40 (58.9 mg/L), and LC50 (77.0 mg/L) concentrations. These five thiamethoxam concentrations (LC10~LC50) reduced adult longevity and fecundity in the F1 generation females. Thiamethoxam treatment also significantly decreased the population trend index, intrinsic rate of increase, net reproductive rate, gross reproductive rate, and finite rate of increase and increased the mean generation time. These results show that thiamethoxam hinders and suppresses the development and growth of the F1 population of R. pedestris. Thiamethoxam is recommended for spray control during peak adult emergence, as it not only has a controlling effect on the parental generation but also a negative impact on the F1 generations.

Different types of soil macropores respond differently to various tillage practices, owing to disparities in origin, scale, morphology, and function, consequently exerting distinct effects on soil structure. This study aimed to investigate the response mechanisms of three different soil pore types (total macropores, non-biopores, and biopores) to two distinct tillage practices: smash-ridging tillage (T) and no-tillage (NT) in sugarcane fields. The parameters characterizing soil pore treatments in two and three dimensions were obtained using X-ray computed tomography scanning technology. ImageJ and MATLAB software were employed to analyze the data and separate soil macropores into biopores and non-biopores categories. The results showed that non-biopores predominated in two-dimensional cross-sectional areas in NT treatment, whereas biopores were more dominant in T treatment. Biopores in T treatment had a higher proportion of two-dimensional pores compared to NT treatment. A three-dimensional analysis indicated that total macropores had larger mean diameters (MD) and macroporosity, with more continuous tubular pores in T treatment than that in NT treatment. However, NT treatment had more numerous non-biopores with broader spatial distribution and complex morphology. Additionally, biopores in T treatment had larger MD and branching length density (LD). These vertically developed biopores, along with high macropore connectivity and under smash-ridging tillage, could improve soil water and pore conductivity. Therefore, smash-ridging tillage was more beneficial for sugarcane growth compared to no-tillage in Guangxi of China.

The ecological environment of the Hexi Corridor in China is fragile owing to its unique geographical conditions. Since the 21st century, the construction of highway projects in the Hexi Corridor has increased with the implementation of China’s western development policy. The impact of highway construction on vegetation along roads is uncertain and requires attention. In this study, the normalized difference vegetation index (NDVI) was obtained based on remote sensing data, and the correlations between the vegetation index, climate changes, and highway construction from 2000 to 2019 were analyzed. The results showed that the NDVI of the Hexi Corridor showed a significant increasing trend, and the spatial difference was obvious, which was largely controlled by climatic conditions. Generally, the vegetation index was negatively correlated with temperature, but positively correlated with precipitation, and the correlation between the NDVI and precipitation was greater than that of temperature. The impact of highways on vegetation is a long-term process. In the eastern region of the Hexi Corridor, where the ecological environment is better, highway construction promoted vegetation development. However, in the western region with high desertification, the damage caused by highway construction to vegetation was serious, and the recovery rate of degraded vegetation was slow after the completion of highway construction. Although the vegetation development in the Hexi Corridor was mainly affected by precipitation, in the western region, highway construction was the main factor controlling vegetation disturbance within a certain range on both sides, and its contribution to vegetation disturbance reached 60%. The research results can improve understanding of the disturbance effect of highway construction on vegetation in arid areas.

The permeability of natural gas hydrate (NGH) turbidite reservoirs typically exhibits significant anisotropy, with anisotropy being a crucial basis for evaluating reservoir production. The presence of hydrates, as a crucial constituent of the solid framework, not only impacts the overall permeability but also influences the permeability anisotropy. To investigate the saturation sensitivity of permeability anisotropy, a series of simulations are performed by integrating particle flow and computational fluid dynamics methods to construct the homogeneous and layered numerical samples and compute the evolution of permeability anisotropy. It is shown that the permeability is isotropic for homogeneous sediments and the isotropy remains unchanged regardless of variations in hydrate saturation. The permeability of layered sediments, in contrast, exhibits significant anisotropy due to the presence of dominant channels within the coarse layer. For uniformly distributed hydrates, the more effective blockage in coarse layers results in a reduction in anisotropy. While for preferentially distributed hydrates, the excess blocking of coarse layers makes the dominant channels transfer to the fine layers, the further blocking causes a U-shaped anisotropy–saturation curve characterized by a decrease–increase transformation. During the reservoir production process, the preponderance channels blocked by hydrates will be cleared and the horizontal permeability will significantly increase. As a result, the production efficiency of horizontal wells may exceed expectations. The findings offer a parameter support for production estimation and environmental assessment.

The natural gas (NG)-powered compressors/engines used in liquified natural gas (LNG) plants are a major source of methane emission. The Allam–Fetvedt cycle (AFC), an oxyfuel, carbon-neutral, high-efficiency power plant, generates pipeline-grade CO2. This work performed novel process modeling, economic analysis, and greenhouse gas emissions analysis for a heat-integrated, electrified LNG/AFC/air separation unit (ASU) complex (LAA), then compared it to standalone LNG and AFC/ASU plants (baseline) as well as an LNG plant electrified with AFC/ASU without heat integration. The low-grade heat generated from compressors of the LNG plant can enhance the AFC net power output by 7.1%. Utilizing the nitrogens cold energy reduces the compressor power requirement by 1.6%. In the integrated LAA complex, not only are GHG emissions avoided, but the energy efficiencies are also improved for both the LNG plant and the AFC power plant. A cash flow analysis of LAA was performed over a 20-year period with 5%, 7%, and 10% discount rates and three levels of LNG prices. The 45Q CO2 credit of USD 85/T as stipulated by the recent Inflation Reduction Act (IRA) of 2022 has been incorporated. The results clearly indicate the economic and environmental benefits of the proposed electrification and heat/power integration.

Hydrogen production technology has triggered a research boom in order to alleviate the problems of environmental pollution and the pressure on non-renewable energy sources. The key factor of this technology is the use of an efficient photocatalyst. g-C3N4 is a typical semiconductor photocatalytic material that is non-toxic and environmentally friendly and does not cause any serious harm to human beings. Therefore, it can be applied to drug degradation and the photocatalytic production of H2. Combined with ZnIn2S4, this semiconductor photocatalytic material, with a typical lamellar structure, has become one of the most promising catalysts for research due to its suitable bandgap structure and excellent photoelectric properties. In this study, 10% g-C3N4/ZnIn2S4 nano-heterojunction composite photocatalytic materials were successfully prepared by compounding ZnIn2S4 and g-C3N4 semiconductor materials with good visible-light-trapping ability. Under visible light irradiation, the photocatalytic activity of the composites was significantly better than that of pure g-C3N4 and ZnIn2S4. This is attributed to the formation of a heterojunction structure, which effectively inhibited the recombination of photogenerated carriers through the interfacial contact between the two semiconducting materials, and then improved the separation efficiency of the photogenerated electron–hole pairs, thus enhancing the catalytic activity. In this study, pure g-C3N4 and ZnIn2S4 were prepared using calcination and hydrothermal methods, and then, the composites were synthesized using ultrasonic and hydrothermal means. The differences in the structure, morphology, and hydrogen production performance of the materials before and after recombination were analyzed in detail using XRD, SEM, and FTIR characterization, which further verified that the 10% g-C3N4/ZnIn2S4 nano-heterojunction composites possessed excellent photocatalytic activity and stability, providing new possibilities for the optimization and application of photocatalytic hydrogen production technology.

Auxins play crucial regulatory roles in plants coping with cadmium (Cd) stress. However, the regulatory mechanism by which auxins alleviate Cd toxicity in tomato seedlings remains unclear. Here, we demonstrate that exposure to Cd stress leads to dynamic changes in the auxin response in tomato roots, characterized by an initial increase followed by a subsequent weakening. Under Cd stress, tomato seedlings show primary root- and hypocotyl-growth inhibition, accompanied by the accumulation of Cd and reactive oxygen species (ROS) in the roots. The exogenous application of 1-naphthylacetic acid (NAA) does not mitigate the inhibitory effect of Cd toxicity on primary root growth, but it does significantly enhance lateral root development under Cd stress. Auxin transport inhibitors, such as 1-N-naphthylphthalamic acid (NPA) and 2,3,5-triiodobenoic acid (TIBA), aggravate the growth inhibition of primary roots caused by Cd stress. Additionally, lateral root development was inhibited by NPA. However, applying auxin synthesis inhibitors L-kynurenine (kyn) and yucasin alleviated the tomato root growth inhibition caused by Cd stress; between them, the effect of yucasin was more pronounced. Yucasin mitigates Cd toxicity in tomato seedlings by reducing Cd2+ absorption and auxin accumulation, strengthening ROS scavenging, and reducing cell death in roots. These observations suggest that yucasin potentially mitigates Cd toxicity and improves the tolerance of tomato seedlings to Cd stress.

The microstructural characteristics of reclaimed soil in Guangxi’s bauxite mining area play a pivotal role in determining soil reclamation quality, yet they remain poorly understood. To explore the impact of varying reclamation years and modes on pore structure characteristics in this region, we selected four reclamation regions: grassland reclamation with 2 years (RG2a), grassland reclamation with 10 years (RG10a), bare ground reclamation with 2 years (RW2a) and bare ground reclamation with 10 years (RW10a). Utilizing X-ray CT technology, we scanned soil columns within a 30 cm depth to analyze pore distributions using Avizo 2020 software combined with ImageJ 1.53c and its plugins. The findings revealed a significant increase in the number of 2D and 3D macropores by 1.09% and 88.89% in RG10a compared to RG2a, as well as 39.01% and 13.33% in RG10a compared to RW10a, respectively. Furthermore, RG10a was observed to be more effective in enhancing the rounding rate of macropores and mesopores, as well as average branch length and density. Additionally, RG10a demonstrated a greater capacity to increase porosity and connectivity while reducing curvature and specific surface area among the three-dimensional parameters. The 3D reconstruction illustrated that RG modes exhibited a more abundant distribution of macropores compared to RW modes and 10a modes showed a higher presence of macropores than 2a modes, which displayed a tilted laminar pattern. Soil moisture movement simulations conducted through Avizo 2020 under various modes indicated that RG modes presented a more extensive capacity for vertical flow, while 10a modes displayed more abundant flow lines and a higher infiltration rate (K) compared to 2a modes. In conclusion, prolonged reclamation years favoring grassland reclamation modes could enhance water and nutrient transport pathways toward traditional agricultural soil.

A multi-layer stacked Dynamic Random Access Memory (DRAM) platform is introduced to address the memory wall issue. This platform features high-density vertical interconnects established between DRAM units for high-capacity memory and logic units for computation, utilizing Wafer-on-Wafer (WoW) hybrid bonding and mini Through-Silicon Via (TSV) technologies. This 3DIC architecture includes commercial DRAM, logic, and 3DIC manufacturing processes. Their design documents typically come from different foundries, presenting challenges for signal integrity design and analysis. This paper establishes a lumped circuit based on 3DIC physical structure and calculates all values of the lumped elements in the circuit model with the transmission line model. A Cross-Process Signal Integrity Analysis (CPSIA) method is introduced, which integrates three different manufacturing processes by modeling vertical stacking cells and connecting DRAM and logic netlists in one simulation environment. In combination with the dedicated buffer driving method, the CPSIA method is used to analyze 3DIC impacts. Simulation results show that the timing uncertainty introduced by 3DIC crosstalk ranges from 31 ps to 62 ps. This analysis result explains the stable slight variation in the maximum frequency observed in vertically stacked memory arrays from different DRAM layers in the physical testing results, demonstrating the effectiveness of this CPSIA method.

Sulfur hexafluoride (SF6) is a typical fluorine gas with excellent insulation and arc extinguishing properties that has been widely used in large-scale power equipment. The detection of SF6 gas in high-power electrical equipment is a necessary measure to ensure the reliability and safety of power grid operation. A failure of SF6 insulated electrical equipment, such as discharging or overheating conditions, can cause SF6 gas decomposition, resulting in various decomposition products. The decomposed gases inside the equipment decrease the insulating properties and are toxic. The leakage of SF6 can also decrease the insulating properties. Therefore, it is crucial to monitor the leakage of SF6 decomposed gases from electrical equipment. Quantitative testing of decomposition products allows us to assess the insulation state of the equipment, identify internal faults, and maintain the equipment. This review comprehensively introduces the decomposition formation mechanism of SF6 gas and the current detection technology of decomposition products from the aspects of principle and structure, materials, test effect, and practicability. Finally, the development trends of SF6 and decomposition gas detection technology for the reliability and safety of power grid operation are prospected.

Six new 2α-hydroxy ursane triterpenoids, 3α-cis-p-coumaroyloxy-2α,19α-dihydroxy-12-ursen-28-oic acid (1), 3α-trans-p-coumaroyloxy-2α,19α-dihydroxy-12-ursen-28-oic acid (2), 3α-trans-p-coumaroyloxy-2α-hydroxy-12-ursen-28-oic acid (3), 3β-trans-p-coumaroyloxy-2α-hydroxy-12,20(30)-ursadien-28-oic acid (4), 3β-trans-feruloyloxy-2α-hydroxy-12,20(30)-ursadien-28-oic acid (5), and 3α-trans-feruloyloxy-2α-hydroxy-12,20(30)-ursadien-28-oic acid (6), along with eleven known triterpenoids (7–17), were isolated from the leaves of Diospyros digyna. Their chemical structures were elucidated by comprehensive analysis of UV, IR, HRESIMS, and NMR spectra. All the isolated compounds were evaluated for their PTP1B inhibitory activity. 3β-O-trans-feruloyl-2α-hydroxy-urs-12-en-28-oic acid (13) showed the best inhibition activity with an IC50 value of 10.32 ± 1.21 μM. The molecular docking study found that the binding affinity of compound 13 for PTP1B was comparable to that of oleanolic acid (positive control).

Bifidobacterium longum is a common probiotic; both viable and heat-inactivated Bifidobacterium longum have many probiotic effects, such as anticancer effects. But some mechanisms of anticancer effects are still unclear, especially for heat-inactivated probiotics. In this study, we analyzed the effects of viable and heat-inactivated Bifidobacterium longum D42 on human colon cancer cells (HT-29). Cell proliferation, membrane permeability and apoptosis were detected by using the CCK-8 method, LDH method and Annexin V-FITC/PI kits. The ROS level and mitochondrial membrane potential were examined using the fluorescent probes DCFH-DA and JC-1. Real-time fluorescence quantitative PCR (RT-qPCR) and Western blot were used to detect the expression of mitochondrial apoptosis pathway genes and proteins. The results showed that viable and heat-inactivated Bifidobacterium longum D42 at concentrations of 1 × 106 CFU/mL significantly inhibited the proliferation of and increased the level of LDH release of HT-29 colon cancer cells. We found that they could increase the apoptosis rate of HT-29 cells. Moreover, they could also induce apoptosis by inducing cells to produce ROS and destroying the mitochondrial membrane potential of cells. Further studies found that they could increase the mRNA transcription and protein expression levels of the Caspase-3, Caspase-9 and Bax genes in cells, and reduce the mRNA transcription and protein expression levels of the Bcl-2 gene. In summary, our findings revealed that viable and heat-inactivated Bifidobacterium longum D42 have inhibitory effects on proliferation and promote the apoptosis of human colon cancer cells, and also have certain adjuvant drug therapeutic effects and have potential application value in the adjuvant treatment of colon cancer.

The fusion of infrared and visible images is a well-researched task in computer vision. These fusion methods create fused images replacing the manual observation of single sensor image, often deployed on edge devices for real-time processing. However, there is an issue of information imbalance between infrared and visible images. Existing methods often fail to emphasize temperature and edge texture information, potentially leading to misinterpretations. Moreover, these methods are computationally complex, and challenging for edge device adaptation. This paper proposes a method that calculates the distribution proportion of infrared pixel values, allocating fusion weights to adaptively highlight key information. It introduces a weight allocation mechanism and MobileBlock with a multispectral information complementary module, innovations which strengthened the model’s fusion capabilities, made it more lightweight, and ensured information compensation. Training involves a temperature-color-perception loss function, enabling adaptive weight allocation based on image pair information. Experimental results show superiority over mainstream fusion methods, particularly in the electric power equipment scene and publicly available datasets.

Background: Cancer-related fatigue (CRF) is a common and burdensome symptom in cancer patients that is influenced by multiple factors. Identifying factors associated with CRF may help in developing tailored interventions for fatigue management. This study aimed to examine the correlates of CRF among colorectal cancer patients undergoing postoperative adjuvant therapy based on the theory of unpleasant symptoms. Methods: A cross-sectional study was implemented, and finally, a sample of 363 participants from one tertiary general hospital and one tertiary cancer hospital was purposively recruited. Data were collected using the general information questionnaire, cancer fatigue scale, the distress disclosure index, Herth hope index, and perceived social support scale. Univariate analysis and multiple linear regression analysis were performed to determine the correlates of CRF. Results: The mean score of CRF among colorectal cancer patients was 21.61 (SD = 6.16, 95% CI 20.98–22.25), and the fatigue degree rating was “moderate”. The multiple linear regression model revealed that 49.1% of the variance in CRF was explained by hope, sleep disorder, internal family support, self-disclosure, pain, and time since operation. Conclusions: Our study identified several significant, modifiable factors (self-disclosure, hope, internal family support, pain, and sleep disorder) associated with CRF. Understanding these correlates and developing targeted psychosocial interventions may be associated with the improvement of CRF in patients with colorectal cancer.

The influenza BM2 transmembrane domain (BM2TM), an acid-activated proton channel, is an attractive antiviral target due to its essential roles during influenza virus replication, whereas no effective inhibitors have been reported for BM2. In this study, we draw inspiration from the properties of cyclodextrins (CDs) and hypothesize that CDs of appropriate sizes may possess the potential to act as inhibitors of the BM2TM proton channel. To explore this possibility, molecular dynamics simulations were employed to assess their inhibitory capabilities. Our findings reveal that CD4, CD5, and CD6 are capable of binding to the BM2TM proton channel, resulting in disrupted water networks and reduced hydrogen bond occupancy between H19 and the solvent within the BM2TM channel necessary for proton conduction. Notably, CD4 completely obstructs the BM2TM water channel. Based on these observations, we propose that CD4, CD5, and CD6 individually contribute to diminishing the proton transfer efficiency of the BM2 protein, and CD4 demonstrates promising potential as an inhibitor for the BM2 proton channel.