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With the development of society and changes in the human living environment, people are increasingly attaching importance to their own health. Regarding medical imaging examinations of certain parts of the body, the process of medical image segmentation has become extremely important. This paper presents a novel hybrid algorithm: SAOBL-IA, a fusion of the Simulated Annealing(SA), Opposition-based Learning(OBL)and Island Algorithm(IA). The Island Algorithm itself suffers from slow convergence speed and the tendency to get stuck in local optimum. To address these limitations, we introduce opposition-based learning to enhance the search range and avoid local optimum. Furthermore, we leverage the simulated annealing approach to accelerate the convergence of SAOBL-IA. Comparing the experimental results, it can be seen that SAOBL-IA has better comprehensive performance. Subsequently, the SAOBL-IA algorithm is utilized in conjunction with an optimized two-dimensional OTSU fusion segmentation technique for the purpose of medical image processing. This study proposes an application of image segmentation based on the SAOBL-IA. The segmentation of pixels around the background and target regions using the two-dimensional OTSU method faces challenges in terms of accuracy. To address this issue, an adaptive thresholding technique known as Adaptive Forking is employed for optimization. By determining the slope of the fork based on the misclassified pixel ratio, enhanced segmentation accuracy can be achieved. This improved approach is then integrated with the SAOBL-IA algorithm and applied to the segmentation of lung medical images. The experimental findings show that the amalgamation of SAOBL-IA with the adaptive two-dimensional OTSU segmentation approach, as proposed in this study, manifests superior segmentation speed and enhanced precision in the context of medical image segmentation.

Water inrush is one of the most dangerous disasters in coal mining. Due to the large-scale mining and complicated hydrogeological conditions, thousands of deaths and huge economic losses have been caused by water inrush disasters in China. There are two main factors determining the occurrence of water inrush: water source and water-conducting pathway. Research on the formation mechanism of the water-conducting pathway is the main direction to prevent and control the water inrush, and the seepage mechanism of rock mass during the formation of the water-conducting pathway is the key for the research on the water inrush mechanism. This paper provides a state-of-the-art review of seepage mechanisms during water inrush from three aspects, i.e., mechanisms of stress-seepage coupling, flow regime transformation and rock erosion. Through numerical methods and experimental analysis, the evolution law of stress and seepage fields in the process of water inrush is fully studied; the fluid movement characteristics under different flow regimes are clearly summarized; the law of particle initiation and migration in the process of water inrush is explored, and the effect of rock erosion on hydraulic and mechanical properties of the rock media is also studied. Finally, some limitations of current research are analyzed, and the suggestions for future research on water inrush are proposed in this review.

Short-video platforms are increasingly utilized as preliminary sources of oral health information, yet the clinical value of patient-facing content varies across platforms. This study evaluated and compared the educational usability, clinical accuracy, transparency, and misinformation risk of apical surgery videos across four major Chinese social media platforms. A standardized search using the term \"\" (apical surgery) was conducted on March 15, 2026, across TikTok, Bilibili, Kwai, and WeChat Channels. To minimize algorithmic bias, newly registered accounts under default sorting criteria were used to select 150 consecutive eligible videos per platform (  = 600). Videos were evaluated using the Patient Education Materials Assessment Tool (PEMAT), a study-specific 12-item clinical accuracy checklist, and JAMA benchmarks. Multivariable linear regression identified independent predictors of clinical accuracy. Bilibili and WeChat Channels demonstrated significantly higher educational usability and clinical accuracy than TikTok and Kwai (  < 0.001). Median PEMAT understandability scores were 85% for Bilibili and 82% for WeChat Channels, versus 68% for TikTok and 70% for Kwai. Mean clinical accuracy scores (out of 24) were 20.1 ± 2.8 and 19.5 ± 3.0 for Bilibili and WeChat Channels, compared to 12.4 ± 3.2 for TikTok and 12.6 ± 3.4 for Kwai. Sourcing transparency was generally deficient; only 9.2% of the total sample provided references to evidence sources. Severe misinformation was significantly more prevalent on Kwai (18.7%) and TikTok (15.3%) than on Bilibili (4.0%) and WeChat Channels (5.3%) (  < 0.001). Multivariable analysis confirmed that professional uploader status (β = 3.85,  < 0.001) and longer video duration (β = 1.72 per 60 s,  < 0.001) were independent predictors of superior clinical accuracy. Patient-directed information regarding apical surgery is highly heterogeneous and strongly modulated by platform ecology. Public health initiatives should encourage qualified endodontic professionals to actively participate in video creation and advocate for platform environments that privilege balanced, source-verified clinical communication.

The ocular surface system, essential for maintaining visual function, is highly susceptible to a range of ocular surface diseases (OSDs) that significantly impair patients’ quality of life. Current treatments for OSDs often face limitations including low bioavailability, A lack of targeted delivery, and an inadequate capacity to fully address the complex pathophysiology involving inflammation, oxidative stress, and impaired tissue repair. In recent years, exosomes have emerged as promising cell-free therapeutic platforms for OSDs. This review evaluates their therapeutic potential across the OSD spectrum, focusing on three key aspects: mechanisms—modulation of inflammation, oxidative stress, and tissue repair via bioactive cargo; applications—preclinical therapeutic effects in dry eye disease, corneal injury, keratitis, and transplant rejection; and optimization strategies—engineering approaches and biomaterial integration to enhance stability, targeting, and ocular retention. We also discuss critical challenges in standardization, scalable production, and clinical translation, highlighting future directions for exosome-based OSD therapies.

Fault rock is a typical hazardous material of water–silt inrush during the excavation in underground mines. To investigate hydraulic characteristics of fault rock during the water–silt inrush, a one-dimensional radial three-phase flow model of water–rock–silt was established in this study. In the proposed model, the mass conservation and continuity equations of the three-phase flow were obtained; the rock particle migration and the momentum conservation of the three-phase fluid migration were described by erosion constitutive equations and non-Darcy flow equations, respectively. The laboratory tests of porosity and the evolution of volume discharge rate were compared, and the accuracy of the proposed three-phase model was verified by the comparison results. From the test and numerical results, a high standard deviation of repeated results is observed in the case with high silt concentrations, and the erosion effect is inhibited by the silt flow. Last but not least, the temporal–spatial distribution of hydraulic properties is obtained by the numerical simulation: With the progress of the three-phase flow, rock particles near the fluid outlet are first fluidized and constantly migrate outward, resulting in an increase of the porosity and permeability in fault rock. Subsequently, water-conducting pathways are gradually formed inside the fault rock, and then more fluidized rock particles flow out. Finally, the fluidized rock particles have completely migrated, and the porosity and permeability tend to be stable with the more significant non-uniform spatial distribution.HighlightsA one-dimensional radial three-phase flow model of water-rock-silt is established.Mass conservation, continuity, erosion constitutive and non-Darcy flow relations are considered.Laboratory tests are designed to verify the proposed model from porosity and volume discharge rate.Temporal-spatial distribution of hydraulic properties during water-silt inrush is obtained.

High Mountain Asia (HMA) is one of the concentrated areas of surging glaciers in the world. The dynamic movement of surging glaciers not only reshapes the periglacial landscape but also has the potential to directly or indirectly trigger catastrophic events. Therefore, it is crucial to understand the distribution patterns, periodicities, and occurrence mechanisms of surging glaciers. Based on Landsat TM/ETM+/OLI remote sensing images from 1986 to 2021, a total of 244 surging glaciers were identified in HMA in this study, covering an area of 11,724 km2 and accounting for 12.01% of the total area of glaciers in this region. There are 185 surging glaciers identified within the Karakoram Range and Pamirs, which constitute the primary mountainous regions in HMA. From 1986 to 2021, these surging glaciers advanced at least 2802 times and exhibited different temporal and spatial patterns. A total of 36 glaciers in HMA experienced 2 or more surges during this period, with the highest number observed in the Pamirs (19), followed by the Karakorum (13), with the other regions having fewer occurrences. Obvious differences exist in the surge phase and the quiescent phase of glaciers in different regions of HMA. The surge phase of surging glaciers in the Karakoram Range and Pamirs is generally short, mostly in the range of 2~6 years. The quiescent phase lasts for 5~19 years and the overall surge cycle ranges from 9 to 24 years. The complex nature of glacier surges in HMA suggests that multiple mechanisms may be at play, necessitating further research.

Groundwater inrush is a typical hydrologic natural hazard in mining engineering. Since 2000 to 2012, there have been 1110 types of mine groundwater inrush hazards with 4444 miners died or missing. As a general geological structure in the northern China coalfields, the karst collapse pillar (KCP) contains a significant amount of granular rocks, which can be easily migrated under high hydraulic pressure. Therefore, the KCP zone acts as an important groundwater inrush pathway in underground mining. Grouting the KCP zone can mitigate the risk of groundwater inrush hazard. However, the fracture or instability of the coal pillar near KCP can cause the instability of surrounding rock and even groundwater inrush hazard. To evaluate the risk of groundwater inrush from the aquifer that is caused by coal pillars instability within grouted KCP in a gob, an in-situ investigation on the deformation of the surrounding strata was conducted. Besides, a mechanical model for the continuous effect on the coal pillar with the floor-pillar-roof system was established; then, a numerical model was built to evaluate the continuous instability and groundwater inrush risk. The collective energy and stiffness in the floor-pillar-roof system are the two criterions for judging the stability of the system. As a basic factor to keep the stability of floor-pillar-roof system, the collective energy in coal pillar is larger than that in floor-roof system. Moreover, if the stiffness of floor-roof or coal pillar meets a negative value, the system will lose stability; thus, the groundwater inrush pathway will be produced. However, if there is a negative value occurring in floor-pillar-roof system meets, it indicates that the system structure is situated in a damage state; a narrower coal pillar will enlarge the risk of continuous instability in the system, leading to a groundwater inrush pathway easily. Continuous coal pillars show a lower probability of instability. Conversely, the fractured coal pillars have a greater probability of failure. The plastic zone and deformation of the roadway roof in the fractured coal pillar are larger than that of continuous coal pillar, indicating that the continuous coal pillars mitigate the risk of groundwater inrush hazard effectively.

Water inflow from fault (WIF) and its secondary impacts are the main environmental challenges in the mining industry. Traditional prediction methods for WIF are exceedingly challenging and costly. In this article, two exponentially weighted moving average (EWMA) modified grey models (GMs, i.e., EGM and REGM) were established to predict the WIF. Particle swarm optimization (PSO) algorithm was employed to optimize parameters of the models. Based on actual WIF data from Buliangou coal mine, the optimized models (i.e., EGM-PSO, REGM-PSO) were used to obtain the prediction equations for WIF. To investigate the validity of the proposed models, the differences between actual values and predicted values were analyzed, and comparison results were obtained by the commonly used GM and GM-PSO. Results show that, for the sample with the larger initial particle swarm and smaller inertia weight, there is a faster convergence speed of the PSO algorithm. Particle search efficiency in the PSO-optimized EWMA-GM is higher than that in the GM-PSO. Through the predicted results of WIF, it is found that the REGM-PSO is the best choice for WIF prediction, and the more historical information, the higher the predicted accuracy. Besides, the parameter optimization by the PSO, the EWMA optimization method and optimization of residuals all can improve the predicted accuracy. Predicted results also show that WIF will have a substantial growth in the future. Therefore, reasonable measures (e.g., draining and grouting) need to be taken to mitigate the damage caused by fault water inflow.

With climate warming and intensification of human activities, the eco-environmental problems of lakes in middle and high latitudes become increasingly prominent. Qinghai Lake, located in the northeastern of the Tibetan Plateau, is the largest inland saltwater lake in China. Recently, the problem of Cladophora blooms has been widely concerning. In this study, the area of floating Cladophora blooms (hereafter FCBs) in Qinghai Lake from 1986 to 2021 was extracted using Floating Algal Index (FAI) method based on Landsat TM/ETM+/OLI and Sentinel-2 MSI images, and then the intra- and inter-annual variation characteristics and spatial patterns of FCBs were analyzed. The results show that the general change trend of FCBs in Qinghai Lake featured starting in May, expanding rapidly from June to August, and increasing steadily from September to October. From 1986 to 2021, the area of FCBs in Qinghai Lake showed an overall increasing trend in all months, with the largest increase in July at 0.1 km2/a, followed by October at 0.096 km2/a. Spatially speaking, the FCBs area showed a significant increasing trend in the northern Buha River estuary (BRN) and southern Buha River estuary (BRS) regions, a slight increase in the Shaliu River estuary (SR) region, and a decreasing trend in the Quanji River estuary (QR) region and the Heima River estuary (HR) region. The correlation between the meteorological factors and the changes in FCBs was weak, but the increase in flooded pastures in the BRN region (Bird Island) due to rising water levels was definitely responsible for the large-scale increase in FCBs in this region. However, the QB, northeastern bay of Shaliu River estuary (SRB) and HR regions, which also have extensive inundated grassland, did not have the same increase in FCBs area, suggesting that the growth of Cladophora is caused by multiple factors. The complex relationships need to be verified by further research. The current control measures have a certain inhibitory effect on the Cladophora bloom in Qinghai Lake because the FCBs area was significantly smaller in 2017–2020 (5.22 km2, 3.32 km2, 4.55 km2 and 2.49 km2), when salvage work was performed, than in 2016 and 2021 (8.67 km2 and 9.14 km2), when no salvage work was performed.