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Abstract Gastric cancer (GC) contains subpopulations of cancer stem cells (CSCs), which are described as the main contributors in tumor initiation and metastasis. It is necessary to clarify the molecular mechanism underlying CSCs phenotype and develop novel biomarkers and therapeutic targets for gastric cancer. Here, we show that POLQ positively regulates stem cell-like characteristics of gastric cancer cells, knockdown of POLQ suppressed the stemness of GC cells in vitro and in vivo. Further mechanistic studies revealed that POLQ knockdown could downregulate the expression of dihydroorotate dehydrogenase (DHODH). DHODH overexpression rescued the reduced stemness resulted by POLQ knockdown. Furthermore, we found that POLQ expression correlated with resistance to ferroptosis, and POLQ inhibition renders gastric cancer cells more vulnerable to ferroptosis. Further investigation revealed that POLQ regulated DHODH expression via the transcription factors E2F4, thereby regulating ferroptosis resistance and stemness of gastric cancer cells. Given the importance of POLQ in stemness and ferroptosis resistance of GC, we further evaluated the therapeutic potential of POLQ inhibitor novobiocin, the results show that novobiocin attenuates the stemness of GC cells and increased ferroptosis sensitivity. Moreover, the combination of POLQ inhibitor and ferroptosis inducer synergistically suppressed MGC-803 xenograft tumor growth and diminished metastasis. Our results identify a POLQ-mediated stemness and ferroptosis defense mechanism and provide a new therapeutic strategy for gastric cancer.

Abstract In recent years, immunotherapy has emerged as a promising strategy for treating solid tumors, although its efficacy remains limited to a subset of patients. Transforming non-responsive “cold” tumor types into immuno-responsive “hot” ones is critical to enhance the efficacy of immune-based cancer treatments. Pyroptosis, a programmed cell death mechanism, not only effectively eliminates tumor cells but also triggers a potent inflammatory response to initiate anti-tumor immune activities. This sheds light on the potential of pyroptosis to sensitize tumors to immune therapy. Hence, it is urgent to explore and develop novel treatments (e.g., nanomedicines) which are capable of inducing pyroptosis. In this study, we constructed tumor-targeting nanoparticles (CS-HAP@ATO NPs) by loading atorvastatin (ATO) onto chondroitin sulfate (CS) modified hydroxyapatite (HAP) nanoparticles (CS-HAP). CS was strategically employed to target tumor cells, while HAP exhibited the capacity to release calcium ions (Ca2+) in response to the tumor microenvironment. Moreover, ATO disrupted the mitochondrial function, leading to intracellular energy depletion and consequential changes in mitochondrial membrane permeability, followed by the influx of Ca2+ into the cytoplasm and mitochondria. CS and HAP synergetically augmented mitochondrial calcium overload, inciting the production of substantial amount of reactive oxygen species (ROS) and the subsequent liberation of oxidized mitochondrial DNA (OX-mitoDNA). This intricate activation process promoted the assembly of inflammasomes, most notably the NLRP3 inflammasome, followed by triggering caspase-1 activation. The activated caspase-1 was able to induce gasderminD (GSDMD) protein cleavage and present the GSDM-N domain, which interacted with phospholipids in the cell membrane. Then, the cell membrane permeability was raised, cellular swelling was observed, and abundant cell contents and inflammatory mediators were released. Ultimately, this orchestrated sequence of events served to enhance the anti-tumor immunoresponse within the organism.

Two critical factors, namely intense precipitation and intricate excavation, can trigger rock mass disasters in mining operations. In this study, an indoor rainfall system was developed to precisely regulate the flow and intensity of precipitation. A large-scale model experiment was conducted on a self-designed physical simulation experiment platform to investigate the failure and instability of high-steep rock slopes under unsaturated conditions. The real-time reproduction of the progressive failure process in high-steep rock slopes enabled the determination of the critical rainfall intensity and revealed the mechanism underlying slope instability. Experiment results indicated that rainfall may be the primary factor contributing to rock mass instability, while continuous pillar mining exacerbates the extent of rock mass failure. The critical failure stage of high-steep rock slopes occurs at a rainfall intensity of 40 mm/h, whereas a rainfall exceeding 50 mm can induce critical instability and precipitation reaching up to 60 mm will result in slope failure. The improved region growing segmentation method (IRGSM) was subsequently employed for image recognition of rock mass deformation in underground mines. Herein an error comparison with the simple linear iterative cluster (SLIC) superpixel method and the original region growing segmentation method (ORGSM) showed that the average identification error in the X and Y directions by the method was reduced significantly (1.82% and 1.80% in IRGSM; 4.70% and 6.26% in SLIC; 9.45% and 12.40% in ORGSM). Ultimately, the relationship between rainfall intensity and failure probability was analyzed using the Monte Carlo method. Moreover, the stability assessment criteria of rock slope under unsaturated condition were quantitatively and accurately evaluated.

Monocular 3D object detection plays a pivotal role in autonomous driving, presenting a formidable challenge by requiring the precise localization of 3D objects within a single image, devoid of depth information. Most existing methods in this domain fall short of harnessing the limited information available in monocular 3D detection tasks. They typically provide only a single detection outcome, omitting essential uncertainty analysis and result post-processing during model inference, thus limiting overall model performance. In this paper, we propose a comprehensive framework that maximizes information extraction from monocular images while encompassing diverse depth estimation and incorporating uncertainty analysis. Specifically, we mine additional information intrinsic to the monocular 3D detection task to augment supervision, thereby addressing the information scarcity challenge. Moreover, our framework handles depth estimation by recovering multiple sets of depth values from calculated visual heights. The final depth estimate and 3D confidence are determined through an uncertainty fusion process, effectively reducing inference errors. Furthermore, to address task weight allocation in multi-task training, we present a versatile training strategy tailored to monocular 3D detection. This approach leverages measurement indicators to monitor task progress, adaptively adjusting loss weights for different tasks. Experimental results on the KITTI and Waymo dataset confirm the effectiveness of our approach. The proposed method consistently provides enhanced performance across various difficulty levels compared to the original framework while maintaining real-time efficiency.

The Xihu Depression is the largest hydrocarbon-bearing depression of the East China Sea Shelf Basin (also referred to as the ECSSB). However, the depositional systems and reservoir distribution of the Oligocene Huagang Formation in the Xihu Depression are still controversial. Under the guidance of sedimentology and stratigraphy, this study documented a marine-terrestrial transitional environment in the restricted bay setting of the Oligocene Huagang Formation through core description, well logging, and seismic data analysis. This study also revealed that the Oligocene Huagang Formation is dominated by tidal delta, estuary, and gravity flow deposits in the central anticline zone of the Xihu Depression. The new understanding of the sedimentary systems and the discovery of the transgressive gap in the eastern Diaoyu Islands uplift explain the origin of fine-grained sediments and the EW-trending sand bodies in the central depression and the sand bodies parallel to shoreline in the west slope belt, which cannot be explained by previous study results, such as southern transgression or fluvial deltas and even lacustrine deposition. Moreover, the tidal channels, tidal sand flats, and gravity flow sand bodies formed by the transgressive tides are high-quality reservoirs. The study will provide a basis for well placement and serve as guidance for the selection of favorable hydrocarbon exploration areas in the Xihu Depression.

At present, the architecture modeling method of fluvial reservoirs are still developing. Traditional methods usually use grids to characterize architecture interbeds within the reservoir. Due to the thin thickness of this type of the interlayers, the number of the model grids must be greatly expanded. The number of grids in the tens of millions often makes an expensive computation; however, upscaling the model will generate a misleading model. The above confusion is the major reason that restricts the large-scale industrialization of fluvial reservoir architecture models in oilfield development and production. Therefore, this paper explores an intelligent architecture modeling method for multilevel fluvial reservoirs based on architecture interface and element. Based on the superpositional relationship of different architectural elements within the fluvial reservoir, this method uses a combination of multilevel interface constraints and non-uniform grid techniques to build a high-resolution 3D geological model for reservoir architecture. Through the grid upscaling technology of heterogeneous architecture elements, different upscaling densities are given to the lateral-accretion bedding and lateral-accretion bodies to simplify the model gridding. This new method greatly reduces the number of model grids while ensuring the accuracy of lateral-accretion bedding models, laying a foundation for large-scale numerical simulation of the subsequent industrialization of the architecture model. This method has been validated in A layer of X oilfield with meandering fluvial channel sands as reservoirs and B layer of Y oilfield with braided river sands as reservoirs. The simulation results show that it has a higher accuracy of production history matching and remaining oil distribution forecast of the targeted sand body. The numerical simulation results show that in the actual development process of oilfield, the injected water will not displace oil in a uniform diffusive manner as traditionally assumed, but in a more complex pattern with oil in upper part of sand body being left behind as residual oil due to the influences of different levels of architecture interfaces. This investigation is important to guiding reservoir evaluation, remaining oil analysis, profile control and potential tapping and well pattern adjustment.

Fracturing with proppants is often used to improve the permeability of coalbed methane (CBM) reservoir. The fracture is easy to close under the closure stress and the proppant distribution in fractures greatly influences the extraction efficiency of CBM. The past research mainly considered the impact of fracturing damage on the coalbed methane extraction but rarely investigated the influence of the proppant distribution forms on CBM extraction. Therefore, based on the theory of dual-porous media, this paper establishes a theoretical model of CBM extraction with different proppant distribution forms, which considers the proppant compaction, embedment, and fracture aperture change. The model is implemented numerically and is validated against field results of CBM production. The research results show that the extraction efficiency of CBM from high to low is the pulse proppant injection, continuous proppant injection, no proppant injection, no fracturing. The continuous proppant injection should ensure that the proppant placement rate is more than 60 %. The CBM extraction efficiency is the highest when the proppant column length is 0.2 m–0.3 m and the void area length is 0.5 m. The research results provide a theoretical basis for improving the extraction efficiency of coalbed methane using fracturing with sand injection.

Background The primary objective of this study was to investigate if hepatic impairment alters the safety, pharmacokinetics, and pharmacodynamics of HSK3486.Research design and methods This was a clinical trial of HSK3486 in subjects with normal hepatic function (n = 8), and mild (Child-Pugh A; n = 8), or moderate (Child-Pugh B; n = 8) hepatic impairment. Each subject received an IV bolus dose of 0.4 mg/kg HSK3486 for 1 min, immediately followed by a maintenance infusion of 0.4 mg/kg/h HSK3486 for 30 min.Results In total, 24 subjects were enrolled and completed the study. HSK3486 was generally well tolerated by all subjects. There were no serious AEs and no deaths reported during the study. The incidence of AEs was numerically highest in subjects with moderate hepatic impairment. The exposure (AUC) of HSK3486 increased gradually with the decrease in hepatic function; however, degree of hepatic impairment had little effect on HSK3486 PD (MOAA/S and BIS).Conclusions Overall, there were no clinically relevant differences in HSK3486 exposure or PD in subjects with mild or moderate hepatic impairment compared to normal control. These data imply that HSK3486 dose adjustment is not warranted in subjects with mild or moderate hepatic impairment.Trial registration The trial is registered at ClinicalTrials.gov (CT.gov identifier: NCT04145596).Key MessageHSK3486 at an IV bolus dose of 0.4 mg/kg and a maintenance infusion of 0.4 mg/kg/h was safe and well tolerated by all mild or moderate hepatic impairment subjects and normal hepatic function subjects.There were no clinically relevant differences in HSK3486 exposure or PD in subjects with mild or moderate hepatic impairment compared to subjects with normal hepatic function.HSK3486 dose adjustment is not required in subjects with mild or moderate hepatic impairment.

The Ordovician reservoirs in the Tahe oilfield are dominated by fractured-vuggy carbonate reservoirs, of which fault-karst reservoirs are a hot topic in recent years. Fault-karst reservoirs feature high production, large burial depth, and strong heterogeneity under the control of faulting and karstification. Based on geological, logging, and seismic data, this study classified the Ordovician fault-karst reservoirs in the Yuejin block of the Tahe oilfield into three types, namely karst-cave, dissolved-vug, and fractured types, and established the integrated identification criteria of the three types of reservoirs. This study characterized karst caves, dissolved vugs, and multi-scale faults through seismic wave impedance inversion and frequency-domain detection of multi-scale faults. 3D geological models of different types of reservoirs were built using the combined deterministic and stochastic methods and characterized the spatial distribution of multi-scale faults, karst caves, dissolved vugs, and physical property parameters of reservoir. This study established the method for the geological modeling of fault-karst reservoirs, achieved the quantitative characterization and revealed the heterogeneity of fault-karst reservoirs. The karst-cave and dissolved-vug types are high in porosity and act as reservoirs, while the fractured type is high in permeability and act as flow pathway. This study lays the foundation for the development index prediction, well emplacement, and efficient development of the fault-karst carbonate reservoirs.

Abstract In view of the shortcomings of existing artificial neural network (ANN) and support vector regression (SVR) in the application of three-dimensional displacement back analysis, Gaussian process regression (GPR) algorithm is introduced to make up for the shortcomings of existing intelligent inversion methods. In order to improve the generality of the standard GPR algorithm with single kernel function, an improved Gaussian process regression (IGPR) algorithm with combined kernel function is proposed by adding two single kernel functions. In addition, in the training process of IGPR model, the particle swarm optimization (PSO) is combined with the IGPR model (PSO-IGPR) to optimize the parameters of the IGPR model. After the IGPR model can accurately map the relationship between geomechanical parameters and rock mass deformation, the PSO algorithm is directly used to search the best geomechanical parameters to match the deformation calculated by igpr model with the measured deformation of rock mass. The application case of Beikou tunnel shows that the combined kernel function GPR has higher identification accuracy than the single kernel function GPR and SVR model, the IGPR model with automatic correlation determination (ARD) kernel function can obtain higher identification accuracy than the IGPR model with isotropic (ISO) kernel function, and the PSO-IGPR hybrid model based on ARD kernel function has the highest identification accuracy. Therefore, this paper proposes a displacement back analysis method of the PSO-IGPR hybrid algorithm based on ARD kernel function, which can be used to identify the geomechanical parameters of rock mass and solve other engineering problems.

Abstract Colorectal cancer (CRC) is a malignant tumor and morbidity rates are among the highest in the world. The variation in CRC patients' prognosis prompts an urgent need for new molecular biomarkers to improve the accuracy for predicting the CRC patients' prognosis or as a complement to the traditional TNM staging for clinical practice. CRC patients' gene expression data of HTSeq‐FPKM and matching clinical information were downloaded from The Cancer Genome Atlas (TCGA) datasets. Patients were randomly divided into a training dataset and a test dataset. By univariate and multivariate Cox regression survival analyses and Lasso regression analysis, a prediction model which divided each patient into high‐or low‐risk group was constructed. The differences in survival time between the two groups were compared by the Kaplan–Meier method and the log‐rank test. The weighted gene co‐expression network analysis (WGCNA) was used to explore the relationship between all the survival‐related genes. The survival outcomes of patients whose overall survival (OS) time were significantly lower in the high‐risk group than that in the low‐risk group both in the training and test datasets. Areas under the ROC curves which termed AUC values of our 9‐gene signature achieved 0.823 in the training dataset and 0.806 in the test dataset. A nomogram was constructed for clinical practice when we combined the 9‐gene signature with TNM stage and age to evaluate the survival time of patients with CRC, and the C‐index increased from 0.739 to 0.794. In conclusion, we identified nine novel biomarkers that not only are independent prognostic indexes for CRC patients but also can serve as a good supplement to traditional clinicopathological factors to more accurately evaluate the survival of CRC patients.

AbstractIn this paper, the effect of high temperature on the mechanical properties of quartz-rich sandstone was studied by true triaxial pressure experiment. The density, P-wave velocity, elastic modulus, peak stress, peak strain, and failure mode of quartz-rich sandstone before and after heat treatment were analyzed and compared. It was found that the color of quartz-rich sandstone changes greatly when heated to 500°C. In detail, the brittleness of quartz-rich sandstone gradually decreased and the ductility increased at high temperature. Although the density, P-wave velocity, and elastic modulus fluctuate, they showed a decreasing trend as a whole. In addition, the peak stress and peak strain showed an overall upward trend with the increase of temperature, and 500°C was the high-temperature failure threshold of quartz-rich sandstone. The failure mode of quartz-rich sandstone at high temperature changes from shear failure to shear-tension combined failure, and the number of cracks increases. Therefore, these research results can provide a certain reference for high-temperature underground operation.

The disposal of industrial by-product tailings has become an important issue in solving environmental pollution. In this study, 15%, 30%, 50%, and 70% iron tailings were used to replace the natural sand in concrete, and 1.5% steel fiber and 0–0.75% PVA fibers were added to the iron tailings concrete. The effects of the iron tailings replacement rate and the fiber content on the mechanical properties, carbonization depth, and concrete porosity were studied in a carbonization environment. The results demonstrated that the compressive and splitting tensile strengths of concrete first increased and subsequently decreased with an increase in the iron tailings replacement rate, while the carbonation depth and porosity initially decreased and subsequently increased. When the replacement rate of iron tailings was 30%, the compressive strength and split tensile strength were increased by 7.6% and 17.7%, respectively, and the porosity was reduced by 8.9%. The compressive strength, carbonation depth and porosity of single-doped steel-fiber concrete were superior to those of ordinary iron tailings concrete. However, compared with single-doped steel fiber, the performance of steel-PVA fiber was further improved. Based on the mechanical properties, the carbonation depth test results of the three aforementioned types of concrete, the mathematical expression of the uniaxial compression stress–strain curve of iron tailings concrete, and the prediction equation of the carbonation depth of mixed-fiber iron tailings concrete were proposed. This study provides a reference for the application and popularization of fiber-reinforced iron tailings concrete in carbonization environments.

Immune system disorder is associated with metastasis of triple-negative breast cancers (TNBCs). A robust, individualized immune-related genes (IRGs)-based classifier was aimed to develop and validate in our study to precisely estimate the axillary lymph node (ALN) status preoperatively in patients with early-stage TNBC. We first analyzed RNA sequencing profiles in TNBC patients from The Cancer Genome Atlas database by using bioinformatics approaches, and screened 23 differentially expressed IRGs. A 9-gene panel was generated with an area under the curve (AUC) of 0.77 [95% confidence interval (95% CI), 0.68–0.87]. We detected the 9 ALN-status-related IRGs in the training set (n = 133) and developed a reduced and optimized five-IRGs signature, which effectively distinguished TNBC patients with ALN metastasis (AUC, 0.80; 95% CI, 0.65–0.86), and was superior to preoperative ultrasound-based ALN status (AUC, 0.73; 95% CI, 0.53–0.93). Predictive efficiency (AUC, 0.77; 95% CI 0.61–0.93) of this five-IRGs signature was validated in the validation set (n = 81). Furthermore, IRGs nomogram incorporated IRGs signature with US-based ALN status showed higher ALN status prediction efficacy than US-based ALN status and five-IRGs signature alone in both training and validation sets. IRGs nomogram may aid in identifying patients who can be exempted from axillary surgery.Novelty and impact: An immune-related genes (IRGs) nomogram was first developed and externally validated in our study, which incorporated the IRGs signature with ultrasound (US)-based axillary lymph nodes (ALN) status. IRGs nomogram is superior to IRGs signature alone for preoperative estimation of ALN metastasis in patients with triple-negative breast cancer (TNBC). It is a favourable biomarker for preoperatively predicting ALN metastasis risk and may aid in clinical decision-making in early-stage TNBCs.

The observation of the air gap discharge process is the basis of revealing the physical mechanism of gas discharge and establishing the accurate numerical simulation model. In order to obtain the variation characteristics at different development stages during the air gap discharge processes under positive and negative lightning impulses in this paper, repetitive discharge tests of 1 m rod-plate air gap under standard lightning impulse were carried out in the National Engineering Laboratory (Kunming) for Ultrahigh-voltage Engineering Technology. An improved discharge observation method, using electron-multiplying intensified charge-coupled device (EMICCD) camera, was adopted in the test. A series of discharge spatial-temporal distribution images with nanosecond exposure time and interval time were captured by changing the shooting time delay of the EMICCD in repetitive discharges. The complete discharge development process was reproduced by the image stitching. The development process and the characteristics of the air gap discharge under lightning impulse were analyzed qualitatively. The characteristics of the measured discharge current under the positive lightning impulse were discussed. The testing results and the analysis show that the shape and the development process of the ionization region of the streamer are quite different under different lightning impulses. There are spherical and fan-shaped streamer regions under the positive and negative lightning impulse, respectively. After the streamer runs through the entire gap, the leader develops from the rod electrode to the plate electrode (under the positive impulse) or from both the rod and the plate electrode to the middle area (under the negative impulse). Then the final jump occurs and the gap is broken down. If the streamer still cannot penetrate the entire gap when the applied impulse voltage exceeds the peak, the gap will not be broken down finally.

Gas outburst can result in great loss of life and property during tunnel construction. Gas outburst in tunnels in non-coal formation is often more harmful than that in coal-bearing formation. In order to take effective countermeasures to prevent the occurrence of gas outburst during tunnel construction, it is essential to assess the risk of gas outburst before tunnel construction. This paper attempts to establish an assessment system for evaluating the risk of gas outburst in tunnels in non-coal formation in the survey phase of tunnelling based on the attribute mathematical theory. Based on the principle of relevance and operability, eight factors that influence the gas outburst in non-coal formation are selected as the attribute evaluation indices. Attribute measure functions are constructed to calculate the single index attribute measures for evaluation indices. The fuzzy Analytic Hierarchy Process is used to determine weights of evaluation indices. A confidence criterion is applied to recognize the risk grade of the evaluation object. The proposed attribute evaluation system is applied to assess the gas outburst risk in a tunnel in the survey phase. The evaluation results show good agreement with the practical situation of gas, verifying the applicability of this attribute assessment system.

Sweet corn seeds are sensitive to storage due to their low starch content and poor seed vigor. Therefore, it is important to understand their physiological and biochemical behavior during storage to prolong their longevity and prevent the loss of vigor. The purpose of this study was to elucidate the physiological and biochemical changes in sweet corn seeds during storage. Artificial accelerated aging and natural aging were applied to 19 inbred lines. We found that GP, GR and VI decreased as aging proceeded. The physiological and biochemical characteristics of seeds three days after artificial aging (AA3d) and eight months after natural aging (NA8M) were evaluated. The contents of GA, ABA, and malondialdehyde and amylase activity in AA3d and NA8M seeds showed significant differences among the lines, while the total protein and total starch content showed nonsignificant or small differences. We found significant differences among the lines and a nonsignificant difference between AA3d and NA8M seeds in the activity of antioxidant enzymes. A correlation analysis showed that the germination rate was significantly negatively correlated with the ABA content in AA3d seeds, while SOD was positively correlated with GR and GI in NA8M seeds. This study provides a useful catalog of physiological and biochemical changes in sweet corn seeds, offering insights for the future genetic improvement of sweet corn’s storage tolerance.

The triggering threshold is one of the most important parameters for landslide early warning systems (EWSs) at the slope scale. In the present work, a velocity threshold is recommended for an early warning system of the Gapa landslide in Southwest China, which was reactivated by the impoundment of a large reservoir behind Jinping’s first dam. Based on GNSS monitoring data over the last five years, the velocity threshold is defined by a novel method, which is implemented by the forward and reverse double moving average of time series. As the landslide deformation is strongly related to the fluctuations in reservoir water levels, a crucial water level is also defined to reduce false warnings from the velocity threshold alone. In recognition of the importance of geological evolution, the evolution process of the Gapa landslide from topping to sliding is described in this study to help to understand its behavior and predict its potential trends. Moreover, based on the improved Saito’s three-stage deformation model, the warning level is set as “attention level”, because the current deformation stage of the landslide is considered to be between the initial and constant stages. At present, the early warning system mainly consists of six surface displacement monitoring sites and one water level observation site. If the daily recorded velocity in each monitoring site exceeds 4 mm/d and, meanwhile, the water level is below 1820 m above sea level (asl), a warning of likely landslide deformation accelerations will be released by relevant monitoring sites. The thresholds are always discretely exceeded on about 3% of annual monitoring days, and they are most frequently exceeded in June (especially in mid-June). The thresholds provide an efficient and effective way for judging accelerations of this landslide and are verified by the current application. The work presented provides critical insights into the development of early warning systems for reservoir-induced large-scale landslides.

Lightning strike is the main reason for the transmission line tripping. Studies on the insulator flashover characteristics and the accurate flashover criteria under the lightning impulse are the basis for correctly evaluating the lightning resistance performance of the transmission line. In this paper, an experimental study on the flashover characteristics of the insulators with different materials was carried out on the 110-kV double-circuit transmission line tower. The insulators were hung on the umbrella-shaped tower and the drum-shaped tower in the test, and both the standard lightning impulse (1.2/ $50~\mu \text{s}$ ) and the short-tail lightning impulse (1/ $10~\mu \text{s}$ ) were used. The flashover test of a single composite insulator was also carried out for comparatively analyzing the influence of the true tower on the insulator flashover performance. According to the test results on the true tower, the lightning flashover criteria of the insulators with different materials are given. The influencing factors of the insulator flashover characteristics, including the impulse waveform, the insulator material, the tower type, and the insulator suspension position, were further compared and analyzed. Meanwhile, the results of the single insulator test proved that the true tower has great influence on the insulator flashover characteristics and that the flashover test on the true tower can reflect actual situation better and obtain more accurate results. In addition, based on the simulation analysis results of the electric-field distribution around the insulators, the difference of 50% impulse flashover voltage ( $U_{\mathrm {50\%}}$ ) of the insulators in different conditions was partly explained.

The emission of SO2 from ships is an important source of atmospheric pollution. Therefore, the International Maritime Organization (IMO) has established strict requirements for the sulfur content of marine fuel oil. In this paper, a new optical noncontact detection technique for ship exhaust emissions analysis is studied. Firstly, the single-band simulation analysis model of the imaging detection technology for SO2 concentration in ship exhaust gas and the deep neural network model for the prediction of sulfur content were established. A bench test was designed to monitor the tail gas concentration simultaneously using online and imaging detection methods, so as to obtain the concentration data in the flue and the ultraviolet image data. The results showed that 300 nm had a higher inversion accuracy than the other two bands. Finally, a deep neural network model was trained with the SO2 concentration data from the inversion and the engine power, and the predictive model of sulfur content in marine fuel oil was thereby obtained. When the deep learning model was used to predict sulfur content, the prediction accuracy at 300, 310, and 330 nm was 73%, 94%, and 71%, respectively.

The SO2 discharged by ships causes serious pollution to the atmosphere. Therefore, the International Maritime Organization has set strict requirements on the sulfur content of marine fuel. For the first time, this study investigates the optimal detection wavelength based on the imaging technology to realize an accurate monitoring of the SO2 concentration in ship exhaust. First, a simulation analysis model of the optimal imaging detection (SAMID) wavelength of the SO2 concentration in ship exhaust is proposed and analyzed in this study. Next, a bench experiment is designed. The values and the range of the gas concentration values required for the simulation are obtained. Finally, based on the principle of minimum error, the optimal detection wavelengths of the single- and the dual-wavelength imaging detection technologies are determined as 287 nm and 297 nm and 298 nm, respectively. During the SO2 concentration retrieval, the minimum values of the root mean squared error, the mean absolute error, and the mean absolute percentage error of the single- and the dual-wavelengths are 563.14 molecules/cm3, 445.11 molecules/cm3, and 347.22% and 0.62 molecules/cm3, 0.49 molecules/cm3, and 0.85%, respectively. The simulation analysis results provide a theoretical basis for the future hardware development of an optical remote sensing system based on the imaging detection technology.

Mixed Poisson–Gaussian noise exists in the star images and is difficult to be effectively suppressed via maximum likelihood estimation (MLE) method due to its complicated likelihood function. In this article, the MLE method is incorporated with a state-of-the-art machine learning algorithm in order to achieve accurate restoration results. By applying the mixed Poisson–Gaussian likelihood function as the reward function of a reinforcement learning algorithm, an agent is able to form the restored image that achieves the maximum value of the complex likelihood function through the Markov Decision Process (MDP). In order to provide the appropriate parameter settings of the denoising model, the key hyperparameters of the model and their influences on denoising results are tested through simulated experiments. The model is then compared with two existing star image denoising methods so as to verify its performance. The experiment results indicate that this algorithm based on reinforcement learning is able to suppress the mixed Poisson–Gaussian noise in the star image more accurately than the traditional MLE method, as well as the method based on the deep convolutional neural network (DCNN).

Limit equilibrium method (LEM) and strength reduction method (SRM) are the most widely used methods for slope stability analysis. However, it can be noted that they both have some limitations in practical application. In the LEM, the constitutive model cannot be considered and many assumptions are needed between slices of soil/rock. The SRM requires iterative calculations and does not give the slip surface directly. A method for slope stability analysis based on the graph theory is recently developed to directly calculate the minimum safety factor and potential critical slip surface according to the stress results of numerical simulation. The method is based on current stress state and can overcome the disadvantages mentioned above in the two traditional methods. The influences of edge generation and mesh geometry on the position of slip surface and the safety factor of slope are studied, in which a new method for edge generation is proposed, and reasonable mesh size is suggested. The results of benchmark examples and a rock slope show good accuracy and efficiency of the presented method.

Understanding the interaction of surface water and groundwater affected by anthropogenic activities is of great importance for water resource and water quality management. The Xiong’an New Area, located in the North China Plain, has been designated a new building area by China’s government. Groundwater has been over pumped and artificial water was transferred to meet the water supply in this region. Therefore, the natural interaction of surface water and groundwater has been greatly changed and there has been a complex impact of the groundwater from anthropogenic activities. In this study, we used water chemical ions and stable isotopes of δ2H and δ18O to assess the interaction of surface water and groundwater in the Xiong’an New Area. We carried out field surveys and water sampling of the Fu River (domestic waste water discharge), Lake Baiyangdian (artificial water transfer), and the underlying groundwater along the water bodies. Results show that the artificial surface water (discharged and transferred) became the major recharge source for the local groundwater due to the decline of groundwater table. We used groundwater table observations, end-member mixing analysis of the stable isotopic composition and chloride tracers to estimate the contributions of different recharge sources to the local groundwater. Due to the over pumping of groundwater, the lateral groundwater recharge was dominant with a contribution ratio ranging from 12% to 78% in the upper reach of the river (Sections 1–3). However, the contribution of lateral groundwater recharge was estimated to be negligible with respect to the artificial water recharge from Lake Baiyangdian. Seepage from the Fu River contributed a significant amount of water to the connecting aquifer, with a contribution ranging from 14% to 75% along the river. The extent of the river influence into the aquifer ranges as far as 1400 m to the south and 400 m to the north of the Fu River. Estimations based on isotopic fractionation shows that about 25% of Lake Baiyangdian water was lost by evaporation. By using the stable isotopes of oxygen and hydrogen in the lake water, an influencing range of 16 km west of the lake was determined. The interaction of the surface water and groundwater is completely changed by anthropogenic activities, such as groundwater over pumping, waste water discharge and water transfer. The switched interaction of surface water and groundwater has a significant implication on water resources management.

Three strategies using lamivudine have been proposed to prevent chemotherapy-induced HBV (hepatitis B virus) reactivation in the clinical setting. The purpose of this meta-analysis is to evaluate the efficacy of the early preemptive strategy, deferred preemptive strategy and therapeutic strategy in patients with HBsAg-positive breast cancer during chemotherapy.Clinical studies published from database inception until Nov 1, 2014, were included for analysis. The primary outcomes were overall survival, rate of chemotherapy disruption and virological and clinical reactivation. The secondary outcomes were the rates of HBV-related chemotherapy disruption, HBV-related mortality, YMDD mutations and withdrawal hepatitis.Four hundred and thirty patients in four studies that compared the early preemptive strategy with a therapeutic strategy were included. Application of early preemptive lamivudine was superior in reducing HBV recurrence (pooled OR: 0.12, 95% CI, 0.04 to 0.31, P< 0.0001), the incidence of HBV-related hepatitis (pooled OR: 0.13, 95% CI, 0.04 to 0.37, P< 0.0001) and the rate of chemotherapy disruption (pooled OR: 0.37, 95% CI, 0.23 to 0.60, P< 0.0001). In these two groups, no significant difference was found in overall mortality (P = 0.32), YMDD mutant rate (P = 0.13) or incidence of withdrawal hepatitis (P = 0.38). Of the two studies that compared the efficacy of an early and a deferred preemptive strategy, one showed that an early preemptive strategy significantly reduced the incidence of hepatitis (P = 0.046), whereas the other showed no significant difference (P = 0.7).An early preemptive strategy is superior to a therapeutic strategy in decreasing the incidence of HBV reactivation, incidence of HBV-related hepatitis and rate of chemotherapy disruption in patients with breast cancer. A deferred preemptive strategy might be an alternative approach to controlling viral replication.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications. [ABSTRACT FROM AUTHOR]