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Abstract As a necessary part of intelligent control of a joint station, the automatic identification of abnormal conditions and automatic adjustment of operation schemes need to judge the running state of the system. In this paper, a combination of Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) is proposed to optimize the Backpropagation Neural Network (BP) model (PSO-GWO-BP) and a pressure drop prediction model for the joint station export system is established using PSO-GWO-BP. Compared with the traditional hydraulic calculation modified (THCM) models and other machine learning algorithms, the PSO-GWO-BP model has significant advantages in prediction accuracy. Based on the PSO-GWO-BP pressure drop prediction model, the determination method of state identification threshold is established, and a state identification method based on dynamic threshold is proposed, which realizes the intelligent identification of the system operation state by automatically adjusting the threshold. Through the analysis of the production and operation data of the joint station, the abnormal working conditions are successfully identified, and the effectiveness and accuracy of the method are verified. This method not only enhances the ability to discriminate abnormal working conditions but also adaptively adjusts the operation scheme, which effectively improves the intelligence level of the joint station export system.

Debris flow landslides usually exhibit high sliding speed and long-distance slip, and their unstable slide is easy to cause serious damage to the surrounding area and significant property loss. On July 21, 2020, under the continuous influence of heavy rainfall, the Shaziba landslide in Enshi lost stability and transformed into a debris flow landslide, ultimately depositing within the Qing River, forming a dammed lake. To explore its kinematic features, such as velocity and displacement, during the Shaziba landslide’s sliding process and the evolving patterns of the landslide mass, a three-dimensional numerical model of the landslide was constructed using high-precision ortho-images obtained from unmanned aerial vehicles (drones). The parameters of the model were calibrated based on the mechanical properties of the landslide mass obtained from laboratory tests. Finally, the Particle Flow Code (PFC3D) software was used to simulate the process of the Shaziba debris flow landslide from sliding to deposition. It is determined that the movement time of the landslide was approximately 757 seconds, with a maximum average velocity of 4.9 m/s, and an average sliding distance of about 960 m. The dynamic process of the landslide can be divided into three stages: unstable sliding (0～18 s), flow propagation (18～331 s), and low-speed deposition (331～757 s). Throughout the sliding process, it exhibited the characteristics of hyper-distance and loss-distance, as well as the volume-increasing effect of debris flow landslides. The deposition pattern of the landslide mass in the Qing River displayed a conical accumulation shape, with thick accumulation near the landslide exit and thin accumulation in the opposite direction of the landslide, which closely matched the actual situation. The model effectively reproduces the sliding process of the Shaziba landslide from instability to deposition. This study can provide valuable insights for the prevention and study of geological hazards related to debris flow landslides.

Abstract Accurately determining the initial acoustic field excitation load of a piezoelectric ultrasonic probe is essential for simulating electrical signals and calculating wall thickness during ultrasonic internal inspection of pipelines. A new method for determining the initial excitation load of the acoustic field is proposed, incorporating the focusing effect of the curved surface of pipelines on the ultrasonic signal from the piezoelectric ultrasonic probe. Finite element models were established for the new and old methods using COMSOL software, facilitating the analysis of the initial acoustic field distribution and associated electrical signal characteristics. Scenarios considered included pipelines with and without inner wall defects, and with or without a deviation angle between the pipeline and the probe. The pipeline wall thickness was calculated inversely for each condition. Comparisons with actual wall thickness revealed that the initial excitation load determined by the new method significantly improved accuracy in wall thickness inversion, compared to the published existing method. This indicates that considering the focusing effect of the curved surface of pipelines on ultrasonic signals enhances the accuracy of simulation for piezoelectric ultrasonic internal inspection. This lays the groundwork for developing a digital research and development platform tailored for the ultrasonic internal detectors of pipeline.

Powdery mildew (PM) is a fungus that causes disease in both the field and the greenhouse. Utilizing resistant cultivars is the most effective approach of disease management. To develop insertion-deletion (InDel) markers associated to this trait, the whole genomes of the PM resistant line M17050 (P1) and the PM-susceptible line 28-1-1 (P2) were sequenced. A total of 1 200 InDels, with an average of 100 markers per chromosome, were arbitrarily chosen from the sequencing data for experimental validation. One hundred InDel markers were ultimately selected due to their informative genetic bands. Further, an F2 segregating population of melons generated from these two parents was inoculated by the PM pathogen. Based on bulk segregant analysis (BSA) using these 100 InDel markers, the powdery mildew resistance was associated with the genomic region LVpm12.1 on the melon chromosome 12. This region overlapped the previously described quantitative trait locus (QTL)-hotspot area carrying multiple PM-resistance QTLs. Moreover, conventional QTL mapping analysis was done, which located LVpm12.1 in the region between 22.72 and 23.34 Mb, where three highly polymorphic InDel markers MInDel89, MInDel92, and MInDel93 were detected. Therefore, these markers could be used to track this resistance locus in melon while the lines carrying this locus could be employed in PM melon resistance breeding programs after validation tests.

Objective Water inrush in karst tunnel has a great influence on tunnel safety. Methods Taking the Wufeng Tunnel of Yilai Expressway as the research object, the risk of water inrush in the tunnel was identified though field hydrogeological investigation, borehole water level and indoor rainfall monitoring, numerical simulation and small-scale model tests. Results The test results show that the risk of water inrush in the tunnel is mainly affected by the relative spatial position between the karst pipeline and tunnel, including the water pressure of the pipeline. The influence of seepage on the tunnel can be effectively reduced by increasing the thickness of the overlying soil when the test water pressure is 0.2 MPa. But with the increase in water pressure, the seepage of pipeline water is not only vertical seepage but also includes horizontal seepage. The intermittent cracks in the waterproof layer expand, which finally results in water inrush damage in the tunnel. The numerical simulation results show that the maximum shear force of the Wufeng Tunnel is at the arc and shoulder, which may easily form tensile shear failure along this part under groundwater seepage. The finding is consistent with the test results of the small-scale model. The water inrush in the tunnel is the coupling effect of the shear force and seepage field. Conclusion The primary factor of water inrush in the tunnel is water pressure and is closely related to the thickness of water barrier rock.

Objective The dry-wet cycles can promote the deterioration of the mechanical properties and stability of schist slope rock masses and induce geological disasters such as landslides and collapses. Methods Taking mica quartz schist, which is widely distributed in Shiyan, Hubei Province, as the research object, uniaxial compression tests and electron microscope scanning were carried out on mica quartz schist samples under different dry-wet cycles to reveal the degradation law and mechanism of its compressive property. Results The results show that under the action of dry-wet cycles, the degradation effect of the compressive strength and elastic modulus of mica quartz schist were obvious. The degradation rate was fast and the degradation range was large in the early stage, but the degradation rate was slow and the degradation range was low in the later stage. The macroscopic failure modes were gradually controlled by the schistosity planes, which gradually evolved from styles of "X" and "Y" failure to along the schistosity planes failure. The microstructure was characterized by continuous spalling and granulation of flake mineral particles, and the microcracks as well as pores were gradually developed, expanded and connected. The mica quartz schist produces secondary minerals, ions and rock cuttings and leaves the rock continuously under dry-wet cycles, which promotes the preferential expansion and cracking of schistosity, microcracks and other structural planes. which then degrades the overall mechanical properties of the mica quartz schist. Conclusion The research results can provide a theoretical basis for the stability analysis and treatment design of schist slopes.

The circular helicoid pile (CH pile) is a special-shaped pile with outstanding axial bearing properties developed in the last ten years, its pile-soil interaction problem has nonplanar strain and is non-axisymmetric. The coupled Eulerian-Lagrangian (CEL) method was applied to simulate the entire process of installation, axial compression and pullout loading of the CH pile in undrained clay to assess the interaction between the pile and soil, and the accuracy of the CEL model was verified by in-situ test results. The surfaces of the CH pile were divided into the bottom surface, outer and inner surfaces, with the inner surfaces including compressive and pullout surfaces. The variation in axial forces and moments on the CH pile and its various types of surfaces in the whole process of installation and bearing was clarified and the relative contribution of reacting forces and moments on various surfaces to the total resistance of the pile was evaluated. The stress distribution characteristics of the soil around the pile and the pile-soil interfaces after the installation of the CH pile and under the ultimate limit state were obtained, and then the force states of inner surfaces in the whole process of installation and bearing were analysed.

In engineering practice, engineers generally treated tuff as a lumpy material with a poorly defined laminated structure and a rock group that was not susceptible to slide failure. Most studies of tuff landslides had focused on small clastic landslides in shallow strata with weathering boundaries and lithologic interfaces as slip surfaces. This paper takes a large-scale, deep-seated tuff landslide on the southeast coast of China as the research project. We used borehole TV imaging and exploration tunnels to confirm the material composition and structural characteristics of the tuff stratum and used exploration tunnels to expose the slip soil directly. Microscopic identification, mineralogical composition analysis, zircon U-Pb isotope dating, and Hf isotope analysis of slip soils collected from the exploration tunnels elucidated the geologic background and genesis of the large-scale deep-seated landslides in the tuff stratum. It was found that the formation of a tuff stratum in the landslide area was caused by multi-volcanic orogeny and multi-phase tectonics. The timing of the melting of the original magma from these volcanic events also differs. During these intervals between eruptions, deposition occurred, and this sedimentary material formed the slip soil.

When using machine learning models for landslide susceptibility evaluation, the non-landslide sample points are usually selected randomly outside the landslide influence area, leading to a certain error. To improve the accuracy of landslide susceptibility evaluation, this paper couples the self-organizing map (SOM) neural network, information (I) model, and support vector machine (SVM) model, and proposes a SOM-I-SVM model-based method of landslide susceptibility evaluation, comparing with K-means clustering to verify the reliability of this model. The Maojian District of the city of Shiyan is taken as an example, and seven factors of the distance from water system, slope, rainfall, distance from structure, relative height difference, distance from road, stratigraphic lithology are selected by correlation and importance analyses of environmental factors to establish a landslide susceptibility evaluation system. Based on these, the graded information values of each factor are calculated and used as input variables for landslide susceptibility evaluation. The SOM neural network and K-means clustering are used to select non-landslide samples, and the sample data set is substituted into the I-SVM model to predict landslide susceptibility. The prediction accuracies of the four models, SVM, I-SVM, KMeans-I-SVM and SOM-I-SVM, are compared, and the area under the ROC curve (AUC values) are 0.82, 0.88, 0.90 and 0.91, indicating that the SOM-I-SVM model can effectively improve the accuracy of landslide susceptibility prediction.

Taking the Wantan Tunnel of Yilai Highway as the study case, the average water inflow and the water inflow in the wet season of the tunnel are calculated through field investigation, groundwater tracer experiment, groundwater flow monitoring, and atmospheric rainfall infiltration method. Meanwhile, the realistic failure process analysis(RFPA) is used to analyze the possibility of tunnel water inrush is judged. The results of field survey and tracer test show that the karst pipeline of Wantan Tunnel is a multi-branched, mixed-type karst pipeline with complicated hydrogeological conditions. The water inflow in wet season is about 4.6 times of the average tunnel water inflow. Mud failure will go through the stages of crack initiation, crack expansion, further crack expansion, and through-through failure. At the same time, when the water flow at the karst pipeline reaches about 2.7 to 3.5 times the initial value (37 248 m3/d), water gushing and mud inrush damage will occur, that is, when the flow of water outlet 2 reaches 10 000 to 13 000 m3/d, There is a very high risk of water and mud gushing in the Wantan Tunnel.

In order to clarify the ultimate pressure bearing capacity of polyethylene composite pipe reinforced by steel wires (hereinafter referred to as composite pipe) used for oil gathering in oilfields, a study was performed on 4731B composite pipe tried in No. 4 Oil Production Plant and the anti-scaling composite pipe tried in No. 5 Oil Production Plant of Changqing Oilfield. In the study, 2 groups of transient hydraulic fracturing experiment were performed respectively on the new pipe and the in-service pipe with a 100 MPa burst tester. Meanwhile, the break appearance and burst pressure were analyzed, and the instantaneous strains at different positions during the bursting process were recorded through a strain data acquisition system. The results indicate that the average instantaneous bursting pressure of this composite pipe in service is reduced to some extent, with the break appearance changed dramatically, and the expansion deformation increased significantly in comparison with the new pipes. Besides, the change of strain with time before bursting is divided into 3 stages, i.e., zero strain stage, linear growth stage and exponential growth stage. However, the strain after bursting oscillates until it is stabilized. The reason might be the local failure of adhesive between the steel wire and the high-density polyethylene matrix during the construction of composite pipe. These results could provide reference for the failure analysis of this type of composite pipe applied in oil gathering environment.

Mining activities can damage rock masses and easily induce ground collapse, which seriously threatens safe production in mining areas. Micro-seismic systems can monitor rock mass deformation signals in real time and provide more accurate data for rock mass deformation analysis. Therefore, in this study, the waveform characteristics of micro-seismic events induced by ground collapse in the Rongxing gypsum mine were analyzed; the occurrence of these events was introduced on the basis of Fast Fourier Transform, an established Frequency–Time–Amplitude model, in order to put forward the index of energy proportion of the main band. The results showed the following. (1) The seismic sequence type of ground collapse was foreshock–mainshock–aftershocks. The interval between the foreshock and mainshock was longer than that between the mainshock and aftershocks. (2) The deformation corresponding to the foreshock micro-seismic events was mainly that of a small-scale crack. The deformation corresponding to the micro-seismic events during the mainshock was characterized by the gradual development of small-scale cracks, and the development of large-scale cracks accelerated, accompanied by slight rock collapse. The deformation corresponding to the micro-seismic events during the aftershocks showed that almost no small-scale cracks developed, and the large-scale crack development was intense, and accompanied by numerous rock and soil mass collapses. (3) The observed decreasing frequency distribution and energy dispersion can be used as possible precursors of ground collapse.

In the exploration tunnels of the Xiageliao landslide, slide failures were found not only inside the slip soil but also on the contact surface between the slip soil and the tuff. The undisturbed slip soil was collected from the exploration tunnel for testing to explore the pattern of slide failure occurrence. The surfaces of concrete blocks of different shapes were used to simulate slip soil–tuff contact surfaces of different roughness. The shear strength of these contact surfaces with different roughness was tested using a large-scale shear test system and analyzed through comparison with the shear strength of the slip soil. The test results showed that the interface roughness significantly affected the shear strength of the slip soil contact interface and determined the shear failure mode of the slip soil. When the roughness is below a certain level, the shear strength of the contact surface is less than the soil shear strength, and when the roughness reaches a certain level, the shear strength of the contact surface exceeds the strength of the slip soil itself. Thus, the strength of the slip soil itself sometimes differs from the strength of the slip surface. Based on the Moore–Cullen law, the test results found a formula for calculating the contact surface shear strength. These results provide some references for the risk evaluation of landslides.

Landslide susceptibility mapping (LSM) is significant for landslide risk assessment. However, there remains no consensus on which method is optimal for LSM. This study implements a dynamic approach to landslide hazard mapping by integrating spatio-temporal probability analysis with time-varying ground deformation velocity derived from the MT-InSAR (Multi-Temporal InSAR) method. Reliable landslide susceptibility maps (LSMs) can inform landslide risk managers and government officials. First, sixteen factors were selected to construct a causal factor system for LSM. Next, Pearson correlation analysis, multicollinearity analysis, information gain ratio, and GeoDetector methods were applied to remove the least important factors of STI, plan curvature, TRI, and slope length. Subsequently, information quantity (IQ), logistic regression (LR), frequency ratio (FR), artificial neural network (ANN), random forest (RF), support vector machine (SVM), and convolutional neural network (CNN) methods were performed to construct the LSM. The results showed that the distance to a river, slope angle, distance from structure, and engineering geological rock group were the main factors controlling landslide development. A comprehensive set of statistical indicators was employed to evaluate these methods’ effectiveness; sensitivity, F1-measure, and AUC (area under the curve) were calculated and subsequently compared to assess the performance of the methods. Machine learning methods’ training and prediction accuracy were higher than those of statistical methods. The AUC values of the IQ, FR, LR, BP-ANN, RBF-ANN, RF, SVM, and CNN methods were 0.810, 0.854, 0.828, 0.895, 0.916, 0.932, 0.948, and 0.957, respectively. Although the performance order varied for other statistical indicators, overall, the CNN method was the best, while the BP-ANN and RBF-ANN method was the worst among the five examined machine methods. Hence, adopting the CNN approach in this study can enhance LSM accuracy, catering to the needs of planners and government agencies responsible for managing landslide-prone areas and preventing landslide-induced disasters.

The saturated hydraulic conductivity of soils is a critical concept employed in basic calculation in the geotechnical engineering field. The Kozeny–Carman equation, as a well-known relationship between hydraulic conductivity and the properties of soils, is considered to apply to sands but not to clays. To solve this problem, a new formula was established based on Hagen–Poiseuille's law. To explain the influence on the seepage channel surface caused by the interaction of soil particles and partially viscous fluid, the surface area ratio was introduced. A modified framework for determining the hydraulic radius was also proposed. Next, the relationship between the effective void ratio and the total void ratio was established for deriving the correlation of hydraulic conductivity and total void ratio. The improved equation was validated using abundant experimental results from clays, silts, and sands. According to the results, the accuracies of the proposed model with two fitted multipliers for clays, silts, and sands are 94.6, 96.6, and 100%, respectively, but with only one fitted parameter, the accuracies are 97.1, 91.5, and 100%, respectively. The proposed model can be considered to have a satisfactory capability to predict hydraulic conductivity for a wide variety of soils, ranging from clays to sands. HIGHLIGHTS An improved model of the soil particle-water system was proposed.; The surface area ratio δ is introduced.; We establish an improved method for estimating the effective void ratio.; The relationship between LL and As for clay was established.; The correlation between the parameters C and the specific surface area of soils was established.;

The circular helicoid pile (CH pile) is a new type of special-shaped pile that has been developed in Japan and South Korea in the past decade and has been widely used in the fields of construction, transportation, natural energy and agriculture due to its excellent compressive and pullout bearing performances. Consequently, this new type of pile has good engineering application prospects. However, as an innovative engineering structure, the CH pile is not widely known by geotechnical engineers worldwide. The geometric structure of the CH pile is similar to a circular helicoid in differential geometry. Therefore, the pile-soil interaction problem cannot be reduced to a plane strain problem or an axisymmetric problem in theoretical research. In view of this, dry silica sand was used as the model foundation in this study, and a model test device and method that can effectively reflect the installation process and loading-bearing service state of CH piles were developed. Under different installation methods, pile structures and foundation soil conditions, 90 model tests were carried out to evaluate the engineering performances of CH piles during the whole process of installation and bearing, including the installation performances during the installation process, the compressive bearing performances under axial compressive loading and the pullout bearing performances under axial pullout loading. Compared with steel sheet piles and steel pipe piles, CH piles have better engineering performance and more economic benefits from the aspects of installation, construction, recycling, timeliness of engineering application, and the relative relationship between bearing capacity and pile mass.

Corrosion products caused by accumulated water in low places of the product oil pipeline often lead to trunk line equipment blockage.It is an effective method to reduce the corrosion of product oil pipeline and prevent the pipeline blockage by oil flow shear to flush the accumulated water in low places and discharge it out of the pipeline.The research progress on the accumulated water flow characteristics, the accumulated water movement speed, the critical conditions under which accumulated water can be displaced, the influencing factors and rules of critical conditions were summarized, from the aspects of experimental research, theoretical analysis and numerical simulation.The existing problems in the current research were analyzed, and it was proposed that the experimental research on the distribution characteristics and movement speed of accumulated water should be carried out in a wider speed range(0.57–1.53 m/s).In addition, the critical conditions for the transformation from pipes pre-wetted with water to constant oil-wetting pipes should also be studied.The research results have guiding significance to discharging the accumulated water and impurities.

To study the transient characteristics of the sound field of the piezoelectric ultrasonic internal detector probe array, a finite element model of the probe array in the pipeline was established by COMSOL Multiphysics software, and the correctness was verified under experimental test conditions of the self-developed piezoelectric ultrasonic internal detector. Transient characteristics of the sound field under working conditions of single probe and double probes were studied respectively, and the variation of sound pressure at each point of the sound field under the two working conditions was obtained. The results show that the influence of echo signals on the signal reception of adjacent probes is small. When two adjacent probes work at the same time, the sound pressure superposition area is far away from the probe surface, and its influence on signal reception of adjacent probes can be easily eliminated. This model can determine the total sound field of a probe array in the pipeline under given conditions, and provide theoretical basis for the design of the piezoelectric ultrasonic internal detector.

The frequent and sharp fluctuations in garlic prices seriously affect the sustainable development of the garlic industry. Accurate prediction of garlic prices can facilitate correct evaluation and scientific decision making by garlic practitioners, thereby avoiding market risks and promoting the healthy development of the garlic industry. To improve the prediction accuracy of garlic prices, this paper proposes a garlic-price-prediction method based on a combination of long short-term memory (LSTM) and multiple generalized autoregressive conditional heteroskedasticity (GARCH)-family models for the nonstationary and nonlinear characteristics of garlic-price series. Firstly, we obtain volatility characteristic information such as the volatility aggregation of garlic-price series by constructing GARCH-family models. Then, we leverage the LSTM model to learn the complex nonlinear relationships between the garlic-price series and the volatility characteristic information of the series, and predict the garlic price. We applied the proposed model to a real-world garlic dataset. The experimental results show that the prediction performance of the combined LSTM and GARCH-family model containing volatility characteristic information of garlic price is generally better than those of the separate models. The combined LSTM model incorporating GARCH and PGARCH models (LSTM-GP) had the best performance in predicting garlic price in terms of evaluation indexes, such as mean absolute error, root mean-square error, and mean absolute percentage error. The combined model of LSTM-GARCH provides the best results in garlic price prediction and can provide support for garlic price prediction.

The stability of high rock slopes has become a key engineering geological problem in the construction of important projects in mountainous areas. The original slope stability probability classification (SSPC) system, presented by Hack, has made obvious progress and been widely used in rock slope stability analysis. However, the selection and determination of some evaluation indexes in the original SSPC method are usually subjective, such as intact rock strength and weathering degree. In this study, the SSPC method based on geological data obtained in the prospecting tunnels was presented and applied. According to the field survey and exploration of the prospecting tunnels, the weathering degree of the slope rock mass was evaluated. The empirical equation for the maximum stable height of the slope was applied to the slope stability evaluation in the presented SSPC method. Then, the slope stability probability of numerous cutting slopes in the sandstone unit was evaluated using the presented system. Results of the Geostudio software based on the limited equilibrium analysis of the investigated slopes were compared with the results obtained by the SSPC method. The results indicate that the SSPC method is a useful tool for the stability prediction of high and steep rock slopes.

Anticardiolipin antibody (aCL), an important characterization of antiphospholipid syndrome, shows an intense association with vascular endothelial injury. Hyperoside is a flavonoid extracted from medicinal plants traditionally used in Chinese medicines, displaying anti-inflammatory, anti-cancer, and anti-oxidative properties in various diseases. Recent studies have shifted the focus on the protective effects of hyperoside on vascular endothelial injury. However, little is known about the mechanisms involved. In the present study, we investigated the effect of hyperoside on aCL-induced injury of human umbilical vein endothelial cells (HUVECs) in vitro. Our data illustrated that aCL induced HUVEC injury via inhibiting autophagy. Hyperoside reduced aCL-induced secretion of proinflammatory cytokines IL-1β and IL-8 and endothelial adhesion cytokines TF, ICAM1, and VCAM1 in HUVECs. Additionally, hyperoside activated autophagy and suppressed the mTOR/S6K and TLR4/Myd88/NF-κB signaling transduction pathways in aCL-induced HUVECs. To the best of our knowledge, this is the first study to investigate the effect of hyperoside on aCL-induced injury, as well as offer insights into the involved mechanisms, which is of great significance for the treatment of antiphospholipid syndrome.

Objectives This study aimed to explore the effects of astragaloside IV on metabolic syndrome induced by a high-fructose/high-fat diet in rats. Methods Rats were randomized into four groups: normal control, metabolic syndrome, metabolic syndrome + intraperitoneal astragaloside 0.5 mg/kg/day, and metabolic syndrome + intraperitoneal astragaloside 2.0 mg/kg/day (n=30 per group) for 14 continuous days. Left ventricular functions were evaluated by hemodynamic and echocardiographic parameters. Results Metabolic syndrome rats had a thicker interventricular septum and left ventricular posterior wall, accompanied by a higher E/A wave ratio, reduced E′ wave, increased A′ wave, decreased E′/A′ wave ratio, and higher E/E′ wave ratio. Astragaloside decreased insulin and triglyceride levels and improved diastolic dysfunction with no effects on systolic function. A high-fructose/high-fat diet also increased oxidative stress and decreased the myocardial endothelial nitric oxide synthase (NOS) dimer ratio, thus impairing nitric oxide (NO) production and reducing cyclic guanosine monophosphate (cGMP) production. Astragaloside increased NO and cGMP production in the myocardium and improved diastolic function. Conclusions Astragaloside alleviated oxidative stress and restored NO signaling, thus improving myocardial left ventricular diastolic dysfunction in rats with metabolic syndrome. The underlying mechanisms could be associated with alleviation of oxidative stress and activation of the endothelial NOS/NO/cGMP pathway.

Wastes in municipal landfills will release heavy metal cations over a long period of time. Therefore, the objective of this paper was to investigate the effect of copper (Cu) in the leachate from landfill on the swell-shrinking potential of bentonite liner. Copper sulfate solution with 4 different groups of concentrations (0 g/L, 2.5 g/L, 5 g/L, 10 g/L) were added to bentonite for conducting a series of swelling and shrinkage experiments. Then the Does Response model was used to describe the swelling and shrinkage process of bentonite in different copper sulfate solutions and the applicability of the model was evaluated. At the same time, clay mineral analysis experiments (XRD and XRF) were carried out to analyze the variation of interlayer space and element content of montmorillonite. The results show that the swell volume of bentonite decreases with the increase of the concentration of Cu (II). The rate of swelling was high and inversely proportional to the concentration of Cu (II). The shrinkage curve of bentonite could be divided into uniform velocity stage, variable velocity stage, and stable stage. The shrinkage rate at the uniform velocity stage and shrinkage at the stable stage decreased with the increase of the concentration of Cu (II). The model was suitable for describing swelling (or shrinkage) curves with smaller expansibility (or shrinkage). Results of XRD and XRF show that the erosion of Cu (II) led to the decrease of Na+ content in sodium bentonite, and then narrowed interlayer space of montmorillonite. When the solution concentration increases, both values of interlayer space of montmorillonite and Na+ content in sodium bentonite become lower, and that led to swelling and shrinkage of bentonite liner was getting smaller and smaller.

GmNAC5 is a member of NAM subfamily belonging to NAC transcription factors in soybean (Glycine max (L.) Merr.). Studies on NAC transcription factors have shown that this family functioned in the regulation of shoot apical meristem (SAM), hormone signalling, and stress responses. In this study, we examined the expression levels of GmNAC5. GmNAC5 was highly expressed in the roots and immature seeds, especially strongly in immature seeds of 40 days after flowering. In addition, we found that GmNAC5 was induced by mechanical wounding, high salinity, and cold treatments but was not induced by abscisic acid (ABA). The subcellular localization assay suggested that GmNAC5 was targeted at nucleus. Together, it was suggested that GmNAC5 might be involved in seed development and abiotic stress responses in soybean.

Powdery mildew (PM) is a fungus that causes disease in both the field and the greenhouse. Utilizing resistant cultivars is the most effective approach of disease management. To develop insertion-deletion (InDel) markers associated to this trait, the whole genomes of the PM resistant line M17050 (P1) and the PM-susceptible line 28-1-1 (P2) were sequenced. A total of 1 200 InDels, with an average of 100 markers per chromosome, were arbitrarily chosen from the sequencing data for experimental validation. One hundred InDel markers were ultimately selected due to their informative genetic bands. Further, an F2 segregating population of melons generated from these two parents was inoculated by the PM pathogen. Based on bulk segregant analysis (BSA) using these 100 InDel markers, the powdery mildew resistance was associated with the genomic region LVpm12.1 on the melon chromosome 12. This region overlapped the previously described quantitative trait locus (QTL)-hotspot area carrying multiple PM-resistance QTLs. Moreover, conventional QTL mapping analysis was done, which located LVpm12.1 in the region between 22.72 and 23.34 Mb, where three highly polymorphic InDel markers MInDel89, MInDel92, and MInDel93 were detected. Therefore, these markers could be used to track this resistance locus in melon while the lines carrying this locus could be employed in PM melon resistance breeding programs after validation tests [ABSTRACT FROM AUTHOR]