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The construction of intelligent fully mechanized mining faces in China’s coal mines is in its early stages, and the automation technology of hydraulic support electro-hydraulic control has been widely applied. However, at present, the automation control logic of a single solidification of hydraulic supports is difficult to adapt to complex, ever-changing, and dynamic production scenarios. The actual control process in mine face still mostly adopts a collaborative approach of automation and manual intervention. In response to the demand for human-machine interaction and cooperation tasks in the complex scenarios of fully mechanized mining faces, a theoretical method and technical principle of a multimodal human-machine collaborative control system for hydraulic supports following the shearer in the middle range mining face (hereinafter referred to as hydraulic supports following) was proposed. Firstly, four human-machine collaborative modes, namely manual, division of labor, approval, and veto, were designed. Based on the factors such as coal seam geology, gas and dust, shearer speed, hydraulic support intelligence level, system status, job technical level, and task load, an AND-OR graph model for hydraulic support human-machine collaborative mode selection was constructed, which achieved a modal selection with manual or machine preferences. Then, a human-machine collaborative control decision-making mechanism for hydraulic supports following was designed. On this basis, an AI inference technology for the secondary control strategy of hydraulic supports following was proposed. Specifically, using on-site data to learn manual operation experience, a decision tree classification model for whether the hydraulic support should be secondary controlled and a Bayesian regression model for estimating the secondary control time of pulling hydraulic support were constructed. Based on the above model, a human-machine collaborative control decision-making program for the hydraulic support following was developed, which achieved human-machine collaborative control of hydraulic supports following based on AND/OR inference for modal selection and AI inference for secondary control strategy. Finally, using cloud edge end architecture software and hardware technology, a multimodal human-machine collaborative control system for hydraulic supports following was developed, which achieved the control functions such as model evolution, operational reasoning, and program execution. The system has undergone industrial trial operation on the 3404 mining face of Shaqu No.2 Mine. The result shows the efficiency of the hydraulic support following has increased by an average of 2% compared to that before. This paper forms an efficient and safe human-machine interactive decision-making mechanism for the comprehensive mining equipment group, which will provide practical theoretical methods and feasible technical paths for the development of intelligent comprehensive mining working faces.

Abstract Magma intrusion has an important influence on the physical and mechanical properties of coal and rock. In the area of magma intrusion, disasters such as gas outburst are prone to occur. Revealing its invasion law will be conducive to disaster management and energy development. For this purpose, changes in industrial analysis components of coal, mineral composition, major oxides, trace elements, and rare earth elements of coal under the thermal metamorphism of magma intrusion were analyzed. It is found that the moisture and volatile matter contents of the thermally affected coals in the mining face are generally lower than that of normal coals, while moisture and volatile matter contents are reduced towards to the magma intrusion contact. For example, the moisture and volatile matter of coal sample M01 decreased by 64.6% and 38.6% respectively compared with coal sample M05. During magma intrusion, some minerals remain on the surface of the coal body, resulting in changes in the mineral composition of the coal body. The decrease in carbon atom net spacing, the increase in crystallite aggregation and ductility, and aromaticity in thermally affected coals have a positive impact on the improvement of coal metamorphism. Due to the influences of magmatic intrusion, the variation rules of major oxides in coal are different, and the closer to the magmatic intrusion zone, the easier the major oxides are to be depleted. However, magma intrusion will not lead to the loss of all major oxides in thermally affected coals, such as content of CaO is 54.8%, which is higher than that of coal not affected by magmatic hydrothermal fluid. Most of the trace elements in the thermally affected coals of the No. 9 coal seam are depleted. The contents of rare earth elements are low on the whole coalbasis, with an average of 29.48 μg/g, and the distribution pattern towards to magmatic intrusion shows a wide and gentle “V” curve with left high and right low, showing the characteristics of enrichment of light rare earth elements.

Abstract Asphalt overlay is widely used in maintaining and rehabilitating highway system performance. However, explicit calculation methods for the asphalt overlay thickness range is lacking. Taking stone mastic asphalt (SMA) and asphalt concrete (AC) asphalt overlay on cement concrete pavement as examples, the paper proposed a design method for the asphalt overlay thickness range based on the shear performance of the interlayer. Firstly, the shear stress distribution regularities on the asphalt overlay and Portland cement concrete interlayer was calculated with a multilayer elastic theory. Meanwhile, the shear strength was obtained from a series of direct shear tests. The shear characters of the asphalt overlay met with the Mohr–Coulomb criterion, and the shear strength parameters cohesive force $$c$$ c and interface friction angle $$\varphi$$ φ on the interlayer were acquired. Finally, a method for determining the thickness range of double layer asphalt overlay under different traffic conditions was given. The epoxy resin adhesive was recommended for the highway with severe local premature shear failure compared with the modified emulsion asphalt. Therefore, through the above research, the amount of asphalt used is controlled in a reasonable range, thus improving the pavement structure durability and reducing energy consumption.

Efficient carbon use is crucial for biological nitrogen removal. Traditional aerobic processes can waste carbon sources, exacerbating carbon deficiency. This study explores an anaerobic/oxic/anoxic system with sludge double recirculation to improve nitrogen removal in low C/N wastewater. This system integrated aerobic nitrification after the carbon intracellular storage, separating carbon and nitrogen by denitrifying glycogen-accumulating organisms (DGAOs) with endogenous partial denitrification and Anammox within the anoxic units. A significant efficiency of 91.02±7.01% chemical oxygen demand (COD) was converted into intracellular carbon in anaerobic units, significantly reducing carbon futile oxidation in the aerobic units by effectively separating COD from ammonia. Intracellular storage of carbon sources and microbial adaptation to carbon scarcity prevent futile oxidation of COD in the aerobic units even with short-term high dissolved oxygen (DO), thereby enhancing nitrogen removal under anoxic conditions with sufficient intracellular carbon source. The microbial analysis identified Candidatus Brocadia as the dominant anammox bacteria, in combination with the activity of DGAOs and other related microbial communities, accounting for 37.0% of the TN removal. Consequently, the system demonstrated remarkable nitrogen removal efficiencies, achieving 81.3±3.3% for total nitrogen (TN) and 98.5±0.9% for ammonia nitrogen while maintaining an effluent COD concentration of 17.2±9.1 mg/L, treating the low C/N of 4.18 in the influent wastewater. The findings in this study provide a sustainable and energy-saving technique for conventional WWTPs to meet strict discharge standards by avoiding futile oxidation of COD and encouraging anammox contributions.

Infection by multidrug-resistant avian pathogenic Escherichia coli (APEC) in chickens always leads to the uselessness of antibiotics, highlighting the need for alternative antibacterial agents. Sophora flavescens and Coptis chinensis have been a classical combination used together in Traditional Chinese Medicine (TCM) formulas to treat diseases with similar symptoms to colibacillosis for an extended period, but the effect of their active ingredients' combination on APEC infection remains unstudied. The objective of this study was to explore the synergistic effect of matrine and berberine hydrochloride on colibacillosis caused by an isolated multidrug-resistant APEC. In this study, a highly pathogenic E. coli was isolated from the liver of a diseased chicken in a farm suspected of colibacillosis, and it was resistant to multiple antibiotics. The LD50 of the strain was approximately 3.759×108 CFU/mL. The strain harbored several antibiotic resistance genes and virulence genes. Matrine and berberine hydrochloride have synergistic antibacterial effect against the isolated strain in vitro. The combined use of matrine and berberine hydrochloride exhibited synergistic effects in the treatment of APEC infection by regulating the organ indices, improving the pathological situation, decreasing the bacterial load, and regulating the inflammatory factors to enhance the survival rate of chickens in vivo. These results provided a foundation for revealing the effective effects and possible mechanisms of matrine and berberine hydrochloride as potential antimicrobial agents on diseases caused by multidrug-resistant APEC in chickens.

IntroductionThe unique dormancy of Mycobacterium tuberculosis plays a significant role in the major clinical treatment challenge of tuberculosis, such as its long treatment cycle, antibiotic resistance, immune escape, and high latent infection rate.MethodsTo determine the function of MtrA, the only essential response regulator, one strategy was developed to establish its regulatory network according to high-quality genome-wide binding sites.Results and discussionThe complex modulation mechanisms were implied by the strong bias distribution of MtrA binding sites in the noncoding regions, and 32.7% of the binding sites were located inside the target genes. The functions of 288 potential MtrA target genes predicted according to 294 confirmed binding sites were highly diverse, and DNA replication and damage repair, lipid metabolism, cell wall component biosynthesis, cell wall assembly, and cell division were the predominant pathways. Among the 53 pathways shared between dormancy/resuscitation and persistence, which accounted for 81.5% and 93.0% of the total number of pathways, respectively, MtrA regulatory genes were identified not only in 73.6% of their mutual pathways, but also in 75.4% of the pathways related to dormancy/resuscitation and persistence respectively. These results suggested the pivotal roles of MtrA in regulating dormancy/resuscitation and the apparent relationship between dormancy/resuscitation and persistence. Furthermore, the finding that 32.6% of the MtrA regulons were essential in vivo and/or in vitro for M. tuberculosis provided new insight into its indispensability. The findings mentioned above indicated that MtrA is a novel promising therapeutic target for tuberculosis treatment since the crucial function of MtrA may be a point of weakness for M. tuberculosis.

Hydraulic support leg pressure serves as a crucial indicator for assessing work face support quality. Current evaluation methods for support quality primarily concentrate on static analyses-like inadequate initial support force, pressure overrun, and uneven bracket force-while neglecting dynamic column pressure changes. This paper introduces a model for assessing hydraulic support quality using deep learning techniques. Real-time data is preprocessed into a spatio-temporal pressure sub-matrix sample, which is then inputted into the model. This process assesses the support quality type and characterizes its dynamic evolution within the area. The model facilitates the identification of dynamic support quality effects in the working face area, aiding operators in making targeted adjustments to hydraulic support status. Experimental results revealed that the optimized LeNet-5 network-adjusting parameters like convolutional layer count, kernel size, and ReLU activation function-achieved the highest classification accuracy of 85.25 % for support quality, surpassed other networks. Furthermore, the improved LeNet-5 network outperformed other networks in both F1 score and recall. Additionally, the improved LeNet-5 network achieved faster convergence to the optimal solution, accelerated training speed. This highlighted its advantages in evaluating the spatio-temporal support quality of hydraulic supports in smart mining operations.

The coal's particle size distribution properties after pulverization and the gas desorption behavior driven by pulverization are of profound meaning to the study of coal and gas outburst mechanism. In this paper, based on the impact crushing experiment, the tectonic coal and primary coal are crushed under different impact energy conditions. After screening the broken coal, the particle size distribution law is analyzed, and the characterization function suitable for the particle size distribution of coal particles after crushing is determined. The relationship between crushing work and new surface area and fractal dimension of coal body is discussed. The consequences indicated that the mass proportion of tectonic coal below 0.074 mm particle size is much huger than that of raw coal. G-S, R–R, and fractal distribution model describe the best particle size distribution of the two coals in the scope of 0.074∼4 mm. The new surface area added increases with the crushing work, and the tectonic coal is 1.34–1.96 times that of the raw coal. The fractal dimension diminishes first and then increases with the crushing work ratio. In addition, the gas desorption amount of coal particles with different particle sizes after coal pulverization was measured, and a dynamic model suitable for coal pulverization-driven gas desorption was established, and the experimental results were verified. The research results of this paper can provide experimental and theoretical basis for the analysis of energy dissipation in coal and gas outburst.

BackgroundRemimazolam is a new ultra-short-acting benzodiazepine for procedural sedation and general anaesthesia, characterised by rapid onset of action, quick recovery, and organ-independent metabolism. Older patients tend to sustain more treatment-emergent adverse events (TEAEs) and worse perioperative prognoses after receiving remimazolam. However, few studies have investigated the appropriate dose of remimazolam for loss of consciousness (LOC) in geriatric patients. We designed this study to provide evidence for dose references and elucidate the relationship between age and remimazolam requirement for inducing LOC during anaesthesia induction.MethodsExactly 120 patients scheduled for general surgery under general anaesthesia were included and divided into two groups: Group A (60 patients, 18–64 years) and Group B (60 patients, ≥ 65 years). LOC, defined as a Modified Observer’s Assessment of Alertness and Sedation score at 1 had been reached, emerged after all participants received a continuous infusion of remimazolam at a rate of 0.05 mg/kg/min.ResultsThe remimazolam required for inducing LOC was 0.26 and 0.19 mg/kg in groups A and B, respectively, and the remimazolam dose in group B decreased by 26.9% compared to group A. According to the bivariate linear correlation analysis, remimazolam requirement was negatively correlated with age. Multivariable linear regression models and further adjustments for potential impact factors indicated that age was an independent factor for the remimazolam dose required for LOC.ConclusionThis study demonstrated that age was significantly and independently correlated with the remimazolam requirement for inducing LOC. To obtain haemodynamic stability during the induction of general anaesthesia, appropriately reducing the remimazolam dose is recommended for geriatric patients.

Abstract Coal and gas outburst is a complex dynamic disaster during coal underground mining. Revealing the disaster mechanism is of great significance for accurate prediction and prevention of coal and gas outburst. The geo-dynamic system of coal and gas outburst is proposed. The framework of geo-dynamic system is composed of gassy coal mass, geological dynamic environment and mining disturbance. Equations of stress–damage–seepage interaction for gassy coal mass is constructed to resolve the outburst elimination process by gas extraction with boreholes through layer in floor roadway. The results show the occurrence of outburst is divided into the evolution process of gestation, formation, development and termination of geo-dynamic system. The scale range of outburst occurrence is determined, which provides a spatial basis for the prevention and control of outburst. The formation criterion and instability criterion of coal and gas outburst are established. The formation criterion F 1 is defined as the scale of the geo-dynamic system, and the instability criterion F 2 is defined as the scale of the outburst geo-body. According to the geo-dynamic system, the elimination mechanism of coal and gas outburst—‘unloading + depressurization’ is established, and the gas extraction by boreholes through layer in floor roadway for outburst elimination is given. For the research case, when the gas extraction is 120 days, the gas pressure of the coal seam is reduced to below 0.4 MPa, and the outburst danger is eliminated effectively.

Previous studies have shown that Acanthopanax senticosus (AS) has a beneficial preventive and therapeutic effect on colitis. The fermentation of lactic acid bacteria (LAB) can alter the efficacy of AS by modifying or producing new compounds with potential bioactive properties. However, the specific components and mechanisms that enhance the efficacy are still unclear. In the present experiment, untargeted metabolomics was used to analyze the changes in active components before and after LAB fermentation of AS. The aim was to explain the mechanism of AS fermentation in treating colitis using a colitis model in mice. The results indicated that the fermentation of LAB could enhance the levels of total flavonoids and total polyphenols in FAS. Additionally, the beneficial components such as Delphinidin chloride, Diosmetin, Psoralidin, and Catechol significantly increased (p < 0.05). The colitis treatment experiment demonstrated that fermented AS could alleviate symptoms and improve the morphology of colitis in mice by enhancing antioxidant enzymes like CAT, T-SOD, and T-AOC. It also regulated the composition and abundance of intestinal flora species, such as Lactobacillus and Pseudogracilibacillus. The effectiveness of fermented AS was significantly superior to that of unfermented AS (p < 0.05). In conclusion, this study contributes to the application of lactic acid bacteria in AS fermentation and reveals the mechanism of fermentation AS for colitis.

In the steep terrain of southwestern China, there are numerous complex strata characterized by thin overburden layers and well-behaved underlying bedrock, yet excavation poses significant challenges. This situation is unfavorable for the construction of transmission towers’ foundations. To address this issue, inclined anchor short-pile foundations have been proposed as foundations for transmission towers. These foundations not only reduce the depth and construction difficulty of excavation but also make full use of the load-bearing capacity of the bedrock. To investigate the influence of the anchor rods’ layout on the uplift resistance characteristics of inclined anchor short-pile foundations, numerical models were established using FLAC3D. The effects of the anchor rods’ position and the length of the free segment on the uplift resistance characteristics of inclined anchor short-pile foundations were explored. The results indicated that variations in the anchor rods’ position and the length of the free segment had minimal impact on the uplift resistance characteristics of inclined anchor short-pile foundations. The pile head displacements of short piles with different anchor rod positions were similar under both loading conditions. Under pure uplift loads, the maximum displacement before failure was approximately 13 mm, while under combined uplift and horizontal loads, the maximum displacement before failure was around 15 mm. Placing the anchor rod too low increased the difficulty of construction, while positioning it too high resulted in a shorter embedment length of the anchor rod in the pile’s body, leading to potential failure at the pile–anchor node. Therefore, it is recommended to position the anchor rod near the center of the short pile’s body. As the length of the free segment of the anchor rod decreased, there was a slight reduction in the displacement under the same uplift loading conditions, with an overall difference of less than 5%. However, if full-length anchoring was adopted, the anchor rod was prone to tensile shear failure. Compared with short-pile foundations of the same size, inclined anchor short-pile foundations demonstrated enhanced ultimate bearing capacity under uplift and combined uplift and horizontal loading. The improvement was more significant when horizontal loads were present. Under horizontal loading, the ultimate uplift bearing capacity of inclined anchor short-pile foundations decreased by only 14%, whereas that of single-pile foundations decreased by 24%.

Heterogeneity has been one of the main barriers to understanding and treatment of autism spectrum disorder (ASD). Previous studies have identified several subtypes of ASD through unsupervised clustering analysis. However, most of them primarily depicted the pairwise similarity between individuals through second-order relationships, relying solely on patient data for their calculation. This leads to an underestimation of the complexity inherent in inter-individual relationships and the diagnostic information provided by typical development (TD). To address this, we utilized an elastic net model to construct an individual deviation-based hypergraph (ID-Hypergraph) based on functional MRI data. We then conducted a novel community detection clustering algorithm to the ID-Hypergraph, with the aim of identifying subtypes of ASD. By applying this framework to the Autism Brain Imaging Data Exchange repository data (discovery: 147/125, ASD/TD; replication: 134/132, ASD/TD), we identified four reproducible ASD subtypes with roughly similar patterns of ALFF between the discovery and replication datasets. Moreover, these subtypes significantly varied in communication domains. In addition, we achieved over 80% accuracy for the classification between these subtypes. Taken together, our study demonstrated the effectiveness of identifying subtypes of ASD through the ID-hypergraph, highlighting its potential in elucidating the heterogeneity of ASD and diagnosing ASD subtypes.

Abstract Natural defects, such as joints, structural surfaces and voids, significantly affect the mechanical properties and fracture modes of rock mass. Hidden fissures are widely distributed in magmatic rock, while their influences on the mechanical properties and the cracking mechanism are still unclear. Laboratory tests were conducted on prefabricating hidden-fissured rock-like specimens, as well as intact specimens and close-fissured specimens as a comparison. The real-time digital image correlation technology and acoustic emission monitoring technology were synchronously adopted to capture both the external and internal cracking process. The results show that the hidden fissures can weaken the uniaxial compression strength, while the deterioration effect of hidden fissures is weaker than closed fissures due to the internal cohesion among fissure internal particles. What’s more, the initiation behavior of the α = 90° hidden-fissured specimen is different from that of β = 90° closed-fissured specimen. Finally, the cracking mechanism of hidden-fissured specimens was revealed by analyzing the RA–AF relationship. The failure of the close-fissured specimens is mainly the tensile-shear mixed fracture mode, while the failure of the hidden-fissured specimens is mainly the tensile fracture mode and supplemented by the shear. The experimental results contribute to the understanding of cracking properties in hidden-fissured rock.

With the rapid development of hydrogen energy worldwide, the number of hydrogen energy facilities, such as hydrogen refueling stations, has grown rapidly in recent years. However, hydrogen is prone to leakage accidents during use, which could lead to hazards such as fires and explosions. Therefore, research on the safety of hydrogen energy facilities is crucial. In this paper, a study of high-pressure hydrogen jet flame accidents is conducted for a proposed integrated hydrogen production and refueling station in China. The effects of leakage direction and leakage port diameter on the jet flame characteristics are analyzed, and a risk assessment of the flame accident is conducted. The results showed that the death range perpendicular to the flame direction increased from 2.23 m to 5.5 m when the diameter of the leakage port increased from 4 mm to 10 mm. When the diameter of the leakage port is larger than 8 mm, the equipment on the scene will be within the boundaries of the damage. The consequences of fire can be effectively mitigated by a reasonable firewall setup to ensure the overall safety of the integrated station.

Liquid hydrogen storage is an important way of hydrogen storage and transportation, which greatly improves the storage and transportation efficiency due to the high energy density but at the same time brings new safety hazards. In this study, the liquid hydrogen leakage in the storage area of a hydrogen production station is numerically simulated. The effects of ambient wind direction, wind speed, leakage mass flow rate, and the mass fraction of gas phase at the leakage port on the diffusion behavior of the liquid hydrogen leakage were investigated. The results show that the ambient wind direction directly determines the direction of liquid hydrogen leakage diffusion. The wind speed significantly affects the diffusion distance. When the wind speed is 6 m/s, the diffusion distance of the flammable hydrogen cloud reaches 40.08 m, which is 2.63 times that under windless conditions. The liquid hydrogen leakage mass flow rate and the mass fraction of the gas phase have a greater effect on the volume of the flammable hydrogen cloud. As the leakage mass flow rate increased from 5.15 kg/s to 10 kg/s, the flammable hydrogen cloud volume increased from 5734.31 m3 to 10,305.5 m3. The installation of a barrier wall in front of the leakage port can limit the horizontal diffusion of the flammable hydrogen cloud, elevate the diffusion height, and effectively reduce the volume of the flammable hydrogen cloud. This study can provide theoretical support for the construction and operation of hydrogen production stations.

Considering the requirements pertaining to the trafficability of off-road vehicles on rough roads, and since their roll stability deteriorates rapidly when turning violently or passing slant roads due to a high center of gravity (CG), an efficient anti-slip control (ASC) method with superior instantaneity and robustness, in conjunction with a rollover prevention algorithm, was proposed in this study. A nonlinear 14 DOF vehicle model was initially constructed in order to explain the dynamic coupling mechanism among the lateral motion, yaw motion and roll motion of vehicles. To acquire physical state changes and friction forces of the tires in real time, corrected LuGre tire models were utilized with the aid of resolvers and inertial sensors, and an adaptive sliding mode controller (ASMC) was designed to suppress each wheel’s slip ratio. In addition, a model predictive controller (MPC) was established to forecast rollover risk and roll moment in reaction to the change in the lateral forces as well as the different ground heights of the opposite wheels. During experimentation, the mutations of tire adhesion capacity were quickly discerned and the wheel-hub drive motors (WHDM) and ASC maintained the drive efficiency under different adhesion conditions. Finally, a hardware-in-the-loop (HIL) platform made up of the vehicle dynamic model in the dSPACE software, semi-active suspension (SAS), a vehicle control unit (VCU) and driver simulator was constructed, where the prediction and moving optimization of MPC was found to enhance roll stability effectively by reducing the length of roll arm when necessary.

With the increasing consumer focus on automotive safety, Autonomous Emergency Braking (AEB) systems, recognized as effective active safety technologies for collision avoidance and the mitigation of collision-related injuries, are gaining wider application in the automotive industry. To address the issues of the insufficient working reliability of AEB systems and their unsatisfactory level of accordance with the psychological expectations of drivers, this study proposes an optimized second-order Time to Collision (TTC) safety time algorithm based on the motion state of the preceding vehicle. Additionally, the study introduces a safety distance algorithm derived from an analysis of the braking process of the main vehicle. The safety time algorithm focusing on comfort and the safety distance algorithm focusing on safety are effectively integrated in the time domain and the space domain to obtain the safety time–safety distance fusion algorithm. A MATLAB/Simulink–Carsim joint simulation platform has been established to validate the AEB control strategy in terms of safety, comfort, and system responsiveness. The simulation results show that the proposed safety time–safety distance fusion algorithm consistently achieves complete collision avoidance, indicating a higher safety level for the AEB system. Furthermore, the application of active hierarchical braking minimizes the distance error, at under 0.37 m, which meets psychological expectations of drivers and improves the comfort of the AEB system.

Lakes on the Qinghai Tibet Plateau (QTP) are widely distributed spatially, and they are mostly seasonally frozen. Due to global warming, the thickness and phenology of the lake ice has been changing, which profoundly affects the regional climate evolution. There are a few studies about lake ice in alpine regions, but the understanding of climatological characteristics of lake ice on the QTP is still limited. Based on a field experiment in the winter of 2022, the thermal conductivity of Qinghai Lake ice was determined as 1.64 W·m−1·°C−1. Airborne radar ice thickness data, meteorological observations, and remote sensing images were used to evaluate a quasi-steady ice model (Leppäranta model) performance of the lake. This is an analytic model of lake ice thickness and phenology. The long-term (1979–2017) ice history of the lake was simulated. The results showed that the modeled mean ice thickness was 0.35 m with a trend of −0.002 m·a−1, and the average freeze-up start (FUS) and break-up end (BUE) were 30 December and 5 April, respectively, which are close to the field and satellite observations. The simulated trend of the maximum ice thickness from 1979 to 2017 (0.004 m·a−1) was slightly higher than the observed result (0.003 m·a−1). The simulated trend was 0.20 d·a−1 for the FUS, −0.34 d·a−1 for the BUE, and −0.54 d·a−1 for the ice duration (ID). Correlation and detrending analysis were adopted for the contribution of meteorological factors. In the winters of 1979–2017, downward longwave radiation and air temperature were the two main factors that had the best correlation with lake ice thickness. In a detrending analysis, air temperature, downward longwave radiation, and solar radiation contributed the most to the average thickness variability, with contributions of 42%, 49%, and −48%, respectively, and to the maximum thickness variability, with contributions of 41%, 45%, and −48%, respectively. If the six meteorological factors (air temperature, downward longwave radiation, solar radiation, wind speed, pressure, and specific humidity) are detrending, ice thickness variability will increase 83% on average and 87% at maximum. Specific humidity, wind, and air pressure had a poor correlation with ice thickness. The findings in this study give insights into the long-term evolutionary trajectory of Qinghai Lake ice cover and serve as a point of reference for investigating other lakes in the QTP during cold seasons.

IntroductionAtherosclerosis is the primary pathological basis of ischemic stroke, and dyslipidemia is one of its major etiological factors. Acute ischemic stroke patients exhibit imbalances in lymphocyte subpopulations, yet the correlation between these dynamic changes in lymphocyte subpopulations and lipid metabolism disorders, as well as carotid atherosclerosis in stroke patients remains poorly understood.MethodsWe retrospectively analyzed the demographic data, risk factors of cerebrovascular disease, laboratory examination (lymphocyte subsets, lipid indexes, etc.), clinical features and c;/]-sity from December 2017 to September 2019 and non-stroke patients with dizziness/vertigo during the same period.ResultsThe results showed that peripheral B lymphocyte proportions are elevated in acute ischemic stroke patients compared with those of the control group (13.6 ± 5.3 vs. 11.7 ± 4.4%, p = 0.006). Higher B lymphocyte proportions are associated with concurrent dyslipidemia, increased levels of vascular risk factors including triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and very-low-density lipoprotein cholesterol (VLDL-C), as well as decreased levels of the protective factor high-density lipoprotein cholesterol (HDL-C). Elevated B lymphocyte proportions are independently correlated with carotid atherosclerosis in stroke patients.DiscussionWe found CD19 positive B Lymphocytes increase after ischemic stroke and correlate with Carotid Atherosclerosis. Lymphocyte subpopulations should be highlighted in stroke patients.

Paclitaxel (Taxol@) as a cornerstone of chemotherapy remains in high demand. The semi-synthesis of paclitaxel via coupling of Taxus leaf-produced baccatin III and manually synthesized isoserine (C-13 side chain) is one of the solutions to avoid environmental damage caused by the sacrifice of the whole Taxus brevifolia. A green synthesis of the C-13 side chain is pivotal to the green production of paclitaxel. We herein report a green synthesis of isoserine derivatives and the semi-synthesis of paclitaxel via a straightforward assembly of isoserines based on an Rh2(TPA)3(OAc)/CPA1 co-catalyzed asymmetric multi-component reaction of ethyl diazoacetate, triethyl silanol and N-(anthrancen-9-ylmethyl)benzaldimine. The method is featured by improved atom economy, effective mass yield, and environmental factors compared to our previous racemic method and BMS company's semi-synthesis method. And the method allows for rapid access to paclitaxel derivatives with varied C-13 side chains.

The mainstream instance segmentation is a comprehensive computer vision task, which involves computer vision tasks such as image classification, object detection, and semantic segmentation. Aiming at the Prototype mask for initial segmentation mask with incorrect segmentation, this paper uses YOLACT (You Only Look at CoefficienTs) as the benchmark, in order to improve the network performance in the interfernce situation by enhancing the response of prototype mask, the multi-scale YOLACT for instance segmentation (MS YOLACT) is proposed, which increases the accuracy of segmentation by designing a lightweight network structure. First, the image gets multi-scale features through the residual network and the feature pyramid network. Then, the deep up-sampling and shallow down-sampling in the multi-scale feature layer are realized respectively to the size required by the prototype mask branch input, and all the deep information that has been up-sampled is further learned by convolution. Finally, at the input end of the prototype mask branch, the deep information and the shallow information are sequentially merged in an additive manner to improve the response of the prototype mask, thereby improving the accuracy of the target's mask segmentation. The experimental results show that compared with the benchmark on COCO test-dev, when the speed is reduced by only 1 FPS, the overall segmentation accuracy reaches an improvement of 0.6, and the segmentation accuracy of small and large targets reaches an improvement of 0.4 and 0.7 respectively; the visualization results also show that the segmentation mask of MS YOLACT is more accurate. In addition, MS YOLACT has the advantages of higher speed and lower requirements on equipment.

In order to deepen the understanding of the role and regulation mechanisms of prokaryotic global transcription regulators in complex processes, including virulence, the associations between the affinity and binding sequences of Mycobacterium tuberculosis MtrA have been explored extensively. Analysis of MtrA 294 diversified 26 bp binding sequences revealed that the sequence similarity of fragments was not simply associated with affinity. The unique variation patterns of GC content and periodical and sequential fluctuation of affinity contribution curves were observed along the sequence in this study. Furthermore, docking analysis demonstrated that the structure of the dimer MtrA-DNA (high affinity) was generally consistent with other OmpR family members, while Arg 219 and Gly 220 of the wing domain interacted with the minor groove. The results of the binding box replacement experiment proved that box 2 was essential for binding, which implied the differential roles of the two boxes in the binding process. Furthermore, the results of the substitution of the nucleotide at the 20th and/or 21st positions indicated that the affinity was negatively associated with the value of minor groove width precisely at the 21st position. The dimerization of the unphosphorylated MtrA facilitated by a low-affinity DNA fragment was observed for the first time. However, the proportion of the dimer was associated with the affinity of substrate DNA, which further suggested that the affinity was actually one characteristic of the stability of dimers. Based on the finding of 17 inter-molecule hydrogen bonds identified in the interface of the MtrA dimer, including 8 symmetric complementary ones in the conserved α4-β5-α5 face, we propose that hydrogen bonds should be considered just as important as salt bridges and the hydrophobic patch in the dimerization. Our comprehensive study on a large number of binding fragments with quantitative affinity values provided new insight into the molecular mechanism of dimerization, binding specificity and affinity determination of MtrA and clues for solving the puzzle of how global transcription factors regulate a large quantity of target genes.

To overcome the poor mechanical strength of copper tailing powders- Portland cement, diatomite was added into this cementitious system.Diatomite replaced the copper tailing powders- Portland cement with 0.5%, 1.0%, 1.5% and 2.0% in weight.The fluidity, setting time, water absorption, porosity, bulk density, mechanical properties and microscopic properties of the composite cement materials were tested. The results showed that with the increase of the dosage of diatomite, the fluidities of the pastes decrease, the setting time shortens, water absorptions and porosities decrease, bulk densities increase, compressive strength and flexural strength of the mortars increase. After curing for 28 days, the addition of diatomite makes the SiO2 and Ca(OH)2 content in the hydration products decrease, the C-S-H (Calcium Silicate Hydrate) gels increase, and the whole is denser.

In order to quantitatively characterize the pore structure of thermally contacted metamorphic coal by igneous intrusion and investigate the intrinsic connection between the pore and dispersion properties of coal, the samples of metamorphic coal from different locations of Daxing Coal Mine were collected and processed. The correlative analysis on pore characteristics, including pore area, perimeter, shape factor and fractal dimension of pores with different sizes, were carried out by using scanning electron microscopy (SEM) and pore-fracture analysis system (PCAS). The results show that the porosity of macro- and meso-pores and the number of pores in the metamorphic coal are larger than those of the normal coal. The total length of pores per unit area and the average shape factor increase, and the connectivity of pore is raised, resulting in an enhanced gas release capacity (increased V1) within the first one second. The proportion of gas emission in the first one second of metamorphic coal is much higher than that of other coals. The decrease of pore volume and specific surface area of micropores makes the adsorption capacity weaker, which results in a decrease in the total amount of emission - smaller Δp value, and earlier inflection point and faster attenuation on the emission curve, namely an increased α value. In addition, the V1, α value and volatile content satisfy the quadratic nonlinear and linear relationships, respectively. In the prediction of outburst risk of thermally contacted metamorphic coal, it is more reasonable to use the V1 index to characterize the gas release rate.

Abstract The diagnosis of Parkinson’s disease (PD) is challenging at all stages due to variable symptomatology, comorbidities, and mimicking conditions. Postmortem assessment remains the gold standard for a definitive diagnosis. While it is well recognized that PD manifests pathologically in the central nervous system with aggregation of α-synuclein as Lewy bodies and neurites, similar Lewy-type synucleinopathy (LTS) is additionally found in the peripheral nervous system that may be useful as an antemortem biomarker. We have previously found that detection of LTS in submandibular gland (SMG) biopsies is sensitive and specific for advanced PD; however, the sensitivity is suboptimal especially for early-stage disease. Further, visual microscopic assessment of biopsies by a neuropathologist to identify LTS is impractical for large-scale adoption. Here, we trained and validated a convolutional neural network (CNN) for detection of LTS on 283 digital whole slide images (WSI) from 95 unique SMG biopsies. A total of 8,450 LTS and 35,066 background objects were annotated following an inter-rater reliability study with Fleiss Kappa = 0.72. We used transfer learning to train a CNN model to classify image patches (151 × 151 pixels at 20× magnification) with and without the presence of LTS objects. The trained CNN model showed the following performance on image patches: sensitivity: 0.99, specificity: 0.99, precision: 0.81, accuracy: 0.99, and F-1 score: 0.89. We further tested the trained network on 1230 naïve WSI from the same cohort of research subjects comprising 42 PD patients and 14 controls. Logistic regression models trained on features engineered from the CNN predictions on the WSI resulted in sensitivity: 0.71, specificity: 0.65, precision: 0.86, accuracy: 0.69, and F-1 score: 0.76 in predicting clinical PD status, and 0.64 accuracy in predicting PD stage, outperforming expert neuropathologist LTS density scoring in terms of sensitivity but not specificity. These findings demonstrate the practical utility of a CNN detector in screening for LTS, which can translate into a computational tool to facilitate the antemortem tissue-based diagnosis of PD in clinical settings.

Abstract The 15# coal seam of Yangmei No.5 Mine, which produces anthracite, which is the least prone to spontaneous combustion, has a serious hidden danger of spontaneous combustion due to the high sulfur content in the coal. Based on the better conductivity of anthracite, we designed an electrolysis experiment to accelerate the electrochemical oxidation of pyrite in coal. Through experiments and analysis of thermodynamic characteristic parameters, it is obtained that the electrochemical oxidation of pyrite and its main products Fe3+ and Fe2+ have a coupled catalytic effect on the spontaneous combustion of high-sulfur coal in Yangquan. Combined with the FTIR test and analysis, it is found that the electrochemical process causes spatial polarization in the coal, so that polar groups such as –OH undergo spatial diversion and increase the activity. Due to the high content of –OH in Yangquan anthracite, the electrochemical process has the greatest effect on promoting –OH oxidation. Fe3+ and Fe2+ act as strong oxidants and free radicals to promote the –CH2– reaction to generate C=O and promote the generation of CO. This research provides a new direction for the exploration of the spontaneous combustion mechanism of high-sulfur anthracite.

Experimental results indicate that the conventional program suspend scheme in 3D NAND flash memory chip can generate unexpected additional read fail bits and reduce the reliability of 3D NAND flash memory. These extra read fail bits are observed when the program suspend command is issued during the program stage, and particularly, they become more obvious as the delay time between program suspend operation and other following operations exceeds tens of milliseconds. By analyzing the waveform of conventional program suspend scheme, it is suggested that the unexpected extra read fail bits are caused by the different occupancy of grain boundary traps (GBTs) in the polycrystalline silicon (poly-Si) channel during the idle time after the program suspend operation. Accordingly, a novel program suspend scheme is proposed by adding a “stabilizing” pulse immediately after the program stage. Silicon experimental data show that the proposed scheme can effectively limit the read fail bit count (FBC) to a normal range, thus improving the reliability of 3D NAND flash memory significantly.

The dietary composition has been approved to be strongly associated with the risk of colorectal cancer (CRC), one of the most serious malignancies worldwide, through regulating the gut microbiota structure, thereby influencing the homeostasis of colonic epithelial cells by producing carcinogens, i.e., ammonia or antitumor metabolites, like butyrate. Though butyrate-producing Fusobacterium nucleatum has been considered a potential tumor driver associated with chemotherapy resistance and poor prognosis in CRC, it was more frequently identified in the gut microbiota of healthy individuals rather than CRC tumor tissues. First, within the concentration range tested, the fermentation broth of F. nucleatum exhibited no significant effects on Caco-2 and NCM460 cells viability except for a notable up-regulation of the expression of TLR4 (30.70%, p < 0.0001) and Myc (47.67%, p = 0.021) and genes encoding proinflammatory cytokines including IL1B (197.57%, p < 0.0001), IL6 (1704.51%, p < 0.0001), and IL8 (897.05%, p < 0.0001) in Caco-2 cells exclusively. Although no marked effects of polydextrose or fibersol-2 on the growth of F. nucleatum, Caco-2 and NCM460 cells were observed, once culture media supplemented with polydextrose or fibersol-2, the corresponding fermentation broths of F. nucleatum significantly inhibited the growth of Caco-2 cells up to 48.90% (p = 0.0003, 72 h, 10%) and 52.96% (p = 0.0002, 72 h, 10%), respectively in a dose-dependent manner. These two kinds of fibers considerably promoted butyrate production of F. nucleatum up to 205.67% (p < 0.0001, 6% polydextrose at 24 h) and 153.46% (p = 0.0002, 6% fibersol-2 at 12 h), which explained why and how the fermentation broths of F. nucleatum cultured with fibers suppressing the growth of Caco-2 cells. Above findings indicated that dietary fiber determined F. nucleatum to be a carcinogenic or antitumor bacterium, and F. nucleatum played an important role in the association between the dietary composition, primarily the content of dietary fibers, and the risk of CRC.

We report the behaviour of the dark current and gain characteristics of Si- and GaN-based avalanche photodiodes (APDs) irradiated by fast neutrons. For Si-based APDs, the dark current increases with the increase of neutron fluence, indicating that the avalanche property has been seriously affected. The gain values of Si-based APD slightly increase after irradiation by a low neutron fluence of 1.0 × 1012 cm−2, while the device exhibits gain degradation as the fluence increases to 1.0 × 1013 cm−2 or even above at high reverse bias voltage, unlike the previous studies where only degradation was observed. The steep increase of dark current and gain when approaching the breakdown voltage after neutron irradiation indicate that the avalanche property is almost unaffected for GaN-based APDs. Furthermore, we infer that the optical absorption between acceptor state and conduction band in the p-type layer plays an important role in influencing the change of dark current and gain at high reverse bias voltage. The findings not only enrich the understanding of neutron irradiation effect on Si- and GaN-based APDs, but also experimentally prove that GaN-based APDs hold better radiation resistance than Si-based devices.

Amomum tsaoko (AT) is a dietary botanical with laxative properties; however, the active ingredients and mechanisms are still unclear. The active fraction of AT aqueous extract (ATAE) for promoting defecation in slow transit constipation mice is the ethanol-soluble part (ATES). The total flavonoids of ATES (ATTF) were the main active component. ATTF significantly increased the abundance of Lactobacillus and Bacillus and reduced the dominant commensals, such as Lachnospiraceae, thereby changing the gut microbiota structure and composition. Meanwhile, ATTF changed the gut metabolites mainly enriched in pathways such as the serotonergic synapse. In addition, ATTF increased the serum serotonin (5-HT) content and mRNA expression of 5-hydroxytryptamine receptor 2A (5-HT2A), Phospholipase A2 (PLA2), and Cyclooxygenase-2 (COX2), which are involved in the serotonergic synaptic pathway. ATTF increased Transient receptor potential A1 (TRPA1), which promotes the release of 5-HT, and Myosin light chain 3(MLC3), which promotes smooth muscle motility. Notably, we established a network between gut microbiota, gut metabolites, and host parameters. The dominant gut microbiota Lactobacillus and Bacillus, prostaglandin J2 (PGJ2) and laxative phenotypes showed the most significant associations. The above results suggest that ATTF may relieve constipation by regulating the gut microbiota and serotonergic synaptic pathway and has great potential for laxative drug development in the future.

Highlights Shape memory self-soldering tape used as conductive interconnecting material. Perfect shape and conductivity memory performance and anti-fatigue performance. Reversible strong-to-weak adhesion switched by temperature. Abstract With practical interest in the future applications of next-generation electronic devices, it is imperative to develop new conductive interconnecting materials appropriate for modern electronic devices to replace traditional rigid solder tin and silver paste of high melting temperature or corrosive solvent requirements. Herein, we design highly stretchable shape memory self-soldering conductive (SMSC) tape with reversible adhesion switched by temperature, which is composed of silver particles encapsulated by shape memory polymer. SMSC tape has perfect shape and conductivity memory property and anti-fatigue ability even under the strain of 90%. It also exhibits an initial conductivity of 2772 S cm−1 and a maximum tensile strain of ~ 100%. The maximum conductivity could be increased to 5446 S cm−1 by decreasing the strain to 17%. Meanwhile, SMSC tape can easily realize a heating induced reversible strong-to-weak adhesion transition for self-soldering circuit. The combination of stable conductivity, excellent shape memory performance, and temperature-switching reversible adhesion enables SMSC tape to serve two functions of electrode and solder simultaneously. This provides a new way for conductive interconnecting materials to meet requirements of modern electronic devices in the future.

For triple-level or quad-level 3D NAND flash memory, narrowing the Vth distribution of each state without influencing page program performance is one of the challenges. Considering this challenge, a novel adaptive pulse programming (APP) scheme was proposed. The proposed APP scheme adopted additional verify operations to separate the cells with different programming speed. It enhanced the program effect of slow cells by using increasing programming step voltage, and prevented the fast cells from over programming by using shorter programming pulse width through controlling the voltage of bitline. Compared with general incremental step pulse programming scheme, experimental results on TLC 3D NAND flash showed that, APP scheme could reduce the Vth distribution width of cells by around 15% and at the same time save the program time.

In recent years, the single-stage detectors have been developed rapidly; however, compared with the multi-stage detectors, their detection precision is still relatively low. Single-stage detectors and multi-stage detectors are analyzes and compared in detail in this paper, which reveals that single-stage detectors suffer from some problems, including feature loss and inaccurate feature extraction. Therefore, this paper proposes a novel detection model, dubbed Optimized Network (OptNet), to alleviate these deficiencies. OptNet consists of three modules: pyramid of attention features, feature alignment and consistency supervision (CS). The pyramid of attention features, based on feature pyramid networks (FPNs), introduces a novel branch named attention FPN (AtFPN), which aggregates the multi-layer features of the backbone network and optimizes the object features by using lightweight attention modules. AtFPN alleviates the loss of the feature pyramid information and the blocking of feature transmission between adjacent layers. Meanwhile, it provides global information for the model. The feature alignment module aligns the anchor box to the feature by using the object location information to guide the network to extract precise object features. Finally, CS accelerates network optimization and reduces semantic differences between the features on different layers. In the detection stage, OptNet optimizes the prediction of the model with the first detection result to improve the accuracy. Experiments on the MS COCO 2017 dataset demonstrate that OptNet yields significant improvement in the detection precision.

In person re-identification (Re-ID), increasing the diversity of pedestrian features can improve recognition accuracy. In standard convolutional neural networks (CNNs), the receptive fields of neurons in each layer are designed to have the same size. Therefore, in complex pedestrian re-identification tasks, the standard CNNs extract local features but are unable to obtain satisfactory results for global features extracted from the images. Local feature learning methods are helpful for obtaining more abundant features, which focus on the most significant local features and ignore the correlations between features of various parts of the human body. To solve the above problems, a new multiscale reference-aided attentive feature aggregation (MS-RAFA) mechanism is proposed, consisting of three main modules. First, to extract the most significant local features and strengthen the correlations between the features of various parts of the human body, an autoselect module (ASM) is designed, an attentional mechanism that can stack the structural information and spatial relations to form new features. Then, to realize multiscale feature fusion of the multiple output branches of the backbone network and increase feature diversity, we propose a multilayer feature fusion module (MFFM), which enables the model to mine the features hidden by salient features and to learn features better. Finally, to supervise the MFFM and make the network obtain better recognition features, we propose a multiple supervision mechanism. Finally, experimental results demonstrate that our proposed method outperforms the state-of-the-art methods on three large-scale datasets.

Unsupervised person re-identification (re-id) is an effective analysis for video surveillance in practice, which can train a pedestrian matching model without any annotations, and it is easy to deploy in unseen camera scenarios. The most challenging problem in unsupervised re-id task is the huge distribution-gap among different camera views, and the intrinsic correlations in unlabeled identities are also complicated to sufficiently explored. This paper proposes a Multi-order Cross-view Graph adversarial Network (MCGN) to bridge the cross-view distribution-gap, and mine the inherent discriminative information by multi-order triplet correlations. Specifically, MCGN firstly exploits graph representations by a cross-view graph convolutional network according to intra-view and inter-view graph structure, and then encodes each pedestrian image into a view-shared feature space, which is iteratively trained by a graph generative adversarial learning strategy to deeply bridge the distribution-gap. Finally, this paper proposes a multi-order discriminative learning module for composing reasonable triplet samples according to multi-order similarity correlations among unlabeled pedestrian images. Furthermore, sufficient experiments are conducted in two large scale person re-id datasets (Market-1501 and DukeMTMC-reID). The comparison to state-of-the-art methods and ablation study demonstrate the superiority of MCGN and the contribution of each module proposed in this paper.

The ice thermal parameters are the key to reasonably simulating ice phenology, distribution, and thickness, but they have always been a “vulnerable group” in ice research. Technically, it may seem simple to obtain accurate ice thermal property parameters, but in reality, there are numerous impact factors, requiring a rigorous research process. In the 1980s, the thermal conductivity of ice was explored in the field and laboratory, after which there has been no significant progress in China. In this century, mathematics is introduced, after which the inversion identification and analysis with the time-series data of the vertical temperature profiles of ice layers by in situ testing are carried out. The in situ thermal diffusivities of different natural ices were obtained and cross-validated with the inversion identification results. Both natural freshwater ice and sea ice exhibited differences in the thermal diffusivity of the pure ice chosen for the current simulations due to impurities within the unfrozen water among the ice crystals, but the trends are consistent with the results of a small number of laboratory tests on different types of saltwater frozen ice. In this paper, the inversion identification results of the thermal diffusivity of typical ice were selected, and the factors constraining the thermal diffusivities were analyzed. The importance of parameterizing the thermal diffusivity in the phase transition zone of ice under the trend of global warming was illustrated. Future research ideas on the physical mechanism, application value, and parameterization scheme of the thermal diffusivity of natural ice were envisaged.

In deep underground engineering, understanding of time-related stress memory properties is critical to evaluate the in situ stress conditions of a rock mass. In this study, the time-sensitivity mechanism of the rock stress memory properties under tensile stress was investigated. It was found that the material property (Poisson's ratio) and crack angle were the controlling factors of the Kaiser effect (KE) under tensile stress. In particular, the time-sensitivity of the stress memory properties was closely related to the crack growth path. When the failure of the rock specimen was dominated by tensile microcracks and the crack development direction was deflected by up to 30° in the successive loading process, the stress memory capacity was likely to be time-independent for a sandstone specimen. The distribution of the Felicity ratio in a Brazilian test was more discrete than that in a three-point bending test. It also showed that the changes in the crack path, rather than the time interval between successive loading cycles, led to inaccuracy of the detected KE. This study provides insights into stress memory-related issues under uniaxial or more complex stress conditions and thus facilitates development of methods for testing in situ mechanical behaviors of rocks with acoustic emission (AE) technology.

Abstract Primary intracerebral hemorrhage (ICH) is a leading cause of long-term disability and death worldwide. Drug delivery vehicles to treat ICH are less than satisfactory because of their short circulation lives, lack of specific targeting to the hemorrhagic site, and poor control of drug release. To exploit the fact that metal ions such as Fe2+ are more abundant in peri-hematomal tissue than in healthy tissue because of red blood cell lysis, we developed a metal ion-responsive nanocarrier based on a phosphonated calix[4]arene derivative in order to deliver the neuroprotective agent dauricine (DRC) specifically to sites of primary and secondary brain injury. The potential of the dauricine-loaded nanocarriers for ICH therapy was systematically evaluated in vitro and in mouse models of autologous whole blood double infusion. The nanocarriers significantly reduced brain water content, restored blood-brain barrier integrity and attenuated neurological deficits by inhibiting the activation of glial cells, infiltration by neutrophils as well as production of pro-inflammatory factors (IL-1β, IL-6, TNF-α) and matrix-metalloprotease-9. These results suggest that our dauricine-loaded nanocarriers can improve neurological outcomes in an animal model of ICH by reducing inflammatory injury and inhibiting apoptosis and ferroptosis.

One-stage object detectors are simple and efficient; however, they cannot extract sufficient object features due to simplistic structures. At the same time, the classification score cannot reflect the actual positioning of the candidate box. Therefore, it is not accurate to use classification score only as the candidate box position score in non-maximum suppression (NMS) stage. These two shortcomings degrade the detection accuracy. In this paper, a novel feature pyramid architecture named refined feature pyramid network (ReFPN) is introduced to obtain better object features. ReFPN designs a refined module which is parallel with feature pyramid network (FPN) to extract the semantic features of objects, and then the extraction of features are used to optimize the features of FPN by summation. In addition, we design the refined center-ness (RCenter-ness) branch that predicts the position score of each point on the feature map to improve the localization accuracy. The predicted position score is multiplied by the classification score to obtain the final position score that has a stronger correlation with localization accuracy. The final position score is inputted to the subsequent NMS, which improves localization accuracy. The proposed method in this paper is named ReFPN-FCOS. The sufficient experiments on COCO2017 datasets demonstrate the effectiveness of ReFPN-FCOS on improving classification accuracy and localization accuracy. The average precisions of this method achieve 1.1% and 1.3 % higher than those of FCOS, when using ResNet50 and ResNet101 as backbone respectively. Code download link: https://github.com/xjl-le/mmdete.

To reveal the evolution law of coal skeleton deformation during the process of CO2 flooding and displacing CH4 in coal seam, a fluid-solid coupling mathematical model of CO2 injection enhanced CH4 drainage was established based on Fick’s law, Darcy’s law, ideal gas state equation, and Langmuir equation. Meanwhile, numerical simulations were carried out by implementing the mathematical model in the COMSOL Multiphysics. Results show that the CH4 content of both regular gas drainage and CO2 enhanced gas drainage gradually decreases with time, and the decreasing rate is high between 10 and 60 days. Compared with regular gas drainage, the efficiency of CO2 enhanced gas drainage is more obvious with greater amount of CH4 extracted out. When coal seam gas is extracted for 10, 60, 120, and 180 days, CH4 content in coal seam is reduced by 5.2, 17.2, 23.6, and 26.7%, respectively. For regular gas drainage, the deformation of coal skeleton is dominated by the shrink of coal matrix induced by gas desorption, and the strain curve shows a continuous downward trend. For CO2 enhanced gas drainage, the strain curve of coal skeleton showed a decrease—rapid increase—slow increase trend. The evolution of permeability is opposite to the evolution of coal skeleton strain. Higher gas injection pressure will lead to a greater coal skeleton strain. The pumping pressure affects the deformation of coal skeleton slightly compared with that of initial water saturation and initial temperature. Greater initial water saturation leads to larger deformation of coal skeleton in the early stage. The strain value of coal skeleton gradually tends to be consistent as gas injection prolongs. Higher initial temperature leads to greater reduction in coal skeleton strain when the gas injection continues. Research achievements provide a basis for the field application of CO2 injection enhanced CH4 drainage in underground coal mines.

The Si- and InP-based APDs as the most important weak light semiconductor photodetectors to have achieved commercial success and are widely used in irradiation environments. Investigating the influencing mechanism of neutron irradiation on the above two types of APDs is of scientific and practical importance. In this paper, the dark current and gain characteristics of Si- and InP-based APDs around breakdown voltage were analyzed in detail before and after irradiation. The increase of dark current and the decrease of gain were observed for both the neutron irradiated Si- and InP-based APDs. Generation centers induced by neutrons are responsible for the increased dark current. The decrease of gain can be attributed to the increase of multiplied dark current and the change of electric field distribution in APD. The Si-based APD exhibits soft breakdown with the breakdown voltage reduced by ~8 V under the neutron fluence of 1.0 × 1012 cm−2, while the soft breakdown occurs along with a small change of breakdown voltage of ~1.5 V under the neutron fluence of 1.0 × 1013 cm−2 for InP-based APD. The difference in the change of breakdown voltage probably occurs because the Si-based APD uses p-doped Si as the multiplication layer, in which the neutron induced carrier removing effect cannot be ignored to keep the electric field distribution away from the optimal state. Therefore, using an intrinsic multiplication layer in APD is helpful to improve the neutron radiation resistance. The findings here are not only useful for the radiation hardened design of APD, but also deepen the understanding of irradiation mechanism.

Numerous studies have focused on the mechanical properties of shale specimens to support hydraulic fracturing in shale gas engineering. However, the failure modes of shale specimens containing a pre-existing flaw are still not clear. A series of uniaxial compression tests were conducted on shale specimens containing a pre-existing flaw coupled with acoustic emission (AE) technology and a high-speed camera. A slow enough and variable loading speed scheme (0–50 kN: 0.1 kN/s, 50–100 kN: 0.05 kN/s; 100-failure: 0.02 kN/s) is adopted to allow microcracks to fully develop. The damage mechanism in the mesoscale from moment tensor inversion of the AE signals and the cracking behaviors on the macroscale were associated. Both the pre-existing flaw and the bedding layers had significant influences on the mechanical characteristics, progressive cracking, and failure modes of the shale specimens. The peak stress increases fluctuated as the bedding layer angle α increases, and the maximum and minimum values take place at α=90° and α=0°, respectively. In addition, the pre-existing flaw, the bedding layers, and the compression stress field jointly control the failure modes of the shale specimens. It was found that the α=0° specimen failed due to tension splitting, the α=30° specimen failed due to tension splitting and shear across the matrix, the α=60 specimen failed due to shear across the shale matrix and shear along the bedding layers, and the α=90° specimen failed due to tension along the bedding layers and shear across the shale matrix. The study can provide some references to the construction of complex crack networks in shale gas engineering.

AlGaN-based deep ultraviolet (DUV) light emitting diodes (LEDs) are irradiated by fast neutrons, with optical and electrical properties analyzed in detail. Significant enhancement of output power is observed under neutron irradiation fluences of 6.0 × 1012 and 1.5 × 1013 cm−2. However, the device exhibits performance degradation as the fluence increases to 1.0 × 1014 cm−2. As previous observations are limited to degradation. Further analysis reveals that there exist two different competitive mechanisms of neutron radiation effect on DUV LEDs. The enhancement of the output power is attributed to the increased efficiency of the carriers injected into the irradiated multi-quantum wells (MQWs). Meanwhile, neutron irradiation-induced nitrogen vacancies in p-AlGaN electron blocking layer increase the leakage of the current dominating the device performance degradation, in contrast with results from former studies on longer wavelength GaN-based LEDs. Those findings are not only helpful to further enrich the degradation mechanism of neutron irradiated DUV LEDs, but also provide a fresh idea to improve their luminous characteristics.

The question of which turbulence model is better for a given class of applications is always confusing for the CFD researchers and users. Comparative assessments of scale-adaptive simulation (SAS), improved delay detached-eddy simulation (IDDES) and other hybrid RANS/LES models based on eddy-viscosity models (EVMs) are thoroughly investigated. But how well they perform based on a second-moment closure needs to be answered. In this paper, a widely acclaimed Reynolds-stress model (RSM) in aeronautical engineering, SSG/LRR- ω model, is carried out. The relevant test cases include the NACA0012 airfoil stalled flows and turret separated flow. In order to make a more reasonable comparison, a seventh-order scheme WCNS-E8T7 is adopted to reduce the influence of the numerical dissipation and a symmetrical conservative metric method is used to ensure the robustness. By comparing with the relevant experimental data and the solutions by original SSG/LRR- ω model (etc. URANS), it shows that all of the three hybrid methods (SAS, IDDES and hybrid filtering methods) based on the SSG/LRR- ω model have a good ability to simulate unsteady turbulence. Among them, the IDDES correction has the most potential.