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The preferred emulsifier was used to emulsify the plasticizer naphthenic oil (NAP), and uniform and stable NAP emulsion was prepared. The NAP-plasticized natural rubber (NR)/silica (SiO2) (NAP/NR/SiO2) composite was prepared using the resulting NAP emulsion, NR latex and SiO2 slurry by wet mixing process, and the effects of NAP addition amount on Mooney viscosity, physical and mechanical properties, dynamic mechanical properties, dispersion of SiO2, thermal air aging resistance and flexural cracking property of NAP/NR/SiO2 composites were studied. The results showed that Mooney viscosity of NAP/NR/SiO2 composite was significantly lower than that of NR/SiO2 composite, Payne effect was significantly weakened, and dynamic mechanical properties and proces-sability improved significantly. When NAP addition amount was 10 phr (mass), NAP/NR/SiO2 composite had the best comprehensive performance, and tensile strength of NAP/NR/SiO2 composite decreased slightly, whereas elongation at break increased to varying degrees when compared with those of NR/SiO2 composite. Thermal air aging resistance and flexural cracking property of NR/SiO2 composite improved after the addition of NAP.

During the coal caving process in the fully mechanized caving face, due to the impact of coal dust and dust water mist on the workers' line of sight, there are problems of over-caving and under-caving in manually controlled coal caving. In order to solve this problem, the tail beam of the hydraulic support is regarded as an intelligent agent, and the coal caving process is abstracted as a Markov optimal decision. A deep Q-network (DQN) is used to make decisions on the action of the coal drawing port. However, there is an overestimation problem in the DQN algorithm. A fuzzy deep Q-network (FDQN) algorithm is proposed and applied to intelligent decision-making of coal caving. The fuzzy control system is constructed by using the fuzzy features of the coal seam status in the coal caving process. The coal quantity and the coal gangue ratio in the coal seam state are taken as the inputs of the fuzzy control system. The output action of the fuzzy control system is replaced with the action of the DQN algorithm using the max operation to select the output Q value of the target network. It improves the online learning rate of the agent and increases the reward value of coal caving action. The coal caving model for the fully mechanized caving face is constructed. The three-dimensional numerical simulation of the coal caving process based on DQN, double depth Q-network (DDQN), and FDQN algorithms is conducted respectively. The results show that the FDQN algorithm has the fastest convergence speed, which is 31.6% faster than the DQN algorithm. It increases the online learning rate of the intelligent agent. The coal caving effect based on the FDQN algorithm is the best from three aspects: the straightness of the coal gangue boundary, the remaining coal above the tail beam, and the amount of gangue in the released body. The extraction rate based on the FDQN algorithm is the highest and the gangue content is the lowest. Compared with the DQN algorithm and DDQN algorithm, the extraction rate of the FDQN algorithm has increased by 2.8% and 0.7% respectively, and the gangue content has decreased by 2.1% and 13.2% respectively. The FDQN-based intelligent decision-making method for coal caving can adjust the action of the hydraulic support tail beam based on the coal seam occurrence status. It effectively solves the problems of over-caving and under-caving during the coal caving process.

Non-stationary optimization problems are a very important class of problems in many practical applications. These problems are characterized by objective functions and constraints that change with time or environmental conditions, so the optimization solution also needs to be dynamically adjusted accordingly. Many algorithms from the field of evolutionary and biology inspired computation are known as an effective approach for dealing with hard optimization problems in changing environments, that is the result of modelling of self-organized systems in nature and evolution in the biology. Natural systems always exist in the changing environments. This article aims to compare the performance of three common nature-inspired techniques, namely genetic algorithm (GA), particle swarm optimization (PSO) algorithm, and differential evolution (DE) in their standard implementation when solving non-stationary optimization problems, so as to provide a reference and rationale for subsequent selection of appropriate algorithms and improvements.

Although many studies have investigated the influencing factors of adolescents’ Internet gaming addiction, few have investigated the influence factor of exposure to domestic violence, and even fewer have used the General Strain Theory to explain the influence path of exposure to domestic violence on adolescents’ Internet gaming addiction. Based on the GST, this study sought to uncover further insights into the effect of exposure to family violence on adolescents’ Internet gaming addiction, and the mediating role of social control—specifically, parental attachment—and self-control in the association between exposure to family violence and adolescents’ Internet gaming addiction. Adopting a multi-stage cluster random sampling method, we conducted this study with 2,110 adolescents from Liangshan Yi Autonomous Prefecture in Sichuan Province, China. The results suggest that adolescents’ exposure to domestic violence directly affects their addiction to Internet games and indirectly affects it by decreasing social control and self-control. The study not only supplements and improves the explanatory framework of General Strain Theory, but makes a significant contribution to research on the causes of Internet gaming addiction.

Objective: To solve the subjectivity and instability of the traditional Baijiu picking method " liquor-receiving according to liquor hop", and the problem that the existing machine vision hops classification method is difficult to meet the real-time classification. Methods: The lightweight YOLOv5 takes YOLOv5s as the initial model, uses the K-mean clustering anchor box to replace the default anchor box to improve the model detection accuracy and stability, uses the shufflenetv2 network to replace the YOLOv5s backbone network for feature extraction, so as to achieve the purpose of lightweight model, and adds the CBAM attention mechanism to make the model pay more attention to the characteristics of hops. Results: Compared with the initial YOLOv5s model, the memory occupied by the lightweight YOLOv5 model is reduced by 92.5%, the parameters are reduced by 93.7%, the calculation is reduced by 63.4%, the detection accuracy is improved by 2.8%, and the FPS is up to 526. Conclusion: The lightweight YOLOv5 reduces the requirements for hardware configuration and can well realize the real-time detection and classification of hops.

Gastric tube placement is a common clinical procedure. During the catheterization process, the gastric tube may enter the trachea by mistake, presenting symptoms such as choking, dyspnea, cyanosis and so on. Occasionally, patients have atypical symptoms, which are easily ignored in clinical practice, bringing great safety risks to the operation. This paper reported a case of gastric tube misplacement into the trachea using tetracaine gel as lubricant before gastrointestinal surgery, analyzed the causes and summarized the preventive and nursing measures, and reviewed the new methods, new techniques and relatively rare complications of gastric tube placement. The lubricant with anesthetic effect should be used carefully when placing gastric tube. The application of new technology can improve the success rate of gastric tube placement. (安置胃管是常见的临床操作。在置管过程中, 胃管可能会误入气管, 表现为呛咳、呼吸困难、发绀等症状, 偶有患者症状不典型, 存在安全隐患。现报告1例应用丁卡因胶浆置管过程中胃管误入气管且无典型症状的病例, 分析原因并总结预防护理措施, 并结合文献对安置胃管的新方法、新技术及相对罕见的并发症进行总结。 安置胃管时使用带有麻醉作用的润滑剂需谨慎, 新技术的应用可提高安置胃管的成功率。)

The Chongming Island Landsenses Ecol-industrial Park is a demonstration park which integrates many kinds of industrial functions to realize the scientific development of clean energy and ecological agriculture, including photovoltaic power generation, freshwater aquaculture, and sightseeing agriculture. In order to establish an Ecol-industrial park with an intergrowth between production process and ecological construction, resource utilization and green development, as well as industrial function design and landsense creation, this study aims to plan and design the landsenses of the Chongming Island Landsenses Ecol-industrial Park based on the landsenses idea of 'the sun-moon shine together on the five continents' and the technology of Environmental Internet of Things. The Chongming Island Landsenses Ecol-industrial Park incorporates various industrial models and areas, including an ecological photovoltaic demonstration area, a landsenses ecology demonstration area, and a Popular Science recreation area, which would create a demonstration park for the industrialization of ecological resources, the ecologicalization of industries, and the characteristic services of landsenses. This study addresses the value-added services of ecological asset and the integration of industry in the traditional industrial park, and provides a theoretical and technical demonstration of industrial planning and landsense design for other industrial parks in the future. [ABSTRACT FROM AUTHOR]

Background: Erectile dysfunction (ED) is a common complication in patients with diabetes mellitus (DM) that severely affects the patients' quality of life. However, the effectiveness of oral phosphodiesterase type 5 inhibitors in these patients is poor. Sphingosine‐1‐phosphate (S1P) and S1P receptor 2 (S1PR2) are important factors regulating the Rho‑kinase pathway, and understanding these factors may provide ideas for new therapeutic strategies for ED. Objectives: To investigate whether the S1PR2 receptor antagonist JTE‐013 could improve DM‐induced ED (DMED) in rats and to explore the potential mechanisms. Materials and methods: We used 50 male Sprague Dawley rats (8 weeks old) for this experiment. Type Ⅰ DM was induced in forty‐two rats via streptozotocin administration; the rest of the rats served as controls. Eight weeks after DM induction, rats with ED were selected via an apomorphine test. Eight of them were injected intraperitoneally with JTE‐013 each day for 4 weeks. The rest were fed under the same conditions for 4 weeks. Erectile function was measured by cavernous nerve electrostimulation. The expression levels of related signaling pathways were evaluated using Western blotting, real‐time PCR, and immunohistochemistry. Results: Erectile function was significantly impaired in the DMED group compared with the control group and was partially improved in the DMED + JTE‐013 group. The expression of S1PR2 and the activity of the RhoA/ROCK/phospho‐myosin phosphatase target subunit 1 (p‐MYPT1) pathway proteins were higher in the DMED group than in the other two groups, and JTE‐013 treatment significantly reduced the expression/activity of these proteins. Furthermore, the DMED group showed severe corporal fibrosis, a higher apoptotic index and increased activity in the TGF‐β1/LIMK2/Cofilin pathway compared with the control group. JTE‐013 supplementation significantly ameliorated these pathological changes. Discussion and conclusion: JTE‐013 supplementation partially improved erectile function in rats with DMED, likely by inhibiting smooth muscle contraction, corporal fibrosis, and apoptosis. [ABSTRACT FROM AUTHOR]

Multi-layer InAs quantum wire stacks with different layer separations (8, 15, and 25 nm) and InAs thicknesses (3, 4, 5, and 7 monolayers [ML]) were grown on and embedded in In0.53Ga0.27Al0.20As barrier/spacer layers lattice-matched to an InP substrate. For the samples with 4 ML of InAs and different layer separations, double peak photoluminescence was observed from quantum wire stacks separated by 8 nm, and with a 15 nm spacer layer a long wavelength component was observed extending from the main peak. Only a single peak was found as the spacer layer thickness was increased to 25 nm. For the quantum wire stacks with different InAs layer thicknesses and a separation of 8 nm, double peak photoluminescence spectra were observed in the sample with 4 ML of InAs, and a main peak with a long wavelength component was obtained from the sample with 3 ML of InAs. Only a single peak was detectable for the InAs layer thicknesses of 5 and 7 ML. The optical emission features were studied via temperature and excitation laser power dependent photoluminescence. Based on the photoluminescence and transmission electron microscopy observations, photoluminescence spectral features can be attributed to a bi-modal height distribution in certain samples. In order to extend the optical emission to room temperature, the sample with 5 ML of InAs and an 8 nm spacer layer was subjected to post-growth rapid thermal annealing at different temperatures. The emission wavelength was tunable from 1.63 to 1.72 μm at room temperature. [ABSTRACT FROM AUTHOR]

Composition modulations are observed by transmission electron microscopy in In0.53Ga0.37Al0.10As barrier layers that overgrow both single- and multilayer InAs quantum wire structures grown on an InP substrate. Indium-rich (gallium-deficient) regions were observed in the region of the barrier layer lying directly above individual quantum wires, while indium-deficient (gallium-rich) regions were detected in the barrier above the gaps between adjacent underlying quantum wires. The magnitude of such modulation was typically 7% (atomic percent) for both indium and gallium as estimated from the energy dispersive x-ray analysis. The origin of such composition modulations was determined by modeling the chemical potential distribution for indium and gallium on the growth front of the barrier layer at the initial capping stage of the quantum wires with finite element simulations. It is found that the number and positions of the indium-rich regions are determined by the combined effects of strain and surface energy distributions on the barrier material capping the quantum wires. Moreover the estimated magnitudes of the composition modulation for both indium and gallium from the finite element models are in good agreement with the experimental observations. This method provides a simple way to understand the origin of, and to estimate the magnitude of the quantum wire-induced composition modulation in the barrier layer. [ABSTRACT FROM AUTHOR]

Quantitative compositional analysis of InAs quantum wires deposited between In0.53Ga0.37Al0.1As barrier layers grown on InP substrates was performed by electron energy loss spectrometry and energy dispersive x-ray spectrometry. An indium-rich region in the center of the wire, with decreasing indium concentration toward the interface with the barrier layers, was observed from indium concentration maps for individual quantum wires. “Stripelike” contrast modulation was observed in diffraction contrast transmission electron microscope images of the In0.53Ga0.37Al0.1As barrier layer immediately above the quantum wires. The contrast originated from indium compositional modulations in the upper barrier layer as confirmed by electron energy loss spectrometry and the modulation is attributed to the presence of an inhomogeneous elastic strain field generated by the buried quantum wires. These results suggest that quantitative analysis of the composition and strain distributions at very high spatial resolution provides insights necessary to further model the physical properties and to understand the growth of these nanostructures. [ABSTRACT FROM AUTHOR]

The environment of the fully mechanized working face is complex. The terrain is long and narrow. The multi-object and multi-equipment often appear in the same scene, which makes object detection more difficult. At present, the object detection method applied to the underground coal mine has the problems of high difficulty in characteristic extraction, poor generalization capability, and relatively single detection object category. The existing method is mainly applied to open scenes such as a roadway, a shaft bottom station, and is rarely applied to scenes of a fully mechanized working face. In order to solve the above problems, a video object detection method based on deep neural network is proposed. Firstly, in view of the unfavorable conditions such as complex and changeable environments, uneven illumination, and much coal dust in the fully mechanized working face, the monitoring videos are selected which containing key equipment and personnel of the fully mechanized working face at various angles and under various environmental conditions. By editing, deleting and selecting, an object detection data set covering various scenes of the working face site as much as possible is produced. Secondly, the LiYOLO object detection model is constructed by lightweight improvement of YOLOv4 model. The model fully extracts video characteristics by using CSPDarknet, SPP, PANet and other enhanced characteristic extraction modules. This model uses 6-classification YoloHead for object detection, which has good robustness to the dynamic change of environment and coal dust interference in fully mechanized working face. Finally, the LiYOLO object detection model is deployed to the fully mechanized working face. While the video stream is managed by Gstreamer, TensorRT is used to accelerate the reasoning of the model, and realize the real-time detection of multi-channel video streams. Compared with the YOLOv3 and YOLOv4 models, the LiYOLO object detection model has good detection capability, and can meet the real-time and precision requirements of video object detection in the fully mechanized working face. The mean average precision on the data set of fully mechanized working face is 96.48%, the recall rate is 95%, and the frame rate of video detection can reach 67 frames/s. The engineering application results show that the LiYOLO object detection model can detect and display 6-channel videos at the same time. The model has relatively good detection effect for detection of objects in different scenes.

Transmission electron microscopy is used for observing composition modulation in [In.sub.0.53][Ga.sub.0.37][Al.sub.0.10]As barrier layers that overgrow both single- and multilayer InAs quantum wire structures grown on an InP substrate. The number and positions of the indium-rich regions are determined by the combined effects of strain and surface energy distributions on the barrier material capping the quantum wires and the method has helped in estimating the magnitude of the quantum wire-induced composition modulation in the barrier layer.