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Underground coal mining will cause large-scale surrounding rock movement, resulting in surface subsidence and irreversible deformation of surface morphology, which would lead to geological disasters and ecological environment problems. In this paper, FLAC3D numerical model is built based on the natural slope gradient, slope type, and included angle between the slope and working face, and their influences on the change of surface morphology and soil erosion caused by underground coal mining is studied. Research results show that the change of slope gradient caused by underground mining decreases with the increase of natural slope gradient, while slope length has opposite laws; different slope types have different changes of slope morphology. The order of slope types corresponding to gradient changes is mixed slope α

Methane is one of the most abundant molecules on Earth. Most of the state-of-the-art methane chemical conversion technologies require high temperatures, they are accompanied by insufficient selectivity, carbon deposition and major production of carbon dioxide. Development of the methane conversion technologies at mild conditions is important for the rational utilization of renewable and fossil feedstocks and for the environment. The goal of this review is to perform a comparative analysis of low temperature methane photocatalytic conversion routes such as methane oxidation, methane reforming and methane coupling. Methane photocatalytic reforming and selective oxidation currently exhibit the highest conversion rates, while methane coupling shows the highest selectivity. The most promising routes could be methane oxidation to methanol, which simultaneously exhibits higher productivity and selectivity. Further improvements in the methane conversion can be achieved by the design of new materials, photoreactors and operating modes, such as photochemical looping and combining photocatalysis with electrocatalysis.

Aiming at the problems in organizing command application skills training of junior commanding officer, it is proposed to build a simulated training environment based on UML (a kind of system description language). After the brief introduction of the UML, it uses UML to model the basic process of command training, then analyzes the overall structure of the simulation training environment. Finally, the application characteristics of command simulation training are briefly described.

International audience; Fischer-Tropsch synthesis (FTS) is an essential approach to convert coal, biomass, and shale gas into fuels and chemicals, such as lower olefins, gasoline, diesel, and so on. In recent years, there has been increasing motivation to deploy FTS at commercial scales which has been boosting the discovery of high performance catalysts. In particular, the importance of support in modulating the activity of metals has been recognized and carbonaceous materials have attracted attention as supports for FTS. In this review, we summarised the substantial progress in the preparation of carbon-based catalysts for FTS by applying activated carbon (AC), carbon nanotubes (CNTs), carbon nanofibers (CNFs), carbon spheres (CSs), and metal-organic frameworks (MOFs) derived carbonaceous materials as supports. A general assessment of carbon-based catalysts for FTS, concerning the support and metal properties, activity and products selectivity, and their interactions is systematically discussed. Finally, current challenges and future trends in the development of carbon-based catalysts for commercial utilization in FTS are proposed.

In the field of narratology and artificial intelligence (AI), AI Agent intervention has been paid attention to for many years. But typical AI researchers often lack the motivation to study the narrative model of humanities. On this basis, this paper combed basic understanding of studies on the AI intervention of narrative. It attempted to construct Generalized Story World Model from the perspective of media and literature genre and to expand AI Storytelling into the scope of electronic literature, hoping to attract the attention of researchers in related fields such as computer science, communication, art, design and psychology, so as to promote the research field into a stage of large number of trial and error as early as possible. Finally, the possibility of cross- media engineering practice of the Story Generator is predicted and inferred.

In order to promote the deployment of large-scale energy storage power stations in the power grid, the paper analyzes the economics of energy storage power stations from three aspects of business operation mode, investment costs and economic benefits, and establishes the economic benefit model of multiple profit modes of demand-side response, peak-to-valley price difference and auxiliary peak shaving service. Finally the paper have analyzed and verified the model in the power grid of a province in North China as an example.

With the continuous decline in the cost of distributed photovoltaic systems, distributed photovoltaic systems have met the conditions for user-side parity to grid-connected. Its grid-connected capacity and installation penetration rate in some areas have also continued to rise, which has greatly affected the safe and stable operation of the distribution network and the main network. After the high penetration rate of distributed photovoltaic is connected, while increasing the line loss and reducing the economy, it also raises the voltage of the user's grid connection point, increases the neutral line current, and affects the user's power supply quality and power safety. Large-scale access has even changed the operation of the Power grid. This paper analyzes the impact of distributed photovoltaics on the grid from the aspects of voltage rise, line loss, etc., and analyzes the characteristics of distributed photovoltaic output, and finally gives some suggestions to solve the problems of distributed photovoltaics.

Designing a swarm of robots to address different tasks and adapt to various environments through self-assembly is one of the most challenging topics in the field of robotics research. Here, we present an assembly robotic system with inchworm robots as modules. The system is called BioARS (Bionic Assembly Robotic System). It can either work as a swarm of individual untethered inchworm robots or be assembled into a quadruped robot. The inchworm robots are connected by magnets using a "shoulder-to-shoulder" connecting method, which helps strengthen the magnetic connection. Central pattern generators are used to control the trot gait of the quadruped robot. Our experiments demonstrate that the bionic assembly system is adaptive in that it can pass through confined spaces in the form of inchworms and walk on rough terrain in the form of a quadruped robot. The proposed BioARS, therefore, combines the flexibility of inchworms and the adaptability of quadruped animals, which is promising for application in planetary exploration, earthquake search and rescue operations. We also provide several examples of directions for future research regarding our system.

With the country’s emphasis on education, the average educational level of Chinese people is constantly improving, a growing number of families have realized the importance of early education. With the boom of "Internet + education" and the popularity of intelligent terminals, the development of early education began to enter the field of mobile applications. In recent years, artificial intelligence has been widely used in education by combining machine deep learning technology. This system combines CNN (Convolutional Neural networks, CNN) deep learning technology to design an early education auxiliary system for children. The technology and the accumulation of the amount of data by using CNN makes it a personalized early education assistant. Not only can solve the daily problems raised by children when they are studying together, but also provide parents with children’s learning data and learning reports. This system is aimed to help children develop early learning ability and assist parents to provide personalized education programs for their children.

Objective. To explore the relationship between elevated serum C-reactive protein (CRP) level and postoperative delirium (POD). Methods. 206 patients scheduled to receive cervical or lumbar vertebra surgery under general anesthesia for more than 2 hours in a single medical center were observed and analyzed. Patients’ serum CRP, delirious status (using the confusion assessment method (CAM)), and delirious score (using the memorial delirium assessment scale (MDAS)) were examined before surgery and 1-2 days after surgery. The association of a serum CRP elevation value from before to after surgery (D-CRP) with delirium occurrence within 2 days after surgery was assessed with a binary logistic regression model, while the association of D-CRP with the postoperative delirious score was assessed with a linear regression model. The effect of D-CRP on predicting delirium occurrence was evaluated with the area under the receiver operating characteristic (ROC) curve (AUC). Results. D-CRP was significantly positively associated with postoperative delirium occurrence (OR=1.047, 95%CI=1.013, 1.082), and D-CRP was also significantly linearly associated with the postoperative delirious score (β=0.014, 95%CI=0.006, 0.023). AUC of ROC was 0.711 (P=0.014), suggesting that D-CRP had moderate efficacy on predicting postoperative delirium occurrence (P<0.05). Conclusions. Elevated serum CRP after surgery may be a risk factor for and a predictor of postoperative delirium.

The performance of electronic switching between multiple backward-wave modes is studied in a designed extended interaction oscillator (EIO) based on a ladder circuit with finite number of periods to overcome electronic tuning range limits of EIOs operated in standing-wave mode. The dispersion characteristic of the circuit with finite number of periods, which is constructed by a series of discrete modes, is investigated. The mode separation is analyzed and reduced to support continuous switching between multiple different modes by increasing the number of periods as compared with the standing-wave EIO approach. An output circuit is designed to extract the power of backward wave. The electronic switching between nine backward-wave modes has been achieved by changing the beam voltage from 4.1 to 10.5 kV, where the maximum output power over 58 W is obtained at 5.3 kV from the simulation prediction. The EIO can operate over an electronic tuning range of 3.53 GHz from 89.65 to 93.18 GHz in ensuring the output power no less than 20 W. This technique can be extensively applied to increase operating band for extended interaction klystrons (EIKs) and electronic tuning range for EIOs, making them more suitable for many potential applications.

Based on the current status of the schedule management software, this paper analyzes the basic functions of the schedule management software, and proposes the design and improvement of the intelligent management personal schedule system for its single and inefficient schedule management method. At present, the schedule management method of the schedule management software, through the intelligent statistics and analysis of the user schedule, pushes scientific and reasonable scheduling schemes and suggestions to the user, and achieves the purpose of helping the user to effectively improve the life and work efficiency.

The doctor's assessment of the degree for pulmonary embolism often needs to calculate the volume about it. The most important thing is to accurately segment pulmonary embolism in the Computed Tomography Pulmonary Angiography (CTPA) images. This paper proposes a method to segment the pulmonary embolism from CTPA images and the method is based on U-net which is an effective semantic segmentation network in deep learning. This work uses partial weights from the VGG16 pre-training model to initialize the parameters of the contracting path in the U-net. It can extremely reduce time of training and improve the generalization ability of the network. However, the class of the samples is unbalanced extremely. This paper defined a new loss function which is combined Focal loss and Dice loss to solve this problem. And the experiment shows that the proposed method can get effectively segmentation of pulmonary embolism in CTPA images.

Inherent optical properties (IOPs) play a key role in modulating an aquatic light field; they are the core link for remotely sensing water constituents based on ocean color remote sensing. Many semi-analytical algorithms (SAAs) have been developed to obtain IOPs from remote sensing reflectance (R r s ) data; these algorithms require a forward model (FM) to link the IOPs to R r s . Most currently available SAAs use the FM presented by Gordon et al.[J. Geophys. Res.93, 10909 (1988)JGREA20148-022710.1029/JD093iD09p10909] (G88 hereafter) without knowledge of how other models would impact the retrieval of IOPs from R r s . This study evaluates the effects of two popular SAAs, namely, the quasi-analytical algorithm (QAA) and the generalized IOP algorithm (GIOP), combined with six different FMs on the retrieval of IOPs from a synthetic data set generated with Hydrolight software. The results indicated that different FMs can have quite different effects on the computed R r s (λ), and the effects were not uniform across the R r s spectrum. Of the six FMs tested, G88 and P05 [Appl. Opt.44, 1236 (2005)APOPAI0003-693510.1364/AO.44.001236] produced the best estimates of R r s (λ) at 350, 440, and 550 nm in both oceanic and coastal sub-datasets; they also were less impacted by changes in the particle phase function. M02 also produced a good estimation of R r s but only at 440 nm, and L04 performed well only in the oceanic condition. When the two SAAs were combined with the six FMs, in the oceanic condition, QAA and GIOP combined with M02 (QM02 and GM02) provided better quality for the absorption coefficient [a(λ)] at 350, 440, and 550 nm when compared with the SAAs combined with the other models. However, for the retrieval of the particle backscattering coefficient [b b p (λ)] in the oceanic condition, QAA and GIOP combined with L04 (QL04 and GL04) performed better than the others, and GL04 always provided a better estimation of b b p (λ) than QL04. In the coastal condition, QAA and GIOP combined with G88 or P05 produced slightly better quality of IOPs compared with the other four FMs. Compared with GIOP in the coastal condition, QAA combined with G88 or P05 always showed better quality of retrieval of a(λ) but weaker quality of retrieval of b b p (λ).

The development of railway integrated video monitoring system has experienced analog TV monitoring, digital video monitoring and network monitoring. But it still stays in the application of supervision and control. This paper focuses on the development of the Intelligent Railway Video Recognition(IRVR), and designs a general framework for IRVR platform. Firstly, the necessity of IRVR platform is stated form value of staff, technology and standard operation, which is based on the current situation and requirements analysis of railway video monitoring. Secondly, a general framework for IRVR platform is designed to deal with the actual problems. Thirdly, object detection algorithm flow for IRVR platform is proposed based on the analysis of key technology, especially revolve around deep learning. Finally, the experimental environment is built to verify the feasibility of the object detection algorithm for IRVR platform.

The lacustrine shales (e.g. shales deposited in the lake) are important commercial production targets for the oil and gas industrial. The pore network of shales has a significant effect on the occurrence state of natural gas&oil and reserve calculation. The exploration practice has indicated that the pore network of lacustrine shale is very different from that of marine shale. Although many researches have proposed that the pore network of lacustrine shales is influenced by clay minerals, however, the origin, evolution and preservation of pores in the lacustrine shales are still obscure. This study aims to reveal the effect of synchronous hydrocarbon generation and smectite-illite conversion on the formation and evolution of pores in lacustrine shales from the Chang #7 (C7) Member of the Upper Triassic Yanchang Formation in Ordos Basin, China. The middle and lower part of C7 Member is known as the “Zhangjiatan” shale, which is focused by oil shale exploration recently in China. The combination of analytical techniques was used to investigate the pore evolution related to clay minerals. The clay minerals within shales from the C7 Member consist of illite-smectite mixed layer minerals, illite, kaolinite and chlorite, accounting for 25.9–59.1% of the whole rock. There is a positive relationship between density functional theory (DFT) pore volumes and the content of clay minerals. DFT method is appropriate for all types of the pore, especially micropores. The mesopores (2–50 nm) dominated in the shale samples, while the organic matter only hosted a small amount of micropores ( 50 nm) can increase with the formation of illite layers, caused by the minerals volume shrinks and overpressure. The smectite-to-illite conversion is favorable for the pore network under the moderate thermal maturity. The synchronous smectite-to-illite conversion and hydrocarbon generation is a critical mechanism for the formation and preservation of pores in the lacustrine shale.

During the long service period of the transmission tower, the severe environment, material aging and fatigue effects result in the damage accumulation and resistance fading of the transmission tower, which even lead to the structural failure. In this paper, a stochastic subspace-based damage detection algorithm combined with statistical model is proposed for the damage identification of transmission tower structures through processing and analysing its vibration signals. Based on the structural modal parameters identified from the structural vibration response, the nominal modal parameters are defined. Considering that the Hankel matrixes constructed by the system observability matrix and the system output covariance matrix have the same kernel space, the damage index sensitive to the modal parameters is constructed. In the manuscript, firstly, the damage index establishment method and process of the algorithm are presented; and then the vibration data of transmission tower structure simulation under different damage conditions are obtained through numerical simulations; finally, above data are analysed to obtain the damage identification results of transmission tower. The results show that the method proposed in this work can effectively identify the local damage of transmission tower structure.

The new energy vehicles industry is the strategic development direction of China’s vehicles industry when there is an important need for this industry to realize the goal of energy conservation and environment protection, and of industry transformation and upgrading. It is an important approach that cooperatively innovating in the innovation network of industrial cluster to improve the industry’s innovation level and core competitiveness. Based on the empirical investigation of the innovation network of industrial cluster of new energy vehicles in the northeast China, this paper uses complex network theory to study the network structure from the perspectives of whole network, community and ego network of Hub. Moreover, this paper further discusses the matching problem of Hubs’ influence in the network. In addition, the relative suggestions about network governance on the innovation network of industrial cluster of new energy vehicles in the northeast China are proposed.

Summary Background/Objective Surgical technology has advanced rapidly with the introduction of robot technology. Apart from mechanical and electronic elements, housing design is an essential component that must be thoughtfully considered, bearing in mind the general requirements for medical devices used in operating theatres. The aim of this study was to design a modern and safe housing for a surgical robotic system for orthopaedic applications in Hong Kong that would meet the general requirements for obtaining local regulatory body approval. Methods Based on the general requirements for Class II Medical Devices, industrial product designers worked in close collaboration with a robot research team formed by engineers and orthopaedic surgeons to design a modern and safe housing for the HybriDot ® Surgical Robotic System that performs computer-assisted surgery. Results The design received local regulatory body approval for its application in operating theatres and was approved for orthopaedic surgery in Hong Kong after fulfilling the general requirements for safety, accuracy, movability and operability. Conclusion This project demonstrated a good model of multidisciplinary R&D of surgical robotics led by orthopaedic surgeons, in collaboration with mechanical and electronic engineers and industrial designers.

It is the first time that we constructs the evaluation index system of Guangzhou’s ecosystem status from three aspects of ecological resources, ecological structure and ecological quality, analyzes the historical change characteristics of Guangzhou’s ecosystem status in the past 11 years and the ecosystem status of 11 districts. Due to the decrease of ecological land area and the continuous increase of construction land area, the evaluation scores of ecosystem status in Guangzhou have declined in recent years, and the differences of ecosystem status in 11 districts are also obvious. Guangzhou will promote the regional ecological environment and further carry forward the construction of ecological civilization through various methods, such as strengthening the protection of natural ecological environment, stepping up the supervision of ecological environment, etc.

Private colleges and universities have made great contributions to solving the problem of insufficient educational resources. However, private colleges and universities have encountered many problems in the process of development, and the development of teaching staff is a prominent problem. Based on the author’s work experience, the paper analyzes the problems existing in the development of the teaching staff of the private higher vocational colleges, and puts forward corresponding countermeasures and suggestions, which will play a guiding role in the development of the teachers of the private higher vocational colleges.

Since the gradient vector flow (GVF)model is not suitable for multi-objects edges detection and cannot adapt to the change of the object's geometric topology, and the Chan-Vese (CV)model is easy to result in false detection, this paper proposes a new method for detecting the edges of the pulmonary artery for the computed tomographic pulmonary angiography (CTPA)image sequences which combines the advantages of GVF model and CV model. Firstly, the initial contour is driven by the GVF field. After getting the converged contour curve, the image inside the curve is extracted; Secondly, CV model-based edge detection is performed on the segmented image to solve the problem of multi-objects detection. Experiments show that the proposed method can effectively solve the problem of pulmonary artery edges detection in CTPA images. Applying the algorithm to targets tracking for image sequence, the method can detect the edges of each target separately, and obtain the independent contours, when the pulmonary artery is split into two.

We have previously demonstrated that anti-IL-1β immunoglobulin yolk(IgY) inhibits pathological responses in allergic asthma guinea pigs induced by ovalbumin(OVA). This study aims to determine whether the combined blockade of IL-1β and TNF-α can more effectively inhibit allergic inflammation in allergic rhinitis(AR) guinea pigs induced by OVA. Healthy guinea pigs treated with saline were used as the healthy control. The AR guinea pigs induced by OVA were randomly divided into (1) the AR model group containing negative control animals treated with intranasal saline; (2) the 0.1% non-specific IgY treatment group treated with non-specific IgY; (3) the 0.1% anti-TNF-α IgY treatment group treated with 0.1% anti-TNF-α IgY; (4) the 0.1% anti-IL-1β IgY treatment group treated with 0.1% anti-IL-1β IgY; (5) the 0.1% combined anti-IL-1β IgY and anti-TNF-α IgY treatment group treated with 0.1% combined anti-IL-1β IgY and anti-TNF-α IgY; and (6) the fluticasone propionate treatment group treated with fluticasone propionate. Cytokines were measured using an enzyme-linked immunosorbent assay. The results showed that IL-1β, IL-5, IL-9, IL-13, IL-18, IL-22, IL-33, TNF-α, TGF-β1 and OVA-specific IgE levels in the peripheral blood (PB) and nasal lavage fluid (NLF) significantly decreased at 2h, 4h or 8h in the 0.1% combined anti-IL-1β IgY and anti-TNF-α IgY treatment group compared to the AR model group and the 0.1% non-specific IgY treatment group (P

State-of-the-art deep neural network classifiers are highly vulnerable to adversarial examples which are designed to mislead classifiers with a very small perturbation. However, the performance of black-box attacks (without knowledge of the model parameters) against deployed models always degrades significantly. In this paper, We propose a novel way of perturbations for adversarial examples to enable black-box transfer. We first show that maximizing distance between natural images and their adversarial examples in the intermediate feature maps can improve both white-box attacks (with knowledge of the model parameters) and black-box attacks. We also show that smooth regularization on adversarial perturbations enables transferring across models. Extensive experimental results show that our approach outperforms state-of-the-art methods both in white-box and black-box attacks.

There are high demands for research of new device with greater accessing speed and stability to replace the current SRAM storage cell. The resistive random access memory (ReRAM) is a metal oxide which is based on nonvolatile memory device possessing the characteristics of high read/write speed, high storage density, low power, low cost, very small cell, being nonvolatile, and unlimited writing endurance. The device has extreme short erasing time and the stored charge cannot be destroyed after power-off. Therefore, the ReRAM device is a significant storage device for many applications in the next generation. In this paper, we first explored the mechanism of the ReRAM device based on ion mobility model and then applied this device to optimize the design of FPGA switching matrix. The results show that it is beneficial to enhance the FPGA performance to replace traditional SRAM cells with ReRAM cells for the switching matrix.

Sentiment analysis in news is different from normal text sentiment analysis. News usually have a specific topic, a focus semantic emotion, therefore, this paper, based on the principal of using Emotion Dependency Tuple (EDT) as the basic unit of news emotion analysis, resolves topic sentiment analysis in news into three progressive sub-problem, namely, topic sentence recognition, EDT extraction and topic sentiment analysis. We use an improved TF- IDF and cross entropy to extract feature set of topics. Then, based on space vector model, calculate the topic association of a sentence and extract topic sentence. Finally, we construct topic sentence based on EDT and complete clustering of news topic sentiment. This method is evaluated using COAE2014 dataset, and differential means shows that our results close to the best results. This shows that the topic based EDT could effectively improve performance of sentiment analysis in news.

Power line communication (PLC) has received much attention recently because of the need of reliable and automatic metering, In this paper we present a comprehensive study over the use of PLC in China. We begin with some background including the distribution grid topology, the power line channel environments, and the deployment of PLC network. Then we show some field test results of PLC-based meter-reading in a high frequency band. In addition, a suggestion how to improve G3-PLC is presented which can adapt China grid better.

The digital design of mechanical products is usually first reference existing parts, drawings, and experience to make original design data and design requirements, according to the design of digital model is set up, after an analysis of the finite element model according to the analysis results contrast design goal to design or structure parameter changes, to the expected design purpose. Analysis of the product is an essential part of product design.

To improve the designers’ work efficiency, reduce the design strength, transportation pallet modeling was built through three-dimensional software Pro/E, and the model was secondary developed by using Pro/Toolkit, Pro/E secondary development tools. Designer design independent program interface for drive Pro/E parameters of three-dimensional modeling of the transportation pallet.

To improve the designers’work efficiency, reduce the design strength, ceramicgear modeling was built through three-dimensional softwarePro/E, and the model was secondary developed by using Pro/Toolkit, Pro/Esecondary development tools. Designer design independent program interface fordrive Pro/E parameters of three-dimensional modeling of the ceramic gear.

This paper analyzes the stamping process of a rigid gasket, designs a set of progressive die for gasket. Three-position of the die includes the punching, cutting, bending and blanking. And compared with single-process die and compound die, the gasket can obtain better surface quality, the die can prevent poor strength and partial load, and punching hole in the ear and separating bending process can improve the accuracy of stamping parts, it has some reference value for the progressive die of the stamping parts. Throughout the design process, the model of rigid gasket and 3D mold design are established in Pro/E4.0 and PDX, this can significantly shorten the design cycle; the process of open-mode is simulated in the Simulation module.