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Carbon-free energy utilization in steel production is an effective way for China's iron and steel industry to achieve low carbon development. Thus, coal gasification-shaft furnace-electric furnace (CSE) technology, which use hydrogen-enriched gas for steel production, has recently become a sustainable topic of great concern. In the current study, the material flow analysis (MFA) and exergy assessment of the CSE process are conducted to investigate the material consumption and energy efficiency of this new steelmaking process. The exergy efficiency of the CSE process is calculated to be 50.11%, indicating a great potential for energy-saving. The results indicate that the coal gasification & gas purification that responsible for hydrogen-enriched gas production is the system with the largest exergy loss (account for 23.13% of the total exergy input), while the pelletizing system has the lowest efficiency (13.33%) due to heat loss. The key to further improve the thermal performance of this process lies in the heat recovery of the coal gasifier and pelletizing. It is also found that when the H2 content in reducing gas rise from 57.00% to 100.00%, the exergy efficiency of the shaft furnace is only increased by 1.58%, while the demand volume of reducing gas significantly increases from 1326.30 Nm3/t to 2201.50 Nm3/t. The environmental benefits of hydrogen reduction based steelmaking must be considered together with energy utilization and production cost. The present work should do helpful effort for the application and further improvement of the CSE process in China.

The stable tracking of small infrared targets in the complex backgrounds such as ground, sea surface and sky is an urgent problem to be solved. Taking into account both the robustness and real-time performances, based on the discriminative scale space tracking algorithm, the generalized structure tensor algorithm was applied that could effectively characterize the gray-scale mutation characteristics of the target area and the target shape information as a feature extraction method. The improved algorithm was more suitable for the rapid infrared image processing, which could improve the tracking robustness, and had a small amount of calculation, high efficiency, and low target feature dimension. In order to improve the stability of the model, it was decided to track the model update according to the confidence level, so as to avoid the model being disturbed by the wrong samples. Compared with the discriminative scale space tracking algorithm, the proposed algorithm has significant advantages in accuracy, real time and robustness, and achieves a tracking speed of 300 fps @256×256 pixels of image.

A new process for preparing high-purity iron (HPI) was proposed, and it was investigated by laboratory experiments and pilot tests. The results show that under conditions of a reduced temperature of 1075°C, reduced time of 5 h, and CaO content of 2.5wt%, a DRI with a metallization rate of 96.5% was obtained through coal-based direct reduction of ultra-high-grade iron concentrate. Then, an HPI with a Fe purity of 99.95% and C, Si, Mn, and P contents as low as 0.0008wt%, 0.0006wt%, 0.0014wt%, and 0.0015wt%, respectively, was prepared by smelting separation of the DRI using a smelting temperature of 1625°C, smelting time of 45 min, and CaO content of 9.3wt%. The product of the pilot test with a scale of 0.01 Mt/a had a lower impurity content than the Chinese industry standard. An HPI with a Fe purity of 99.98wt% can be produced through the direct reduction?smelting separation of ultra-high-grade iron concentrate at relatively low cost. The proposed process shows a promising prospect for application in the future.

Traditional high-precision long-distance time–frequency transmission requires a complex compensation structure and a continuous optical link, which make high-precision transmission difficult. In this study, we use two counter-propagating optical frequency combs to realize high-precision two-way time–frequency transfer over a 20-km fiber link. The transmission distance transmitted in this experiment is also farther greater than the current free-space transmission distances transmitted over free space. The two optical frequency combs are locked to the same radio frequency reference source. The method makes measurements more flexible and reduces interference. To suppress the effect of dispersion, we use an optical filter to narrow the bandwidth of the optical comb. Meanwhile, the bandwidth of the optical filter is chosen to ensure that the optical comb has the best signal-to-noise ratio at a remote site. We measure the timing difference over 24 h between the local site and remote site.

This paper presented a numerical simulation of drag reduction on a superhydrophobic surface with a groove structure. The computational fluid dynamics (CFD) method was used to analyze the effect of the groove microstructure when droplets impacted a superhydrophobic surface. The simulation results revealed three main characteristics: (1) The distance the droplet spread was larger along the direction parallel to the groove and smaller perpendicular to the groove; (2) Two protruding small spheres were formed at the edge of the droplet along the groove direction; (3) During retraction, the droplets presented a narrow, cross-shaped morphology. The effect of the groove structure in the two-dimensional microchannel on drag reduction near the wall was analyzed based on slip theory by the coupled level set/volume of fluid (CLSVOF) method. The air in the superhydrophobic pit formed a low-velocity vortex, which made the fluid roll on the air surface. The rolling on the surface produced a velocity slip at the gas–liquid interface. In addition, the superhydrophobic surface had an obvious drag reduction effect in the laminar flow state, but the drag reduction effect in the turbulent state was not ideal and even increased the flow resistance at the wall.

Ali CMB Polarization Telescope (AliCPT-1) is the first CMB degree-scale polarimeter to be deployed on the Tibetan plateau at 5,250m above sea level. AliCPT-1 is a 90/150 GHz 72 cm aperture, two-lens refracting telescope cooled down to 4 K. Alumina lenses, 800mm in diameter, image the CMB in a 33.4{\deg} field of view on a 636mm wide focal plane. The modularized focal plane consists of dichroic polarization-sensitive Transition-Edge Sensors (TESes). Each module includes 1,704 optically active TESes fabricated on a 150mm diameter silicon wafer. Each TES array is read out with a microwave multiplexing readout system capable of a multiplexing factor up to 2,048. Such a large multiplexing factor has allowed the practical deployment of tens of thousands of detectors, enabling the design of a receiver that can operate up to 19 TES arrays for a total of 32,376 TESes. AliCPT-1 leverages the technological advancements in the detector design from multiple generations of previously successful feedhorn-coupled polarimeters, and in the instrument design from BICEP-3, but applied on a larger scale. The cryostat receiver is currently under integration and testing. During the first deployment year, the focal plane will be populated with up to 4 TES arrays. Further TES arrays will be deployed in the following years, fully populating the focal plane with 19 arrays on the fourth deployment year. Here we present the AliCPT-1 receiver design, and how the design has been optimized to meet the experimental requirements., Comment: Proc. SPIE, 11453, 114532A (2020)

When nuclear power plants (NPPs) are in failure state, it may release radioactive substance into the environment. Thus, the safety of NPPs is put forward a high standard. Fault detection and diagnosis (FDD) are significant for NPPs to help operator timely know the state of system and provide the online guidance. Fault diagnosis can improve the safety of nuclear power plants, but current fault diagnosis methods pay too much attention to accuracy of diagnostic results. As a complex industrial system, how to explain the causes of faults in NPPs becomes more important. Although there are many studies on the knowledge graph, there is no detailed description on the failure process (consider timing). This paper proposed a three-layer structure for FDD in NPPs. Each layer represents the stage of the accident, it can give the operator a clear cognitive process to faults. The three-layer structure includes “smooth layer”, “threshold layer” and “fault layer”. The three layers indicate the reason of faults, the response of the parameters at each stage, and clearly showing the accident process. The smooth layer uses the stability analysis to analyze whether the current NPP is operating abnormally; the threshold layer uses the thresholds of the NPP to monitor which parameters have exceeded the upper limit or the lower limit; the fault layer reflects what is happening in the current operation and accidents are explained using signed directed graph. This paper takes the loss of coolant accident as an example, three-layer structure is analyzed, which shows the feasibility of the method. The case shows that the proposed method is superior to the conventional SDG method, can diagnose the faults, and give the reason of diagnosis results.

Fault tree analysis (FTA) is one of the most important methods of probabilistic risk assessment (PRA). The fault state of the system is taken. While traditional FTA is based on static failure model. FTA is not applicable for systems that include redundant, sequence-related systems. At the same time, nuclear power plants (NPPs) contains a large number of redundant equipment, and FTA is difficult to solve these dynamic problems. Therefore, it is necessary to use dynamic fault tree analysis (DFTA) for PRA. In DFTA research, the modular analysis method was first proposed. The modular method divides the dynamic fault tree into a dynamic fault tree and a static fault tree. Among them, the dynamic fault tree is analyzed using a Markov chain, and the static fault tree is studied using a binary decision diagrams method. However, the shortcomings are that when the system is complicated, the information explosion in the Markov chain is appeared. To solve this problem, a dynamic fault tree is transformed into a Bayesian network. At the same time, to verify the feasibility of the method, Monte Carlo random sampling was used to evaluate the method. Other methods are relatively infrequently studied. In this paper, firstly, status of dynamic fault trees has been investigated. Secondly, each method is analyzed and the problems of dynamic fault tree are described. Finally, a survey and analysis on the dynamic fault tree is finished, and the main problems of the dynamic fault tree are: information explosion; the lack of commercial software to apply to engineering. Through this review, we hope to play a certain guiding role in the subsequent research on dynamic fault trees.

INTRODUCTION AND OBJECTIVE:Premature ejaculation (PE) is one of the most common sexual dysfunctions and shows genetic predisposition. In this study, we aimed at exploring the mutation spectrum of l...

Objective: To ensure the accuracy and reliability of the data collection, access, processing and analysis of the reproductive toxicity test, and to improve the efficiency of the test, a computer management system for the reproductive toxicity test, Reprodv1.0, was developed. Method: Referring to the ICHS5a technical requirements and the national GLP specifications, the Access database was used as the basic database, and the VisualBasic6.0 computer language and tools were used to compile the database. Result: The main performance characteristics of the Reprodv1.0 software are as follows. The main window includes nine main menus of the files, data input, printing original records, printing logs, statistical analysis, data query, data modification, port setting and help. Computer automatic grouping and manual grouping before and after the mating are allowed in the system. The frequency of the weighing and the feed consumption testing can be determined according to the specifications. The self-developed database contains the most abnormal behavior signs of the laboratory animals. There are more than 800 common abnormal or variant names of the laboratory animals in the database of appearance and visceral and skeletal deformities. Printing operation logs and screen prompts are used to solve the problem of missing or miss-electing the objects caused by the complex and tedious test procedures. The experimental results were analyzed by the nest-based statistical method. The data query and the printing module can analyze and inspect or print the periodic test results at any time. Set up the multi-level security passwords to ensure that researchers of all kinds can get the data they should know in time. Conclusion: The performance and the technical indicators of Reprodv1.0, a computer management system for the reproductive toxicity test developed by this research institute, meet the design requirements. This software can not only improve the efficiency of the test work, but can also increase the accuracy and reliability of the data acquisition, access, processing and analysis.

Astragalus membranaceus is widely used in the treatment of clinical tumors. Astragalus polysaccharide is an important bioactive substance extracted from Astragalus membranaceus. In recent years, it has been found that it plays an important role in the anti-tumor and immunity process of Astragalus membranaceus, and plays an anti-tumor role through a variety of ways. The study of its anti-cancer mechanism will help to further explore the mechanisms of the action of Astragalus membranaceus, and provide basis for its further clinical application, so that it can play a better role in the clinical treatment and play the advantages of the traditional Chinese medicine in anti-cancer, so as to improve the curative effect of cancer patients.

The reward management is the focus of the human resource management, and the salary system is the basis of the reward management. As the reward management is very sensitive, which not only involves the interests of employees, but also affects the operation efficiency and development of the unit, therefore, we should standardize the design of the reward management from a scientific perspective, so as to achieve the best results of the staff compensation and welfare. The salary management and optimization of the medical staff in Shaanxi public hospitals of traditional Chinese medicine is of great significance to the medical work of the relevant personnel. Therefore, it is very important to give full play to the advantages of the information technology and innovate the salary management system.

Gastric cancer is a malignant tumor with a high degree of malignancy. Multiple liver metastases from gastric cancer (LMGCs) are common. However, the treatment of LMGCs is very difficult. It is rare to achieve complete remission (CR) and long-term survival after treatment. We present the case of a patient with gastric adenocarcinoma and multiple liver metastases who showed CR for more than 33 months after perioperative EOX (epirubicin, oxaliplatin, and capecitabine) combination chemotherapy with radical distal gastrectomy and resection of liver metastases. The patient is still in follow-up without tumor recurrence. These findings suggest that LMGC does not necessarily mean a poor prognosis; preoperative chemotherapy combined with surgery may be a good treatment option for LMGC in selected patients. Further studies are needed to support this treatment approach.

Trigger characteristics of electrostatic discharge (ESD) protecting devices operating under various ambient temperatures ranging from 30 °C to 195 °C are investigated. The studied ESD protecting devices are the H-gate NMOS transistors fabricated witha 0.18-μm partially depleted silicon-on-insulator (PDSOI) technology. The measurements are conducted by using a transmission line pulse (TLP) test system. The different temperature-dependent trigger characteristics of grounded-gate (GGNMOS) mode and the gate-triggered (GTNMOS) mode are analyzed in detail. The underlying physical mechanisms related to the effect of temperature on the first breakdown voltage V T1 are investigated through the assist of technology computer-aided design (TCAD) simulation.

Vertical integration is one of the important means to achieve coal-electricity joint ventures. According to the comprehensive analysis of domestic and foreign literature, based on the field survey, nine key drivers of vertical integration of coal-electric energy supply chain are proposed. This basis, using interpretative structural modelling (ISM), a five-level hierarchical structure model of the vertical integration motivation of the coal-electric energy supply chain is constructed, which clearly characterization of the hierarchical relationship between the various drivers. Using MICMAC, find the independent and dependent factors. Furthermore, it reveals the most direct motivation and the most fundamental motivation for driving the vertical integration of coal-electric energy supply chain. At the same time, it can clearly show the role of each driver in the vertical integration of coal-fired energy supply chain.

Recently, global economy is undergoing a structural change. The current world economic structure is mainly characterized by low growth rates in the economy, investment and trade, as well as low coal prices, interest rates and inflation. Overcapacity is a problem in many traditional industries. With the deterioration of overcapacity in coal-rich province of China, how to reduce coal production overcapacity is becoming an urgent problem to be solved. China’s coal market is still under the pressure of excess production capacity, the structural overcapacity has not been completely resolved. The coal industry is highly market-oriented, so the market mechanism plays an important role in the market downturn performance. Based on the Cournot competition model, this paper obtains the optimal cut coal production overcapacity output of coal production enterprises, the scenario of each firm enters the market in normal coal production capacity is analysed, in excess coal production capacity scenario without or with cut coal production overcapacity output. The analysis as show that: optimal cut coal production overcapacity output is the optimal choice for coal production enterprises in coal-rich province of China.

The quality of underwater imaging can be severely degraded by particles in the turbid water due to absorption and backscatter effects. This study proposes an underwater image recovery method based on hyperspectral polarization imaging. The proposed method is based on a physical degradation model, and combines polarization recovery and spectral fusion methods. Thus, the optimal spectral fusion is realized according to the spectral selectivity of the polarization recovery method, leading to underwater imaging with improved clarity as well as effective colour information restoration. The experimental results show that, compared with other methods, the comprehensive restorative abilities of the method proposed in this study are better with respect to subjective vision and various image quality evaluation indexes. The proposed method is effective for enhancing the visibility and contrast of underwater images for objects comprising different materials and at different imaging distances. Consequently, the proposed method has potential application value in many underwater complex environments.

China’s steel industry has been phenomenally developed. However, approximately 90% of the crude steel is produced through the blast furnace-basic oxygen furnace (BF-BOF) process with high energy consumption and high pollution. The coal gasification-shaft furnace-electric furnace (CSE) steelmaking technology has recently become a sustainable topic of great concern, due to its environmental and economic benefits. The life cycle assessment (LCA) of the CSE process is conducted to quantify the environmental impact of this new steelmaking process. The GaBi 7.3 software and CML 2001 method are used and the Ecoinvent database is accessed. The life cycle inventory data of the CSE process and BF-BOF process are obtained from a 0.1-Mt/a scale pilot plant and a large-scaled steel plant in China, respectively. The assessment results show that the electric arc furnace (EAF), decarburization, pelletizing and gas heating plants yield the highest contributions to environmental impacts. The environmental impacts of the CSE process and BF-BOF process are 1.83 E−11 and 9.33 E−11, respectively. Compared with the BF-BOF process, the carbon emission and energy consumption of the CSE process can be reduced by 58.1% and 60.6%. Besides, when the ratio of hot metal increases, the environmental performance of the CSE process deteriorates despite the decrease in power consumption. Due to the lower environmental impacts, the CSE process, which is designed to produce steel based on coal, iron ore and scrap instand of hot metal, should be advocated. From the perspective of comprehensive environmental impact, it is necessary to reduce the steel production through the BF-BOF process.

The coal quality characteristics of urban sludge were analyzed, and three types of coal-sludge-coupled power generation technologies were introduced, including direct sludge mixing, flue gas direct drying sludge and steam indirect drying sludge coupling power generation. Three types of sludge coupling power generation technologies in coal-fired power plant were introduced, including direct sludge blending process, sludge blending after drying directly by flue gas and indirectly by steam. The control values of sludge blending ratio and moisture content after sludge drying are analyzed, and it is considered that the direct sludge blending ratio should be controlled within 5%. The moisture content after sludge drying should be controlled at 30-40% and the blending ratio should be controlled within 10%. The influence of sludge blending on the operation of the unit is analyzed. The operation of coal-fired boiler is stable, the quality of fly ash and slag has little change, and the emission of pollutants and heavy metals reaches the standard if the proportion of sludge mixed with combustion is controlled within 10%.

Solar energy is regarded as the most promising resource, and its application is critical to establish global energy interconnection. The paper sets up the AHP (Analytic Hierarchy Process) model for comprehensive assessment of solar energy technology, and assess the development and application of solar energy technologies, including concentrating solar thermal power(CSP), photovoltaic(PV) power generation, solar heating, solar cooling, solar fuels, etc. According to the comprehensive assessment results, the paper determines priorities, analyzes the advantages and drawbacks of various technologies, and proposes the countermeasures on the further developing of solar energy technologies.

In order to improve the comprehensive qualities of students in all respects, fully reflect and evaluate the achievements of students, inspire students to improve themselves unceasingly, encourage them to strive to be the best, develop their personalities and strive for truth and innovation, as well as achieve the institutionalization, standardization and scientificalness of students management work gradually, meanwhile, along with the development of university construction and students management, maintenance and management of students’ data information has been exceptionally heavy, so it cries out for a set of reasonable and convenient students quality evaluation system. Students’ quality evaluation system is designed to make better use of computer technology in managing and inquiring about total performance of students’ qualities. Through analysis of the objective of system construction, combining design principle of the system, this thesis analyses and designs the quality evaluation system architecture from the perspectives of architecture, function module and security model.

Wang Jiaxin emerged in the 1980s as one of the most prominent post-Misty poets while serving as editor of Shikan (Poetry Monthly) from 1985 to 1990. In addition to publishing his own collections of...

Combined with the dispatching automation information of the power supply enterprise has been released to the power grid managers through the WEB, the power grid dispatchers constant changes and automation system updated frequently, discussed the simple and convenient dispatching automation SCADA (Data Acquisition and Monitoring) online application guidance and PAS (Grid Analysis Software) training and examination scheme. Dispatching automation SCADA application guidance focuses on the operation of the man-machine interface and the understanding of the data meaning, while PAS focuses on the state estimates and dispatcher power flow typical operation. The practical application results showed that the method is urgent, necessary and effective.

This paper introduces methods of several transformation matrixs in filight simulation on digital Earth. Use these methods and use double-precision matrix, avoiding the calculation of the simulation engine, the error caused by an error caused by simulation results, to better meet the design requirements.

This paper introduce a method of data recording system, which is designed with low power consumption and recording mass data storage requirements, and to facilitate rapid unloading the flight data processing requirements.

The concern about national security has increased significantly since the 9/11 attacks. However, information overload and lack of advanced, automated techniques hinders the effective analysis of criminal and terrorist activities. Data mining applied in the context of law enforcement and intelligence analysis, called investigative data mining (IDM), holds the promise of alleviating such problems. In this paper, we present an understanding to show how IDM works and the importance of this approach in identifying key nodes in terrorist networks.

In this paper, we focus on the parameter identification problem, one of the most essential problems in the 3D cloth animation created by multimedia software. We present a novel interactive parameter identification framework which integrates the industry knowledge. The essential of this paper is that we design a hybrid intelligent learning system using statistical analysis of kawabata evaluation system(KES) data from fabric industry database, fuzzy system and radial basis function(RBF) neural networks. By adopting our method the 3D cloth animator can interactively identify the parameters of cloth simulation with subjective linguistic variables while in the past decades it is very difficult for cloth animators to tune the parameters. We solve the 3D cloth parameter problem using the intelligent knowledge integration method for the first time in the multimedia and graphics research area and our method is applied to the most popular 3D tool Maya. The experimental results illustrate the practicability and expansibility of this method.

In this paper we present a novel parameter learning and identification method of virtual garment. We innovate in the ordinary parameter identification process and introduce the fabric data (Kawabata Evaluation System data) to combine the expert’s knowledge with fuzzy system. With our method the parameters of virtual garment can be calculated automatically which are assigned by the animator’s experience and hard to tune in the past years. The statistic analysis and machine learning method are used to build the fuzzy system to present the fabric expert’s knowledge. With interactively inputting the human subjective variables to our method, the animator who knows little knowledge in physical attributes of fabric material can also create and tune the virtual garment application. The experimental results indicate that this method can be used in practical virtual environments and has the expansibility to other applications.

The identification of traditional Chinese medicine is a difficult subject in pharmacology. The development of chemical measurement and pattern recognition make chemical pattern recognition possible. In this paper a new chemical pattern recognition method named NN2GA is proposed, in which a simple method named corresponding-peak distance calculation is used to compute the distance between samples for a nearest neighbor (NN) classifier, and a genetic algorithm is used to optimize the parameters of the NN classifier. A method named NN3GA, which is realized by adding a parameter to NN2GA, is proposed to improve the performance of the classifier. Experiments are carried out on chromatogram data of Panax, and comparisons are made between NNPR, NN2GA, and NN3GA classifiers. The results indicate that the method which combines NN with a genetic algorithm can identify medicine material having different harvest times or habitats. Furthermore, this method is robust, accurate and easy to implement.

To control the free floating spacecraft in outer space, this paper builds a model of free floating sphere movement under the action or multi-thrusters, and uses genetic algorithm (GA) to optimize the path and position in different control phases by using a combination of thrusters. In each phase, it makes the control target as the fitness function of GA to search the best solution, then uses this combination to move the sphere to an objective position and stabilizes it in the objective state. Contrasted to the traditional optimal control method, this control method is much simple and does not need a complicated algorithmic analysis, but can achieve a much effective result.

The identification of Chinese traditional medicine is a difficult subject in pharmacology. The development of chemical measurement and pattern recognition make chemical pattern recognition possible. In the paper a new chemical pattern recognition method is proposed, in which a simple method called corresponding-peak distance calculation is used to compute the distance between samples for a nearest neighbor (NN) classifier, and a genetic algorithm is used to optimize the parameters of the NN classifier. With the proposed method, experiments are carried out on chromatogram data of Panax. The results indicate that the method can identify the medicine material of different harvest time or habitats, furthermore, this method which combines pattern matching, genetic algorithm and NN classifier is robust, accurate and easy to implement.