华能日照电厂1号、2号机组AGC控制功能优化研究

针对华能日照电厂一期2×350 MW机组控制系统存在的负荷响应速度慢,无法满足电网自动发电控制(AGC)功能要求等问题,对机组协调控制、过热蒸汽温度、一次风压力、磨煤机一次风量等相关控制逻辑进行了优化,并对相关控制系统调节器参数进行了整定,广泛使用变结构、变参数控制,提高了机组控制系统的控制品质。1号、2号机组在投入协调控制方式后,分别进行了变负荷速率、变负荷范围的试验,以及AGC考核试验。结果表明,优化后的协调控制系统各项控制指标能够满足电网AGC功能的要求,机组负荷变化范围为175~350 MW,负荷变化率达到4.5 MW/min,机组主要参数满足运行要求。     

A nonlinear model to rank association rules based on semantic similarity and genetic network programing

Many methods have been studied for mining association rules efficiently. However, because these methods usually generate a large number of rules, it is still a heavy burden for the users to find the most interesting ones. In this paper, we propose a novel method for finding what the user is interested in by assigning several keywords, like searching documents on the Web using search engines. By considering both the semantic similarity between the rules and keywords, and the statistical information like support, confidence, chi-squared value, etc. we could rank the rules by a new method named RuleRank, where evolutionary methods are applied to find the optimal ranking model. Experiments show that our approach is effective for the users to find what they want. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Augmentation of polysialic acid by valproic acid in early postnatal mouse hippocampus and primary cultured hippocampal neurons

We examined the effects of valproic acid (VPA) on hippocampal neurons. Prenatal VPA exposure significantly increased polysialic acid (PSA) expression in the early postnatal mouse hippocampus. Moreover, VPA treatment significantly enhanced PSA expression in primary cultured hippocampal neurons and stimulated neurite growth. Our results suggest that VPA exposure in ovo affects hippocampal development.     

Analysis of energy consumption of elevator group supervisory control system based on genetic network programming

Elevator Group Supervisory Control System (EGSCS) is a traffic system, which provides the transportation services for passengers in modern buildings. As the elevator systems include uncertainty due to the future arrival of the passengers, it difficult to model, analyze, and optimize the elevator group supervisory control system. Recently, artificial intelligence technology has been used in such complex systems. Genetic Network Programming(GNP), a graph‐based evolutionary method extended from genetic algorithm and genetic programming, has been already applied to EGSCS. On the other hand, since energy consumption is becoming one of the greatest challenges in the society, it should be taken as one of the criteria of the elevator operations. The elevators with maximum energy efficiency are therefore required. In this paper, the GNP is used to solve EGSCS with energy consumption (EC). Moreover, the idle car assignment has been embedded in the proposed method. Finally, the simulations show that some factors should be introduced into GNP in order to deal with the higher EC in the light traffic of the elevator systems. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A portfolio selection model using genetic relation algorithm and genetic network programming

In this paper, new evolutionary computation methods named genetic relation algorithm (GRA) and genetic network programming (GNP) have been applied to the portfolio selection problem. The number of brands in the stock market is generally very large, therefore, techniques for selecting the effective portfolio are likely to be of interest in the financial field. In order to pick up the most efficient portfolio, the proposed model considers the correlation coefficient between stock brands as strength, which indicates the relation between nodes in GRA. The algorithm evaluates the relationships between stock brands using a specific measure of strength and generates the optimal portfolio in the final generation. Then, the selected portfolio is further optimized by the stock trading model of GNP. In a sense, the proposed model is an integrated intelligent model. A comprehensive analysis of the results is provided, and it is clarified that the proposed model can obtain much higher profits than other traditional methods. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Image denoising using pulse coupled neural network with an adaptive Pareto genetic algorithm

Recently, pulse coupled neural network (PCNN) attracts much attention in image denoising as a nonlinear filtering technique. The PCNN‐based anisotropic diffusion (PCNN‐AD) method has been proposed previously for flicker noise reduction and its effectiveness has been demonstrated. Using the visual characteristics of PCNN, PCNN‐AD has also solved the problem of AD that AD is not able to suppress the isolate noise. However, there are still two drawbacks in PCNN‐AD, that is, time consuming and PCNN parameters' estimation. In order to improve the efficiency and the denoising performance of PCNN‐AD, a PCNN‐based method with an adaptive Pareto genetic algorithm (GA‐PCNN) has been proposed to restrain from additive white Gaussian noise (AWGN) in this paper. GA‐PCNN firstly integrates the PCNN and AD as a parallel system, then, optimizes the parameters of a simplified PCNN by the adaptive Pareto GA. Experimental results indicate that GA‐PCNN has better performances than the previous denoising techniques, i.e. median filter, Wiener filter, AD filter, and PCNN‐AD. The effectiveness of GA‐PCNN on AWGN reduction and edge preservation are shown finally. The results will also contribute to denoising in CMOS image sensors in the future. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Molecular Features and Clinical Management of Hereditary Gynecological Cancers

Hereditary gynecological cancers are caused by several inherited genes. Tumors that arise in the female reproductive system, such as ovaries and the uterus, overlap with hereditary cancers. Several hereditary cancer-related genes are important because they might lead to therapeutic targets. Treatment of hereditary cancers should be updated in line with the advent of various new methods of evaluation. Next-generation sequencing has led to rapid, economical genetic analyses that have prompted a concomitant and significant paradigm shift with respect to hereditary cancers. Molecular tumor profiling is an epochal method for determining therapeutic targets. Clinical treatment strategies are now being designed based on biomarkers based on tumor profiling. Furthermore, the National Comprehensive Cancer Network (NCCN) guidelines significantly changed the genetic testing process in 2020 to initially consider multi-gene panel (MGP) evaluation. Here, we reviewed the molecular features and clinical management of hereditary gynecological malignancies, such as hereditary breast and ovarian cancer (HBOC), and Lynch, Li–Fraumeni, Cowden, and Peutz–Jeghers syndromes. We also reviewed cancer-susceptible genes revealed by MGP tests.     

Effect of Ultrasonic Irradiation on the Probability of Primary Nucleation of L-Arginine Hydrochloride

Most of the amino acids that are utilized as medical raw materials and food additives show polymorphism. To improve the functionality of amino acid crystals, an effective method of polymorph control is required in the crystallization process. Here, primary nucleation of L-arginine hydrochloride by ultrasonication was investigated. L-Arginine hydrochloride exhibits polymorphism, and it crystallizes into three distinct crystal forms. A cooling crystallization experiment was performed, and nucleation of each polymorph upon ultrasonication was observed. In addition, the nucleation was analyzed using the nucleation probability theory. The results indicate that ultrasonic irradiation would significantly induce the nucleation of a particular polymorph.     

Effect of additives on the renaturation of reduced lysozyme in the presence of 4 M urea

Reduced lysozyme was renatured by sulfhydryl-disuffide interchangereactions at pH 8.0 in the presence of 4 M urea, with or withoutadditives at 40°C. In the absence of additives, the finalfolding yield of reduced lysozyme was 40%. In the presence ofsarcosine, glycerol, ammonium sulfate, N-acetyl glucosamineand glucose, its folding yields increased in all cases. In particular,yields increased up to 90% in the presence of 4 M sarcosine.On the other hand, the melting temperatures of lysozyme withor without additives in 0.02 M citrate buffer (pH 6.0) wereevaluated using differential scanning calorimetry. In the absenceof additive, the melting temperature of lysozyme was 73.8°C.In the presence of additives, all melting temperatures werehigher than that of lysozyme in the absence of additives. Moreover,there was a good correlation on addition of additives betweenan increase in the folding yield of reduced lysozyme with 4M urea and an increase in the melting temperature without 4M urea. Therefore, we conclude that additives, which stabilizenative lysozyme, are effective at increasing the folding yieldof reduced lysozyme in 4 M urea.     

Biocatalytic Synthesis of Nitriles through Dehydration of Aldoximes: The Substrate Scope of Aldoxime Dehydratases

Nitriles, which are mostly needed and produced by the chemical industry, play a major role in various industry segments, ranging from high‐volume, low‐price sectors, such as polymers, to low‐volume, high‐price sectors, such as chiral pharma drugs. A common industrial technology for nitrile production is ammoxidation as a gas‐phase reaction at high temperature. Further popular approaches are substitution or addition reactions with hydrogen cyanide or derivatives thereof. A major drawback, however, is the very high toxicity of cyanide. Recently, as a synthetic alternative, a novel enzymatic approach towards nitriles has been developed with aldoxime dehydratases, which are capable of converting an aldoxime in one step through dehydration into nitriles. Because the aldoxime substrates are easily accessible, this route is of high interest for synthetic purposes. However, whenever a novel method is developed for organic synthesis, it raises the question of substrate scope as one of the key criteria for application as a “synthetic platform technology”. Thus, the scope of this review is to give an overview of the current state of the substrate scope of this enzymatic method for synthesizing nitriles with aldoxime dehydratases. As a recently emerging enzyme class, a range of substrates has already been studied so far, comprising nonchiral and chiral aldoximes. This enzyme class of aldoxime dehydratases shows a broad substrate tolerance and accepts aliphatic and aromatic aldoximes, as well as arylaliphatic aldoximes. Furthermore, aldoximes with a stereogenic center are also recognized and high enantioselectivities are found for 2‐arylpropylaldoximes, in particular. It is further noteworthy that the enantiopreference depends on the E and Z isomers. Thus, opposite enantiomers are accessible from the same racemic aldehyde and the same enzyme.