A Fuzzy Neural Network Model of Linguistic Dynamic Systems Based on Computing with Words

Linguistic dynamic systems(LDS)are dynamic processes involving computing with words(CW)for modeling and analysis of complex systems.In this paper,a fuzzy neural network(FNN)structure of LDS was proposed.In addition,an improved nonlinear particle swarm optimization was employed for training FNN.The experiment results on logistics formulation demonstrates the feasibility and the efficiency of this FNN model.

Recent Requirements and Future Development of Integrated EMS/DTS System in China

Resent status for dispatch automation systems in China is introduced and the requirement for integrated EMS/DTS is discussed. The advantages of the integration of EMS/DTS are analyzed. Large benefit can be obtained to develop an integrated EMS/DTS system. EMS/DTS functions for district power system application are investigated and introduced. An application of the LINUX based EMS/DTS to Yulin power system is reported and is used to show the advantage of an open system. Future development of integrated EMS/DTS systems in China is discussed.

不同EMS处理时间对大豆诱变后代主要品质含量变化影响分析

为探究不同EMS处理时间对大豆诱变后代主要品质含量变化的影响,文章利用0.5%EMS溶液处理大豆高蛋白品系公交1057-1,分别浸泡4、7和10 h(清水冲洗处理为对照),对播种后获得的连续4代诱变后代主要品质含量变化进行分析。结果表明,与对照相较,经EMS处理后的植株成活率随处理时间延长而降低。其中,经EMS-4处理后的植株成活率最高,为43.5%;经EMS-10处理后的植株成活率最低,仅为16.0%。不同EMS处理时间对大豆诱变后代的蛋白质含量影响显著,对脂肪含量影响不明显。其中经EMS-4处理的诱变后代蛋白质含量高于其他3组处理;经EMS-4处理后的M2代蛋白质含量发生显著分离,并出现超亲个体,脂肪含量变化不显著。

甲基磺酸乙酯(EMS)对谷子种子及幼苗活力的影响

为了探明甲基磺酸乙酯(EMS)诱变嫩选18种子构建突变体库的最适条件,加快品种选育进程,本研究对嫩选18种子进行了3种处理时间、3种EMS处理浓度的化学诱导,并对M1种子发芽及幼苗生长的诱变效应进行研究。结果表明:与对照相比,EMS处理在浓度0.4%下浸种6 h对嫩选18的发芽率及幼苗生长影响差异不显著,随着EMS浸种浓度、时间增加,种子萌发及幼苗生长逐渐受到抑制,在1.2%浓度下浸种14 h对种子萌发及幼苗生长抑制作用最强,极大降低了嫩选18的发芽势、发芽率、成苗率,并且导致幼苗生长缓慢。以存活率达到50%为标准,通过回归方程计算出在6 h、10 h、14 h浸种时间下,EMS浓度的半致死剂量分别为0.99%、0.72%、0.38%,可作为嫩选18 EMS诱变建立突变体库的适合条件。

达乌里胡枝子愈伤组织及种子EMS诱变研究

为优化达乌里胡枝子愈伤诱导培养基的激素含量及比例,明确甲基磺酸乙酯(EMS)诱变愈伤组织及种子的最佳条件,本研究以达乌里胡枝子种子为外植体,探究了不同激素配比对愈伤诱导的影响,并针对愈伤组织和种子处理分别设置了两时间两浓度(2 h和6 h,0.3%和0.9%)及三时间两浓度(6 h、8 h、10 h,0.4%、0.8%)的EMS处理时间和浓度的组合,研究各处理对愈伤分化系数和后期植株成活率以及种子发芽率、发芽势和幼苗表型变异的影响。结果表明,达乌里胡枝子种子愈伤的最佳激素配比为0.25 mg/L NAA+0.5 mg/L 6-BA+0.5 mg/L 2,4-D,此时达乌里胡枝子愈伤诱导率为94.9%。EMS诱变达乌里胡枝子愈伤组织的适宜浓度为0.3%,处理时间为6 h,分化系数和植株相对成活率分别为46.31%和47.78%,接近半致死范围,且生根数、根长和平均株高等指标与高浓度EMS处理相比受到的负面影响较小。EMS诱变达乌里胡枝子种子的适宜浓度为0.8%,处理时间10 h,发芽率、出苗率、成苗率分别为53.61%、51.06%和53.28%,均接近半致死量,同时发现多株幼苗叶片出现了明显的形态变异。本试验在达乌里胡枝子原有种质资源基础上,丰富了达乌里胡枝子突变体库,也为后续开展达乌里胡枝子诱变育种研究提供理论依据。

On loan words between English and Chinese——Discussion about the openness and assimilation of the words system

This paper mainly discusses the openness and assimilation of the words system from the viewpoint of loan words between English and Chinese.Both the history of loan words and the ways of borrowing words in English and Chinese have shown us the strong abilities of languages.

On the Relation of Shadowing and Expansivity in Nonautonomous Discrete Systems

In this paper we study shadowing property for sequences of mappings on compact metric spaces, i.e., nonautonomous discrete dynamical systems. We investi- gate the relations of various expansivity properties with shadowing and h-shadowing property.

Analysis English Translation of Chinese Poems' Color Words——Functional Equivalence Theory

The translation of Chinese ancient poems has always been the direction of many translators at home and abroad,and the translation of color words has gradually become the object of study.However,due to the difference between translation theory and perspective,there are many controversial translations.Based on the theory of "functional equivalence" proposed by American translation theorist Eugene Nida,this paper analyzes the concrete translation of Chinese ancient poems,and aims to explore how to translate the color words in ancient poems in the best way,And summed up the specific and practical translation methods.

Channel estimation for MIMO-OFDM systems in rapid fading channels

A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multipleoutput （MIMO-OFDM） in rapid fading channels is proposed. This approach combines the advantages of an optimal training sequence based least-square （OLS） algorithm and an expectation-maximization （EM） algorithm. The channels at the training blocks are estimated using an estimator based on the OLS algorithm. To compensate for the fast Rayleigh fading at the data blocks, a time domain based Gaussian interpolation filter is presented. Furthermore, an EM algorithm is introduced to improve the performance of channel estimation by a few iterations. Simulations show that this channel estimation approach can effectively track rapid channel variation.

Input-to-state stability of Euler-Maruyama method for stochastic delay control systems

This paper develops the mean-square exponential input-to-state stability（exp-ISS） of the Euler-Maruyama（EM） method for stochastic delay control systems（SDCSs）.The definition of mean-square exp-ISS of numerical methods is established.The conditions of the exact and EM method for an SDCS with the property of mean-square exp-ISS are obtained without involving control Lyapunov functions or functional.Under the global Lipschitz coefficients and mean-square continuous measurable inputs,it is proved that the mean-square exp-ISS of an SDCS holds if and only if that of the EM method is preserved for a sufficiently small step size.The proposed results are evaluated by using numerical experiments to show their effectiveness.

Improved H-infinity channel estimator based on EM for MIMO-OFDM systems

H-infinity estimator is generally implemented in timevariant state-space models, but it leads to high complexity when the model is used for multiple input multiple output with orthogo- hal frequency division multiplexing （MIMO-OFDM） systems. Thus, an H-infinity estimator over time-invariant system models is pro- posed, which modifies the Krein space accordingly. In order to avoid the large matrix inversion and multiplication required in each OFDM symbol from different transmit antennas, expectation maximization （EM） is developed to reduce the high computational load. Joint estimation over multiple OFDM symbols is used to resist the high pilot overhead generated by the increasing number of transmit antennas. Finally, the performance of the proposed estimator is enhanced via an angle-domain process. Through performance analysis and simulation experiments, it is indicated that the pro- posed algorithm has a better mean square error （MSE） and bit error rate （BER） performance than the optimal least square （LS） estimator. Joint estimation over multiple OFDM symbols can not only reduce the pilot overhead but also promote the channel performance. What is more, an obvious improvement can be obtained by using the angle-domain filter.

禾本科植物EMS诱变研究进展

EMS是化学诱变中最常用的诱变剂,EMS诱变具有单个碱基点突变率高、成本低、易操作等优点,通过EMS诱变获得突变体可以为育种和基因功能研究提供有利的材料。EMS诱变技术的关键是确定EMS浓度和诱变时间,一般以达到半致死率的浓度和时间为最佳处理组合。禾本科植物中主要以种子为诱变材料,同时花粉、愈伤组织以及依靠营养繁殖的禾本科植物的营养器官也可以作为诱变材料。不同植物材料对EMS的耐受性不同,花粉最敏感,其次是愈伤组织,无性繁殖材料和种子的耐受性较强。突变体的筛选方式包括表型对比筛选、逆境定向筛选和正、反向遗传学筛选。本文综述了近年来EMS诱变技术在禾本科植物育种和基因功能研究中的应用,介绍了EMS的诱变原理、诱变剂浓度、处理时间、诱变处理材料的选择及突变体的筛选,并对未来禾本科植物中的EMS诱变研究进行了展望,为今后禾本科植物的EMS诱变研究提供参考。

Survey on AI and Machine Learning Techniques for Microgrid Energy Management Systems

In the era of an energy revolution,grid decentralization has emerged as a viable solution to meet the increasing global energy demand by incorporating renewables at the distributed level.Microgrids are considered a driving component for accelerating grid decentralization.To optimally utilize the available resources and address potential challenges,there is a need to have an intelligent and reliable energy management system(EMS)for the microgrid.The artificial intelligence field has the potential to address the problems in EMS and can provide resilient,efficient,reliable,and scalable solutions.This paper presents an overview of existing conventional and AI-based techniques for energy management systems in microgrids.We analyze EMS methods for centralized,decentralized,and distributed microgrids separately.Then,we summarize machine learning techniques such as ANNs,federated learning,LSTMs,RNNs,and reinforcement learning for EMS objectives such as economic dispatch,optimal power flow,and scheduling.With the incorporation of AI,microgrids can achieve greater performance efficiency and more reliability for managing a large number of energy resources.However,challenges such as data privacy,security,scalability,explainability,etc.,need to be addressed.To conclude,the authors state the possible future research directions to explore AI-based EMS's potential in real-world applications.

A simple channel estimator for space-time coded OFDM systems in rapid fading channels

A simple channel estimator for space-time coded orthogonal frequency division multiplexing (OFDM) systems in rapid fading channels is proposed. The channels at the training bauds are estimated using the EM (expectation-maximization) algorithm, while the channels at the data bauds are estimated based on the method for modelling the time-varying channel as the linear combination of several time-invariant " Doppler channels". Computer simulations showed that this estimator outperforms the decision-directed tracking in rapid fading channels and that the performance of this method can be improved by iteration.

甲基磺酸乙酯(EMS)对黄蜀葵植株表型性状和花黄酮类成分含量的影响及优株筛选

以甲基磺酸乙酯(EMS)为化学诱变剂,对体积分数1.0%(T1)、1.2%(T2)、1.4%(T3)、1.6%(T4)EMS诱变处理后黄蜀葵〔Abelmoschus manihot(Linn.)Medik.〕植株表型性状和花黄酮类成分含量差异进行比较,对单株花产量和花黄酮类成分含量与植株表型性状进行相关性分析,并基于单株花总黄酮产量进行优株筛选。结果表明:与对照组(体积分数0.0%EMS)相比,EMS处理组黄蜀葵株型变为接近丛生或丛生,叶裂片细长,花冠较小。4个EMS处理组黄蜀葵的株高较对照组显著(P<0.05)降低,茎粗与对照组差异不显著;随着EMS体积分数增加,叶片长、叶片宽、叶裂片长、叶裂片宽总体上先降低后升高,其中,体积分数1.4%和1.6%EMS处理组的叶片长、叶片宽、叶裂片长、叶裂片宽均高于或显著高于对照组;4个EMS处理组的花直径和花瓣宽低于或显著低于对照组,花瓣长和始花节数与对照组差异不显著,但体积分数1.4%和1.6%EMS处理组的单株开花数和单株花产量显著高于对照组。与对照组相比,4个EMS处理组花中6个黄酮类成分及总黄酮含量多无显著变化,仅体积分数1.0%和1.4%EMS处理组的棉皮素-8-O-β-D-葡萄糖醛酸苷含量以及体积分数1.0%EMS处理组的槲皮素-3′-O-葡萄糖苷含量显著升高。相关性分析结果显示:单株花产量与茎粗、叶片长、叶裂片长、始花节数和蒴果长显著正相关,与单株开花数极显著(P<0.01)正相关,而花中6个黄酮类成分和总黄酮含量与植株表型性状多无显著相关性。优株筛选结果显示:编号T3-3、T4-5、T3-1和T1-3植株的单株花总黄酮产量均在65 g以上,排名前4。总体来看,体积分数1.4%EMS的诱变效果最佳;并且,编号T3-3、T4-5、T3-1和T1-3单株可作为黄蜀葵高花总黄酮产量的优株。

EMS诱变对鹰嘴紫云英种子萌发及幼苗表型特征的影响

【目的】筛选适宜鹰嘴紫云英的EMS诱变条件。【方法】以鹰嘴紫云英品种甘绿2号种子为试验材料,采用不同浓度(0、0.2%、0.4%、0.6%、0.8%)的甲基磺酸乙酯(EMS)进行不同时间(2、4、6、8 h)的诱变处理,探究EMS对鹰嘴紫云英种子萌发特征及表型变化的影响。【结果】低浓度和短时间EMS处理促进鹰嘴紫云英种子的萌发,随EMS浓度升高和诱变时间的增加,对鹰嘴紫云英种子萌发产生抑制作用。种子浸出液电导率随诱变条件的加深呈上升趋势,在2~6 h时,萌发期发芽率、发芽势、幼苗苗长和根长均随处理时间和诱变浓度的增加呈先升高后降低的趋势,在8 h处理下,随EMS浓度的增加呈逐渐降低趋势,EMS浓度在0.8%时,种子发芽率和发芽势均达到最低,较对照分别降低了54.45%和56.67%;经形态学筛选,发现有鹰嘴紫云英幼苗表现出幼苗矮小、停滞生长、叶片黄化、宽叶、窄叶、叶片发紫、诸多病斑等特殊变异性状。【结论】0.8%EMS处理6 h可作为最佳诱变组合;幼苗的生长随诱变时间和浓度增加而明显受到抑制,且表型变异类型也逐步增多。

芒果^(60)Co-γ、EMS诱变及SC-SSR分子标记遗传多样性分析

诱变育种是短时间内增加物种遗传多样性和表型变异的最有效方法之一。为探明诱变创制芒果突变体基因库可行性,本研究以凯特芒果为试验材料,通过^(60)Co-γ射线辐射枝条和EMS溶液浸泡种子创制诱变群体材料,利用SC-SSR分子标记进行遗传多样性分析。结果表明:^(60)Co-γ射线辐射半致死剂量为31.37 Gy,0.2%EMS溶液浸泡半致死时间为5.9 h;利用16对SC-SSR引物分析100份诱变材料和1份凯特材料的遗传多样性,共检测出117个多态性位点,引物多态性条带百分比、多态性信息含量(PIC)、观测等位基因数(Na)、有效等位基因数(Ne)、Nei’s基因多样性指数(H)和Shannon’s信息指数(I)平均值分别为93.18%、0.610、1.923、1.583、0.334和0.493;试验材料间遗传相似系数在0.373~0.984之间,平均为0.779。诱变增加了芒果遗传信息,其中EMS诱变种子变异更大,本研究结果为芒果诱变育种提供了理论依据。

A Methodology to Develop the Integration of the Environmental Management System with Other Standardized Management Systems

Traditionally the global management system of an organization is frequently split into a number of individual management systems that are defined and implemented according to specific management systems standards (MSSs) as well as managed independently. The individual implementation of MSSs is an option that leads to several inefficiencies and sub-optimization of the global management system of an organization. As referred by ISO [1] the interested parties’ requirements increase. A more effective and efficient option for an organization is to integrate, into an integrated management system (IMS), the implementation and management of requirements of multiple MSSs. Certain difficulties are associated to the structuring process, implementation, verification, evaluation, improvement and progressive development of an IMS in the organizations. Several scholars have proposed various theoretical approaches regarding the integration of individual management systems (MSs) leading to the conclusion that there is not a common practice for all organizations as they encompass different characteristics. This paper aims to present and justify a designed methodology to be used by organizations to support the integration of various MSs. Among them are highlighted: the Environmental Management System (EMS) according ISO 14001 [2], the Quality Management System (QMS) according ISO 9001 [3], and the Occupational Health and Safety Management System (OH & SMS) according OHSAS 18001 [4]. The methodology was designed in the context of a Portuguese company, on sequence of an organizational diagnosis and a research that was performed through a questionnaire. The strategy and the research methods took into consideration the case study.

A BiLSTM cardinality estimator in complex database systems based on attention mechanism

An excellent cardinality estimation can make the query optimiser produce a good execution plan.Although there are some studies on cardinality estimation,the prediction results of existing cardinality estimators are inaccurate and the query efficiency cannot be guaranteed as well.In particular,they are difficult to accurately obtain the complex relationships between multiple tables in complex database systems.When dealing with complex queries,the existing cardinality estimators cannot achieve good results.In this study,a novel cardinality estimator is proposed.It uses the core techniques with the BiLSTM network structure and adds the attention mechanism.First,the columns involved in the query statements in the training set are sampled and compressed into bitmaps.Then,the Word2vec model is used to embed the word vectors about the query statements.Finally,the BiLSTM network and attention mechanism are employed to deal with word vectors.The proposed model takes into consideration not only the correlation between tables but also the processing of complex predicates.Extensive experiments and the evaluation of BiLSTM-Attention Cardinality Estimator(BACE)on the IMDB datasets are conducted.The results show that the deep learning model can significantly improve the quality of cardinality estimation,which is a vital role in query optimisation for complex databases.