Effect of Anion Surface Active Agent on the Preparation of SrTiO_3 Nano-Crystals

SrTiO_3 nano-crystal samples with floccule or flake crystal morphology,which were indexed as a perovskite-type crystal structure based on the results of XRD and TEM,were successfully prepared by one-step liquid reaction method.And the growth mechanism of the SrTiO_3 nano-crystals under the liquid condition with/without adding the surface active agent was investigated.It was found that adding the surface active agent contributes to the processing in which the ions gathering bodies transit to a more stable phase through the chemical reaction and form the flake SrTiO_3 nano-crystals.

CONSENSUS OF THE SECOND-ORDER MULTI-AGENT SYSTEMS WITH AN ACTIVE LEADER AND COUPLING TIME DELAY

This article investigates the consensus problem of the second-order multi-agent systems with an active leader and coupling time delay in direct graph. One decentralized state control rule is constructed for each agent to track the active leader and it is proved that the proposed control scheme enables the consensus to be obtained when the adjacency topology is fixed/switched. Simulation results show effectiveness of the proposed theoretical analysis.

Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

In this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and recovery.The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance.Although many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during analysis.Therefore,this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning(SPR-SVIAL)for Smart Healthcare Monitoring.At first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction process.Here,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from IoT wearable devices.To attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced features.After that,with these resulting features,SVIAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and Intelligent Agents to minimize both analysis falsification and overhead.Experimental evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several instances.The quantitatively analyzed results indicate the better performance of our proposed SPR-SVIAL method when compared with two state-of-the-art methods.

Agent和Active Object概念分析及其在数据库中应用的基本问题

较明确的表达了Agent及Active Object的概念，研究了在数据库中设计Agent及Active Object的基本问题，并简要讨论了Active Object和Active DBMS之间的联系．

Effects of Water-retaining Agents on Growth, Development, Yield and Quality of Soybean under Drought Stress

[Objectives]The paper was to explore the effects of different doses of water-retaining agent on the growth and development indicators,yield and quality of soybean plants subjected to drought stress.[Methods]The effects of drought stress(MDS)and drought stress with low(MDS-L),medium(MDS-M)and high doses(MDS-H)of the water-retaining agent on the growth and development indicators,root activity,MDA content,antioxidant enzyme activity,yield and quality of soybean were studied by field plot test,with the normal water supply serving as the control(CK).[Results]In response to drought stress,the plant height,stem diameter,and yield of soybean exhibited a notable decline.Additionally,the contents of protein,fat,linoleic acid,and linolenic acid in seeds demonstrated a significant reduction.Conversely,the root activity and antioxidant enzyme activity exhibited a noticeable decline,while the MDA content exhibited an increase.The application of varying doses of the water-retaining agent was found to significantly enhance soybean growth,stimulate root activity,and elevate antioxidant enzyme activity,while concurrently reducing MDA content.The observed effects were found to be dose-dependent,with the greatest effects observed at the highest dose.In comparison to MDS,the yields of soybean in the MDS-L,MDS-M,and MDS-H treatments exhibited a 18.38%,25.58%,and 46.26%increase,respectively.Additionally,the content of protein,fat,linoleic acid,and linolenic acid in seeds demonstrated a notable enhancement.[Conclusions]The application of the water-retaining agent has been demonstrated to significantly promote the growth of soybean plants under conditions of drought stress,resulting in an improvement in both the yield and the quality of the soybean crop.The recommended dosage of the water-retaining agent is 3.3 kg/667 m 2.

基于多Agent的锂电池主动均衡策略控制仿真研究

【目的】针对锂电池的荷电状态均衡管理问题,提出一种基于多智能体的电池组荷电状态一致性均衡方案。【方法】首先,将多智能体控制策略引入电池管理的下垂控制中,实现了主动均衡电路拓扑下的自主均衡;其次,建立领航跟随者模型,利用参数已知的虚拟智能体使各个荷电状态不一致的电池的状态向其靠近,实现充放电模式下的荷电状态均衡;最后,对二阶多智能体荷电状态均衡控制策略进行仿真验证。【结果】实验结果表明,相比一阶均衡控制策略,自主均衡时间减少了43.02%,充电模式中均衡时间减少了16.13%,放电模式中均衡时间降低了32.90%。【结论】多智能体系统在电池的均衡管理中能够实现荷电状态的均衡,有效地降低了锂电池荷电状态到达一致性的收敛时间。

Selection of extractive agent for mixture chlorobenzene and measurement of VLE data for m-dichlorobenzene-p-dichlorobenzene -o-dichlorobenzene -diphenylamine

Extractive agents of extractive distillation separation for mixtures of dichlorobenzene were analyzed and compared, gas-liquid equilibrium data （VLE data） was measured for dichlorobenzene and diphenylamine, the appropriate extractive agent was selected by relatively volatility, the temperature was studied on the effect of extractive separation. VLE data was measured for dichlorobenzene, the parameters were simulated in Wilson equation. The infinite dilute activity coefficient of dichlorobenzene in diphenylamine were measured by chromatogram apparatus, the model parameters were correlated by the single parameter method for dichlorobenzene and diphenyl -amine, VLE data of m-dichlorobenzene-p- dichlorobenzene -o-dichlorobenzene-diphenylamine system was measured and calculated by six part model parameters. The results of correlation and experiment were provided a basis for study of extractive distillation simulation and experiment in this work.

The Synthesis of the Reactive Antibacterial Agents and Their Antibacterial Activities

A series of monochlorotriazine reactive antibacterial agents were synthesised by using 2,4,4’ - trichloro -2’ - hydroxydiphenyl ether as a starting material. The spectrum analyses (UV and MS) and elementary analy-ses were also carried out. These antibacterial agents can be used as the bacteria - resistance finishing agents of the cellulose fabrics. The treated fabrics possess excellent antibacterial activity and durable wash fastness. For ex-ample , the percentages of bacterial reduction of the fab-ric finished with reactive antibacterial agent 2RSDP are 98.5%, 98. 86% and 96.67% for Staphylococcus au-reus, Escherichia coli and Pseudomonas aeruginose re-spectively. After more than 100 times of washing at 60°C, the antibacterial activity still retains at a level of about 90% of the original. The relationships between the molecular structures of the reactive antibacterial finish-ing agents and their antibacterial activities are discussed.

Research on active defense decision-making method for cloud boundary networks based on reinforcement learning of intelligent agent

The cloud boundary network environment is characterized by a passive defense strategy,discrete defense actions,and delayed defense feedback in the face of network attacks,ignoring the influence of the external environment on defense decisions,thus resulting in poor defense effectiveness.Therefore,this paper proposes a cloud boundary network active defense model and decision method based on the reinforcement learning of intelligent agent,designs the network structure of the intelligent agent attack and defense game,and depicts the attack and defense game process of cloud boundary network;constructs the observation space and action space of reinforcement learning of intelligent agent in the non-complete information environment,and portrays the interaction process between intelligent agent and environment;establishes the reward mechanism based on the attack and defense gain,and encourage intelligent agents to learn more effective defense strategies.the designed active defense decision intelligent agent based on deep reinforcement learning can solve the problems of border dynamics,interaction lag,and control dispersion in the defense decision process of cloud boundary networks,and improve the autonomy and continuity of defense decisions.

Prediction Model of Antibacterial Activities for Inorganic Antibacterial Agents Based on Artificial Neural Networks

Quantitatively evaluation of antibacterial activities of inorganic antibacterial agents is an urgent problem to be solved. Using experimental data by an orthogonal design, a prediction model of the relation between conditions of preparing inorganic antibacterial agents and their antibacterial activities has been developed. This is accomplished by introducing BP artificial neural networks in the study of inorganic antibacterial agents. It provides a theoretical support for the development and research on inorganic antibacterial agents. Key words inorganic antibacterial agent - antibacterial activity - neural networks - nanometer material

Multi-Path Routing and Resource Allocation in Active Network

An algorithm of traffic distribution called active multi-path routing (AMR)in active network is proposed. AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths. It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly. The frame of AMR includes adaptive trafficallocation model, the conception of supply bandwidth and its' allocation model, the principle ofcongestion restraint and its' model, and the implement of AMR based on multi-agents system in activenetwork. Through simulations, AMR has distinct effects on network performance. The results show AMRisa valid traffic regulation algorithm.

Egg shell waste as an activation agent for the manufacture of porous carbon

Egg shell waste was used as an activation agent directly for the manufacture of a biomass-derived porous carbon,which possessed a surface area of 626 m2·g-1 and was rich in nitrogen,sulfur and oxygen functionalities.The activation mechanism was proposed,and the carbon showed its potential to act as an adsorbent for the adsorptive removal of various contaminants from both aqueous and non-aqueous solutions,possessing maximum adsorption capacities of 195.9,185.1,125.5 and 44.6 mg·g-1 for sulfamethoxazole,methyl orange,diclofenac sodium and dibenzothiophene,respectively.Through the utilization of egg shell waste as a sustainable activation agent,this work may help to make the widely applied biomass-derived porous carbons more economical and ecological.

The Antimicrobial Activity of Wool Fabrics Treated with Crosslinking Agents and Polyhexamethylene Biguanide

In this study,we used citric acid(CA)as a crosslinking agent,mixed with polyhexamethylene biguanide,to perform a pad-dry-cure treatment on wool fabrics to study its antimicrobial effects and physical properties.

Preparation and application of active gangue＇s carbon black

After three-stage pulverization, dry-distillated activation and coupling agent surface modification, the kaolinite-typed gangue of Sichuan Hongni Coal Mine（SHCM） can be manufactured into activated gangue＇s carbon black. Its surface area is 〉25 m^2/g, and possesses carbon black＇s carbon framework and structure. It can be used as strengthening agent of high polymer material such as rubber.

Effect of microbial agent ARC-BBBE demonstration application on peanut production in the Huang-huai-hai area of China

The microbial agent ARC-BBBE demonstration trials were conducted in four provinces in the main peanutproducing areas of the Huang-huai-hai plain of China.The results revealed that the application of ARC-BBBE led to a 1.09–1.70 fold increase in the number of nodules in the treatment group at the demonstration site compared to the control group.Moreover,the nodule weight in the treatment group was 0.80–3.32 times higher than that of the control group,and nitrogenase activity per plant showed a significant enhancement by 1.00–2.83 fold compared to controls.Additionally,notable improvements were observed in terms of increased fresh weight of whole plants,well-filled pod numbers,and enhanced growth performance;ultimately resulting in a harvest yield increase ranging from 9.46%to 49.04%.The abundance of Aspergillus flavus in rhizosphere soil was determined by the dilution spread plate method,and the inhibition rate was up to 86.7%.The application of ARC-BBBE in the significant peanut-producing areas of Huang-huai-hai has effects of promoting growth,nodulation,and increasing production.At the same time,it has the effect of inhibiting and controlling soil Aspergillus flavus,which provides a new green and low-carbon way to promote the high-quality development of the peanut industry.

Labeling and stability study On^（99m）Tc－tissue plasminogen activator as thrombus and tumor imaging agent

ＬａｂｅｌｉｎｇａｎｄｓｔａｂｉｌｉｔｙｓｔｕｄｙＯｎ￣（９９ｍ）Ｔｃ－ｔｉｓｓｕｅｐｌａｓｍｉｎｏｇｅｎａｃｔｉｖａｔｏｒａｓｔｈｒｏｍｂｕｓａｎｄｔｕｍｏｒｉｍａｇｉｎｇａｇｅｎｔＬｉＷｅｉ－Ｙｉ（李卫一），ＣａｏＧｕｏ－Ｘｉａｎ（曹国宪），Ｙｕ...

基于云环境下Agent的电力信息恶意代码防御研究

面对不同类别的恶意代码,电力信息恶意代码防御方法的能量损耗存在差距,基于此,提出基于云环境多路移动Agent的电力信息恶意代码防御方法,测试该方法下能量损耗最低的恶意代码类别。分割节点数据迁移路线,定义活跃节点与休眠节点的二叉树结构;建立基于云环境多路移动Agent的信息管理模型,计算数据交换单位能量阈值;设计恶意代码低能耗防御算法,设置节点迁移共享认证码。实验结果显示,通过数据结果可知,该方法对恶意软件的防御效果好、能耗低、节点利用率高。

施用不同有益菌剂对长期连作烤烟根际土壤微生态的影响

【目的】探究不同有益菌剂对长期连作烤烟根际土壤微生态环境的影响,为连作土壤改良及连作障碍消减提供参考依据。【方法】采用盆栽试验和高通量测序技术,分析长期连作烤烟后添加有益菌哈茨木霉菌剂T-22(T1处理)、枯草芽孢杆菌剂(T2处理)、哈茨木霉菌剂T-22+枯草芽孢杆菌剂(T3处理)的烤烟根际土壤理化性质、酶活性及微生物群落结构和功能。【结果】相较于不施有益菌(对照,CK),施用有益菌剂可提高长期连作烤烟根际土壤的速效养分含量和酶活性,其中,在10个环境因子中,速效磷(AP)含量对烤烟根际土壤细菌群落分布的贡献度(4.97%)最高,碱解氮(AN)含量对烤烟根际土壤真菌群落分布的贡献度(6.91%)最高,蔗糖酶(SC)活性对烤烟根际土壤真菌群落分布的贡献度(6.75%)次之;施用有益菌剂可提高长期连作烤烟根际土壤微生物群落丰度、多样性指数和细菌特有OTUs数;施用有益菌剂可改变长期连作烤烟根际土壤的指示物种丰度,其中,细菌假单胞菌属(Pseudomonas)为T1处理的指示物种,鞘氨醇单胞菌属(Sphingomonas)和被孢霉属(Mortierella)为T1处理的优势菌属,丰度分别为12.2%和25.0%,Minimedusa属为T3处理的指示物种。单施细菌有益菌剂可降低长期连作烤烟根际土壤细菌群落主要代谢途径的丰度,单施真菌有益菌剂则相反;单施真菌、细菌与真菌有益菌剂混施可提高烤烟根际土壤真菌代谢途径的丰度。【结论】施用有益菌剂对长期连作烤烟根际土壤微生态环境具有一定的改良效应,其中,哈茨木霉T-22的施用效果较好,可用于烤烟连作障碍防控。

复合木霉制剂防治黄连根腐病及其机理研究

为评价复合木霉制剂对黄连根腐病的防治效果,并揭示其防病机理,为黄连根腐病专用微生物农药的研发奠定基础,本试验将深绿木霉Trichoderma atroviride、长枝木霉T.longibrachiatum、钩状木霉T.hamatum、拟康宁木霉T.koningiopsis等4种木霉配制的复合制剂和尖镰孢Fusarium oxysporum以不同的方式分别施用于黄连,统计根腐病发生情况,检测黄连根部防御酶活性,用高通量测序分析根际土壤真菌群落结构。结果表明,复合木霉制剂对尖镰孢导致的根腐病具有明显预防效果;复合木霉制剂和尖镰孢分别接种黄连可提高SOD、POD、CAT、PAL、PPO等防御性酶活性,产生诱导抗性;而它们先后接种黄连可产生强化效应,从另一个途径提高植株抗病性。复合木霉制剂和尖镰孢都会降低真菌的数量、多样性,和某些真菌的相对丰度,而复合木霉制剂的抑菌作用更强烈,尤其能明显抑制尖镰孢、Ilyonectria sp.等病原真菌的生长,且能改善土壤真菌群落结构。木霉和尖镰孢都能在土壤中较长期定殖。可见,复合木霉制剂可以预防尖镰孢导致的黄连根腐病,防病机理包括诱导黄连植株产生抗性,接种后再遭受病原菌侵染产生的强化效应,优化土壤真菌群落结构,抑制土壤中病原菌等,且有效期较长。因此复合木霉制剂具有开发为微生物农药防治黄连根腐病的潜力。