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Antibacterial Activities of Three Kinds of Plant Extracts against Ralstonia solanacearum of Cherry Tomato

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Plant Diseases and Pests 2016年第2期7卷 15-17页

作者： Chen Yinhua cao pengfei Lishui Institute of Agricultural Science Lishui 323000 China

Bacterial wilt has become an important obstacle restricting high quality and high yield of cherry tomato. In this paper, the antibacterial activities of ex- tracts from Allium sativum, Ginkgo biloba and Lygodium japonicum against Ralstonia solanacearum were compared. The results indicated that with the increasing concentrations of three extracts, the antibacterial effect enhanced gradually. The lowest concentrations of three extracts with the inhibitory effects significantly higher than that of pesticide control were 20% A. sativum extract, 40% G. biloba extract and 60% L japonicum extract, and the antibacterial effect of 20% A. sativum extract was significantly higher than those of other two plant extracts. The inhibition zone diameters of R. solanacearum strains B2. 1.2.2, I1.2. 1.1, KS. 1.1.1 and 1.***.3.1.2 were 9.23, 8.30, 8.12 and 9.19 mm, respectively. The antibacterial effects of three plant extracts reached the maximums when the concentration was 100%, but A. sativum extract had the strongest antibacterial effect against test strains. Therefore, A. sativum can be used as the main raw material for development of plant protectant for cherry tomato.

关键词： Cherry tomato Ralstonia solanacearum Antibacterial activity

AO工艺高效处理N,N-二甲基甲酰胺废水的研究

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兰州交通大学学报 2024年第4期43卷 134-144页

作者：曹鹏飞任学昌陈作雁冯浩杨镇瑜安菊范新露兰州交通大学环境与市政工程学院兰州730070 甘肃省自然能源研究所兰州730046

利用微生物高效降解N,N-二甲基甲酰胺(DMF)的研究是一项极具挑战的课题。通过缺氧驯化(HA)筛选并获得高效降解DMF的菌群是研究DMF废水生化降解的关键。微生物群落扩增子测序(16S rDNA)结果表明,驯化出的缺氧菌群中Proteobacteria、Firmi... 详细信息

利用微生物高效降解N,N-二甲基甲酰胺(DMF)的研究是一项极具挑战的课题。通过缺氧驯化(HA)筛选并获得高效降解DMF的菌群是研究DMF废水生化降解的关键。微生物群落扩增子测序(16S rDNA)结果表明,驯化出的缺氧菌群中Proteobacteria、Firmicutes和Euryarchaeota为降解DMF的优势菌门,其中Zavarzinia、Petrimonas、Acholeplasma、Brevundimonas、Arenimonas和Bosea在缺氧条件下可以有效降解DMF,且DMF降解菌的相对丰度与DMF降解效率具有明显相关性。当HA污泥中DMF降解菌的相对丰度达到86.37%时,HA污泥对210 mg·L^(-1)的DMF去除效率达到99.98%。DMF降解菌降解DMF的产物为二甲胺(DMA)和甲胺(MMA)。DMF降解菌的相对丰度低于40.25%时,HA污泥对DMF的去除效率仅为57.22%,DMA对DMF降解菌表现出明显的抑制作用。实验采用缺氧/好氧联合(AO)工艺进一步提高了出水水质,好氧污泥(AS)出水中DMA和MMA的浓度均小于0.5 mg·L^(-1),且AS反应器出水中化学需氧量(COD)≤40.6 mg·L^(-1),该水质满足GB 21902-2008《合成革与人造革工业污染物排放标准》中对现有企业污染物排放的要求。

关键词： N,N-二甲基甲酰胺生物降解物种差异代谢途径

滑膜间充质干细胞联合富血小板血浆在软骨损伤修复中的研究

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中国医学装备 2024年第3期21卷 148-153,158页

作者：徐训安徐同光曹鹏飞黄永丰王强何毅刘勇苏州高新区人民医院骨科苏州215010

目的:对比滑膜间充质干细胞(SMSCs)、富血小板血浆(PRP)及两者联合的膝关节腔注射3种治疗方式对于兔软骨损伤的修复效果。方法:选取新西兰大耳兔24只,采用手术在兔膝关节中建造软骨损伤模型,采用随机数表法将软骨损伤模型分为空白组、单... 详细信息

目的:对比滑膜间充质干细胞(SMSCs)、富血小板血浆(PRP)及两者联合的膝关节腔注射3种治疗方式对于兔软骨损伤的修复效果。方法:选取新西兰大耳兔24只,采用手术在兔膝关节中建造软骨损伤模型,采用随机数表法将软骨损伤模型分为空白组、单独SMSCs关节腔注射组(SMSCs组)、单独PRP关节腔注射组(PRP组)和SMSCs联合PRP关节腔注射组(SMSCs+PRP组)4组,每组6只。剔取4组兔关节滑膜进行SMSCs的体外培养,并进行SMSCs的形态学观察及鉴定。抽取兔静脉血,离心制备PRP,对比PRP与全血中血小板及生长因子的含量。将SMSCs和PRP注射入已造模的3组兔膝关节腔中,于注射治疗2、4和6周后根据国际软骨修复协会(ICRS)软骨修复评分对各组的软骨缺损区的修复情况进行评价。结果:兔膝关节滑膜的原代滑膜细胞分离初为圆形,传代后均为梭形。4组的SMSCs表面抗原CD73、CD90和CD105检测阳性率分别为100%、99.22%和99.99%,CD45检测0.5%,具备干细胞的性质。4组的血小板计数显示PRP中血小板浓度约为全血的6倍。PRP中血小板源性生长因子(PDGF)、转化生长因子-β(TGF-β)和血管内皮生长因子(VEGF)的浓度水平分别为(569.15±57.48)ng/ml、(633.56±63.90)ng/ml和(1243.55±106.04)ng/ml,约为全血中的5倍、6倍、7倍。关节腔注射治疗后2周时,4组的软骨修复评分差异均无统计学意义(P>0.05);注射治疗4周、6周后,SMSCs+PRP组软骨修复宏观形态学及组织学评分较空白组显著提高,差异均有统计学意义(t4周=6.35、9.15,t6周=8.16、8.60,P<0.05);结论:SMSCs联合PRP对于兔软骨损伤的修复效果明显优于单独进行PRP和单独SMSCs的治疗,且均优于未进行治疗情况,SMSCs联合PRP能够显著提高软骨损伤自我修复的效果。

关键词：富血小板血浆(PRP) 滑膜间充质干细胞(SMSCs) 软骨损伤修复

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ANGPTL4的作用及机制

生命的化学 2024年第5期44卷 890-899页

作者：郑执一曹鹏飞陈文奇王锐乔建龙邵花香李华玲扬州大学医学院扬州225000

血管生成素样蛋白4(angiopoietin-like 4,ANGPTL4)是血管生成素家族的一员。作为多功能分泌蛋白,ANGPTL4能抑制脂蛋白脂肪酶的活性,在脂质代谢中发挥重要生理作用。ANGPTL4在血管生成、糖脂能量代谢、肿瘤发生发展及代谢性疾病中起调节... 详细信息

血管生成素样蛋白4(angiopoietin-like 4,ANGPTL4)是血管生成素家族的一员。作为多功能分泌蛋白,ANGPTL4能抑制脂蛋白脂肪酶的活性,在脂质代谢中发挥重要生理作用。ANGPTL4在血管生成、糖脂能量代谢、肿瘤发生发展及代谢性疾病中起调节作用,提示ANGPTL4有望成为相关疾病的潜在治疗靶点。本文就ANGPTL4在动脉粥样硬化、糖脂代谢、肿瘤发生发展、血管生成、抗炎作用以及神经退行性疾病中的基本作用作一综述,旨在为ANGPTL4的系统研究提供理论参考依据。

关键词： ANGPTL4 糖脂代谢神经退行性疾病肿瘤炎症

AI for science: Predicting infectious diseases

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Journal of Safety Science and Resilience 2024年第2期5卷 130-146页

作者： Alexis pengfei Zhao Shuangqi Li Zhidong cao Paul Jen-Hwa Hu Jiaojiao Wang Yue Xiang Da Xie Xi Lu Institute of Automation Chinese Academy of SciencesUniversity of Chinese Academy of SciencesBejing 100090China Systems Engineering Cornll UniversityIthacaNY 14853USA David Eccles School of Business the University of UtahUtahUSA Collge of Electrical Engineering Sichuan UniversityChina Department of Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China School of Electrical Engineering Southeast UniversityNanjing 210096China

The global health landscape has been persistently challenged by the emergence and re-emergence of infectious *** epidemiological models,rooted in the early 2oth century,have provided foundational in-sights into disease ***,the intricate web of modern global interactions and the exponential growth of available data demand more advanced predictive *** is where AI for Science(AI4S)comes into play,offering a transformative approach by integrating artificial intelligence(Al)into infectious disease *** paper elucidates the pivotal role of AI4s in enhancing and,in some instances,superseding tradi-tional epidemiological *** harnessing AI's capabilities,AI4S facilitates real-time monitoring,sophisticated data integration,and predictive modeling with enhanced *** comparative analysis highlights the stark contrast between conventional models and the innovative strategies enabled by *** essence,Al4S represents a paradigm shift in infectious disease *** addresses the limitations of traditional models and paves the way for a more proactive and informed response to future *** we navigate the complexities of global health challenges,Al4S stands as a beacon,signifying the next phase of evolution in disease prediction,characterized by increased accuracy,adaptability,and efficiency.

关键词： AI for science(AI4S) Data integration Global healthchallenges Infectious disease prediction Predictive modeling Real-timemonitoring

基于太钢粉煤灰-矿粉-脱硫石膏制备固废聚合物材料的技术研究

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山西冶金 2024年第6期47卷 42-44页

作者：曹鹏飞胡荣建杨朝刚龚运林任建伟张美霞张慧月宝武环科山西资源循环利用有限公司山西太原030003

以粉煤灰、矿粉和脱硫石膏作为碱性固废制备新型低碳绿色废聚合材料,并围绕废聚合材料水化过程中3种固废间复合协同效应、性能变化与微结构演变的关系展开研究,通过不同的矿粉、粉煤灰、脱硫石膏添加量对制品性能的影响,得到最优配比,... 详细信息

以粉煤灰、矿粉和脱硫石膏作为碱性固废制备新型低碳绿色废聚合材料,并围绕废聚合材料水化过程中3种固废间复合协同效应、性能变化与微结构演变的关系展开研究,通过不同的矿粉、粉煤灰、脱硫石膏添加量对制品性能的影响,得到最优配比,最后应用到实际生产上,为企业实现降本增效的目的。

关键词：粉煤灰矿粉聚合材料工艺配比

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化工过程软测量建模方法研究进展

化工学报 2013年第3期64卷 788-800页

作者：曹鹏飞罗雄麟中国石油大学自动化研究所北京102249

软测量仪表是解决化工过程中质量变量难以实时测量的重要手段。软测量仪表的核心问题是软测量建模。阐述了软测量建模与辨识和非线性建模的关系:质量变量和易测变量的动态关系存在于增量之间,辨识模型依赖于增量数据,软测量建模则是依... 详细信息

软测量仪表是解决化工过程中质量变量难以实时测量的重要手段。软测量仪表的核心问题是软测量建模。阐述了软测量建模与辨识和非线性建模的关系:质量变量和易测变量的动态关系存在于增量之间,辨识模型依赖于增量数据,软测量建模则是依赖于实测变量数据来获取这个动态关系;非线性建模建立了变量间的静态关系,忽略了对象动态特性,而软测量建模要兼顾对动态特性的表征。随着人们对过程特性的认识加深,软测量建模方法不断发展,经历了从机理建模到数据驱动建模,从线性建模到非线性建模,从静态建模到动态建模的过程。详细讨论了软测量建模的发展过程,众多建模方法的优缺点及适用情况和现在建模的热点,最后对软测量建模方法进行了总体展望。

关键词：软测量建模辨识非线性建模数据驱动建模非线性动态建模

Soft Sensor Model Derived from Wiener Model Structure: Modeling and Identification

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Chinese Journal of Chemical Engineering 2014年第5期22卷 538-548页

作者：曹鹏飞罗雄麟 Research Institute of Automation China University of Petroleum

The processes of building dynamic and static relationships between secondary and primary variables are usually integrated in most of nonlinear dynamic soft sensor models. However, such integration limits the estimation accuracy of soft sensor models. Wiener model effectively describes dynamic and static characteristics of a system with the structure of dynamic and static submodels in cascade. We propose a soft sensor model derived from Wiener model structure, which is an extension of Wiener model. Dynamic and static relationships between secondary and primary variables are built respectively to describe the dynamic and static characteristics of system. The feasibility of this model is verified. Then the expression of discrete model is derived for soft sensor system. Conjugate gradient algorithm is applied to identify the dynamic and static model parameters alternately. Corresponding update method for soft sensor system is also given. Case studies confirm the effectiveness of the proposed model, alternate identification algorithm, and update method.

关键词： soft sensor Wiener model modeling alternate identification

A social computing method for energy safety

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Journal of Safety Science and Resilience 2024年第1期5卷 64-82页

作者： pengfei Zhao Shuangqi Li Zhidong cao Paul Jen-Hwa Hu Daniel Dajun Zeng Da Xie Yichen Shen Jiangfeng Li Tianyi Luo Institute of Automation Chinese Academy of SciencesUniversity of Chinese Academy of SciencesBeijing 100090China Systems Engineering Cornell UniversityIthacaNY 14853USA David Eccles School of Business the University of UtahUtahUSA Department of Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China China University of Mining and Technology China

Information and communication technologies enable the transformation of traditional energy systems into cyber-physical energy systems(CPESs),but such systems have also become popular targets of ***,available methods for evaluating the impacts of cyberattacks suffer from limited resilience,efficacy,and practical *** mitigate their potentially disastrous consequences,this study suggests a two-stage,discrepancy-based optimization approach that considers both preparatory actions and response measures,integrating concepts from social *** proposed Kullback-Leibler divergence-based,distributionally robust optimization(KDR)method has a hierarchical,two-stage objective function that incorporates the operating costs of both system infrastructures(e.g.,energy resources,reserve capacity)and real-time response measures(e.g.,load shedding,demand-side management,electric vehicle charging station management).By incorporating social computing principles,the optimization framework can also capture the social behavior and interactions of energy consumers in response to *** preparatory stage entails day-ahead operational decisions,leveraging insights from social computing to model and predict the behaviors of individuals and communities affected by potential *** mitigation stage generates responses designed to contain the consequences of the attack by directing and optimizing energy use from the demand side,taking into account the social context and preferences of energy consumers,to ensure resilient,economically efficient CPES *** method can determine optimal schemes in both stages,accounting for the social dimensions of the *** original disaster mitigation model uses an abstract formulation to develop a risk-neutral model that characterizes cyberattacks through KDR,incorporating social computing techniques to enhance the understanding and response to cyber *** approach can mitigate the impacts more

关键词： Cyberattacks Cyber-physical energy systems Distributionally robust optimization False data injections Two-stage modeling Social computing