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作者：李建勋(s.c. lee)

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近代开关理论及数字设计

近代开关理论及数字设计

加速溶剂萃取-气相色谱质谱法测定太子参中酰胺类除草剂的含量

作者： s.c.·李建勋(s.c. lee)

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分析化学 2007年第2期35卷 206-210页

作者：徐晓琴李庆玲袁济端王树贵王文慎黎先春王小如厦门大学化学化工学院化学系现代分析科学教育部重点实验室国家海洋局第一海洋研究所青岛现代分析技术及中药标准化重点实验室 3. 福建柘荣县农业技术推广中心 4. 厦门倍尔思生化科技有限公司

建立了太子参中乙草胺、丁草胺和s-异丙甲草胺的加速溶剂萃取-气相色谱/质谱测定的分析方法。对提取溶剂、萃取温度、净化材料、不同冲洗体积和静态萃取时间、循环次数等实验条件进行了优化。用HP-5Ms弹性石英毛细管柱经柱程序升温技术... 详细信息

建立了太子参中乙草胺、丁草胺和s-异丙甲草胺的加速溶剂萃取-气相色谱/质谱测定的分析方法。对提取溶剂、萃取温度、净化材料、不同冲洗体积和静态萃取时间、循环次数等实验条件进行了优化。用HP-5Ms弹性石英毛细管柱经柱程序升温技术分离,并用质谱检测器检测,内标法计算含量。本方法测定太子参中乙草胺、丁草胺和s-异丙甲草胺的检出限分别为0.16 ng/g、0.18 ng/g和0.05 ng/g,精密度分别为2.6%、3.9%和3.1%,回收率为80.2%-104.1%。所测样品不含上述3种除草剂残留。本方法简便、干扰小、检测效果好,可用于太子参药材中此类除草剂残留的分析。

关键词：太子参乙草胺丁草胺 s-异丙甲草胺加速溶剂萃取气相色谱质谱

Effect of Excited and Fourth Generation Leptons in Lepton Flavor Violating μ− → e- 2γ Decay

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chinese Phys.c. Letters 2011年第8期28卷 51-53页

作者： s.c.İnan Department of Phys.c. Cumhuriyet UniversitySivas 58140Turkey

We study the lepton flavor violatingμ−→e-2γdecay induced by the mediation of heavy leptons,s.c. as the excited and fourth generation *** of these leptons inμ−→e-2γdecay are *** is found that the branching ratio of this decay is very sensitive to excited and fourth generation ***,we obtain the bounds on model parameters by using the current experimental limit of this decay.

关键词： decay excited branching

Direct Graviton Production via Photon-Photon Fusion at the cERN-LHc

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chinese Phys.c. Letters 2012年第3期29卷 63-66页

作者： s.c.İnan Department of Phys.c. Cumhuriyet University58140SivasTurkey

The potential of pp→pγγp/→pGp process in scenarios of the Arkani-Hamed,Dimopoulos,Dvali(ADD)and Randall-sundrum(Rs)model at the LHc is examined,and 95%*** on the model parameters are *** is found that the sensitiv... 详细信息

关键词： reaction bounds LHc

Machine learning empowers efficient design of ternary organic solar cells with PM6 donor

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Journal of Energy chemistry 2025年第1期100卷 337-347页

作者： Kiran A.Nirmal Tukaram D.Dongale santosh s.sutar Atul c.Khot Tae Geun Kim school of Electrical Engineering Korea University computational Electronics and Nanoscience Research Laboratory School of Nanoscience and Biotechnology Shivaji University Yashwantrao chavan school of Rural Development Shivaji University

Organic solar cells(Oscs) hold great potential as a photovoltaic technology for practical ***, the traditional experimental trial-and-error method for designing and engineering Oscs.c.n be complex, expensive, and time-consuming. Machine learning(ML) techniques enable the proficient extraction of information from datasets, allowing the development of realistic models that are capable of predicting the efficacy of materials with commendable accuracy. The PM6 donor has great potential for high-performance Oscs. However, it is.c.ucial for the rational design of a ternary blend to accurately forecast the power conversion efficiency(PcE) of ternary Oscs(TOscs) based on a PM6 ***, we collected the device parameters of PM6-based TOscs and evaluated the feature importance of their molecule descriptors to develop predictive models. In this study, we used five different ML algorithms for analysis and prediction. For the analysis, the classification and regression tree provided different rules, heuristics, and patterns from the heterogeneous dataset. The random forest algorithm outperforms other prediction ML algorithms in predicting the output performance of PM6-based TOscs. Finally, we validated the ML outcomes by fabricating PM6-based TOscs. Our study presents a rapid strategy for assessing a high PcE while elucidating the substantial influence of diverse descriptors.

关键词： Random forests

A selective view of stochastic inference and mod-eling problems in nanoscale biophys.c.

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science china Mathematics 2009年第6期52卷 1181-1211页

作者： KOU s.c. Department of statistics Harvard UniversityCambridgeMA 02138USA

Advances in nanotechnology enable scientists for the first time to study biological pro-cesses on a nanoscale molecule-by-molecule *** also raise challenges and opportunities for statisticians and applied *** exemplify the stochastic inference and modeling problems in the field,this paper discusses a few selected cases,ranging from likelihood inference,Bayesian data augmentation,and semi-and non-parametric inference of nanometric biochemical systems to the uti-lization of stochastic integro-differential equations and stochastic networks to model single-molecule biophys.c.l *** discuss the statistical and probabilistic issues as well as the biophys.c.l motivation and phys.c.l meaning behind the problems,emphasizing the analysis and modeling of real experimental data.

关键词： likelihood analysis Bayesian data augmentation semi-and non-parametric inference single-molecule experiment subdiffusion generalized Langevin equation fractional Brownian motion stochastic network enzymatic reaction

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Traditional Ecological Knowledge and community-based Natural Resource Management in Northeast India

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Journal of Mountain science 2007年第3期4卷 248-258页

作者： s.c. Rai Department of Geography Delhi School of EconomicUniversity of Delhi

community-based natural resource management in northeast India has a long history. Indigenous knowledge and adaptation are the collective information, with improvement from generation to generation. The expectation is that under community control, local expertise on biodiversity will play a significant role in natural resource management through traditional practices. This paper discusses the characteristics and application of the traditional ecological knowledge of aboriginal peoples in northeast India and its role in natural resource management. Examples are provided in two different eco-cultural landscapes, i.e., Demazong (the Buddhist eco-cultural landscape in sikkim Himalaya) and the Apatani eco-cultural landscape in Arunachal Pradesh, which illustrate the utility value of traditional ecological knowledge in sustainable natural resource management. Both eco-cultural landscapes are indeed very complex and highly evolved systems with high levels of economic and ecological efficiencies. The paper concludes that traditional ecological knowledge systems and institutions.c.uld serve as entry points into the sustainable utilization and management of natural resources. This.c.uld be achieved through the exploration of the cultural practices of the local people and integrating useful aspects into the modern natural resource management expertise. With rapidly depleting biodiversity in the developing tropic regions, there is a greater utilization today than ever before of the value of respecting the "s.c.ed" as a tool towards better conservation of natural resources.

关键词： Traditional ecological knowledge resource management cultural landscape sustainable development northeast India

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A survey on dependability improvement techniques for pervasive computing systems

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science china(Information sciences) 2015年第5期58卷 19-32页

作者： YANG WenHua LIU YePang XU chang cHEUNG s.c. state Key Laboratory for Novel software Technology Nanjing University Department of computer science and Technology Nanjing University Department of computer science and Engineering The Hong Kong University of Science and Technology

The goal of this survey is to summarize the state-of-the-art research results and identify research challenges of developing and deploying dependable pervasive computing systems. We discuss the factors that affect the system dependability and the studies.c.nducted to improve it with respect to these factors. These studies were categorized according to their similarities and differences in hope of shedding some insight into future research. There are three categories: context management, fault detection, and uncertainty *** three categories of work address the three most difficult problems of pervasive computing systems. First,pervasive computing systems’ perceived environments, which are also called their contexts, can vary intensively,and thus have a great impact on the systems’ dependability. s.c.nd, it is.c.allenging to guarantee the correctness of the systems’ internal computations integrated with interactions with external environments for *** detection is then an important issue for improving dependability for these systems. Last but not least importantly, pervasive computing systems interact with their environments frequently. These interactions.c.n be affected by many uncertainties, which can jeopardize the systems’ dependability. After a discussion of these pieces of work, we present an outlook for its future research directions.

关键词： pervasive computing system dependability context fault detection uncertainty