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其真商群为满足极大条件的FC_c-群的群 被引量:1
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作者 张志让 邢世奇 《西南师范大学学报(自然科学版)》 CAS CSCD 北大核心 2012年第12期6-9,共4页
如果FCc-群满足极大条件,那么称之为(FCc)max-群;如果群G的所有真商群都是(FCc)max-群,但是G本身不是(FCc)max-群,那么称群G为外(FCc)max-群.主要利用外FNc-群的结果,给出外(FCc)max-群的结构描述,同时还推广了群的上下中心列的有限性条件.
关键词 (fcc)max- 外FNc- 外(fcc)max- 外有限模
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用于FCC汽油辛烷值预测的非线性数学模型 被引量:11
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作者 孙忠超 山红红 +2 位作者 刘熠斌 杨朝合 李春义 《炼油技术与工程》 CAS 2012年第2期60-64,共5页
依据汽油正构烷烃、异构烷烃、烯烃、环烷烃和芳烃(PIONA)的烃组成数据,将催化裂化(FCC)汽油单体烃组成分为37组,利用BP神经网络算法和支持向量机回归(SVR)分别建立了FCC汽油研究法辛烷值对37个变量的非线性数学模型。由MATLAB软件编写... 依据汽油正构烷烃、异构烷烃、烯烃、环烷烃和芳烃(PIONA)的烃组成数据,将催化裂化(FCC)汽油单体烃组成分为37组,利用BP神经网络算法和支持向量机回归(SVR)分别建立了FCC汽油研究法辛烷值对37个变量的非线性数学模型。由MATLAB软件编写程序,利用Levenberg-Marquardt优化算法训练BP神经网络。支持向量机回归模型采用粒子群算法优化支持向量机参数及核函数参数,并采取交叉验证方法防止机器学习的欠学习和过拟合问题。计算结果表明:两种模型都能够较好地反映汽油单体烃组成与辛烷值之间的非线性关系;BP神经网络模型对辛烷值的预测性能好于支持向量机回归模型;增加样本数量,两种方法的预测准确性皆变好;针对40个样本的学习结果,两种模型预测的相对误差绝对值的平均值分别为0.148 7和0.167 4。 展开更多
关键词 fcc汽油 研究法辛烷值 BP神经网络 支持向量机 粒子算法
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Catalytic Cracking and PSO-RBF Neural Network Model of FCC Cycle Oil 被引量:3
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作者 Liu Yibin Tu Yongshan +1 位作者 Li Chunyi Yang Chaohe 《China Petroleum Processing & Petrochemical Technology》 SCIE CAS 2013年第4期63-69,共7页
Catalytic cracking experiments of FCC cycle oil were carried out in a fixed fluidized bed reactor. Effects of reac- tion conditions, such as temperature, catalyst to oil ratio and weight hourly space velocity, were in... Catalytic cracking experiments of FCC cycle oil were carried out in a fixed fluidized bed reactor. Effects of reac- tion conditions, such as temperature, catalyst to oil ratio and weight hourly space velocity, were investigated. Hydrocarbon composition of gasoline was analyzed by gas chromatograph. Experimental results showed that conversion of cycle oil was low on account of its poor crackability performance, and the effect of reaction conditions on gasoline yield was obvi- ous. The paraffin content was very high in gasoline. Based on the experimental yields under different reaction conditions, a model for prediction of gasoline and diesel yields was established by radial basis function neural network (RBFNN). In the model, the product yield was viewed as function of reaction conditions. Particle swarm optimization (PSO) algorithm with global search capability was used to obtain optimal conditions for a highest yield of light oil. The results showed that the yield of gasoline and diesel predicted by RBF neural network agreed well with the experimental values. The optimized reac- tion conditions were obtained at a reaction temperature of around 520 ~C, a catalyst to oil ratio of 7.4 and a space velocity of 8 h~. The predicted total yield of gasoline and diesel reached 42.2% under optimized conditions. 展开更多
关键词 catalytic cracking cycle oil radical basis function neural network particle swarm optimization
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Porcine FcεRI Mediates Porcine Reproductive and Respiratory Syndrome Virus Multiplication and Regulates the Inflammatory Reaction 被引量:4
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作者 Peidian Shi Lilin Zhang +6 位作者 Jiashun Wang Dong Lu Yi Li Jie Ren Menglu Shen Lei Zhang Jinhai Huang 《Virologica Sinica》 SCIE CAS CSCD 2018年第3期249-260,共12页
Porcine reproductive and respiratory syndrome virus(PRRSV) shows characteristic antibody-dependent enhancement(ADE) of infection and causes porcine systemic inflammation, which is similar to a type I allergic reaction... Porcine reproductive and respiratory syndrome virus(PRRSV) shows characteristic antibody-dependent enhancement(ADE) of infection and causes porcine systemic inflammation, which is similar to a type I allergic reaction; however, the role of porcine FceεRI in ADE is still unclear. In this study, the expression of different Fc receptors(Fc Rs) on macrophages was investigated in a PRRSV 3D4/21 cell infection model in the presence or absence of PRRSV antibody. The transcription level of Fcc II and FceεRI was significantly up-regulated under PRRSV-antibody complex infection. Internalization and proliferation of PRRSV were promoted by the ADE mechanism when FceεRI was expressed in permissive 3D4/21 cells and the non-permissive cell line HEK 293T. Transcriptome sequencing data showed that the expression levels of AKT,ERK and other signal molecules in the anti-inflammatory pathway were significantly increased, especially in the cells infected with the PRRSV-antibody immune complex. Inflammatory regulatory molecules such as PLA2G6, LOX, TRPM8 and TRPM4 were significantly up-regulated following PRRSV infection but significantly down-regulated in the cells infected with the PRRSV-antibody immune complex. Our results demonstrated that FceεRI could be involved in PRRSV ADE, the antigen presenting process and regulation of the inflammatory response during PRRSV infection, which provides new insights into PRRSV infection mediated by FceεRI and the PRRSV-antibody immune complex. 展开更多
关键词 Porcine reproductive and respiratory syndrome virus (PRRSV) FcεRI - Antibody-dependent enhancement(ADE) Inflammatory response
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