In this article,an efficient,simple and environmentally friendly approach to the synthesis of diacetals(diketals) pentaerythritol using SOH-functionalized ionic liquids(ILs) as catalysts was reported.The ILs show high...In this article,an efficient,simple and environmentally friendly approach to the synthesis of diacetals(diketals) pentaerythritol using SOH-functionalized ionic liquids(ILs) as catalysts was reported.The ILs show high catalytic activity and reusability with good to excellent yields of the desired products.Hammett method has been used to determine the acidity order of these ionic liquids and the results are consistent with the catalytic activities observed in acetalization reaction.Maximum product yield of 93%was observed on using[PSPy][OTf]as catalyst and it can be reused at least 8 times without obvious activity loss.展开更多
In this article, series of novel bi-SOaH-functionalized ILs were synthesized using simple, efficient and economic procedure. Hammer method had been used to determine the acidity order of these ionic liquids, and the a...In this article, series of novel bi-SOaH-functionalized ILs were synthesized using simple, efficient and economic procedure. Hammer method had been used to determine the acidity order of these ionic liquids, and the acidifies of bi-SOaH-functionalized ILs were stronger than that of traditional single-SOaH-functionalized ILs. Their catalytic activities in the synthesis of N-（3-phenyl）-3- oxo-1-（phenylpropyl）acetamide were investigated and they were consistent with their acidities.展开更多
The object of this article is to study and develop the generalized fractional calcu- lus operators given by Saigo and Maeda in 1996. We establish generalized fractional calculus formulas involving the product of R-fun...The object of this article is to study and develop the generalized fractional calcu- lus operators given by Saigo and Maeda in 1996. We establish generalized fractional calculus formulas involving the product of R-function, Appell function F3 and a general class of poly- nomials. The results obtained provide unification and extension of the results given by Saxena et al. [13], Srivastava and Grag [17], Srivastava et al. [20], and etc. The results are obtained in compact form and are useful in preparing some tables of operators of fractional calculus. On account of the general nature of the Saigo-Maeda operators, R-function, and a general class of polynomials a large number of new and known results involving Saigo fractional calculus operators and several special functions notably H-function, /-function, Mittag-Leffier function, generalized Wright hypergeometric function, generalized Bessel-Maitland function follow as special cases of our main findings.展开更多
为了解决牛只多尺度、多目标、多部位状态信息的快速准确识别问题,笔者提出一种基于实时多目标注意力模型的牛只多部位快速自动化检测方法,采用多尺度注意力网络MSEAY,在网络中加入了SE(squeeze and excitation networks)注意力机制、H-...为了解决牛只多尺度、多目标、多部位状态信息的快速准确识别问题,笔者提出一种基于实时多目标注意力模型的牛只多部位快速自动化检测方法,采用多尺度注意力网络MSEAY,在网络中加入了SE(squeeze and excitation networks)注意力机制、H-swish激活函数及SIoU损失函数,消除现有牛群图像检测中光照、重叠、多类型等对图像检测结果产生的影响,先对牛只图像进行标注及预处理,然后采用MoibleNetv3模型作为Backbone进行牛只的部位划分识别,进而实现了多尺度、多部位牛只状态信息的精准分类与识别。结果表明:在选用含肉牛样本集合的前提下,各部位平均分类结果的精确率为96.6%,召回率为94.7%,F1值为94.1%,mAP@50值为97.4%;在仅选用种牛样本集合的前提下,各部位检测精确率为头部96.4%,躯干97.2%,腿部97.3%,平均值97.0%。本算法在保证检测实时性的同时提高了多尺度、多牛只的检测精度,验证了方法的鲁棒性与可泛化性,可用于多尺度、多目标、多部位状态信息的快速准确识别。展开更多
基金supported by National 863 High-Tech Research and Development Program of China(No. 2007AA05Z101)
文摘In this article,an efficient,simple and environmentally friendly approach to the synthesis of diacetals(diketals) pentaerythritol using SOH-functionalized ionic liquids(ILs) as catalysts was reported.The ILs show high catalytic activity and reusability with good to excellent yields of the desired products.Hammett method has been used to determine the acidity order of these ionic liquids and the results are consistent with the catalytic activities observed in acetalization reaction.Maximum product yield of 93%was observed on using[PSPy][OTf]as catalyst and it can be reused at least 8 times without obvious activity loss.
基金the National Natural Science Foundation ofChina(Nos.21003049,21073064)the Fundamental Research Funds for the Central Universities for financial support
文摘In this article, series of novel bi-SOaH-functionalized ILs were synthesized using simple, efficient and economic procedure. Hammer method had been used to determine the acidity order of these ionic liquids, and the acidifies of bi-SOaH-functionalized ILs were stronger than that of traditional single-SOaH-functionalized ILs. Their catalytic activities in the synthesis of N-（3-phenyl）-3- oxo-1-（phenylpropyl）acetamide were investigated and they were consistent with their acidities.
基金NBHM Department of Atomic Energy,Government of India,Mumbai for the finanicai assistance under PDF sanction no.2/40(37)/2014/R&D-II/14131
文摘The object of this article is to study and develop the generalized fractional calcu- lus operators given by Saigo and Maeda in 1996. We establish generalized fractional calculus formulas involving the product of R-function, Appell function F3 and a general class of poly- nomials. The results obtained provide unification and extension of the results given by Saxena et al. [13], Srivastava and Grag [17], Srivastava et al. [20], and etc. The results are obtained in compact form and are useful in preparing some tables of operators of fractional calculus. On account of the general nature of the Saigo-Maeda operators, R-function, and a general class of polynomials a large number of new and known results involving Saigo fractional calculus operators and several special functions notably H-function, /-function, Mittag-Leffier function, generalized Wright hypergeometric function, generalized Bessel-Maitland function follow as special cases of our main findings.
文摘为了解决牛只多尺度、多目标、多部位状态信息的快速准确识别问题,笔者提出一种基于实时多目标注意力模型的牛只多部位快速自动化检测方法,采用多尺度注意力网络MSEAY,在网络中加入了SE(squeeze and excitation networks)注意力机制、H-swish激活函数及SIoU损失函数,消除现有牛群图像检测中光照、重叠、多类型等对图像检测结果产生的影响,先对牛只图像进行标注及预处理,然后采用MoibleNetv3模型作为Backbone进行牛只的部位划分识别,进而实现了多尺度、多部位牛只状态信息的精准分类与识别。结果表明:在选用含肉牛样本集合的前提下,各部位平均分类结果的精确率为96.6%,召回率为94.7%,F1值为94.1%,mAP@50值为97.4%;在仅选用种牛样本集合的前提下,各部位检测精确率为头部96.4%,躯干97.2%,腿部97.3%,平均值97.0%。本算法在保证检测实时性的同时提高了多尺度、多牛只的检测精度,验证了方法的鲁棒性与可泛化性,可用于多尺度、多目标、多部位状态信息的快速准确识别。
