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10篇 您的检索式：作者名="Gajendra Kumar"

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		题名	作者	年代	出处	被引量
	1	Astrocytes: a double-edged sword in neurodegenerative diseases显示文摘Astrocytes play multifaceted and vital roles in maintaining neurophysiological function of the central nervous system by regulating homeostasis, increasing synaptic plasticity, and sustaining neuroprotective effects. Astrocytes become activated as a result of inflammatory responses during the progression of pathological changes associated with neurodegenerative disorders. Reactive astrocytes(neurotoxic A1 and neuroprotective A2) are triggered during disease progression and pathogenesis due to neuroinflammation and ischemia. However, only a limited body of literature describes morphological and functional changes of astrocytes during the progression of neurodegenerative diseases. The present review investigated the detrimental and beneficial roles of astrocytes in neurodegenerative diseases reported in recent studies, as these cells have promising therapeutic potential and offer new approaches for treatment of neurodegenerative diseases.	Zhi-Bin Ding Li-Juan Song Qing Wang Gajendra Kumar Yu-Qing Yan Cun-Gen Ma	2021	Neural Regeneration Research2021，16，9：	5
	2	A branch and bound algorithm for class based storage location显示文摘	Venkata Reddy Muppani Gajendra Kumar Adil	2008	European Journal of Operational Research2008，，189：	1
	3	Oral health and pregnancy:a review显示文摘	GAJENDRA S KUMAR J V	2004	N Y State Dent J2004，70，1：	1
	4	Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach显示文摘	Venkata Reddy Muppani (Muppant) Gajendra Kumar Adil	2007	Omega2007，，4：	1
	5	查看详情显示文摘	Gajendra Kumar Dharmendra Kumar Shoma Devi Rajeev Johari C P Singh		0，，07：	1
	6	Enzymatic transesteri cation of Jatropha curcas oil assisted by ultrasonication显示文摘	Gajendra Kumar Dharmendra Kumar Poonam	2011	Ultrasonics Sonochemistry2011，18，：	1
	7	Efficient formation ofstorage classes for warehouse storage location assignment:Asimulated annealing approach显示文摘	Muppani VR Gajendra Kumar Adil GK	2008	Omega2008，38，：	1
	8	An Efficient Class of Estimators for the Mean of a Finite Population in Two-Phase Sampling Using Multi-Auxiliary Variates显示文摘This paper presents an efficient class of estimators for estimating the population mean of the variate under study in two-phase sampling using information on several auxiliary variates.The expressions for bias and mean square error(MSE)of the proposed class have been obtained using Taylor series method.In addition,the minimum attainableMSE of the proposed class is obtained to the first order of approximation.The proposed class encompasses a wide range of estimators of the sampling literature.Efficiency comparison has been made for demonstrating the performance of the proposed class.An attempt has been made to find optimum sample sizes under a known fixed cost function.Numerical illustrations are given in support of theoretical findings.	Gajendra K.Vishwakarma Manish Kumar	2015	Communications in Mathematics and Statistics2015，3，4：	1
	9	Ul- trasonic-assisted transesterification of Jatropha curcus oil using solid catalyst, Na/Si02 显示文摘	Dharmendra Kumar Gajendra Kumar Poonam	2010	Ultrasonics Sonoche- mistry2010，17，5：	1
	10	Estimation of Mean in Double Sampling Using Exponential Technique on Multi-auxiliary Variates显示文摘This paper presents exponential-type ratio and product estimators for a finite population mean in double sampling using information on several auxiliary variates.The proposed estimators can be viewed as a generalization over the estimators suggested by Singh and Vishwakarma(Austrian J Stat 36(3):217–225,2007).The expressions for biases and mean square errors(MSEs)of the proposed estimators have been derived to the first degree of approximation.In addition,the expressions for minimum attainable MSEs are also investigated using the criterion for optimality of the weights.An empirical study is carried out in the support of the present study.Both theoretical andempirical findings are encouraging and support thesoundness that the proposed procedures for mean estimation perform better than the usual unbiased estimators and other well-known estimators under some realistic conditions.	Manish Kumar Gajendra K.Vishwakarma	2017	Communications in Mathematics and Statistics2017，5，4：	0

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