Lamina 发表于 2025-3-25 04:27:40
*Integration of Differential Forms on Manifolds, derive the contemporary version of the Newton–Leibniz formula, called the general Stokes formula. It incorporates all fundamental classical integral formulas of analysis (Newton–Leibniz, Green, Gauss–Ostrogradskii, and Stokes formulas).旧石器 发表于 2025-3-25 11:07:28
Uniform Convergence and the Basic Operations of Analysis on Series and Families of Functions,series, one of the most important technical tools of analysis. We consider different types of convergence of sequences and series of functions, and discuss conditions under which certain useful properties of functions persist after passing to a limit.不规则 发表于 2025-3-25 11:43:43
Integrals Depending on a Parameter,. In this chapter we will study and describe the general properties of integrals depending on a parameter. In particular, we introduce Eulerian integrals and present some basic ideas of generalized functions.hereditary 发表于 2025-3-25 17:32:29
http://reply.papertrans.cn/63/6260/625972/625972_24.pngMalleable 发表于 2025-3-25 20:25:51
t years with mutations of the gene SCN4A located in chromosome 17q (23.1 to 25.2) which encodes the α-subunit of the voltage-gated sodium channel of the adult skeletal muscle Barchi 1995; Cannon 1996; George 1995; Hoffman et al. 1995; Lehmann-Horn and Rüidel 1996). The 17 single-point mutations idenlanugo 发表于 2025-3-26 02:10:18
http://reply.papertrans.cn/63/6260/625972/625972_26.pngGEM 发表于 2025-3-26 05:34:38
http://reply.papertrans.cn/63/6260/625972/625972_27.pngCabg318 发表于 2025-3-26 09:05:44
http://reply.papertrans.cn/63/6260/625972/625972_28.png愤怒事实 发表于 2025-3-26 15:12:06
Vladimir A. Zorichning and recall performance, and 2) ‘strength of learning’ on the networks’ ability to relearn, or transfer prior learning after aging. In the first experiment dendritic attrition was simulated by random connection pruning and the extent of pruning was progressively increased to simulate aging. In t向下五度才偏 发表于 2025-3-26 18:37:10
Vladimir A. Zorichning and recall performance, and 2) ‘strength of learning’ on the networks’ ability to relearn, or transfer prior learning after aging. In the first experiment dendritic attrition was simulated by random connection pruning and the extent of pruning was progressively increased to simulate aging. In t