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人类胚胎的不完全性与伦理问题 被引量:2
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作者 李才华 房彬 《医学与哲学(A)》 CSSCI 北大核心 2008年第10期16-17,59,共3页
人类胚胎伦理地位的道德两分法不具有合理性,应该从人类胚胎是"人的不完全态"着手分析他的发育连续性,并相应的考虑他的伦理地位。胚胎伦理学包含着内在的伦理悖论,所以道义论和效果论都不能很好地解决。考虑"人的不完全... 人类胚胎伦理地位的道德两分法不具有合理性,应该从人类胚胎是"人的不完全态"着手分析他的发育连续性,并相应的考虑他的伦理地位。胚胎伦理学包含着内在的伦理悖论,所以道义论和效果论都不能很好地解决。考虑"人的不完全态"的连续统,提出了中庸主义的解决方案。 展开更多
关键词 胚胎伦理 不完全态 道义论 效果论
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Joint Energy-Efficient Power Allocation and Beamforming Design for mm Wave-NOMA System with Imperfect CSI 被引量:1
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作者 CAI Jiali YU Xiangbin +1 位作者 XU Fangcheng WANG Guangying 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2021年第S01期115-121,共7页
The joint power allocation(PA)and beamforming(BF)design problem is studied to maximize the energy efficiency of a two-user downlink millimeter-wave system with non-orthogonal multiple access under imperfect channel st... The joint power allocation(PA)and beamforming(BF)design problem is studied to maximize the energy efficiency of a two-user downlink millimeter-wave system with non-orthogonal multiple access under imperfect channel state information(CSI).By means of block coordinate descent,convex-concave procedure,and successive convex approximate,we propose a suboptimal joint PA and BF design scheme to address this non-convex problem.Simulation results verify that the proposed joint PA and BF design scheme is more effective when compared to some existing schemes. 展开更多
关键词 energy efficiency millimeter wave non-orthogonal multiple access(NOMA) imperfect channel state information
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NONPARAMETRIC REGRESSION UNDER DOUBLE-SAMPLING DESIGNS
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作者 Xuejun JIANG Jiancheng JIANG Yanling LIU 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2011年第1期167-175,共9页
This paper studies nonparametric estimation of the regression function with surrogate outcome data under double-sampling designs, where a proxy response is observed for the full sample and the true response is observe... This paper studies nonparametric estimation of the regression function with surrogate outcome data under double-sampling designs, where a proxy response is observed for the full sample and the true response is observed on a validation set. A new estimation approach is proposed for estimating the regression function. The authors first estimate the regression function with a kernel smoother based on the validation subsample, and then improve the estimation by utilizing the information on the incomplete observations from the non-validation subsample and the surrogate of response from the full sample. Asymptotic normality of the proposed estimator is derived. The effectiveness of the proposed method is demonstrated via simulations. 展开更多
关键词 Local linear smoother surrogate validation sample
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