Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi...Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi-supervised Incremental Learning(IL),we propose an online hybrid beamforming scheme.Firstly,given the constraint of constant modulus on analog beamformer and combiner,we propose a new broadnetwork-based structure for the design model of hybrid beamforming.Compared with the existing network structure,the proposed network structure can achieve better transmission performance and lower complexity.Moreover,to enhance the efficiency of IL further,by combining the semi-supervised graph with IL,we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning,where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data chunk.Unlike the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update,all transmissions,even the ones during the model update,would make contributions to model update in the proposed method.During the model update,the amount of unlabelled transmissions is very large and they also carry some information,the prediction performance can be enhanced to some extent by these unlabelled channel data.Simulation results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single approach.Besides,we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.展开更多
目的:系统评价昆仙胶囊相关治疗方案对狼疮肾炎(LN)的有效性,以期为LN患者的治疗策略提供参考依据。方法:计算机检索PubMed、Web of Science、Cochrane Library、CBM、中国知网、万方及维普数据库中昆仙胶囊治疗LN的相关研究,限定时间...目的:系统评价昆仙胶囊相关治疗方案对狼疮肾炎(LN)的有效性,以期为LN患者的治疗策略提供参考依据。方法:计算机检索PubMed、Web of Science、Cochrane Library、CBM、中国知网、万方及维普数据库中昆仙胶囊治疗LN的相关研究,限定时间为数据库建立至2022年4月6日,对符合标准的研究使用R 4.0.2软件与Revman 5.3软件进行Meta分析。结果:最终纳入4个随机对照研究与1个队列研究,包括310例患者。Meta分析结果显示:在24 h尿蛋白与SLEDAI评分方面,糖皮质激素+环磷酰胺+昆仙胶囊治疗后效果最优;在Scr、IgE与IgG方面,糖皮质激素+环磷酰胺+昆仙胶囊各指标水平明显低于糖皮质激素+环磷酰胺,差异有统计学意义(P<0.05)。结论:对比5种方案在治疗LN患者的临床疗效方面,以糖皮质激素+环磷酰胺+昆仙胶囊的效果最佳。因纳入研究的质量与数量限制,还需开展更多高质量的研究进行验证。展开更多
在全球气候变化的背景下,干旱半干旱区草地作为陆地生态系统中重要且非常脆弱的组分之一,显现出一系列生态问题。探究气候变化及人类活动对于该区草地生态系统净初级生产力(NPP)的影响,对于合理利用自然资源,保持农牧业可持续发展具有...在全球气候变化的背景下,干旱半干旱区草地作为陆地生态系统中重要且非常脆弱的组分之一,显现出一系列生态问题。探究气候变化及人类活动对于该区草地生态系统净初级生产力(NPP)的影响,对于合理利用自然资源,保持农牧业可持续发展具有重要的意义。施肥作为促进作物生长的一种方式,合理施肥也可以提高退化草地的NPP。基于此,本研究拟以天山北坡沿海拔梯度分布的4种草地类型:高山草甸(AM)、中山森林草甸(MMFM)、低山干草原(LMDG)和平原荒漠草原(PDG)为研究对象,基于反硝化-分解模型(DNDC)分析该区典型草地生态系统净初级生产力对施加不同氮肥的响应,并揭示施肥阈值及最优施肥方式。结果表明:1)适度氮肥添加促进了各个类型草地生态系统NPP的增长,但草地NPP对施肥量的响应存在阈值,且不存在适用于4种草地类型的统一最优施肥方式。LMDG草地生态系统对施氮肥的响应最敏感。2)PDG草地NPP达到最大的施肥方式为一年分两次施加100 kg·hm^(-2)硝酸盐,NPP的最大值为68.72 g C·m^(-2)·a^(-1)。LMDG草地NPP最大的施肥方式为一年分两次施加尿素260 kg·hm^(-2),NPP的最大值为263.28 g C·m^(-2)·a^(-1)。MMFM草地生态系统达到NPP最大的施肥方式为一年一次施尿素80 kg·hm^(-2),NPP的最大值为171.22 g C·m^(-2)·a^(-1)。无水氨作为在AM草地中反应最好的氮肥,以最小的施肥量(60 kg·hm^(-2))达到了NPP的最大值(114.62 g C·m^(-2)·a^(-1))。3)通过蒙特卡洛不确定分析的结果显示,施肥时间对PDG和LMDG的影响更为明显,施肥量波动对LMDG和MMFM的影响较其他两种草地更为明显。展开更多
基金supported by the National Science Foundation of China under Grant No.62101467.
文摘Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi-supervised Incremental Learning(IL),we propose an online hybrid beamforming scheme.Firstly,given the constraint of constant modulus on analog beamformer and combiner,we propose a new broadnetwork-based structure for the design model of hybrid beamforming.Compared with the existing network structure,the proposed network structure can achieve better transmission performance and lower complexity.Moreover,to enhance the efficiency of IL further,by combining the semi-supervised graph with IL,we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning,where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data chunk.Unlike the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update,all transmissions,even the ones during the model update,would make contributions to model update in the proposed method.During the model update,the amount of unlabelled transmissions is very large and they also carry some information,the prediction performance can be enhanced to some extent by these unlabelled channel data.Simulation results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single approach.Besides,we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.
文摘在全球气候变化的背景下,干旱半干旱区草地作为陆地生态系统中重要且非常脆弱的组分之一,显现出一系列生态问题。探究气候变化及人类活动对于该区草地生态系统净初级生产力(NPP)的影响,对于合理利用自然资源,保持农牧业可持续发展具有重要的意义。施肥作为促进作物生长的一种方式,合理施肥也可以提高退化草地的NPP。基于此,本研究拟以天山北坡沿海拔梯度分布的4种草地类型:高山草甸(AM)、中山森林草甸(MMFM)、低山干草原(LMDG)和平原荒漠草原(PDG)为研究对象,基于反硝化-分解模型(DNDC)分析该区典型草地生态系统净初级生产力对施加不同氮肥的响应,并揭示施肥阈值及最优施肥方式。结果表明:1)适度氮肥添加促进了各个类型草地生态系统NPP的增长,但草地NPP对施肥量的响应存在阈值,且不存在适用于4种草地类型的统一最优施肥方式。LMDG草地生态系统对施氮肥的响应最敏感。2)PDG草地NPP达到最大的施肥方式为一年分两次施加100 kg·hm^(-2)硝酸盐,NPP的最大值为68.72 g C·m^(-2)·a^(-1)。LMDG草地NPP最大的施肥方式为一年分两次施加尿素260 kg·hm^(-2),NPP的最大值为263.28 g C·m^(-2)·a^(-1)。MMFM草地生态系统达到NPP最大的施肥方式为一年一次施尿素80 kg·hm^(-2),NPP的最大值为171.22 g C·m^(-2)·a^(-1)。无水氨作为在AM草地中反应最好的氮肥,以最小的施肥量(60 kg·hm^(-2))达到了NPP的最大值(114.62 g C·m^(-2)·a^(-1))。3)通过蒙特卡洛不确定分析的结果显示,施肥时间对PDG和LMDG的影响更为明显,施肥量波动对LMDG和MMFM的影响较其他两种草地更为明显。
