Summary During embryogenesis, plants are thought to use a mechanism that allows the suspensor to maintain its identity. Here, we reported that RPL18a is involved in this mechanism in Arabidopsis thaliana. The suspenso...Summary During embryogenesis, plants are thought to use a mechanism that allows the suspensor to maintain its identity. Here, we reported that RPL18a is involved in this mechanism in Arabidopsis thaliana. The suspensor cells proliferated in rp118aB and formed a multicellular structure rather than undergo pro- grammed cell death, as in wild type. Suspensors of rpl18a expressed the embryo proper marker, DRN：： GFP, but not the suspensor marker, WOX8：：GFP. In addition, auxin accumulated throughout the suspensors of rpl18a proembryos. Suspensor-specific expression of RPL18a could rescue the cell proliferation defects in rpl18a suspensors. These findings supported a role for RPL18a in maintaining suspensor identity.展开更多
This standard specifies the classification, shape, dimension, technical requirements, test method, inspection rules, packing, marking, transportation, storage and quality certification of fireclay refractory bricks fo...This standard specifies the classification, shape, dimension, technical requirements, test method, inspection rules, packing, marking, transportation, storage and quality certification of fireclay refractory bricks for hot blast stove.展开更多
针对矿井涌水量预测中存在的深度学习模型预测精度不高和适用性不强的问题,提出了一种基于深度残差网络(Deep Residual Network,DRN)和双向长短记忆网络(Bidirectional short and long memory network,BiLSTM)的矿井涌水量预测方法。首...针对矿井涌水量预测中存在的深度学习模型预测精度不高和适用性不强的问题,提出了一种基于深度残差网络(Deep Residual Network,DRN)和双向长短记忆网络(Bidirectional short and long memory network,BiLSTM)的矿井涌水量预测方法。首先,将矿井涌水量数据进行小波分解和归一化处理,得到趋势项数据和细节项数据;其次,采用DRN网络方法对趋势项数据进行预测,采用BiLSTM网络方法对细节项数据进行预测;最后,将2部分预测结果进行重构得到矿井涌水量预测结果。研究结果表明:DRN-BiLSTM模型相比于单一模型预测精度更高,说明该模型具有更好的泛化性。展开更多
基金supported by the National Natural Science Foundation of China(31570317 and 31270362)
文摘Summary During embryogenesis, plants are thought to use a mechanism that allows the suspensor to maintain its identity. Here, we reported that RPL18a is involved in this mechanism in Arabidopsis thaliana. The suspensor cells proliferated in rp118aB and formed a multicellular structure rather than undergo pro- grammed cell death, as in wild type. Suspensors of rpl18a expressed the embryo proper marker, DRN：： GFP, but not the suspensor marker, WOX8：：GFP. In addition, auxin accumulated throughout the suspensors of rpl18a proembryos. Suspensor-specific expression of RPL18a could rescue the cell proliferation defects in rpl18a suspensors. These findings supported a role for RPL18a in maintaining suspensor identity.
文摘This standard specifies the classification, shape, dimension, technical requirements, test method, inspection rules, packing, marking, transportation, storage and quality certification of fireclay refractory bricks for hot blast stove.
文摘针对矿井涌水量预测中存在的深度学习模型预测精度不高和适用性不强的问题,提出了一种基于深度残差网络(Deep Residual Network,DRN)和双向长短记忆网络(Bidirectional short and long memory network,BiLSTM)的矿井涌水量预测方法。首先,将矿井涌水量数据进行小波分解和归一化处理,得到趋势项数据和细节项数据;其次,采用DRN网络方法对趋势项数据进行预测,采用BiLSTM网络方法对细节项数据进行预测;最后,将2部分预测结果进行重构得到矿井涌水量预测结果。研究结果表明:DRN-BiLSTM模型相比于单一模型预测精度更高,说明该模型具有更好的泛化性。
