Destination-aware metric based social routing for mobile opportunistic networks

Wireless Networks - Although centrality is widely used to differentiate the importance of nodes for social-aware routing in mobile opportunistic networks (MONs), it is destination-agnostic since...     

新型防屈曲高强钢腹板可更换钢连梁抗震性能研究

文章率先提出一种新型防屈曲高强钢腹板可更换钢连梁(简称“新型钢连梁”)：腹板采用高强钢，可提高钢连梁的屈服抗剪强度，连梁变形减小，从而减小可更换结构整体变形，便于更换；加劲肋紧贴腹板(但不焊接)提供约束，仅与上下翼缘焊接，可减少60%以上的焊接量。其次，设计并开展了11个试件的拟静力试验，研究了加劲肋间距(规范限值dmax、0.85dmax)、腹板厚度(6mm、8mm)、腹板钢材强度(Q460、Q550)和构造形式(加劲肋与腹板贴紧或焊接)等参数对新型钢连梁抗震性能的影响。试验结果表明：试件均发生剪切破坏；满足加劲肋间距限值的新型钢连梁，滞回曲线饱满，峰值时腹板未发生鼓曲且极限转角均超过0.1rad，大于规范限值0.08rad，表现出良好的耗能和变形能力；缩小加劲肋间距、增加腹板厚度或提高腹板钢材强度，新型钢连梁刚度及承载力提高；新型钢连梁峰值承载力较传统构造试件低约5%。最后，基于试验结果建立了有限元模型并开展了分析，研究结果表明：对腹板采用Q460、Q550高强钢材的新型钢连梁，峰值承载力计算时超强系数建议取1.43(长度比为0.5～1.0)或1.39(长度比为1.0～1.6)、1.25，以期为实际工程设计提供依据。     

Co?N graphene encapsulated cobalt catalyst for H2O2 decomposition under acidic conditions

Hydrogen peroxide (H₂O₂) has been listed as one of the 100 most important chemicals in the world. However, huge amount of residual H₂O₂ is hard to timely decomposed into O₂ and H₂O under acidic condition, easily resulting in explosion hazard. Here, we reported a core–shell structure catalyst, that is graphene with Co N structure encapsulated Co nanoparticles. Co N graphene shell serves as the active site for the H₂O₂ decomposition, and Co core further enhance this decomposition. Benefiting from it, the H₂O₂ decomposition were close to 100% after 6 cycles without pH adjustment, which increased 6 orders of magnitude compared with no catalyst. At the same time, the O₂ generation reached 99.67% in 2 h with little metal leaching, and ·OH has been greatly inhibited to only 0.08%. This work can cleanly remove H₂O₂ with little deep oxidation and protect the process of H₂O₂ utilization to achieve a safer world.     

Study on the removal of olefins from naphtha by clay loaded with trifluoromethanesulfonic acid

Journal of Porous Materials - In this work, a trifluoromethanesulfonic acid (TFOH) modified clay (TFOH-Clay) was developed for the removal of trace olefins in heavy naphtha. 5%TFOH-Clay can...     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。