Multilayer Si@SiOx@void@C anode materials synthesized via simultaneously carbonization and redox for Li-ion batteries

In the development of high-performance lithium-ion batteries (LIBs), the composition and structure of electrode materials are of critical importance. Silicon has a theoretical specific capacity 10 times that of graphite, nonetheless, its application as an anode material confronts challenge as it undergoes huge volume change and pulverization amidst the alloying and dealloying processes. Herein, a novel method to prepare a multilayer Si-based anode was proposed. Three layers, SiO₂, nickel and triethylene glycol (TEG), were coated successively on Si nanoparticles, which served respectively as the sources of SiO_x, sacrificial templates and carbon. Nickel can not only serve as a hollow template, but also play a catalytic role, which makes carbonization and redox reactions occur synchronously under a mild condition. Amid the carbonization process of TEG at 450 °C, several-nm-thick SiO₂ layer can react with the as-derived carbon to form a silicon suboxides (SiO_x (0 < x < 2)) intermedium layer. After removing the nickel template, a micro-nano scaled Si@SiO_x@void@C with conformal multilayer-structure can be obtained. The BET specific surface area and pore volume of powders were increased dramatically because of the derivation of abundant voids, which can not only buffer the swelling effect of silicon, but also provide richer ionic conductivity. The as-assembled half-cell with Si@SiOx@void@C as the anode material possesses high capacity (～1000 mAh g^?1 at 3 A g^?1), long cycle life (300 cycles with 77% capacity retention) and good rate performance (558 mAh g^?1 at 5 A g^?1).     

基于近红外光谱技术的马铃薯叶片含水率高效预测

提出了运用近红外光谱技术检测新鲜马铃薯叶片中含水量的方法，并通过预测结果和运算量的对比得出一种高效率的预测方法。采集了900～2100 nm波段范围内110个新鲜马铃薯叶片的光谱反射率信息，经SG（Savitzky-Golay）平滑、多元散射校正（MSC）和标准正态变量变换（SNV）3种预处理后，分别建立偏最小二乘回归（PLSR）模型和BP神经网络模型，再运用回归系数（regression coefficients, RC）法在全波段光谱中提取特征波长，同样经3种预处理后分别建立预测模型。结果表明：在运用光谱全波段信息构建的模型中，经多元散射校正（MSC）预处理建立的BP神经网络模型预测效果最好，预测集决定系数R²为0.9791，均方根误差RMSE为0.3723；在基于特征波长构建的模型中，经SG平滑预处理建立的神经网络模型预测效果最优，预测集决定系数R²为0.9658，均方根误差RMSE为0.4759；验证了特征波段结合BP神经网络建立的模型与全波段建立的模型预测结果相差不大，因而能够极大地减少运算量，提高预测效率。     

帕金森氏病关联miRNAs的功能和调控

帕金森病（Parkinson's disease, PD）是一种老年期常见的神经系统退行性疾病，致病过程复杂，其发病机制尚未明确，目前普遍认为帕金森病的发生与环境、遗传和年龄等多个因素有关。microRNAs（miRNAs）是一种内源性的小分子非编码RNAs，在转录后水平调控人类基因组中约1/3的基因。大量研究表明，帕金森病与miRNAs存在密切关联，在PD的发生发展、诊断甚至治疗过程中起到重要作用。本综述讨论了最近研究报道的和帕金森病相关的miRNAs，并分析了miRNAs的特异性表达在帕金森病的致病机制和诊断中发挥的作用。     

污泥生物炭中氮硫行为及环境效应研究进展

污泥生物炭中氮硫元素含量高，其氮硫行为和环境效应对全球气候变化的影响不容忽视。以往的研究中，研究者往往以富碳生物炭作为主要研究对象，关注碳对全球气候变化的行为和功效，而对氮硫元素的作用关注不够。本文从原始污泥基本性质到其热解过程，再到生物炭的老化，逐步对污泥生物炭整个生命周期内氮硫的行为及其环境效应研究进行综述，并对未来应注重开展的研究方向进行展望，为生物炭中氮硫元素固定、释放及与之关联的环境效应和温室气体排放控制研究提供理论基础。分析表明，污泥中氮元素含量普遍高于硫元素，且热解过程中氮比硫更容易转移至气相产物。氮硫元素随热解温度的增加，在三相产物中的分配都是炭中持续减少，油中先增后减，气中一直增加。高温（＞800℃）条件下，气相中的氮含量高于固相，而硫元素则仍然主要存在于固相中。污泥生物炭老化及其环境效应研究表明，污泥生物炭氮硫元素与土壤的相互作用及其温室效应问题在今后的研究中应引起重视。     

探究智能变电站的继电保护二次回路故障诊断问题

本文即针对当前智能变电站中的故障诊断问题展开分析,主要以继电保护二次回路故障检测为主,就诊断检测系统进行阐述,总结了能够针对各种故障问题进行检测手段,意在能够借此提升变电站的智能化发展水平。     

高掺量温拌再生沥青混合料设计及性能研究

厂拌热再生作为当前应用最为广泛的沥青路面再生技术,RAP掺加比例普遍较低。将温拌技术和再生技术相结合,对基于温拌的高掺量厂拌热再生混合料的配合比设计以及混合料的性能进行研究,并指导实体工程施工。结果表明,温拌剂Evotherm可提高老化沥青的性能,40%RAP+Evotherm再生混合料Sup-20的路用性能均符合技术要求,且表现出更好的高温抗车辙变形能力。高掺量温拌再生技术在S325省道的成功应用,为类似工程提供借鉴和参考。     

Elp3 modulates neural crest and colorectal cancer migration requiring functional integrity of HAT and SAM domains

Cell migration is a finely tuned biological process that often involves epithelial-mesenchymal transition (EMT). EMT is typically characterized by the upregulation of mesenchymal markers such as Snail1. This process has been shown to be of critical importance to normal developmental processes, including neural crest migration and invasion. Interestingly, similar mechanisms are utilized in disease processes, such as tumor metastasis and migration. Notably, EMT and EMT-like processes confer tumor cells with the ability to migrate, invade, and adopt stem cell-like properties that largely account for immunosuppression and tumor recurrence. Therefore, identifying sensitive EMT markers may contribute to cancer prognosis and diagnosis in many facets. Previously, we showed that Elp3 plays an essential role during neural crest migration by stabilizing Snail1. In the current study, we further elucidate the molecular mechanism underlying colorectal cancer migration. We found that mElp3 exerted an identical function to xElp3 in modulating neural crest migration, and both HAT and SAM domains are imperative during this migratory process. Interestingly, overexpression of mElp3 in SW480 cells promoted cell migration and invasion, and we further showed that Elp3 stabilized Snail1 requiring integrity of both SAM and HAT domains. Our findings warrant further exploration of the specific target of Elp3 in cancer cells.     

糖蜜及其发酵制品的应用研究进展

糖蜜是制糖工业的副产物。对甘蔗糖蜜、甜菜糖蜜、大豆糖蜜、柑橘糖蜜、石榴糖蜜的来源、成分及它们在各自相关领域的应用进行了简要概括,重点综述了以糖蜜为微生物发酵底物,生产相关活性物质的研究进展以及它们的相关作用,旨在为其在医药、食品、化妆品等领域的应用提供参考依据。     

机制砂和Ⅲ级粉煤灰配制低水泥用量C60高性能混凝土的试验和工程应用

针对C60大体积转换层的施工，在混凝土配比、水化放热等方面进行了试验研究，成功地配制出水泥用量为328kg／m^3的机制砂C60高性能混凝土，并有效地控制了大体积高强混凝土的收缩变形和温度变形，解决了用机制砂、特细砂和Ⅲ级粉煤灰配制高性能混凝土以及减小高强混凝土的水化放热的问题。     

基于LSTM网络的变压器油中溶解气体浓度预测

电力变压器作为电力系统中传输和变换电能的主要设备,其安全稳定性运行在电网中起着重要的作用。对变压器油中溶解气体浓度变化的趋势进行预测,可为其运行状态评估提供重要依据,鉴于此提出了一种基于长短期记忆网络(LSTM)的变压器油中溶解气体浓度预测模型。该模型克服了传统神经网络在序列预测方面存在的"梯度消散"问题,利用油中溶解气体的序列数据对长短期记忆网络进行训练,得到最优的预测模型参数。以变压器油中溶解的7种特征气体浓度为输入,以待预测气体的浓度为输出。通过算例分析表明,相比于传统的机器学习预测方法支持向量机(support vector machine, SVM)与反向传播神经网络(back propagation neural network,BPNN),本文所提的LSTM预测模型更能准确地预测油中溶解气体的浓度。