The effects of washing a collagen sample prior to TEM examination

Transmission electron microscopy (TEM) is an important analysis technique to visualize (bio)macromolecules and their assemblies, including collagen fibers. Many protocols for TEM sample preparation of collagen involve one or more washing steps to remove excess salts from the dispersion that could hamper analysis when dried on a TEM grid. Such protocols are not standardized and washing times as well as washing solvents vary from procedure to procedure, with each research group typically having their own protocol. Here, we investigate the influence of washing with water, ethanol, but also methanol and 2-propanol, for both mineralized and unmineralized collagen samples via a protocol based on centrifugation. Washing with water maintains the hydrated collagen structure and the characteristic banding pattern can be clearly observed. Conversely, washing with ethanol results in dehydration of the fibrils, often leading to aggregation of the fibers and a less obvious banding pattern, already within 1 min of ethanol exposure. As we show, this process is fully reversible. Similar observations were made for methanol and propanol. Based on these results, a standardized washing protocol for collagenous samples is proposed.     

Solution-Synthesized Multifunctional Janus Nanotree Microswimmer

Synthetic active matters are perfect model systems for non-equilibrium thermodynamics and of great potential for novel biomedical and environmental applications. However, most applications are limited by the complicated and low-yield preparation, while a scalable synthesis for highly functional microswimmers is highly desired. In this paper, an all-solution synthesis method is developed where the gold-loaded titania-silica nanotree can be produced as a multi-functional self-propulsion microswimmer. By applying light, heat, and electric field, the Janus nanotree demonstrated multi-mode self-propulsion, including photochemical self-electrophoresis by UV and visible light radiation, thermophoresis by near-infrared light radiation, and induced-charge electrophoresis under AC electric field. Due to the scalable synthesis, the Janus nanotree is further demonstrated as a high-efficiency, low-cost, active adsorbent for water decontamination, where the toxic mercury ions can be reclaimed with enhanced efficiency.     

高分子材料导热性能影响因素研究进展

介绍了高分子材料导热性能影响因素研究进展，重点阐释了聚合物基体的结构特性（链结构、分子间相互作用、取向、结晶度等）、导热填料（种类、含量、形态、尺寸等）以及制备方法等对高分子材料导热性能的影响。     

乌兰矿采矿现状及技术应对方案

本文分析了乌兰矿投产前期采矿现状及存在的主要问题,针对该矿所处蒙古国经济落后、投资风险大的现实状况,为避免生产中断、规避投资风险,早日回收前期投资考虑,采取了双斜坡道开拓、全尾胶结充填、高端壁空场嗣后充填采矿、多中段组合式连续开采等系列技术应对方案。大大降低了一次性投资规模及投资风险,前期投资得以快速回笼的同时,矿山产能也充分释放,确保了矿山的持续稳定,取得了较好的经济和社会效益。为海外地下近地表矿体开采矿山规避投资风险提供了很好的技术方案借鉴。     

变形铝合金表面锆基化学转化膜的研究现状

化学转化膜是金属表面主要的处理方法之一，具备良好的附着力和耐蚀性，能为铝合金提供一定的临时防护。传统的六价铬酸盐化学转化膜在日渐严苛的环保压力下已经逐渐淘汰，取而代之的是近几年发展迅猛的三价铬及无铬锆基化学转化膜。铝合金可分为铸造铝合金和变形铝合金，按照所含主要合金元素和热处理状态可分为若干个系列和型号。本文选取几种典型的变形铝合金，综述了不同铝合金微观组织对转化膜成膜过程的影响，化学转化液添加剂、预处理和后处理工艺对转化膜性能的调控及作用机理，以及几种典型商业钝化剂在变形铝合金表面的应用。总结了目前变形铝合金表面锆基化学转化膜仍面临的问题和发展趋势，未来化学转化膜需在满足新型铝合金发展要求的基础上，通过不同有机、无机添加剂以及外场作用对转化膜的成膜均一性、完整性进行调控，以提高转化膜的综合性能。     

Deep reinforcement learning-based cooperative interactions among heterogeneous vehicular networks

Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution.     

柠檬酸铋合成新工艺研究

针对现有柠檬酸铋制备工艺合成时间长、能耗高、产品纯度不高等不足,介绍了一种常温下制备柠檬酸铋的新工艺。新工艺制备时间短,制备的柠檬酸铋产品质量好,合成过程产生的废水可循环利用,废气经碱液循环吸收可生产硝酸钠副产品。     

内热型超声雾化溶液再生系统最优内热量的研究

基于质量守恒、能量守恒定律，建立了内热型超声雾化溶液再生系统（IH-UARS）的再生性能预测模型并进行了充分的实验验证，通过研究不同内热量下IH-UARS的再生性能及其变化规律，寻求系统所需的最佳内热量并明确其可能的影响因素。结果表明：IH-UARS系统存在最优的内热量范围，使其再生系统性能最佳；所需最优内热量随着再生溶液流量增大呈显著的对数增长，但受空气流量的影响较弱；在该研究中的标准工况下，IH-UARS所需最优内热量约为275~350 W。此外研究发现：内热量的增长有益于促进初始浓度较高的溶液进一步浓缩再生，如当IH-UARS中内热量增至800 W时，其初始浓度为36%的溶液比24%的溶液浓度增量指标改善幅度高37%。研究所得结果可对提高溶液再生性能及经济性提供积极参考。