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.     

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。     

A hybrid homogeneously weighted moving average control chart for process monitoring

Several modifications and enhancements to control charts in increasing the performance of small and moderate process shifts have been introduced in the quality control charting techniques. In this paper, a new hybrid control chart for monitoring process location is proposed by combining two homogeneously weighted moving average (HWMA) control charts. The hybrid homogeneously weighted moving average (HHWMA) statistic is derived using two smoothing constants λ₁ and λ₂ . The average run length (ARL) and the standard deviation of the run length (SDRL) values of the HHWMA control chart are obtained and compared with some existing control charts for monitoring small and moderate shifts in the process location. The results of study show that the HHWMA control chart outperforms the existing control charts in many situations. The application of the HHWMA chart is demonstrated using a simulated data.     

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.     

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。     

积分中值屈服准则解析厚板轧制椭圆速度场

为解决非线性Mises比塑性功率积分困难以及由此导致的轧制功率解析式难以获得的问题,本文通过建立并利用线性比塑性功率表达式对提出的椭圆速度场进行能量分析,得到了轧制力能参数的解析解.文中通过对变角度屈服函数求积分中值,构建了一个新的屈服准则,它是主应力分量的线性组合,在π平面上的轨迹是逼近Mises圆的等边非等角的十二边形,其基于Lode参数表达式的理论结果也与实验数据吻合较好.同时,根据厚板轧制时金属流动速度从入口到出口逐渐增大的特点,提出了水平速度分量满足椭圆方程的速度场,该速度场满足运动许可条件.通过相应的轧制能量分析,获得了基于线性屈服准则的内部变形功率以及基于应变矢量内积法上的摩擦功率与剪切功率.在此之上,通过泛函的极值变分导出了轧制力矩、轧制力以及应力状态系数的解析解,并与现场实测数据进行了对比,结果表明利用本文提出的屈服准则与速度场所建立的轧制力矩与轧制力模型与实测值吻合较好,其中轧制力误差小于5.3%,轧制力矩误差在6%左右.     

Hydrogenation process in multiphase alloys of Ti-Zr-Mn-V system on the example of Ti42.75Zr27Mn20.25V10 alloy

The influence of phase composition and microstructure of Ti_42.75Zr₂₇Mn_20.25V₁₀ alloy on its hydrogenation kinetic and phase composition of hydrogenated product was studied. It is established that the process of dissociation of hydrogen molecules begins on the surface of Laves phase crystallites. The dissolution of atomic hydrogen in the material volume leads to the formation of cracks in the intermetallic crystallites, which further appear as additional centers of dissociation of hydrogen molecules and noticeably accelerate the diffusion of hydrogen into the bulk material. It was shown that the Laves phase acts as a donor of atomic hydrogen for the BCC solid solution during hydrogenation of two-phase structure, initiating intensive hydrogenation of the BCC phase at room temperature.     

基于分段加权的反向稀疏跟踪算法研究

为提高稀疏表示跟踪模型性能，提出一种分段加权的反向稀疏跟踪算法，将跟踪问题转化为在贝叶斯框架下寻找概率最高的候选对象问题，构造不同的分段权重函数来分别度量候选目标与正负模板的判别特征系数。通过池化来降低跟踪结果的不确定性干扰，选择正负模板加权系数差值最大的候选表示作为跟踪结果。实验表明，在光照变化、遮挡、快速运动、运动模糊情况下，所提出的算法可以确保跟踪结果的准确性和鲁棒性。