自旋轨道耦合引起的电偶极矩

文章介绍了由于自旋轨道耦合导致的电子的电偶极矩在自旋电子学理论中的基本意义.研究发现,该电偶极矩与自旋流张量的反对称部分直接相关.它不仅直接导致可观测的电磁学效应,而且与电子在电场受到的力以及力矩有关,从而为自旋的电子学操控提供了可能.     

An Edge Server Placement Method Based on Reinforcement Learning

In mobile edge computing systems, the edge server placement problem is mainly tackled as a multi-objective optimization problem and solved with mixed integer programming, heuristic or meta-heuristic algorithms, etc. These methods, however, have profound defect implications such as poor scalability, local optimal solutions, and parameter tuning difficulties. To overcome these defects, we propose a novel edge server placement algorithm based on deep q-network and reinforcement learning, dubbed DQN-ESPA, which can achieve optimal placements without relying on previous placement experience. In DQN-ESPA, the edge server placement problem is modeled as a Markov decision process, which is formalized with the state space, action space and reward function, and it is subsequently solved using a reinforcement learning algorithm. Experimental results using real datasets from Shanghai Telecom show that DQN-ESPA outperforms state-of-the-art algorithms such as simulated annealing placement algorithm (SAPA), Top-K placement algorithm (TKPA), K-Means placement algorithm (KMPA), and random placement algorithm (RPA). In particular, with a comprehensive consideration of access delay and workload balance, DQN-ESPA achieves up to 13.40% and 15.54% better placement performance for 100 and 300 edge servers respectively.     

Hotel Performance in the UK: The Role of Information Entropy in a Novel Slack-Based Data Envelopment Analysis

Previous hotel performance studies neglected the role of information entropy in feedback processes between input and output management. This paper focuses on this gap by exploring the relationship between hotel performance at the industry level and the capability of learning by doing and adopting best practices using a sample of 153 UK hotels over a 10-year period between 2008–2017. Besides, this research also fills a literature gap by addressing the issues of measuring hotel performance in light of negative outputs. In order to achieve this, we apply a novel Modified slack-based model for the efficiency analysis and Least Absolute Shrinkage and Selection Operator to examine the influence of entropy related variable on efficiency score. The Results indicate that less can be learnt from inputs than from outputs to improve efficiency levels and resource allocation is more balanced than cash flow and liquidity. The findings suggest that market dynamics explains the cash flow generation potential and liquidity. We find that market conditions are increasingly offering the opportunities for learning and improving hotel efficiency. The results report that the distinctive characteristic of superior performance in hotel operations is the capability to match the cash flow generation potential with market opportunities.     

HL-2M 磁体系统安装中的定位与测量

为提高磁体系统安装精度,在 HL-2M 集成大厅建立 63 个基准点构成测量基准网,并利用激光跟 踪仪等高精度测量设备建立每个磁体的局部坐标系,测量特征点的局部坐标;基于测量基准网和公共测量点,采 用最佳拟合得到坐标转换矩阵,以此得到特征点在测量基准网的位置,指导磁体安装。完成安装后的中心柱同支 撑基础的同轴度为∅2.03mm;PF1~PF4 线圈安装标高偏差为±0.5mm,与中心柱的同轴度为∅2.60mm;PF5/6/7/8 线圈与中心柱的同轴度偏差小于∅3.00mm,标高偏差在[−1mm, 1mm]区间内。基于以上方法所得到的线圈安装精 度都满足设计需求。     

HL-2M 装置真空室设计

HL-2M 真空室结构为“D”形截面的双层-薄壁-全焊接式-环状结构,内环直径 2m,外环径 5.22m, 高 3.02m,由 20 个扇形段组成而成。真空室上开设有 121 个窗口以满足真空抽气、实验诊断、辅助加热及工程安 装等方面的要求;支撑采用滑动杆式结构;材料选用 Inconel625、Inconel718 与 316L 组合。运用有限元法对真空 室进行了结构强度评估,真空室满足设计要求。     

基于手性声子晶体的谷拓扑声输运

研究手性风车形散射体构建的谷拓扑声波导。具有右手与左手手性风车形散射体的声子晶体具有截然不同的声谷拓扑特性。当两种手性风车形散射体从-60°旋转到60°时,其所构建的声子晶体均出现2次偶然简并的狄拉克点与谷霍尔相变。基于两种具有相反谷霍尔相的手性声子晶体构建的谷拓扑声波导,在其重叠体带隙内存在一对局域在波导分界面处的谷态边缘态。实验研究表明,该边缘态可以很好的支持谷拓扑声输运,且对弯曲与无序两种缺陷具有一定的鲁棒性.     

弯曲圆盘换能器与镜像虚源的互辐射作用

建立了弯曲圆盘换能器镜像虚源等效模型,利用脉动球源互作用原理对弯曲圆盘与其镜像虚源的互辐射作用进行理论分析,给出了互辐射阻抗及系统谐振频率的数学表达。提出了虚源互作用的低频换能器设计思想,将刚性反射板引入弯曲圆盘换能器临近辐射面的声场中,通过理论分析、有限元模拟和样机实验研究了低频换能器谐振频率与主要结构参数之间的关系。结果表明,弯曲圆盘与镜像虚源间的互辐射作用可以有效降低换能器的谐振频率,当反射板直径与弯曲圆盘辐射面直径相当时,谐振频率可降低至其自身谐振频率的50%以下;当反射板直径为弯曲圆盘辐射面直径2倍时,谐振频率可降低至37%。     

Enhanced Directed Random Walk for the Identification of Breast Cancer Prognostic Markers from Multiclass Expression Data

Artificial intelligence in healthcare can potentially identify the probability of contracting a particular disease more accurately. There are five common molecular subtypes of breast cancer: luminal A, luminal B, basal, ERBB2, and normal-like. Previous investigations showed that pathway-based microarray analysis could help in the identification of prognostic markers from gene expressions. For example, directed random walk (DRW) can infer a greater reproducibility power of the pathway activity between two classes of samples with a higher classification accuracy. However, most of the existing methods (including DRW) ignored the characteristics of different cancer subtypes and considered all of the pathways to contribute equally to the analysis. Therefore, an enhanced DRW (eDRW+) is proposed to identify breast cancer prognostic markers from multiclass expression data. An improved weight strategy using one-way ANOVA (F-test) and pathway selection based on the greatest reproducibility power is proposed in eDRW+. The experimental results show that the eDRW+ exceeds other methods in terms of AUC. Besides this, the eDRW+ identifies 294 gene markers and 45 pathway markers from the breast cancer datasets with better AUC. Therefore, the prognostic markers (pathway markers and gene markers) can identify drug targets and look for cancer subtypes with clinically distinct outcomes.     

利用综合复用技术拓展数字全息显微系统中的记录视场

为了解决现有数字全息显微系统中高分辨率与大记录视场无法同时兼得的问题, 提出了一种在不牺牲分辨率的前提下拓展数字全息显微记录视场的方法. 该方法中运用了波长不同、偏振态不同的四路相互不相干的探测物光, 同时探测被测样品四个相邻的不同区域, 并使这四束探测物光分别与其相应的参考光相干, 在记录面上同时记录下含有被测样品不同区域信息的复合全息图. 将获得的复合全息图经过频谱变换和数字滤波, 分别重构出所记录区域的振幅和相位分布.最后通过图像拼接和图像融合技术, 可实现接近原记录视场四倍的大视场数字全息显微记录. 该方法在测量过程中无需移动记录装置、光源和被测样品, 单次曝光即可实现, 实验结果验证了本文所提方法的可行性. 关键词： 数字全息显微术 角分复用 偏振复用 波长复用