A polarization modulated directional backlight autostereoscopic display

A polarization modulated directional backlight autostereoscopic display is proposed and demonstrated. The system consists of the orthogonally polarized backlight, the Fresnel lens array, a light shaping diffuser film, and a liquid crystal display (LCD) with a microphase retardation film. The autostereoscopic image pair carried by the directional light with different polarization directions is simultaneously projected to different spatial directions. The simulation and experimental results show that the directional projection of parallax images is realized for a high-quality autostereoscopic display with large viewing angle and continuous viewing volume, hence making it suitable for practical applications.     

A survey on deploying mobile deep learning applications: A systemic and technical perspective

With the rapid development of mobile devices and deep learning, mobile smart applications using deep learning technology have sprung up. It satisfies multiple needs of users, network operators and service providers, and rapidly becomes a main research focus. In recent years, deep learning has achieved tremendous success in image processing, natural language processing, language analysis and other research fields. Despite the task performance has been greatly improved, the resources required to run these models have increased significantly. This poses a major challenge for deploying such applications on resource-restricted mobile devices. Mobile intelligence needs faster mobile processors, more storage space, smaller but more accurate models, and even the assistance of other network nodes. To help the readers establish a global concept of the entire research direction concisely, we classify the latest works in this field into two categories, which are local optimization on mobile devices and distributed optimization based on the computational position of machine learning tasks. We also list a few typical scenarios to make readers realize the importance and indispensability of mobile deep learning applications. Finally, we conjecture what the future may hold for deploying deep learning applications on mobile devices research, which may help to stimulate new ideas.     

Fast medical concept normalization for biomedical literature based on stack and index optimized self-attention

Neural Computing and Applications - Medical concept normalization aims to construct a semantic mapping between mentions and concepts and to uniformly represent mentions that belong to the same...     

Exploring Statistical Arbitrage Opportunities Using Machine Learning Strategy

Computational Economics - Arbitrage opportunity exploration is important to ensure the profitability of statistical arbitrage. Prior studies that concentrate on cointegration model and other...     

Surface Energy and Surface Stability of Ag Nanocrystals at Elevated Temperatures and Their Dominance in Sublimation‐Induced Shape Evolution

The surface energy and surface stability of Ag nanocrystals (NCs) are under debate because the measurable values of the surface energy are very inconsistent, and the indices of the observed thermally stable surfaces are apparently in conflict. To clarify this issue, a transmission electron microscope is used to investigate these problems in situ with elaborately designed carbon‐shell‐capsulated Ag NCs. It is demonstrated that the {111} surfaces are still thermally stable at elevated temperatures, and the victory of the formation of {110} surfaces over {111} surfaces on the Ag NCs during sublimation is due to the special crystal geometry. It is found that the Ag NCs behave as quasiliquids during sublimation, and the cubic NCs represent a featured shape evolution, which is codetermined by both the wetting equilibrium at the Ag–C interface and the relaxation of the system surface energy. Small Ag NCs (≈10 nm) no longer maintain the wetting equilibrium observed in larger Ag NCs, and the crystal orientations of ultrafine Ag NCs (≈6 nm) can rotate to achieve further shape relaxation. Using sublimation kinetics, the mean surface energy of Ag NCs at 1073 K is calculated to be 1.1–1.3 J m^?2.     

Isolation and characterization of seven quorum quenching bacteria for biofouling control in MBR

Recently, interspecies quorum quenching (QQ) by bacteria has been reported as a novel approach in biofouling control in membrane bioreactor (MBR) for wastewater treatment. In this study, seven QQ bacteria, named RO1 to RO7, were isolated from fouling reverse osmosis (RO) membrane and were encapsulated in the microbial filters for biofouling control in MBR. Results showed that all isolates have extracellular QQ activity, and RO1 to RO6 were characterized as heat-stable enzymatic degradation of N-acyl homoserine lactones (AHLs), while RO7 was mainly pH-dependent. Analysis of the 16S rRNA gene indicated that RO7 was a species of Pseudomonas sp., others belonged to the species of Bacillus, Stenotrophomonas maltophilia and Delftia tsuruhatensis, respectively. Then, the microbial filters encapsulated each isolate were applied in a laboratory-scaled MBR and proved the substantial inhibition effect on membrane biofouling except for RO7, indicating that QQ bacteria employing enzymes to degrade AHLs have great potential in biofouling control in MBR.     

A two-step approach to synthesis of Co(OH)<Subscript>2</Subscript>/γ-NiOOH/reduced graphene oxide nanocomposite for high performance supercapacitors

A two-step approach was reported to fabricate cobaltous hydroxide/γ- nickel oxide hydroxide/reduced graphene oxide (Co(OH)₂/γ-NiOOH/RGO) nanocomposites on nickel foam by combining the reduction of graphene oxide with the help of reflux condensation and the subsequent hydrothermal of Co(OH)₂ on RGO. The microstructural, surface morphology and electrochemical properties of the Co(OH)₂/γ-NiOOH/RGO nanocomposite were investigated. The results showed that the surface of the first-step fabricated γ-NiOOH/RGO nanocomposites was uniformly coated by Co(OH)₂ nanoflakes with lateral size of tens of nm and thickness of several nm. Co(OH)₂/γ-NiOOH/RGO nanocomposite demonstrated a high specific capacitance (745 mF/cm² at 0.5 mA/cm²) and a cycling stability of 69.8% after 1000 cycles at 30 mV/cm². γ-NiOOH/RGO//Co(OH)₂/γ-NiOOH/RGO asymmetric supercapacitor was assembled, and maximum gravimetric energy density of 57.3 W?h/kg and power density of 66.1 kW/kg were achieved. The synergistic effect between the highly conductive graphene and the nanoflake Co(OH)₂ structure was responsible for the high electrochemical performance of the hybrid electrode. It is expected that this research could offer a simple method to prepare graphene-based electrode materials.     

开关磁阻电机稳态特性的等效磁网络模型分析方法Ⅰ.数学模型

本文利用开关磁阻电机的等效磁网络模型,推导出了电机绕组满足的以绕组磁链为状态变量的微分方程,建立了电机稳态运行分析的数学模型。本文成功地将非线性磁参数法的思想从单相电流系统推广到了多相电流系统,对开关磁阻电机的理论研究具有重要的意义。