配合参数对单晶炉驱动系统的影响分析

光伏产业的发展使得对硅材料的需求日益增加,同时硅单晶生产行业竞争也日趋激烈。作为生产硅单晶的重要装备,单晶炉的稳定性和可靠性关系到硅单晶生产效率的提升和成本的下降,因此其驱动系统的设计和优化成为装备制造的关键环节。本文以NVT-HG2000-V1型硅单晶生长炉的驱动系统为研究对象,用SolidWorks三维建模实现虚拟装配,采用ADAMS建立其动力学仿真模型,并对驱动系统的运动过程进行仿真模拟。采用控制变量法定量分析了铜套与升降轴的配合间隙及丝杠参数对驱动力和驱动力矩的影响规律,进而在提高硅单晶生长炉装备稳定性和可靠性方面给出合理的技术建议。结果表明,铜套与升降轴的配合间隙达到0.071 mm后能有效降低驱动系统运行所需驱动力矩,丝杠倾斜度、螺纹螺距与螺纹间摩擦系数的增大均会导致驱动系统运行所需力矩大幅增加。     

Dendritic polyurethane-based prodrug as unimolecular micelles for precise ultrasound-activated localized drug delivery

Ultrasound has been recognized as an exciting tool to enhance the therapeutic efficacy in tumor chemotherapy owing to the triggered drug release, facilitated intracellular drug delivery, and improved spatial precision. Aiming for a precise localized drug delivery, novel dendritic polyurethane-based prodrug (DOX-DPU-PEG) was fabricated with a drug content of 18.9% here by conjugating DOX onto the end groups of the functionalized dendritic polyurethane via acid-labile imine bonds. It could easily form unimolecular micelles around 38 nm. Compared with the non-covalently drug-loaded unimolecular micelles (DOX@Ph-DPU-PEG), they showed excellent pH/ultrasound dual-triggered drug release performance, with drug leakage of only 4% at pH 7.4, but cumulative release of 14% and 88% at pH 5.0 without and with ultrasound, respectively. The ultrasound responsiveness was attributed to the unique strawberry-shaped topological structure of the DOX-DPU-PEG, in which DOX was embedded in the skin layer of the hydrophobic DPU cores. With ultrasound, the DOX-DPU-PEG unimolecular micelles possessed enhanced tumor growth inhibition than free DOX but showed no obvious cytotoxicity on the tumor cells without ultrasound. Such feature makes them promising potential for precise localized drug delivery.     

Classical solution for a nonlinear hybrid system modeling combustion in a multilayer porous medium

Combustion processes in porous media have been used by the petroleum engineering industry to extract heavy oil from reservoirs. This study focuses on a one-dimensional nonlinear hybrid system consisting of $n$ reaction–diffusion–convection equations coupled with $n$ ordinary differential equations, which models a combustion front moving through a porous medium with $n$ parallel layers. The state variables are the temperature and fuel concentration in each layer. Coupling occurs in both the reaction function and differential operator coefficients. We prove the existence of a classical solution, first locally and then globally over time, to an initial and boundary value problem for the corresponding system. The proof uses a new approach for combustion problems in porous media. The local solution is obtained by defining an operator in a set of Hölder continuous functions and using Schauder’s fixed-point theorem to find a fixed point as the desired solution. Using Zorn’s lemma, we extend the local solution to a global solution, proving that the first-order spatial derivative of the temperature in each layer is a bounded function.     

突出矿井瓦斯抽放限制影响因素的AHP-熵权法评价模型

为提高煤与瓦斯突出矿井瓦斯抽放效果,建立了3个一级指标、14个二级指标的突出矿井瓦斯抽放限制影响因素评价指标体系,利用AHP和熵权法分别确定指标因子主、客观权重.通过实地调研分析和反馈验证了AHP-熵权法的可行性和正确性,利用加权平均法确定评价模型的综合权重.研究表明:封孔方式、钻孔半径、抽放时间、煤体裂隙发育程度和抽放负压是目前影响煤矿瓦斯抽放效果的主控因素.     

Group mobility assisted network selection framework in 5G vehicular cognitive radio networks

The heterogeneity nature of networks is the most eminent characteristic in 5G vehicular cognitive radio networks across complex radio environments. Since multiple communicating radios may be in motion at the same time in a vehicle. So, group mobility is the most prominent characteristic that requires to be a deep investigation. Therefore, different communication radios that are moving on a train/bus needed to select the networks simultaneously. Without considering the group mobility feature, there is a possibility that the same network may be selected by each moving node and cause congestion in a particular network. To overcome this problem, a novel network selection technique considering the group mobility feature is proposed to improve the throughput of the network. In this work, a 5G vehicular cognitive radio network scenario is also realized using USRP-2954 and LabVIEW communications system design suite testbed. The performance metrics like transmission delay, packet loss rate, reject rate and, channel utilization for vehicular nodes, are gained to analyze the proposed technique in vehicular cognitive radio networks environment. The proposed technique demonstrates a remarkable improvement in channel utilization for vehicular nodes and outperformed conventional schemes.     

Versatile Near-Infrared Super-Resolution Imaging of Amyloid Fibrils with the Fluorogenic Probe CRANAD-2

CRANAD-2 is a fluorogenic curcumin derivative used for near-infrared detection and imaging in vivo of amyloid aggregates, which are involved in neurodegenerative diseases. We explore the performance of CRANAD-2 in two super-resolution imaging techniques, namely stimulated emission depletion (STED) and single-molecule localization microscopy (SMLM), with markedly different fluorophore requirements. By conveniently adapting the concentration of CRANAD-2, which transiently binds to amyloid fibrils, we show that it performs well in both techniques, achieving a resolution in the range of 45–55 nm. Correlation of SMLM with atomic force microscopy (AFM) validates the resolution of fine features in the reconstructed super-resolved image. The good performance and versatility of CRANAD-2 provides a powerful tool for near-infrared nanoscopic imaging of amyloids in vitro and in vivo.