稀土上转换发光纳米材料的防伪安全应用

与有机荧光染料、量子点等传统发光材料相比,稀土上转换发光纳米材料(UCNPs)具有反斯托克斯位移大、发光谱带多且狭窄、荧光寿命长、光化稳定性高、无光闪烁和光漂白等独特优势,将其与图形编码、防伪印刷技术结合可获得难以仿冒的隐形荧光图案,这已经成为防伪安全领域的应用研究热点。本文首先介绍了UCNPs的上转换发光机理及其合成方法,然后阐述近年来UCNPs在防伪安全领域的研究现状,归纳总结出上转换防伪安全图案的四种形式(NIR单波长激发、NIR双波长激发、NIR/UV双波长激发以及三波长激发)。最后,本文指出UCNPs应用于防伪安全领域所面临的问题与挑战,并对未来的发展方向进行了展望。     

高温熔体表面张力测量方法的进展

高温熔体表面现象在冶金、化工、熔盐和材料科学等领域十分普遍。测量高温熔体表面张力有着重要的意义。本文评述了高温熔体表面张力的测量原理和方法。并简述了当前关于高温熔体表面现象以及相关的微重力科学的研究进展。     

近代历史海图集编制的特殊原则和方法

本文讨论了近代历史海图集及其编制的了'}i夕殊问题,主要有近代历史海图集的功能与编辑方针、数学基础的选择、图集结构的总体设计以及若干特殊图载要素的技术处:理、它们已在浙江海区近代历史海图集的编制中得到应用和验证,并对我国其它海尽近代历史海图集的编制具有参考价值.     

Machine-Learning-Enabled Virtual Screening for Inhibitors of Lysine-Specific Histone Demethylase 1

A machine learning approach has been applied to virtual screening for lysine specific demethylase 1 (LSD1) inhibitors. LSD1 is an important anti-cancer target. Machine learning models to predict activity were constructed using Morgan molecular fingerprints. The dataset, consisting of 931 molecules with LSD1 inhibition activity, was obtained from the ChEMBL database. An evaluation of several candidate algorithms on the main dataset revealed that the support vector regressor gave the best model, with a coefficient of determination (R2) of 0.703. Virtual screening, using this model, identified five predicted potent inhibitors from the ZINC database comprising more than 300,000 molecules. The virtual screening recovered a known inhibitor, RN1, as well as four compounds where activity against LSD1 had not previously been suggested. Thus, we performed a machine-learning-enabled virtual screening of LSD1 inhibitors using only the structural information of the molecules.     

Dynamics of a Deterministic and Stochastic Susceptible-exposed-infectious-recovered Epidemic Model

We investigate a susceptible-exposed-infectious-recovered (SEIR) epidemic model with asymptomatic infective individuals. First, we formulate a deterministic model, and give the basic reproduction number $\mathcal{R}_{0}$. We show that the disease is persistent, if $\mathcal{R}_{0}>1$, and it is extinct, if $\mathcal{R}_{0}<1$. Then, we formulate a stochastic version of the deterministic model. By constructing suitable stochastic Lyapunov functions, we establish sufficient criteria for the extinction and the existence of ergodic stationary distribution to the model. As a case, we study the COVID-19 transmission in Wuhan, China, and perform some sensitivity analysis. Our numerical simulations are carried out to illustrate the analytic results.