有分压电阻和e偏振非相干背景光辐照的光折变晶体中非相干耦合空间孤子对

为了得到光折变晶体中非相干耦合空间孤子对统一理论的结果,基于单光子光折变空间光孤子的基本理论模型,建立了稳态条件下有分压电阻和e偏振非相干均匀背景光辐照的单光子光伏光折变晶体中非相干耦合空间孤子对理论. 研究表明:这种孤子对是由两束偏振方向和波长都相同的互不相干光束耦合形成的, 孤子对两光束都能在晶体中稳定传播;当分压电阻、e偏振背景光、外加电场和光伏场取不同值时, 可获得14种光折变非相干耦合空间孤子对. 本文的结果对完善和充实光折变空间孤子理论体系有重要意义.     

区间值模糊概率集及其在模式识别中的应用

首次提出区间值模糊概率集(IvFPS)的概念.区间值模糊概率集的矩和其他一些重要性质,以及区间值模糊概率集间的相关性也将得到研究和探讨.最后通过一个实际数例来阐述区间值模糊概率集的相关系数在模式识别中的应用.     

随机森林结合CatBoost的近红外光谱药品鉴别

药品质量关乎人民健康和国家命脉,随着社会经济的飞速发展对药品质量的快速、有效鉴别具有极其重要的作用。光谱分析技术具有较高的准确性、较快的分析速度且对样品不存在污染等突出优点,广泛应用在化工、石油以及医药等重要的领域。为了解决传统药品鉴别模型存在的鉴别精度低、鉴别速度不能满足实际需求且鉴别模型稳定性差的问题,采用光谱仪采集药品的近红外光谱数据达到对药品无污染鉴别的目的。结合随机森林和CatBoost对药品进行分类鉴别,以实现快速且准确的鉴别。首先采用随机森林(RF)对光谱仪采集的光谱数据进行有效特征波长的筛选,从而将药品光谱数据中的无关波长去除、筛选出最能表征样品属性的特征波长,然后以极限学习机(ELM)作为CatBoost的弱分类器分析筛选的特征波长对药品的属性鉴别。由于ELM仅只含有一个隐含层且无需多次迭代寻优保证了鉴别模型运行速度更快,CatBoost通过集成弱分类器以改善模型鉴别准确性。为对所提出的药品鉴别模型性能进行有效评估,采用随机抽取训练集的方式构造不同规模药品光谱数据并分别上进行独立实验且以10次运行结果的均值作为其最终结果,并通过与CatBoost、持向量机(SVM)、...     

Hydrogen Peroxide Sensor Based on Horseradish Peroxidase Combined with CaCO3 Microspheres and Gold Nanoparticles

Direct electrochemistry and electrocatalysis of horseradish peroxidase(HRP) were achieved by entrapping the enzyme between CaCO3 microspheres and gold nanoparticles through forming sandwich configuration (CaCO3-HRP-AuNPs). Polyanion, poly(styrene sulfonate)(PSS), was hybrid with CaCO3 microspheres to increase the surface negative charges for binding with HRP through electrostatic interaction. After the bioconjugate CaCO3 PSS-HRP was entrapped in chitosan based sol-gel(CS-GPTMS) film, HRP was encapsulated by in situ formation of an outer layer of AuNPs through electrochemical reduction of HAuCl4. The composite film containing AuNPs, CaCO3-PSS-HRP bioconjugates and CS-GPTMS can provide favorable microenvironment for HRP to perform direct electron transfer at glassy carbon electrode(GCE). HRP retained its bioelectrocatalytic activity and lead to sensitive and fast amperometric response for the determination of H2O2. H2O2 could be detected in a very wide linear range from 5.0×10–6 mol/L to 7.1×10–2 mol/L. The sandwich configuration of CaCO3-biomolecules-AuNPs could serve as a versatile platform for enzyme immobilization and biosensing.     

近50年鄱阳湖流域降水时空特征及其对水文过程的驱动

依照鄱阳湖流域79个国家气象站的逐月降水资料(1961~2010年),基于BCC-CSM全球气候系统模式预估数据(2014~2050年),对鄱阳湖流域降水变化趋势和空间分布变化趋势进行分析。选取赣江外洲站1961~2010年逐日径流量和1960~2010年年代径流量、输沙量数据,利用HBV水文模型、SPSS统计软件对赣江流域面雨量及径流量进行相关性分析,探讨降水特征对水文过程的驱动性。结果表明:1961~2010年间鄱阳湖流域降水量总体略呈上升趋势,降水日数呈下降趋势,降水强度增加、降水时间分布不均匀性更加明显,旱涝等极端事件发生更为频繁;年内变化特征为分布不均匀,以4~6月为汛期,其中6月降水量最大;空间分布特征总体表现为东部降水大于西部,丘陵地区降水大于平原地区;降水变化为径流量、输沙量变化等水文响应的主要驱动力,赣江流域面雨量及径流量呈显著线性相关,相关系数高达0.909。未来37年降水呈现略上升趋势,但趋势不显著。若鄱阳湖流域长期存在高能源需求及高温室气体排放,则洪涝灾害发生将更为频繁。研究为预测鄱阳湖流域水资源科学管理提供科学依据。     

Hawking Radiation of Charged Particles via Tunne ling from a Cylindrically Symmetric Black Hole in Anti-de Sitter Space-Time

Applying Parikh-Wilzcek‘s semi-classical quantum tunneling model, we study the Hawking radiation of charged particles as tunneling from the event horizon of a cylindrically symmetric black hole in anti-de Sitter space-time.The derived result shows that the tunneling rate of charged particles is related to the change of Bekenstein-Hawking entropy and that the radiation spectrum is not strictly pure thermal after taking the black hole background dynamical and self-gravitation interaction into account, but is consistent with the underlying unitary theory.     

Bernstein算子导数与高阶光滑性

借助于r阶光滑模ωφ^r(f,t)φ是一般的步权函数，给出了Bernstein算子导数与函数高阶光滑性之间的等价关系。     

液相金纳米粒子非线性光散射方程的研究

将激励光与液相金纳米粒子相互作用的运动方程表达为朗之万方程,对金纳米粒子的共振散射、2/3分频共振散射和2倍频共振散射进行了分析,较好地解释了液相金纳米粒子产生的一些非线性散射现象.     

Some Extension Conditions of Iπ Characters

In 1984, Isaacs proposed the theories of Bπ-character and Iπ-character in n-separated group. This paper gives some new extension conditions of Iπcharacters.     

Modeling Evolution of Weighted Clique Networks

We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique (maximal complete sub-graph) at each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges' weight and vertices' strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights' enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices' strength and the distribution of edges' weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices' strength and edges' weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are
consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.