Non parametric estimation of the diffusion coefficients of a diffusion with jumps

In this article, we consider a jump diffusion process ${\left(X_t\right)}_{t\ge 0}$, with drift function $b$, diffusion coefficient $\sigma$ and jump coefficient ${\xi }^2$. This process is observed at discrete times $t=0,\Delta ,\dots ,n\Delta$. The sampling interval $\Delta$ tends to 0 and the time interval $n\Delta$ tends to infinity. We assume that ${\left(X_t\right)}_{t\ge 0}$ is ergodic, strictly stationary and exponentially $\beta$-mixing. We use a penalized least-square approach to compute adaptive estimators of the functions ${\sigma }^2+{\xi }^2$ and ${\sigma }^2$. We provide bounds for the risks of the two estimators.     

直觉模糊模型检测在工程决策上的应用

将直觉模糊Kripke结构扩展到加权直觉模糊Kripke结构,将直觉模糊计算树逻辑诱导到加权直觉模糊计算树逻辑;研究在此之上的直觉模糊期望测度和多属性工程决策问题。用加权直觉模糊Kripke结构的权值自然地刻画了工程问题中的成本和收益,直觉模糊测度量化工程进展的不确定性,用加权直觉模糊计算树逻辑描述不确定性工程属性约束。给出了基于直觉模糊模型检测的多属性工程寻优算法,并讨论了算法的复杂度。     

Muon g-2 discrepancy:new physics or a relatively light Higgs?

After a brief review of the muon g-2 status,we discuss hypothetical errors in the Standard Model prediction that might explain the present discrepancy with the experimental value.None of them seems likely.In particular,a hypothetical increase of the hadroproduction cross section in low-energy e+e-collisions could bridge the muon g-2 discrepancy,but it is shown to be unlikely in view of current experimental error estimates.If,nonetheless,this turns out to be the explanation of the discrepancy,then the 95% CL upper bound on the Higgs boson mass is reduced to about 135 GeV which,in conjunction with the experimental 114.4 GeV 95%CL lower bound,leaves a narrow window for the mass of this fundamental particle.     

Reactivity profiles of ligands of mammalian retinoic acid receptors: A preliminary COREPA analysis

Retinoic acid and associated derivatives comprise a class of endogenous hormones that bind to and activate different families of retinoic acid receptors (RARs, RXRs), and control many aspects of vertebrate development. Identification of potential RAR and RXR ligands is of interest both from a pharmaceutical and toxicological perspective. The recently developed COREPA (COmmon REactivity PAttern) algorithm was used to establish reactivity profiles for a limited data set of retinoid receptor ligands in terms of activation of three RARs ( f , g , n ) and an RXR ( f ). Conformational analysis of a training set of retinoids and related analogues in terms of thermodynamic stability of conformers and rotational barriers showed that these chemicals tend to be quite flexible. This flexibility, and the observation that relatively small energy differences between conformers can result in significant variations in electronic structure, highlighted the necessity of considering all energetically reasonable conformers in defining common reactivity profiles. The derived reactivity patterns for three different subclasses of the RAR ( f , g , n ) were similar in terms of their global electrophilicity (nucleophilicity) and steric parameters. However, the profile of active chemicals with respect to interaction with the RXR- f differed qualitatively from that of the RARs. Variations in reactivity profiles for the RAR versus RXR families would be consistent with established differences in their affinity for endogenous retinoids, likely reflecting functional differences in the receptors.     

A model validation and consensus building environment

Over half of the failures in drug development are due to problems with the absorption, distribution, metabolism, excretion, and toxicity, or ADME/Tox properties of a candidate compound. The utilization of in silico tools to predict ADME/Tox and physicochemical properties holds great potential for reducing the attrition rate in drug research and development, as this technology can prioritize candidate compounds in the pharmaceutical R&D pipeline. However, a major concern surrounding the use of in silico ADME/Tox technology is the reliability of the property predictions. Bio-Rad Laboratories, Inc. has created a computational environment that addresses these concerns. This environment is referred to as KnowItAll®. Within this platform are encoded a number of ADME/Tox predictors, the ability to validate these predictors with/without in-house data and models, as well as build a ‘consensus’ model that may be a much better model than any of the individual predictive model. The KnowItAll® system can handle two types of predictions: real number and categorical classification.     

Nature of Alkali- and Coinage-Metal Bonds versus Hydrogen Bonds

We have quantum chemically studied the structure and nature of alkali- and coinage-metal bonds (M-bonds) versus that of hydrogen bonds between A−M and B⁻ in archetypal [A−M⋅⋅⋅B]⁻ model systems (A, B=F, Cl and M=H, Li, Na, Cu, Ag, Au), using relativistic density functional theory at ZORA-BP86-D3/TZ2P. We find that coinage-metal bonds are stronger than alkali-metal bonds which are stronger than the corresponding hydrogen bonds. Our main purpose is to understand how and why the structure, stability and nature of such bonds are affected if the monovalent central atom H of hydrogen bonds is replaced by an isoelectronic alkali- or coinage-metal atom. To this end, we have analyzed the bonds between A−M and B⁻ using the activation strain model, quantitative Kohn-Sham molecular orbital (MO) theory, energy decomposition analysis (EDA), and Voronoi deformation density (VDD) analysis of the charge distribution.     

Study of ozone generation in an atmospheric dielectric barrier discharge reactor

Ozone (O₃) generation in a dielectric barrier discharge (DBD) reactor driven by a pulsed power supply was investigated at atmospheric pressure and room temperature. An O₃ generation efficiency model is established in which discharge power, O₂ concentration, gas flow rate, and volume of the discharge space are included. Constants in the O₃ generation efficiency model were obtained by fitting the model with experiment results. O₃ concentration can be simply calculated from the energy density and initial O₂ concentration. Comparison on O₃ concentrations from calculation with references is given.     

基于GA的主汽温系统内模控制研究

主汽温控制系统是典型的大迟延、大惯性、时变控制系统,一直以来都是火电厂自动控制的难点。为此将内模控制引入主汽温控制系统,并提出采用遗传算法对滤波器参数优化整定,该方法简单易行,相较于传统PID参数整定方法具有一定的优越性。并对内模控制为主控制器的IMC-PI控制系统进行SIMULINK仿真,与PID-PI控制系统进行对比,仿真结果表明IMC-PID控制系统相比于传统PID-P串级控制系统过渡时间短、超调量小、鲁棒性好等特点。其控制效果好于常规串级 PID 控制系统,适用于大迟延、大惯性过程的控制,并且易于在工业上实现。     

A novel graphene nanoribbon field effect transistor with two different gate insulators

In this paper, a novel structure for a dual-gated graphene nanoribbon field-effect transistor (GNRFET) is offered, which combines the advantages of high and low dielectric constants. In the proposed Two Different Insulators GNRFET (TDI-GNRFET), the gate dielectric at the drain side is a material with low dielectric constant to form smaller capacitances, while in the source side, there is a material with high dielectric constant to improve On-current and reduce the leakage current. Simulations are performed based on self-consistent solutions of the Poisson equation coupled with Non-Equilibrium Green's Function (NEGF) formalism in the ballistic regime. We assume a tight-binding Hamiltonian in the mode space representation. The results demonstrate that TDI-GNRFET has lower Off-current, higher On-current and higher transconductance in comparison with conventional low-K GNRFET. Furthermore, using a top-of-the-barrier two-dimensional circuit model, some important circuit parameters are studied. It is found that TDI-GNRFET has smaller capacitances, lower intrinsic delay time and shorter power delay product (PDP) in comparison with high-K GNRFET. Moreover, mobile charge and average velocity are improved in comparison with low dielectric constant GNRFET. The results show that the TDI-GNRFET can provide Drain Induced Barrier Lowering (DIBL) and Subthreshold Swing near their theoretical limits.     

液-固色谱流动相体积分数层次结构模型与保留值的关系

用液-固色谱流动相"假定"的体积分数层次结构模型,可得到质点团溶解溶质时的体积分数,进而得到共溶剂中溶质的溶解度、固定相上的溶质吸附量,从而推导出多元流动相组成与溶质保留值的关系.如三元流动相与溶质保留值的关联式为:lnk'=φB3lnk'B3 φB2lnk'B2 φB1lnk'B1 φB1(φB20.5 φB30.5)ln(q)(外Ⅱ) φB30.5φB21.0φB11.5ln(q)(外Ⅰ),经实验数据拟合,本式较其他关联式略胜一筹.