A statistical model for global optimization by means of select and clone

A statistical model tor giobai optimization is constructed generalizing some properties ofthe Wiener process to the multidimensional case. A new approach, which is similar to the Branch and Bound approach, is proposed to the construction of algorithms based on statistical models. A two dimensional version of the algorithm is implemented, and test results are presented     

Investigation of quadrature imbalance compensation algorithm for coherent 6PolSK-QPSK

6PolSK-QPSK is a promising modulation format in optical fiber communication. Because of the damage suffered during the transmission and reception, a series of algorithms are needed to be adopted to recover the original data. We proposed a novel quadrature imbalance compensation algorithm based on the data statistical properties. Simulation results show that the quadrature imbalance can be well compensated with the proposed algorithm.     

Statistical discrimination of steroid profiles in doping control with support vector machines

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society.     

A re-examination of platinum-group element concentrations in the environmental certified reference material BCR-723

A detailed statistical examination of replicated data used to certify platinum-group elements (PGEs) in environmental reference material BCR-723 is presented. Certification of Pt, Pd, and Rh concentrations in BCR-723 was based on 16, eight, and nine accepted data sets, respectively. Each accepted data set contained six replicated measurements for each PGE, and the statistical properties of these concentration data were examined, i.e. 96 for Pt, 48 for Pd, and 54 for Rh. This level of investigation has received limited attention but is critical in furthering our understanding of PGE variability and representativeness. Concentrations of Pt, Pd, and Rh were shown to differ significantly between accepted data sets. Palladium and Pt differed in their quantification between detection techniques. Additionally, Pd and Pt concentrations varied significantly between laboratories using a similar definitive method (inductively coupled plasma-isotope dilution mass spectrometry). The distribution of Pd concentrations was found to be bimodal, with a secondary population exhibiting a contamination signal of about 15%. The secondary population, not previously reported in BCR-723, is likely a measurement artifact and not due to a nugget effect. Comparisons of BCR-723 with other environmental media from Europe, i.e. airborne particulate matter, tunnel dust, and road-deposited sediment, indicated that Pd is uncommonly low in BCR-723 (6.0?ng?g^?1) and is generally not representative in terms of its distribution relative to Pt and Rh. Serious consideration should be given to developing a new PGE certified environmental reference material.     

END样本最近邻密度估计的强相合速度

本文研究了扩展负相依(END)样本最近邻密度估计的强相合性问题.利用END序列的Bernstein型不等式和截尾的方法,获得了END样本最近邻密度估计的强相合速度,推广了NA样本和ND样本最近邻密度估计的相应结果.     

Estimation of rating classes and default probabilities in credit risk models with dependencies

Let Y = m(X) + ε be a regression model with a dichotomous output Y and a one‐step regression function m . In the literature, estimators for the three parameters of m , that is, the breakpoint θ and the levels a and b , are proposed for independent and identically distributed (i.i.d.) observations. We show that these standard estimators also work in a non‐i.i.d. framework, that is, that they are strongly consistent under mild conditions. For that purpose, we use a linear one‐factor model for the input X and a Bernoulli mixture model for the output Y . The estimators for the split point and the risk levels are applied to a problem arising in credit rating systems. In particular, we divide the range of individuals' creditworthiness into two groups. The first group has a higher probability of default and the second group has a lower one. We also stress connections between the standard estimator for the cutoff θ and concepts prevalent in credit risk modeling, for example, receiver operating characteristic. Copyright © 2014 John Wiley & Sons, Ltd.     

Scattering problem with nonlocal separable potential of rank-two: Application to statistical mechanics

In this paper, we present a formulation of statistical mechanics of a thermodynamic system consisting of free particles and independent correlated pairs interacting via nonlocal potential in terms of the scattering properties. Some quantum statistical properties such as energy, heat capacity, second virial coefficient, virial pressure and quantum correction of kinetic energy are described analytically. The difference between the resolvents of the interacting and free Hamiltonians, represented as , that is associated with particle correlations is used for the evaluation of the properties. The statistical properties are related to correlated states, when making a pole expansion of the analytically continued momentum matrix element of . The present work illustrates these relations for a three-dimensional nonlocal separable potential of rank-two.     

教学评一致性视域下金属单元复习课的实践*

分析金属知识在中考和教材中的地位,针对当前单元复习教学中存在的问题,依据教学评一致性原则,将“金属知识”的单元复习在“订书钉”为主要线索的探究活动中展开,以此激发学生的学习兴趣,优化学生单元知识结构,发展学生分析问题、解决问题的能力,同时提高学生对学科价值的认识。     

Identifying critical states of hepatocellular carcinoma based on landscape dynamic network biomarkers

Hepatocellular carcinoma (HCC) is the major histological form of primary liver cancer. It has usually reached the disease state once the patient is diagnosed since there are no specific symptoms in the early stages of HCC. This fact increases the difficulty of curing HCC. Recently, quantities of evidence have shown that many mathematical methods (such as dynamic network biomarkers, DNB) can be used to detect critical states or tipping points of complex diseases. However, it is difficult to apply the DNB theory to the clinic since multiple samples are generally unavailable for individual patient. This paper constructs a novel method based on landscape dynamic network biomarkers (L-DNB), which aims to detect early warning signals from cirrhosis state to very advanced HCC state in individual patient. The selected dataset contains multiple samples for each HCC state. A score that indicates the disease characteristics is calculated for each sample by RNA-seq data, and several scores constitute a distribution in the same state. Quantifying the statistical characteristics of these distributions and determining that low-grade dysplastic and high-grade dysplastic are the critical states of HCC. These results can provide scientific advice for early warning indicators and optimal treatment time for HCC.