应用结构异质性阈模型定位阈性状基因位点:I理论研究(英文)

结构异质性是在定位阈性状基因位点过程中普遍存在的一个问题 .例如 ,数量遗传学家通常根据连锁分子标记推断性状位点基因型 ,由于性状位点基因型的不确定性 ,一个亲折方差组分被引入阈模型 .针对这个问题 ,我们提出了一个新颖的统计模型并推广到多阈值性状 .在这篇理论文章中 ,我们给出了详细的理论推导和计算策略     

应用结构异质性阈模型定位性状基因位点：I理论研究

结构异质性是在定位阈性状基因位点过程中普遍存在的一个问题。例如,数量遗传学家通常根据锁分子标记推断性状位点的基因型,由于性状位点基因型的不确定性,一个亲折方差组分被引入阈模型,针对这个问题,我们提出了一个新颖的统计模型并推广到多阈值性状。在这篇理论文章中,我们给出了详细的理论推导和计算策略。     

设备空间磁场预测的传感器布阵优化

本文研究了铁磁性设备周围空间传感器布阵的问题。我们建立了关于传感器位置和数量优化的数学模型,并通过遗传算法对模型进行求解。首先,本文选用对传感器数量和距离要求较少的旋转椭球体作为磁场远场换算的模型。在旋转椭球体模型中,传感器分布位置不当会导致磁场计算系数矩阵的条件数过大,模型将出现病态,因而计算得到的远场磁场结果不可靠。所以,本文以旋转椭球体模型中的系数矩阵条件数为优化目标,建立数学模型优化单个设备上方传感器的数量与位置分布,并利用遗传算法对模型求解。其次,通过实验验证了本模型对于单个设备的传感器位置和数量优化是有效的,且所用传感器数量少,计算结果可靠。最后,将单个设备传感器位置和数量的优化模型推广到多个设备,以两个设备为代表用同时优化和分别优化两种方法计算传感器位置,根据实验计算这两种方法都具有较高的远场磁场计算精度,但分开优化的方法在实际计算更加简便、容易操作。     

具有遗传性疾病和性状的遗传位点分析

随着信息技术的进步和发展,现代生物学越来越多地将这些技术用于大规模生物数据的收集、分析、挖掘等过程.大量计算机技术,特别是统计方法被用来进行复杂疾病的分析.大量研究表明,人体的许多表型性状差异以及对药物和疾病的易感性等都可能与某些位点相关联,或和包含有多个位点的基因相关联.因此,定位与性状或疾病相关联的位点在染色体或基因中的位置,能帮助研究人员了解性状和一些疾病的遗传机理,也能使人们对致病位点加以干预,防止一些遗传病的发生.利用随机森林方法、Bootstrap重抽样、logistic回归等大数据分析方法,意在解决优化生物学位点关联性分析中单一致病位点识别、多位点相互作用和多性状位点关联性分析等子问题.     

中等稀疏条件下基因交互作用的两步Bayes方法

植物遗传与基因组学研究表明许多重要的农艺性状有影响的基因位点不是稀疏的,受到大量微效基因的影响,并且还存在基因交互项的影响.本文基于重要油料作物油菜的花期数据,研究中等稀疏条件下的基因选择问题,提出了一种两步Bayes模型选择方法.考虑基因间的交互作用,模型的维数急剧增长,加上数据结构特别,通常的变量选择方法效果不好.本文提出两步变量选择的方法:首先利用Kolmogorov特征扫描方法筛除那些明显不重要的变量,达到降维的目的;其次,在选出的位点中考虑交互作用.为了克服Bayes方法计算速度慢的问题,本文在模型中引入指示变量,通过估计指示变量的后验分布选择模型.模拟结果表明本文提出的方法在预测精度和计算稳定性上有良好的表现,与不加指示变量的Bayes方法相比,在预测精度上有很大的提高.最后,利用本文提出的方法分析一个油菜花期数据,发现了一些交互效应的基因位点.     

发现并定位黄球

本文讨论了如何设置红球和蓝球的数量和位置,发现圆柱区域内的黄球并进行定位的问题.我们考虑了一对红球蓝球发现黄球并定位的问题,在此基础上进行扩展,基本解决了黄球的发现并定位的问题.在静止黄球发现问题中,采用了正三角形扩展和正六边形扩展两种方法.在静止黄球的定位问题中,我们结合正三角形和正六边形运用了旋转法和添点法进行扩展.在运动黄球的定位问题中,讨论了体积概率模型和时间概率模型,给出了两种模型的概率求解公式.在系统协同定位模型中,我们给出了发现定位分步模型和周期系统跟踪模型,其中后者在仿真中实现了大于80%的定位性能,该系统可以简单扩展为多目标快速定位问题.此外,文章讨论了精确测量和颜色切换模型,快速定位问题,多目标定位等问题.     

供给总量限定需求区间约束型运输问题——时限费用优化模型与算法

本文目的是为建立与运输问题有关的决策支持系统提供方便.本文建立了供给总量限定需求区间约束型运输问题的对时限与费用两个目标进行优化的多目标规划模型,给出了求解模型的算法,并举例说明了算法的应用.该算法能求得问题的最优解,并具有易于编程实现、收敛性好等优点.数值实验表明该算法有较高的计算效率,可用于求解某些类型的指派问题.     

基于虚拟变形法的供水管网漏损定位方法

针对供水管网的漏损探测与定位问题,采用虚拟变形法对管网各参数进行计算,通过漏损影响矩阵和流量影响矩阵来表征管网的状态,并提出了漏损探测定位的优化计算模型.由于管网漏损点数量事先难以预先获取,提出了基于贝叶斯理论的管网漏损探测、定位模型,并结合Matlab和Epanet编制了相应的优化计算程序,数值仿真结果验证了方法的有效性和可行性.     

基于统计检验与机器学习的全基因组关联研究框架

采用统计检验和机器学习的方法来研究SNP或基因与疾病(可测性状)的关联性.先对SNP选择合适的数值编码方式,并设计了相应的统计检验流程,随后通过P值初步筛选出了与疾病或性状相关联的位点.在此基础上,对筛选出的位点,采用随机森林,XGBoost等机器学习方法,从样本外预测的角度判断SNP与疾病或性状的关联度.相关结果,显示发现运用该分析框架能较好地筛选出与疾病或性状关联的SNP(基因).并且框架由于考虑了多种分类模型,有着稳健性高,计算开销较小以及可以交叉比对等优势.框架未来在还可在金融,社交网络等方面发挥作用.     

数量特征敏感性问题随机化回答的改进模型

研究数量特征敏感性问题的调查方法,设计了一种数量特征敏感性问题的随机化回答改进模型,计算了改进模型的估计量及其方差,并对改进模型进行了分析,得出改进模型具有较好的精度。     

Empirical likelihood inference for censored median regression with weighted empirical hazard functions

In recent years, median regression models have been shown to be useful for analyzing a variety of censored survival data in clinical trials. For inference on the regression parameter, there have been a variety of semiparametric procedures. However, the accuracy of such procedures in terms of coverage probability can be quite low when the censoring rate is heavy. In this paper, based on weighted empirical hazard functions, we apply an empirical likelihood (EL) ratio method to the median regression model with censoring data and derive the limiting distribution of EL ratio. Confidence region for the regression parameter can then be obtained accordingly. Furthermore, we compared the proposed method with the standard method through extensive simulation studies. The proposed method almost always outperformed the existing method.     

An optimal control model of oil discovery and extraction

Starting with Hotelling (1931) [7] the stock of non-renewable resources have been treated as fixed. Along the line of Pindyck (1978) [8] and Greiner and Semmler (in press) [5] we treat the stock of oil resources as time varying, depending on new discoveries. The resource is finite and only a part of the resource is known while the rest has not yet been discovered. The discovery leads to a rise of known oil resource which can then be optimally exploited. The optimal control model has two state variables, the known stock of the resource and the cumulated past extraction. The control variable is the optimal extraction rate. The optimal control model assumes a monopolistic resource owner who maximizes intertemporal profits from exploiting the resource where the price of the resource depends on the extraction rate, the known stock of the resource, and the cumulated past extraction. The model is solved for a finite time horizon using NUDOCCCS, a numerical solution method to solve finite horizon optimal control problems. Various parameter constellations are explored. For certain parameter constellations the price path becomes U-Shaped as some empirical research, see Greiner and Semmler (in press) [5], have found to hold for actual price data. This holds if the stock of the initially known resource is small.     

A direct search method for determination of DAEM kinetic parameters from nonisothermal TGA data (note)

In this study, a simple direct search method to be used for the determination of distributed activation energy model (DAEM) kinetic parameters from the nonisothermal thermogravimetric analysis (TGA) data of coals has been introduced. Process steps of direct search method that depends on the grid technique have been given. The method has been applied to the nonisothermal TGA data of one Turkish coal and one imported coal, and DAEM kinetic parameters of these coal samples have been determined. Calculated model results from determined kinetic parameters have been compared with nonisothermal TGA data of the coals.     

A discrete epidemic model for SARS transmission and control in China

Severe acute respiratory syndrome (SARS) is a rapidly spreading infectious disease which was transmitted in late 2002 and early 2003 to more than 28 countries through the medium of international travel. The evolution and spread of SARS has resulted in an international effort coordinated by the World Health Organization (WHO).

We have formulated a discrete mathematical model to investigate the transmission of SARS and determined the basic reproductive number for this model to use as a threshold to determine the asymptotic behavior of the model. The dependence of the basic reproductive number on epidemic parameters has been studied. The parameters of the model have been estimated on the basis of statistical data and numerical simulations have been carried out to describe the transmission process for SARS in China. The simulation results matches the statistical data well and indicate that early quarantine and a high quarantine rate are crucial to the control of SARS.     

Linearized Alternating Direction Method of Multipliers for Separable Convex Optimization of Real Functions in Complex Domain

The alternating direction method of multipliers (ADMM) for separable convex optimization of real functions in complex variables has been proposed recently[21]. Furthermore, the convergence and $O(1/K)$ convergence rate of ADMM in complex domain have also been derived[22]. In this paper, a fast linearized ADMM in complex domain has been presented as the subproblems do not have closed solutions. First, some useful results in complex domain are developed by using the Wirtinger Calculus technique. Second, the convergence of the linearized ADMM in complex domain based on the VI is established. Third, an extended model of least absolute shrinkage and selectionator operator (LASSO) is solved by using linearized ADMM in complex domain. Finally, some numerical simulations are provided to show that linearized ADMM in complex domain has the rapid speed.     

油田高含水期稳产措施配置多层目标规划

措施规划对于延长油田稳产年限 ,提高采油速度及提高最终采收率是十分必要的 .有些学者建立了油田稳产措施规划的整体或区块规划模型 ,但没有考虑实际油田生产各生产层系的地质特性和所采取措施的差别 .本文针对油田开发实际中存在多层现象 ,以区块的各个生产层为基础 ,建立了油田措施的多层目标规划模型 ,并采用合理的算法进行求解 .应用结果表明 ,多层目标规划使措施配置更精细 ,更能反映生产实际 ,是解决油田措施配置问题的一项有力工具     

Some effects of aircraft arrival sequence algorithms

Although various airport landing sequencing algorithms have been considered in the literature, little work has been done in comparing their effects on Air Traffic Control, especially against first-come first-served (FCFS) runway sequences, the method most widely used in practice. This paper compares a number of such algorithms using a discrete-event simulation model of an airport with a single landing runway. Statistical methods are used to test for effects of sequencing algorithm, delay-sharing strategy, arrival rate and wake-vortex mix. Little benefit to delay, or stability of sequencing advice, is found from advanced sequencing when small changes are made to inputs calibrated to a specific airspace. Advanced sequencing improves landing rate, compared with FCFS sequencing, only when aircraft arrival rate is greater than maximum runway landing rate, and wake-vortex mix is sufficiently varied. Constrained position shifting constraints limit these improvements and it is shown that deterministic optimal techniques may actually be sub-optimal in a dynamic environment. Our main conclusion is that FCFS is a robust method under many conditions.     

Neural firing rate model with a steep firing rate function

In this study we justify rigorously the approximation of the steep firing rate functions with a unit step function in a two-population neural firing rate model with steep firing rate functions. We do this justification by exploiting the theory of switching dynamical systems. It has been demonstrated that switching dynamics offer a possibility of simplifying the dynamical system and getting approximations of the solution of the system for any specific choice of parameters. In this approach the phase space of the system is divided into regular and singular domains, where the limit dynamics can be written down explicitly. The advantages of this method are illustrated by a number of numerical examples for different cases of the singular domains (i.e. for black, white and transparent walls) and for specific choices of the parameters involved. General conditions have been formulated on these parameters to give black, white and transparent walls. Further, the existence and stability of regular and singular stationary points have been investigated. It has been shown that the regular stationary points (i.e. stationary points inside the regular domains) are always stable and this property is preserved for smooth and sufficiently steep activation functions. In the most technical part of the paper we have provided conditions on the existence and stability of singular stationary points (i.e. those belonging to the singular domains). For the existence results, the implicit function theorem has been used, whereas the stability of singular stationary points is addressed by applying singular perturbation analysis and the Tikhonov theorem.     

A semiparametric panel approach to mortality modeling

During the past twenty years, there has been a rapid growth in life expectancy and an increased attention on funding for old age. Attempts to forecast improving life expectancy have been boosted by the development of stochastic mortality modeling, for example the Cairns–Blake–Dowd (CBD) 2006 model. The most common optimization method for these models is maximum likelihood estimation (MLE) which relies on the assumption that the number of deaths follows a Poisson distribution. However, several recent studies have found that the true underlying distribution of death data is overdispersed in nature (see Cairns et al. 2009 and Dowd et al. 2010). Semiparametric models have been applied to many areas in economics but there are very few applications of such models in mortality modeling. In this paper we propose a local linear panel fitting methodology to the CBD model which would free the Poisson assumption on number of deaths. The parameters in the CBD model will be considered as smooth functions of time instead of being treated as a bivariate random walk with drift process in the current literature. Using the mortality data of several developed countries, we find that the proposed estimation methods provide comparable fitting results with the MLE method but without the need of additional assumptions on number of deaths. Further, the 5-year-ahead forecasting results show that our method significantly improves the accuracy of the forecast.     

Properties of simple model problems for reacting gas flows

The compressible Navier–Stokes equations for reacting gases are extremely complex. Simpler models have been considered, and for these completely non-physical propagation speeds have been observed. These model problems are stiff, meaning that several different scales are present in the solution. Numerical solution of non-reacting flows almost always involves addition of extra dissipation. It will be shown that this action will render a totally wrong propagation speed for a simple model equation of reacting flows. This problem will be accentuated by increasing stiffness of the problem. Existence and uniqueness of a solution to this model equation is proved. The dependence of the propagation speed on the viscosity and a term governing the stiffness (comparable to the reaction rate for a more complete model) is investigated. A remedy for the wrong propagation speed for this simple model equation is proposed such that the speed is correct although the front is smeared out.