Identifying mutated driver pathways in cancer by integrating multi-omics data

Since the driver pathway in cancer plays a crucial role in the formation and progression of cancer, it is very imperative to identify driver pathways, which will offer important information for precision medicine or personalized medicine. In this paper, an improved maximum weight submatrix problem model is proposed by integrating such three kinds of omics data as somatic mutations, copy number variations, and gene expressions. The model tries to adjust coverage and mutual exclusivity with the average weight of genes in a pathway, and simultaneously considers the correlation among genes, so that the pathway having high coverage but moderate mutual exclusivity can be identified. By introducing a kind of short chromosome code and a greedy based recombination operator, a parthenogenetic algorithm PGA-MWS is presented to solve the model. Experimental comparisons among algorithms GA, MOGA, iMCMC and PGA-MWS were performed on biological and simulated data sets. The experimental results show that, compared with the other three algorithms, the PGA-MWS one based on the improved model can identify the gene sets with high coverage but moderate mutual exclusivity and scales well. Many of the identified gene sets are involved in known signaling pathways, most of the implicated genes are oncogenes or tumor suppressors previously reported in literatures. The experimental results indicate that the proposed approach may become a useful complementary tool for detecting cancer pathways.     

Nonintrusive data-based learning of a switched control heating system using POD,DMD and ANN

The aim of this work is to derive an accurate model of two-dimensional switched control heating system from data generated by a Finite Element solver. The nonintrusive approach should be able to capture both temperature fields, dynamics and the underlying switching control rule. To achieve this goal, the algorithm proposed in this paper will make use of three main ingredients: proper orthogonal decomposition (POD), dynamic mode decomposition (DMD) and artificial neural networks (ANN). Some numerical results will be presented and compared to the high-fidelity numerical solutions to demonstrate the capability of the method to reproduce the dynamics.     

基于支持向量机的模型传递方法研究

模型传递是以数学方法通过在2台不同仪器之间寻求一种变换关系来增强光谱仪数据通用性、可比性的一种基本途径。由于实际测量数据具有非线性特征,加上校正样本集合的有限性,使得解决小样本条件下非线性关系的模型传递问题显得尤为重要。文章在概述支持向量机基本原理的基础上,探讨了支持向量机方法在光谱仪的模型传递问题中的应用,提出了基于支持向量机的分段直接校正方法,最后采用计算机模拟的方式对该方法进行了举例说明,并和人工神经网络方法进行了相应的比较。     

桂花酒中山梨酸钾拉曼表面增强预测模型在其他果酒中的传递

自行搭建的拉曼光谱点扫描系统,以柠檬酸钠还原法配制的SC银溶胶为表面增强剂,建立了桂花酒中山梨酸钾的定量预测模型,模型校正集决定系数(R2_C)和均方根误差(RMSEC)分别为0.978 9和0.070 3 g·kg-1,验证集决定系数(R2_P)和均方根误差(RMSEP)分别为0.934和0.165 7 g·kg-1。桂花酒中山梨酸钾的定量预测模型为主光谱模型,结合K/S算法,探讨了基于DS算法和PDS算法将桂花酒主光谱模型向杨梅酒的修正传递方法。结果显示,用K/S算法选取4个杨梅酒样品,基于DS算法传递桂花酒主光谱模型验证结果R_P和RMSEP值分别为0.906 1和0.215 0 g·kg-1。K/S算法选取3个杨梅酒样品(窗口宽度为5),基于PDS算法传递桂花酒主光谱模型验证结果R_P和RMSEP值分别为0.905 5和0.225 0 g·kg-1。DS算法和PDS算法均可以用少量样品将桂花酒中山梨酸钾的主光谱预测模型有效传递给杨梅酒,实现了一种被测物预测模型在同类物种间的传递,具有重要实用意义。     

New physics hints in B decays and collider outlook

There are currently two hints for new physics involving CP violation in b → s transitions: ΔS ≡ S _f − S _J ^ϕK ≠ 0, and difference in direct CP asymmetry ΔA _Kπ ≡ A _K+π ⁰ − A _K+π ⁻ ≠ 0. We explore the two scenarios with a large and unique new CP phase in b ↔ s transitions. Motivated by ΔS ≠ 0, we update on the right-handed strange-beauty squark sb _1R at TeV scale. Motivated by ΔA _Kπ ≠ 0, we explore sequential fourth generation t′ and b′ quarks. Both scenarios can survive constraints such as SM level b → sγ, sll and B _s mixing, and predict sizable CP violation in B _s mixing. The fourth generation picture predicts sizable K _L → π ⁰ vv. Direct search for sb _R, b′ and t′ at hadronic colliders, such as Tevatron Run II and LHC, can complement further CP violation studies at these machines, as well as at the future Super B factory.     

Short time synthesis of high quality carbon nanotubes with high rates by CVD of methane on continuously emerged iron nanoparticles

We report the variation of yield and quality of carbon nanotubes (CNTs) grown by chemical vapor deposition (CVD) of methane on iron oxide-MgO at 900-1000 °C for 1-60 min. The catalyst was prepared by impregnation of MgO powder with iron nitrate, dried, and calcined at 300 °C. As calcined and unreduced catalyst in quartz reactor was brought to the synthesis temperature in helium flow in a few minutes, and then the flow was switched to methane. The iron oxide was reduced to iron nanoparticles in methane, while the CNTs were growing.TEM micrographs, in accordance with Raman RBM peaks, indicate the formation of mostly single wall carbon nanotubes of about 1.0 nm size. High quality CNTs with I_G/I_D Raman peak ratio of 14.5 are formed in the first minute of CNTs synthesis with the highest rate. Both the rate and quality of CNTs degrades with increasing CNTs synthesis time. Also CNTs quality sharply declines with temperature in the range of 900-1000 °C, while the CNTs yield passes through a maximum at 950 °C. About the same CNTs lengths are formed for the whole range of the synthesis times. A model of continuous emergence of iron nanoparticle seeds for CNTs synthesis may explain the data. The data can also provide information for continuous production of CNTs in a fluidized bed reactor.     

中微子质量和中微子振荡实验

本文介绍中微子质量测量的历史和现状。介绍太阳中微子丢失实验的结果和大气 μ中微子丢失实验结果。这些结果表明存在中微子振荡 ,即中微子具有质量。它是超出标准模型的信号。本文还介绍了 2 1世纪初研究中微子振荡的若干重要实验 ,例如长基线中微子振荡实验以及建造 μ子贮存环来产生高能电子中微子束进行中微子振荡的实验以及测量中微子振荡时的CP破坏的设想。     

Heteroepitaxial praseodymium sesquioxide films on Si(1 1 1): A new model catalyst system for praseodymium oxide based catalysts

The structure, growth and stoichiometry of heteroepitaxial Pr₂O₃ films on Si(1 1 1) were characterized by a combined RHEED, XRD, XPS and UPS study in view of future applications as a surface science model catalyst system. RHEED and XRD confirm the growth of a (0 0 0 1) oriented hexagonal Pr₂O₃ phase on Si(1 1 1), matching the surface symmetry by aligning the oxide in-plane direction along the Si azimuth. After an initial nucleation stage RHEED growth oscillation studies point to a Frank-van der Merwe growth mode up to a thickness of approximately 12 nm. XPS and UPS prove that the initial growth of the Pr₂O₃ layer on Si up to ∼1 nm thickness is characterized by an interface reaction with Si. Nevertheless stoichiometric Pr₂O₃ films of high crystalline quality form on top of these Pr-silicate containing interlayers.     

水稻糙米粗蛋白近红外光谱定量分析模型的优化研究

筛选有代表性的191份糙米样品为试材,其中42份来自国家稻种资源库、149份来自水旱稻杂交产生的DH系,蛋白质含量变幅5.90％～14.50％,采用偏最小二乘法(PLS)建立模型,并构造模型的评价参数——目标函数[R/(1+RMSECV)], 同时借助校正集和验证集两个载荷向量得分二维空间投影图,对近红外定量模型进行评价和优化。结果表明: 在5 000～9 000 cm-1范围内,预处理方法为一阶导数,校正模型和外部检验的目标函数值分别为0.701和0.687;两载荷向量得分直观分布图显示样品的聚类结果与目标函数筛选结果一致,也进一步验证了目标函数是模型评价和优化的有效指标。     

静态傅里叶变换光谱仪的机理及干涉条纹的校正

针对高速、瞬时光谱测量要求光谱仪的结构简单、装备方便、实时性强的特点,文章介绍了一种静态傅里叶变换光谱仪,并对其原理进行了推导与剖析。针对其调整中出现的干涉条纹的倾斜校正问题,进行了详细的理论分析和干涉条纹模型的数学推导,得出倾斜镜旋转参数和光学元件最小通光口径之间的数学关系,以及倾斜镜旋转参数和干涉条纹旋转参数之间的数学关系。通过利用Matlab7.0数学工具,对所总结推导的干涉条纹模型进行模拟,对所得的各种参数之间的数学关系进行验证。分析结果表明据此数学关系所求得的β角校正精度达到1.4%,是一种有效可行的校正方法。