Germline gain-of-function mutations in SOS1 cause Noonan syndrome

Noonan syndrome, the most common single-gene cause of congenital heart disease, is characterized by short stature, characteristic facies, learning problems and leukemia predisposition. Gain-of-function mutations in PTPN11, encoding the tyrosine phosphatase SHP2, cause approximately 50% of Noonan syndrome cases. SHP2 is required for RAS-ERK MAP kinase (MAPK) cascade activation, and Noonan syndrome mutants enhance ERK activation ex vivo and in mice. KRAS mutations account for <5% of cases of Noonan syndrome, but the gene(s) responsible for the remainder are unknown. We identified missense mutations in SOS1, which encodes an essential RAS guanine nucleotide-exchange factor (RAS-GEF), in approximately 20% of cases of Noonan syndrome without PTPN11 mutation. The prevalence of specific cardiac defects differs in SOS1 mutation-associated Noonan syndrome. Noonan syndrome-associated SOS1 mutations are hypermorphs encoding products that enhance RAS and ERK activation. Our results identify SOS1 mutants as a major cause of Noonan syndrome, representing the first example of activating GEF mutations associated with human disease and providing new insights into RAS-GEF regulation.     

基于构件建造信息系统的自适应体系结构

本文基于Ｈ．Ａ．Ｓｉｍｏｎ的决策认知过程分析,提出了一种用构件组装方式产生适应不同需求的信息系统。为了提高研制效率,给出了信息系统及其构件的形式化描述。在软件集成块 Ｓｏｆｔｗａｒｅ－ＩＣ的思路影响下提出了一种系统构成的自组织方法。     

Fuzzy Filter Design for Affine Systems with Sensor Faults: A Dynamic Event-Triggered Approach

This study addresses the issue of dynamic event-triggered-based filtering for fuzzy affine systems. To alleviate the utilization of constraint bandwidth resources and improve the efficiency of the signals exchange, a dynamic event-triggered protocol is forwarded to regulate the trigger instants with objective system states. Meanwhile, the nonhomogeneous Markov process is proposed to characterize the dynamic behaviors of sensor faults, where the time-varying transition probabilities belong to a c...     

Single-Index Quantile Regression with Left Truncated Data

The purpose of this paper is two fold. First, the authors investigate quantile regression(QR) estimation for single-index QR models when the response is subject to random left truncation.The random weights are introduced to deal with left truncated data and the associated iteration estimation method is proposed. The asymptotic properties for the proposed QR estimates of the index parameter and unknown link function are both obtained. Further, by combining the QR loss function and the adaptive LA...     

A new adaptive state space construction method for the mobile robot navigation

In order to solve the combinative explosion problems in a continuous and high dimensional state space, a function approximation approach is usually used to represent the state space. The normalized radial basis function （NRBF） was adopted as the local function approximator and a kind of adaptive state space construction strategy based on the NRBF （ASC-NRBF） was proposed, which enables the system to allocate appropriate number and size of the basis functions automatically. Combined with the reinforce- ment learning method, the proposed ASC-NRBF method was applied to the robot navigation problem. Simulation results illustrate the performance of the proposed method.     

Parallel Optimization of the Crystal-KMC on Tianhe-2

The Kinetic Monte Carlo(KMC) is one of the commonly used methods for simulating radiation damage of materials. Our team develops a parallel KMC software named Crystal-KMC, which supports the Embedded Atom Method(EAM) potential energy and utilizes the Message Passing Interface(MPI) technology to simulate the vacancy transition of the Copper(Cu) element under neutron radiation. To make better use of the computing power of modern supercomputers, we develop the parallel efficiency optimization model for the Crystal-KMC on Tianhe-2, to achieve a larger simulation of the damage process of materials under irradiation environment. Firstly, we analyze the performance bottleneck of the Crystal-KMC software and use the MIC offload statement to implement the operation of key modules of the software on the MIC coprocessor. We use Open MP to develop parallel optimization for the Crystal-KMC, combined with existing MPI inter-process communication optimization, finally achieving hybrid parallel optimization. The experimental results show that in the single-node CPU and MIC collaborative parallel mode, the speedup of the calculation hotspot reaches 30.1, and the speedup of the overall software reaches 7.43.     

MADDPG算法并行优先经验回放机制

多智能体深度确定性策略梯度(multi-agent deep deterministic policy gradient,MADDPG)算法是深度强化学习方法在多智能体系统(multi-agent system,MAS)领域的重要运用,为提升算法性能,提出基于并行优先经验回放机制的MADDPG算法.分析算法框架及训练方...     

核桃青皮主要活性物质及提取工艺研究进展

核桃青皮中含有多种活性物质,具有抑菌、杀虫、抗病毒等多种功效,然而其成分含量、提取工艺、检测技术存在差异。本文归纳整理了国内外与青皮主要活性物质的相关文献,综述其主要的有效成分、提取工艺、检测技术,为优化核桃青皮主要有效成分的提取工艺、进一步开发核桃青皮资源高效利用提供科学依据。     

基于有序Logistic回归模型的北京高校男生有氧能力

为探索北京高校男生有氧能力的影响因素,通过随机抽样法抽取134名18~25岁北京高校男生,空腹抽静脉血测血液指标,用德国MetaMax 3B系统实时监测气体代谢,通过线性递增方案测得VO2max相对值。基于Spearman相关、有序Logistic回归等分析方法进行分析处理。结果表明：北京高校男生有序Logistic回归方程：Ln{P(Y≤1|x)/1-P(Y≤1|x)}=-2.757-0.067*X1-0.025*X2+0.066*X3+0.018*X4-0.009*X5;Ln{P(Y≤2|x)/1-P(Y≤2|x)}=-0.771-0.067*X1-0.025*X2+0.066*X3+0.018*X4-0.009*X5（X1=体重、X2=心率(heart rate, HR)、X3=每搏输出量(stroke volume, SVI)、X4=心室射血时间(ventricular ejection time, VET)、X5=血红蛋白(hemoglobin, HGB)）。回归方程模型系数综合检验步(step)、块(block)、模型(model)检验的P值均小于0.01;拟合优度检验的-2对数似然值(-2LL)为159.374,Cox&SnellR2为0.331,NagelkerkeR2为0.373;预测等级1准确率为45.5%,等级2准确率为100%,等级3准确率为100%,综合为81.8%,说明Logistic回归模型性能良好。Hosmer和Lemeshow检验预测值与观望值无显著性差异（P>0.05）。可见北京高校男生定量负荷心功能、血液指标与有氧能力的多元Logistic回归模型拟合度较好,且HR、SVI、VET、HGB是有氧运动能力的重要预测因素。     

基于VENN模型的民航飞行员胜任力评估标准优化

传统的飞行训练评估依赖教员的主观评价,且对能力的量化评估标准模糊,难以保证评估的一致性和有效性。本文基于VENN模型对飞行训练中行为指标展现的数量、频次及威胁与差错管理结果三个胜任力特征进行数学建模,将飞行训练中对科目的检查转化为对能力的量化评估,并结合历史检查工作单数据,提出了一种胜任力评估标准优化方法。最后,以实际的手动飞行操纵技能评估为例,验证了提出方法的有效性。测试结果表明：由算法得出的评分标准获得的技能评分与教员经验给出的评级结果显著相关,且评分保持一致的样本占比83.3%,其余样本评分偏差均在1级以内,表明了提出方法能有效的从历史检查单数据中提取对能力的评估标准,为数据驱动的胜任力量化评估标准制定提供了理论支撑及新方法。