脉冲高度权重技术测量197Au中子俘获截面

脉冲高度权重技术是利用C_6D_6探测器测量中子俘获截面的一种数据处理方法。在中国散裂中子源(China Spallation Neutron Source,CSNS)的反角白光中子源(Back-n)靶站上,通过测量金靶(~(197)Au)的中子俘获截面,验证了该方法的可靠性。首先利用Geant4蒙特卡罗程序模拟给出了不同靶条件下的探测器效率,脉冲高度权重函数等基本项,使得加权后的探测器效率与γ能量成正比。然后通过实验测量了~(197)Au中子俘获截面。结果表明:测量获得的中子俘获截面数据和ENDF/B-VⅢ.0评价数据相符合,同时发现随着实验靶尺寸的不同和质子束功率的增加,会使得实验本底的扣除误差越来越大。     

Precise Extraction of Charge Carrier Mobility for Organic Transistors

Unreliable mobility values, and particularly greatly overestimated values and severely distorted temperature dependences, have recently hampered the development of the organic transistor field. Given that organic field‐effect transistors (OFETs) have been routinely used to evaluate mobility, precise parameter extraction using the electrical properties of OFETs is thus of primary importance. This review examines the origins of the various mobilities that must be determined for OFET applications, the relevant extraction methods, and the data selection limitations, which help in avoiding conceptual errors during mobility extraction. For increased precision, the review also discusses device fabrication considerations, calibration of both the specific gate‐dielectric capacitance and the threshold voltage, the contact effects, and the bias and temperature dependences, which must actually be handled with great care but have mostly been overlooked to date. This review serves as a systematic overview of the OFET mobility extraction process to ensure high precision and will also aid in improving future research.     

Chloroform Hydrodechlorination on Palladium Surfaces: A Comparative DFT Study on Pd(111), Pd(100), and Pd(211)

Topics in Catalysis - Palladium has been shown to be an effective catalyst for chloroform hydrodechlorination, which serves as a promising treatment method for industrial chloroform waste. To...     

基于BP神经网络的条带刚凸特征回弹预测

为了研究核燃料组件格架的条带刚凸特征的回弹量与压边力、冲压速度、凸凹模间隙、摩擦系数等冲压工艺参数之间的关系,首先,获取包含50个GA拉丁超立方抽样的数据点以及10个随机抽样的数据点的数据集,前者作为训练集、后者作为测试集。将前者输入到BP神经网络进行训练,后者验证训练模型的精度。最后,通过响应面图研究各因素之间的交互作用以及各因素的敏感程度。结果表明:BP神经网络能够有效预测刚凸回弹量与冲压工艺参数之间的关系,相对于其他因素,压边力对回弹量的影响特别明显,冲压速度对回弹量的影响不明显,但与凸凹模间隙和摩擦系数有明显的交互作用。     

Dual Inhibition of Pyruvate Dehydrogenase Complex and Respiratory Chain Complex Induces Apoptosis by a Mitochondria-Targeted Fluorescent Organic Arsenical in vitro and in vivo

Based on the potential therapeutic value in targeting mitochondria and the fluorophore tracing ability, a fluorescent mitochondria-targeted organic arsenical PDT-PAO-F16 was fabricated, which not only visualized the cellular distribution, but also exerted anti-cancer activity in vitro and in vivo via targeting pyruvate dehydrogenase complex (PDHC) and respiratory chain complexes in mitochondria. In details, PDT-PAO-F16 mainly accumulated into mitochondria within hours and suppressed the activity of PDHC resulting in the inhibition of ATP synthesis and thermogenesis disorder. Moreover, the suppression of respiratory chain complex I and IV accelerated the mitochondrial dysfunction leading to caspase family-dependent apoptosis. In vivo, the acute promyelocytic leukemia was greatly alleviated in the PDT-PAO-F16 treated group in APL mice model. Our results demonstrated the organic arsenical precursor with fluorescence imaging and target-anticancer efficacy is a promising anticancer drug.     

南美洲某铜矿排土场边坡稳定性研究#br#

为保证排土场安全生产，以南美某铜矿排土场边坡为例，应用极限平衡法模拟现状排土场边坡在降雨入渗前后以及地震工况下安全系数、渗流场变化规律，结果表明，在降雨入渗之前，排土场安全系数高于规范值，边坡处于稳定状态；降雨入渗之后，边坡体积含水率增加，土体发生软化，强度参数降低，边坡沿软弱层面发生滑动破坏，造成边坡失稳；在地震工况下，安全系数下降明显。在其基础上，利用MIDAS软件建立排土场边坡三维数值模型，并利用有限元法进行数值模拟，结果表明，排土场最易发生屈服的区域为坡角基底处，其物理力学指标较低，底部土体先发生屈服破坏，之后带动上部台阶边坡发生破坏，排土场破坏模式主要以深层滑动为主。2种计算方法结果得出边坡破坏模式不同，边坡发生破坏的趋势相近，体现了2种计算方法的合理性。     

红岭矿18线南西翼通风系统技术改造

针对矿山18线南西翼矿体开采过程中存在的通风系统不完善、风量欠缺、污风无法及时排出等问题，运用风压平衡原理、网络优化技术、机站优化技术以及计算机网络模拟技术展开研究，拟定了3种可行的通风方案。经技术经济比较，确定了新掘18线905～855 m回风井（1.5 m），保留该井905 m 水平回风机站，并在855 m 水平新设1台K45 6 №12风机（18.5 kW）方案。数值模拟结果表明：18线南西翼通风系统总风量达到20.5 m3/s，井下风流的可调性和稳定性增强，为矿山的安全生产提供了有力保障。     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Disease Ionomics: Understanding the Role of Ions in Complex Disease

Ionomics is a novel multidisciplinary field that uses advanced techniques to investigate the composition and distribution of all minerals and trace elements in a living organism and their variations under diverse physiological and pathological conditions. It involves both high-throughput elemental profiling technologies and bioinformatic methods, providing opportunities to study the molecular mechanism underlying the metabolism, homeostasis, and cross-talk of these elements. While much effort has been made in exploring the ionomic traits relating to plant physiology and nutrition, the use of ionomics in the research of serious diseases is still in progress. In recent years, a number of ionomic studies have been carried out for a variety of complex diseases, which offer theoretical and practical insights into the etiology, early diagnosis, prognosis, and therapy of them. This review aims to give an overview of recent applications of ionomics in the study of complex diseases and discuss the latest advances and future trends in this area. Overall, disease ionomics may provide substantial information for systematic understanding of the properties of the elements and the dynamic network of elements involved in the onset and development of diseases.