WO3 nanoflakes decorated with CuO clusters for enhanced photoelectrochemical water splitting

The low quantum efficiency arising from poor charges transfer and insufficient light absorption is one of the critical challenges toward achieving highly efficient water splitting in photoelectrochemical cells. Three dimensions(3D) structures and heterojunctions have received intensive research interests recent years due to their excellent ability to separate photo-generated charges as well as the enhanced light harvesting property. Herein,3 D Cu O/WO_3 structure was fabricated through a facile solvothermal method followed by chemical bath deposition. The loading of Cu O clusters on WO_3 nanoflake arrays results in a much improved photocurrent density compared with that of pristine WO_3 nanoflake arrays, which reaches 1.8 m A/cm2 at 1.23 V vs. the reversible hydrogen electrode. The electrochemical impedance spectroscopy measurement demonstrates that the improved performance of Cu O/WO_3 electrode is attributed to the accelerated charge transfer kinetics as a result of the desirable band alignment in Cu O/WO_3 heterojunction. This work demonstrates a facile strategy to construct superior WO_3 electrode, which will ultimately allow for efficient storage of solar energy into hydrogen.     

城市轨道交通网络化运营条件下车辆基地的资源共享研究

随着国内城市轨道交通建设的快速发展与网络化运营的需求,车辆基地的资源共享研究受到日益广泛的关注与重视.该文旨在从线网车辆运用及维修角度对整个线网车辆基地进行分析研究,探讨相关各专业各种资源的共享、合理取舍和确定各车辆基地的规模.     

System deployment optimization in architecture design

Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.     

Cost and Service-Level-Based Model for a Seru Production System Formation Problem with Uncertain Demand

With increasing demand diversification and short product lifecycles, industries now encounter challenges of demand uncertainty. The Japanese seru production system has received increased attention owing to its high efficiency and flexibility. In this paper, the problem of seru production system formation under uncertain demand is researched. A multi-objective optimization model for a seru production system formation problem is developed to minimize the cost and maximize the service level of the system. The purpose of this paper is to formulate a robust production system that can respond efficiently to the stochastic demand. Sample average approximation (SAA) is used to approximate the expected objective of the stochastic programming. The non-dominated sorting genetic algorithm II (NSGA-II) is improved to solve the multi-objective optimization model. Numerical experiments are conducted to test the tradeoff between cost and service level, and how the performance of the seru production system varies with the number of product types, mean and deviation of product volume, and skill-level-based cost.     

The distributed representation for societal risk classification toward BBS posts

The risk classification of BBS posts is important to the evaluation of societal risk level within a period. Using the posts collected from Tianya forum as the data source, the authors adopted the societal risk indicators from socio psychology, and conduct document-level multiple societal risk classification of BBS posts. To effectively capture the semantics and word order of documents, a shallow neural network as Paragraph Vector is applied to realize the distributed vector representations of the posts in the vector space. Based on the document vectors, the authors apply one classification method KNN to identify the societal risk category of the posts. The experimental results reveal that paragraph vector in document-level societal risk classification achieves much faster training speed and at least 10% improvements of F-measures than Bag-of-Words. Furthermore, the performance of paragraph vector is also superior to edit distance and Lucene-based search method. The present work is the first attempt of combining document embedding method with socio psychology research results to public opinions area.     

Effect of Graphene Nanoplatelets addition on mechanical properties of pure aluminum using a semi-powder method

In recent years, graphene has attracted considerable research interest in all fields of science due to its unique properties. Its excellent mechanical properties lead it to be used in nano-composites for strength enhancement. This paper reports an Aluminum–Graphene Nanoplatelets(Al/GNPs)composite using a semi-powder method followed by hot extrusion. The effect of GNP nano-particle integration on tensile, compressive and hardness response of Al is investigated in this paper. It is demonstrated that 0.3 wt% Graphene Nanoplatelets distributed homogeneously in the matrix aluminum act as an effective reinforcing filler to prevent deformation. Compared to monolithic aluminum(in tension), Al–0.3 wt% GNPs composite exhibited higher 0.2% yield strength(+14.7%), ultimate tensile strength(+11.1%) and lower failure strain( -40.6%). Surprisingly, compared to monolithic Al(in compression), Al–0.3 wt% GNPs composite exhibited same 0.2% compressive yield strength and lower ultimate compression strength(- 7.8%),and lower failure strain(- 20.2%). The Al–0.3 wt% GNPs composite exhibited higher Vickers hardness compared to monolithic aluminum(+11.8%).Scanning electron microscopy(SEM), Energy-Dispersive X-ray Spectroscopy(EDS) and X-ray diffraction(XRD) were used to investigate the surface morphology, elemental percentage composition, and phase analysis, respectively.     

美国中产阶级的“美国梦”研究——以《兔子,快跑》为例

"美国梦"的概念的出现,反映了美国人积极向上的精神,即人只要努力奋斗就能过上体面人的生活。围绕这种共识,约翰·厄普代克出版的《兔子,快跑》一书,生动地刻画了在美国梦理念下哈利·阿斯特罗姆的人生历程,折射了美国中产阶级面临的困惑与迷茫,并对美国梦进行了深刻的反思。     

An important functional group,benzo[1,3]dioxole,of alkaloids induces the formation of the human telomeric DNA G-quadruplex

Over the past few decades, numerous molecules have been discovered or designed to interact efficiently and selectively with a peculiar DNA structure named G-quadruplex. Some of these molecules have been developed as anticancer agents. To aid the design of anticancer agents, the ability of alkaloids possessing Protoberberine and Benzophenanthridine groups to induce the formation of G-quadruplexes were studied using CD spectroscopy. By careful examination of their structures, we found that a benzo[1,3]dioxole group plays an important role in influencing their inductive properties. The more functional groups the alkaloids have, the stronger their G-quadruplex inductive ability.     

BiPAP无创通气与常规治疗COPD呼吸衰竭50例观察

目的:观察无创正压通气(NPPV)治疗慢性阻塞型肺疾病急性加重(AECOPD)合并重度呼吸衰竭的临床效果.方法:回顾分析AECOPD合并重度呼吸衰竭应用NPPV治疗的28例患者(NPPV组),同期住院未接受NPPV治疗的22例患者作为对照组.比较两组血气变化、血气改善时间、住院天数及气管插管率.结果:NPPV组患者动脉血酸碱度(pH)、氧分压(paO2)、动脉血氧饱和度(SaO2)及二氧化碳分压(paCO2) 改善更明显(P<0.05).NPPV组血气改善时间比对照组缩短[分别为(7±4)d与(15±7)d,P<0.05].NPPV组平均住院时间比对照组缩短[分别为(14±5)d与(27±6) d,P<0.05].气管插管率明显下降(分别为3.5%,22.8%,P<0.05)结论:BiPAP呼吸机辅助通气治疗COPD呼吸衰竭疗效肯定,减少了气管插管,有利于患者康复.     

文章世所希——晏殊之赋研究

北宋前期政坛、文坛领袖之一的晏殊常常仅被当作一个＂北宋倚声家之初祖＂的词人;其实晏殊残留下来的几篇赋体文章在铺陈、骈俪方面的艺术形式十分精美,颇具悠游富贵气象,鲜明具体的表现了北宋前期文坛学习李商隐骈文的情况。