Scalable Yielding of Highly Stable Polyelectrolyte-Coated Copper Sulfide Nanoparticles by Flash Nanoprecipitation for Photothermal-Chemotherapeutics

Photothermal-chemotherapeutic nanoparticles (NPs) are attracting increasing attention and becoming more widely used for cancer therapy in the clinic due to their noninvasiveness, notable tissue penetration abilities, and low systemic adverse effects. However, functional ligands are conventionally modified onto photothermal NPs to well stabilize the inorganic particles suffering from complex chemical modifications, low productivity, and batch-to-batch inconsistencies, and thus significantly restricting their clinical applications. Herein, flash nanoprecipitation (FNP) is taken advantage of to afford rapid and uniform mixing for generating local supersaturated CuS clusters for small and highly stable CuS NPs effectively stabilized by polyacrylic acid through a continuous strategy. It greatly reduces the complexity for CuS NPs synthesis and functionalization in a facile intensified mixing process. These as-synthesized particles are high-drug loading, scalable, and most importantly, it is easy to control their sizes and charges through external conditions. Toxicity and tumor inhibition experiments confirm the high cell toxicity and good suppression of tumor growth under near-infrared irradiation indicating a promising prospect of FNP in the large-scale and continuous yielding of highly stable and high-performing photothermal-chemotherapeutic NPs for cancer therapy.     

一字形型钢高强混凝土短肢剪力墙抗震性能试验研究

对6片一字形型钢高强混凝土短肢剪力墙试件进行低周反复荷载试验,研究不同型钢配置形式、不同轴压比的型钢高强混凝土短肢剪力墙的承载力、滞回特性及破坏机理。试验结果表明：格构式配钢试件和实腹式配钢试件的破坏过程相近,试件内置实腹式钢板较好地抑制了斜裂缝的发展;轴压比对两种配钢形式试件的承载力和延性影响规律一致,即随着轴压比的提高,试件承载力提高而延性下降;格构式配钢试件承载力比实腹式配钢试件略高,但实腹式配钢试件的延性更好。根据试验结果,提出型钢高强混凝土短肢剪力墙承载力计算式,与试验结果对比表明两者吻合较好。     

CDMA无线传播模型校正探讨

传播模型是无线网络规划和优化的基础,每一个模型反映了特定地区的电波传播特性,由于各个地区,各个不同的城市,其地物地貌有着很大的不同,需要建立适合当地特点的模型来指导网络规划和优化工作,无线传播模型校正必须在通用传播模型的基础上根据合理的测试数据和物理数据,关注模型校正中可能出现的误差,合理设置参数,最终形成适合当地无线传播环境的传播模型。     

捷联惯性组合导航系统测试平台的研究与实现

提出了一种基于虚拟仪器的捷联惯性组合导航系统的测试系统。介绍了虚拟仪器的概念及特点，简单论速了系统的总体设计，详细给出了测试系统的硬件和软件的构成。该系统硬件设计简单合理，软件采用LabVIEW7．0进行开发，充分体现了“软件就是仪器”的设计思想。     

单颗粒煤粉燃烧数学模型

建立了单颗粒煤粉燃烧数学模型，并模拟了不同条件下煤粉的燃烧过程。模拟给出了煤粒表面温度随燃烧时间的变化关系，燃烧率与燃烧时间及煤粒直径的关系，煤粒周转膜层中气相成分及温度的分布等。     

Performance and calculations of recycled aggregate concrete-filled steel tubular (RACFST) short columns under axial compression

This paper describes a series of tests on steel tubular short columns of circular section filled with normal concrete (NA) and recycled aggregate concrete (RAC). Twenty-two specimens, including 11 small diameter of RAC-filled steel tubular (RACFST) columns named CA series and 11 larger diameter of RACFST columns called CB series, were tested to research the influence of variations in confinement index and replacement ratio of recycled coarse aggregate (RCA), from 0% to 100% with 10% increasing. The test results show that both types of RACFST columns and normal concrete-filled steel tubular (CFST) columns failed due to oblique shear pressure damage with a drum-like. Comparisons are made with predicted bearing capacities of RACFST columns using the existing theories, such as Unified Strengthen theory (I), Confinement theory (II) and Superposition theory (III). The equation for axial compression stress-strain curves of the whole process are proposed in this investigation for RACFST short columns, which can be directly used in theoretical and numerical analysis as well as practical engineering design and evaluation of RACFST structures.     

论政府投资代建制项目监管利益相关者的界定与分类

利益相关者分析作为一种社会学的定性分析方法,主要用来识别和把握利益相关者的多种诉求,既包括经济因素,也包括道德、政治、法律和技术利益等非经济因素.将利益相关者分析运用到政府投资代建制监管体系的研究中,有利于看清监管体系的全景(big picture).通过对政府投资代建制项目监管利益相关者的界定和分类,可以清楚地了解各利益相关者的利益诉求和冲突,辩明这些利益相关者在参与政府投资代建制项目监管过程中的伦理思维和特征,从而制定出更加符合实际、更有成效的监管措施.     

基于SCP的转轨时期我国建筑业市场绩效研究

分析转轨时期我国建筑业市场绩效及其影响因素——市场结构、产权结构和企业行为。基于产业组织理论的SCP范式(市场结构-企业行为-市场绩效),结合转轨时期我国建筑业组织特点,增加产权结构变量,建立SSCP分析框架(市场结构&产权结构-企业行为-市场绩效)。在此基础上,通过理论分析,建立转轨时期我国建筑业市场绩效多元回归模型,并选取市场集中度、公有经济比重、产值利润率等指标进行实证分析,验证SSCP分析框架,证明转轨时期,我国建筑业市场结构和产权结构共同影响企业行为,进而决定市场绩效。     

Traffic Signal Timing via Deep Reinforcement Learning

In this paper, we propose a set of algorithms to design signal timing plans via deep reinforcement learning. The core idea of this approach is to set up a deep neural network (DNN) to learn the Q-function of reinforcement learning from the sampled traffic state/control inputs and the corresponding traffic system performance output. Based on the obtained DNN, we can find the appropriate signal timing policies by implicitly modeling the control actions and the change of system states. We explain the possible benefits and implementation tricks of this new approach. The relationships between this new approach and some existing approaches are also carefully discussed.