调节性B细胞在自身免疫性溶血性贫血患者外周血中的表达及临床意义

目的: 探讨自身免疫性溶血性贫血（AIHA）患者外周血中调节性B细胞（Bregs）的表达及其在该病发病中的意义。方法:选择16例自身免疫性溶血性贫血患者和14例健康志愿者为研究对象，用流式细胞术分析外周血CD19+IL-10+调节性B细胞及CD19+CD24hiCD27+调节性B细胞的表达；ELISA方法检测培养上清液中IL-10的水平。结果:自身免疫性溶血性贫血患者外周血中CD19+IL-10+调节性B细胞、CD19+CD24hiCD27+调节性B细胞的表达分别为（1.27±0.39）％、（9.85±2.18）％，健康志愿者组分别为（2.92±0.71）％、（26.47±4.31）％，两组比较差异有统计学意义（P<0.05）；自身免疫性溶血性贫血患者细胞培养上清中IL-10的水平低于健康志愿者组（P<0.05）。结论:自身免疫性溶血性贫血患者外周血中CD19+IL-10+调节性B细胞及CD19+CD24hiCD27+调节性B细胞比例降低，提示调节性B细胞可能参与自身免疫性溶血性贫血的发病过程。     

Personalized broad learning system for facial expression

Multimedia Tools and Applications - Understanding human emotions through facial expressions is key enabling technology for interactive robots. Most approaches of facial expression recognition are...     

A distributed energy system integrating SOFC-MGT with mid-and-low temperature solar thermochemical hydrogen fuel production

Solar thermochemical hydrogen production with energy level upgraded from solar thermal to chemical energy shows great potential. By integrating mid-and-low temperature solar thermochemistry and solid oxide fuel cells, in this paper, a new distributed energy system combining power, cooling, and heating is proposed and analyzed from thermodynamic, energy and exergy viewpoints. Different from the high temperature solar thermochemistry (above 1073.15 K), the mid-and-low temperature solar thermochemistry utilizes concentrated solar thermal (473.15–573.15 K) to drive methanol decomposition reaction, reducing irreversible heat collection loss. The produced hydrogen-rich fuel is converted into power through solid oxide fuel cells and micro gas turbines successively, realizing the cascaded utilization of fuel and solar energy. Numerical simulation is conducted to investigate the system thermodynamic performances under design and off-design conditions. Promising results reveal that solar-to-hydrogen and net solar-to-electricity efficiencies reach 66.26% and 40.93%, respectively. With the solar thermochemical conversion and hydrogen-rich fuel cascade utilization, the system exergy and overall energy efficiencies reach 59.76% and 80.74%, respectively. This research may provide a pathway for efficient hydrogen-rich fuel production and power generation.     

Role of Co in formation of Ni-Ti clusters in maraging stainless steel

The effect of Co addition on the formation of Ni-Ti clusters in maraging stainless steel was studied by three dimensional atom probe (3DAP) and first-principles calculation. The cluster analysis based on the maximum separation approach showed an increase in size but a decrease in density of Ni-Ti clusters with increasing the Co content. The first-principles calculation indicated weaker Co-Ni (Co-Ti) interactions than Co-Ti (Fe-Ti) interactions, which should be the essential reason for the change of distribution characteristics of Ni-Ti clusters in bcc Fe caused by Co addition.     

Ni,Cr, and Fe surfaces corroded by molten ZnCl2

Understanding the corrosion of molten ZnCl₂ on metal surfaces is significant for the corrosion protection of metals, sustainable use of molten salts, preparation of ZnO coatings, and so on. In this paper, surfaces of pure Ni, Cr, and Fe corroded by molten ZnCl₂ were investigated. The results show that Ni suffered very slight corrosion, while Cr experienced more serious corrosion than Ni, but lighter corrosion than Fe. The morphology of the corrosion of Cr and Fe, respectively, presented pitting and intergranular corrosion characteristics. Furthermore, nanostructured ZnO coatings were obtained on the surfaces of Ni and Fe, but not on the surface of Cr. The ZnO coating on the Ni surface was doped with a small amount of Zn₅(OH)₈Cl₂, and the ZnO coating on the Fe surface was doped with ZnFe₂O₄ and Zn₂OCl₂. The coatings on the Ni and Fe surfaces had an average thickness of 1.5 and 50 μm, respectively.     

Surface structural and solar absorptance features of nitrate-based copper-cobalt oxides composite coatings: Experimental studies and molecular dynamic simulation

The copper and cobalt oxides composites coatings on aluminum substrates have been successfully synthesized via sol-gel method using nitrate-based sol precursors. The composites were characterized by X-ray Diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Field Emission Scanning Electron Microscopy (FESEM), Atomic Force Microscopy (AFM), and UV–Vis–NIR spectrophotometry. The sol-gel reactions were discussed and Molecular Dynamics (MD) simulation was integrated into the study to predict molecules assembly properties. The XRD analyses revealed that the CuO and the Co₃O₄ composites were formed after the annealing process with the average difference of the calculated lattice parameters compared to ICDDs was 1.17%. The surface electronic structure was mainly consisted of tetrahedral Cu(I), octahedral Cu(II), tetrahedral Co(II), octahedral Co(III) as well as surface, sub-surface and lattice oxygen O^?. The XRD, XPS and MD simulation results showed that there was minimal (or possibly non-existing) indication of copper-cobalt mixed phase oxides formations. FESEM and AFM surveys revealed that the coating had a porous surface composed of interlinked nanoparticles in the range of ~?10 to ~?40?nm. UV–Vis–NIR reflectance spectra showed that the sol precursors concentration and the dip-drying cycle significantly influenced the absorptance value with optimum absorptance (α) of 88.7% exhibited by coating synthesized using sol concentration of 0.1?M and 10 dip-drying cycles. High absorptance value and simplicity in the synthesis process render the coatings to be very promising candidates for solar selective absorber (SSA) applications.     

Computational Fluid Dynamics Study on a Top-Blown Smelting Process with Lance Failure in an Isa Furnace

JOM - The Isa/Ausmelt smelting technology with a top submerged lance (TSL) has been extensively used in copper smelting processes. However, the TSL is extremely vulnerable to damage and failure...     

基于Q-learning的不确定环境BDI Agent最优策略规划研究

BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。