红芪活性成分免疫调节作用及机制研究进展

免疫功能受损或免疫系统紊乱会导致机体疾病发生,影响人身体健康,基于调节机体免疫治疗疾病已成为临床应用热点。红芪作为甘肃大宗药材,临床应用广泛,具有抗肿瘤、抗炎、免疫调节等多种药理作用。红芪活性成分主要有红芪多糖、黄酮类、萜类、皂苷类等,其中红芪多糖为红芪发挥免疫调节作用主要的物质基础。红芪增强机体免疫力主要体现在增强免疫器官功能,诱导免疫细胞分化、促进免疫因子分泌,提高单核巨噬细胞吞噬功能、调节炎性因子水平以及激活相关通路等方面来达到其抗肿瘤、抗炎作用。本文主要对红芪活性物质免疫调节作用进行阐述,为红芪的进一步临床开发应用提供思路。     

退火工艺对HgCdTe材料位错密度及电学性能影响的研究

实验分别采用高低温退火和循环变温退火方式对液相外延生长的HgCdTe材料进行饱和汞压热处理,研究了两种热处理工艺对碲镉汞材料位错密度及电学性能的影响。结果表明：相较于高低温退火,经循环变温退火后HgCdTe材料的位错密度有了明显的降低,并且材料的迁移率有了显著的提升。研究发现循环变温退火是一种较好提升HgCdTe材料性能的热处理方法。     

新型LTCC高隔离低插损3dB90°电桥设计

基于宽边耦合带状线结构,该文设计了一种基于低温共烧陶瓷(LTCC)技术的高隔离低插损3 dB 90°电桥。该电桥使用螺旋耦合线有效地减小了器件尺寸,同时以对称式结构建模更便于后期的优化调整。在宽边螺旋耦合带状线垂直方向引入一个伸入式可调隔离电容,极大地提高了该电桥的隔离度,使其可达27 dB,且插入损耗≤0.2 dB,较之传统的定向耦合器结构,其在提升性能的同时大幅减小了器件尺寸。对耦合线直角拐弯处的电场强度进行分析与优化,采用45°斜切的方式使拐角处的电场强度与直线处大致相等。对上接地金属板进行环形镂空处理,这将改善带内的幅度平衡度。该文设计的3 dB 90°电桥通带为0.96~1.53 GHz,插入损耗≤0.2 dB,幅度平衡度≤±0.7 dB,相位平衡度为90°±1°,隔离度≥27 dB,其具有良好的应用市场。     

基于HSV的乳腺癌细胞识别方法

乳腺癌是女性致死率最高的疾病之一,严重威胁女性的身体健康。目前,病理医生判断病症等级,仍通过观察病理切片中的增殖细胞个数,具有很大的主观性。本文提出了一种将RGB彩色空间和HSV彩色空间模型结合的方法,采用各分量的色度特征,通过量化分析建立色度特征方程,实现从病理图像中检测识别乳腺癌增殖细胞。经20组乳腺癌病理切片图像验证,准确性达到了94.2%,优于单色彩空间模型方法约4%,本文提出方法能够更精确识别乳腺癌细胞,为乳腺癌细胞识别提供了一种新方法。     

基于稀疏采样传播数据和决策树算法的蒸发波导反演

蒸发波导的超视距传播特性是影响海上无线电系统性能的重要因素,准确预测蒸发波导是进行系统 评估的基础。文中提出一种基于稀疏采样传播数据和决策树轻量梯度提升机(Light Gradient Boosting Machine, LightGBM)算法的蒸发波导反演方法。首先,采用抛物方程方法仿真得到稀疏采样传播数据并构建训练集和测试 集;其次,使用决策树LightGBM 算法搭建反演模型,通过不断调参改进模型的精度以达到较高的反演准确度;最后, 调用训练好的LightGBM 模型进行蒸发波导反演,并对反演结果的概率分布进行了分析。结果表明,基于稀疏采样 传播数据的蒸发波导反演方法能够有效且快速地实现蒸发波导反演,为海上蒸发波导预测提供了一种新途径。     

750kV线路杆塔在煤矿采空区的倾斜治理技术研究

针对位于煤矿采空区的某750 kV输电线路杆塔由于基础发生不均匀沉降出现倾斜的情况,经过对采空区场地现场勘察,采用概率积分法计算预测出采空区地表移动和变形最值等数据,并定性评价塔基的稳定性和安全性,从而提出杆塔扶正的处理措施。经运行验证,采取“更换踏脚结构+加垫板+安装起吊板”技术方案进行的扶正效果较好,可为类似工程提供借鉴。     

海上风电交流送出线路继电保护优化设计

针对海上风电运行环境恶劣、平台面积资源有限以及电缆线路电容电流显著等问题,提出一种适用于海上风电送出线路的高压线路保护与电抗器保护一体化设计的新方案。首先,将输电线路和电抗器视为一个电气设备,设计了集成优化整体方案,避免了传统的电抗器支路电流的迭代计算。然后,对比研究了传统差动和行波差动对电缆线路电容电流的补偿效果,提出了线路保护优化处理技术。通过引入更为适合的线路零序电流作为电抗器零序差动的制动电流,提出了电抗器保护功能优化策略。最后,仿真实验验证了所提的优化处理技术能够提高海缆线路差动保护和电抗器零序差动保护的灵敏性和可靠性。     

Blood cell counting based on U-Net++ and YOLOv5

Clinical information about a variety of disorders is available through blood cell counting, which is usually done by manual methods. However, manual methods are complex, time-consuming and susceptible to the subjective experience of inspectors. Although many efforts have been made to develop automated blood cell counting algorithms, the complexity of blood cell distribution and the highly overlapping nature of some red blood cells (RBCs) remain significant challenges that limit the improvement of analytical accuracy. Here, we proposed an end-to-end method for blood cell counting based on deep learning. Firstly, U-Net++ was used to segment the whole blood cell image into several regions of interest (ROI), and each ROI contains only one single cell or multiple overlapping cells. Subsequently, YOLOv5 was used to detect blood cells in each ROI. Specifically, we proposed several strategies, including fine classification of RBCs, adaptive adjustment for non-maximal suppression (NMS) threshold and blood cell morphology constraints to improve the accuracy of detection. Finally, the detection outcomes for each ROI were combined and superimposed. The results show that our method can effectively address the issue of high overlap and precisely segment and detect blood cells, with a 98.18% accuracy rate for blood cell counting.     

Reaching the Fundamental Limitation in CO2 Reduction to CO with Single Atom Catalysts

The electrochemical CO₂ reduction reaction (CO₂RR) to value-added chemicals with renewable electricity is a promising method to decarbonize parts of the chemical industry. Recently, single metal atoms in nitrogen-doped carbon (MNC) have emerged as potential electrocatalysts for CO₂RR to CO with high activity and faradaic efficiency, although the reaction limitation for CO₂RR to CO is unclear. To understand the comparison of intrinsic activity of different MNCs, two catalysts are synthesized through a decoupled two-step synthesis approach of high temperature pyrolysis and low temperature metalation (Fe or Ni). The highly meso-porous structure results in the highest reported electrochemical active site utilization based on in situ nitrite stripping; up to 59±6% for NiNC. Ex situ X-ray absorption spectroscopy (XAS) confirms the penta-coordinated nature of the active sites. The catalysts are amongst the most active in the literature for CO₂ reduction to CO. The density functional theory calculations (DFT) show that their binding to the reaction intermediates approximates to that of Au surfaces. However, it is found that the turnover frequencies (TOFs) of the most active catalysts for CO evolution converge, suggesting a fundamental ceiling to the catalytic rates.     

Boosting Piezo-Catalytic Activity of KNN-Based Materials with Phase Boundary and Defect Engineering

Although the piezo-catalysis is promising for the environmental remediation and biomedicine, the piezo-catalytic properties of various piezoelectric materials are limited by low carrier concentrations and mobility, and rapid electron-hole pair recombination, and reported regulating strategies are quite complex and difficult. Herein, a new and simple strategy, integrating phase boundary engineering and defect engineering, to boost the piezo-catalytic activity of potassium sodium niobate ((K, Na)NbO₃, KNN) based materials is innovatively proposed. Tur strategy is validated by exampling 0.96(K_0.48Na_0.52)Nb_0.955Sb_0.045O₃-0.04(Bi_xNa_4-3x)_0.5ZrO₃-0.3%Fe₂O₃ material having phase boundary engineering and conducted the defect engineering via the high-energy sand-grinding. A high reaction rate constant k of 92.49 × 10⁻³ min⁻¹ in the sand-grinding sample is obtained, which is 2.40 times than that of non-sand-grinding one and superior to those of other representative lead-free perovskite piezoelectric materials. Meanwhile, the sand-grinding sample has remarkable bactericidal properties against Escherichia coli and Staphylococcus aureus. Superior piezo-catalytic activities originate from the enhanced electron-hole pair separation and the increased carrier concentration. This study provides a novel method for improving the piezo-catalytic activities of lead-free piezoelectric materials and holds great promise for harnessing natural energy and disease treatment.