消渴健脾胶囊对2型糖尿病小鼠降血糖作用研究

为研究消渴健脾胶囊对2型糖尿病小鼠的降血糖作用,取75只昆明种雄性小鼠,除正常对照组10只外,其余小鼠腹腔注射链脲佐菌素建立2型糖尿病小鼠模型,将造模成功的糖尿病小鼠随机分为模型组,阳性组(盐酸二甲双胍150.00 mg·kg~(-1)),消渴健脾胶囊低(238.88 mg·kg~(-1))、中(477.75 mg·kg~(-1))、高(955.50 mg·kg~(-1))剂量组,每组10只,正常对照组和模型组给予0.1 mL·(10 g体重)~(-1)蒸馏水,连续给药28 d后,测定小鼠体重、空腹血糖(FBG)值、糖耐量(GT)、糖化血清蛋白(GSP)水平及血清胰岛素(INS)水平。结果表明,与模型组比较,给药28 d后,消渴健脾胶囊各剂量组小鼠体重显著增加,差异具有统计学意义(P0.05);消渴健脾胶囊各剂量组小鼠FBG值显著降低,差异具有统计学意义(P0.05或P0.01);消渴健脾胶囊中、高剂量组小鼠GT显著降低,差异具有统计学意义(P0.05或P0.01);消渴健脾胶囊各剂量组小鼠GSP水平显著降低,差异具有统计学意义(P0.05或P0.01);消渴健脾胶囊高剂量组小鼠INS水平显著升高,差异具有统计学意义(P0.05)。消渴健脾胶囊对链脲佐菌素所致2型糖尿病小鼠有一定的治疗作用。     

Effect of CuSO4 on the Hydromechanical Behavior of Compacted Tailings

Laboratory tests, including compressibility, permeability, and microstructure tests, were conducted on tailings samples using custom-designed test apparatus to investigate the effect of metal contamination (Cu²⁺) on the hydromechanical behavior of compacted tailings. Infiltrating samples with various dry densities with distilled water or CuSO₄ solution at various concentrations showed that the void ratio of compacted tailings decreased with increased dry density. An increase in the metal contaminant concentrations from 0 to 0.1 mol/L increased the compression coefficient of the tailings from 0.14 to 0.84 MPa^?1 under a vertical load of 0.01 to 2.0 MPa, while the yield stress of the tailings decreased from 204.3 to 98.7 kPa, respectively. The linear relationship between permeability coefficient (k) and void ratio (e) is described by k?=???6.48?+?17.17e. Microstructure test results showed that the diffusion double layer thinned, and the surface potential decreased, indicating that the contaminant of Cu²⁺ enhanced the compressibility and permeability of the tailings. The microstructure test results also showed that the amount of fine-grained soil in the copper tailings was significantly less after the hydromechanical test. Therefore, the permeability and compressibility of copper tailings increased. The experimental results are in good agreement with the estimated results.

     

Visual Detection of Adenosine Triphosphate by Taylor Rising: A Simple Point-of-Care Testing Method Based on Rolling Circle Amplification

Rapid and sensitive point-of-care testing (POCT) is an extremely critical mission in practical applications, especially for rigorous military medicine, home health care, and in the third world. Here, we report a visual POCT method for adenosine triphosphate (ATP) detection based on Taylor rising in the corner of quadratic geometries between two rod surfaces. We discuss the principle of Taylor rising, demonstrating that it is significantly influenced by contact angle, surface tension, and density of the sample, which are controlled by ATP-dependent rolling circle amplification (RCA). In the presence of ATP, RCA reaction effectively suppresses Taylor-rising behavior, due to the increased contact angle, density, and decreased surface tension. Without addition of ATP, untriggered RCA reaction is favorable for Taylor rising, resulting in a significant height. With this proposed method, visual sensitive detection of ATP without the aid of other instruments is realized with only a 5 μL droplet, which has good selectivity and a low detection limit (17 nM). Importantly, this visual method provides a promising POCT tool for user-friendly molecular diagnostics.     

内插法在相关干涉仪测向体制中的应用

测向误差的减小一直以来都是无线电测向精度提高的一个难点,对于不同的测向体制所采用的减小测向误差的方法都不尽相同。本文主要介绍的是相关干涉仪测向体制的基本原理以及通过内插法的应用来减小测向误差的方法。     

汽车空调的操作和应用分析

2013年国内汽车产销量超过2000万台,汽车正在快速进入中国的千家万户,但大部分车主还缺乏对汽车空调知识的了解,夏天又是空调故障多发期,如果车主了解相关汽车空调知识,在实际应用中会达到事倍功半的效果,因此介绍了一般车型的空调结构、工作原理以及特殊气候下的调节。     

铜基化合物的可见光催化研究进展

与传统贵金属光催化剂相比，铜基光催化剂具有价格低廉、绿色环保、反应条件温和、光催化活性可调节等优势，受到合成化学家们广泛关注。本文简述了铜基催化剂的光催化历史，回顾了近五年来铜基化合物在可见光催化领域的研究成果与进展，总结了铜基催化剂的独立光催化机理与协同光催化机理；简要阐述了铜催化剂在不同类型反应中的应用，重点讨论了铜(Ⅰ)催化剂在烯烃官能化、碳-碳偶联、碳-杂偶联、原位催化等反应中的应用研究，表明铜基化合物在光催化合成领域具有很大的应用潜力。对未来的研究工作进行了展望，指出拓展催化剂的反应适用性、探索催化剂的氧化还原能力、进一步开发催化剂在手性合成中的应用将是该领域的研究重点。     

深度学习识别光网络单元故障的设计与应用

为解决依赖装维上门鉴别光网络单元故障带来的不便,可以从机器视觉入手实现自动化故障识别。近年,ImageNet挑战赛的成功推动了物体识别技术的跨越式发展,特别是基于卷积的深度学习技术在视觉识别方面已经达到人类水平,为光网络单元故障的自动识别提供了技术基础。文章对识别光网络单元的工作状态进行了研究,将设备工作状态分为7个场景,提出了利用手机APP采集图片识别故障的解决方案并投入了实际生产;重点阐述了深度学习模块的设计与实现,提出一种通过算法整合的方式综合运用物体检测和图像分类算法,分3阶段逐步求精,解决了图片过滤,光网络单元型号和状态识别等问题,实现了基于计算机视觉自动识别光网络单元故障。从数据上看产品的端到端准确率超过84%,识别速度达到10 FPS,月均提供服务超过1万人次,在减少用户等待的同时节约了人力资源。