清热化毒丸的薄层色谱鉴别研究

目的:建立清热化毒丸的薄层色谱鉴别方法,为制定其质量控制标准提供试验依据。方法:采用薄层色谱鉴别法鉴别处方中的主要药味。结果:处方中的赤芍、甘草、荆芥、青黛四味药的薄层色谱具有鉴别特征。结论:薄层色谱鉴别方法简便可靠,专属性、重现性好,可作为清热化毒丸的质量控制指标。     

正胃片中药材的薄层色谱鉴别研究

目的建立正胃片的薄层色谱鉴别方法。方法用薄层色谱法对甘草、七叶莲、陈皮、猴耳环进行了定性鉴别。结果薄层色谱法鉴别的4种供试品色谱中,在与对照品或对照药材色谱相应的位置上,均能显示相同颜色的斑点。结论利用薄层色谱法可对正胃片中的4种药材进行鉴别,可用于正胃片的质量控制。     

淡黄香茶菜地下部位化学成分

目的: 研究淡黄香茶菜Isodon flavida地下部分的主要化学成分. 方法: 采用硅胶、葡聚糖凝胶Sephadex LH-20,MCI 树脂等多种柱色谱技术进行分离纯化,运用理化性质和现代波谱技术鉴定结构. 结果: 从淡黄香茶菜地下部分的70%丙酮提取物的乙酸乙酯部位分离鉴定11个化合物,分别为角鲨烯(1),豆甾-4-烯-3-酮(2),豆甾-4-烯-3,6-二酮(3),8(17),13-ent-labdadien-15→16-lactone-19-oic acid(4),1-油酸单甘油酯(5),2α-羟基-乌索酸(6),山楂酸(7),2α,3α,23-三羟基乌苏-12,20(30)-二烯-28-酸(8),豆甾醇(9),7α-羟基谷甾醇(10),β-谷甾醇(11). 结论: 除化合物7外均为首次从该植物中分离得到.本研究对于深入了解认识香茶菜属植物地下部分的化学品质具有一定的帮助.     

海洋药材石首鱼的TG-DSC热分析研究

目的 为海洋鱼类药材石首鱼的快速鉴别提供新方法。方法 采用热重—微分热重( TG-DTG) 和差示扫描量热（DSC）方法分别对石首鱼的药材来源小黄鱼和大黄鱼以及易混淆品棘头梅童鱼进行热谱扫描。结果 石首鱼的两种正品来源与棘头梅童鱼的TG-DTG和DSC图谱存在一定的差异。在TG-DTG谱图中,小黄鱼和大黄鱼的TG-DTG曲线总体趋势一致,二者与棘头梅童鱼的TG-DTG曲线具有明显的不同,且三者的峰形、峰值等均存在差异。在DSC谱图中,小黄鱼和大黄鱼具有2个吸热峰和2个放热峰,而棘头梅童鱼具有3个吸热峰和2个放热峰。结论 热分析法具有用量少、易操作、图谱易懂、分析快速等优点,可以作为一种快速鉴定石首鱼药材的方法。     

人血小板衍生生长因子BB原核表达及生物学活性鉴定

目的 表达人血小板衍生生长因子(PDGF)BB蛋白并进行生物学活性鉴定.方法 基因扩增方法获得人PDGF-B基因;原核表达PDGF-BB蛋白,并纯化、复性;免疫印迹分析重组蛋白的免疫原性;应用培养的大鼠成骨细胞对其生物学活性进行鉴定.结果 扩增出327bp目的基因,与预期结果吻合,DNA序列分析正确.SDS-PAGE和免疫印记检测表明获得新生蛋白的分子量及免疫原性均与预期符合.体外细胞学鉴定表明,获得的rhPDGF-BB可明显促进大鼠成骨细胞的增殖和DNA复制,表明重组的PDGF-BB具有较好的生物学活性.结论 PDGF-B成熟肽基因克隆成功并成功地在大肠杆菌中实现了高表达.复性后细胞学MTT和FCM鉴定表明获得的rhPDGF-BB具有较好的生物学活性,为生产活性PDGF-BB蛋白及其在促进骨组织和创伤修复方面的进一步功能研究奠定了基础.     

毛裂蜂斗菜的生药鉴定

目的研究毛裂蜂斗菜的生药学特征,为进一步开发利用提供鉴别依据。方法观察植物性状、显微结构、理化特征等。结果描述了毛裂蜂斗菜的生药学特征。结论为毛裂蜂斗菜的鉴别、质量标准的制定以及进一步开发利用提供依据。     

罗布麻叶HPLC指纹图谱构建及在种属鉴别中的应用

目的 建立罗布麻叶的HPLC指纹图谱,用以控制罗布麻叶的内在质量,并对罗布麻叶药材与其混淆品进行鉴别.方法 采用HPLC梯度洗脱的方法建立指纹图谱,"计算机辅助相似度评价系统"软件进行数据处理,据此对不同种属的药材进行比较.结果 建立的罗布麻HPLC指纹图谱方法的精密度、稳定性和重现性较好.罗布麻叶(红麻叶)HPLC指纹图谱共标定12个共有指纹峰,与白麻属样品图谱之间呈显著差异,可以依此鉴别.结论 HPLC指纹图谱可以用作罗布麻叶药材的质量控制.     

消炎解毒丸质量标准的研究

目的 建立消炎解毒丸的质量标准,为本产品提供完善、可控的质量标准.方法 采用薄层色谱法鉴别消炎解毒丸中的金银花、防风、连翘、甘草;采用HPLC法测定咖啡酸质量分数,色谱柱为DIKMADiamonsil C18柱(250 mm×4.6 mm,5μm),流动相为甲醇-磷酸缓冲盐(体积比23∶77),检测波长为323nm,柱温为40℃.结果 在薄层色谱中检出金银花、防风、连翘、甘草,各药材薄层色谱斑点清晰,阴性无干扰;HPLC法测定中咖啡酸在0.031 2～0.780 0 μg范围内线性关系良好(r=0.999 95),平均回收率为99.52％,RSD值为1.53％(n=6).结论 本方法快速、简便、精密度好、灵敏度高,提高了消炎解毒丸的质量控制标准.     

Machine Learning Approaches for Monitoring of Tool Wear during Grey Cast-Iron Turning

The dynamic development of new technologies enables the optimal computer technique choice to improve the required quality in today’s manufacturing industries. One of the methods of improving the determining process is machine learning. This paper compares different intelligent system methods to identify the tool wear during the turning of gray cast-iron EN-GJL-250 using carbide cutting inserts. During these studies, the experimental investigation was conducted with three various cutting speeds vc (216, 314, and 433 m/min) and the exact value of depth of cut a_p and federate f. Furthermore, based on the vibration acceleration signals, appropriate measures were developed that were correlated with the tool condition. In this work, machine learning methods were used to predict tool condition; therefore, two tool classes were proposed, namely usable and unsuitable, and tool corner wear VBc = 0.3 mm was assumed as a wear criterium. The diagnostic measures based on acceleration vibration signals were selected as input to the models. Additionally, the assessment of significant features in the division into usable and unsuitable class was caried out. Finally, this study evaluated chosen methods (classification and regression tree, induced fuzzy rules, and artificial neural network) and selected the most effective model.     

Investigation of Adhesion Properties of Tire—Asphalt Pavement Interface Considering Hydrodynamic Lubrication Action of Water Film on Road Surface

To obtain the tire–pavement peak adhesion coefficient under different road states, a field measurement and FE simulation were combined to analyze the tire–pavement adhesion characteristics in this study. According to the identified texture information, the power spectral distribution of the road surface was obtained using the MATLAB Program, and a novel tire hydroplaning FE model coupled with a textured pavement model was established in ABAQUS. Experimental results show that here exists an “anti-skid noncontribution area” for the insulation and lubrication of the water film. Driving at the limit speed of 120 km/h, the critical water film thickness for the three typical asphalt pavements during hydroplaning was as follows: AC pavement, 0.56 mm; SMA pavement, 0.76 mm; OGFC pavement, 1.5 mm. The road state could be divided into four parts dry state, wet sate, lubricated state, and ponding state. Under the dry road state, when the slip rate was around 15%, the adhesion coefficient reached the peak value, i.e., around 11.5% for the wet road state. The peak adhesion coefficient for the different asphalt pavements was in the order OGFC > SMA > AC. This study can provide a theoretical reference for explaining the tire–pavement interactions and improving vehicle brake system performance.