NH_4HCO_3作沉淀剂制备超细Ce-Zr-O粉末的研究

为寻求简便、合理的合成超细粉体的方法,利用NH4HCO3 作沉淀剂,通过考察料液配比、加料速度、升温速度等实验因素,得到了简单的合成超细 Ce Zr O粉末的工艺,并利用比表面积测定仪、激光粒度仪、XRD、Raman等仪器对相关产物进行了表征.结果表明:利用简单工艺合成的超细 Ce Zr O粉末具有中位粒径为0.30μm、比表面积为21.2 m2/g、悬浮性大于30 min、松装密度小于 1 g/cm3等性能,产物具有 CaF2 型的空间结构.     

Pharmacodynamic profile of CQP 201-403, a novel 8α-amino-ergoline

Summary The profile of action in animals of CQP 201-403, a novel 8-amino-ergoline, is in most aspects that of a very potent dopaminomimetic, both as a prolactin secretion inhibitor, and at the levels of the CNS and the cardiovascular system. Qualitatively CQP 201-403 differs slightly from bromocriptine and apomorphine in its effects on the CNS (no influence on serotonin metabolism in the rat cortex; induction of masculine mounting behavior in rats) and the cardiovascular system of the dog (reflex tachycardia in response to a blood-pressure fall). In man the new compound proved to be highly active in lowering prolactin serum levels and to be more potent than bromocriptine (Parlodel^®).In memory of Dr Annemarie Closse, who died 14 June 1987.     

Purification of platelet-derived endothelial cell growth inhibitor and its characterization as transforming growth factor-β type 1

In 1986, Brown and Clemmons (Proc. natl Acad. Sci. USA83 (1986) 3321) showed that platelets contain a substance, platelet-derived growth inhibitor (PDGI), that inhibits in vitro endothelial cell replication. Although platelets are rich in transforming grwoth factor (TGF-), PDGI was considered not to be related to TGF-, on the basis of its reported properties (extraction from platelets at neutral pH, binding to heparin-Sepharose). However, we purified PDGI to near homogeneity and showed that on the basis of HPLC retention behavior, in vitro growth inhibitory activities with several cell types, receptor binding, and immunoneutralization of growth inhibitory activity with specific anti-TGF- type 1 antibodies, PDGI is most probably identical with TGF- type 1.     

Flow-induced release of adenosine 5′-triphosphate from endothelial cells of the rat mesenteric arterial bed

Adenosine 5-triphosphate (ATP) was released into the perfusate of rat isolated mesenteric arterial beds during each of two consecutive increases in flow. There was no significant difference between the amounts of ATP released on each occasion. Substance P was also released into the perfusate by increased flow, although its release was more variable. Removal of the endothelium of the mesenteric vessels with sodium deoxycholate led to a significant reduction (74%) in the amount of ATP released compared with the release before the endothelium had been removed. This suggests that the ATP released into the mesenteric arterial perfusate during increased flow arises from endothelial cells.     

Determination of erythrocyte pyrimidine 5′-nucleotidase activity by31P nuclear magnetic resonance: Comparison of normal controls and multiple sclerosis patients

Summary A technique to assay erythrocyte pyrimidine 5-nucleotidase activity in situ using³¹P nuclear magnetic resonance spectroscopy is presented. The assay is chemically specific, simple and applicable to untreated lysates. A comparison of enzyme levels in normal controls and in multiple sclerosis patients employing the assay yielded no significant differences between both groups. Difficulties encountered in the quantitative analysis of the assay using¹H-NMR spectroscopy are briefly discussed.     

电子束熔化成形与锻造Ti6Al4V合金的腐蚀行为对比研究

本工作采用电化学工作站研究了电子束熔化技术（EBM）成形TC4样品和传统锻造TC4在3.5wt% NaCl溶液中的电化学腐蚀行为. 结果表明EBM成形TC4样品的非平衡微观结构使其与传统锻造的TC4相比,表现出不同的耐腐蚀性. EBM成形TC4样品与锻件TC4相比,EBM成形样品不同平面存在耐蚀性差异,而且EBM水平面大于锻件,EBM垂直面小于锻件. EBM成形TC4样品垂直面出现的腐蚀性能的各向异性主要是β柱状晶导致的. 在腐蚀的过程中,点蚀优先发生在α晶界,因为晶界能量较高,形成多孔的钝化层. 本项工作有助于丰富增材制造制备TC4合金在航空钛合金领域的腐蚀性能研究.     

改进的YOLOv4肺结节检测算法

针对目标检测YOLOv4算法在肺结节检测中存在的小目标漏检和肺结节位置失真等问题,设计了一种改进的YOLOv4肺结节检测算法.在原始YOLOv4网络的基础上,将特征融合网络的上采样过程替换为双线性插值法,并采用张量堆叠的方法使顶层的语义信息与底层的位置信息形成更高通道的特征张量.实验结果表明,与原始的YOLOv4算法相比,改进的YOLOv4算法在公开数据集LUAN16上的平均精确度与预测速度分别提高了4.54%和28.1%,可视化结节位置表达更精准.     

基于轻量化深度学习网络的数字仪表识别

数字式仪表常用于变电站、工厂等生产环境,是一种直观的设备监测仪器。然而当前数字式仪表的读取方式还依赖于人工巡检,手动记录等,这些传统的巡检方式来监测设备的运行状态大大降低了巡检效率。为了实现传统行业的数字化转型,本文提出基于轻量化深度学习的数字仪表识别方法,通过改进的YOLOv5的目标检测框架,针对数字仪表目标区域在整张图片大小不一致的情况,提出对于感兴趣区域（ROI）的迭代目标检测方法,首次检测将感兴趣区域进行检测并切割统一到相同的尺度,随后迭代检测网络针对感兴趣区域内的字符进行检测并分类,以达到精确读数的目的。为提升多尺度检测性能,本文采用Res2Net模块主干网络中的的残差模块。采用GIoU取代通用的IoU作为位置损失函数加速模型训练效果的收敛。实验表明,改进后的框架实现了99.62%的准确率和99.55%的召回率,相比基线网络分别提升了12.72%和5.85%。通过将框架在边缘计算平台上的终端部署,在实际生产中取代了人工巡检,实现了商业化运行。