车身曲面的光顺品质分析与应用

文章对车身反求工程中曲面光顺的含义、常用光顺检查方法( 曲面曲率法、光照模型法、等高线法、线性变换法)的特点及原理进行论述;介绍CATIA软件Freestyle模块的外形分析功能的使用,其目的是在图形终端屏幕上直观分析曲面光顺品质,满足用户对产品外形的视觉要求,给汽车外观赋予浓郁的时代感.     

Ultrasonic-assisted drilling of Inconel 738-LC

Generally in the drilling of modern aviation materials such as nickel and titanium base super alloys, problems frequently occur in terms of burr formation at the cutter exit, tool stress, high heat generation on tool surface as well as low process reliability. A recent and promising method to overcome these technological constraints is the use of ultrasonic assistance, where high-frequency and low-amplitude vibrations are superimposed on the movement of cutting tools. This paper presents the design of an ultrasonically vibrated tool holder and the experimental investigation of ultrasonically assisted drilling of Inconel 738-LC. The circularity, cylindricity, surface roughness and hole oversize of the ultrasonically and conventionally drilled workpieces were measured and compared. The obtained results show that the application of ultrasonic vibration can improve the hole quality considerably. Improvements of up to 60% have been achieved.     

饮用水中天然有机物的分析与表征方法

天然有机物(NOM)是一类分布广泛、成分复杂的有机混合物,可严重影响饮用水的处理效率,并可能对出水水质产生严重的不利影响。因此,为了改进和优化饮用水的处理过程,在研究和实际应用阶段对NOM进行表征和定量以了解其结构特性和反应性具有重要意义。文中先对NOM的富集方法进行了介绍,接着梳理了不同分离方法的依据及作用,最后总结了各类表征方法的原理及应用,以期有助于对NOM和饮用水处理的深入研究。     

LED充电台灯产品质量安全风险监测分析

近年来带锂离子电池的可移动式LED充电台灯引发爆炸、起火、燃烧等质量安全事件时有发生,为充分了解该类产品的质量状况,确保消费者的生命财产安全。本文选取了电商平台上销售的30批次样品进行试验、分析和评估,结果显示:样品存在标记缺失、结构不合格、耐热不合格、电池外部短路不合格等质量安全风险。依据国家相关的风险评估标准,将该类产品不同的监测项目应进行风险等级评划分,并针对风险等级程度对产品的质量提升要求提出了相关处置建议。     

基于电容电流的谐波电压在线监测系统研制

我国变电站内的谐波电压监测数据大多取自电容式电压互感器（CVT）的测量结果,受CVT本身工频谐振设计的影响,谐波电压测量数据存在较大畸变。在国家电网公司推广建设电能质量监测平台背景下,针对国内市场上测量准确且简便易行的CVT谐波电压在线监测装置的空白,研制一套基于电容电流法的CVT谐波电压在线监测系统,纠正现场普遍存在的CVT谐波电压测量结果畸变;同时,通过对不同谐波电压测量方法的分析和试验对比,为在不同现场选取适合的谐波电压测量方法提供参考依据。该系统施工量小、准确度高、适用面广,具有良好的工程应用价值。     

氯化聚氯乙烯(PVC-C)管道加工影响因素与质量浅析

本文通过设备、模具、材料配方、加工工艺温度、冷却水温、定径真空压力、摩擦热控制,挤出操作等方面的因素,分析了影响氯化聚氯乙烯(PVC-C)管道生产质量的主要影响因素和预防控制措施。     

The Role of Tumor Microenvironment Cells in Colorectal Cancer (CRC) Cachexia

Cancer cachexia (CC) is a multifactorial syndrome in patients with advanced cancer characterized by weight loss via skeletal-muscle and adipose-tissue atrophy, catabolic activity, and systemic inflammation. CC is correlated with functional impairment, reduced therapeutic responsiveness, and poor prognosis, and is a major cause of death in cancer patients. In colorectal cancer (CRC), cachexia affects around 50–61% of patients, but remains overlooked, understudied, and uncured. The mechanisms driving CC are not fully understood but are related, at least in part, to the local and systemic immune response to the tumor. Accumulating evidence demonstrates a significant role of tumor microenvironment (TME) cells (e.g., macrophages, neutrophils, and fibroblasts) in both cancer progression and tumor-induced cachexia, through the production of multiple procachectic factors. The most important role in CRC-associated cachexia is played by pro-inflammatory cytokines, including the tumor necrosis factor α (TNFα), originally known as cachectin, Interleukin (IL)-1, IL-6, and certain chemokines (e.g., IL-8). Heterogeneous CRC cells themselves also produce numerous cytokines (including chemokines), as well as novel factors called “cachexokines”. The tumor microenvironment (TME) contributes to systemic inflammation and increased oxidative stress and fibrosis. This review summarizes the current knowledge on the role of TME cellular components in CRC-associated cachexia, as well as discusses the potential role of selected mediators secreted by colorectal cancer cells in cooperation with tumor-associated immune and non-immune cells of tumor microenvironment in inducing or potentiating cancer cachexia. This knowledge serves to aid the understanding of the mechanisms of this process, as well as prevent its consequences.     

基于数据挖掘的底水油藏开发预测新方法

底水油藏开发过程中受强底水、油柱高度低、地层原油黏度大、隔夹层分布复杂等因素影响,导致单井开发效果差异大。为解决目前常规方法所存在的多因素数据分析量大、应用局限性大等缺点,提出基于BP神经网络数据挖掘算法的底水油藏水平井可采储量预测新方法,通过数模机理模型分析了该方法的可靠性。针对底水油藏静动态资料,充分挖掘隐含其中的有效信息,在完成基础数据集建立的基础上,构建了基于数据驱动的底水油藏可采储量预测模型。实际应用结果表明,该方法实现了底水油藏水平井开发的影响因素和技术参数界限的定量分析,可采储量预测最大误差低于8%,拟合效果较好,可进一步应用于底水油藏水平井生产动态、开发界限、井位设计等方面。     

基于多任务卷积神经网络的虹膜图像质量评估方法

为了自动、准确、高效地评估采集图像的质量,设计了一个名为MTIQA的卷积神经网络。该网络能够输出与主观评价指标保持较高一致性的客观评估结果。MTIQA采用多任务学习策略,包含网络训练质量评估和失真类型分类两个任务,将两个任务的损失融合并构成新的损失函数。为了评估算法所得到的客观指标的可靠性,建立了名为SIR2019的单眼虹膜质量评估数据集,并召集志愿者进行主观实验以得到主观评价指标。在SIR2019和CASIA-Iris-Distance-Lamp数据集上的实验结果表明,该网络在虹膜图像质量评估上具有较好的可行性、准确性和鲁棒性。     

敏捷化AIOps框架及运维数据质量评估方法

敏捷化智能运维(AIOps)框架将模型构建提前至测试阶段,利用该阶段产生的监控数据代替线上采集的数据以训练AIOps模型,进而实现智能运维的早开发与早使用. 运维数据质量评估方法通过最大均值差异度量方式,分别在健康评估与故障诊断运维场景下对训练数据分别进行趋势性、阶段性、可检测性及可诊断性评估,以预估数据对模型的适用性. 基于华为技术有限公司提供的测试环境设置测试用例并构建实验数据集,在该数据集上的实验结果验证了敏捷化AIOps框架的可行性及数据质量评估方法的有效性.