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关键词： 微生物形态学   感染性疾病   诊断   治疗  

摘要： 研究感染性疾病患者行微生物形态学检验的效果。方法:数据遴选本院2019年2月-2021年2月收治的80例感染性疾病患者,“硬币分组法”分常规组(常规检验,n=40)、形态组(微生物形态学检验,n=40),2组检验结果比较。结果:形态组检查确诊率为95.00%,常规组为80.00%,形态组确诊率高于常规组,差异具有统计学意义(P<0.05);形态组检查感染率为55.00%,常规组为80.00%,形态组感染率低于常规组,差异具有统计学意义(P<0.05)。结论:微生物形态学检验用于感染性疾病诊断中可起到预防、控制感染的作用,检测病原菌、尽早明确疾病,值得推崇。

关键词： 生化检验   糖尿病   肾病   早期诊断  

摘要： 对糖尿病肾病早期诊断中应用生化检验指标的诊断价值进行探讨。方法:研究的对象均为2020年5月~2021年5月时段入院行生化检验者,包括60例糖尿病肾病患者(观察组),以及60例健康体检正常人(对照组),检验完毕后将两组各项生化检验指标进行对比。结果:观察组的C反应蛋白(CRP)、糖化血红蛋白(HbAIc)、血清胱抑素C(CysC)、血肌酐(Cr)水平与对照组比较,前者均表现出明显升高,差异显著(P<0.05)。结论:在糖尿病肾病患者早期诊断中,应用生化检验指标进行诊断能有效提高诊断准确率,做到尽早发现、尽早治疗,提高患者治愈率与预后质量,因此值得临床推广。

关键词： 结直肠癌   血清肿瘤标志物   诊断   联合检验  

摘要： 此次课题主要针对结直肠癌患者治疗工作当中,采取血清肿瘤标志物联合予以检验的临床效果进行分析。方法:选取在我院接受治疗的结直肠癌患者作为研究样本,样本数据为90例,按照随机数字表法,将这些患者分为研究组与常规组,每组各45例患者,其中常规组选取非结直肠癌患者,研究组选取结直肠癌患者,之后分析两组患者的血清肿瘤标志物水平及不同时期患者的血清肿瘤标志物水平等情况。结果:针对研究期间的相关数据实施对比评估,可以掌握到经过一段时间的治疗后,研究组患者的血清肿瘤标志物水平于高于常规组,且随着肿瘤分期的变化,CEA、CA19-9、CA72-4和CA125指标表达水平均逐渐增加,数据之间差异具有统计学意义(P<0.05)。结论:为结直肠癌患者提供诊断工作时,采用血清肿瘤标志物联合检验,可以有效的检验出疾病情况,并可对疾病分期进行准确判断,具有较高的检出率,所以血清肿瘤标志物联合检验诊断方式值得在临床应用推广。

关键词： Fatigue   Nonlinear eddy current   Remaining useful life   Nondestructive evaluation   Martensitic stainless-steel  

摘要： The increasing use of stainless steel in industrial structures can be attributed to its excellent mechanical properties at elevated temperatures. Martensitic grade stainless-steel is used, for example, to manufacture steam turbine blades in power plants. The failure of these turbine blades can result in equipment damage contributing to expensive plant failures and safety concerns. Degradation and structural failure of these blades is largely attributed to material fatigue, at the microstructure level. Hence, it is important to evaluate the level of fatigue prior to the initiation of macro defects to ensure the viability of these components. Conventional nondestructive evaluation (NDE) techniques such as ultrasonic testing and eddy current testing are suitable in detection of macro defects such as cracks, but not very effective in evaluating degradation of the material at a microstructure scale. This article investigates the feasibility of the nonlinear eddy current (NLEC) technique to detect fatigue in martensitic grade stainless-steel samples along with a methodology to classify the samples. K-medoids clustering algorithm and genetic algorithm are used to classify the samples according to the severity of fatigue. Initial results indicate that stainless-steel samples, in different stages of fatigue, can be classified into broad categories of low, mid, and high levels of fatigue.

摘要： Background Many approaches to violence reduction are currently being applied across England. As interest in contextual and thematic responses to violence has increased, so have questions about the relationship between approaches that seek to affect the environments in which violence occurs. We sought to outline the collective potential of three of the most common approaches (contextual safeguarding, public health, and problem-solving policing) and produce an instrument to help practitioners to understand how could these approaches be used collectively at a local level. Methods Colleagues with expertise in, or who were national leads for, public health, contextual safeguarding, and problem-solving approaches formed a professional consensus panel to define the three approaches in practice, the steps required to combine them, and the benefits and challenges of each. The group met virtually for 90–120 min/month between September, 2020, and March, 2021. A panel consensus was reached about how to describe each approach. Ideas were developed and refined independently between meetings through application of approaches to case studies and model development. A practitioner toolkit that set out the findings of the group was co-produced by the professional consensus panel. The practitioner toolkit was distributed to and presented at professional networks. Local authorities were invited to pilot a combined system reform approach, to check how combining the approaches might work in practice. Findings One of the major findings was that theoretical approaches are often not used as intended by those who created them. The panel showed the similarities and co-dependencies of the approaches and proposed models of using them together in practice. The production of a practitioner toolkit has clarified what the fundamentals of each approach are and provided a space where similarities and differences can be seen. The practitioner resource has received positive feedback and discussions have

关键词： 标准样品   分类原则   命名方法   中国标准文献分类法   技术规范  

摘要： 本文系统分析了世界标准样品相关领域分类原则和命名方法的特点,基于中国标准文献分类法(CCS)和我国国家标准样品发展现状,兼顾我国国家标准样品管理特征并与国际接轨,将我国国家标准样品由现行的16主类增至17主类,在主类基础上以标准样品的技术特性划分亚类、次亚类、小类和次小类。同时,提出国家标准样品的命名应使用反映标准样品中最重要特征的短语,力求准确、简明,符合中国语言习惯。我国国家标准样品新的分类原则和命名方法,为进一步规范我国标准样品的制作、使用和管理,提高我国国家标准样品实质性参与国际标准化活动具有重要作用和意义。

关键词： 合同履行过程   解除合同   销售货物   违约行为   价外费用   购买方   涉税处理   违约金  

摘要： 企业无论是销售货物、还是提供服务都需要与购买方签订合同,但是在合同履行过程中,逾期付款、逾期交货、甚至单方面解除合同等违约行为时有发生,而实际工作中由此所涉及的各种违约金与价外费用的涉税处理问题,往往比较模糊或存在诸多困惑。为此,笔者根据合同履行的不同情况,以案例形式作分析如下。

关键词： 新收入准则   违约金   会计核算   税务处理  

摘要： 新收入准则的发布,有助于增强企业合约意识、规范内部合同管理,也直接促进企业内业财一体化融合。本文基于新收入准则下企业发生的各类情形违约金,具体剖析其如何进行规范的会计核算、税务处理等财税管理,并结合具体案例进行实务解读,对同行规范处理违约金相关事项有参考价值。

关键词： 血站   血液检测   献血者   初筛检验   血液标本报废率  

摘要： 目的:探讨献血者初筛检验在血站血液检测中的作用。方法:选择广州血液中心2018年4月—2020年4月间接待的400例无偿献血者进行研究,纳入对象自愿配合研究,以随机数表法分为两组,每组各200例。其中对照组进行常规血液检测,而观察组则在血站血液检测中开展初筛检查。比较两组血液标本报废率,以及血清乙肝表面抗原(HBsAg)、丙氨酸氨基转移酶(ALT)水平。结果:观察组血液标本报废率明显低于对照组,差异有统计学意义(χ^(2)=15.706,P<0.05),但两组检测血清HBsAg阳性、ALT阳性、HBsAg阴性、ALT阴性者相关指标水平对比差异无统计学意义(P>0.05)。结论:血站血液检验中对无偿献血者实施初筛检验,可显著降低血液样本报废率,同时还可保障血清检验结果,从而为临床献血提供可靠的保障,值得血站血液检测中应用。

关键词： Magnetic resonance imaging   Classification   Volume measurement   Cognition   Thickness measurement   Grey matter   Genetics   Mild cognitive impairment   classification   co-training   sMRI   SNP  

摘要： Mild Cognitive Impairment (MCI) is a preclinical stage of Alzheimer's Disease (AD) and is clinical heterogeneity. The classification of MCI is crucial for the early diagnosis and treatment of AD. In this study, we investigated the potential of using both labeled and unlabeled samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to classify MCI through the multimodal co-training method. We utilized both structural magnetic resonance imaging (sMRI) data and genotype data of 364 MCI samples including 228 labeled and 136 unlabeled MCI samples from the ADNI-1 cohort. First, the selected quantitative trait (QT) features from sMRI data and SNP features from genotype data were used to build two initial classifiers on 228 labeled MCI samples. Then, the co-training method was implemented to obtain new labeled samples from 136 unlabeled MCI samples. Finally, the random forest algorithm was used to obtain a combined classifier to classify MCI patients in the independent ADNI-2 dataset. The experimental results showed that our proposed framework obtains an accuracy of 85.50 percent and an AUC of 0.825 for MCI classification, respectively, which showed that the combined utilization of sMRI and SNP data through the co-training method could significantly improve the performances of MCI classification.