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关键词： 债券违约   应对处理机制   借鉴  

摘要： 债券违约是债券市场持续健康发展的一个必然现象。我国债券市场在努力保持长期刚性兑付的状况下也不可回避的面对着债券违约事件。境外成熟市场在长期实践中积累了一整套债券违约应对处理法律机制,包括事前预防措施、事中应急力量和事后处置机制等,我们可以充分借鉴并进行制度完善操作改进。

关键词： 法国法   不公平条款   合同损害   竞业禁止   司法救济  

摘要： 通过司法手段对不公平合同条款予以纠正,是实现"合同正义"的最直接方式。法国法对不公平合同条款的司法救济主要体现为两种方式,一是法庭直接判决撤销合同或合同无效,二是肯定合同的效力,但对合同的不公平条款作出修改。文章将从"合同损害"与"竞业禁止"两类情形入手,结合法国最高法院的典型判决,探讨法国法院是如何对不公平条款进行司法救济,以及当中的考虑因素。

关键词： 足迹检验   侦查   破案  

摘要： 随着犯罪形势的不断变化,在侦查破案的过程中,足迹检验技术也发挥着越来越重要的作用,成为公安机关侦查案件的关键环节之一。足迹本身的特性,也决定了其在侦查破案中的广泛应用。因此,我们应当加强对足迹检验的使用,让足迹检验在侦查破案中发挥重要的作用。文章就结合了足迹使用的科学依据,结合实际的案件,分析了足迹检验在侦查破案中的作用,并提出了存在的问题和改进的方法。希望能为侦查破案提供足迹检验的技术支持。

关键词： 包装材料   静电现象   绿色包装   科研人员   复合功能   面电阻率   金属系   经济环保   表面改性   导电高分子材  

摘要： 包装这门学科,对其材料的性能要求有时较苛刻,物理的、化学的、力学的、电学的等性能往往要同时满足,而且还要赋予特定的多功能,例如防静电、防电磁波等所谓的"双防"材料,甚至多防材料等。随着抗静电包装材料需求的增长以及社会对绿色包装的重视,研制具有高能动化、稳定性好、经济环保的复合功能材料给科研人员提出了更高的要求。

关键词： 样品   采集   分类  

摘要： 区疾控中心卫生科承担着卫生行政部门、食品药品监管部门、上级疾控部门委托或布置的食品流通领域的食品样品、餐茶具消毒样品,农村饮用水安全工程监测和辖区集中式或分散式供水水质样品、医疗机构放射设备的放射防护监测及放射从业人员的体质监测样品、公共场所卫生监测样品的采样与送检和监测评价与检测报告书发送工作。

关键词： 肝硬化   中医病因探析   疾病诊断   生化检验项目   作用  

摘要： 目的探讨生化检验项目在肝硬化疾病诊断中的作用。方法本次共选择50例肝硬化患者(肝硬化组),均为我院2013年1月至2014年1月收治,采用生化检验,就结果与同期收集的50例健康体检者(健康组)进行比较。结果观察组选取病例ASTm、ADA、GIDH、AFU、NAC、LAP值均高于对照组,差异均有统计学意义(P<0.05),前白蛋白(PAB)相对降低。结论加强生化检验项目监测,对早期诊断肝硬化疾病意义重大,可为临床治疗提供准确的参考依据。

关键词： 基层检验专业质控组   区域性   质量控制  

摘要： 目的探讨基层检验专业质控组在区域性质量控制中的作用。方法在我市成立医疗机构基层检验专业质控组,选取从2011年3月至2013年3月之间在我市医疗卫生机构进行治疗的病患5000名,在对治疗结束之后向患者发放治疗情况问卷。对我市的市属、社区、乡镇医疗卫生机构的工作质量进行跟踪监督检查,对各个市属、社区、乡镇卫生医疗机构中出现的问题进行分析和总结,组织个别医疗卫生机构的人员进行单独的医疗培训。结果在建立基层检验专业质控组之后各个卫生医疗机构的医疗事故发生率明显下降,从2011年3月至2013年3月之间各个卫生医疗机构的合格率从60.5%上升到87.5%,优良率从原来的55.7%提升到了80%,各个环节中的事故发生明显减少。结论基层检验专业质控组的介入在区域性的质量控制的作用明显,能够帮助各个医疗卫生机构提升工作水平。制定统一的标准和规范进行质量的监督对于推动整个医疗卫生行业的发展是一件十分重要的举措。

关键词： 第三人   违约责任   合同相对性  

摘要： 我国司法实践中存在着大量涉及第三人的合同,原则上强调合同的相对性,合同关系以外的第三人不享有合同权利也不承担合同义务。但在第三人原因造成违约时,实务处理中对第三人的原因范围如何确定,如何处理与侵权责任的关系等,由于相关法律规范较为简单,学界存在较多争议。因此有必要对这一问题进行全面梳理,明确相关的责任处理问题,以彰显现代合同法自由与秩序理念,完善合同制度。

关键词： Mycobacterium tuberculosis   Microscopic imaging   Pattern recognition   Random forests   Support vector machines  

摘要： The World Health Organization suggests visual examination of stained sputum smear samples as a preliminary and basic diagnostic technique for diagnosing tuberculosis. The visual examination process requires much time of laboratorian, and also, it is prone to mistakes. For this purpose, this paper proposes a novel random forest (RF)-based segmentation and classification approaches for the automated classification of Mycobacterium tuberculosis in microscopic images of Ziehl-Neelsen-stained sputum smears obtained using a light-field microscope. The RF supervised learning method is improved to classify each pixel depending on local color distributions as a part of candidate bacilli regions. Therefore, each pixel is labeled as either a candidate tuberculosis (TB) bacilli pixel or not. The candidate pixels are grouped together using connected component analysis. Each pixel group is then rotated, resized and centrally positioned within a bounding box, respectively, in order to utilize appearance-based tuberculosis bacteria identification algorithms. Finally, each region is classified by using the proposed RF learning algorithm trained on manually marked TB bacteria regions in the training images. The algorithm produces results that agree well with manual segmentation and identification. Different two-class pixel and object classifiers are also compared to show the performance of the proposed RF-based pixel segmentation and bacilli objects identification algorithm. The sensitivity and specificity of the proposed classifier are above 75.77 and 96.97% for the segmentation of the pixels, respectively. It is also revealed that the sensitivity increases over 93% when the staining is performed in accordance with the procedure. Moreover, these measures are above 89.34 and 62.89% for the identification of bacilli objects. The results show that the proposed novel method is quite successful when compared to the other applied methods.

关键词： geographic object-based image analysis   segmentation   classification   sample supervised   spatial metrics   metaheuristics  

摘要： Quality segment generation is a well-known challenge and research objective within Geographic Object-based Image Analysis (GEOBIA). Although methodological avenues within GEOBIA are diverse, segmentation commonly plays a central role in most approaches, influencing and being influenced by surrounding processes. A general approach using supervised quality measures, specifically user provided reference segments, suggest casting the parameters of a given segmentation algorithm as a multidimensional search problem. In such a sample supervised segment generation approach, spatial metrics observing the user provided reference segments may drive the search process. The search is commonly performed by metaheuristics. A novel sample supervised segment generation approach is presented in this work, where the spectral content of provided reference segments is queried. A one-class classification process using spectral information from inside the provided reference segments is used to generate a probability image, which in turn is employed to direct a hybridization of the original input imagery. Segmentation is performed on such a hybrid image. These processes are adjustable, interdependent and form a part of the search problem. Results are presented detailing the performances of four method variants compared to the generic sample supervised segment generation approach, under various conditions in terms of resultant segment quality, required computing time and search process characteristics. Multiple metrics, metaheuristics and segmentation algorithms are tested with this approach. Using the spectral data contained within user provided reference segments to tailor the output generally improves the results in the investigated problem contexts, but at the expense of additional required computing time.