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关键词： Classification   Paediatric   Reference interval   Transference  

摘要： The aim was to elude differences in published paediatric reference intervals (RIs) and the implementations hereof in terms of classification of samples. Predicaments associated with transferring RIs published elsewhere are addressed. A local paediatric (aged 0days to <18years) population of platelet count, haemoglobin level and white blood cell count, based on first draw samples from general practitioners was established. PubMed was used to identify studies with transferable RIs. The classification of local samples by the individual RIs was evaluated. Transference was done in accordance with the Clinical and Laboratory Standards Institute EP28-A3C guideline. Validation of transference was done using a quality demand based on biological variance. Twelve studies with a combined 28 RIs were transferred onto the local population, which was derived from 20,597 children. Studies varied considerably in methodology and results. In terms of classification, up to 63% of the samples would change classification from normal to diseased, depending on which RI was applied. When validating the transferred RIs, one RI was implementable in the local population. Conclusion: Published paediatric RIs are heterogeneous, making assessment of transferability problematic and resulting in marked differences in classification of paediatric samples, thereby potentially affecting diagnosis and treatment of children.

关键词： Large sample   Coal's bursting liability   Classification   Index relevance   Distance discriminant analysis   Comprehensive evaluation  

摘要： In order to evaluate the intensity of the coal's bursting liability scientifically and accurately, the index relevance problems existing in the current classification methods were focused on, and the Mahalanobis distance discriminant analysis (DDA) method was introduced on the basis of establishing a measured database with the large sample of the coal's bursting liability. Besides, the DDA model of coal's bursting liability classification was also established. Then, with the duration of dynamic fracture, elastic strain energy index, bursting energy index, and uniaxial compressive strength selected as evaluation indicators, three grade-discrimination functions of the bursting liability were established through training the data of 95 groups of bursting liability of different coal seams that were collected extensively. After training, the accuracy rate of the DDA model reached 96%. The results of the application of DDA model to the classification of coal samples from 10 coal mines exhibited remarkable agreement with the actual situation, which also solved the difficult problem that the fuzzy comprehensive evaluation method could not distinguish 8 kinds of samples. Its application to the engineering project shows that the classification result of coal's bursting liability based on the DDA method is both accurate and easy to calculate, and the DDA model has good engineering application prospect.

关键词： GAN   Active learning   Classification   Chest xray   Informative samples  

摘要： Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem is especially acute, where there is a severe class imbalance. We propose an active learning (AL) framework to select most informative samples for training our model using a Bayesian neural network. Informative samples are then used within a novel class aware generative adversarial network (CAGAN) to generate realistic chest xray images for data augmentation by transferring characteristics from one class label to another. Experiments show our proposed AL framework is able to achieve state-of-the-art performance by using about 35% of the full dataset, thus saving significant time and effort over conventional methods.

关键词： Face recognition   Virtual face images   Representation classification   Principal component analysis  

摘要： Classifiers such as sparse representation or collaborative representation can get good performance in face recognition. But these methods require a number of train samples in each class to construct the dictionary. On the condition of undersampled train samples, their performance decreases dramatically. A novel method is proposed in this paper to address undersampled face recognition problem. Firstly, virtual face images are generated by principal component analysis and mirror transform. Secondly, the test sample is collaboratively represented by the augmented train samples and is recognized by classifier based on representation. A number of face recognition experiments on three benchmark face database show that the recognition accuracy of our method is greater than that of a similar method, while time efficiency of our method is competitive to similar method.

关键词： FannDESIGN model   Farmer livelihoods   Labor   Multi-objective optimization   Nutrition   Soil organic matter  

摘要： Farm models have the potential to describe farming systems and livelihoods, identify trade-offs and synergies, and provide ex-ante assessments of agricultural technologies and policies. We developed three new modules related to budget, labor, and human nutrition for the bio-economic whole-farm model 'FarmDESIGN'. The expanded model positions the fanning enterprise within the farm household. We illustrate the model's new capabilities for farm households in two villages in Northwest Vietnam, where we conducted multi-objective optimization to identify options for improving the farm households' current performance on key sustainability and livelihood indicators. Modeling results suggest trade-offs between environmental, economic, and social objectives are common, although not universal. The new modules increase the scope for modeling flows of resources (namely cash, labor, and food) between the farm enterprise and the farm household, as well as beyond the farm gate. This allows conducting modeling explorations, optimization routines, and scenario analyses in farming systems research.

关键词： Chemiluminescence detection   Gas chromatography   Nitrosamines   Discrimination analysis  

摘要： The problems of contamination of many products by nitroso compounds have been discussed since 1970's and have been partially solved, namely, the contamination by carcinogenic volatile N-nitrosamines. However, there is still a gap in knowing non-volatile nitroso compounds in terms of both the determination of these compounds and the description of their toxicity. Therefore, a procedure for their detailed non-targeted study is necessary to be developed. Based on these facts, a new method permitting the detection and the classification of nitroso compound groups, such as N-nitroso, C-nitroso, and interfering substances in the nitrosamine specific chemiluminescence detection after previous gas chromatographic separation, was developed. The method is based on signal profiling of chromatographic peaks recorded by a chemiluminescence detector at different pyrolytic temperatures and subsequent multivariate chemometric classification. The resulting classification function by linear discriminant analysis shows good performance with total accuracy of 96.12% after the method validation. The method was successfully applied and demonstrated on a non-targeted beer sample analysis. Nitroso compounds detected by the method were selected for detailed structural analysis by GC-MS/MS. The combination of the presented method with the MS/MS instrumentation provides a really powerful analytical tool for the identification of unknown nitroso compounds in complex samples. This study represents a valuable contribution to the protocols of identification of organic compounds with the nitrogen functional groups - toxicologically and analytically important nitroso compounds. (C) 2019 Elsevier B.V. All rights reserved.

关键词： 受伤运动员   运动康复   遵医意图   计划行为理论   模型检验  

摘要： 以计划行为理论为基础,选取中国19个省市专业队的350名正在接受治疗的受伤运动员作为研究对象,现场匿名填写计划行为量表、行动计划量表、预期后悔量表及遵医行为量表,构建并检验受伤运动员遵医行为混合模型,揭示受伤运动员康复遵医意图与行为的作用机制。结果显示:①在计划行为理论传统的3个行为意图前因变量中,仅主观规范能有效预测康复遵医行为意图;②行动计划在行为意图与遵医行为之间起部分中介作用;③预期后悔对行为意图与遵医行为之间关系的调节作用通过行动计划的前半部分中介实现。提示:①对于受伤运动员而言,周围重要人物(主观规范)能够显著影响其康复遵医意图;②某些受伤运动员需要通过制订行动计划才能促成遵医行为的实现,另一些则不需要;③相对于预期后悔评分较低的受伤运动员,间接效果对预期后悔评分较高的受伤运动员的影响更显著。

关键词： 教育收益   个体幸福感   中介因素   性别差异  

摘要： 基于个体的教育收益不仅包括以工资收入反映出来的经济回报,还涵盖了涉及人类生存各方面的非经济收益,倍受关注的个体幸福感也是其中之一。以中国综合社会调查2012年的全国数据为基础,对教育是否能够提升个体幸福感及其提升的作用机制进行了研究。结果显示:教育能够促进个体幸福感的提升;个体的健康水平、个体的社会地位、个体的休闲程度和个体的人际关系都可以部分地解释教育提升个体幸福感指数的作用,其部分中介效果成立;个体职业收入这一变量的部分中介效果只在男性子样本中成立,在女性子样本中不成立。

关键词： 全血C反应蛋白   血常规   细菌性感染性   诊断作用  

摘要： 目的主要研究说明CRP、血常规检验的可行性,此方式应用在儿科当中,观察其情况。方法选取我院60例患儿作为分析的对象,参照组开展血常规,实验组开展血常规外,再检验CRP,综合分析其各项情况。结果实验组肺炎的情况占比8/30,肠炎的情况占比5/30,尿路感染的情况占比10/30,脑膜炎的情况占比6/30,其检测正确的情况为29/30,错误的情况为1/30;参照组肺炎的情况占比5/30,肠炎的情况占比4/30,尿路感染的情况占比9/30,脑膜炎的情况占比2/30,其检测正确的情况为20/30,错误的情况为10/30。不同组具有较大的不同(P<0.05)。结论应用实验组的方式,其检验中所具有的问题少,正确性高。

关键词： 生化检验   糖尿病肾病(DN)   早期诊断   作用  

摘要： 于2017年12月-2018年12月100例DN患者为研究组,健康者100例为常规组。结果:研究组RBP、CRP、CysC、HbA1c、UALB/Cr等均高于常规组,(P<0.05);研究组各生化指标检验阳性率也高于常规组,(P<0.05)。结论:糖尿病肾病早期诊断,通过生化指标检验能够有效预防,提高临床诊断阳性率。