Dose-response modeling of Salmonella using outbreak data

Salmonella is a key human pathogen worldwide, most often associated with food poisoning incidences. There is a small number of predominant serotypes found in human cases. The role of exposure in the epidemiology of Salmonella can be explained using dose-response assessment both for infection and acute enteric illness. Dose-response studies are traditionally based on human challenge experiments but an alternative is to use outbreak data. Such data were collected from the published literature which included estimates of the dose ingested and the attack rate. Separate dose-response models for infection and illness given infection were fitted using a multi-level statistical framework. These models incorporated serotype and susceptibility as categorical covariates, and adjusted for heterogeneity in exposure. The results indicate that both the risk of infection and the risk of illness given infection increase with dose. The dose-response model incorporating data from all outbreaks had an infection ID50 of 7 CFU's and illness ID50 of 36 CFUs. This is indicative of much higher infectivity and pathogenicity compared with feeding studies of healthy human volunteers with laboratory adapted strains. No differences were found in the outbreak models between serotypes and susceptibility categories. However, for serotypes other than S. Enteritidis or S. Typhimurium, results indicate that a minor proportion of individuals exposed will not fall ill even at high doses. The dose-response relations indicate that outbreaks are associated with higher doses making it more likely to have a higher attack rate. Applications of the dose-response model in outbreak situations where either dose or attack rate is missing were successfully used to clarify the epidemiology. Finally, the dose-response models described here can be readily used in quantitative microbiological risk assessment to predict human infection and illness rates. A simple Excel spreadsheet implementing the model has been prepared and is available from the authors.     

试题库的数据加载与数据文件共享

运用数据库管理系统的数据加载技术以及对多媒体档链接与嵌入的OLE技术,结合试题库管理应用系统的开发,在数据的组织、数据加载、数据件共享等方面进行了探讨。     

USB在数据采集系统中的应用

已成为PC标准的通用串行总线USB为多点的数据采集提供了很大的便利,利用USB可以实现较传统方式更有效、更经济、点数更多的数据采集。介绍了如何利用USB接口来实现多点数据采集。     

大数据背景下的消费市场研究

以互联网为技术平台的电子商务的发展以及各种智能终端的开发和应用,每天都产生着大量的以TB(太字节)和PB(拍字节)等为单位的大数据。大数据时代的到来,给消费市场的研究带来了几个方面的冲击,包括对消费者数据的获得方式、消费市场数据分析的工具与方法等。同时大数据也改变了传统的调查所产生的数据对于消费市场研究的地位和作业等。本文将从大数据对消费市场的影响入手,通过分析得出大数据背景下如何展开消费市场的研究。     

高效液相色谱法测定纺织品中4-氨基偶氮苯含量的不确定度评定

按照GB/T 23344—2009方法对纺织品中4-氨基偶氮苯检测的不确定度进行了分析和评定。通过对不确定度来源的分析、量化,合成了不确定度。结果表明本次试验条件下产生不确定度的最大影响因素为过程随机效应和标准储备液的配制,并提出增加平行试验次数和配制较高浓度的标准储备液来降低总不确定度,为精确测量纺织品中4-氨基偶氮苯含量提供参考依据。     

中国近代酿酒微生物研究史料

中国酿酒历史源远流长,对酿酒微生物的研究始于近代。日本人齐藤在1904年就对我国的绍兴酒酿造的丝状菌进行了研究,我国对中国酒曲微生物的研究始于20世纪30年代初。老一辈的科技人员的研究成果及文献,对中国酒曲微生物的种类及分布、菌粪学、酒曲的效用等均作了较详细的记载。这些重要参考史料对研究中国酿酒微生物很有帮助。     

基于数据仓库的出版决策支持系统研究

决策支持系统作为一种新型的信息技术,能够为企业提供各种决策信息,提高决策质量和效率。对已有的出版管理系统进行分析,对源数据进行清洗、转换、集成,创建了多维数据模型及面向出版主题的数据仓库。在此基础上,提出了决策支持系统的解决方案,同时,利用SQLServer 2000实现了数据查询和数据分析。决策支持系统的建立,为出版行业的管理者进行科学管理和决策提供了一个有效的工具。     

氢化物原子荧光法测定饮料中总砷含量的不确定度评定

采用现代统计学方法对氢化物原子荧光光度法测定饮料中总砷含量的不确定度进行评估。通过建立数学模型,分析整个过程的不确定度来源,推导计算、合成扩展不确定度。结果表明,当饮料中总砷含量在定量限附近时,扩展不确定度为0.00082mg/L(k=2)。可如实反映测量的置信度和准确性,在实际的工作中具有较强的实用价值。     

SPSS在数据处理中的应用

面对大量零乱的数据,如何从中找出内在规律性,这是一个让人感到非常棘手的问题,也是许多人感到困惑的地方.这一问题在数学建模中尤为突出.探讨如何利用软件SPSS处理实际生活中的数据问题,对一般的数据分析与处理具有较强的实用性和参考价值.     

数据分割与注册:智能化多传感训练系统范例研究

针对多传感器系统的数据融合问题,以自适应性肢体康复训练系统为例,对数据分割与注册进行了研究.对于数据分割中的时间序列对准问题,采用三次样条拟合的方法加以解决;对于数据注册中的形式统一化问题,将实际测量参数经特征提取、适应性建模、预测及自评估,变为特征变量和相应的自评估置信概率表述,其他档案性信息和非模拟量参数则通过模糊化处理变为相同形式的表述,再进一步转换为统一的符号形式,即可解决.仿真结果证明了该融合决策方案的有效性.     

基于LabVIEW的复杂表面压力数据采集处理系统

文章介绍了在复杂表面压力测试系统中,用于该系统的数据采集及离线分析处理子系统。该系统使用了虚拟仪器开发环境和压力传感器、数据采集卡等设备。对传感器数据进行实时采集、存储。在离线回放显示过程中,运用LabVIEW的数字滤波器,对数据杂波进行滤除处理,达到减少外界干扰,增强系统可靠性的作用。     

比对试验数据处理的3种方法

引入比对试验的定义 ,结合两个实验室进行的一组比对试验数据实例 ,介绍比对试验数据处理的 3种基本方法 ,即Grubbs检验、F检验、t检验 ,并阐述三者关系。     

计算机数据采集系统的应用

介绍采用工控产品构建的计算机数据采集系统,实现对锅炉的计算机监控管理。文中重点介绍了系统选型、系统构成和应用软件设计。对大中型锅炉房的设计、改造有一定的参考价值。     

计算机在食品分析数据处理中的应用

将食品分析数据处理中,应用数理统计中显著性检验的ｔ检验,通过ＢＡＳＩＣ语言将其编写成ｔ程序,输入到计算机中,这样可以利用计算机自动进行单个均值的ｔ检验,两个均值的ｔ检验和配对实验数据的ｔ检验,及ｔ检验结果数据的分析和判断。     

高效液相色谱法测定食品中罗丹明B的不确定度分析

建立高效液相色谱法测定食品中罗丹明B结果不确定度评定的数学模型,综合分析测量过程中的不确定度来源,同时对结果的不确定度进行分析;通过评定结果表明:该方法标准曲线的拟合以及样品响应值反带入得到浓度的不确定度是主要来源,通过实验数据提出了降低其不确定度的方式和途径.     

Further Progress on the Abrasion Kinetic Modelling of Woven Fabrics Using the Martindale Abrasion Tester

Abstract

The abrasion behaviour of thirty-nine woven fabrics made of wool, polyester and cellulosic (viscose and flax) fibre blends has been measured using the Martindale wear and abrasion tester. The abrasion resistance has been assessed through the number of cycles needed to produce yarn breakage. The abradability has been measured by the rate of weight loss per 1000 abrasion cycle (kcy). A cumulative distribution of weight loss versus abrasion cycles has been plotted using the weight loss produced at 25%, 50%, 75% and 100% of the number of cycles needed for yarn breakage. The plot shows the abrasion kinetic and a third degree polynomial model has been used to fit it. The first derivative at the origin gave the initial abradability or rate of mass loss (mg/kcy). A very high negative correlation between the number of abrasion cycles to produce yarn breakage and the mean abradability has been observed. The abrasion resistance depends on the fabric type, the woollen fabrics being the less abrasion-resistant while the worsted ones showed higher abrasion resistance. Abrasion kinetics depends on fabric sett, interlacing weave and composition. Closed fabrics with high sett levels, interlacing weaves and polyester content, showed a concave abrasion kinetic while open fabrics with higher content of wool and/or cellulosic fibres showed a convex abrasion kinetic. Using regression analysis, the most relevant fabric parameters related to the abrasion resistance were fabric composition, thickness and the weave interlacing coefficient.     

Modelling and optimization of quality and costs on empirical data of hearth bread

Mathematical programming is an optimization technique, which can be used to simultaneously ensure several qualities of a product (cost, chemical composition, product characteristics, etc.). This requires mathematical models for the qualities, and especially different characteristics of a product may be challenging to model. One approach is to make empirical models based on data from experimental designs. In the present paper hearth breads are studied. The protein quality and protein content of the wheat flour have together with the mixing and proving time been found critical for hearth bread characteristics. By adjusting the process settings according to wheat flour properties, hearth breads within acceptable quality limits may be made from very different flours. A mixture-process design was constructed and 99 hearth bread batches were made. Models for hearth bread characteristics and production costs were estimated and optimized by mathematical programming. The study also considers how model uncertainty and different pricing systems of wheat flours and capacity costs influence the optimal solutions.     

平台平面度检测及数据的计算机处理

针对传统平台检测中存在的数据量大、手工计算繁琐且计算精度低的问题,在分析板桥加水平仪检测方法的基础上,阐述了检测数据从示值输入计算机的转换过程和采用最小二乘法评定平面度原理,并编制出程序可供实际应用。     

三坐标测量数据预处理系统的设计与开发

三坐标测量数据的预处理是逆向工程中的一个重要环节,其结果将直接影响到后期模型重构的质量和效率。针对目前CAD系统的数据预处理功能存在的问题,如处理能力有限,过多依赖人工,无法保证精度等。对三坐标测量数据预处理的功能原理进行了研究,主要包括数据转换、数据整合、数据处理、数据保存4个功能模块。采用VC++和Open-GL作为开发工具,实现了系统的开发。实际应用表明,所开发的系统具有较高的数据处理效率和质量。     

常规烟气检测数据的统计分析

为充分利用卷烟企业卷烟烟气常规检测数据,采用主成分分析、Z分数标准化、方差分析和多重比较以及模糊相近优先比等相结合的统计方法对卷烟烟气常规检测数据进行了分析。结果表明:主成分分析确定的主分量可以作为一种有效的卷烟烟气常规指标赋权方法;由原始数据的Z分数标准化和线性转换,以及各烟气指标的权重求出的综合指标值,能够对不同批次卷烟烟气的差异显著性进行有效评价;利用模糊相近优先比方法可以对不同卷烟品牌的烟气相似性程度进行评价。