冷链条件下气调包装酱卤鸭肉制品货架期预测模型的建立

目的 以气调包装酱卤鸭肉制品为研究对象,在冷链温度范围内建立一套准确、高效的货架期预测模型。方法 利用选择性培养基测定不同温度下产品各微生物数量,确定4~25℃条件下产品优势腐败菌。对乳酸菌数量与感官评定值进行了回归分析确定最小腐败量Ns。分别采用修正的Gompertz方程和平方根方程建立一、二级模型,并通过预测值与实测值对比验证模型的可靠性。结果 确定了4~25℃条件下产品优势腐败菌为乳酸菌,最小腐败量Ns=6.14(lg(cfu /g))。一、二级模型拟合度均良好,三种温度下模型预测值与实际值间的差异均在30％左右,波动幅度在10%以内。结论 实现了对4~25℃内任何时间点产品剩余货架期的预测,为冷链条件下气调包装酱卤鸭肉制品品质的变化提供了理论指导。     

预测油气田产量的β模型

通过对油气田产量变化规律进行系统研究，推导建立了预测油气田产量的β模型。该模型不但可以预测油气田产量、累积产量随生产时间的变化，而且可以预测可采储量、最高年产量及其发生的时间。实例检验该模型是可信的。     

Modified atmosphere packaging of a mixed prepared vegetable salad dish

The aim of this study was to design a modified atmosphere package for a mixed vegetable salad consisting of 75 g of cut carrot, 55 g of cut cucumber, 20 g of sliced garlic and 50 g of whole green pepper. Respiration data of all the components were combined with film permeability data to predict package atmospheres and design optimal packages for experimental testing for improved shelf-life of the produce. The optimal package avoided minimum O₂ and maximum CO₂ tolerance limits, and chilling injury temperatures for any component. A pouch form package made of 27 mm low density polyethylene developed a modified atmosphere of 2.0–2.1% O₂ and 5.5–5.7% CO₂, which was beneficial for all components and provided better quality retention than other test packages.     

Review: Modified Atmosphere Packaging and its effects on the microbiological quality and safety of produce

Modified Atmosphere Packaging and related technologies are increasingly used to extend shelf-life of fresh produce. This paper reviews the effect of such technology on the spoilage microbiological flora and food-borne pathogens which may be present in produce and also on the organoleptic properties of the product.     

提高储层预测精度技术思路与对策

采用地质、地震、测井人员协同一体化作业，对地下地质目标进行综合预测与评价，可提高储层预测精度，降低预测结果的多解性。主要方法是针对不同的区块，采用不同的方法和对策，首先从单井储层划分对比入手，建立储层沉积模式，同时对地震数据目的层段进行精细解释，建立地层构造模式，用沉积、构造等地质规律来指导和约束反演；利用测井资料对地震资料进行精细标定，建立各井的单井波阻抗模型，建立井数据和地震数据沟通的桥梁；在严格的测井约束、地质模型约束、层位控制下进行储层反演；充分利用地质、地震反演结果、地震参数提取及分析结果、测井、测试和分析化验等资料对储层预测结果进行综合分析与评价。该方法应用于长庆、大庆、准噶尔等实际区块，取得了较好的效果。     

Fundamentals of stability testing

The principles on which stability tests are based are reviewed. The need to differentiate between product stability and product-container compatibility is emphasized. Recognition of this distinction is fundamental to the efficient organisation and execution of stability tests.
Attention is also drawn to the desirability of having for every product a release specification with which it must comply when manufactured and a broader check specification with which it must comply throughout its shelf-life.
Test methods and the interpretation of the data accrued throughout a test are also discussed.
It is concluded that stability tests should not be conducted in accordance with a standardized routine pattern but that the objectives of each test should be defined and the test designed to achieve those objectives in the most efficient way.
Les regles fondamentales des essais de stabilite     

基于多渐消因子强跟踪UKF 和约束AR模型的故障估计与预测

针对非线性系统中不可观测故障参数估计和预测问题, 提出一种基于多重渐消因子强跟踪无迹卡尔曼滤波(MSTUKF) 的状态和参数联合估计法, 通过引入多重渐消因子增强了对变化函数未知的故障参数的跟踪能力. 对于得到的故障参数估计值, 利用递推最小二乘法更新约束AR预测模型, 从而实现故障参数的在线估计与预测. 仿真结果表明, MSTUKF方法在故障参数估计精度上优于UKF 和单渐消因子强跟踪UKF, 约束AR模型的预测精度高于无约束条件下的预测精度.

     

IGA-DFNN在瓦斯浓度预测中的应用

为了准确预测采煤工作面的瓦斯浓度,提出免疫遗传算法优化的动态模糊神经网络瓦斯浓度动态预测方法。用无线传感网络系统采集工作面瓦斯浓度数据作为样本,通过小波分析对样本数据进行降噪滤波预处理。采用IGA算法对DFNN网络参数进行优化,建立了瓦斯浓度的预测模型。通过MATLAB仿真研究表明,所建模型对采煤工作面的瓦斯浓度演变趋势预测合理,并且经过IGA算法优化DFNN网络比单纯的DFNN网络具有更快、更准确的预测功能,可以为防治煤矿瓦斯积聚提供更好的理论支持。