Self-modeling curve resolution (SMCR) analysis of near-infrared (NIR) imaging data of pharmaceutical tablets

The idea of quality by design (QbD) has been proposed in pharmaceutical field. QbD is a systematic approach to control the product performance based on the scientific understanding of the product quality and its manufacturing process. In the present study, near-infrared (NIR) imaging is utilized as a tool to achieve this concept. A practical use of a chemometrics technique called self-modeling curve resolution (SMCR) is demonstrated with NIR imaging analysis of pharmaceutical tablets containing two ingredients, a soluble active ingredient, pentoxifylline (PTX), and an insoluble excipient, palmitic acid. Concentration profiles obtained by SMCR reveal that the homogenous distribution of chemical ingredients strongly depends on the grinding time and that its process plays a central role in quantitative control, say sustained-release of PTX. In addition, pure component spectra by SMCR indicate a sequential change of specific NIR peak intensities following the increase of the grinding time. The spectra change shows a molecular structure change related to its crystallinity during grinding process. Accordingly, this study clearly demonstrates that NIR imaging combined with SMCR can be a powerful tool to reveal chemical or physical mechanism induced by the manufacturing process of pharmaceutical products and that it may be a solid solution for QbD of pharmaceutical products.     

NorTRACK product tracking system—development and implementation

This paper presents the experience gained by developers and users with implementation and operation of NorTRACK^TM, a real-time computerized product tracking system. A Programmable Logic Controller (PLC) collects and transfers data in real time to NorTRACK’s Oracle^TM database on a Windows NT^TM server network. After extensive development and Beta testing at MDS Nordion’s Canadian Irradiation Centre in Montreal, Canada, NorTRACK was installed in January 1997 with a new irradiation facility in Ethicon Endo-Surgery Inc.’s Albuquerque plant in the United States. NorTRACK communicates with the irradiator control and safety system, the plant's central manufacturing database, an innovative pallet staging and tote loading robot, and an automated dosimetry reading system. This integrated system allows the sterilization facility to monitor the irradiator operation and the flow of many products, through varied processing modes, continuously and reliably. As a result of operating with NorTRACK, both MDS Nordion’s CIC facility and the Endo-Surgery manufacturing site, are beginning to realize unique benefits in their respective operations. MDS Nordion is also initiating several future product enhancements and additional productivity modules. This paper describes the NorTRACK system, the various stages of the development project and Beta tests, and the experience of the users to date in their operations.     

Flexible software reliability growth model with testing effort dependent learning process

A lot of importance has been attached to the testing phase of the Software Development Life Cycle (SDLC). It is during this phase it is checked whether the software product meets user requirements or not. Any discrepancies that are identified are removed. But testing needs to be monitored to increase its effectiveness. Software Reliability Growth Models (SRGMs) that specify mathematical relationships between the failure phenomenon and time have proved useful. SRGMs that include factors that affect failure process are more realistic and useful. Software fault detection and removal during the testing phase of SDLC depend on how testing resources (test cases, manpower and time) are used and also on previously identified faults. With this motivation a Non-Homogeneous Poisson Process (NHPP) based SRGM is proposed in this paper which is flexible enough to describe various software failure/reliability curves. Both testing efforts and time dependent fault detection rate (FDR) are considered for software reliability modeling. The time lag between fault identification and removal has also been depicted. The applicability of our model is shown by validating it on software failure data sets obtained from different real software development projects. The comparisons with established models in terms of goodness of fit, the Akaike Information Criterion (AIC), Mean of Squared Errors (MSE), etc. have been presented.     

The analysis of process gases: a review

 A general review of key issues involved in the analysis of process gases is presented. The reasons for such measurements – which include safety, quality, environmental and economic factors are considered. The technical issues arising from these measurements are dependent upon a variety of factors, including the overall sampling system, the type of analytical instrumentation, methods of data collection and the specified calibration protocols. The use of gas calibration cylinders as transfer standards is detailed and issues of stability and traceability to reference material discussed. Received: 1 March 2000 / Accepted: 31 March 2000     

索赔次数为复合Poisson-Geometric过程的常利率风险模型的罚金函数

讨论了常利率下索赔次数为复合Poisson-Geometric过程的风险模型的罚金函数,得到了罚金函数的期望所满足的积分方程,并由所得到的积分方程推出了破产概率所满足的积分方程,初始盈余为0时,得到了罚金函数的期望及破产概率的精确解.     

信息系统安全决策模型研究

本文提出从三个方面进行决策:方案组成决策、产品选型决策和安全投资决策,及在对安全方案进行效益评估的基础上,进行方案组成决策和产品选型决策,然后在此基础上形成决策结论。     

变频器在风机泵类节能改造中的应用

本文主要介绍水泵电气控制改为变频器后,系统运行性能得到改善,操作方便,耗电量减少,设备故障降低等优点的分析。     

Simulation of forming processes by FEM with a Bingham fluid model

We model the forming process as a fluid flow. A finite element program, FIDAP, which analyses flow problems, was used to calculate velocity and strain rates at points throughout the material during the deformation process. This allows predictions to be made on the shape and quality of the resulting part. The stress-strain relation we used models the plastic flow of metals (Bingham fluids). The FEM approximation of such a fluid is tested by comparing results for a simple analytical example. In forming processes provision must be made for friction between dye and workpiece, and the program was modified accordingly. Two classical ring forming simulations are compared to published results.     

Grab vs. composite sampling of particulate materials with significant spatial heterogeneity—A simulation study of “correct sampling errors”

Sampling errors can be divided into two classes, incorrect sampling and correct sampling errors. Incorrect sampling errors arise from incorrectly designed sampling equipment or procedures. Correct sampling errors are due to the heterogeneity of the material in sampling targets. Excluding the incorrect sampling errors, which can all be eliminated in practice although informed and diligent work is often needed, five factors dominate sampling variance: two factors related to material heterogeneity (analyte concentration; distributional heterogeneity) and three factors related to the sampling process itself (sample type, sample size, sampling modus). Due to highly significant interactions, a comprehensive appreciation of their combined effects is far from trivial and has in fact never been illustrated in detail. Heterogeneous materials can be well characterized by the two first factors, while all essential sampling process characteristics can be summarized by combinations of the latter three. We here present simulations based on an experimental design that varies all five factors. Within the framework of the Theory of Sampling, the empirical Total Sampling Error is a function of the fundamental sampling error and the grouping and segregation error interacting with a specific sampling process. We here illustrate absolute and relative sampling variance levels resulting from a wide array of simulated repeated samplings and express the effects by pertinent lot mean estimates and associated Root Mean Squared Errors/sampling variances, covering specific combinations of materials’ heterogeneity and typical sampling procedures as used in current science, technology and industry. Factors, levels and interactions are varied within limits selected to match realistic materials and sampling situations that mimic, e.g., sampling for genetically modified organisms; sampling of geological drill cores; sampling during off-loading 3-dimensional lots (shiploads, railroad cars, truckloads etc.) and scenarios representing a range of industrial manufacturing and production processes. A new simulation facility “SIMSAMP” is presented with selected results designed to show also the wider applicability potential. This contribution furthers a general exposé of all essential effects in the regimen covered by “correct sampling errors”, valid for all types of materials in which non-bias sampling can be achieved.     

现场型过程仪表校验仪的设计及应用

本文较为详细地说明了现场型过程仪表校验仪硬件及软件的设计方法,特别讨论了设计现场型校验仪所采用的低功耗设计和面板校准技术.