Improving Workplace Expertise to Meet Increasing Customer Requirements: The Impact of Training

This article focuses upon the training of engineers at a factory producing integrated circuits. Inadequate use of statistical process techniques by the engineers meant that the production process was not being optimised in the context of increasing customer requirements. A training needs analysis was undertaken and a training programme was developed, implemented and evaluated. The results of this programme are presented and conclusions drawn

Effects of heating on hydrophobicity, viscosity, and gelling properties of soy products

The co-product of soybean after oil extraction is the meal, which is rich in protein. From this meal, protein concentrate and protein isolate are prepared and are commercially available as functional ingredients. Thermal treatment is the most common step applied to foods during processing. Changes in structural and functional properties can be affected by thermal or chemical treatments. The objective of this study was to evaluate the effect of heat on surface hydrophobicity, gelling properties, and viscosity of soy meal (SM), soy protein concentrate (SPC), and soy protein isolate (SPI). The soy products were subjected to heat at varying temperatures and heating times. Viscosity of soy protein products treated with heat increased for SM when temperature and heating times increased, but decreased for SPC and SPI. This may be due to the polysaccharides present in SM that could form starch gelation and increase meal viscosity. The surface hydrophobicity of the soy products increased when the proteins were treated with heat, possibly due to heat exposing the hydrophobic amino acids buried within the protein molecule making them become more hydrophobic on the surface of the molecule. When 8% suspensions (protein basis) were heated at 100°C, all soy products formed firm gels, indicating that protein plays an important role in gel network formation. Precaution must be taken to maintain functionality when heat processing is applied to food systems that contain soy protein products as functional ingredients

Application of machine learning and expert systems to Statistical Process Control (SPC) chart interpretation

Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts

MYC is a metastasis gene for non-small-cell lung cancer.

Metastasis is a process by which cancer cells learn to form satellite tumors in distant organs and represents the principle cause of death of patients with solid tumors. NSCLC is the most lethal human cancer due to its high rate of metastasis. Lack of a suitable animal model has so far hampered analysis of metastatic progression. We have examined c-MYC for its ability to induce metastasis in a C-RAF-driven mouse model for non-small-cell lung cancer. c-MYC alone induced frank tumor growth only after long latency at which time secondary mutations in K-Ras or LKB1 were detected reminiscent of human NSCLC. Combination with C-RAF led to immediate acceleration of tumor growth, conversion to papillary epithelial cells and angiogenic switch induction. Moreover, addition of c-MYC was sufficient to induce macrometastasis in liver and lymph nodes with short latency associated with lineage switch events. Thus we have generated the first conditional model for metastasis of NSCLC and identified a gene, c-MYC that is able to orchestrate all steps of this process. Potential markers for detection of metastasis were identified and validated for diagnosis of human biopsies. These markers may represent targets for future therapeutic intervention as they include genes such as Gata4 that are exclusively expressed during lung development