7 research outputs found
Optimizing Neural Network Parameters Using Taguchi’s Design of Experiments Approach: An Application for Equivalent Stress Prediction Model of Automobile Chassis
Optimization of ANN models using different optimization methods for improving CO2 laser cut quality characteristics
An optimized artificial intelligence approach and sensitivity analysis for predicting the biological yield of grass pea ( Lathyrus sativus
Optimization of process parameters during laser beam cutting of Ni-based superalloy thin sheet along curved profile using grey-fuzzy methodology
Taguchi Based Optimisation of Artificial Neural Network to Establish a Direct Microstructure: Mechanical Property Correlation in a near-α Titanium Alloy
Foodborne pathogens and host predilection
During food manufacturing, the potential exists for contamination of products with pathogenic microorganisms. While the ingestion of a bacterial pathogen will typically result in illness in a susceptible host, it is not the case for each strain within a given species. Pathogenic bacteria display various levels of host specificity: some infect a wide range of hosts, while others have strict host selectivity and are obligate pathogens. Host specificity of bacterial pathogens is determined by multiple molecular interactions between both the pathogens and their hosts. Understanding these interactions in detail will allow risk-based decisions to be made on affected foods, informed by knowledge of specific strains or pathotypes. This has the potential to avoid costly and unnecessary recalls with classical pathogens that can be proved to have a low potential for causing illness