Fu, M. C. - Andradottir, S. - Carson, J. S. - Glover, F. - Harrell, C. R.- Ho, Y. C. - Kelly, J. P. -Robinson, S. M. (2000): Integrating Optimization and Simulation: Research and Practice. In: Jones, J. A
Authors:Mariam Achbal, Abdellatif Khamlichi, and Fadoua El Khannoussi
optimisation of PAs design requires simulation tools that have the capacity to enable predicting radiation beam patterns from array transducers with enough accuracy. A series of important works that have been performed in the field of calculation of ultrasonics
Classical swine fever is a highly contagious, notifiable disease of pigs and wild boars listed by the World Organisation for Animal Health (OIE). Therefore, methods employed in the diagnosis of CSF should be fast, sensitive and specific. The aim of this study was optimisation of the reverse transcription reaction to increase the sensitivity of real-time RT-PCR for the detection of classical swine fever virus, the aetiological agent of the disease. The efficiency of reverse transcription reaction was compared including a range of reverse transcriptases, thermal conditions and priming methods based on results obtained in the following realtime PCR. Depending on catalysis and the priming method used in the study a significant diversity of results was observed. The best efficacy of reverse transcription was obtained using SuperScript II reverse transcriptase and priming with random nonamers and reverse, gene-specific primer. This combination improved the sensitivity of RT-PCR nearly 1000 times as compared to the method with AMV reverse transcriptase coupled with random hexamers. In summary, this study has demonstrated that the optimisation of reverse transcription can contribute to a higher sensitivity of RT-PCR diagnostic methods.
Coping with vagueness Understatements Langue du bois Coping with ambiguity Lexical-syntactic Textual Cultural Optimisation Form Content Process 3.1 Non-specificity of DI: Threats (Responsibility, Power, Stressors) It may be that not in every intervention
of adaptive optimization has been employed using evolutionary programming in the optimization of large-scale maintenance systems [ 1 ]. If the optimization problem is complex, it is hard to find the global minimum or maximum [ 2, 3 ]. In this paper