The database modelling method we devised for stage 1 is technology-independent and enables organisations with legacy enterprise systems to understand their database workload and structure.
The method we devised has been significantly influenced by the stakeholders requests which identified very specific KPIs: in order to control the design costs and to have a minimal impact on the layout of existing sorting centres, we relied on low cost video-based technology and reached the required accuracy by carefully implementing simple but effective computer vision algorithms.
These results give us confidence that the correction method we devised can adjust appropriately for the genotyping error and, therefore, should reduce bias in our estimated ORs.
The algorithmic formulation described above provides the theoretical underpinnings of the computational method we devised for identifying structural alterations leading to a transcript.
In the Methods section we devise an adiabatic elimination method by which, starting from equation (8), we obtain a closed-form solution for a linear FPE that describes the time evolution of the joint probability density function of slow variables only.
As described in the Methods Section, we devised a method based on comparing relative read abundance of parent and variant sequences in order to remove sequencing errors from our dataset.
We present a method which we devised in the course of a systematic review of the effects of population-level tobacco control interventions on social inequalities in smoking.
In this regard, we also included the Lycopersicon esculentum agglutinin (LEA) lectin, which has a much narrower specificity consistent with the banding pattern shown in Fig. 1c, but includes lactosamine units that could be substrates for the addition of the Le antigens.> An overview of the general method that we devised is shown in Fig. 2.
Here, we devise methods that preserve the in vivo assemblages of SCF complexes and apply quantitative mass spectrometry to perform a census of these complexes (the "SCFome") in various states.
As we continue to assess the epigenetics of the LINE-1 region, it is important that we devise methods to assess the extent and impact of this variation.
