This approach consists of treating the DNA with a heat labile Ung (Roche), which degrades any molecules containing uracil.
This approach consists of partitioning the velocity field at the crack tip into plastic and elastic parts.
The purpose of this approach consists of conceptual models design allowing knowledge structuration according to multiple completeness scales.
This approach consists of microbial community incubations with isotopically labeled substrates, hybridization of the extracted community rRNA to a microarray and measurement of isotope incorporation and therefore substrate use by secondary ion mass spectrometer imaging (NanoSIMS).
Performance evaluation of this approach consists of improving the bandwidth utilization, supporting different QoS requirements and reducing call reject probability and packet latency.
This approach consists of coverage matrix based reduction and path vector based reduction, so it analyzes not only the test cases coverage but also the concrete path information.
This approach consists of equilibrating chemical potentials, cycle after cycle and species after species, between the confined fluid and the free natural fluid.
This approach consists of a global spacetime evolution algorithm based on a Cauchy initial-value formulation in a bounded interior region and based on characteristic hypersurfaces in the exterior; we match the two schemes at their common interface.
This approach consists of transforming three-phase voltage or current signals into dq0 components to analyze its behavior during faults in order to then recognize patterns that indicate the start of a fault.
This approach consists of two parts, part 1 built a new model for the transformation from FRs to DPs in a distributed resource environment; part 2 proposed an achieving algorithm for the generation of Function unit chain sets (FUCSs).
This approach consists of a novel model-based methodology for the design of dynamic experiments to minimise the required experimentation and to improve parameter precision, as well as model-based control and optimisation techniques.
