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Detection of the M184V, N88D and L90M substitutions by RNA OLA was highly sensitive for virologic failure (sensitivity: 0.93, 1.0 and 1.0; binary classification test).
Notably, a positive RNA OLA at positions M184V, N88D or L80M was highly sensitive for virologic failure (sensitivity: 0.93, 1.0 and 1.0, respectively).
In today's highly competitive manufacturing environment increasing system flexibility, reducing failure sensitivity, improving system balance and productivity are crucial.
The index that characterizes this failure sensitivity is an energy measure called the Area Release Energy, which predicts the amount of energy that is released upon crack initiation at an arbitrary position along an interface.
For all of the above analysis, due to the uncertainty of whether reporting items coded as unclear represented methodological failure, sensitivity analysis was performed excluding unclear as a code and adding it to the not reported group for all comparisons.
For all of the above analysis, due to the uncertainty of whether reporting items coded as unclear represented methodological failure, sensitivity analysis was performed excluding this code and adding it to the not reported group for all comparisons.
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Individual assay performance in detecting virological failure was determined by calculating the percentage of correctly classified samples (virological failure or nonvirological failure), sensitivities, and specificities, using the VLref as the gold standard.
These demonstrate the mechanism of local failure and sensitivity of behaviour to waste properties.
The Gaussian process response surface method, is adopted to determine the system probability of failure and sensitivity analyses of the composite plates.
Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome.
Based on a specified range of periodic inspection periods for network modules and the baseline probability of software failure, a sensitivity study was conducted to analyze the risk effect of network failure between GCs and LCs on ESF-CCS signal failure.
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