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The first is an integrated treatment approach, where anxiety-focused techniques are built into a BD-focused treatment, producing moderate results (Williams et al. 2008; Dusser et al. 2009).
Three main approaches to the psychological treatment of the bipolar-anxiety comorbidity set have been proposed: (1) integrated, where anxiety-focused techniques are built into a BD-focused treatment; (2) sequential, where the BD and the anxiety disorder are targeted separately with disorder-specific interventions; and (3) modular, where anxiety modules are inserted into a standard BD treatment.
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The Delta, using the same techniques, was built from the ground up.
Furthermore, random forests as one of machine learning techniques were built for developing the classifier with three different combinations of features.
Similarly, the use of molecular-biology-based gene marker technologies or bio-informatics to empower conventional breeding techniques is built around a process of cumulative incremental innovation, where the outputs of the research are used in turn as the direct inputs for the next innovation cycle.
Some of these techniques were build on existing technetium-99m-MDP radionuclide scintigraphy, while others are incorporating MRI and PET scan methodologies (Imbriaco et al, 1998; Sabbatini et al, 1999; Sadik et al, 2006; Messiou et al, 2011).
The technique is built around differences in the ways that investment partnerships account for the values of their assets and liabilities.
Furthermore, this acceleration technique is built on top of the previous methods and can be deactivated.
A facile technique was built to fabricate epoxy-based composite film with graphite nanosheets (GN) alignment.
This technique is built into the proposed single Gaussian background subtraction before pixels are thresholded and thus requires some modification; however, the expected behaviour is the same.
The technique is built upon a definition of a stochastic competitive model, which permits one to describe the behavior of the model for different types of networks.
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