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Electrocardiogram (ECG) signals are time series data that are acquired by time change. A problem with these signals is that comparison data that have the same size as the registration data must be acquired every time. A network model of an auxiliary classifier based generative adversarial neural network that is capable of generating synthetic ECG signals is proposed to resolve the data size inconsistency problem. After constructing comparison data with various combinations of the real and generated synthetic ECG signal cycles, a user re

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Despite major expansions of evidence-based treatments of common mental disorders in recent decades, especially antidepressant medication, the point prevalence of depression has not decreased; instead it probably increased in young adults. We question whether antidepressants (AD)-monotherapy and low-fidelity-to-guideline psychological treatment (PT) might have no effect or even adverse effects in some patients and contexts that dilute the benefits of treatment at the population level, making it harder for population-based studies to detect