Abstract: Methods and systems for a cascading model architecture for providing information on a reply email. Training sample data can be created using a user's incoming reply emails from external computer devices to a user's computer device. A receptivity neural network model can be trained using the training sample data of the reply emails, and a trained receptivity neural network model can be used to determine a receptivity classification for whether new reply emails are positive reply emails or non-positive reply emails. Sample data of non-positive reply emails can be augmented, and an objection identification neural network model can be trained on the augmented sample data of the non-positive reply emails. A trained objection identification neural network model can be used to determine a objection classification for new non-positive reply emails.

Abstract: The invention concerns an assembly of at least one electrical or electronic power supply component on a printed circuit board (10) characterized in that said or at least one electrical or electronic power supply component (30) is directly mounted in close thermal contact on a thermally conductive conduction board (20) itself mounted in an opening (13) comprised in said printed circuit board (10), the lugs (32) of said or at least one electrical or electronic power supply component (30) being connected directly on the printed circuit (10).

Abstract: The invention concerns an assembly of at least one electrical or electronic power supply component on a printed circuit board (10) characterized in that said or at least one electrical or electronic power supply component (30) is directly mounted in close thermal contact on a thermally conductive conduction board (20) itself mounted in an opening (13) comprised in said printed circuit board (10), the lugs (32) of said or at least one electrical or electronic power supply component (30) being connected directly on the printed circuit (10).