Patrick Link

In sheet metal forming, the quality of a formed part is strongly influenced by the local lubrication conditions on the blank. Fluctuations in lubrication distribution can cause failures such as excessive thinning and cracks. Predicting these failures in real-time for the entire part is still a very challenging task. Machine learning (ML) based digital twins and advanced computing power offer new ways to analyze manufacturing processes inline in the shortest possible time.

Abstract Idiopathic pulmonary fibrosis (IPF) is an aggressive and thus far incurable disease, characterized by aberrant fibroblast-mediated extracellular matrix deposition. Our understanding of the disease etiology is incomplete; however, there is consensus that a reduction-oxidation (redox) imbalance plays a role.

Footnotes Received September 8, 2022. Accepted March 22, 2023. This work was supported by the National Institutes of Health National Heart, Lung, and Blood Institute [Grants 1R61-HL161804 and 5R01-HL092961]; the American Lung Association Catalyst Award; the Pulmonary Fibrosis Scholar Award; the Boehringer Ingelheim Discovery Award; and the Brewer Family Career Development Award in Support of Idiopathic Pulmonary Fibrosis and Related Interstitial Lung Disease Research (Mayo Clinic).