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Abstract This study examines the climate response to a sea surface temperature (SST) warming imposed over the southwest Tropical Indian Ocean (TIO) in a coupled ocean-atmosphere model. The results indicate that the southwest TIO SST warming can remotely modulate the atmospheric circulation over the western North Pacific (WNP) via inter-basin air-sea interaction during early boreal summer. The southwest TIO SST warming induces a “C-shaped” wind response with northeasterly and northwesterly anomalies over the north and south TIO, respectively. The northeasterly wind anomalies contribute to the north TIO SST warming via a positive Wind-Evaporation-SST(WES) feedback after the Asian summer monsoon onset. In June, the easterly wind response extends into the WNP, inducing an SST cooling by WES feedback on the background trade winds. Both the north TIO SST warming and the WNP SST cooling contribute to an anomalous anticyclonic circulation (AAC) over the WNP. The north TIO SST warming, WNP SST cooling, and AAC constitute an inter-basin coupled mode called the Indo-western Pacific ocean capacitor (IPOC), and the southwest TIO SST warming could be a trigger for IPOC. While the summertime southwest TIO SST warming is often associated with antecedent El Niño, the warming in 2020 seems to be related to extreme Indian Ocean Dipole in 2019 fall. The strong southwest TIO SST warming seems to partly explain the strong summer AAC of 2020 over the WNP even without a strong antecedent El Niño. 

Recent developments in AI have provided assisting tools to support pathologists’ diagnoses. However, it remains challenging to incorporate such tools into pathologists’ practice; one main concern is AI’s insufficient workflow integration with medical decisions. We observed pathologists’ examination and discovered that the main hindering factor to integrate AI is its incompatibility with pathologists’ workflow. To bridge the gap between pathologists and AI, we developed a human-AI collaborative diagnosis tool — xPath — that shares a similar examination process to that of pathologists, which can improve AI’s integration into their routine examination. The viability of xPath  is confirmed by a technical evaluation and work sessions with twelve medical professionals in pathology. This work identifies and addresses the challenge of incorporating AI models into pathology, which can offer first-hand knowledge about how HCI researchers can work with medical professionals side-by-side to bring technological advances to medical tasks towards practical applications.