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Creators/Authors contains: "Li, Xiaohan"

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  1. Free, publicly-accessible full text available December 6, 2025
  2. Free, publicly-accessible full text available December 9, 2025
  3. Abstract Rh(I)‐catalyzed C8‐selective C−H alkenylation and arylation of 1,2,3,4‐tetrahydroquinolines with alkenyl and aryl carboxylic acids under microwave assistance have been realized. Using [Rh(CO)2(acac)] as the catalyst and Piv2O as the acid activator, 1,2,3,4‐tetrahydroquinolines undergo C8‐selective decarbonylative C−H alkenylation with a wide range of alkenyl and aryl carboxylic acids, affording the C8‐alkenylated or arylated 1,2,3,4‐tetrahydroquinolines. This method enables the synthesis of C8‐alkenylated 1,2,3,4‐tetrahydroquinolines that would otherwise be difficult to access by means of conventional C−H alkenylation protocols. Moreover, this catalytic system also works well in C8‐selective decarbonylative C−H arylation of 1,2,3,4‐tetrahydroquinolines with aryl carboxylic acids. The catalytic activity strongly depends on the choice of theN‐directing group, with the readily installable and removableN‐(2‐pyrimidyl) group being optimal. The catalytic pathway is elucidated by mechanistic experiments. 
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  4. A key challenge for generalizing programming-by-demonstration (PBD) scripts is the data description problem - when a user demonstrates performing an action, the system needs to determine features for describing this action and the target object in a way that can reflect the user's intention for the action. However, prior approaches for creating data descriptions in PBD systems have problems with usability, applicability, feasibility, transparency and/or user control. Our APPINITE system introduces a multimodal interface with which users can specify data descriptions verbally using natural language instructions. APPINITE guides users to describe their intentions for the demonstrated actions through mixed-initiative conversations. APPINITE constructs data descriptions for these actions from the natural language instructions. Our evaluation showed that APPINITE is easy-to-use and effective in creating scripts for tasks that would otherwise be difficult to create with prior PBD systems, due to ambiguous data descriptions in demonstrations on GUIs. 
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