We introduce DuoMorph, a design and fabrication method that synergistically integrates Fused Deposition Modeling(FDM) printing and pneumatic actuation to create novel shape-changing interfaces. In DuoMorph, the printed structures and heat-sealed pneumatic elements are mutually designed to actuate and constrain each other, enabling functions that are difficult for either component to achieve in isolation. Moreover, the entire hybrid structure can be fabricated through a single, seamless process using only a standard FDM printer—including both heat-sealing and 3D/4D printing. In this paper, we define a design space including four primitive categories that capture the fundamental ways in which printed and pneumatic components can interact. To support this process, we present a fabrication method and an accompanying design tool. Finally, we demonstrate the potential of DuoMorph through example applications and performance demonstrations.

This paper introduces PuppetLine, an interactive storytelling system that translates natural language narratives into coordinated performances using tabletop robots. The system combines large language models with a constrained set of action and emotion primitives to generate physically executable and interpretable multi-robot motions. We describe the system design and report findings from a designer-centered user study examining how people interpret and reflect on robot enactments. The results provide formative insights into mapping narrative intent to embodied interaction and inform the design of narrative Swarm User Interfaces.

“Ensuring healthy lifestyles and promoting well-being for all ages” is a sustainable development goal of the United Nations. Achieving sustainable living requires sufficient, regular sleep and balanced leisure activities. However, pre-sleep entertainment often leads to heightened mental alertness, making it difficult to fall asleep. Our objective is to develop a new type of robotic interaction, Drowsy Robotic Interaction, which guides the user through the illusion of sleepiness through range of vision changes to help them gradually transition to a state of tranquillity, thus improving the overall health and well-being of a young social group.

MOTIVATION: Virus mutation is one of the most important research issues which plays a critical role in disease progression and has prompted substantial scientific publications. Mutation extraction from published literature has become an increasingly important task, benefiting many downstream applications such as vaccine design and drug usage. However, most existing approaches have low performances in extracting virus mutation due to both lack of precise virus mutation information and their development based on human gene mutations. RESULTS: We developed ViMRT, a text-mining tool and search engine for automated virus mutation recognition using natural language processing. ViMRT mainly developed 8 optimized rules and 12 regular expressions based on a development dataset comprising 830 papers of 5 human severe disease-related viruses. It achieved higher performance than other tools in a test dataset (1662 papers, 99.17% in F1-score) and has been applied well to two other viruses, influenza virus and severe acute respiratory syndrome coronavirus-2 (212 papers, 96.99% in F1-score). These results indicate that ViMRT is a high-performance method for the extraction of virus mutation from the biomedical literature. Besides, we present a search engine for researchers to quickly find and accurately search virus mutation-related information including virus genes and related diseases. AVAILABILITY AND IMPLEMENTATION: ViMRT software is freely available at http://bmtongji.cn:1225/mutation/index.