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Abstract Predicting protein localization and understanding its mechanisms are critical in biology and pathology. In this context, we propose a new web application of MULocDeep with improved performance, result interpretation, and visualization. By transferring the original model into species-specific models, MULocDeep achieved competitive prediction performance at the subcellular level against other state-of-the-art methods. It uniquely provides a comprehensive localization prediction at the suborganellar level. Besides prediction, our web service quantifies the contribution of single amino acids to localization for individual proteins; for a group of proteins, common motifs or potential targeting-related regions can be derived. Furthermore, the visualizations of targeting mechanism analyses can be downloaded for publication-ready figures. The MULocDeep web service is available at https://www.mu-loc.org/. 

Abstract 3D printing has been extensively used for rapid prototyping as well as low-volume production in aerospace, automotive, and medical industries. However, conventional manufacturing processes (i.e., injection molding and CNC machining) are more economical than 3D printing for high-volume mass production. In addition, current 3D printing techniques are not capable of fabricating large components due to the limited build size of commercially available 3D printers. To increase 3D printing throughput and build volume, a novel cooperative 3D printing technique has been recently introduced. Cooperative 3D printing is an additive manufacturing process where individual mobile 3D printers collaborate on printing a part simultaneously, thereby increasing printing speed and build volume. While cooperative 3D printing has the potential to fabricate larger components more efficiently, the mechanical properties of the components fabricated by cooperative 3D printing have not been systematically characterized. This paper aims to develop a data-driven predictive model that predicts the tensile strength of the components fabricated by cooperative 3D printing. Experimental results have shown that the predictive model is capable of predicting tensile strength as well as identifying the significant factors that affect the tensile strength. 

Bistable electroactive polymers (BSEP) combine shape memory with large-strain actuation at the rubbery state to achieve rigid-to-rigid actuation. The stiffness of the BSEP is tunable via glass transition or phase changing. The reversible melting-crystallization of the polymer chains in the phase changing BSEP contributes to the stiffness change within a narrow temperature range. A modulus change of more than 1000 folds can be achieved within 3 °C. Additionally, large actuation strains rivaling those of VHB acrylic elastomers can be obtained at the rubbery state. Explorations regarding potential applications of this material have been focused on tactile displays. In one design, Joule heating of a serpentine-shaped compliant electrode coated on a BSEP film, coupled with a pneumatic pressure source has been employed to raise diaphragm dots with 1.5 mm base diameter to heights up to 0.7 mm. The resulting Braille electronic readers could thus be actuated with low voltages.