Abstract3D shape models are naturally parameterized using vertices and faces, i.e., composed of polygons forming a surface. However, current 3D learning paradigms for predictive and generative tasks using convolutional neural networks focus on a voxelized representation of the object. Lifting convolution operators from the traditional 2D to 3D results in high computational overhead with little additional benefit as most of the geometry information is contained on the surface boundary. Here we study the problem of directly generating the 3D shape surface of rigid and non-rigid shapes using deep convolutional neural networks. We develop a procedure to create consistent 'geometry images' representing the shape surface of a category of 3D objects. We then use this consistent representation for category-specific shape surface generation from a parametric representation or an image by developing novel extensions of deep residual networks for the task of geometry image generation. Our experiments indicate that our network learns a meaningful representation of shape surfaces allowing it to interpolate between shape orientations and poses, invent new shape surfaces and reconstruct 3D shape surfaces from previously unseen images 1 .
Factor VIII is a multidomain protein composed of A1, A2, B, A3, C1, and C2 domains. Deficiency or dysfunction of factor VIII causes hemophilia A, a bleeding disorder. Administration of exogenous recombinant factor VIII as a replacement leads to development of inhibitory antibodies against factor VIII in 15-30% of hemophilia A patients. Hence, less immunogenic preparations of factor VIII are highly desirable. Inhibitory antibodies against factor VIII are mainly directed against immunodominant epitopes in C2, A3, and A2 domains.
We introduce Cubimorph, a modular interactive device that accommodates touchscreens on each of the six module faces, and that uses a hinge-mounted turntable mechanism to self-reconfigure in the user's hand. Cubimorph contributes toward the vision of programmable matter where interactive devices reconfigure in any shape that can be made out of a chain of cubes in order to fit a myriad of functionalities, e.g. a mobile phone shifting into a console when a user launches a game. We present a design rationale that exposes user requirements to consider when designing homogeneous modular interactive devices. We present our Cubimorph mechanical design, three prototypes demonstrating key aspects (turntable hinges, embedded touchscreens and miniaturization), and an adaptation of the probabilistic roadmap algorithm for the reconfiguration.
Factor VIII (FVIII) is a multidomain protein that is deficient in hemophilia A, a clinically important bleeding disorder. Replacement therapy using recombinant human FVIII (rFVIII) is the main therapy. However, approximately 15-30% of patients develop inhibitory antibodies that neutralize rFVIII activity. Antibodies to epitopes in C2 domain, which is involved in FVIII binding to phospholipids, are highly prevalent. Here, we investigated the effect of phosphatidylserine (PS)-containing liposomes, which bind to C2 domain with high affinity and specificity, upon the immunogenicity of rFVIII. Circular dichroism studies showed that PS-containing liposomes interfered with aggregation of rFVIII. Immunogenicity of free- versus liposomal-rFVIII was evaluated in a murine model of hemophilia A. Animals treated with s.c. injections of liposomal-rFVIII had lower total- and inhibitory titers, compared to animals treated with rFVIII alone. Antigen processing by proteolytic enzymes was reduced in the presence of liposomes. Animals treated with s.c. injections of liposomal-rFVIII showed a significant increase in rFVIII plasma concentration compared to animals that received rFVIII alone. Based on these studies, we hypothesize that specific molecular interactions between PS-containing bilayers and rFVIII may provide a basis for designing lipidic complexes that improve the stability, reduce the immunogenicity of rFVIII formulations, and permit administration by s.c. route.
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