Functionally heterogeneous porous scaffold design for tissue engineering

Most of the current tissue scaffolds are mainly designed with homogeneous porosity which does not represent the spatial heterogeneity found in actual tissues. Therefore engineering a realistic tissue scaffolds with properly graded properties to facilitate the mimicry of the complex elegance of native tissues are critical for the successful tissue regeneration. In this work, novel bio-mimetic heterogeneous porous scaffolds have been modeled. First, the geometry of the scaffold is extracted along with its internal regional heterogeneity. Then the model has been discretized with planner slices suitable for layer based fabrication. An optimum filament deposition angle has been determined for each slice based on the contour geometry and the internal heterogeneity. The internal region has been discritized considering the homogeneity factor along the deposition direction. Finally, an area weight based approach has been used to generate the spatial porosity function that determines the filament deposition location for desired biomimetic porosity. The proposed methodology has been implemented and illustrative examples are provided. The effective porosity has been compared between the proposed design and the conventional homogeneous scaffolds. The result shows a significant error reduction towards achieving the biomimetic porosity in the scaffold design and provides better control over the desired porosity level. Moreover, sample designed structures have also been fabricated with a NC motion controlled micro-nozzle biomaterial deposition system

Detail-Preserving Controllable Deformation from Sparse Examples

published_or_final_versio

Flexibility in metal–organic frameworks : a basic understanding

Much has been written about the fundamental aspects of the metal-organic frameworks (MOFs). Still, details concerning the MOFs with structural flexibility are not comprehensively understood. However, a dramatic increase in research activities concerning rigid MOFs over the years has brought deeper levels of understanding for their properties and applications. Nonetheless, robustness and flexibility of such smart frameworks are intriguing for different research areas such as catalysis, adsorption, etc. This manuscript overviews the different aspects of framework flexibility. The review has touched lightly on several ideas and proposals, which have been demonstrated within the selected examples to provide a logical basis to obtain a fundamental understanding of their synthesis and behavior to external stimuli

VeRi3D: Generative Vertex-based Radiance Fields for 3D Controllable Human Image Synthesis

Unsupervised learning of 3D-aware generative adversarial networks has lately made much progress. Some recent work demonstrates promising results of learning human generative models using neural articulated radiance fields, yet their generalization ability and controllability lag behind parametric human models, i.e., they do not perform well when generalizing to novel pose/shape and are not part controllable. To solve these problems, we propose VeRi3D, a generative human vertex-based radiance field parameterized by vertices of the parametric human template, SMPL. We map each 3D point to the local coordinate system defined on its neighboring vertices, and use the corresponding vertex feature and local coordinates for mapping it to color and density values. We demonstrate that our simple approach allows for generating photorealistic human images with free control over camera pose, human pose, shape, as well as enabling part-level editing