In 3D (bio)printing, it is critical to optimize the printing conditions to obtain scaffolds with designed structures and good uniformities. Traditional approaches for optimizing the parameters oftentimes rely on the prior knowledge of the operators and tedious optimization experiments, which can be both time‐consuming and labor‐intensive. Moreover, with the rapid increase in the types of biomaterial inks and the geometrical complexities of the scaffolds to be fabricated, such a traditional strategy may prove less effective. To address the challenge, an artificial intelligence‐assisted high‐throughput printing‐condition‐screening system (AI‐HTPCSS) is proposed, which is composed of a programmable pneumatic extrusion (bio)printer and an AI‐assisted image‐analysis algorithm. Based on the AI‐HTPCSS, the printing conditions for obtaining uniformly structured hydrogel architectures are screened in a high‐throughput manner. The results show that the scaffolds printed under the optimized conditions demonstrate satisfying mechanical properties, in vitro biological performances, and efficacy in accelerating the diabetic wound healing in vivo. The unique AI‐HTPCSS is expected to offer an enabling platform technology on streamlining the manufacturing of tissue‐engineering scaffolds through 3D (bio)printing techniques in the future.
We prove essentially sharp incidence estimates for a collection of δ-tubes and δ-balls in the plane, where the δ-tubes satisfy an α-dimensional spacing condition and the δ-balls satisfy a β-dimensional spacing condition. Our approach combines a combinatorial argument for small α, β and a Fourier analytic argument for large α, β.
We study the $$\delta $$
δ
-discretized Szemerédi–Trotter theorem and Furstenberg set problem. We prove sharp estimates for both two problems assuming tubes satisfy some spacing condition. For both problems, we construct sharp examples that share common features.
We study the δ-discretized Szemerédi-Trotter theorem and Furstenberg set problem. We prove sharp estimates for both two problems assuming tubes satisfy some spacing condition. For both two problems, we construct sharp examples that have many common features.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.