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Recent work on hybrid quantum-classical machine learning systems has demonstrated success in utilizing parameterized quantum circuits (PQCs) to solve the challenging reinforcement learning (RL) tasks, with provable learning advantages over classical systems, e.g., deep neural networks. While existing work demonstrates and exploits the strength of PQC-based models, the design choices of PQC architectures and the interactions between different quantum circuits on learning tasks are generally underexplored. In this work, we introduce a Multi-objective Evolutionary Architecture Search framework for parameterized quantum circuits (MEAS-PQC), which uses a multi-objective genetic algorithm with quantum-specific configurations to perform efficient searching of optimal PQC architectures. Experimental results show that our method can find architectures that have superior learning performance on three benchmark RL tasks, and are also optimized for additional objectives including reductions in quantum noise and model size. Further analysis of patterns and probability distributions of quantum operations helps identify performance-critical design choices of hybrid quantum-classical learning systems. 

The Arf-family GTPases can switch on a central actin regulator named the WAVE Complex to promote actin polymerization. 

Pore size, external shape, and internal complexity of additively manufactured porous titanium scaffolds are three primary determinants of cell viability and structural strength of scaffolds in bone tissue engineering. To obtain an optimal design with the combination of all three determinants, four scaffolds each with a unique topology (external geometry and internal structure) were designed and varied the pore sizes of each scaffold 3 times. For each topology, scaffolds with pore sizes of 300, 400, and 500 µm were designed. All designed scaffolds were additively manufactured in material Ti6Al4V by the direct metal laser melting machine. Compression test was conducted on the scaffolds to assure meeting minimum compressive strength of human bone. The effects of pore size and topology on the cell viability of the scaffolds were analyzed. The 12 scaffolds were ultrasonically cleaned and seeded with NIH3T3 cells. Each scaffold was seeded with 1 million cells. After 32 days of culturing, the cells were fixed for their three-dimensional architecture preservation and to obtain scanning electron microscope images.