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   Williamson, John Garrett; Schell, Caroline; Keller, Michael; Schultz, Joshua (August 2024, Frontiers for Young Minds)

   You can print anything... or can you? 3D printing is an exciting new technology that promises to very quickly create anything people can design. Scientists who want to make soft robots, like Baymax from Big Hero 6^TM, are excited about 3D printers. Our team uses 3D printing to make molds to produce soft robots. Molding is like using a muffin tin to make cupcakes. But can you make anything with 3D printing or are there times when 3D-printed molds do not work? Just like a cupcake liner, 3D-printed molds leave ridges, like a Ruffles potato chip, in soft robots. These ridges are a weak point where cracks can form, causing the robot to pop like a balloon. To prevent this, we sometimes need to make our robots using very smooth molds made from metal. This article talks about when and how 3D printing is useful in making soft robots. 

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   We ask how fiscal deficits are financed in environments with two key features: (i) nominal rigidity, and (ii) a violation of Ricardian equivalence due to finite lives or liquidity constraints. In such environments, deficits can contribute to their own financing through two channels: a boom in real economic activity, which expands the tax base; and a surge in inflation, which erodes the real value of nominal government debt. Our main theoretical result establishes that this mechanism becomes more potent as fiscal adjustment is delayed, leading to full self‐financing in the limit: if the monetary authority does not lean too heavily against the fiscal stimulus, then the government can run a deficit today, refrain from tax hikes or spending cuts in the future, and still see its debt converge back to its initial level. We further demonstrate that a significant degree of self‐financing is achievable when the theory is disciplined by empirical evidence on marginal propensities to consume, nominal rigidities, the monetary policy reaction, and the speed of fiscal adjustment. 

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5. Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again

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