Prediction of new Ti-N phases using machine learned interatomic potential

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Netflix's plan drew warnings that it would give the dominant streaming player even more power over actors and screenwriters, while putting further pressure on local cinemas.

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The pipeline was very similar to icon-to-image above: ask Opus 4.5 to fulfill a long list of constraints with the addition of Python bindings. But there’s another thing that I wanted to test that would be extremely useful if it worked: WebAssembly (WASM) output with wasm-bindgen. Rust code compiled to WASM allows it to be run in any modern web browser with the speed benefits intact: no dependencies needed, and therefore should be future-proof. However, there’s a problem: I would have to design an interface and I am not a front end person, and I say without hyperbole that for me, designing even a simple HTML/CSS/JS front end for a project is more stressful than training an AI. However, Opus 4.5 is able to take general guidelines and get it into something workable: I first told it to use Pico CSS and vanilla JavaScript and that was enough, but then I had an idea to tell it to use shadcn/ui — a minimalistic design framework normally reserved for Web Components — along with screenshots from that website as examples. That also worked.

t.to_gpu(); // optional — Metal acceleration

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增值税法第三条所称不动产,是指不能移动或者移动后会引起性质、形状改变的资产,包括建筑物、构筑物等。