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Bump version to v0.3.1 and update README badge
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Project.toml

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name = "MaterialPointGenerator"
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uuid = "18deba1c-5063-41ee-a388-01f264c5a914"
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authors = ["ZenanH <zenan.huo@outlook.com>"]
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version = "0.3.0"
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version = "0.3.1"
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[deps]
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DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
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[compat]
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DelimitedFiles = "1"
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FastPointQuery = "0.3"
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FastPointQuery = "0.4"
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LiveServer = "1.5"
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NearestNeighbors = "0.4"
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PrecompileTools = "1.2"

README.md

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[![CI](https://github.com/LandslideSIM/MaterialPointGenerator.jl/actions/workflows/ci.yml/badge.svg)](https://github.com/LandslideSIM/MaterialPointGenerator.jl/actions/workflows/ci.yml)
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[![Stable](https://img.shields.io/badge/docs-stable-blue.svg?logo=quicklook)](https://LandslideSIM.github.io/MaterialPointGenerator.jl/stable)
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[![Dev](https://img.shields.io/badge/docs-dev-red.svg?logo=quicklook)](https://LandslideSIM.github.io/MaterialPointGenerator.jl/dev)
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[![Version](https://img.shields.io/badge/version-v0.3.0-pink)]()
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[![Version](https://img.shields.io/badge/version-v0.3.1-pink)]()
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During the EGU2023 conference, when I presented a high-performance MPM (Material Point Method) solver, I was asked,
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"How do you discretize the computational model for the MPM?" I didn't have a clear answer (I didn't even consider it a problem) because the models were relatively simple and could be generated directly using some straightforward functions. However, as computational models gradually became more complex and diverse, I began to realize that this was indeed a very good question. The preprocessing for MPM should not be a computationally intensive task; it should be fast enough. Yet, I couldn't find a "plug-and-play" generalized code for this purpose. Some literatures have contributed to this issue, and I built upon their work to create a comprehensive and refined julia package.

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