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remain poorly understood. Their structural heterogeneity and chemical complexity make accurate atomistic modeling particularly challenging. Recent advances in machine learning approaches provide a powerful
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complex metamaterial structures. At these frequencies, wave propagation is extremely sensitive to manufacturing imperfections, mode mismatches at interfaces, and energy losses due to reflections
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(scRNA-seq) data, and structural data from cnidarians, and we will develop new algorithms to analyze the evolutionary history of muscle components. You will study the evolution of muscle components during
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understood and difficult to predict. Their behaviour emerges from complex and highly variable interactions between geology, topography, and climate. Across Europe, this diversity leads to strong contrasts in
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of climate models. Simple parameterizations exist to represent melting beneath unresolved or partially resolved ice shelves, but they generally fail to capture the complexity of the response to changing ocean
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. One possible strategy is to use a polycation as a vector by complexing it with the mRNA. A key challenge is identifying a polymer capable of sufficiently complexing mRNA to protect it from enzymatic
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for its complexity and the rich physical phenomena it reveals. Coupling these nonlinear dynamics with a lattice structure, where light can tunnel between sites, enables the exploration of collective effects
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computing and storage capacities. The maturity of virtualization techniques has enabled the emergence of complex virtualized infrastructures, capable of rapidly deploying and reconfiguring virtual and elastic
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exploration of the design space. In this context, artificial intelligence (AI) emerges as a promising solution [3]-[4]: by learning the complex relationships between structural parameters and EM responses, AI
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, droughts, windstorms, and heavy precipitation, are increasingly affecting energy production and distribution systems. At seasonal time scales, these impacts arise from complex mechanisms combining climate