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Additionally we show the results of adsorption on compressed nanotubes.
Additionally, we show examples of carbon estimates indicating the benefits of an increasing resolution.
Additionally, we show that residually finite groups of finite exponent are never just-infinite.
Additionally, we show the (strong) scalability and multi-tracer efficiency using several benchmark tests.
Additionally, we show that limt→0‖Tf(t)‖t="‖f‖∞ holds for all f∈L∞(Cn).
Additionally, we show that the Lie algebra generates Gaussian random variables.
Additionally, we show a correlation between α-sheet structural stability and inhibitory activity.
Additionally, we show that MLMs and GEEs have adequate performance for common research designs.
Additionally, we show the improvement of the classification results by appropriate data preprocessing.
Additionally, we show a software design for heterogeneous computations on GPU and CPU utilizing optimized kernels.
Additionally, we show how the Open PHACTS Discovery Platform implements this extended architecture.
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