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The first paper presents a method to tackle the protein folding problem using principles from statistical physics, emphasizing the stochastic nature of how polypeptides achieve their functional 3D structures. The second paper explores constraint solving within constraint logic programs, specifically focusing on domain reduction through chaotic iterations to aid in debugging efforts. Both works highlight the application of computational techniques in their respective scientific domains.
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In this paper, we introduce an approach to the protein folding problem from the point of view of statistical physics. Protein folding is a stochastic process by which a polypeptide folds into its characteristic and functional 3D structure from random coil. The process involves an intricate interplay…
This work is devoted to constraint solving motivated by the debugging of constraint logic programs a la GNU-Prolog. The paper focuses only on the constraints. In this framework, constraint solving amounts to domain reduction. A computation is formalized by a chaotic iteration. The computed result is…