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Keywords: Gaussian process model Dynamic systems modeling Spatial statistics Reduced-order model Nanoparticle synthesis a b s t r a c t Gaussian process modeling (also known as kriging) is an empirical modeling approach that has been widely applied in engineering for the approximation of deterministic functions, due to its flexibility and ability to(More)
We present a de novo re-determination of the secondary (2°) structure and domain architecture of the 23S and 5S rRNAs, using 3D structures, determined by X-ray diffraction, as input. In the traditional 2° structure, the center of the 23S rRNA is an extended single strand, which in 3D is seen to be compact and double helical. Accurately assigning nucleotides(More)
Many models for the origin of life have focused on understanding how evolution can drive the refinement of a preexisting enzyme, such as the evolution of efficient replicase activity. Here we present a model for what was, arguably, an even earlier stage of chemical evolution, when polymer sequence diversity was generated and sustained before, and during,(More)
RiboVision is a visualization and analysis tool for the simultaneous display of multiple layers of diverse information on primary (1D), secondary (2D), and three-dimensional (3D) structures of ribosomes. The ribosome is a macromolecular complex containing ribosomal RNA and ribosomal proteins and is a key component of life responsible for the synthesis of(More)
Although it is generally accepted that amino acids were present on the prebiotic Earth, the mechanism by which α-amino acids were condensed into polypeptides before the emergence of enzymes remains unsolved. Here, we demonstrate a prebiotically plausible mechanism for peptide (amide) bond formation that is enabled by α-hydroxy acids, which were likely(More)
— We propose a Model Predictive Control (MPC) method to facilitate self-assembly of a quadrupole colloidal system for defect-free two-dimensional crystals. A Langevin equation model is developed to model the thermodynamics of the colloidal system and provides predictions for optimization. A finite prediction horizon is used to optimize the input trajectory(More)