Strategies for articulated multibody-based adaptive coarse grain simulation of RNA.

Efficient modeling approaches are necessary to accurately predict large-scale structural behavior of biomolecular systems like RNA (ribonucleic acid). Coarse-grained approximations of such complex systems can significantly reduce the computational costs of the simulation while maintaining sufficient fidelity to capture the biologically significant motions. However, given the coupling and nonlinearity of RNA systems (and effectively all biopolymers), it is expected that different parameters such as geometric and dynamic boundary conditions, and applied forces will affect the system's dynamic behavior.

Simulation of manual materials handling: biomechanial assessment under different lifting conditions.

Manual material handling (MMH) tasks were evaluated and compared under different lifting conditions. For the theoretical evaluations, a two-dimensional sagittally symmetric human-body model was established to compute the moment and joint load time histories for MMH tasks for a variety of different lift specifications and constraints such as lifting durations, loads, and modes. Nonlinear control techniques and genetic algorithms were utilized in the optimizations to explore optimal lifting patterns.