Protein is animportant macro molecular organic compound that body need tomaintain itself and grow. Proteins are linear polymers made of 20kinds of amino acids linked by peptide bonds, which fold intounique 3-dimensional structures. Biological functions are closelyrelated to protein structure dynamics, and different proteinstructures generate accordingly different biological functions inbiochemistry process. For a protein structure, structure dynamicsmodels can produce protein movement trajectories, or decomposecollective motions into a combination of independent harmonicoscillators with different frequencies. In this way, many of thosefunctional motions of active sites can be analyzed in detail andunderstood that occur in numerous biological phenomena, such asligand binding and catalytic activity of enzymes. This studyelucidates the latest advances in protein structure harmonicdynamics. Three important physical models are analyzed, andcomputation methods are discussed for protein dynamics. Detailedformulations are given for harmonic dynamics model, includingatomic normal modes analysis (NMA), elastic network model (ENM)and other dynamics methods. Some applications of structuredynamics methods are presented with respect to biologicalresearch. Highlighted by recent advances in protein structuredynamics, it is clear that theoretical methods based on physicalprinciple and simplified models can lend important supports tofrontier research in biology, and protein structure dynamicsbecomes now an important research direction in protein folding andprotein structure prediction.

The simulation ofdissipative particle dynamics (DPD) is a new mesoscale numericsimulation technique. DPD is one of the most important methods forthe study mesoscopic structure of complex systems, and is also oneof important methods linking macroscale with microscalesimulation. The present paper first reviews the development ofDPD, and then elaborates the methodology of DPD, includingtheoretical model, numeric integration methods, selection ofparameters and mapping the simulatied system to the real one.Thirdly, the applications of DPD to the simulation of complexfluid systems are presented, involving assembly of multiphaseflow, separation of microphase, distortion and crash of drops,flows in microchannel and so on. Finally, the current problems andfuture trends are discussed.

The advances andcurrent state of the aerodynamic noise in turbomachinery arereviewed in terms of noise generation mechanism, numericalprediction and control method, respectively. Firstly, thetheoretical development of noise generation mechanism issummarized in terms of discrete noise and broadband noise, inwhich the discrete noise consists of self noise and interactionnoise, and the broadband noise comprises noises induced by flowdistortion, blade tip clearance flow, viscous wake flow and vortexshedding. Then, the advancements of noise numerical prediction arereviewed based on the sound analogy. Thirdly, the noise controlmethods are presented in terms of active noise control, blade wakemanagement, uneven blade control and porous surface control.Finally, achievements of researches on aerodynamic noise inturbomachinery are summarized and prospect is outlined.