DESIGN AND IMPLEMENTATION OF AN INFRARED SCENE TARGET SIMULATOR

A general review is presented of the development of infrared scene targetsimulators; special characters and advantages of scene simulators based on computer-MOSresistor array are discussed by comparing with scaled model simulators; the system principle, structure, key technologies, software and hardware implementation are described.

Development of a New Target Simulator

The.functions of a general target simulator are too few to provide the sonar equipmentand sonar signal-Processing algorithm with a set of integrated experimental data. In this paper anew universal target simulator is developed based on the sound scattering theory. It can produceintegrated simulated data for the various existing sonar equipment and the usual sonar signalprocessing algorithms. The means and efficiency of detection of sonar equipment are improvedby this new simulator In the meantime, this new device stimulates the research on sonar signalprocessing algorithms.

SCSI Target Simulator Based on FC and IP Protocols in TH-MSNS

Storage area networks （SAN） generally use fiber channel （FC） disks, but they are expensive, hard to scale, and incompatible with previous storage arrays. This paper describes an SCSI interface disk array, which is controlled by a simulated target controller, as the target device of an SAN system. A detailed target- mode SCSI middle level design and implementation is described with interfaces to efficiently supervise the entire target simulator. The target simulator has control flexibility, wide applicability, reduced SAN system cost, and compatibility with current SAN systems. The present mass data storage system uses a 2-Gb/s fiber network. Performance and compatibility tests demonstrate the efficiency of the target simulator design.

Allosteric Mechanism of Calmodulin Revealed by Targeted Molecular Dynamics Simulation

Calmodulin （CAM） is involved in the regulation of a variety of cellular signaling pathways. To accomplish its physiological functions, CaM binds with Ca2＋ at its EF-hand Ca2＋ binding sites which induce the conformational switching of CaM. However, the molecular mechanism by which Ca2＋ binds with CaM and induces conformational switching is still obscure. Here we combine molecular dynamics with targeted molecular dynamics simulation and achieve the state-transition pathway of CaM. Our data show that Ca2＋ binding speeds up the conformational transition of CaM by weakening the interactions which stabilize the closed state. It spends about 6.5 ns and 5.25 ns for transition from closed state to open state for apo and holo CaM, respectively. Regarding the contribution of two EF-hands, our data indicate that the first EF-hand triggers the conformational transition and is followed by the second one. We determine that there are two interaction networks which contribute to stabilize the closed and open states, respectively.

A Fast Algorithm for Solving CNOP and Associated Target Observation Tests

Conditional Nonlinear Optimal Perturbation （CNOP） is a new method proposed by Mu et al. in 2003, which generalizes the linear singular vector （LSV） to include nonlinearity. It has become a powerful tool for studying predictability and sensitivity among other issues in nonlinear systems. This is because the CNOP is able to represent, while the LSV is unable to deal with, the fastest developing perturbation in a nonlinear system. The wide application of this new method, however, has been limited due to its large computational cost related to the use of an adjoint technique. In order to greatly reduce the computational cost, we hereby propose a fast algorithm for solving the CNOP based on the empirical orthogonal function （EOF）. The algorithm is tested in target observation experiments of Typhoon Matsa using the Global/Regional Assimilation and PrEdiction System （GRAPES）, an operational regional forecast model of China. The effectivity and feasibility of the algorithm to determine the sensitivity （target） area is evaluated through two observing system simulation experiments （OSSEs）. The results, as expected, show that the energy of the CNOP solved by the new algorithm develops quickly and nonlinearly. The sensitivity area is effectively identified with the CNOP from the new algorithm, using 24 h as the prediction time window. The 24-h accumulated rainfall prediction errors （ARPEs） in the verification region are reduced significantly compared with the ＂true state,＂ when the initial conditions （ICs） in the sensitivity area are replaced with the ＂observations.＂ The decrease of the ARPEs can be achieved for even longer prediction times （e.g., 72 h）. Further analyses reveal that the decrease of the 24-h ARPEs in the verification region is attributable to improved simulations of the typhoon＇s initial warm-core, upper level relative vorticity, water vapor conditions, etc., as a result of the updated ICs in the sensitivity area.