Experimental study of oscillating SD8020 foil for propulsion

The thrust producing performance and efficiency of an SD8020 oscillating foil with a symmetrical saw-tooth angle of attack pitching profile was studied through force and torque measurements, as well as dye flow visualization, in the water tunnel at low Reynolds number of 13,000-16,000. The propulsive efficiency and thrust coefficient of the pitching foil were determined as a function of the Strouhal number, pitch amplitude and angular frequency. A propulsive efficiency of 30% was obtained experimentally at low Strouhal numbers. The flow visualization has revealed different wake patterns at various Strouhal numbers and can be classified into three regimes – a drag wake, a transition wake and a thrust wake. The drag wake consists of a combination of a regular Kármán street and an array of ‘primary’ stop-start vortices, whereas the thrust wake consists of a reverse Kármán vortex street, commonly observed in swimming fish. The transition wake regime, which occurs at approximately 0.2 < St < 0.5, is interpreted as a momentum balanced wake, where the thrust developed by the foil approximately balances its produced drag. This wake was observed to either consist of an inclined vortex street, or a paired vortex pattern. Based on the force and efficiency data collected, increasing pitch amplitude and angular frequency was associated with a decrease in propulsive efficiency and an increase in thrust forces produced. A high efficiency value of 0.3, accompanied by a thrust coefficient of order one is found at a low pitch amplitude of 10°, angular frequency of 0.79 rad/s and Strouhal number of 0.05. This presented the best conditions for thrust production observed at low Strouhal and Reynolds numbers

ProactiveCrowd: modeling proactive steering behaviours for agent-based crowd simulation

How to realistically model an agent's steering behavior is a critical issue in agent-based crowd simulation. In this work, we investigate some proactive steering strategies for agents to minimize potential collisions. To this end, a behavior-based modeling framework is first introduced to model the process of how humans select and execute a proactive steering strategies in crowded situations and execute the corresponding behavior accordingly. We then propose behavior models for two inter-related proactive steering behaviors, namely gap seeking and following. These behaviors can be frequently observed in real-life scenarios, and they can easily affect overall crowd dynamics. We validate our work by evaluating the simulation results of our model with the real-world data and comparing the performance of our model with that of another state-of-the-art crowd model. The results show that the performance of our model is better or at least comparable to the compared model in terms of the realism at both individual and crowd level

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

An optical study of interdiffusion in ZnSe/ZnCdSe

Copyright 1996 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. This article appeared in Applied Physics Letters 69, 1579 (1996) and may be found at

Magnetic field calculation for a 13 MeV PET cyclotron

A design study of the main magnet for a 13 MeV cyclotron has been carried out in a joint collaboration between the Korea Cancer Center Hospital (KCCH) and POSTECH. A maximum energy of 13 MeV has been chosen to produce radioisotopes such as /sup 18/F. There are four magnet sectors, each with radial-ridged shape. Maximum magnetic fields are 1.85 T and 0.48 T at hill and valley centers, respectively. The total size of the cyclotron is less than 2 m in diameter. The program TOSCA has been utilized for the field calculation and optimization. In this paper, we describe design parameters of the 13 MeV PET cyclotron, with emphasis on the magnetic field shape and the beam optics calculation. (3 refs)

Integral Grothendieck-Riemann-Roch theorem

We show that, in characteristic zero, the obvious integral version of the Grothendieck-Riemann-Roch formula obtained by clearing the denominators of the Todd and Chern characters is true (without having to divide the Chow groups by their torsion subgroups). The proof introduces an alternative to Grothendieck's strategy: we use resolution of singularities and the weak factorization theorem for birational maps.Comment: 24 page

The Future is Hera! Analyzing Astronomical Over the Internet

Hera is the data processing facility provided by the High Energy Astrophysics Science Archive Research Center (HEASARC) at the NASA Goddard Space Flight Center for analyzing astronomical data. Hera provides all the pre-installed software packages, local disk space, and computing resources need to do general processing of FITS format data files residing on the users local computer, and to do research using the publicly available data from the High ENergy Astrophysics Division. Qualified students, educators and researchers may freely use the Hera services over the internet of research and educational purposes

The activation energy for GaAs/AlGaAs interdiffusion

Copyright 1997 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. This article appeared in Journal of Applied Physics 82, 4842 (1997) and may be found at

Topological superfluid of spinless Fermi gases in p-band honeycomb optical lattices with on-site rotation

In this paper, we put forward to another route realizing topological superfluid (TS). In contrast to conventional method, spin-orbit coupling and external magnetic field are not requisite. Introducing an experimentally feasible technique called on-site rotation (OSR) into p-band honeycomb optical lattices for spinless Fermi gases and considering CDW and pairing on the same footing, we investigate the effects of OSR on superfluidity. The results suggest that when OSR is beyond a critical value, where CDW vanishes, the system transits from a normal superfluid (NS) with zero TKNN number to TS labeled by a non-zero TKNN number. In addition, phase transitions between different TS are also possible