Taehyoun Kim

Frequency-Domain Karhunen -Loeve Method and Its Application to Linear Dynamic Systems

Forthee rsttime,theKarhunen ‐Loeve(KL)procedureisderivedinthefrequencydomainasatoolforcalculating eigenmodes of linear systems. The new derivation is based on the discrete Fourier transform representation of a time average of proe le energy including a proper system response and a proe le function. Taking the variational problem posed as such with respect to the proe le function leads to an eigenformulation in the frequency domain. Choice of a system response for efe cient KL mode calculation and construction of reduced-order systems using the KL eigenmodes are also discussed. To demonstrate themethod, both mechanical and e uid dynamic models are considered. The method is equally useful in extracting eigenmodes of an experimentally generated database. Nomenclature c = wing chord length F = snapshot matrix as dee ned in Eq. (13) F = Fourier operator GIk = impulse response for the kth input GSk = step response for the kth input i

Aeroelastic Model Reduction for Affordable Computational Fluid Dynamics-Based Flutter Analysis

A new approach is presented to generate computational fluid dynamics (CFD)-based reduced-order aerodynamic and aeroelastic models for rapid flutter analysis at an affordable cost. The technique is based on the single-composite-input/eigensystem realization algorithm (SCI/ERA) that has been newly developed at Boeing. Given a large-scaled, discrete-time CFD model whose moving surface boundary is described by multiple structural mode shapes, the SCI/ERA takes time samples of the unsteady response due to a simultaneous excitation of the inputs and identifies the aerodynamic system in terms of low-order matrices. Because the CFD response is sampled almost exclusively for the single representative input this technique can significantly reduce the model construction time. The reduced-order aerodynamic model is coupled with a discrete-time structural model to generate a reduced-order aeroelastic model. For a demonstration of the method, a representative Boeing wind-tunnel airplane modeled by a finite element method and the CFL3D CFD code is studied. It is shown that for the case of 10 structural modes the proposed scheme can reduce the model construction time by a factor of 4-6, yet its unsteady aerodynamic and flutter results are as accurate as those created by other reduction methods.

Bone morphogenetic protein 7 induces mesenchymal-to-epithelial transition in melanoma cells, leading to inhibition of metastasis

Bone morphogenetic protein (BMP) 7 counteracts physiological epithelial‐to‐mesenchymal transition, a process that is indicative of epithelial plasticity in developmental stages. Because epithelial‐to‐mesenchymal transition and its reversed process mesenchymal‐to‐epithelial transition (MET) are also involved in cancer progression, we investigated whether BMP7 plays a role in WM‐266‐4 melanoma cell growth and metastasis. An MTT assay was conducted in WM‐266‐4 and HEK293T cell lines to show the cell growth inhibition ability of BMP7 and cisplatin. Semiquantitative RT‐PCR was used to determine MET in morphologically changed BMP7‐treated melanoma cells. MET‐induced cells expressed less a basic helix‐loop‐helix transcription factor (TWIST) in western blot analysis, and we confirm that BMP receptor (Alk2) siRNA transduction could restore TWIST protein expression via blocking of Smad 1, 5 and 8 signaling. Matrigel invasion and cell migration assays were done to investigate the BMP7‐induced metastasis inhibition ability. BMP7 treatment only slightly reduced cell growth rate, but induced apparent MET. BMP7 also reduced the invasion and migration ability. Furthermore, BMP7 reduced the resistance of WM‐266‐4 cells to cisplatin. Collectively, our findings indicate that the metastatis inhibition ability of BMP7 is involved in MET, and that BMP7 could be used as a potential metastasis inhibitor in human melanoma cells. (Cancer Sci 2009)

Efficient Reduced-Order System Identification for Linear Systems with Multiple Inputs

A new, efficient discrete-time-domain system identification and model reduction method for a large-scaled linear dynamic system with multiple inputs is presented. The method is based on a modification of the classical eigensystem realization algorithm and a simultaneous injection of multiple inputs, so called the single-composite-input method. Because the system response is sampled almost exclusively for the single representative input, this technique can significantly reduce the model construction time as well as the amount of the sampled data. For derivation of the new algorithm, the singular value decomposition is performed using output measurements that are not necessarily attributed to pulse inputs. Application to general computational-fluid-dynamic systems and formulation of reduced-order aeroelastic models are also presented. The efficiency and accuracy of the method is demonstrated via a simple aeroelastic system, which is modeled by the three-dimensional vortex lattice and a six-degrees-of-freedom plate-like structure.

Scheduling garbage collector for embedded real-time systems

This paper proposes a new scheduling method for multiple mutators and a garbage collector running on embedded real-time systems with a single processor and no virtual memory. The hard real-time tasks should reserve a certain amount of heap memory to prevent memory starvation and/or deadline miss. Since the memory requirement depends on the worst-case response time of a garbage collector, the traditional approach in which garbage collection is performed in the background demands large memory space. The proposed scheduling algorithm is based on an aperiodic scheduling technique, sporadic server. This paper also presents a modified copying garbage collection algorithm with hardware support. In order to minimize the worst-case response time of a garbage collector thus reducing the memory requirement, the garbage collector runs as the highest priority task with a preset bandwidth. This paper also investigates the schedulability of a garbage collector and mutator tasks as well as the worst-case memory requirement. Performance analysis shows that the proposed algorithm can provide a considerable reduction in the worst-case memory requirement compared with the background policy. Simulation results demonstrate that the proposed algorithm can produce the feasible memory requirement comparable to the complex on-line scheduling algorithm such as slack stealing.

Diverse Toll-Like Receptors Mediate Cytokine Production by Fusobacterium nucleatum and Aggregatibacter actinomycetemcomitans in Macrophages

ABSTRACT Toll-like receptors (TLRs) orchestrate a repertoire of immune responses in macrophages against various pathogens. Fusobacterium nucleatum and Aggregatibacter actinomycetemcomitans are two important periodontal pathogens. In the present study, we investigated TLR signaling regulating cytokine production of macrophages in response to F. nucleatum and A. actinomycetemcomitans. TLR2 and TLR4 are redundant in the production of cytokines (interleukin-6 [IL-6] and tumor necrosis factor alpha [TNF-α]) in F. nucleatum- and A. actinomycetemcomitans-infected macrophages. The production of cytokines by macrophages in response to F. nucleatum and A. actinomycetemcomitans infection was impaired in MyD88-deficient macrophages. Moreover, cytokine concentrations were lower in MyD88-deficient macrophages than in TLR2/TLR4 (TLR2/4) double-deficient cells. An endosomal TLR inhibitor, chloroquine, reduced cytokine production in TLR2/4-deficient macrophages in response to F. nucleatum and A. actinomycetemcomitans, and DNA from F. nucleatum or A. actinomycetemcomitans induced IL-6 production in bone marrow-derived macrophages (BMDMs), which was abolished by chloroquine. Western blot analysis revealed that TLR2/4 and MyD88 were required for optimal activation of NF-κB and mitogen-activated protein kinases (MAPKs) in macrophages in response to F. nucleatum and A. actinomycetemcomitans, with different kinetics. An inhibitor assay showed that NF-κB and all MAPKs (p38, extracellular signal-regulated kinase [ERK], and Jun N-terminal protein kinase [JNK]) mediate F. nucleatum-induced production of cytokines in macrophages, whereas NF-κB and p38, but not ERK and JNK, are involved in A. actinomycetemcomitans-mediated cytokine production. These findings suggest that multiple TLRs may participate in the cytokine production of macrophages against periodontal bacteria.

Bounding worst case garbage collection time for embedded real-time systems

Execution of programs with various data structures often requires dynamic memory management based on garbage collection for better productivity, robustness and program integrity. In spite of its benefits, garbage collection has not been widely used in embedded real-time systems partly because it often causes unpredictable pause delay. Guaranteeing real-time operations with garbage collection aims to bound and estimate the worst case computation time of a garbage collector as well as application tasks. We introduce a new technique for bounding and estimating the worst case garbage collection time in light of task scheduling. Since the worst case live memory is the dominant factor to determine the worst case garbage collection time, we quantify the worst case live memory using the states of periodic tasks. We also present a predictable real-time copying collection algorithm in order to assess the effectiveness of the proposed approach. Performance evaluation shows that the proposed approach provides a safe and effective bound on the garbage collection time, thus reducing the upper bound of live memory size by up to 35% compared with the trivial bound. It also demonstrates that our algorithm can accomplish 7/spl sim/14% reduction in the memory requirement.

High animal fat intake enhances prostate cancer progression and reduces glutathione peroxidase 3 expression in early stages of TRAMP mice.

Prostate cancer is the most frequently diagnosed cancer in Western men, and more men have been diagnosed at younger ages in recent years. A high‐fat Western‐style diet is a known risk factor for prostate cancer and increases oxidative stress.

Joint scheduling of garbage collector and hard real-time tasks for embedded applications

Programs with complex data structures often require dynamic memory management based on automatic memory reclamation (garbage collection). A major problem in adopting garbage collection for embedded real-time systems is that it often causes unpredictable pauses and that, as a result of such delays, hard real-time tasks may miss their deadlines. In this paper, we propose a new real-time garbage collection technique for embedded applications. In our approach, the system jointly schedules garbage collector and hard real-time tasks using one of the aperiodic server approaches. Our study focuses on reducing memory requirements while guaranteeing the deadlines of hard real-time tasks. To achieve this objective, we model garbage collection requests as aperiodic hard real-time tasks, and schedule them using the sporadic server (SS). We also present an effective live-memory analysis to bound the worst-case garbage collection time. Performance analysis shows that the proposed approach considerably reduces the worst-case memory reservation compared with a background policy. The analytic results are verified by simulation based on trace-driven data.

System Identification for Coupled Fluid-Structure: Aerodynamics is Aeroelasticity Minus Structure

A new method that identifies coupled fluid-structure systems with a reduced set of state variables is presented. Assuming that the structural model is known a priori, from either an analysis or a test and using linear transformations between structural and aeroelastic states, it is possible to deduce aerodynamic information from sampled time histories of the aeroelastic system. More specifically, given a finite set of structural modes, the method extracts a generalized aerodynamic force matrix corresponding to these mode shapes. Once the aerodynamic forces are known, an aeroelastic reduced-order model can be constructed in discrete-time state-space format by coupling the structural model and the aerodynamic system. It is demonstrated that the resulting reduced-order models are accurate, robust, and suitable for aeroelastic analysis at constant Mach, varying density conditions.