• Title/Summary/Keyword: complex signals

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Arabidopsis cyclin D2 expressed in rice forms a functional cyclin-dependent kinase complex that enhances seedling growth

  • Oh, Se-Jun;Kim, Su-Jung;Kim, Youn Shic;Park, Su-Hyun;Ha, Sun-Hwa;Kim, Ju-Kon
    • Plant Biotechnology Reports
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    • v.2 no.4
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    • pp.227-231
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    • 2008
  • D-class cyclins play important roles in controlling the cell cycle in development and in response to external signals by forming the regulatory subunit of cyclin-dependent kinase (CDK) complexes. To evaluate the effects of D-class cyclins in transgenic rice plants, Arabidopsis cyclin D2 gene (CycD2) was linked to the maize ubiquitin1 promoter (Ubi1) and introduced into rice by the Agrobacterium-mediated transformation method. Genomic deoxyribonucleic acid (DNA), ribonucleic acid (RNA), and Western blot hybridizations of the Ubi1:-CycD2 plants revealed copy number of transgene and its increased expression in leaf and callus cells at messenger RNA (mRNA) and/or protein levels. The H1 kinase assay using the immunoprecipitates of protein extracts from the Ubi1:CycD2 plants and nontransgenic controls demonstrated that the introduced Arabidopsis CycD2 forms a functional CycD2/CDK complex with an unidentified CDK of rice. Shoot and root growth was enhanced in the Ubi1:CycD2 seedlings compared with nontransgenic controls, together, suggesting that Arabidopsis cyclin D2 interacts with a rice cyclin-dependent kinase, consequently enhancing seedling growth.

Rectangular prism pressure coherence by modified Morlet continuous wavelet transform

  • Le, Thai-Hoa;Caracoglia, Luca
    • Wind and Structures
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    • v.20 no.5
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    • pp.661-682
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    • 2015
  • This study investigates the use of time-frequency coherence analysis for detecting and evaluating coherent "structures" of surface pressures and wind turbulence components, simultaneously on the time-frequency plane. The continuous wavelet transform-based coherence is employed in this time-frequency examination since it enables multi-resolution analysis of non-stationary signals. The wavelet coherence quantity is used to identify highly coherent "events" and the "coherent structure" of both wind turbulence components and surface pressures on rectangular prisms, which are measured experimentally. The study also examines, by proposing a "modified" complex Morlet wavelet function, the influence of the time-frequency resolution and wavelet parameters (i.e., central frequency and bandwidth) on the wavelet coherence of the surface pressures. It is found that the time-frequency resolution may significantly affect the accuracy of the time-frequency coherence; the selection of the central frequency in the modified complex Morlet wavelet is the key parameter for the time-frequency resolution analysis. Furthermore, the concepts of time-averaged wavelet coherence and wavelet coherence ridge are used to better investigate the time-frequency coherence, the coherently dominant events and the time-varying coherence distribution. Experimental data derived from physical measurements of turbulent flow and surface pressures on rectangular prisms with slenderness ratios B/D=1:1 and B/D=5:1, are analyzed.

Nonlinear analysis of the effects on the brain waves of the stimulation on specific area of the sole of the foot (발바닥 특정 부위 자극이 뇌파에 미치는 효과에 대한 비선형 분석)

  • Oh, Yeong-seon;Oh, Min-seok;Song, Tae-won
    • Journal of Haehwa Medicine
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    • v.10 no.1
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    • pp.365-374
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    • 2001
  • The brain is one of the most complex systems in nature. Brain waves, or the "EEG", are electrical signals that can be recorded from the brain, either directly or through the scalp. The kind of brain wave recorded depends on the behavior of the animal, and is the visible evidence of the kind of neuronal (brain cell) processing necessary for that behavior. But, EEG had been considered as a virtually infinite-dimensional random signal. However, nonlinear dynamics light on dynamical aspects of the human EEG. The methods of nonlinear dynamics provide excellent tolls for the study of multi-variable, complex system such as EEG. In this study, 20 persons seperated in 2 groups were examined with EEG, one group stimulated on specific area of the sole of the foot with footbed inside the shoes. This experiment resulted in at the group stimulated on specific area of the sole of the foot correlation dimension of P4 and O1 channels increased significantly. Therefore. we obserbed that stimulation on specific area of the body had a constant effections on the specific channels.

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A Study on the Optimum Weight Vector of Linearly Constrained Conditions (선형 제한 조건의 최적 가중 벡터에 대한 연구)

  • Shin, Ho-Sub
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.5
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    • pp.101-107
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    • 2011
  • The optimum weight vector is studied to remove interference and jamming signals in adaptive array antenna system. The optimum weight vector is calculated to apply a minimum variance algorithm and cost function in linearly constrained conditions, and accurately estimates target's signal. Adaptive array antenna system is the system which improves signal to noise ratio(SNR) and decreases interference and jammer power. Adaptive array antenna system delays at tap output of antenna array element. Each tap finally makes the complex signal of one in multiplier complex weight. In order to obtain optimum's weight calculation, optimum weight vector is used in this paper. After simulation, resolution is increased below $3^{\circ}$, and sidelobe is decreased about 10 dB.

A Novel Phase Locked Loop for Grid-Connected Converters under Non-Ideal Grid Conditions

  • Yang, Long-Yue;Wang, Chong-Lin;Liu, Jian-Hua;Jia, Chen-Xi
    • Journal of Power Electronics
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    • v.15 no.1
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    • pp.216-226
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    • 2015
  • Grid synchronization is one of the key techniques for the grid-connected power converters used in distributed power generation systems. In order to achieve fast and accurate grid synchronization, a new phase locked loop (PLL) is proposed on the basis of the complex filter matrixes (CFM) orthogonal signal generator (OSG) crossing-decoupling method. By combining first-order complex filters with relation matrixes of positive and negative sequence voltage components, the OSG is designed to extract specific frequency orthogonal signals. Then, the OSG mathematical model is built in the frequency-domain and time-domain to analyze the spectral characteristics. Moreover, a crossing-decoupling method is suggested to decouple the fundamental voltage. From the eigenvalue analysis point of view, the stability and dynamic performance of the new PLL method is evaluated. Meanwhile, the digital implementation method is also provided. Finally, the effectiveness of the proposed method is verified by experiments under unbalanced and distorted grid voltage conditions.

PVC Classification Algorithm Through Efficient R Wave Detection

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of Sensor Science and Technology
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    • v.22 no.5
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    • pp.338-345
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    • 2013
  • Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and the prevention of possible life threatening cardiac diseases. Most methods for detecting arrhythmia require pp interval, or the diversity of P wave morphology, but they are difficult to detect the p wave signal because of various noise types. Thus, it is necessary to use noise-free R wave. So, the new approach for the detection of PVC is presented based on the rhythm analysis and the beat matching in this paper. For this purpose, we removed baseline wandering of low frequency band and made summed signals that are composed of two high frequency bands including the frequency component of QRS complex using the wavelet filter. And then we designed R wave detection algorithm using the adaptive threshold and window through RR interval. Also, we developed algorithm to classify PVC using RR interval. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate average detection rate of 99.76%, sensitivity of 99.30% and specificity of 98.66%; accuracy respectively for R wave and PVC detection.

Localization of Autophagosome in Porcine Follicular Cumulus-oocyte Complex

  • Lee, Seunghoon;Kim, Dong-Hoon;Im, Gi-Sun;Ock, Sun-A;Ullah, Imran;Hur, Tai-Young
    • Journal of Embryo Transfer
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    • v.32 no.3
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    • pp.105-109
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    • 2017
  • Autophagy is an intracellular degradation and recycling system. Oocyte maturation is dynamic process, in which various proteins should be synthesized and degraded. In our previous study, we reported the loci of autophagosome and dynamics of autophagic activity in porcine oocytes during in vitro maturation. In this study, we verified loci of autophagosome in porcine follicular cumulus-oocyte complex by detection of microtubule-associated protein 1A/1B-light chain 3 (LC3) which is the reliable marker of autophagosome. Porcine ovary including various sizes of follicles was fixed within 1 hour after collection from slaughterhouse. After fixation, immunohistochemistry was conducted on sliced ovary tissue containing various sizes of follicles by using LC3 antibody. As a result, LC3 signal was clearly detected in both cumulus and oocytes of various sizes of follicles. We also found ring shaped signal which represent autophagosome near oocyte membrane. Most of the signals in oocytes were localized nearby cellular membrane while evenly dispersed in cumulus cells. Therefore, this result suggests that autophagy occurs in porcine COCs (cumulus-oocyte complexes) at follicular stage.

Fourier and Wavelet Analysis for Detection of Sleep Stage EEG (수면단계 뇌파 검출을 위한 Fourier 와 Wavelet해석)

  • Seo Hee-Don;Kim Min-Soo
    • Journal of Biomedical Engineering Research
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    • v.24 no.6 s.81
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    • pp.487-494
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    • 2003
  • The sleep stages provides the most basic evidence for diagnosing a variety of sleep diseases. for staging sleep by analysis of EEG(electroencephalogram), it is especially important to detect the characteristic waveforms from EEG. In this paper, sleep EEG signals were analyzed using Fourier transform and continuous wavelet transform as well as discrete wavelet transform. Proposeed system methods. Fourier and wavelet for detecting of important characteristic waves(hump, sleep spindles. K-complex, hill wave, ripple wave) in sleep EEG. Sleep EEG data were analysed using Daubechies wavelet transform method and FFT method. As a result of simulation, we suggest that our neural network system attain high performance in classification of characteristic waves.

A Theoretical Representation of Relaxation Processes in Complex Spin System Using Liouville Space Method

  • Kyunglae Park
    • Bulletin of the Korean Chemical Society
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    • v.14 no.1
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    • pp.21-29
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    • 1993
  • For the study of relaxation processes in complex spin system, a general master equation, which can be used to simulate a vast range of pulse experiments, has been formulated using the Liouville representation of quantum mechanics. The state of a nonequilibrium spin system in magnetic field is described by a density vector in Liouville space and the time evolution of the system is followed by the application of a linear master operator to the density vector in this Liouville space. In this master equation the nuclear spin relaxation due to intramolecular dipolar interaction or randomly fluctuating field interaction is explicitly implemented as a relaxation supermatrix for a strong coupled two-spin (1/2) system. The whole dynamic information inherent in the spin system is thus contained in the density vector and the master operator. The radiofrequency pulses are applied in the same space by corresponding unitary rotational supertransformations of the density vector. If the resulting FID is analytically Fourier transformed, it is possible to represent the final nonstationary spectrum using a frequency dependent spectral vector and intensity determining shape vector. The overall algorithm including relaxation interactions is then translated into an ANSIFORTRAN computer program, which can simulate a variety of two dimensional spectra. Furthermore a new strategy is tested by simulation of multiple quantum signals to differentiate the two relaxation interaction types.

Dioxygen Binding to the Singly Alkoxo-Bridged Diferrous Complex: Properties of [$Fe^{Ⅱ}_2$(N-Et-HPTB)$Cl_2$]$BPh_4$

  • 김은석;이강봉;Jang, Ho G.
    • Bulletin of the Korean Chemical Society
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    • v.17 no.12
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    • pp.1127-1131
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    • 1996
  • [FeⅡ2(N-Et-HPTB)Cl2]BPh4(1), where N-Et-HPTB is the anion of N,N,N',N'-tetrakis(N-ethyl-2-benzimidazolylmethyl)-2-hydroxy-l,3-diaminopropane, has been synthesized to model dioxygen binding to the diferrous centers of proteins. 1 has a singly bridged structure with a μ-alkoxo of N-Et-HPTB and contains two five-coordinate iron(Ⅱ) centers with two chloride ligands as exogenous ligands. 1 exhibits an electronic spectrum with a λmax at 336 nm in acetone. 1 in acetone exhibits no EPR signal at 4 K, indicating diiron(Ⅱ) centers are antiferromagnetically coupled. Exposure of acetone solution of 1 to O2 at -90 ℃ affords an intense blue color intermediate showing a broad band at 586 nm. This absorption maximum of the dioxygen adduct(1/O2) was found in the same region of μ-l,2-peroxo diiron(Ⅲ) intermediates in the related complexes with pendant pyridine or benzimidazole ligand systems. However, this blue intermediate exhibits EPR signals at g = 1.93, 1.76, and 1.59 at 4 K. These g values are characteristic of S = 1/2 system derived from an antiferromagnetically coupled high-spin Fe(Ⅱ)Fe(Ⅲ) units. 1 is the unique example of a (μ-alkoxo)diferrous complex which can bind dioxygen and form a metastable mixed-valence intermediate. At ambient temperature, most of 1/O2 intermediate decays to form a diamagnetic species. It suggests that the dacay reaction of the intermediate might be bimolecular, implying the formation of mixed-valence tetranuclear species in transition state.