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Brain Metabolic Network Redistribution in Patients with White Matter Hyperintensities on MRI Analyzed with an Individualized Index Derived from 18F-FDG-PET/MRI

  • Jie Ma;Xu-Yun Hua;Mou-Xiong Zheng;Jia-Jia Wu;Bei-Bei Huo;Xiang-Xin Xing;Xin Gao;Han Zhang;Jian-Guang Xu
    • Korean Journal of Radiology
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    • v.23 no.10
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    • pp.986-997
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    • 2022
  • Objective: Whether metabolic redistribution occurs in patients with white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) is unknown. This study aimed 1) to propose a measure of the brain metabolic network for an individual patient and preliminarily apply it to identify impaired metabolic networks in patients with WMHs, and 2) to explore the clinical and imaging features of metabolic redistribution in patients with WMHs. Materials and Methods: This study included 50 patients with WMHs and 70 healthy controls (HCs) who underwent 18F-fluorodeoxyglucose-positron emission tomography/MRI. Various global property parameters according to graph theory and an individual parameter of brain metabolic network called "individual contribution index" were obtained. Parameter values were compared between the WMH and HC groups. The performance of the parameters in discriminating between the two groups was assessed using the area under the receiver operating characteristic curve (AUC). The correlation between the individual contribution index and Fazekas score was assessed, and the interaction between age and individual contribution index was determined. A generalized linear model was fitted with the individual contribution index as the dependent variable and the mean standardized uptake value (SUVmean) of nodes in the whole-brain network or seven classic functional networks as independent variables to determine their association. Results: The means ± standard deviations of the individual contribution index were (0.697 ± 10.9) × 10-3 and (0.0967 ± 0.0545) × 10-3 in the WMH and HC groups, respectively (p < 0.001). The AUC of the individual contribution index was 0.864 (95% confidence interval, 0.785-0.943). A positive correlation was identified between the individual contribution index and the Fazekas scores in patients with WMHs (r = 0.57, p < 0.001). Age and individual contribution index demonstrated a significant interaction effect on the Fazekas score. A significant direct association was observed between the individual contribution index and the SUVmean of the limbic network (p < 0.001). Conclusion: The individual contribution index may demonstrate the redistribution of the brain metabolic network in patients with WMHs.

Event-Triggered H2 Attitude Controller Design for 3 DOF Hover Systems (3 자유도 비행체 시스템의 이벤트 트리거 기반의 H2 자세 제어기 설계)

  • Jung, Hyein;Han, Seungyong;Lee, Sangmoon
    • IEMEK Journal of Embedded Systems and Applications
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    • v.15 no.3
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    • pp.139-148
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    • 2020
  • This paper is concerned with the H2 attitude controller design for 3 degree of freedom (DOF) Hover systems with an event-triggered mechanism. The 3 DOF Hover system is an embedded platform for unmanned aerial vehicle (UAV) provided by Quanser. The mathematical model of this system is obtained by a linearization around operating points and it is represented as a linear parameter-varying (LPV) model. To save communication network resources, the event-triggered mechanism (ETM) is considered and the performance of the system is guaranteed by the H2 controller. The stabilization condition is obtained by using Lyapunov-Krasovskii functionals (LKFs) and some useful lemmas. The effectiveness of the proposed method is shown by simulation and experimental results.

Design of Resonant Network for Potable Induction Cooker with 12V Battery of Vehicle (12V 차량용 배터리를 이용한 캠핑용 Induction Cooker 공진 네트워크 설계)

  • Kim, Junghwan;Jang, Eunsu;Park, Sang Min;Lee, Byoung Kuk
    • Proceedings of the KIPE Conference
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    • 2019.11a
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    • pp.28-30
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    • 2019
  • 본 논문은 차량용 12V 배터리 전원을 이용한 캠핑용 Induction Cooker를 설계한다. 캠핑용 Induction Cooker의 전력변환장치에 적합한 DC-link 전압 (VDC) 및 동작 주파수(fsw)를 선정하기 위해 각 조건에 따른 전력변환장치의 공진 네트워크를 설계한다. 또한 이론적 분석 및 시뮬레이션을 통해 각 조건별 전력반도체 소자에서 발생하는 손실 비교 분석을 수행한다. 분석 결과를 통해 공진 네트워크의 적합한 VDC 및 fsw를 선정한다.

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A Study on Development of an Earthquake Ground-motion Database Based on the Korean National Seismic Network (국가지진관측망 기반 지진동 데이터베이스 개발 연구)

  • Choi, Sae-Woon;Rhie, Junkee;Lee, Sang-Hyun;Kang, Tae-Seob
    • Journal of the Earthquake Engineering Society of Korea
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    • v.24 no.6
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    • pp.277-283
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    • 2020
  • In order to improve the ground-motion prediction equation, which is an important factor in seismic hazard assessment, it is essential to obtain good quality seismic data for a region. The Korean Peninsula has an environment in which it is difficult to obtain strong ground motion data. However, because digital seismic observation networks have become denser since the mid-2000s and moderate earthquake events such as the Odaesan earthquake (Jan. 20, 2007, ML 4.8), the 9.12 Gyeongju earthquake (Sep. 12, 2016, ML 5.8), and the Pohang earthquake (Nov. 15, 2017, ML 5.4) have occurred, some good empirical data on ground motion could have been accumulated. In this study, we tried to build a ground motion database that can be used for the development of the ground motion attenuation equation by collecting seismic data accumulated since the 2000s. The database was constructed in the form of a flat file with RotD50 peak ground acceleration, 5% damped pseudo-spectral acceleration, and meta information related to hypocenter, path, site, and data processing. The seismic data used were the velocity and accelerogram data for events over ML 3.0 observed between 2003 and 2019 by the Korean National Seismic Network administered by the Korea Meteorological Administration. The final flat file contains 10,795 ground motion data items for 141 events. Although this study focuses mainly on organizing earthquake ground-motion waveforms and their data processing, it is thought that the study will contribute to reducing uncertainty in evaluating seismic hazard in the Korean Peninsula if detailed information about epicenters and stations is supplemented in the future.

Development of HRP-modified Carbon Composite Biosensor and Electrochemical Analysis of H2O2 (Horseradish peroxidase가 변성된 탄소복합 바이오센서 개발 및 전기화학적 H2O2분석)

  • Park, Deog-Su
    • Journal of the Korean Chemical Society
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    • v.56 no.5
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    • pp.571-576
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    • 2012
  • A sol-gel derived carbon composite electrodes (CCEs) were fabricated by mixing horseradish peroxidase (HRP), sol of tetraethoxysilane (TESO), and graphite powder. The HRP solution was added to the sol solution of TEOS, and then graphite powder was added to this mixture. The resulting carbon ceramic network effectively encapsulated HRP and shows a catalytic reduction starting at -0.2 V for $H_2O_2$. The optimum conditions for $H_2O_2$determination have been characterized with respect to the enzyme loading ratio and pH. The linear range and detection limit of $H_2O_2$ detection were from 0.2 mM to 2.2 mM and 0.035 mM, respectively. The common electroactive interferences such as ascorbic acid, acetaminophene, and uric acid were not affected upon the response to $H_2O_2$ at the HRP biosensor due to low detection potential.

Evaluation of selection program by assessing the genetic diversity and inbreeding effects on Nellore sheep growth through pedigree analysis

  • Illa, Satish Kumar;Gollamoori, Gangaraju;Nath, Sapna
    • Asian-Australasian Journal of Animal Sciences
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    • v.33 no.9
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    • pp.1369-1377
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    • 2020
  • Objective: The main objectives of the present study were to assess the genetic diversity, population structure and to appraise the efficiency of ongoing selective breeding program in the closed nucleus herd of Nellore sheep through pedigree analysis. Methods: Information utilized in the study was collected from the pedigree records of Livestock Research Station, Palamaner during the period from 1989 to 2016. Genealogical parameters like generation interval, pedigree completeness, inbreeding level, average relatedness among the animals and genetic conservation index were estimated based on gene origin probabilities. Lambs born during 2012 and 2016 were considered as reference population. Two animal models either with the use of Fi or ΔFi as linear co-variables were evaluated to know the effects of inbreeding on the growth traits of Nellore sheep. Results: Average generation interval and realized effective population size for the reference cohort were estimated as 3.38±0.10 and 91.56±1.58, respectively and the average inbreeding coefficient for reference population was 3.32%. Similarly, the effective number of founders, ancestors and founder genome equivalent of the reference population were observed as 47, 37, and 22.48, respectively. Fifty per cent of the genetic variability was explained by 14 influential ancestors in the reference cohort. The ratio fe/fa obtained in the study was 1.21, which is an indicator of bottlenecks in the population. The number of equivalent generations obtained in the study was 4.23 and this estimate suggested the fair depth of the pedigree. Conclusion: Study suggested that the population had decent levels of genetic diversity and a non-significant influence of inbreeding coefficient on growth traits of Nellore lambs. However, small portion of genetic diversity was lost due to a disproportionate contribution of founders and bottlenecks. Hence, breeding strategies which improve the genetic gain, widens the selection process and with optimum levels of inbreeding are recommended for the herd.

Effect of packing structure on anisotropic effective thermal conductivity of thin ceramic pebble bed

  • Wang, Shuang;Wang, Shuai;Wu, Bowen;Lu, Yuelin;Zhang, Kefan;Chen, Hongli
    • Nuclear Engineering and Technology
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    • v.53 no.7
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    • pp.2174-2183
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    • 2021
  • Helium cooled solid breeder blanket as an important blanket candidate of the Tokamak fusion reactor uses ceramic pebble bed for tritium breeding. Considering the poor effective thermal conductivity of the ceramic breeder pebble bed, thin structure of tritium breeder pebble bed is usually adopted in the blanket design. The container wall has a great influence on the thin pebble bed packing structure, especially for the assembly of mono-sized particles, and thin pebble bed will appear anisotropic effective thermal conductivity phenomenon. In this paper, thin ceramic pebble beds composed of 1 mm diameter Li4SiO4 particles are generated by the EDEM 2.7. The effective thermal conductivity of different thickness pebble beds in the three-dimensional directions are analyzed by three-dimensional thermal network method. It is observed that thin Li4SiO4 pebble bed showing anisotropic effective thermal conductivity under the practical design size. Normally, the effective thermal conductivity along the bed vertical direction is higher than the horizontal direction due to the gravity effect. As the thickness increases from 10 mm to 40 mm, the effective thermal conductivity of the pebble bed gradually increases.

Machine learning in survival analysis (생존분석에서의 기계학습)

  • Baik, Jaiwook
    • Industry Promotion Research
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    • v.7 no.1
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    • pp.1-8
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    • 2022
  • We investigated various types of machine learning methods that can be applied to censored data. Exploratory data analysis reveals the distribution of each feature, relationships among features. Next, classification problem has been set up where the dependent variable is death_event while the rest of the features are independent variables. After applying various machine learning methods to the data, it has been found that just like many other reports from the artificial intelligence arena random forest performs better than logistic regression. But recently well performed artificial neural network and gradient boost do not perform as expected due to the lack of data. Finally Kaplan-Meier and Cox proportional hazard model have been employed to explore the relationship of the dependent variable (ti, δi) with the independent variables. Also random forest which is used in machine learning has been applied to the survival analysis with censored data.

A Broadband High Gain Planar Vivaldi Antenna for Medical Internet of Things (M-IoT) Healthcare Applications

  • Permanand, Soothar;Hao, Wang;Zaheer Ahmed, Dayo;Falak, Naz;Badar, Muneer;Muhammad, Aamir
    • International Journal of Computer Science & Network Security
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    • v.22 no.12
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    • pp.245-251
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    • 2022
  • In this paper, a high gain, broadband planar vivaldi antenna (PVA) by utilizing a broadband stripline feed is developed for wireless communication for IoT systems. The suggested antenna is designed by attaching a tapered-slot construction to a typical vivaldi antenna, which improves the antenna's radiation properties. The PVA is constructed on a low-cost FR4 substrate. The dimensions of the patch are 1.886λ0×1.42λ0×0.026λ0, dielectric constant Ɛr=4.4, and loss tangent δ=0.02. The width of the feed line is reduced to improve the impedance bandwidth of the antenna. The computed reflection coefficient findings show that the suggested antenna has a 46.2% wider relative bandwidth calculated at a 10 dB return loss. At the resonance frequencies of 6.5 GHz, the studied results show an optimal gain of 5.82 dBi and 85% optimal radiation efficiency at the operable band. The optometric analysis of the proposed structure shows that the proposed antenna can achieve wide enough bandwidth at the desired frequency and hence make the designed antenna appropriate to work in satellite communication and medical internet of things (M-IoT) healthcare applications.

Analysis of Input Factors of DNN Forecasting Model Using Layer-wise Relevance Propagation of Neural Network (신경망의 계층 연관성 전파를 이용한 DNN 예보모델의 입력인자 분석)

  • Yu, SukHyun
    • Journal of Korea Multimedia Society
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    • v.24 no.8
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    • pp.1122-1137
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    • 2021
  • PM2.5 concentration in Seoul could be predicted by deep neural network model. In this paper, the contribution of input factors to the model's prediction results is analyzed using the LRP(Layer-wise Relevance Propagation) technique. LRP analysis is performed by dividing the input data by time and PM concentration, respectively. As a result of the analysis by time, the contribution of the measurement factors is high in the forecast for the day, and those of the forecast factors are high in the forecast for the tomorrow and the day after tomorrow. In the case of the PM concentration analysis, the contribution of the weather factors is high in the low-concentration pattern, and that of the air quality factors is high in the high-concentration pattern. In addition, the date and the temperature factors contribute significantly regardless of time and concentration.