http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Zhongbao Wang,Shaojun Fang,Shiqiang Fu 한국전자통신연구원 2012 ETRI Journal Vol.34 No.5
Accurate synthesis models based on artificial neural networks (ANNs) are proposed to directly obtain the physical dimensions of an asymmetric coplanar waveguide with conductor backing and substrate overlaying (ACPWCBSO). First, the ACPWCBSO is analyzed with the conformal mapping technique (CMT) to obtain the training data. Then, a modified genetic-algorithm-Levenberg-Marquardt (GA-LM) algorithm is adopted to train ANNs. In the algorithm, the maximal relative error (MRE) is used as the fitness function of the chromosomes to guarantee that the MRE is small, while the mean square error is used as the error function in LM training to ensure that the average relative error is small. The MRE of ANNs trained with the modified GA-LM algorithm is less than 8.1%, which is smaller than those trained with the existing GA-LM algorithm and the LM algorithm (greater than 15%). Lastly, the ANN synthesis models are validated by the CMT analysis, electromagnetic simulation, and measurements.
Broadband Stacked Patch Antenna with Low VSWR and Low Cross-Polarization
Zhongbao Wang,Shaojun Fang,Shiqiang Fu 한국전자통신연구원 2010 ETRI Journal Vol.32 No.4
A low cross-polarization broadband stacked patch antenna is proposed. By means of the stacked patch configuration and probe-fed strip feed technique, the VSWR 1.2:1 bandwidth of the patch antenna is enhanced to 22% from 804 MHz to 1,002 MHz, which outperforms the other available patch antennas (<10%). Furthermore, the antenna has a cross-polarization level of less than –20 dB and a gain level of about 9 dBi across the operating bandwidth. Simulation results are compared with the measurements, and a good agreement is observed.
Yang Sheng,Xie JiaJun,Pan ZhiJie,Guan HongMei,Tu YueSheng,Ye YuanJian,Huang ShouBin,Fu ShiQiang,Li KangXian,Huang ZhiWei,Li XiaoQi,Shi ZhanJun,Li Le,Zhang Yang 생화학분자생물학회 2024 Experimental and molecular medicine Vol.56 No.-
The meniscus is vital for maintaining knee homeostasis and function. Meniscal calcification is one of the earliest radiological indicators of knee osteoarthritis (KOA), and meniscal calcification is associated with alterations in biomechanical properties. Meniscal calcification originates from a biochemical process similar to vascular calcification. Advanced glycation end products (AGEs) and their receptors (RAGEs) reportedly play critical roles in vascular calcification. Herein, we investigated whether targeting AGE-RAGE is a potential treatment for meniscal calcification. In our study, we demonstrated that AGE-RAGE promotes the osteogenesis of meniscal cells and exacerbates meniscal calcification. Mechanistically, AGE-RAGE activates mTOR and simultaneously promotes ATF4 accumulation, thereby facilitating the ATF4-mTOR positive feedback loop that enhances the osteogenic capacity of meniscal cells. In this regard, mTOR inhibits ATF4 degradation by reducing its ubiquitination, while ATF4 activates mTOR by increasing arginine uptake. Our findings substantiate the unique role of AGE-RAGE in the meniscus and reveal the role of the ATF4-mTOR positive feedback loop during the osteogenesis of meniscal cells; these results provide potential therapeutic targets for KOA.