The two key variables of an Si solar cell, i.e., emitter (n-type window layer) and base (p-type substrate) doping levels or concentrations, are studied using Medici, a 2-dimensional semiconductor device simulation tool. The substrate is ptype and 150 μm thick, the pn junction is 2 μm from the front surface, and the cell is lit on the front surface. The doping concentration ranges from 1 × 1010 cm−3 to 1 × 1020 cm−3 for both emitter and base, resulting in a matrix of 11 by 11 or a total of 121 data points. With respect to increasing donor concentration (Nd) in the emitter, the open-circuit voltage (Voc) is little affected throughout, and the short-circuit current (Isc) is affected only at a very high levels of Nd, exceeding 1 × 1019 cm−3, dropping abruptly by about 12%, i.e., from Isc = 6.05 × 10−9 A·μm−1, at Nd = 1 × 1019 cm−3 to Isc = 5.35 × 10−9 A·μm−1 at Nd = 1 × 1020 cm−3, likely due to minority-carrier, or hole, recombination at the very high doping level. With respect to increasing acceptor concentration (Na) in the base, Isc is little affected throughout, but Voc increases steadily, i.e, from Voc = 0.29 V at Na = 1 × 1012 cm−3 to 0.69 V at Na = 1 × 1018 cm−3. On average, with an order increase in Na, Voc increases by about 0.07 V, likely due to narrowing of the depletion layer and lowering of the carrier recombination at the pn junction. At the maximum output power (Pmax), a peak value of 3.25 × 10−2 W· cm−2 or 32.5 mW· cm−2 is observed at the doping combination of Nd = 1 × 1019 cm−3, a level at which Si is degenerate (being metal-like), and Na = 1 × 1017 cm−3, and minimum values of near zero are observed at very low levels of Nd ≤ 1 × 1013 cm−3. This wide variation in Pmax, even within a given kind of solar cell, indicates that selecting an optimal combination of donor and acceptor doping concentrations is likely most important in solar cell engineering.

The various sintered samples comprising of 72 wt%(Al2O3) : 28 wt%(SiO2) based ceramics were fabricated using a colloidal processing route. The phase analysis of the ceramics was performed using an X-ray diffractometer (XRD) at room temperature confirming the presence of Al2O5Si and Al5.33Si0.67O9.33. The surface morphology of the fracture surface of the different sintered samples having different sizes of grain distribution. The resistive and capacitive properties of the three different sintered samples at frequency sweep (1 kHz to 1 MHz). The contribution of grain and the non-Debye relaxation process is seen for various sintered samples in the Nyquist plot. The ferroelectric loop of the various sintered sample shows a slim shape giving rise to low remnant polarization. The excitation performance of the sample at a constant electric signal has been examined utilizing a designed electrical circuit. The above result suggests that the prepared lead-free ceramic can act as a base for designing of dielectric capacitors or resonators.

목적 : 인공지능의 기계학습 또는 심층학습을 이용한 연구가 다양한 분야에서 시도되고 있다. 본 연구는 공공 시력데이터를 자동화 수집하고, 수집한 데이터를 기계학습에 적용 및 예측하였다. 다양한 학습모델간 성능을 비교 함으로써, 시과학분야에서 적용 가능한 기계학습 최적화모델을 제시함에 있다. 방법 : 국민건강보험(NHISS) 및 통계포털(KOSIS)에 발표된 국민 시력분포 현황관련 자료를 특정 색인을 포함하 는 자료검색기법인 크롤링(crawling)을 사용하여 검색 및 수집을 자동화하였다. 2011년부터 2018년까지 보고된 모든 자료를 수집하였으며, 데이터 학습을 위해 Linear Regression, LASSO, Ridge, Elastic Net, Huber Regression, LASSO/LARS, Passive Aggressive Regressor 그리고 Pansacregressor 총 8개 모델을 사용하여 각각 데이터 학습 하였다. 결과 : 수집한 데이터를 기반으로 기계학습 모델을 통해 2018년을 예측하였다. 각 모델간 2018년도 실제-예측데 이터 차이를 MAE(Mean Absolute Error)와 RMSE(Root Mean Square Error) 점수로 각각 나타냈다. 학습모델 별 차이 중 MAE 평가결과 모델간 우/좌 Linear Regression(0.22/0.22), LASSO(0.83/0.81), RIDGE(0.31/0.31), Elastic Net(0.86/0.84), Huber Regression(0.14/0.07), LASSO/LARS(0.15/0.14), Passive Aggressive Regressor (0.29/0.18) 그리고 RANSA Regressor(0.22/0.22)를 보였다. RMSE에서 Linear Regression(0.40/0.40), LASSO (1.08/1.06), Ridge(0.54/0.54), Elastic Net(1.19/1.17), Huber Regression(0.20/0.20), LASSO/LARS(0.24/0.23), Passive Aggressive Regressor(0.21/0.58) 그리고 RANSA Regressor(0.40/0.40) 각각 나타냈다. 결론 : 본 연구는 자동화 자료검색 및 수집을 위한 크롤링 기법을 이용하여 데이터를 수집하였다. 이를 기반으 로 고전 선형모델을 기계학습에 적용할 수 있도록 하고, 데이터 학습을 위한 8개 학습모델들 간 성능을 비교하였다.

Runt related transcription factors (RUNX), a family of well-known transcription factors, play key regulatory roles in diverse biological processes, such as proliferation, differentiation, and DNA repair. Of RUNX family, RUNX3 is the least well characterized of the three family members. Nevertheless, the role of RUNX3 as a key regulator in essential biological pathways has been reported and inactivation of RUNX3 leads to a variety of disease, such as cancer, via regulation of Wnt signaling and K-ras mutations in many mammalian tissues. Recent studies using RUNX3-deficient cells and mice revealed an association with hematopoiesis and hypersensitivity to granulocytecolony stimulating factor. Nevertheless, protein dynamics associated with RUNX3 remain poorly understood. In the present study, we performed a large-scale protein study from Runx3 knockout (KO) mouse embryonic stem cells (mESC) using a stable isotope labeling by amino acids (SILAC)-based quantitative proteomics approach. The results showed that 67 proteins were significantly up and downregulated after Runx3 KO. Bioinformatic analyses that revealed that these proteins have diverse biological functions, such as substances transport and cellular structure. Thus, our results enhance our current understanding of the function of RUNX3 in mESCs and suggest potential roles for RUNX proteins in diverse diseases. Additionally, our results can be used as a database to help us understand the mechanism of action of RUNX3.

이 논문은 『매의 우물에서』와 『이머의 유일한 질투』가 어떻게 예이츠 자신의 독특한 영성에 대한 생각을 문화적 민족주의와 결합시키는지를 보여준다. 두 극은 쿠훌린을 주제로 사용함으로써 강렬한 감정을 불러일으키고, 이를 통해 민족의식을 불러일으키고 있다. 그 중 첫 번째 작품인 『매의 우물에서』는 쿠훌린이 영생의 샘물을 찾아나선 젊은이로 등장한다. 그러나 쿠훌린은 결국 샘물을 얻지 못하고 떠난다. 두 번째 작품인 『이머의 유일한 질투』는 그보다 훨씬 이후의 이야기를 다루고 있는데, 극에서 쿠훌린은 아들을 제 손으로 죽인 후 미쳐서 파도와 싸운 후 의식을 잃은 모습으로 등장한다. 그 다음으로, 논문에서는 두 극에 영향을 주었다고 생각되는 노 극 『요로』 (養老)와 『아우이노우에』(葵上)에 대한 논의를 통하여 예이츠가 어떻게 노 극의 전통을 따르면서도 동시에 변형시키는지에 대하여 알아본다.