Cordycepin induces human lung cancer cell apoptosis by inhibiting nitric oxide mediated ERK/Slug signaling pathway

Nitric oxide (NO) is an important signaling molecule and a component of the inflammatory cascade. Besides, it is also involved in tumorigenesis. Aberrant upregulation and activation of the ERK cascade by NO often leads to tumor cell development. However, the role of ERK inactivation induced by the negative regulation of NO during apoptosis is not completely understood. In this study, treatment of A549 and PC9 human lung adenocarcinoma cell lines with cordycepin led to a reduction in their viability. Analysis of the effect of cordycepin treatment on ERK/Slug signaling activity in the A549 cell line revealed that LPS-induced inflammatory microenvironments could stimulate the expression of TNF-α, CCL5, IL-1β, IL-6, IL-8 and upregulate NO, phospho-ERK (p-ERK), and Slug expression. In addition, constitutive expression of NO was observed. Cordycepin inhibited LPS-induced stimulation of iNOS, NO, p-ERK, and Slug expression. L-NAME, an inhibitor of NOS, inhibited p-ERK and Slug expression. It was also found that cordycepin-mediated inhibition of ERK downregulated Slug, whereas overexpression of ERK led to an upregulation of Slug levels in the cordycepin-treated A549 cells. Inhibition of Slug by siRNA induced Bax and caspase-3, leading to cordycepin-induced apoptosis. Cordycepin-mediated inhibition of ERK led to a reduction in phospho-GSK3β (p-GSK3β) and Slug levels, whereas LiCl, an inhibitor of GSK3β, upregulated p-GSK3β and Slug. Overall, the results obtained indicate that cordycepin inhibits the ERK/Slug signaling pathway through the activation of GSK3β which, in turn, upregulates Bax, leading to apoptosis of the lung cancer cells

Efficient Wear Simulation Methodology for Predicting Nonlinear Wear Behavior of Tools in Sheet Metal Forming

In conventional wear simulation, the geometry must be updated for succeeding iterations to predict the accumulated wear. However, repeating this procedure up to the desired iteration is rather time consuming. Thus, a wear simulation process capable of reasonable quantitative wear prediction in reduced computational time is needed. This study aimed to develop an efficient wear simulation method to predict quantitative wear reasonably in reduced computational time without updating the geometry for succeeding iterations. The wear resistance of a stamping tool was quantitatively evaluated for different punch shapes (R3.0 and R5.5) and coating conditions (physical vapor deposition of CrN and AlTiCrN coatings) by using a progressive die set. To capture the nonlinear wear behavior with respect to strokes, a nonlinear equation from a modified form of Archard’s wear model was proposed. By utilizing the scale factor representing the changes in wear properties with respect to wear depth as input, the simulation can predict the behavior of rapidly increasing wear depth with respect to strokes after failure initiation. Furthermore, the proposed simulation method is efficient in terms of computational time because it does not need to perform geometry updates

초고장력강판의 냉간성형의 금형 마모 평가를 위한 실험적 수치적 해석

학위논문(박사) -- 서울대학교대학원 : 공과대학 재료공학부(하이브리드 재료), 2022. 8. 이명규.The body of an automobile must be lightweight and crash-worthy. The use of advanced high-strength steel reduces the manufacturing cost for automobile body and improves energy absorption during an impact. However, increasing the strength of the steel sheet results in a variety of issues related to tool wear due to a higher forming pressure in the sheets than that in the conventional low-strength steel sheets. Therefore, systematic wear experimentation and prediction procedure are required to quantify the extent of tool wear during the press forming process. This study aims to develop a methodology for quantifying the wear of a sheet metal forming tool using experimental databases and a wear simulation procedure capable of predicting the nonlinear wear behavior of stamping tools in reduced computational time. A progressive die set is used to enable continuous sheet metal stamping at a consistent work rate and designed to conduct the wear test systematically, saving both time and cost. The testing machine is capable of testing four different types of punches simultaneously under a variety of tooling and process parameters, such as different tool materials, punch shapes, and coating conditions. The punches used in the wear test are designed to mimic the curvature geometry of the stamping tool used to manufacture the automotive components. The wear depth, roughness, and surface imaging of the tool, as well as the product roughness are all used for tool wear evaluation in the sheet metal forming process. The wear depth of the punch is close to 0, and the roughness of the punch is also comparable to that of the as-produced prior to failure. When severe wear occurs, the depth of the wear and roughness of the punch rapidly increase. Prior to failure, micro-scratches on the punch surface do not degrade the punch quality. However, worn punches develop a very rough surface on the stamped product. Wear of coated tool is caused by the fretting wear mechanism when stamping uncoated steel sheets. By referring to the measured wear database, it was confirmed that the proposed methodology for wear testing and measurement in the sheet metal forming process is suitable for quantitatively and qualitatively evaluating the wear lifetime, and analyzing the wear characteristics and mechanism, as well as developing a reliable wear prediction model. To capture the nonlinear wear behavior with respect to strokes, a nonlinear equation from a modified form of Archard’s wear model was constructed based on the wear test results. The scale factor, which represents the changes in wear properties with respect to wear depth, was utilized in the wear simulation to avoid the update of geometry from the previous iteration of wear simulation. By formulating a wear coefficient of Archard’s wear model as a function of strokes and implementing it into the scale factor of wear simulation, the nonlinear wear behavior of the stamping tools could be estimated. Therefore, the proposed simulation method is efficient in terms of computational time because it does not need to perform geometry updates.자동차는 연비 효율성 및 승객의 충돌안전성 향상을 위해 차체의 경량화 및 충돌성능을 만족해야 한다. 초고장력강판의 적용은 차체의 생산비용 절감 및 충돌에너지 흡수 성능을 향상할 수 있다. 그러나 초고장력강판의 성형 시 일반적으로 사용되는 판재보다 더 높은 성형 반력으로 인해 예상보다 이른 금형마모를 유발하며 이로 인한 다양한 문제점들을 야기시킨다. 따라서, 프레스 성형 공정에서 금형마모를 정량화하기 위한 효율적인 마모 실험방법 및 예측 기법이 필요하다. 본 연구에서는 판재 성형공정에서 금형마모를 정량화 할 수 있는 실험적 방법 및 해석의 연산 속도를 줄이면서 비선형 마모거동을 예측할 수 있는 효율적인 금형마모 해석 프로세스를 개발하는 것을 목표로 한다. 일정한 성형속도로 연속 판재성형이 가능하며, 실험 시간과 비용 면에서 효율적인 프로그레시브 금형을 금형마모 실험에 사용하였다. 설계된 금형은 다양한 금형강종, 금형형상, 코팅과 같은 다양한 조건으로 제작된 네 가지 펀치 금형을 동시에 실험할 수 있도록 설계하였다. 펀치의 형상은 자동차 부품 성형 금형에서 마모 민감 형상을 모사하여 설계하였다. 금형의 마모깊이 그리고 금형과 제품의 표면거칠기를 정량적으로 측정하여 금형마모를 평가하였다. 제품의 표면에 스크레치로 인한 품질 저하가 발생하기 전까지 금형은 미세한 스크레치는 관찰되었지만 극심한 마모는 발생하지 않았으며, 표면 프로파일 변화는 없었다. 하지만 제품 표면 품질이 저하되었을 때 금형 표면의 마모깊이 및 표면거칠기가 급격하게 증가하였다. 마모실험 결과를 바탕으로 마모 특성을 분석하여 프레팅 마모가 비도금강판의 성형공정에서 주요한 마모 메커니즘인 것을 확인하였으며, 제안된 금형마모 실험방법이 금형의 내마모 성능을 정량적으로 평가하고 마모 특성 및 메커니즘을 분석하기에 적합한 것을 확인하였다. 이러한 비선형 마모거동을 예측하기 위해, 아차드 마모모델을 변형한 수정 아차드 마모모델을 제안하였다. 수정 아차드 마모모델은 마모계수를 성형 타수의 함수로 구성하여 타수에 따른 비선형 마모거동을 예측할 수 있도록 하였다. 이 모델을 마모 시뮬레이션에 적용하여 이전 성형 타수에서의 마모 시뮬레이션으로부터 금형 형상을 이용한 반복적인 시뮬레이션의 수행을 피할 수 있도록 하였다. 따라서 제안한 마모시뮬레이션 방법은 형상 업데이트를 할 필요가 없기 때문에 연산 시간 측면에서 효율적이다.1. Introduction 1 1.1. Research background 1 1.2. Wear testing methods 5 1.3. General wear simulation scheme 10 1.4. Objective and scope 12 2. Experimental setup for evaluating tool wear 15 2.1. Punch design 15 2.2. Design of continuous wear test 18 2.3. Tool and sheet materials 22 2.4. Test conditions 26 2.5. Wear measurement methods 28 2.5.1. Punch surface profile 28 2.5.2. Punch roughness 30 2.5.3. Product roughness 33 3. Wear test results 34 3.1. Wear depth 37 3.2. Punch roughness 41 3.3. Product roughness 50 3.4. Discussion 54 4. Application to stamping analysis considering tool wear 71 4.1. Forming simulation 71 4.2. Tool wear prediction model 82 4.3. Wear simulation 87 4.4. Verification of wear simulation 92 4.5. Discussion 100 5. Tool wear prediciton in forming an automotive part 106 5.1. Simulation setup 106 5.2. Tool wear prediction 109 6. Conclusion 115 Reference 118 Korean abstract 124박

Tool Wear Prediction in the Forming of Automotive DP980 Steel Sheet Using Statistical Sensitivity Analysis and Accelerated U-Bending Based Wear Test

The forming process of ultra-high-strength steel (UHSS) may cause premature damage to the tool surface due to the high forming pressure. The damage to and wear of the tool surface increase maintenance costs and deteriorate the surface quality of the sheet products. Hence, a reliable prediction model for tool wear can help in the efficient management of the quality and productivity of formed sheet products of UHSS. In this study, a methodology is proposed for predicting the wear behavior of stamping tools that are used in the forming process of DP980 steel sheet. Pin-on-disk tests were conducted based on the Taguchi method to develop the tool wear prediction model. Using statistical analysis based on the signal-to-noise (S/N) ratio and ANOVA result, the contact pressure and the sliding distance were selected as the major contact parameters for tool wear. The Archard wear model has a limitation in predicting the nonlinear behavior of tool wear. Therefore, the power-law nonlinear regression model as a function of the contact pressure and the sliding distance was constructed. To verify the reliability of the constructed tool wear prediction model, the U-draw bending tests were designed. The modified U-draw bending test, which accelerates tool wear, is newly designed to evaluate the tool wear for different contact pressures and sliding distances. The modified die generated a contact pressure four times higher than that of the conventional die from the finite element (FE) simulation results. The tool wear prediction model was validated by comparing the predicted results with the experimental results of DP980 sheets formed using the physical vapor deposition (PVD) CrN-coated STD11 tool steel

The State-of-the-Art of Knowledge-Intensive Agriculture: A Review on Applied Sensing Systems and Data Analytics

The application of sensors and information and communication technology (ICT) in agriculture has played a vital role in improving agricultural production and the value chain. Recently, the use of data analytics has shifted agriculture from input-intensive to knowledge-intensive as a large amount of agricultural data can be stored, shared, and analyzed to create information. In this paper, we have reviewed existing sensors and data analytics techniques used in different areas of agriculture. We have classified agriculture into five categories and reviewed the state-of-the-art technology in practice and ongoing research in each of these areas. Also, we have presented a case study of Korean scenario compared with other developed nations and addressed some of the issues associated with it. Finally, we have discussed current and future challenges and provided our views on how such issues can be addressed

Time-resolved Rayleigh scattering measurements of methane clusters for laser-cluster fusion experiments

We present a time-resolved analysis of Rayleigh scattering measurements to determine the average size of methane clusters and find the optimum timing for laser-cluster fusion experiments. We measure Rayleigh scattering and determine the average size of methane clusters varying the backing pressure (P0) from 11 bar to 69 bar. Regarding the onset of clustering, we estimate that the average size of methane clusters at the onset of clustering is Nc0≅20 at 11 bar. According to our measurements, the average cluster radius r follows the power law of r∝P01.86. Our ion time-of-flight measurements indicate that we have produced energetic deuterium ions with kT = 52±2 keV after laser-cluster interaction using CD4 gas at 50 bar. We find that this ion temperature agrees with the predicted temperature from CD4 clusters at 50 bar with r = 14 nm assuming the Coulomb explosion model.11Nsciescopu

Calculation of BAS-TR imaging plate responses to carbon and titanium ion beams

We calculate BAS-TR imaging plate (IP) responses to laser-accelerated heavy ion beams such as carbon ion beam and titanium ion beam. We introduce two theoretical models widely used for the prediction of an IP response. We perform Monte Carlo simulations based on these two models, and compare the predictions with the available experimental data. Our calculations of the IP response to carbon ions show discrepancy in the location of the maximum IP response, while those to titanium ions present a different slope in the IP response curve. We find that both the linear and the exponential models are insufficient to explain the measured IP responses to carbon and titanium ion beams, and attempt to explain the reason for these differences.11Nsciescopuskc

An Intelligent Fault Detection Model for Fault Detection in Photovoltaic Systems

Effective fault diagnosis in a PV system requires understanding the behavior of the current/voltage (I/V) parameters in different environmental conditions. Especially during the winter season, I/V characters of certain faulty states in a PV system closely resemble that of a normal state. Therefore, a normal fault detection model can falsely predict a well-operating PV system as a faulty state and vice versa. In this paper, an intelligent fault diagnosis model is proposed for the fault detection and classification in PV systems. For the experimental verification, various fault state and normal state datasets are collected during the winter season under wide environmental conditions. The collected datasets are normalized and preprocessed using several data-mining techniques and then fed into a probabilistic neural network (PNN). The PNN model will be trained with the historical data to predict and classify faults when new data is fetched in it. The trained model showed better performance in prediction accuracy when compared with other classification methods in machine learning

Rapid, uniform, and efficient heat transfer into dense matter using energetic proton beams with finite energy spreads

© 2022 Elsevier LtdEnergetic charged particles such as laser-driven protons or ions can transfer heat into a small solid-density sample very quickly, sometimes heating it to temperatures beyond 10,000 K. Uniform and efficient heat transfer would be desirable when measuring the physical properties of the sample after heating, but heating a thick solid-density sample both uniformly and efficiently in a short time has been very challenging. Here we show that a thick (> 1 cm) solid-density aluminum sample can be heated rapidly, uniformly, and efficiently all at the same time using an energetic proton beam with a finite energy spread. We perform Monte Carlo simulations to study the relationship between the energy spread of the incident protons and the heat transferred onto the sample for rapid, uniform, and efficient heating. We find that a 100 MeV proton beam with a Gaussian energy spread of ΔE/E ~ 70% can transfer heat into a 32 mm thick solid-density aluminum sample uniformly (temperature nonuniformity 62% heat transfer efficiency) on a sub-nanosecond time scale.11Nsciescopu