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A semi-permanent and durable nanoscale-crack-based sensor by on-demand healing
Park, Byeonghak,Lee, Sori,Choi, Hyesu,Kim, Jong Uk,Hong, Haeleen,Jeong, Chanho,Kang, Daeshik,Kim, Tae-il The Royal Society of Chemistry 2018 Nanoscale Vol.10 No.9
<P>Although sensitivity and durability are desirable in a sensor, both of them cannot be easily achieved. Site-specific and effective signal acquisition on the limited area of a sensor inevitably allows fatigue accumulation and contamination. For example, an ultrasensitive nanoscale-crack-based sensor for detecting a mechanical stimulus with tremendous sensitivity (a gauge factor greater than 2000 under 2% strain), yet limited durability (up to a few thousand stretching cycles in tensile tests) has been presented previously. Herein, we suggest a simple yet robust nanoscale-crack-based sensor that achieves remarkable durability through the use of a self-healable polymer. The self-healable polymer helps the crack gap recover and maintain high stability for 1 million cycles under 2% strain. Moreover, site-specific recovery with infrared light irradiation was demonstrated with monolithic arrayed sensors. The proposed strategy provides a unique solution to achieving highly enhanced durability and high mechanosensitivity, which are typically incompatible.</P>
Kim, Mijie,Park, Yong Joo,Ahn, Huiyeon,Moon, Byeonghak,Chung, Kyu Hyuck,Oh, Seung Min The Korean Society of Environmental Toxicology 2016 환경독성보건학회지 Vol.31 No.-
Objectives Aromatase inhibitors that block estrogen synthesis are a proven first-line hormonal therapy for postmenopausal breast cancer. Although it is known that standardized extract of Ginkgo biloba (EGb761) induces anti-carcinogenic effects like the aromatase inhibitors, the effects of EGb761 on steroidogenesis have not been studied yet. Therefore, the effects of EGb761 on steroidogenesis and aromatase activity was studied using a H295R cell model, which was a good in vitro model to predict effects on human adrenal steroidogenesis. Methods Cortisol, aldosterone, testosterone, and $17{\beta}$-estradiol were evaluated in the H295R cells by competitive enzyme-linked immunospecific assay after exposure to EGb761. Real-time polymerase chain reaction were performed to evaluate effects on critical genes in steroid hormone production, specifically cytochrome P450 (CYP11/ 17/19/21) and the hydroxysteroid dehydrogenases ($3{\beta}$-HSD2 and $17{\beta}$-HSD1/4). Finally, aromatase activities were measured with a tritiated water-release assay and by western blotting analysis. Results H295R cells exposed to EGb761 (10 and $100{\mu}g/mL$) showed a significant decrease in $17{\beta}$-estradiol and testosterone, but no change in aldosterone or cortisol. Genes (CYP19 and $17{\beta}$-HSD1) related to the estrogen steroidogenesis were significantly decreased by EGb761. EGb761 treatment of H295R cells resulted in a significant decrease of aromatase activity as measured by the direct and indirect assays. The coding sequence/Exon PII of CYP19 gene transcript and protein level of CYP19 were significantly decreased by EGb761. Conclusions These results suggest that EGb761 could regulate steroidogenesis-related genes such as CYP19 and $17{\beta}$-HSD1, and lead to a decrease in $17{\beta}$-estradiol and testosterone. The present study provides good information on potential therapeutic effects of EGb761 on estrogen dependent breast cancer.
Lee, Sori,Park, Byeonghak,Kim, Jun Sik,Kim, Tae-il IOP 2016 Nanotechnology Vol.27 No.47
<P>The patterning of high-resolution-featured deep-nanoscale structures with a high aspect ratio (AR) has received increasing attention in recent years as a promising technique for a wide range of applications, including electrical, optical, mechanical and biological systems. Despite extensive efforts to develop viable nanostructure fabrication processes, a superior technique enabling defect-free, high-resolution control over a large area is still required. In this review, we focus on recent important advances in the designs and processes of high-resolution nanostructures possessing a high AR, including hierarchical and 3D patterns. The unique applications of these materials are also discussed.</P>
박은수(Eunsoo Park),장철용(Cheolyong Jang),임병학(Byeonghak Lim),김학일(Hakil Kim) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.6
This paper proposes a traffic sign recognition algorithm that is robust in various environments. Color information is an important element in the traffic sign recognition system, as the performance depends on variations in weather conditions, illumination, and type of cameras used. Besides the above factors, traffic signs also differ across countries. To overcome these problems, our approach involves traffic sign detection, classification, and tracking. In the detection module, color enhancement with maximally stable extremal regions is performed to improve the extracting candidate regions of traffic signs. Support vector machine classifiers with distance to border and histogram of oriented gradient feature vectors are used to detect the traffic signs. Detected traffic signs are thereby classified using convolutional neural networks with fine-tuning. Additionally, Kalman filter-based multi-target tracking not only verifies traffic sign detection but also optimizes the detection of regions of interest. The result of traffic sign detection is 95.67% when trained on the Belgium Traffic Signs Dataset for Detection (BTSD) training dataset and tested on the Germany Traffic Signs Detection Benchmark test dataset. Moreover, while using the BTSD training dataset, the area under the curve of our method is 89.56%. In classification, the performance of INHA Traffic Signs Classification is increased to 97.48% by adding transfer learning.