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Super-resolution visible photoactivated atomic force microscopy
Lee, Seunghyun,Kwon, Owoong,Jeon, Mansik,Song, Jaejung,Shin, Seungjun,Kim, HyeMi,Jo, Minguk,Rim, Taiuk,Doh, Junsang,Kim, Sungjee,Son, Junwoo,Kim, Yunseok,Kim, Chulhong Nature Publishing Group 2017 Light, science & applications Vol.6 No.11
<P>Imaging the intrinsic optical absorption properties of nanomaterials with optical microscopy (OM) is hindered by the optical diffraction limit and intrinsically poor sensitivity. Thus, expensive and destructive electron microscopy (EM) has been commonly used to examine the morphologies of nanostructures. Further, while nanoscale fluorescence OM has become crucial for investigating the morphologies and functions of intracellular specimens, this modality is not suitable for imaging optical absorption and requires the use of possibly undesirable exogenous fluorescent molecules for biological samples. Here we demonstrate super-resolution visible photoactivated atomic force microscopy (pAFM), which can sense intrinsic optical absorption with ~8 nm resolution. Thus, the resolution can be improved down to ~8 nm. This system can detect not only the first harmonic response, but also the higher harmonic response using the nonlinear effect. The thermoelastic effects induced by pulsed laser irradiation allow us to obtain visible pAFM images of single gold nanospheres, various nanowires, and biological cells, all with nanoscale resolution. Unlike expensive EM, the visible pAFM system can be simply implemented by adding an optical excitation sub-system to a commercial atomic force microscope.</P>
최소 영역 접근 기반의 고속 문자/숫자 인식 가속기 구현
김민국(Minguk Kim),손인호(Inho Son),이동엽(Dongyeop Lee) 한국정보기술학회 2022 Proceedings of KIIT Conference Vol.2022 No.12
문자를 인식하는 방법은 빠른 속도로 발전해왔다. 특히 SW로 문자를 인식하는 방법은 상당한 수준에 도달했다. 그러나 SW를 이용한 문자인식 방법의 발전은 폰노이만 구조의 CPU 한계에 부딪혀 메모리와 프로세서 사이에 데이터 전송 병목현상을 유발한다. 이 논문에서는 문자/숫자 이미지에서 최소한의 영역만을 읽어내서 각 문자/숫자를 구분하는 알고리즘을 제안한다. Xilinx Alveo U50 가속기와 고수준 합성을 통한 HW 구현의 장점을 적극적으로 활용함으로써 전체 영역을 인식하는 SW 기술 대비 약 66,651배 실행시간을 단축했다. 또한 해당 기술은 이미지 전처리에 주로 활용되었던 가속기를 판단 단계에서 활용하는데 큰 의미가 있다. Methods for recognizing charaters have been developed at a rapid pace. In particular, the method using SW has reached a considerable level. However, the development of method using SW encounters the CPU limitation of the Von Neumann structure, causing a data transfer bottleneck between the memory and the processor. In this paper, we propose an algorithm to distinguish each character/number by reading only the minimum area from the character/number image. By using the advantages of HW implementation through Xilinx Alveo U50 accelerator and high-level synthesis, the execution time is reduced about 66,651 times compared to the recognition of the entire area. In addition, this method has great significance in using the accelerator ,which was mainly used for image pre-processing, in the judgment stage.
Yoo, Min-Sang,Shin, Minguk,Kim, Younghun,Jang, Min,Choi, Yoon-E,Park, Si Jae,Choi, Jonghoon,Lee, Jinyoung,Park, Chulhwan Elsevier 2017 CHEMOSPHERE - Vol.175 No.-
<P><B>Abstract</B></P> <P>We developed a single-walled carbon nanotubes (SWCNTs)-based electrochemical biosensor for the detection of <I>Bacillus subtilis,</I> one of the microorganisms observed in Asian dust events, which causes respiratory diseases such as asthma and pneumonia. SWCNTs plays the role of a transducer in biological antigen/antibody reaction for the electrical signal while 1-pyrenebutanoic acid succinimidyl ester (1-PBSE) and ant-<I>B. subtilis</I> were performed as a chemical linker and an acceptor, respectively, for the adhesion of target microorganism in the developed biosensor. The detection range (10<SUP>2</SUP>–10<SUP>10</SUP> CFU/mL) and the detection limit (10<SUP>2</SUP> CFU/mL) of the developed biosensor were identified while the response time was 10 min. The amount of target <I>B. subtilis</I> was the highest in the specificity test of the developed biosensor, compared with the other tested microorganisms (<I>Staphylococcus aureus</I>, <I>Flavobacterium psychrolimnae</I>, and <I>Aquabacterium commune</I>). In addition, target <I>B. subtilis</I> detected by the developed biosensor was observed by scanning electron microscope (SEM) analysis.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A SWCNTs-based biosensor was developed for the detection of <I>Bacillus subtilis.</I> </LI> <LI> The biosensor was composed of SWCNTs, 1-PBSE, and anti-<I>B. subtilis</I> antibody. </LI> <LI> The performance of the biosensor was assessed using a sensor sensitivity and specificity tests. </LI> <LI> The detection limit and detection range were 10<SUP>2</SUP> and 10<SUP>2</SUP>–10<SUP>10</SUP> CFU/mL, respectively. </LI> <LI> The detection time of the biosensor was identified as 10 min. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>