首站-论文投稿智能助手
典型文献
Deep Learning-Assisted Visualized Fluorometric Sensor Array for Biogenic Amines Detection
文献摘要:
Biogenic amines(BAs)are important biomarkers for monitoring food quality and assisting in the diagnosis of disease.Facial,porta-ble,accurate and high-throughput BAs detection is still challenging by the specific sensor compounds development or the compli-cated instrument operation.Deep learning(DL)algorithms are blooming for their superiority on the nonlinear and multidimensional data analysis,which endow the great advantage for the artificial intelligence assisted large sample analysis of the environmental or daily health monitoring.In this work,we developed a deep learning-assisted visualized fluorometric array-based sensing method.Two commercial fluorescent dyes were selected and combined into sensor arrays.Variation in the alkalinity of BAs causes significant and distinct fluorescence changes of the dyes.In conjunction with pattern recognition by the pretrained CNN models,the sensor ar-ray clearly differentiates seven BAs with 99.29%prediction accuracy and allows rapid single and multi-component quantification with a volume fraction range from 200 cm3/m3 to 2500 cm3/m3.This method also provides a new way for meat freshness monitor-ing.We envision that this novel analytical method for BAs can be used as an alternative and promising tool for the detection of a wider variety of analytes.
文献关键词:
作者姓名:
Xiaoqing Tan;Yingying Ye;Hong Liu;Jianxin Meng;Lin-Lin Yang;Fengyu Li
作者机构:
College of Chemistry and Materials Science,Guangdong Provincial Key Laboratory of Functional Supramolecular Coordination Materials and Applications,Jinan University,Guangzhou,Guangdong 510632,China;Department of Pediatrics,Guangdong Women and Children Hospital,Guangzhou,Guangdong 510000,China
引用格式:
[1]Xiaoqing Tan;Yingying Ye;Hong Liu;Jianxin Meng;Lin-Lin Yang;Fengyu Li-.Deep Learning-Assisted Visualized Fluorometric Sensor Array for Biogenic Amines Detection)[J].中国化学(英文版),2022(05):609-616
A类:
Fluorometric,Amines,porta,fluorometric
B类:
Deep,Learning,Assisted,Visualized,Sensor,Array,Biogenic,Detection,amines,BAs,are,important,biomarkers,monitoring,food,quality,assisting,diagnosis,disease,Facial,ble,accurate,high,throughput,detection,still,challenging,by,specific,sensor,compounds,development,compli,cated,instrument,operation,learning,DL,algorithms,blooming,their,superiority,nonlinear,multidimensional,data,analysis,which,endow,great,advantage,artificial,intelligence,assisted,large,sample,environmental,daily,health,In,this,work,developed,deep,visualized,sensing,method,Two,commercial,fluorescent,dyes,were,selected,combined,into,arrays,Variation,alkalinity,causes,significant,distinct,fluorescence,changes,conjunction,pattern,recognition,pretrained,models,clearly,differentiates,seven,prediction,accuracy,allows,rapid,single,component,quantification,volume,fraction,range,from,cm3,This,also,provides,new,way,meat,freshness,We,envision,that,novel,analytical,be,used,alternative,promising,tool,wider,variety,analytes
AB值:
0.671722
相似文献
Visualized SERS Imaging of Single Molecule by Ag/Black Phosphorus Nanosheets
Chenglong Lin;Shunshun Liang;Yusi Peng;Li Long;Yanyan Li;Zhengren Huang;Nguyen Viet Long;Xiaoying Luo;Jianjun Liu;Zhiyuan Li;Yong Yang-State Key Laboratory of High-Performance Ceramics and Superfine Microstructures,Shanghai Institute of Ceramics,Chinese Academy of Sciences,1295 Dingxi Road,Shanghai 200050,People's Republic of China;Graduate School of the Chinese Academy of Sciences,No.19(A)Yuquan Road,Beijing 100049,People's Republic of China;Center of Materials Science and Optoelectronics Engineering,University of Chinese Academy of Sciences,Beijing 100049,People's Republic of China;State Key Laboratory of Oncogenes and Related Genes,Shanghai Cancer Institute,Renji Hospital,Shanghai Jiaotong University School of Medicine,200032 Shanghai,People's Republic of China;School of Physics and Optoelectronics,South China University of Technology,Guangzhou 510641,People's Republic of China;Department of Electronics and Telecommunications,Saigon University,Hochiminh City,Vietnam
Humidity Sensing of Stretchable and Transparent Hydrogel Films for Wireless Respiration Monitoring
Yuning Liang;Qiongling Ding;Hao Wang;Zixuan Wu;Jianye Li;Zhenyi Li;Kai Tao;Xuchun Gui;Jin Wu-State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology,School of Electronics and Information Technology,Sun Yat-Sen University,Guangzhou 510275,People's Republic of China;Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace,Northwestern Polytechnical University,Xi'an 710072,People's Republic of China Acknowledgements J.W.acknowledges financial supports from the National Natural Science Foundation of China(61801525),the Guangdong Basic and Applied Basic Research Foundation(2020A1515010693)and the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(22lgqb17).
106 New Emission-line Galaxies and 29 New Galactic H Ⅱ Regions are Identified with Spectra in the Unknown Data Set of LAMOST DR7
Yan Lu;A-Li Luo;Li-Li Wang;You-Fen Wang;Yin-Bi Li;Jin-Shu Han;Li Qin;Yan-Ke Tang;Bo Qiu;Shuo Zhang;Jian-Nan Zhang;Yong-Heng Zhao-CAS Key Laboratory of Optical Astronomy,National Astronomical Observatories,Chinese Academy of Sciences,Beijing 100101,China;College of Computer and Information Engineering&Institute for Astronomical Science,Dezhou University,Dezhou 253023,China;University of Chinese Academy of Science,Beijing 100049,China;College of Physics and Electronic Information,Dezhou University,Dezhou 253023,China;School of Electronic Information Engineering,Hebei University of Technology,Tianjin 300401,China;Department of Astronomy,School of Physics,Peking University,Beijing 100871,China;Kavli institute of Astronomy and Astrophysics,Peking University,Beijing 100871,China
Adaptive Barebones Salp Swarm Algorithm with Quasi-oppositional Learning for Medical Diagnosis Systems:A Comprehensive Analysis
Jianfu Xia;Hongliang Zhang;Rizeng Li;Zhiyan Wang;Zhennao Cai;Zhiyang Gu;Huiling Chen;Zhifang Pan-Department of General Surgery,The Second Affiliated Hospital of Shanghai University(Wenzhou Central Hospital),Wenzhou 325000,Zhejiang,People's Republic of China;Soochow University,Suzhou,Jiangsu,People's Republic of China;Department of Computer Science and Artificial Intelligence,Wenzhou University,Wenzhou 325035,People's Republic of China;School of Artificial Intelligence,Jilin International Studies University,Changchun 130000,People's Republic of China;Wenzhou Polytechnic,Wenzhou 325035,People's Republic of China;The First Affiliated Hospital of Wenzhou Medical University,Wenzhou 325000,People's Republic of China
Ground-Based Hyperspectral Stereoscopic Remote Sensing Network:A Promising Strategy to Learn Coordinated Control of O3 and PM2.5 over China
Cheng Liu;Chengzhi Xing;Qihou Hu;Qihua Li;Haoran Liu;Qianqian Hong;Wei Tan;Xiangguang Ji;Hua Lin;Chuan Lu;Jinan Lin;Hanyang Liu;Shaocong Wei;Jian Chen;Kunpeng Yang;Shuntian Wang;Ting Liu;Yujia Chen-Department of Precision Machinery and Precision Instrumentation,University of Science and Technology of China,Hefei 230026,China;Centerfor Excellence in Regional Atmospheric Environment,Institute of Urban Environment,Chinese Academy of Sciences,Xiamen 361021,China;Key Lab of Environmental Optics and Technology,Anhui Institute of Optics and Fine Mechanics,Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei 230031,China;Key Laboratory of Precision Scientific Instrumentation of Anhui Higher Education Institutes,University of Science and Technology of China,Hefei 230026,China;Anhui Province Key Laboratory of Polar Environment and Global Change,University of Science and Technology of China,Hefei 230026,China;Institute of Physical Science and Information Technology,Anhui University,Hefei 230601,China;School of Environment and Civil Engineering,Jiangnan University,Wuxi 214122,China;School of Environmental Science and Optoelectronic Technology,University of Science and Technology of China,Hefei 230026,China;School of Earth and Space Sciences,University of Science and Technology of China,Hefei 230026,China
机标中图分类号,由域田数据科技根据网络公开资料自动分析生成,仅供学习研究参考。