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A New Staining Method Using Different Targeted Fluorescent Carbon Dots For Tissue Sections Analysis and Diagnosis

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SSRN 2024年

作者： Duan, Qianqian Guo, Qingxia Xi, Yanfeng Su, Hong Xue, Juanjuan Zhang, Qi Guo, Xing Han, Haixuan Zhou, Yangming Sang, Shengbo Wang, Xiaojuan Shanxi Key Laboratory of Artificial Intelligence & Micro Nano Sensors College of Integrated Circuits Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan030024 China Department of Pathology Shanxi Tumour Hospital Shanxi Taiyuan030024 China

Visualization imaging of tissue sections is a crucial method for pathological diagnosis of tumour. Carbon dots (CDs) targeting specific organelles have attracted a lot of attention due to their inexpensive raw materials and excellent luminescent property, and they are expected to be used for labeling of nuclei and cytoplasm in tissue sections. In this paper, nuclear targeting carbon dots (N-CDs) with green fluorescence and cytoplasmic targeting carbon dots (C-CDs) with red fluorescence were prepared to achieve co-staining imaging of tissue sections. The two CDs had good fluorescent stability, and their targeting performance and mechanism were studied by cells co-staining and digestion experiments. The section staining method with N-CDs&C-CDs were developed, which is low-cost, simple operation, and time saving. The stained tissues structure distribution were very clear and the information of nucleus and cytoplasm could be extracted. The morphology features and statistic nucleus-cytoplasmic ratio were significantly different and consistent with the results of H&E staining. Therefore, N-CDs&C-CDs are expected to be potential alternative dyes to H&E, and a new method of tissue section staining by dual channel imaging of N-CDs&C-CDs has been developed. These results provide an important research idea for exploring the morphological differences between different cells on tissue sections, quickly and more accurately identifying sections, quantifying the ratio nucleus-cytoplasmic on sections, and then improving the efficiency of clinical diagnosis. © 2024, The Authors. All rights reserved.

关键词： Fluorescence imaging

BP Neural Network Regularized by Wall Temperature Characteristics to Reduce the Ill-Posedness of Two-Dimensional Inverse Heat Transfer Problems in Rotating Disk Cavities

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SSRN 2024年

作者： Deng, Changchun Qiu, Tian Liu, Peng Ding, Shuiting Luo, Xiang Research Institute of Aero-Engine Beihang University Beijing102206 China Aircraft Engine Integrated System Safety Beijing Key Laboratory Beihang University Beijing100191 China Collaborative Innovation Center for Advanced Aero-Engine Beihang University Beijing102206 China National Key Laboratory of Science and Technology on Aero-Engine Aero-thermodynamics Beihang University Beijing100191 China

In the two-dimensional heat transfer experiments of aero-engine rotating disk cavities, the inverse heat transfer problem method can be used to obtain the wall heat flux numerically, which uses the two-dimensional measured wall temperature to solve the rotating disk heat conduction equation. A BP neural network data approximation method is proposed to reduce the ill-posedness of the two-dimensional inverse heat transfer problems in rotating disk cavities in this paper. The priori knowledge of wall temperature characteristics expressed by two-dimensional wall temperature first-order radial derivative distribution is used for BP neural networks’ regularization. The distribution characteristics of the wall temperature first-order radial derivative in a typical preswirl rotating disk cavity were investigated by the flow-thermal coupling numerical simulation. Based on these characteristics, the BP neural network construction and training method with uncertain regularization coefficient is adopted. The numerical experiment results show that compared with the traditional polynomial fitting methods, the BP neural network approximation methods in this paper show significant advantages in data processing performance and stability;The fluctuation amplitude of the heat flux relative error on the disk surface can be reduced by 1 ~ 3 orders of magnitude, reducing the relative error of heat flux in most areas of the disk to within 20% of the original value;The maximum heat flux relative error suppression area where |δqr,cal/δqr,mea × 100%| © 2024, The Authors. All rights reserved.

关键词： Heat conduction

Using Neural Networks to Reduce the Ill-Posedness of Inverse Heat Transfer Problems in the Temperature Rise Transient Process of a Rotating Disk

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SSRN 2024年

作者： Qiu, Tian Deng, Changchun Liu, Peng Ding, Shuiting Luo, Xiang Research Institute of Aero-Engine Beihang University Beijing102206 China Aircraft Engine Integrated System Safety Beijing Key Laboratory Beihang University Beijing100191 China Collaborative Innovation Center for Advanced Aero-Engine Beihang University Beijing102206 China National Key Laboratory of Science and Technology on Aero-Engine Aero thermodynamics Beihang University Beijing100191 China

The working state change of the rotating disk cavities caused by the transient heat transfer is one of the main reasons for the high failure risk of aero-engines in the transient process, which makes the accurate measurement of transient heat transfer characteristics in the transient process of rotating disk cavities become an extremely important issue for the safety design of aero-engines. However, as one of the most widely used methods for measuring heat transfer characteristics, the inverse heat transfer problem method has the characteristics of ill-posed, and the errors of heat transfer characteristics are extremely sensitive to temperature errors. In this paper, a back propagation (BP) neural network approximation technique is used to reduce the ill-posedness of transient inverse heat transfer problems of a rotating disk. The numerical experimental results show that the application of this method in transient inverse heat transfer problems will generate a time-space end edge effect, that is, the ill-posedness in the area near the end edge of time and space has not been effectively reduced, and the wall heat flux still has significant errors in this area. To address this issue, the radial basis function (RBF) neural network local data correction method and time dimension data extension method are proposed to effectively suppress the time-space end edge effect. After improvement, the method proposed in this paper can reduce the transient wall heat flux errors in most time-space regions by 1 ~ 2 orders of magnitude;Within the scope of this study, the minimum proportion of the area where the ill-posedness of transient inverse heat transfer problem is reduced in the entire time-space region is about 91.7%, and the maximum proportion can reach about 98.6%. Finally, the advantages and disadvantages of the two improved methods are compared. © 2024, The Authors. All rights reserved.

关键词： Numerical methods

A Novel Microwave Humidity sensor Based on a Complementary Interdigital Capacitor Resonator

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SSRN 2024年

作者： Wang, Litian Chen, Jie Li, Dan Qian, Lirong Xiong, Yang Miao, Lin Zhang, Rong Li, Cuiping Tianjin Key Laboratory of Film Electronic and Communication Devices School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Resonant for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China

This study presents a novel microwave humidity sensor that utilizes a complementary interdigital capacitor resonator (CIDCR), an advanced design derived from the traditional complementary split ring resonator (CSRR) structure. The CIDCR design enhances the sensor's performance by concentrating the electric field in a more compact region, leading to improved sensitivity and miniaturization. The sensor is coated with a composite film of chitosan (CS) and polyacrylamide-glycerol (PAMG), combining the high moisture sensitivity of PAMG with the stability of CS. The CIDCR-based sensor demonstrates superior performance, including high sensitivity, a broad detection range, rapid response/recovery times, and excellent long-term stability. Density functional theory (DFT) calculations further elucidate the moisture-sensitive mechanisms at the molecular level, highlighting the role of hydrogen bonding in the composite film. Application tests confirm the sensor's potential for use in respiratory monitoring, non-contact sensing, and health monitoring, showcasing the advantages of the CIDCR structure in achieving enhanced humidity sensing capabilities. © 2024, The Authors. All rights reserved.

关键词： Humidity sensors

Non-Stoichiometric Protic Ionic Liquids for Efficient Carbon Dioxide Capture and Subsequent Conversion Under Mild Conditions

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SSRN 2024年

作者： Wang, Litian Chen, Jie Wang, Shuai Zhou, Tongyao Li, Dan Li, Cuiping Qian, Lirong Xiong, Yang Miao, Lin Xie, Zhiyong Tianjin Key Laboratory of Film Electronic and Communication Devices School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China China Tianjin Bohua Yongli Chemical Industry CO. Ltd Tianjin30045 China

Protic ionic liquids (PILs) have emerged as innovative solvents with significant potential for CO2 capture and transformation, presenting a sustainable alternative to conventional methods which often involve energy-intensive processes or environmentally detrimental chemicals. Herein, a novel strategy for CO2 capture and conversion at mild conditions using non-stoichiometric protic ionic liquids (NPILs) was demonstrated for the first time. These NPILs, employed as sorbents, solvents, and catalysts, were composed of imidazole (Im) and 1,8-diazabicyclo [5.4.0] undec-7-ene (DBU) in various ratios. Correlations between the mole ratio of DBU/Im and physicochemical properties such as viscosity, conductivity, thermal stability, and the distribution of neutral and ionic species were systematically investigated. Effects of the absorption temperature and CO2 partial pressure on the absorption capacity were also studied. Different absorption mechanisms, including carbonate and carbamate pathways, were analyzed using FT-IR and NMR spectroscopy. Moreover, the fixed CO2 could be catalytically converted to quinazoline-2,4(1H,3H)-diones under exceptionally mild reaction conditions (1atm, 50 °C, metal-free process). A plausible reaction mechanism involving simultaneous CO2 activation and substrate activation for the transformation of CO2 into quinazoline-2,4(1H,3H)-diones was verified through NMR spectra. It is believed that the new insights into the CO2 mechanism will facilitate the rationaldesign of functional ionic liquids for CO2 capture, utilization, and storage in the future. © 2024, The Authors. All rights reserved.

关键词： Carbon dioxide

TL-KDNET: A Malicious Traffic Detection Model Integrating Transfer Learning and Knowledge Distillation

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TL-KDNET: A Malicious Traffic Detection Model Integrating Tr...

International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Kun Yu YuanYuan Huang Linshan Zhang Jun Lv Jiazhong Lu School of Cybersecurity (Xin Gu Industrial College Chengdu University of Information Technology Chengdu China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu China SUGON Industrial Control and Security Center Chengdu China MetaX Integrated Circuits (Shanghai) Co. Ltd

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

With the evolution of cyberattacks, traditional methods for malicious traffic detection face increasingly complex threats. To address this challenge, we propose a novel model, TL-KDNet, which integrates transfer learning, domain adaptation, and knowledge distillation techniques to enhance the accuracy and generalization capabilities of malicious traffic detection. In our model, KullbackLeibler (KL) divergence serves as a core module to quantify the differences in probability distributions between the source and target domains, thereby effectively facilitating knowledge transfer from known source domains to unknown target domains. Additionally, by leveraging Maximum Mean Discrepancy (MMD) and a single-sample distillation loss function, we achieve alignment of domain features and transfer of knowledge. Experimental results demonstrate that TL-KDNet improves detection accuracy by 4% on public datasets compared to existing methods.

关键词： Performance evaluation Adaptation models Accuracy Quantization (signal) Computational modeling Scalability Transfer learning Training data Real-time systems Probability distribution

Ultrafast polarization modulation with high-purity chiral quasi-BIC metasurfaces

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Chinese Optics Letters 2025年第5期 142-148页

作者：赖方兴范宇斌沙新博邓画春蒋雄肖淑敏黄灿宋清海 Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of Technology (Shenzhen) Department of Electrical Engineering City University of Hong Kong Heilongjiang Provincial Key Laboratory of Advanced Quantum Functional Materials and Sensor Devices

Precise control of the polarization state of light on ultrafast time scales plays a key role in revealing the inherent chiral or anisotropic optical responses in various material systems, and it is crucial for applications that require complex polarization encoding. Here, we explore ultrafast polarization control enabled by silicon-based chiral bound state in the continuum（BIC）metasurfaces. By utilizing the intrinsic chiral mode, we achieve high-purity chiral reflection light（S3～-0.92） and rapid modulation（～0.4 ps） of polarization states through all-optical methods. Unlike traditional polarization modulation techniques, our approach leverages the unique advantages of slanted etching dielectric chiral BIC metasurfaces, which facilitate high-Q resonance and exhibit narrow linewidths. These advantages allow swift alterations in polarization states with minimal modulation energy consumption, which should help for greater control of light in integrated photonic applications.

关键词：

LOGNET: A Knowledge Distillation-Based Model for Log Anomaly Detection

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LOGNET: A Knowledge Distillation-Based Model for Log Anomaly...

International Conference on Wavelet Active Media Technology and Information Processing (ICWAMTIP)

作者： Kun Yu Yuanyuan Huang Linshan Zhang Jun Lv Jiazhong Lu School of Cybersecurity (Xin Gu Industrial College) Chengdu University of Information Technology Chengdu China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu China SUGON Industrial Control and Security Center Chengdu China MetaX Integrated Circuits (Shanghai) Co. Ltd

ISBN: (数字)9798331519254

ISBN: (纸本)9798331519261

Due to the diverse nature of attack forms, supervised log anomaly detection models require a large volume of labeled data, making the annotation process time-consuming and labor-intensive. Conversely, unsupervised log anomaly detection models often struggle to effectively capture log features and accurately identify anomalous logs. To address these challenges, this study constructs a collaborative learning framework and proposes the LogNet model. This framework enables mutual learning between two distinct models, enhancing their performance synergistically. In the LogNet model, log data is first converted into directed graphs, leveraging the strengths of Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT). Through collaborative learning, the two models guide each other, boosting their detection capabilities. The effectiveness of LogNet is validated on five public datasets, with experimental results demonstrating that LogNet significantly outperforms traditional models in malicious log detection, achieving up to a 4 % improvement in accuracy.

关键词： Knowledge engineering Solid modeling Accuracy Federated learning Graph convolutional networks Information processing Media Feature extraction Data models Anomaly detection

Applications of MXenes in human-like sensors and actuators

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Nano Research 2023年第4期16卷 5767-5795页

作者： Jinbo Pang Songang Peng Chongyang Hou Xiao Wang Ting Wang Yu Cao Weijia Zhou Ding Sun Kai Wang Mark H.Rümmeli Gianaurelio Cuniberti Hong Liu Institute for Advanced Interdisciplinary Research(iAIR) Collaborative Innovation Center of Technology and Equipment for Biological Diagnosis and Therapy in Universities of ShandongUniversity of JinanJinan 250022China Institute for Materials Science and Max Bergmann Center of Biomaterials Technische Universität DresdenDresden 01069Germany Center for Advancing Electronics Dresden Technische Universität DresdenDresden 01069Germany Dresden Center for Computational Materials Science Technische Universität DresdenDresden 01062Germany Dresden Center for Intelligent Materials(GCL DCIM) Technische Universität DresdenDresden 01062Germany High-Frequency High-Voltage Device and Integrated Circuits R&D Center Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Microelectronic Devices&Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijing 100029China Shenzhen Key Laboratory of Nanobiomechanics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China State Key Laboratory of Biobased Material and Green Papermaking Qilu University of TechnologyShandong Academy of SciencesJinan 250353China School of Bioengineering Qilu University of TechnologyShandong Academy of ScienceJinan 250353China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Ministry of Education) Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Northeast Electric Power UniversityJilin 132012China School of Electrical Engineering Weihai Innovation Research InstituteQingdao UniversityQingdao 266000China School of Electrical and Computer Engineering Jilin Jianzhu UniversityChangchun 130118China Institute for Complex Materials Leibniz Institute for Solid State and Materials Research Dresden(IFW Dresden)20 Helmholtz StrasseDresden 01069Germany College of Energy Soochow Institute for Energy and Materials Innovations Soochow UniversitySuzhou 215006China Key L

Human beings perceive the world through the senses of sight,hearing,smell,taste,touch,space,and *** first five senses are prerequisites for people to *** sensing organs upload information to the nervous systems,including the brain,for interpreting the surrounding ***,the brain sends commands to muscles reflexively to react to stimuli,including light,gas,chemicals,sound,and ***,as an emerging two-dimensional material,has been intensively adopted in the applications of various sensors and *** this review,we update the sensors to mimic five primary senses and actuators for stimulating muscles,which employ MXene-based film,membrane,and composite with other functional ***,a brief introduction is delivered for the structure,properties,and synthesis methods of ***,we feed the readers the recent reports on the MXene-derived image sensors as artificial retinas,gas sensors,chemical biosensors,acoustic devices,and tactile sensors for electronic ***,the actuators of MXene-based composite are ***,future opportunities are given to MXene research based on the requirements of artificial intelligence and humanoid robot,which may induce prospects in accompanying healthcare and biomedical engineering applications.

关键词： MXenes sensors actuators gas sensors biosensors tactile sensors sound sensors artificial retina