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Molecule aging induced by electron attacking

Journal of Energy Chemistry 2024年第6期93卷 519-525,I0013页

作者： Ping Song Yining Dong Xue Gong Mingbo Ruan Baoxin Ni Xuanhao Mei Kun Jiang Weilin Xu State Key Laboratory of Electroanalytical Chemistry and jilin province Key Laboratory of Low Carbon Chemical Power Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun 130022JilinChina School of Applied Chemistry and Engineering University of Science and Technology of Chin1Hefei 230026AnhuiChina Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials Collaborative Innovation Center of Chemistry for Energy MaterialsDepartment of ChemistryFudan UniversityShanghai 200438China

Here we propose a new concept of"molecule aging":with some special treatment,a molecule could be"aged"by losing some unknown tiny particles or pieces from atoms in the molecule,Such"aging"or loss of unknown tiny particles does not change apparently its molecular structure or chemical composition,but some physicochemical properties could be changed *** further confirm such"molecule aging"via a long-term electron attacking to age water(H_(2)O)*** IR spectra show no structural difference between the fresh water and the aged one,while the NMR spectra show that the electron attacking can decrease the size of water *** facts indicate that the electron attacking indeed can"affect"the structure of water molecule slightly but without damaging to its basic molecule *** exploration reveals that the hydrogen evolution reaction(HER)activity of the aged water molecule is lower than the fresh water on the same Pt/C *** density functional theory calculations indicate that the shortened O-H bond in H_(2)O indeed can present lower HER activity,so the observed size decrease of water clusters from NMR probably could be attributed to the shortening of O-H bond in water *** results indicate significantly that the molecule aging can produce materials with new functions for new possible applications.

关键词： Aging of molecules Electron attacking Full width at half maxima Hydrogen evolution reaction

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Aggregation-induced T_(1)/T_(2) contrast enhancement for magnetic resonance imaging-guided intraoperative surgery

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Science China Chemistry 2024年第6期67卷 2046-2055页

作者： Wenbo Sun Bin Yu Dianshuai Huang Chunhuan Jiang Wei Wang Jianhua Liu Zonghua Wang Lehui Lu State Key Laboratory of Electroanalytical Chemistry Changchun Institute of Applied ChemistryChinese Academy of SciencesChangchun130022China College of Chemistry and Chemical Engineering Shandong Sino-Japanese Center for Collaborative Research of Carbon NanomaterialsQingdao Application Technology Innovation Center of Photoelectric Biosensing for Clinical Diagnosis and TreatmentQingdao UniversityQingdao266071China Department of Radiology Second Hospital of Jilin UniversityChangchun130041China

Magnetic resonance imaging(MRI)plays an important role in precision medicine that is hampered by the lack of contrast agents with high efficiency and the ability to translate diagnostic accuracy into therapeutic ***,we demonstrate a DNA-based MRI probe that overcomes previous single-mode enhancement and provides a mechanism of action for aggregationinduced dual-modal MRI signal enhancement.A facile method is developed to produce aggregated T_(1)/T_(2)dual-modal NaGdF_(4):Dy@PDA-DNA(PDA=polydopamine)MRI *** aggregated,this probe can further amplify MRI signal intensity and exhibit improved geometrical and positional stability in *** performance of the NaGdF_(4):Dy@PDA-DNA MRI probe toward MRI-guided preoperative planning and visualization-guided surgery is verified using an orthotopic tumor-bearing mouse *** result shows that the rapid metabolism of the degraded probe leads to the mitigation of long-term toxic ***,the developed high-performance MRI probe is of great significance for enhancing MRI diagnostic accuracy into precision medical therapeutic interventions.

关键词： MRI probe DNA aggregation-induced T_(1)/T_(2)contrast enhancement precision medicine degradable probe

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Sugar-Based Water Retention Agents in Meat Products: Enhancing Water-Holding Capacity and Promoting Health Benefits

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Food Science and Human Wellness 2024年

作者： Jiahui Ma Pengyu Lei Lei Wang Jia Yi Yilei Ma Yimeng Fang Linkai Qu Li Luo Kun Zhang Libo Jin Qinsi Yang Wei Wu Da Sun Bioengineering College of Chongqing University Institute of Life Sciences & Biomedical collaborative innovation center of Zhejiang province Wenzhou University Wenzhou Institute University of Chinese Academy of Sciences Affiliated Dongguan Hospital Southern Medical University College of Veterinary Medicine jilin University

For the purpose of satisfying high demands for taste， color， flavor， and storage of meat products， water retention agents (WRAs) play an important role. Phosphate has been widely used as an attractive functional material for water retention in current practical applications. However， excessive phosphate addition and long-term consumption may be harmful impacts on health and the environment. Therefore， it is vital to develop safe and efficient phosphate-free WRAs for further improving water-holding capacity (WHC) efficacy and edible safety， especially in meat products. In particular， sugar water retention agents (SWRAs) are increasingly popular because of their perfect safety， excellent WHC， and superior biological properties. This review discusses the inducements and mechanisms underlying water loss in meat products. In addition， we focused on the research progresses and related mechanisms of SWRAs in the WHC of meat products and its unique biological functions， as well as the extraction technology. Finally， the future application and development of SWRA were prospected.

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Pure-high-even-order dispersion bound solitons complexes in ultra-fast fiber lasers

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Light(Science & Applications) 2024年第5期13卷 957-972页

作者： Ying Han Bo Gao Honglin Wen Chunyang Ma Jiayu Huo Yingying Li Luyao Zhou Qi Li Ge Wu Lie Liu College of Communication Engineering Jilin UniversityChangchun 130012China. Research center of Circuits and Systems Peng Cheng LaboratoryShenzhen 518055China. International collaborative Laboratory of 2D Materials for Optoelectronics Science and technology of Ministry of Education Institute of Microscale OptoelectronicsShenzhen UniversityShenzhen 518060China. College of Electronic Science and Engineering Jilin UniversityChangchun 130012China

Temporal solitons have been the focus of much research due to their fascinating physical *** solitons can form bound states,which are fundamentally crucial modes in fiber laser and present striking analogies with their matter molecules counterparts,which means they have potential applications in large-capacity transmission and alloptical information *** traditionally,second-order dispersion has been the dominant dispersion for conventional solitons,recent experimental and theoretical research has shown that pure-high-even-order dispersion(PHEOD)solitons with energy-width scaling can arise from the interaction of arbitrary negative-even-order dispersion and Kerr *** these advancements,research on the bound states of PHEOD solitons is currently *** this study,we obtained PHEOD bound solitons in a fiber laser using an intra-cavity spectral pulse shaper for high-order dispersion ***,we experimentally demonstrate the existence of PHEOD solitons and PHEOD bound solitons with pure-quartic,-sextic,-octic,and-decic *** simulations corroborate these experimental ***,vibrating phase PHEOD bound soliton pairs,sliding phase PHEOD bound soliton pairs,and hybrid phase PHEOD bound tri-soliton are discovered and *** results broaden the fundamental understanding of solitons and show the universality of multi-soliton patterns.

关键词： dispersion solitons soliton

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Aggregation-induced T/Tcontrast enhancement for magnetic resonance imaging-guided intraoperative surgery

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Science China Chemistry 2024年

作者： Wenbo Sun Bin Yu Dianshuai Huang Chunhuan Jiang Wei Wang Jianhua Liu Zonghua Wang Lehui Lu College of Chemistry and Chemical Engineering Shandong Sino-Japanese Center for Collaborative Research of Carbon NanomaterialsQingdao Application Technology Innovation Center of Photoelectric Biosensing for Clinical Diagnosis and Treatment Qingdao University Department of Radiology Second Hospital of Jilin University State Key Laboratory of Electroanalytical Chemistry Changchun Institute of Applied Chemistry Chinese Academy of Sciences

Magnetic resonance imaging(MRI) plays an important role in precision medicine that is hampered by the lack of contrast agents with high efficiency and the ability to translate diagnostic accuracy into therapeutic intervention. Herein, we demonstrate a DNA-based MRI probe that overcomes previous single-mode enhancement and provides a mechanism of action for aggregationinduced dual-modal MRI signal enhancement. A facile method is developed to produce aggregated T1/T2dual-modal NaGdF4:Dy@PDA-DNA(PDA = polydopamine) MRI probes. When aggregated, this probe can further amplify MRI signal intensity and exhibit improved geometrical and positional stability in vivo. The performance of the NaGdF4:Dy@PDA-DNA MRI probe toward MRI-guided preoperative planning and visualization-guided surgery is verified using an orthotopic tumor-bearing mouse model. The result shows that the rapid metabolism of the degraded probe leads to the mitigation of long-term toxic ***, the developed high-performance MRI probe is of great significance for enhancing MRI diagnostic accuracy into precision medical therapeutic interventions.

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Lightweight Multi-scale Convolutional Neural Network for Rice Leaf Disease Recognition

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Computers, Materials & Continua 2023年第1期74卷 983-994页

作者： Chang Zhang Ruiwen Ni Ye Mu Yu Sun Thobela Louis Tyasi College of Information technology Jilin Agricultural UniversityChangchun130118China jilin province agricultural internet of things technology collaborative innovation center Changchun130118China jilin province Intelligent Environmental Engineering Research center Changchun130118China jilin province Information technology and Intelligent Agriculture Engineering Research center Changchun130118China Department of agricultural Economics and Animal Production University of LimpopoPrivate Bag X 1106Sovenga0727PolokwaneSouth Africa

In the field of agricultural information,the identification and prediction of rice leaf disease have always been the focus of research,and deep learning(DL)technology is currently a hot research topic in the field of pattern *** research and development of high-efficiency,highquality and low-cost automatic identification methods for rice diseases that can replace humans is an important means of dealing with the current situation from a technical *** paper mainly focuses on the problem of huge parameters of the Convolutional Neural Network(CNN)model and proposes a recognitionmodel that combines amulti-scale convolution module with a neural network model based on Visual Geometry Group(VGG).The accuracy and loss of the training set and the test set are used to evaluate the performance of the *** test accuracy of this model is 97.1%that has increased 5.87%over ***,the memory requirement is 26.1M,only 1.6%of the *** results show that this model performs better in terms of accuracy,recognition speed and memory size.

关键词： Rice leaf diseases deep learning lightweight convolution neural networks VGG

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Sika Deer Behavior Recognition Based on Machine Vision

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Computers, Materials & Continua 2022年第12期73卷 4953-4969页

作者： He Gong Mingwang Deng Shijun Li Tianli Hu Yu Sun Ye Mu Zilian Wang Chang Zhang Thobela Louis Tyasi jilin agricultural University Changchun130118China Wuzhou University Wuzhou543000China jilin province agricultural internet of things technology collaborative innovation center Changchun130118China jilin province Intelligent Environmental Engineering Research center Changchun130118China Department of agricultural Economics and Animal Production University of LimpopoSovenga0727PolokwaneSouth Africa Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou543000China

With the increasing intensive and large-scale development of the sika deer breeding industry,it is crucial to assess the health status of the sika deer by monitoring their behaviours.A machine vision-based method for the behaviour recognition of sika deer is proposed in this *** Inception Net(GoogLeNet)is used to optimise the model in this ***,the number of layers and size of the model were ***,the 5×5 convolution was changed to two 3×3 convolutions,which reduced the parameters and increased the nonlinearity of the model.A 5×5 convolution kernel was used to replace the original convolution for extracting coarse-grained features and improving the model’s extraction ability.A multi-scale module was added to the model to enhance the multi-faceted feature extraction capability of the ***,the Squeeze-and-Excitation Networks(SE-Net)module was included to increase the channel’s attention and improve the model’s *** dataset’s images were rotated to reduce *** image rotation,the angle wasmultiplied by 30°to obtain the dataset enhanced by rotation operations of 30°,60°,90°,120°and 150°.The experimental results showed that the recognition rate of this model in the behaviour of sika deer was 98.92%.Therefore,the model presented in this paper can be applied to the behaviour recognition of sika *** results will play an essential role in promoting animal behaviour recognition technology and animal health monitoring management.

关键词： Behaviour recognition SE-Net module multi-scale module improved Inception module

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Segmentation of Remote Sensing Images Based on U-Net Multi-Task Learning

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Computers, Materials & Continua 2022年第11期73卷 3263-3274页

作者： Ni Ruiwen Mu Ye Li Ji Zhang Tong Luo Tianye Feng Ruilong Gong He Hu Tianli Sun Yu Guo Ying Li Shijun Thobela Louis Tyasi College of Information technology Jilin Agricultural UniversityChangchun130118China jilin province agricultural internet of things technology collaborative innovation center Changchun130118China jilin province Intelligent Environmental Engineering Research center Changchun130118China jilin province Information technology and Intelligent Agriculture Engineering Research center Changchun130118China College of Information technology Wuzhou UniversityWuzhou543003China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou543003China Department of agricultural Economics and Animal Production University of LimpopoSovengaPolokwane0727South Africa

In order to accurately segment architectural features in highresolution remote sensing images,a semantic segmentation method based on U-net network multi-task learning is ***,a boundary distance map was generated based on the remote sensing image of the ground truth map of the *** remote sensing image and its truth map were used as the input in the U-net network,followed by the addition of the building ground prediction layer at the end of the U-net *** on the ResNet network,a multi-task network with the boundary distance prediction layer was *** involving the ISPRS aerial remote sensing image building and feature annotation data set show that compared with the full convolutional network combined with the multi-layer perceptron method,the intersection ratio of VGG16 network,VGG16+boundary prediction,ResNet50 and the method in this paper were increased by 5.15%,6.946%,6.41%and 7.86%.The accuracy of the networks was increased to 94.71%,95.39%,95.30%and 96.10%respectively,which resulted in high-precision extraction of building features.

关键词： Multitasking learning U-net ResNet remote sensing image semantic segmentation

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A Lightweight Model of VGG-U-Net for Remote Sensing Image Classification

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Computers, Materials & Continua 2022年第12期73卷 6195-6205页

作者： Mu Ye Li Ji Luo Tianye Li Sihan Zhang Tong Feng Ruilong Hu Tianli Gong He Guo Ying Sun Yu Thobela Louis Tyasi Li Shijun College of Information technology Jilin Agricultural UniversityChangchun130118China jilin province agricultural internet of things technology collaborative innovation center Changchun130118China jilin province Intelligent Environmental Engineering Research center Changchun130118China jilin province Information technology and Intelligent Agriculture Engineering Research center Changchun130118China College of Engineering and technology Jilin Agricultural UniversityChangchun130118China Department of agricultural Economics and Animal Production University of LimpopoSovenga0727PolokwaneSouth Africa College of Information technology Wuzhou UniversityWuzhou543003China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou543003China

Remote sensing image analysis is a basic and practical research hotspot in remote sensing *** sensing images contain abundant ground object information and it can be used in urban planning,agricultural monitoring,ecological services,geological exploration and other *** this paper,we propose a lightweight model combining vgg-16 and u-net *** combining two convolutional neural networks,we classify scenes of remote sensing *** ensuring the accuracy of the model,try to reduce the memory of *** to the experimental results of this paper,we have improved the accuracy of the model to 98%.The memory size of the model is 3.4 *** the same time,The classification and convergence speed of the model are greatly *** simultaneously take the remote sensing scene image of 64×64 as input into the designed *** the accuracy of the model is 97%,it is proved that the model designed in this paper is also suitable for remote sensing images with few target feature points and low ***,the model has a good application prospect in the classification of remote sensing images with few target feature points and low pixels.

关键词： VGG-16 U-Net fewer feature points nonlinear correction layer zero padding

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Sika Deer Facial Recognition Model Based on SE-ResNet

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Computers, Materials & Continua 2022年第9期72卷 6015-6027页

作者： He Gong Lin Chen Haohong Pan Shijun Li Yin Guo Lili Fu Tianli Hu Ye Mu Thobela Louis Tyasi College of Information technology Jilin Agricultural UniversityChangchun130118China College of Electronic and Information Engineering Wuzhou UniversityWuzhou543003China jilin province agricultural internet of things technology collaborative innovation center Changchun130118China jilin province Intelligent Environmental Engineering Research center Changchun130118China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou543003China Department of agricultural Economics and Animal Production University of Limpopo0727PolokwaneSouth Africa

The scale of deer breeding has gradually increased in recent years and better information management is necessary,which requires the identification of individual *** this paper,a deer face dataset is produced using face images obtained from different angles,and an improved residual neural network(ResNet)-based recognition model is proposed to extract the features of deer faces,which have high *** model is based on ResNet-50,which reduces the depth of the model,and the network depth is only 29 layers;the model connects Squeeze-and-Excitation(SE)modules at each of the four layers where the channel changes to improve the quality of features by compressing the feature information extracted through the entire layer.A maximum pooling layer is used in the ResBlock shortcut connection to reduce the information loss caused by messages passing through the *** Rectified Linear Unit(ReLU)activation function in the network is replaced by the Exponential Linear Unit(ELU)activation function to reduce information loss during forward propagation of the *** preprocessed 6864 sika deer face dataset was used to train the recognition model based on SEResnet,which is demonstrated to identify individuals *** setting up comparative experiments under different structures,the model reduces the amount of parameters,ensures the accuracy of the model,and improves the calculation speed of the *** the improved method in this paper to compare with the classical model and facial recognition models of different animals,the results show that the recognition effect of this research method is the best,with an average recognition accuracy of 97.48%.The sika deer face recognition model proposed in this study is *** results contribute to the practical application of animal facial recognition technology in the breeding of sika deer and other animals with few distinct facial features.

关键词： Sika deer facial recognition model ResNet-50 se module shortcut connection ELU

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