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Strong and tough chitin hydrogel constructed by dehydration and rehydration strategy

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Nano Research 2024年第9期17卷 8192-8199页

作者： Rui-Rui Liu Li-Bo Mao Shu-Hong Yu Division of Nanomaterials and chemistry Hefei National Research Center for Physical Sciences at the MicroscaleDepartment of ChemistryInstitute of Biomimetic Materials and ChemistryAnhui Engineering Laboratory of Biomimetic MaterialsUniversity of Science and Technology of ChinaHefei 230026China institute of Innovative Materials Department of Materials Science and EngineeringDepartment of ChemistrySouthern University of Science and TechnologyShenzhen 518055China

As a renewable,biocompatible,biodegradable soft material,chitin hydrogels have better advantages in stability,antibacterial activity,antifouling,cost,immunogenicity,and so on than most polymer ***,compared with other widely used polymer hydrogels with high strength and toughness,the practical applications of chitin-based hydrogels have been limited by their weak mechanical properties,such as cartilage repair and meniscus ***,we present the design and fabrication of chitin hydrogels with excellent mechanical strength and toughness by a dehydration and rehydration *** sequential dehydration and rehydration processes,the crystalline domains in the chitin hydrogels can be properly *** optimized crystallinity,the elastic modulus of the chitin hydrogels exceeds all previously reported values,and the fracture toughness is even comparable to some synthetic polymer hydrogels,while maintaining a high-water-content of about 80 wt.%.At the same water content,the mechanical properties of the chitin hydrogels are positively correlated with the hydrogel crystallinity,which proves that the change of mechanical properties of hydrogels is not simply dependent on weight *** hydrogels can be further strengthened by incorporating other biopolymers that are intrinsically weak,which makes the hydrogels promising for applications in fields such as cartilage repair and meniscus ***,the hydrogels enable loading and release of water-soluble and poorly water-soluble *** highly extendable strengthening and toughening strategy of chitin and chitin-based biopolymer hydrogels paves the way for their widely applications.

关键词： chitin hydrogel crystallinity rehydration chemical transformation strong and tough

Upper-rim-modified thioether thiacalix[4]arene used for liquid-liquid extraction of Au(Ⅲ)and Pd(Ⅱ)in hydrochloric acid medium

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Chinese Journal of Chemical Engineering 2024年第2期66卷 110-118页

作者： Sheng Wan Rong Xie Jianhong Fan Kewen Tang department of chemistry and Chemical Engineering Hunan Institute of Science and TechnologyYueyang 414006China

Gold(Au)and palladium(Pd)play an increasing role in the production and human life;Therefore,it is of great significance to study their recovery.A 5,11,17,23-tetra-ethylthio-25,26,27,28-tetra-hydroxyl thiacalix[4]arene(TCAET)was synthesized specifically for the capture of Au(Ⅲ)and Pd(Ⅱ)from HCl medium by liquid-liquid *** a 0.1 mol·L^(-1)HCl medium,the transfer of Au(Ⅲ)and Pd(Ⅱ)from the aqueous phase to the organic phase was highly efficient,with a transfer ratio of 100%for Au(Ⅲ)and 98%for Pd(Ⅱ).Furthermore,the extraction equilibrium time for Au(Ⅲ)was just 5 ***'s method data demonstrated that TCAET formed complexes with Au(Ⅲ)and Pd(Ⅱ)in a ratio of 2:3 and 1:1,respectively,during the extraction *** showed high selectivity toward Pd(Ⅱ)and Au(Ⅲ)over other competing metal ***,both Au(Ⅲ)and Pd(Ⅱ)could be successfully stripped from the loaded organic phases with a 1.0 mol·L^(-1)thiourea in 0.5 mol·L^(-1)HCl and 0.5 mol·L^(-1)thiourea in 0.5 mol·L^(-1)HCl,*** obtained from five consecutive extraction-stripping cycles showed good reusability of TCAET toward Au(Ⅲ)and Pd(Ⅱ)*** conclusion can provide a certain reference for thiacalixarene in the recovery of precious metal species.

关键词： Thiacalixarene Upper-rim modification Liquid-liquid extraction Precious metal Thioether

Path signature-based XAI-enabled network time series classification

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Science China(information Sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng XIA department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment technology(CICAEET) Nanjing University of Information Science and Technology School of Computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

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High-responsivity on-chip waveguide coupled germanium photodetector for 2 μm waveband

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Photonics Research 2024年第1期12卷 115-122页

作者： JIANING WANG XI WANG YIHANG LI YANFU YANG QINGHAI SONG KE XU Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of TechnologyShenzhen 518055China department of Electronic&information Engineering Harbin Institute of TechnologyShenzhen 518055China department of Science Harbin Institute of TechnologyShenzhen 518055China

Recently,the emerging 2μm waveband has gained increasing interest due to its great potential for a wide scope of *** with the existing optical communication windows at shorter wavelengths,it also offers distinct advantages of lower nonlinear absorption,better fabrication tolerance,and larger free carrier plasma effects for silicon photonics,which has been a proven device *** much progress has been witnessed for silicon photonics at the 2μm waveband,the primary challenge still exists for on-chip *** the maturity and compatibility of the waveguide coupled photodetectors made of germanium,the 2μm regime is far beyond its cutoff *** this work,we demonstrate an efficient and high-speed on-chip waveguidecoupled germanium photodetector operating at the 2μm *** weak sub-bandgap absorption of epitaxial germanium is greatly enhanced by a lateral separation absorption charge multiplication *** detector is fabricated by the standard process offered by a commercial *** device has a benchmark performance with responsivity of 1.05 A/W and 3 dB bandwidth of 7.12 GHz,which is able to receive high-speed signals with up to 20 Gbit/s data *** availability of such an efficient and fast on-chip detector circumvents the barriers between silicon photonic integrated circuits and the potential applications at the 2μm waveband.

关键词： waveguide responsivity wave

WavEnhancer: Unifying Wavelet and Transformer for Image Enhancement

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Journal of Computer Science & technology 2024年第2期39卷 336-345页

作者：李梓诺陈绪行郭淑娜王书强潘治文 department of Computer and information Science University of MacaoMacao 999078China Research Center for Biomedical information technology Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

Image enhancement is a widely used technique in digital image processing that aims to improve image aesthetics and visual quality. However, traditional methods of enhancement based on pixel-level or global-level modifications have limited effectiveness. Recently, as learning-based techniques gain popularity, various studies are now focusing on utilizing networks for image enhancement. However, these techniques often fail to optimize image frequency domains. This study addresses this gap by introducing a transformer-based model for improving images in the wavelet domain. The proposed model refines various frequency bands of an image and prioritizes local details and high-level features. Consequently, the proposed technique produces superior enhancement results. The proposed model’s performance was assessed through comprehensive benchmark evaluations, and the results suggest it outperforms the state-of-the-art techniques.

关键词： transformer wavelet transform image enhancement

Quantum self-attention neural networks for text classification

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Science China(information Sciences) 2024年第4期67卷 301-313页

作者： Guangxi LI Xuanqiang ZHAO Xin WANG institute for Quantum Computing Baidu Research Centre for Quantum Software and information University of Technology Sydney QICI Quantum information and Computation Initiative Department of Computer ScienceThe University of Hong Kong Thrust of Artificial Intelligence Information HubHong Kong University of Science and Technology(Guangzhou)

An emerging direction of quantum computing is to establish meaningful quantum applications in various fields of artificial intelligence, including natural language processing(NLP). Although some efforts based on syntactic analysis have opened the door to research in quantum NLP(QNLP), limitations such as heavy syntactic preprocessing and syntax-dependent network architecture make them impracticable on larger and real-world data sets. In this paper, we propose a new simple network architecture, called the quantum selfattention neural network(QSANN), which can compensate for these limitations. Specifically, we introduce the self-attention mechanism into quantum neural networks and then utilize a Gaussian projected quantum self-attention serving as a sensible quantum version of self-attention. As a result, QSANN is effective and scalable on larger data sets and has the desirable property of being implementable on near-term quantum devices. In particular, our QSANN outperforms the best existing QNLP model based on syntactic analysis as well as a simple classical self-attention neural network in numerical experiments of text classification tasks on public data sets. We further show that our method exhibits robustness to low-level quantum noises and showcases resilience to quantum neural network architectures.

关键词： quantum neural networks self-attention natural language processing text classification parameterized quantum circuits

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Visible-Light-Promoted Palladium-Catalyzed Cross-Coupling of lodocarboranes with Disulfides and Phenylselenyl Chloride

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Chinese Journal of chemistry 2024年第2期42卷 129-134页

作者： Shimeng Li Yizhen Liu Zuowei Xie Shenzhen Grubbs institute and department of chemistry Southern University of Science and TechnologyShenzhenGuangdong 518055China

This work describes a general method for the synthesis of a series of sulfenylated and selenylated carboranes at room temperature using readily available iodocarboranes as starting materials via boron-centered carboranyl *** hypervalent boron radicals are generated by a visible-light-promoted Pd(O)/Pd(I)*** are useful intermediates and can be trapped by disulfides and phenylselenyl chloride for the convenient construction of B-S/Sebonds.

关键词： Carborane Sulfenylation Selenylation B-I activation Radical Photocatalysis Boron Selectivity

Integral precession calibration method of PIGA on linear vibration table

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Chinese Journal of Aeronautics 2024年第3期37卷 219-236页

作者： Chuang SUN Shun-qing REN Jun-wei CAO Ru HUO department of Automation Tsinghua UniversityBeijing 100084China School of Astronautics Harbin Institute of TechnologyHarbin 150001China Beijing National Research Center for information Science and technology Tsinghua UniversityBeijing 100084China Faculty of information technology Beijing University of TechnologyBeijing 100124China

Linear vibration table can provide harmonic accelerations to excite the nonlinear error terms of Pendulous Integrating Gyro Accelerometer(PIGA).Integral precession calibration method is proposed to calibrate PIGA on a linear vibration table in this *** on the precise expressions of PIGA’s inputs,the error calibration model of PIGA is *** angular velocity errors of PIGA are suppressed by integer periodic precession and the errors caused by non-integer periods vibrating are *** complete calibration process,including planning,preparation,PIGA testing,and coefficient identification,is designed to optimize the test operations and evaluate the calibration *** effect of the main errors on calibration uncertainty is analyzed and the relative sensitivity function is proposed to further optimize the test *** and simulation results verify that the proposed 10-position calibration method can improve calibration uncertainties after compensating for the related *** order of calibration uncertainties of the second-and third-order coefficients are decreased to 10^(-8)(rad.s^(-1))/g^(2)and 10^(-8)(rad.s^(-1))/g3,*** with the other two classical calibration methods,the calibration uncertainties of PIGA’s nonlinear error coefficients can be effectively reduced and the proportional residual errors are decreased less than 3×10-6(rad.s^(-1))/g by using the proposed calibration method.

关键词： PIGA Linear vibration table Vibration measurement Calibration Error analysis Uncertainty analysis

Workout Action Recognition in Video Streams Using an Attention Driven Residual DC-GRU Network

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Computers, Materials & Continua 2024年第5期79卷 3067-3087页

作者： Arnab Dey Samit Biswas Dac-Nhuong Le department of Computer Science and technology Indian Institute of Engineering Science and TechnologyShibpurHowrah711103India Faculty of information technology Haiphong UniversityHaiphong180000Vietnam

Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd datas

关键词： Workout action recognition video stream action recognition residual network GRU attention