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Synthesis of interfacial electric field-enhanced CdS/CdxZn1-xS/ZnO ternary heterojunction by lye dissolution etching mechanism for photocatalytic H2 production and CO2 reduction

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材料科学技术（英文版） 2025年第1期204卷 152-165页

作者： Qi Li Shengchao Yang Yufan Huang Yuwei Liang Chunling Hu Min Wang Zhiyong Liu Yanlong Tai Jichang Liu Yongsheng Li School of Chemistry and Chemical Engineering Shihezi University/Key Laboratory of Green Process for Chemical Engineering/Key Laboratory for Chemical Materials of Xinjiang Uygur Autonomous Region/Engineering Center for Chemical Materials of Xinjiang BingtuanShihezi UniversityShihezi 832003China Shanghai Institute of Ceramics Chinese Academy of SciencesShanghai 200050China School of Chemistry and Chemical Engineering Shihezi University/Key Laboratory of Green Process for Chemical Engineering/Key Laboratory for Chemical Materials of Xinjiang Uygur Autonomous Region/Engineering Center for Chemical Materials of Xinjiang BingtuanShihezi UniversityShihezi 832003China Key Laboratory of Human-Machine Intelligence-Synergy Systems of Chinese Academy of Sciences(CAS) Shenzhen Institutes of Advanced TechnologyShenzhen 518055China School of Chemistry and Chemical Engineering Shihezi University/Key Laboratory of Green Process for Chemical Engineering/Key Laboratory for Chemical Materials of Xinjiang Uygur Autonomous Region/Engineering Center for Chemical Materials of Xinjiang BingtuanShihezi UniversityShihezi 832003China Lab of Low-Dimensional Materials Chemistry Key Laboratory for Ultrafine Materials of Ministry of Education School of Materials Science and Engineering East China University of Science and Technology ShanghaiShanghai 200237China

The difficulty in fabricating a multifaceted composite heterojunction system based on CdxZn1-xS limits the enhancement of photocatalytic *** the present scrutiny,novel ZnO/CdxZn1-xS/CdS com-posite heterojunctions are successfully prepared by the alkaline dissolution etching *** internal electric field at the interface of Ⅰ-type and Z-scheme heterojunction improved the effective charge *** ZC 8 sample exhibits excellent photocatalytic performance and the H2 production efficiency is 15.67 mmol g-1 h-1 with good stability up to 82.9％in 24-hour *** performance of CH4 and CO capacity in the CO2RR process is 3.47 μmol g-1 h-1 and 23.5 μmol g-1 h-1,*** photogener-ated accelerated charge transport is then examined in detail by in situ X-ray photoelectron spectroscopy(ISXPS)and density functional theory(DFT)*** work presents a new idea for the synthe-sis of CdxZni-xS solid-solution-based materials and provides a solid reference for the detailed mechanism regarding the electric field at the heterojunction interface.

关键词： Photocatalysis Interface electric field Composite heterostructure Photocatalytic mechanism CdxZn1-xS solid-solution

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RL-Based USV Path Planning under the Marine Multimodal Features Considerations

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IEEE Internet of Things Journal 2025年

作者： Lin, Quanbao Gou, Huaxing Tian, Peidong Zuo, Tian-Yu Zhang, Hanzhong Wang, Xin Sun, Poly Z. H. Shanghai Jiao Tong University School of Aeronautics and Astronautics Shanghai200240 China Southeast University School of Computer Science and Engineering Nanjing211189 China Shanghai University School of Microelectronics Shanghai200444 China Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Guangdong Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Guangdong Shenzhen518055 China East China Normal University School of Psychology and Cognitive Science Shanghai200062 China Shanghai Jiao Tong University Department of Industrial Engineering Shanghai200240 China

Path planning is an important step in ensuring the safety of Unmanned Surface Vehicle (USV) navigation and executing missions quickly and efficiently. However, current USV path planning methods lack comprehensive consideration of electronic nautical charts and meteorological data, resulting in planned paths being unable to fully utilize marine environmental conditions, which may easily lead to collisions and long navigation times. Based on the above considerations, our study designs a USV path planning system that comprehensively considers the multimodal information from electronic nautical charts and meteorological data. The system consists of three parts: (1) image processing module, (2) meteorological analysis module, and (3) path planning module. In detail, the image processing module obtains the geographical feature information from the electronic chart and constructs a static obstacle environment. The meteorological analysis module obtains the meteorological feature information from meteorological data and constructs a dynamic meteorological vector field environment. The path planning module introduces a designed double deep Q-Network (DQN) structure, a multivariate weighted Dueling network, and a priority sampling mechanism to enhance the DQN algorithm for promising performance in USV path planning. Extensive experiments illustrate the superior performance of the proposed fusion DQN algorithm. Furthermore, the feasibility of the entire path planning system is confirmed. © 2014 IEEE.

关键词： Unmanned surface vehicles

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DCSENets: Interpretable deep learning for patient-independent seizure classification using enhanced EEG-based spectrogram visualization

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Computers in Biology and Medicine 2025年 185卷 109558-109558页

作者： Aboyeji, Sunday Timothy Ahmad, Ijaz Wang, Xin Chen, Yan Yao, Chen Li, Guanglin Tong, Michael Chi Fai Siu, Alice K.Y. Zhao, Guoru Chen, Shixiong CAS Key Laboratory of Human–Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Guangdong-Hong Kong-Macao Joint Laboratory of Human–Machine Intelligence-Synergy Systems Guangdong Shenzhen518055 China Surgery Division Epilepsy Center Shenzhen Children's Hospital Shenzhen518036 China Department of Neurosurgery The National Key Clinic Specialty Shenzhen Key Laboratory of Neurosurgery the First Affiliated Hospital of Shenzhen University Shenzhen Second People's Hospital Shenzhen518035 China Department of Otorhinolaryngology Head and Neck Surgery The Chinese University of Hong Kong Hong Kong School of Medicine The Chinese University of Hong Kong Shenzhen Guangdong518172 China

Neurologists often face challenges in identifying epileptic activities within multichannel EEG recordings, requiring extensive hours of analysis. Computer-aided diagnosis systems have been proposed to reduce manual inspection of EEG signals by neurologists. However, direct analysis of EEG signals is difficult due to their complex and dynamic nature, with variation across multiple patients. Therefore, researchers have proposed the short-time Fourier transform (STFT) to capture dynamic events indicative of seizures through time-varying frequency representation of EEG signals. However, tradeoffs between time and frequency resolution limited the spectrogram's interpretability and affected clinical deployment. Hence, this study proposes extracting high-resolution channels via a novel STFT spectrogram construction algorithm encompassing taper functions for seizure diagnosis. Initially, we extracted seizure and non-seizure segments from each channel of selected patients in the CHB-MIT dataset. Next, we systematically apply taper functions like Hann and Gaussian windows to minimize the edge effect during the construction of spectrogram images. Finally, we employ Dilated Convolutional Squeeze and Excitation Networks (DCSENets) through leave-one-patient-out cross-validation (LOPOCV) to perform patient-independent seizure classification. The proposed DCSENets achieve an average accuracy of 87.20±11.48% and 87.29±10.48% with Hann and Gaussian taper functions, respectively, and 86.85±11.56% without the taper function. Most patients with high performances indicate similarity in train-test sample distribution using the Kolmogorov–Smirnov test at 0.010.05. Furthermore, the Grad CAM deep visual explainer integration enhances the interpretability of the deep learning model's decision-making process. Consequently, neurologists are provided not only with enhanced visualized spectrograms but also a transparent model for improved seizure diagnosis. © 2024 Elsevier Ltd

关键词： Spectrographs

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Automatic Assessment of Chinese Dysarthria Using Audio-visual Vowel Graph Attention Network

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 1454-1466页

作者： Xiaokang Liu Xiaoxia Du Juan Liu Rongfeng Su Manwa Lawrence Ng Yumei Zhang Yudong Yang Shaofeng Zhao Lan Wang Nan Yan ICAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Shenzhen China Department of Neurorehabilitation Beijing Boai Hospital China Rehabilitation Research Center Beijing China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Division of Speech and Hearing Sciences University of Hong Kong Hong Kong China Department of Rehabilitation Medicine Beijing Tiantan Hospital Capital Medical University Beijing China Department of Rehabilitation Medicine The Eighth Affiliated Hospital of Sun Yat-sen University Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

Automatic assessment of dysarthria remains a highly challenging task due to the high heterogeneity in acoustic signals and the limited data. Currently, research on the automatic assessment of dysarthria primarily focuses on two approaches: one that utilizes expert features combined with machine learning, and the other that employs data-driven deep learning methods to extract representations. Studies have shown that expert features can effectively account for the heterogeneity of dysarthria but may lack comprehensiveness. In contrast, deep learning methods excel at uncovering latent features. Therefore, integrating the advantages of expert knowledge and deep learning to construct a neural network architecture based on expert knowledge may be beneficial for interpretability and assessment performance. In this context, the present paper proposes a vowel graph attention network based on audio-visual information, which effectively integrates the strengths of expert knowledge and deep learning. Firstly, the VGAN (Vowel Graph Attention Network) structure based on vowel space theory was designed, which has two branches to mine the information in features and the spatial correlation between vowels respectively. Secondly, a feature set based on expert knowledge and deep representation is designed. Finally, visual information was incorporated into the model to further enhance its robustness and generalizability. Tested on the Mandarin Subacute Stroke Dysarthria Multimodal (MSDM) Database, this method exhibited superior performance in regression experiments targeting Frenchay scores compared to existing approaches.

关键词： Resonant frequency Hidden Markov models Deep learning Visualization Feature extraction Resonance Mel frequency cepstral coefficient Tongue Speech processing Data mining

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Contrast of multi-resolution analysis approach to transhumeral phantom motion decoding

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CAAI Transactions on intelligence Technology 2021年第3期6卷 360-375页

作者： Ejay Nsugbe Oluwarotimi William Samuel Mojisola Grace Asogbon Guanglin Li Independent Scholar Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences(CAS)Shenzhen Institutes of Advanced TechnologyShenzhenChina

In signal processing,multiresolution decomposition techniques allow for the separation of an acquired signal into sub levels,where the optimal level within the signal minimises redundancy,uncertainties,and contains the information required for the characterisation of the sensed *** the area of physiological signal processing for prosthesis control,scenarios where a signal decomposition analysis are required:the wavelet decomposition(WD)has been seen to be the favoured time-frequency approach for the decomposition of non-stationary *** a research perspective,the WD in certain cases has allowed for a more accurate motion intent decoding process following feature extraction and *** this,there is yet to be a widespread adaptation of the WD in a practical setting due to perceived computational ***,for neuro-muscular(electromyography)and brainwave(electroencephalography)signals acquired from a transhumeral amputee,a computationally efficient time domain signal decom-position method based on a series of heuristics was applied to process the acquired signals before feature *** results showed an improvement in motion intent decoding prowess for the proposed time-domain-based signal decomposition across four different classifiers for both the neuromuscular and brain wave signals when compared to the WD and the raw signal.

关键词： motion approach analysis

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Movement Control and Attitude Adjustment of Climbing Robot on Flexible Surfaces

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2018年第3期65卷 2618-2628页

作者： Wu, Xinyu Liu, Jia Zhou, Yimin Lv, Qin Hu, Chaofang CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems and Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Electrical and Information Engineering Tianjin University Tianjin China

In this paper, a series of control algorithms have been designed for the climbing cloth robot, "Clothbot" to climb vertically. The developed algorithm consists of three parts: a sliding mode control with integral action (SMC with integral action), a linear quadratic regulator, and dead reckoning for semi-autonomous navigation. First, the SMC with integral action is developed for high-precision position tracking and speed tracking of the permanent magnet direct current (PMDC) motor installed on the robot. The error between the expected velocity and the actual velocity of the PMDC motor is adopted to design the sliding surface. In order to compensate the fluctuation of the load torque due to the varied friction during climbing, an observer is formulated to estimate the load torque in real-time. Second, the LQR is employed for attitude adjustment by an active torque so as to prevent the robot from falling or being jammed during the movement. Third, due to the onboard-limited energy, the robot is just equippedwith semi-autonomous navigation named dead reckoning carrying on primary localization and primary path planning. Experiments are performed to verify the efficacy of the proposed control algorithms.

关键词： Climbing robot flexible surface linear quadratic regulator load observer sliding mode control with integral action

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Spasticity assessment with muscle coactivation of elbow flexors during passive stretch in Post-stroke Hemiplegia

Spasticity assessment with muscle coactivation of elbow flex...

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45th Annual International Conference of the IEEE Engineering in Medicine and Biology Conference, EMBC 2023

作者： Wang, Hui Geng, Yanjuan Fang, Peng Li, Guanglin Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China

ISBN: (纸本)9798350324471

the assessment of muscle properties is an essential prerequisite in the treatment of post-stroke muscle spasticity. Previous studies have shown that muscle coactivation, which reflects the simultaneous activation of agonist and antagonist muscle groups, is associated with muscle spasticity during voluntary contraction. However, current spasticity assessment approaches do not often consider muscle coactivation for passive contraction measured with surface electromyography (sEMG). The purpose here is to evaluate the validity and reliability of muscle co-activation based on sEMG for assessing spasticity of post-stroke patients. This study was conducted on 39 chronic hemiplegia post-stroke patients with varying degrees of elbow flexor spasticity. The severity of spasticity was assessed with Modified Ashworth Scale (MAS). The patients produced elbow flexion passively on affected arm. Two-channel surface sEMG recordings were acquired simultaneously for the biceps and triceps muscles. The effectiveness and reliability of the EMG-based spasticity assessment method were evaluated using Spearman's correlation analysis and intra class correlation coefficients (ICCs). The results showed that there was a statistically significant positive relationship between the level of activity and the coactivation index (R=0.710, P=0.003), while the ICCs for intra trial measures ranged between 0.928 and 0.976. Muscle coactivation is a promising tool for continuously quantifying muscle spasticity in post-stroke patients, suggesting that the EMG-based muscle coactivation index could be useful for assessing motor function. © 2023 IEEE.

关键词： Muscle

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Exploring the Relationship Between Imitated and Associated Mechanism on Performance of Visual Imagery Brain-Computer Interface 46

Exploring the Relationship Between Imitated and Associated M...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Tai, Pengrui Yang, Jingcheng Qi, Shaowen Li, Guanglin Fu, Yunfa Li, Yongcheng Kunming University of Science and Technology Kunming China Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems SIAT-CAS China Cas Key Laboratory of Human-Machine Intelligence-Systems SIAT-CAS China

ISBN: (纸本)9798350371499

Visual Imagery (VI) can be defined as the manipulation of visual information derived from memory rather than perception. Currently, the brain responses underlying imitation and associative VI are not clear. In this study, we explore the differences from imitation to associative VI on the brain responses based on EEG signals. In this study, eight participants were instructed to observe visual cues from three predefined images or characters (tree, computer, or sphere), and then imagine the same cues. The results indicate that there is a significant difference in power intensity among electrode channels in the occipital lobe, posterior parietal lobe, and temporal lobe during the imagination phase between imitative tasks and associative tasks, as revealed by t-tests (p © 2024 IEEE.

关键词： Long short-term memory

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Characterizing Multiple Patterns of Motor Intent Using Spatial-Temporal Information for Intuitively Active Motor Training in Stroke Survivors 42

Characterizing Multiple Patterns of Motor Intent Using Spati...

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42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020

作者： Samuel, Oluwarotimi Williams Grace Asogbon, Mojisola Geng, Yanjuan Rusydi, Muhammad I. Mzurikwao, Zacharia B. Chen, Shixiong Fang, Peng Li, Guanglin Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Guangdong518055 China

ISBN: (纸本)9781728119908

Upper extremity motor function loss severely affects stroke survivors during daily life activities. Different rehabilitation robotic systems have been developed to allow stroke survivors regain their motor function. Meanwhile, most of the robots only operate in a passive mode and restrict the users to navigate predefined trajectories which may not align with their motion intent, thus limiting motor recovery. One way to resolve this issue would be to utilize a decoded movement intent to trigger intuitively active motor training for patients. In this direction, this study proposed and investigated the use of spatial-temporal neuromuscular descriptor (STD) for optimal decoding of multiple patterns of movement intents in patient to provide inputs for active motor training in the rehabilitation robotic systems. The STD performance was validated using High-Density surface electromyogram recordings from five stroke survivors who performed 21 limb movements. Experimental results show that the STD achieved a significant reduction in limb movement classification error (13.36%) even in the presence of the inevitable White Gaussian Noise compared to other methods (p © 2020 IEEE.

关键词： Decoding

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Single-Wavelength Laminar Optical Tomography for In Vivo Microvascular Three-Dimensional Imaging 46

Single-Wavelength Laminar Optical Tomography for In Vivo Mic...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Cui, Han Han, Dewei Liu, Wenquan Deng, Xinping Xin, Zhixuan Li, Guanglin Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen China

ISBN: (纸本)9798350371499

Laminar Optical Tomography (LOT) is a promising non-invasive technique for three-dimensional imaging of complex biological structures, combining high resolution and deep penetration. In this study, a LOT system was assembled using a 520nm continuous-wave laser, exploiting the contrast mechanism provided by the unique optical absorption coefficient of hemoglobin at this wavelength for microvascular imaging. The system utilizes raster scanning to illuminate the target tissue's surface, capturing backscattered light intensity with a multi-channel Photomultiplier Tubes. The inverse problem of light propagation within the tissue is solved to reconstruct a three-dimensional image of microvasculature. Phantom and in-vivo rat ear results demonstrate the system's ability to image micro vessels with diameters of several hundred micrometers within the tissue. The implemented LOT system, known for its simplicity and cost-effectiveness, showcases its potential for applications in microvascular physiological and pathological research, as well as clinical diagnostics. © 2024 IEEE.

关键词： Clinical research

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