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A kinetic study and factor analysis of solar thermochemical membrane reactors for syngas production

Science China(Technological Sciences) 2025年第1期68卷 203-217页

作者： Jiaxin XING Chao XU Xiangyu SUN Xin XIA Fei JIN Qiongqiong JIANG Jiale GAO Key Laboratory of Power Station Energy Transfer Conversion and System of MOE School of Energy Power and Mechanical EngineeringNorth China Electric Power UniversityBeijing 102206China Department of Chemistry University College LondonLondon WC1H 0AJUK School of Chemistry and Chemical Engineering Ningxia Key Laboratory of Solar Chemical Conversion TechnologyState Ethnic Affairs CommissionNorth Minzu UniversityYinchuan 750021China

Solar thermochemical conversion technologies are promising for effectively utilizing solar energy by capturing the full spectrum of solar *** overcome the challenges of low energy conversion efficiency and intermittency faced by solar thermochemical conversion,these technologies can be effectively integrated with membrane reactor *** the performance of solar thermochemical membrane reactors has been experimentally tested,the chemical reactions and oxygen transport mechanisms during the energy conversion process remain poorly *** study introduces a resistance network model to elucidate the interactions between interfacial reactions and bulk diffusion during simultaneous oxidationreduction reactions on both sides of the *** analyzed the oxygen flux of the membrane reactor under various operating conditions using this model to identify the reaction/transport-limiting side of the overall *** most effective solar membrane reactor configuration utilizes natural gas and CO_(2),facilitating clean conversion of fossil fuels with significant advantages in fuel production and energy *** CH_4 lowers the overall reaction temperature,maintains low oxygen partial pressure on the sweep side,and produces a synthesis gas with a 2:1 H_2/CO molar ***,a sensitivity analysis was used to explore the relationship between overall fuel production performance and operational parameters,highlighting the critical role of this research in enhancing the reaction and transport performance of membrane reactors and advancing the development of solar-driven thermochemical fuel production technologies.

关键词： thermochemistry oxygen-permeable membrane membrane reactor chemical kinetics

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Augmented Reality Based Navigation system for Endoscopic Transnasal Optic Canal Decompression

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 34-42页

作者： FU Hang XU Jiangchang LI Yinwei ZHOU Huifang CHEN Xiaojun Institute of Biomedical Manufacturing and Life Quality Engineering State Key Laboratory System and VibrationSchool of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Ophthalmology Shanghai Ninth People's HospitalShanghai Jiao Tong University School of MedicineShanghai 200011China Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Key Laboratory of Orbital Diseases and Ocular Oncology Shanghai 200011China

Endoscopic transnasal optic nerve decompression surgery plays a crucial role in minimal invasive treatment of complex traumatic optic ***,a major challenge faced during the procedure is the inability to visualize the optic nerve *** address this issue,an endoscopic image-based augmented reality surgical navigation system is developed in this *** system aims to virtually fuse the optic nerve onto the endoscopic images,assisting surgeons in determining the optic nerve’s position and reducing surgical ***,a calibration algorithm based on a checkerboard grid of immobile points is proposed,building upon existing calibration ***,to tackle accuracy issues associated with augmented reality technology,an optical navigation and visual fusion compensation algorithm is proposed to improve the intraoperative tracking *** evaluate the system’s performance,model experiments were meticulously designed and *** results confirm the accuracy and stability of the proposed system,with an average tracking error of(0.99±0.46)*** outcome demonstrates the effectiveness of the proposed algorithm in improving the augmented reality surgical navigation system’s ***,the system successfully displays hidden optic nerves and other deep tissues,thus showcasing the promising potential for future applications in orbital and maxillofacial surgery.

关键词： optic nerve decompression endoscopy augmented reality surgical navigation

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Precise real-time navigation of the LEO satellite enhanced by BDS-3 PPP-B2b service

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Advances in Space Research 2025年第10期75卷 7003-7019页

作者： Gong, Xuewen Zhang, Wanwei Zhao, Aili Gao, Shuaihe Wang, Fuhong Zhang, Jingkui Xie, Song Feng, Guodong Yang, Zaichun National Time Service Center Chinese Academy of Sciences Xi'an710600 China Key Laboratory of Time Reference and Applications Chinese Academy of Sciences Xi'an710600 China School of Geodesy and Geomatics Wuhan University Wuhan430079 China State Key Laboratory of Satellite Navigation System and Equipment Technology Shijiazhuang0500081 China University of Chinese Academy of Sciences Beijing China

For the real-time navigation of LEO satellites based on GNSS, the achievable real-time orbit accuracy is generally limited by the quality of GNSS broadcast ephemeris. In this paper, the correction data released by the BDS-3 PPP-B2b service are introduced to correct the broadcast ephemeris of GPS and BDS-3 satellites, aiming to enhance the real-time orbit accuracy of LEO satellites. Experimental analysis reveals that the errors in the orbits and clock offsets of GPS and BDS-3 satellites are significantly reduced after applying PPP-B2b corrections. Considering that PPP-B2b corrections are only available within the Asia-Pacific region, centered around China, for those epochs where some of the tracked GPS/BDS-3 satellites have access to PPP-B2b corrections while others must rely solely on broadcast ephemerides, an improved measurement update strategy (IMUS) is proposed. This strategy excludes the observations of those GPS/BDS-3 satellites relying on broadcast ephemeris from the measurement update of real-time navigation filtering when the number of satellites available for PPP-B2b reaches a certain threshold. Real-time navigation experiments are conducted on the LT-1A satellite separately using single GPS L1/L2 and single BDS-3 B1C/B2a observations. The results demonstrate that, regardless of whether it is based on GPS or BDS-3, the improvement in real-time orbit accuracy achieved by IMUS after applying PPP-B2b corrections is slightly greater than that achieved by the conventional measure update strategy (CMUS), which treats all tracked satellites equally without differentiation. This indicates that the proposed IMUS could further enlarge the enhancement effect of PPP-B2b corrections on LEO real-time navigation. With the application of PPP-B2b corrections and IMUS, the real-time orbit accuracy of the LT-1A satellite, based on GPS and BDS-3, improves by more than 10% and 8%, respectively, over the entire orbital arc compared to using broadcast ephemeris alone. If only co

关键词： Global positioning system

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Deep Learning and Projection Neural Network With Finite-Time Convergence for Energy Management of Multi-Energy system

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IEEE Transactions on Smart Grid 2025年第3期16卷 2156-2168页

作者： Liu, Xueying He, Xing Li, Chaojie Huang, Tingwen Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China North China Electric Power University State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources Beijing102206 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this paper, an approach based on projection neural network (PNN), sliding mode control technique, and deep learning is proposed to solve the energy management problem of multi-energy systems (MES) containing dynamic parameters. First, the sliding mode technique is introduced in the PNN to design a finite-time PNN (FTPNN). The stability and finite-time convergence of the proposed FTPNN are proved by the Lyapunov method and the setting time bound is given. Then, the deep FTPNN (DFTPNN) is designed by combining deep learning with the proposed FTPNN. The dynamic parameters in the MES that change over time are used as input variables for the DFTPNN, allowing the trained DFTPNN to respond immediately to changes in the dynamic parameters and to predict the solutions of the FTPNN with different parameters directly. Simulation experiments show that FTPNN has faster convergence compared to PNN. DFTPNN significantly reduces the computation time compared to FTPNN. DFTPNN provides predicted solutions to FTPNN. Since DFTPNN can respond immediately to changes in dynamic parameters and directly provide energy management strategies under different parameters, it can adapt to changing environments and promote the economic and stable operation of MES. © 2010-2012 IEEE.

关键词： Cogeneration Heuristic algorithms Convergence Deep learning Prediction algorithms Optimization Heating systems Energy management Approximation algorithms Power system stability

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Disparities in carbon emissions across households: insights from daily diet

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Frontiers of Environmental Science and Engineering 2025年第7期19卷 87-87页

作者： Yue, Jia Weng, Zhixiong Chen, Siyao Tong, Dan Xie, Yang Xu, Meng Ma, Hao School of Business Xiangtan Institute of Technology Xiangtan411100 China Graduate School University of Perpetual Help System DALTA Las Piñas1740 Philippines Institute of Circular Economy Beijing University of Technology Beijing100124 China State Key Laboratory of Materials Low-Carbon Recycling Beijing University of Technology Beijing100124 China Department of Earth System Science Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies Tsinghua University Beijing100084 China School of Economics and Management Beihang University Beijing100191 China School of Environmental Sciences and Engineering Peking University Beijing100871 China BGRIMM Technology Group Beijing100160 China

This study examines household food carbon emissions in rural China, focusing on the inequality of these emissions and the influence of household characteristics on their variation. Our findings indicate that the average food consumption per rural household is 1031.66 kg. Among all food types, pork contributes the highest share of carbon emissions at 39.75%, followed by beef and mutton at 15.14%, while milk accounts for the lowest share at just 1.38%. Additionally, as household income increases, both food consumption and associated carbon emissions rise accordingly. The food-related carbon emissions tend to be higher in households that are more educated, younger, and larger in size. There are notable regional and income disparities in rural food-related carbon emissions. The regional inequalities appear primarily driven by interactions between different regions, while income inequality is influenced by both intra-group disparities and overlaps among income groups. The results from our threshold regression suggest that carbon emissions are particularly elevated in households where the head has a college-level education or higher, is aged between 32.80 and 33.25 years, and has a household size of three to five members. It is essential to develop and implement flexible policies aimed at reducing the consumption of high-carbon foods. By taking these steps, we can work toward a more sustainable future and promote greater equity in food-related carbon emissions. © Higher Education Press 2025.

关键词： Beef

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Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3235-3248页

作者： Liang, Weisheng Amer, Abdelhakim Mehndiratta, Mohit Chen, Zheng Yao, Bin Kayacan, Erdal Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China Aarhus University Artificial Intelligence in Robotics Laboratory Department of Electrical and Computer Engineering Aarhus8000 Denmark GIM Robotics Espoo02650 Finland Zhejiang University Ocean College Ocean Research Center of Zhoushan Zhoushan316021 China Purdue University School of Mechanical Engineering West Lafayette47907 United States Department of Electrical Engineering and Information Technology Paderborn33098 Germany

With increasingly challenging applications for quadrotors, higher requirements are emerging for tracking accuracy and safety. While high accuracy is a prerequisite for complex tasks, safety is ensured through tolerance to actuator faults and resistance to external disturbances. In this article, adaptive robust control (ARC) integrated with Gaussian processes (GPs), i.e., ARC-GP, is proposed to achieve enhanced accuracy, fault tolerance, and anti-disturbance. These three requirements are interrelated and affected by uncertainties. The primary idea of this article is to categorize uncertainties into parametric and nonparametric types, which are then addressed through parameter adaptation and GP, respectively. First, a detailed dynamic model is established, including actuator models that reflect different types of faults corresponding to changes in different physical parameters. Then, parameter adaptation is designed, with direct and indirect methods adopted for different parameters. In particular, the actuator parameters are effectively estimated to achieve targeted fault compensation. Regarding GP for nonparametric uncertainties, its model parameters are also updated via parameter adaptation. The GP thereby also learns parameter estimation errors along with external disturbances. Accordingly, ARC controllers are designed, for which robust feedback terms are constructed to further mitigate uncertainties on the basis of the covariances predicted by GP. The experiments demonstrate that the proposed ARC-GP can actively tolerate various types of actuator faults and better resist wind disturbances. © 2013 IEEE.

关键词： Robust control

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Design,synthesis and biological evaluation of Leu_(10)-teixobactin analogues

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Chinese Chemical Letters 2025年第4期36卷 157-161页

作者： Yanye Fan Jingjing Chen Bichun Chen Jinyu Bai Bowen Yang Feng Liang Lijing Fang The State Key Laboratory of Refractories and Metallurgy School of Chemistry and Chemical EngineeringWuhan University of Science and TechnologyWuhan 430081China Guangdong Key Laboratory of Nanomedicine CAS-HK Joint Lab of BiomaterialsACS Key Laboratory of Biomedical Imaging Science and SystemInstitute of Biomedicine and BiotechnologyShenzhen Institute of Advanced Technology(SIAT)Chinese Academy of SciencesShenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China Sino-Euro Center of Biomedicine and Health Shenzhen 518024China School of Pharmacy Lanzhou UniversityLanzhou 730000China

Two thioamino acids and four fiuorinated amino acids were employed to substitute either partially or entirely the Ile_(2),Ser_(3),Ile_(6),and Ser_(7) residues of Leu_(10)-teixobactin to prepare ten analogues and the bioactivity of them was *** SAR studies revealed that Ile_(6) was tolerable for both thioamidation and fiuoridation,while Ser_(7) was identified as the most tolerable site for *** 1a demonstrated comparable or slightly improved antibacterial activity,superior protease stability compared to Leu_(10)-teixobactin,while not exhibiting obvious cytotoxicity against mammalian cells.

关键词： Leu_(10)-teixobactin Thioamidation Fluorination Antibacterial activity Protease stability

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A deep learning-based model for automated STN localization using local field potentials in Parkinson’s disease

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Soft Computing 2025年第4期29卷 2343-2362页

作者： Hosny, Mohamed Naeem, Mohamed A. Zhu, Minwei Gao, Wenpeng Elshenhab, Ahmed M. Fu, Yili Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China Department of Mechatronics and Robotics Engineering Faculty of Engineering South Valley University Qena Egypt First Affiliated Hospital Harbin Medical University Harbin150001 China School of Life Science and Technology Harbin Institute of Technology Harbin150080 China Department of Mathematics Faculty of Science Mansoura University Mansoura35516 Egypt

Accurate identification of the subthalamic nucleus (STN) borders is time-consuming, relying heavily on the neurosurgeon expertise in manually interpreting the electrophysiological signals. Local field potentials (LFPs) have garnered imperative attention due to their strong correlation with the STN. However, existing detection models often face challenges with high computational complexity, hyperparameter optimization and lack of explainability, making them unreliable for clinicians. Therefore, this study introduces an explanatory framework using convolutional neural networks (CNN) for detecting the STN region from LFPs. Continuous wavelet transform is employed to convert LFPs signals into scalogram images, which are then processed by sixteen CNN models. We evaluated our framework by examining the impact of various limiting factors on the classification performance, including model size, learning rate (LR), optimizers and data scaling. Deep features are extracted from the top-performing CNN architectures to capture rich representations of the scalograms. These features are then fused and classified using k-nearest neighbour algorithm. Gradient-weighted class activation mapping is used to explain the decisions made by the proposed model. Our approach achieved an accuracy of 99.61%, outperforming individual CNN models for STN localization. The experimental results revealed that CNN models, embedded with additional hyperparameters and layers, generally outperformed smaller models. Besides, low LR significantly enhanced the performance compared to high LR. Moreover, features extracted from untuned networks produced lower performance than tuned networks. The proposed system could revolutionize deep brain stimulation surgery by increasing efficiency and reducing reliance on clinician expertise for STN detection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Wavelet transforms

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Photonics-assisted intensity-modulation and direct-detection MIMO millimeter-wave system in the D-band

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Chinese Optics Letters 2025年第1期23卷 7-12页

作者： Jingwen Tan Peng Tian Jianjun Yu Xianming Zhao Xinglin Dou Long Zhang Xiongwei Yang YangHan Yi Wei Bing Zhang Qinyi Zhang Luhan Jiang Weiping Li Rahim Uddin Kaihui Wang Wen Zhou State Key Laboratory of ASIC and System Key Laboratory for Information Science of Electromagnetic Waves(MoE)School of Information Science and TechnologyFudan UniversityShanghai 200433China Beijing Hongshan Information Technology Research Institute Co. Ltd.Beijing 100176China

We experimentally demonstrate the transmission of discrete multi-tone(DMT)millimeter-wave(mm-wave)signals over a 1.2-km distance at the D-band(110–170 GHz)in a cost-effective intensity-modulation and direct-detection(IM/DD)communication *** the experiment,we successfully achieve the transmission of DMT-QPSK and DMT-16QAM mm-wave signals over multiple-input multiple-output(MIMO)*** the 1.2-km free-space transmission,the bit error rate(BER)of the DMT-16QAM is below the 25%soft decision forward error correction(25%SD-FEC)threshold of 4×10-2,with a maximum net bit rate of 24.62 Gbit/s achieved in this system.

关键词： D-band discrete multi-tone intensity modulation and direct detection long-distance wireless transmission photonics-assisted technique

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A review of solar concentration technology applications in deep space exploration: Environmental adaptability and performance comparison

Space Solar Power and Wireless Transmission

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Space Solar Power and Wireless Transmission 2025年第1期2卷 43-53页

作者： Yanlong Zhang Pengzhen Guo Mengfan Tian Huazhi Chen Rongqiang Liu Zongquan Deng Lifang Li National Key Laboratory of Aerospace Mechanism Harbin Institute of Technology Harbin 150001 PR China National Key Laboratory of Laser Spatial Information Harbin Institute of Technology Harbin 150001 PR China National Key Laboratory of Space Environment and Matter Behaviors Harbin Institute of Technology Harbin 150001 PR China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 PR China

Deep space exploration missions and the construction of planetary research stations impose strict demands on energy self-sufficiency systems. Solar energy, due to its abundant availability and sustainability, has become the preferred solution. However, extreme environmental conditions in space – including drastic temperature fluctuations, vacuum environments, high-energy particles, and intense radiation – pose significant challenges to the performance and lifespan of solar energy systems. Concentration technology, which enhances photoelectric and photothermal conversion efficiency by focusing sunlight, is crucial for space missions. This review examines the primary environmental factors affecting the performance of solar concentrators, including solar irradiance, thermal cycling, vacuum-induced outgassing, radiation effects, and impacts from micrometeoroids and orbital debris. The analysis focuses on three types of high-temperature concentrators: Fresnel lenses, Scheffler concentrators, and parabolic dish concentrators. Fresnel lenses are characterized by low cost and simple structure but are susceptible to optical degradation at high temperatures. Scheffler concentrators utilize geometric optimization to improve uniformity of light distribution, while parabolic dish concentrators achieve high optical efficiency, making them suitable for high-energy applications though requiring precise solar tracking. Performance comparisons in the thermal power range of 0 to 25 kW reveal that parabolic dish concentrators excel in high-power scenarios with greater efficiency and smaller aperture sizes. Conversely, Fresnel lenses and Scheffler concentrators are more effective in medium to low-temperature applications. Based on these findings, this review emphasizes the need to select concentrators according to mission requirements and outlines future research directions. These include the development of advanced materials, optimized optical designs, and improvements in system integr

关键词： Deep space exploration Solar concentrators Extreme environmental conditions

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