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Structural energy storage composites based on modified carbon fiber electrode with metal-organic frame enhancing layered double hydroxide

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Nano Research 2024年第3期17卷 1552-1563页

作者： Jinrui Ye Zhongbao Wang Qin lei lei sun Jinfeng Gu School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Tangshan Research Institute Beijing Institute of TechnologyTangshan 063000China School of Materials Science and Engineering Shenyang Jianzhu UniversityShenyang 110168China Department of Stomatology PLA Strategic Support Force Characteristic Medical CenterBeijing 100101China Beijing Electromechanical Engineering Research Institute Beijing 100074China

Structural energy storage composites present advantages in simultaneously achieving structural strength and electrochemical properties.Adoption of carbon fiber electrodes and resin structural electrolytes in energy storage composite poses challenges in maintaining good mechanical and electrochemical properties at reasonable cost and effort.Here,we report a simple method to fabricate structural supercapacitor using carbon fiber electrodes(modified by Ni-layered double hydroxide(Ni-LDH)and in-situ growth of Co-metal-organic framework(Co-MOF)in a two-step process denoted as Co-MOF/Ni-LDH@CF)and bicontinuous-phase epoxy resin-based structural electrolyte.Co-MOF/Ni-LDH@CF as electrode material exhibits improved specific capacity(42.45 F·g^(-1))and cycle performance(93.3%capacity retention after 1000 cycles)in a three-electrode system.The bicontinuous-phase epoxy resin-based structural electrolyte exhibits an ionic conductivity of 3.27×10^(-4) S·cm^(-1).The fabricated Co-MOF/Ni-LDH@CF/SPE-50 structural supercapacitor has an energy density of 3.21 Wh·kg^(-1) at a power density of 42.25 W·kg^(-1),whilst maintaining tensile strength and modulus of 334.6 MPa and 25.2 GPa.These results show practical potential of employing modified commercial carbon fiber electrodes and epoxy resin-based structural electrolytes in structural energy storage applications.

关键词： carbon fiber electrode structural electrolyte structural energy storage composites supercapacitor

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Cubic S/N co-doped TiO_(2) with rich oxygen vacancies from Ti-MOFs for efficient elimination of formaldehyde

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Chinese Chemical Letters 2024年第2期35卷 512-515页

作者： Qing Gao lei sun Zhihua Wang Jiguang Deng State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical TechnologyBeijing 100029China Beijing Key Laboratory for Green Catalysis and Separation Key Laboratory of Beijing on Regional Air Pollution ControlKey Laboratory of Advanced Functional MaterialsEducation Ministry of ChinaDepartment of Chemical EngineeringBeijing University of TechnologyBeijing 100124China

The cubic S/N co-doped TiO_(2)(TNSx,x is the calcination temperature)photocatalysts with rich oxygen vacancies were obtained by high temperature calcination of sulfur powder and titanium-based MOFs NH_(2)-MIL-125 for the photocatalytic removal of gaseous formaldehyde(a volatile organic compound).Among the obtained catalysts,the presence of oxygen vacancies restricted photogenerated electron and holes recombination.98.00%removal of gaseous formaldehyde in 150 min could be achieved over TNS600 by xenon lamp.The removal efficiency for formaldehyde was well retained for five cycle experiment.The results from PL,TRPL and EIS revealed that TNS600 had the best separation efficiency of photogenerated electrons and holes,and the enhanced charge separation led to a significant increase in photocatalytic activity.The photocatalytic oxidation mechanism indicated that the ^(•)OH and ^(•)O_(2)−radicals were mainly involved in the efficient elimination of gaseous formaldehyde and were able to mineralize formaldehyde to H_(2)O and CO_(2).

关键词： Metal-organic frameworks Photocatalysis Formaldehyde removal S/N co-doped TiO_(2) Oxygen vacancies

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Strengthening Network Security: Deep Learning Models for Intrusion Detectionwith Optimized Feature Subset and Effective Imbalance Handling

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Computers, Materials & Continua 2024年第2期78卷 1995-2022页

作者： Bayi Xu lei sun Xiuqing Mao Chengwei Liu Zhiyi Ding School of Cyber Science and Engineering Zhengzhou UniversityZhengzhou450000China Three Academy Information Engineering UniversityZhengzhou450001China The 3rd Research Department Nanjing Research Institute of Electronic EngineeringNanjing210007China

In recent years,frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security.This paper presents a novel intrusion detection system consisting of a data prepro-cessing stage and a deep learning model for accurately identifying network attacks.We have proposed four deep neural network models,which are constructed using architectures such as Convolutional Neural Networks(CNN),Bi-directional Long Short-Term Memory(BiLSTM),Bidirectional Gate Recurrent Unit(BiGRU),and Attention mechanism.These models have been evaluated for their detection performance on the NSL-KDD dataset.To enhance the compatibility between the data and the models,we apply various preprocessing techniques and employ the particle swarm optimization algorithm to perform feature selection on the NSL-KDD dataset,resulting in an optimized feature subset.Moreover,we address class imbalance in the dataset using focal loss.Finally,we employ the BO-TPE algorithm to optimize the hyperparameters of the four models,maximizing their detection performance.The test results demonstrate that the proposed model is capable of extracting the spatiotemporal features of network traffic data effectively.In binary and multiclass experiments,it achieved accuracy rates of 0.999158 and 0.999091,respectively,surpassing other state-of-the-art methods.

关键词： Intrusion detection CNN BiLSTM BiGRU attention

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Heteroatom doping regulates the catalytic performance of singleatom catalyst supported on graphene for ORR

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Nano Research 2024年第3期17卷 1086-1093页

作者： Ji-Kai sun Yu-Wei Pan Meng-Qian Xu lei sun Shaolong Zhang Wei-Qiao Deng Dong Zhai Institute of Molecular Sciences and Engineering Institute of Frontier and Interdisciplinary ScienceShandong UniversityQingdao 266237China College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China

Replacing fossil fuels with fuel cells is a feasible way to reduce global energy shortages and environmental pollution.However,the oxygen reduction reaction(ORR)at the cathode has sluggish kinetics,which limits the development of fuel cells.It is significant to develop catalysts with high catalytic activity of ORR.The single-atom catalysts(SACs)of Pt supported on heteroatom-doped graphene are potential candidates for ORR.Here we studied the SACs of Pt with different heteroatoms doping and screened out Pt-C_(4) and Pt-C_(3)O_(1) structures with only 0.13 V overpotential for ORR.Meanwhile,it is found that B atoms doping could weaken the adsorption capacity of Pt,while N or O atoms doping could enhance it.This regularity was verified on Fe SACs.Through the electronic interaction analysis between Pt and adsorbate,we explained the mechanism of this regularity and further proposed a new descriptor named corrected d-band center(ε_(d-corr))to describe it.This descriptor is an appropriate reflection of the number of free electrons of the SACs,which could evaluate its adsorption capacity.Our work provides a purposeful regulatory strategy for the design of ORR catalysts.

关键词： single-atom catalyst(SAC) oxygen reduction reaction(ORR) heteroatom doping corrected d-band center descriptor

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Equitable Cluster Partition of Planar Graphs with Girth at Least 12

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Journal of Mathematical Research with Applications 2024年第2期44卷 152-160页

作者： Xiaoling LIU lei sun Wei ZHENG Shandong Normal University Department of Mathematics and Statistics

An equitable(Ok1, Ok2,..., Okm)-partition of a graph G, which is also called a k cluster m-partition, is the partition of V(G) into m non-empty subsets V1, V2,..., Vm such that for every integer i in {1, 2,..., m}, G[Vi] is a graph with components of order at most k, and for each distinct pair i, j in {1,..., m}, there is-1 ≤ |Vi|-|Vj| ≤ 1. In this paper, we proved that every planar graph G with minimum degree δ(G) ≥ 2 and girth g(G) ≥ 12 admits an equitable(O71, O72,..., O7m)-partition, for any integer m ≥ 2.

关键词： equitable cluster partition planar graph girth discharging

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Status and developmental trends in recombinant collagen preparation technology

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Regenerative Biomaterials 2024年第2期3卷 17-36页

作者： Xiaolei Guo Yuan Ma Hang Wang Hongping Yin Xinli Shi Yiqin Chen Guobiao Gao lei sun Jiadao Wang Yunbing Wang Daidi Fan Center for Medical Device Evaluation National Medical Products AdministrationBeijing 100081China State Key Laboratory of Tribology Tsinghua UniversityBeijing 100084China school of Life Science and Technology China Pharmaceutical UniversityNanjing 210009China National Engineering Research Center for Biomaterials&College of Biomedical Engineering Sichuan UniversityChengdu 610064China Biotech.&Biomed.Research Institute Northwest UniversityXi'an 710127China

Recombinant collagen is a pivotal topic in foundational biological research and epitomizes the application of critical bioengineer-ing technologies.These technological advancements have pro-found implications across diverse areas such as regenerative medicine,organ replacement,tissue engineering,cosmetics and more.Thus,recombinant collagen and its preparation methodologies rooted in genetically engineered celis mark pivotal milestones in medical product research.This article pro-vides a comprehensive overview of the current genetic engi-neering technologies and methods used in the production of recombinant collagen,as well as the conventional production process and gquality control detection methods for this material.Furthermore,the discussion extends to foresee the strides in physical transfection and magnetic control sorting studies,envisioning an enhanced preparation of recombinant collagen-seeded cells to further fuel recombinant collagen production.

关键词： recombinant collagen preparation genetic engineering collagen characterization physical transfection seed cell sorting

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Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

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Defence Technology（防务技术） 2024年第3期33卷 573-587页

作者： Qu Wang Meixia Fu Jianquan Wang lei sun Rong Huang Xianda Li Zhuqing Jiang Yan Huang Changhui Jiang School of Automation Science and Electrical Engineering University of Science and Technology BeijingBeijing100083China Shunde Innovation School University of Science and Technology BeijingFo Shan528399China Research Institute of China Unicom Beijing100190China School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing100876China Department of Automation Tsinghua University Beijing100084China GEOLOC Laboratory Universite Gustave EiffelParis77454France

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

关键词： Indoor positioning Inertial navigation system(INS) Zero-velocity update(ZUPT) Internet of things(IoTs) Location-based service(LBS)

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Straw mulching alters the composition and loss of dissolved organic matter in farmland surface runoff by inhibiting the fragmentation of soil small macroaggregates

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Journal of Integrative Agriculture 2024年第5期23卷 1703-1717页

作者： Shanshan Cai lei sun Wei Wang Yan Li Jianli Ding Liang Jin Yumei Li Jiuming Zhang Jingkuan Wang Dan Wei College of Land and Environment Shenyang Agricultural UniversityShenyang 110866China Heilongjiang Academy of Black Soil Conservation and Utilization Harbin 150086China Institute of Plant Nutrition Resources and EnvironmentBeijing Academy of Agricultural and Forestry SciencesBeijing 100097China

Straw mulching is a widespread practice for reducing the soil carbon loss caused by erosion.However,the effects of straw mulching on dissolved organic matter(DOM)runoff loss from black soil are not well studied.How straw mulching affects the composition and loss of runoff DOM by changing soil aggregates remains largely unclear.Here,a straw mulching treatment was compared to a no mulching treatment(as a control)on sloping farmland with black soil erosion in Northeast China.We divided the soil into large macroaggregates(>2 mm),small macroaggregates(0.25-2 mm),and microaggregates(<0.25 mm).After five rain events,the effects of straw mulching on the concentration(characterized by dissolved organic carbon(DoC)and composition(analyzed by fluorescence spectroscopy)of runoff and soil aggregate DOM were studied.The results showed that straw mulching reduced the runoff amount by 54.7%.Therefore,although straw mulching increased the average DOc concentration in runoff,it reduced the total runoff DOM loss by 48.3%.The composition of runoff DOM is similar to that of soil,as both contain humic-like acid and protein-like components.With straw mulching treatment,the protein-like components in small macroaggregates accumulated and the protein-like components in runoff declined with rain events.Fluorescence spectroscopy technology may help in understanding the hydrological paths of rain events by capturing the dynamic changes of runoff and soil DOM characteristics.A variation partitioning analysis(VPA)indicated that the DOM concentration and composition of microaggregates explained 68.2%of the change in runoff DOM from no mulching plots,while the change in runoff DOM from straw mulching plots was dominated by small macroaggregates at a rate of 55.1%.Taken together,our results demonstrated that straw mulching reduces the fragmentation of small macroaggregates and the loss of microaggregates,thus effecting DOM compositions in soil and reducing the DOM loss in runoff.These results provide a theoretical basis for reducing carbon loss

关键词： dissolved organic matter black soil surface runoff aggregates fluorescence spectrum

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A multidimensional platform of patient-derived tumors identifies drug susceptibilities for clinical lenvatinib resistance

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Acta Pharmaceutica Sinica B 2024年第1期14卷 223-240页

作者： lei sun Arabella H.Wan Shijia Yan Ruonian Liu Jiarui Li Zhuolong Zhou Ruirui Wu Dongshi Chen Xianzhang Bu Jingxing Ou Kai Li Xiongbin Lu Guohui Wan Zunfu Ke Department of Pathology the First Affiliated HospitalSun Yat-sen UniversityGuangzhou 510080China National-Local Joint Engineering Laboratory of Druggability and New Drug Evaluation National Engineering Research Center for New Drug and Druggability(Cultivation)Guangdong Province Key Laboratory of New Drug Design and EvaluationSchool of Pharmaceutical SciencesSun Yat-sen UniversityGuangzhou 510006China Department of Medical and Molecular Genetics Indiana University School of MedicineIndianapolisIN 46202USA Department of Medicine Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCA 90033USA Department of Hepatic Surgery and Liver Transplantation Center Third Affiliated HospitalOrgan Transplantation InstituteSun Yat-sen UniversityOrgan Transplantation Research Center of Guangdong ProvinceGuangdong Province Engineering Laboratory for Transplantation MedicineGuangzhou 510630China Guangdong Provincial Key Laboratory of Liver Disease Research Guangzhou 510630China Department of Ultrasound Third Affiliated HospitalSun Yat-sen UniversityGuangzhou 510630China Melvin and Bren Simon Comprehensive Cancer Center Indiana UniversityIndianapolisIN 46202USA

Lenvatinib,a second-generation multi-receptor tyrosine kinase inhibitor approved by the FDA for first-line treatment of advanced liver cancer,facing limitations due to drug resistance.Here,we applied a multidimensional,high-throughput screening platform comprising patient-derived resistant liver tumor cells(PDCs),organoids(PDOs),and xenografts(PDXs)to identify drug susceptibilities for conquering lenvatinib resistance in clinically relevant settings.Expansion and passaging of PDCs and PDOs from resistant patient liver tumors retained functional fidelity to lenvatinib treatment,expediting drug repurposing screens.Pharmacological screening identified romidepsin,YM155,apitolisib,NVP-TAE684 and dasatinib as potential antitumor agents in lenvatinib-resistant PDC and PDO models.Notably,romidepsin treatment enhanced antitumor response in syngeneic mouse models by triggering immunogenic tumor cell death and blocking the EGFR signaling pathway.A combination of romidepsin and immunotherapy achieved robust and synergistic antitumor effects against lenvatinib resistance in humanized immunocompetent PDX models.Collectively,our findings suggest that patient-derived liver cancer models effectively recapitulate lenvatinib resistance observed in clinical settings and expedite drug discovery for advanced liver cancer,providing a feasible multidimensional platform for personalized medicine.

关键词： Lenvatinib Drug resistance High-throughput screening Drug discovery Patient-derived model Romidepsin EGFR Liver cancer

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Towards the universal defense for query-based audio adversarial attacks on speech recognition system

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Cybersecurity 2024年第1期7卷 53-70页

作者： Feng Guo Zheng sun Yuxuan Chen lei Ju School of Cyber Science and Technology Shandong UniversityQingdaoChina Quancheng Laboratory QCLJinanChina

Recently,studies show that deep learning-based automatic speech recognition(ASR)systems are vulnerable to adversarial examples(AEs),which add a small amount of noise to the original audio examples.These AE attacks pose new challenges to deep learning security and have raised significant concerns about deploying ASR systems and devices.The existing defense methods are either limited in application or only defend on results,but not on process.In this work,we propose a novel method to infer the adversary intent and discover audio adversarial examples based on the AEs generation process.The insight of this method is based on the observation:many existing audio AE attacks utilize query-based methods,which means the adversary must send continuous and similar queries to target ASR models during the audio AE generation process.Inspired by this observation,We propose a memory mechanism by adopting audio fingerprint technology to analyze the similarity of the current query with a certain length of memory query.Thus,we can identify when a sequence of queries appears to be suspectable to generate audio AEs.Through extensive evaluation on four state-of-the-art audio AE attacks,we demonstrate that on average our defense identify the adversary’s intent with over 90%accuracy.With careful regard for robustness evaluations,we also analyze our proposed defense and its strength to withstand two adaptive attacks.Finally,our scheme is available out-of-the-box and directly compatible with any ensemble of ASR defense models to uncover audio AE attacks effectively without model retraining.

关键词： Adversarial attacks Defense Memory mechanism Query-based

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