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Two-dimensional transition metal chalcogenide nanomaterials for cancer diagnosis and treatment

Chinese Chemical Letters 2022年第10期33卷 4437-4448页

作者： Jingjing Wu Tingting Hu Guoping Zhao Anran Li Ruizheng Liang State Key Laboratory of Chemical Resource Engineering Beijing Advanced Innovation Center for Soft Matter Science and EngineeringBeijing University of Chemical TechnologyBeijing 100029China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Engineering MedicineBeihang UniversityBeijing 100191China Department of Orthopedics Guilin People's HospitalGuilin 541002China

For more than a decade,the exfoliation of graphene and other layered materials has led to a tremendous amount of research in two-dimensional(2D)materials,among which 2D transition metal chalcogenides(TMCs)nanomaterials have attracted much attention in a wide range of applications including photoelectric devices,lithium-ion batteries,catalysis,and energy conversion and storage owing to their unique photoelectric physical *** such large specific surface area,strong near-infrared(NIR)absorption and abundant chemical element composition,2D TMCs nanomaterials have become good candidates in biomedical imaging and cancer *** review systematically summarizes recent progress on 2D TMCs nanomaterials,which includes their synthesis methods and applications in cancer *** the end of this review,we also highlight the future prospects and challenges of 2D TMCs *** is expected that this work can provide the readers with a detailed overview of the synthesis of 2D TMCs and inspire more novel functional biomaterials based on 2D TMCs for cancer treatment in the future.

关键词： Two-dimensional(2D)nanomaterials Transition metal chalcogenides(TMCs) Synthesis method Biomedical imaging Cancer treatment

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Flexible Selection for Efficient Latin Hypercube Design Optimization Method in Uncertainty Quantification 9

Flexible Selection for Efficient Latin Hypercube Design Opti...

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9th International Symposium on System Security, Safety, and Reliability, ISSSR 2023

作者： Liu, Dong Shi, Jian Zhang, Chao Liu, Di Beihang University School of Automation Science and Electrical Engineering Beijing China Beihang University Beijing Advanced Innovation Center for Big-Data Based Precision Medicine Beijing China

ISBN: (纸本)9798350302479

Design of Experient is an integral part of uncertainty quantification. Latin hypercube designs, including methods such as maximizing distance LHDs and maximizing projection LHDs, are widely used for quantifying and computing engineering uncertainties. In particular, it is challenging to construct efficient designs for large designs with high parameter dimensionality and large data volume. In the current literature, various optimization tools exist to select the optimal LHDs, and each method has its advantages and disadvantages. In this paper, we combine commonly used optimization methods with different space-filling criteria to analyze the effects of parameter dimensionality, data volume, and algorithm hyperparameters for solving the problem of flexibility selection of optimization algorithms. The results of this paper can be used as a guide for the selection of optimization algorithms for experimental design aspects of practical engineering applications. © 2023 IEEE.

关键词： Genetic algorithms

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DDASR: Domain-Distance Adapted Super-Resolution Reconstruction of MR Brain Images

DDASR: Domain-Distance Adapted Super-Resolution Reconstructi...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Cong, Shan Cui, Kailong Yang, Yuzun Zhou, Yang Wang, Xinxin Luo, Haoran Zhang, Yichi Yao, Xiaohui College of Intelligent Systems Science and Engineering Harbin Engineering University Heilongjiang Harbin150001 China Harbin Engineering University Qingdao Innovation and Development Center Shandong Qingdao266000 China Harbin Medical University Cancer Hospital Harbin150000 China School of Data Science Fudan University Shanghai China

ISBN: (纸本)9781665410205

High detail and fast magnetic resonance imaging (MRI) sequences are highly demanded in clinical settings, as inadequate imaging information can lead to diagnostic difficulties. MR image super-resolution (SR) is a promising way to address this issue, but its performance is limited due to the practical difficulty of acquiring paired low- and high-resolution (LR and HR) images. Most existing methods generate these pairs by down-sampling HR images, a process that often fails to capture complex degradations and domain-specific variations. In this study, we propose a domain-distance adapted SR framework (DDASR), which includes two stages: the domain-distance adapted down-sampling network (DSN) and the GAN-based super-resolution network (SRN). The DSN incorporates characteristics from unpaired LR images during down-sampling process, enabling the generation of domain-adapted LR images. Additionally, we present a novel GAN with enhanced attention U-Net and multi-layer perceptual loss. The proposed approach yields visually convincing textures and successfully restores outdated MRI data from the ADNI1 dataset, outperforming state-of-the-art SR approaches in both perceptual and quantitative evaluations. Code is available at https://***/Yaolab-fantastic/DDASR. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Disturbance Observer-Based Minimum Entropy Control for a Class of Disturbed Non-Gaussian Stochastic Systems

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IEEE Transactions on Cybernetics 2022年第6期52卷 4916-4925页

作者： Tian, Bo Wang, Yan Guo, Lei Beihang University School Of Automation Science And Electrical Engineering Beijing100191 China Beihang University Beijing Advanced Innovation Center For Big Data-Based Precision Medicine Beijing100191 China

In this article, a novel control algorithm is developed for a class of nonlinear stochastic systems subject to multiple disturbances, including exogenous dynamic disturbance and general non-Gaussian noise. An observer is designed to estimate the exogenous disturbance, and then the disturbance compensation is incorporated into a feedback control strategy for the non-Gaussian system. Considering the ability of entropy in randomness quantification, a performance index is established based on the generalized entropy optimization principle. Furthermore, it is adjusted to be available for the controller solution, which also solves the coupling between two kinds of disturbances. On this basis, the optimal controller is provided in a recursive way, with which the closed-loop stability and good antidisturbance ability can be guaranteed simultaneously. Compared with the existing studies on the non-Gaussian stochastic systems, the proposed control algorithm has merits in multiple disturbances decoupling and enhanced antidisturbance performance. Finally, a simulation example is given to demonstrate the effectiveness of theoretical results. © 2013 IEEE.

关键词： Stochastic systems

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Novel Audio Mosaic Using LPC-Coefficient and Excitation-Codeword Permutations

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IEEE Signal Processing Letters 2024年 31卷 1690-1694页

作者： Tsai, Morris C.-H. Wu, Hsiao-Chun Huang, Scott C.-H. Chang, Shih Yu National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for Ai Applications Taoyuan City32003 Taiwan San Jose State University Department of Applied Data Science San JoseCA95192 United States

In this letter, a novel light-weight audio mosaic scheme using permutations of linear predictive coding (LPC) coefficients as LPC has been widely adopted in many audio codecs (coder-encoders) nowadays. We establish the theoretical secrecy analysis with respect to the degree of the original LPC polynomial and the minimum-phase population of permuted LPC polynomials. The mosaic (destructuring) performance in terms of DCT-KLD (Kullback-Leibler divergence of discrete cosine transform) is also evaluated through simulations. In comparison with the existing audio-mosaic method using waveform permutations, our proposed new audio-mosaic scheme using LPC-coefficient permutations can achieve a much better mosaic performance (a much higher DCT-KLD) subject to the same key size. © 1994-2012 IEEE.

关键词： Cryptography

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Prediction of futile recanalisation after endovascular treatment in acute ischaemic stroke:development and validation of a hybrid machine learning model

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Stroke & Vascular Neurology 2024年第6期9卷 631-639页

作者： Ximing Nie Jinxu Yang Xinxin Li Tianming Zhan Dongdong Liu Hongyi Yan Yufei Wei Xiran Liu Jiaping Chen Guoyang Gong Zhenzhou Wu Zhonghua Yang Miao Wen Weibin Gu Yuesong Pan Yong Jiang Xia Meng Tao Liu Jian Cheng Zixiao Li Zhongrong Miao Liping Liu Department of Neurology Capital Medical UniversityBeijingChina China National Clinical Research Center for Neurological Diseases Beijing Tiantan HospitalBeijingChina School of Computer and Communication Engineering University of Science and TechnologyBeijingChina Department of Radiology Beijing Tiantan HospitalBeijingChina Key Laboratory of Biomechanics and Mechanobiology Ministry of EducationSchool of Biological Science and Medical Engineering International Research Institute for Multidisciplinary ScienceBeihang UniversityBeijingChina Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Computer Science and EngineeringBeihang UniversityBeijingChina Department of Interventional Neuroradiology Beijing Tiantan HospitalCapital Medical UniversityBeijingChina

Background Identification of futile recanalisation following endovascular therapy(EVT)in patients with acute ischaemic stroke is both crucial and ***,we present a novel risk stratification system based on hybrid machine learning method for predicting futile *** Hybrid machine learning models were developed to address six clinical scenarios within the EVT and perioperative management *** models were trained on a prospective database using hybrid feature selection technique to predict futile recanalisation following *** optimal model was validated and compared with existing models and scoring systems in a multicentre prospective cohort to develop a hybrid machine learning-based risk stratification system for futile recanalisation *** Using a hybrid feature selection approach,we trained and tested multiple classifiers on two independent patient cohorts(n=1122)to develop a hybrid machine learning-based prediction *** model demonstrated superior discriminative ability compared with other models and scoring systems(area under the curve=0.80,95%CI 0.73 to 0.87)and was transformed into a web application(RESCUE-FR Index)that provides a risk stratification system for individual prediction(accessible online atfr-index.biomind.cn/RESCUE-FR/).Conclusions The proposed hybrid machine learning approach could be used as an individualised risk prediction model to facilitate adherence to clinical practice guidelines and shared decision-making for optimal candidate selection and prognosis assessment in patients undergoing EVT.

关键词： database prediction optimal

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Improved LS+MAR hybrid method to UT1-UTC ultra-short-term prediction by using first-order-difference UT1-UTC

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Geodesy and Geodynamics 2024年第4期15卷 379-385页

作者： Fei Ye Yunbin Yuan BeiDou High-precision Satellite Navigation and Location Service Hunan Engineering Research Center Hunan Institute of Geomatics Sciences and TechnologyChangsha410007China State Key Laboratory of Geodesy and Earth's Dynamics Innovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhan430077China HNCORS Data Center Hunan Institute of Geomatics Sciences and TechnologyChangsha 410007China

Accurate ultra-short-term prediction of the Earth rotation parameters(ERP)holds paramount impor-tance for real-time applications,particularly in reference frame *** them,diurnal rota-tion(UT1-UTC)which cannot be directly estimated through Global Navigation Satellite System(GNSS)techniques,significantly affects the rapid and ultra-rapid orbit determination of GNsS ***-ently,the traditional LS(least squares)+AR(autoregressive)and LS+MAR(multivariate autoregressive)hybrid methods stand as primary approaches for UT1-UTC ultra-short-term predictions(1-10 days).The LS+MAR hybrid method relies on the UT1-UTC and LOD(length of day)***,the correlation between LOD and first-order-difference UT1-UTC is stronger than that between LOD and *** light of this,and with the aid of the first-order-difference UT1-UTC,we propose an enhanced LS+MAR hybrid method to UT1-UTC ultra-short-term *** using the UT1-UTC and LOD data series of the IERS(International Earth Rotation and Reference Systems Service)EOP 14 C04 product,we conducted a thorough analysis and evaluation of the improved method's prediction performance compared to the traditional LS+AR and LS+MAR hybrid *** to the numerical results over more than 210 days,they demonstrate that,when considering the correlation information between the LoD and the first-order-difference UT1-UTC,the mean absolute errors(MAEs)of the improved LS+MAR hybrid method range from 21 to 934μs in 1-10 days *** comparison to the traditional LS+AR hybrid method,the MAEs show a reduction of 7-53μs in 1-10 days predictions,with corresponding improvement percentages ranging from 1 to 28%.Similarly,when compared to the traditional LS+MAR hybrid method,the MAEs have a reduction of 5-42μs in 1-10 days predictions,with corresponding improvement percentages ranging from 4-20%.Additionally,when aided by GNSS-derived LOD data series,the MAEs of improved LS+MAR hybrid method experience further

关键词： UT1-UTCultra-short-termprediction Rapidandultra-rapidproducts LS+AR and LS+MAR Correlation First-order-differenceUT1-UTC

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YTHDF1 shapes immune-mediated hepatitis via regulating inflammatory cell recruitment and response

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Genes & Diseases 2025年第3期12卷 550-566页

作者： Hao Li Kailun Yu Xiandan Zhang Jiawen Li Huilong Hu Xusheng Deng Siyu Zeng Xiaoning Dong Junru Zhao Yongyou Zhang State Key Laboratory of Cellular Stress Biology Innovation Center for Cell Signaling NetworkSchool of Life SciencesXiamen UniversityXiamenFujian 361102China National Institute for Data Science in Health and Medicine Engineering Faculty of Medicine and Life SciencesXiamen UniversityXiamenFujian 361102China School of Pharmaceutical Sciences Xiamen UniversityXiamenFujian 361102China

Severe immune responses regulate the various clinical hepatic injuries, includingautoimmune hepatitis and acute viral hepatitis. N6-methyladenosine (m6A) modification is acrucial regulator of immunity and inflammation. However, the precise role of YTHDF1 in Tcell-mediated hepatitis remains incompletely characterized. To address this, we utilizedConcanavalin A (ConA)-induced mouse liver damage as an experimental model for T cell-mediated hepatitis. Our findings found that hepatic YTHDF1 protein rapidly decreased during ConAinduced hepatitis, and YTHDF1-deficient (Ythdf1^(-/-)) mice showed more susceptibility toConA-induced liver injury, along with an intensified inflammatory storm accompanied by aggravated hepatic inflammatory response via ERK and NF-κB pathways. Interestingly, hepatic-specific over-expression or deletion of YTHDF1 exhibited redundancy in ConA-induced liver *** in bone marrow chimeric mice confirmed the necessity of YTHDF1 in hematopoieticcells for controlling the response to ConA-induced hepatitis. Additionally, our data revealedthat YTHDF1 deletion in macrophages exacerbated the inflammatory response induced by lipopolysaccharide. In summary, our study uncovered that YTHDF1 deficiency exacerbates the immune response in ConA-induced hepatitis by modulating the expression of inflammatorymediators, highlighting the potential of YTHDF1 as a therapeutic target for clinical hepatitis.

关键词： Concanavalin A Hepatitis Inflammatory response N6-methyladenine YTHDF1

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Bioinspired polarized light compass in moonlit sky for heading determination based on probability density estimation

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Chinese Journal of Aeronautics 2022年第3期35卷 1-9页

作者： Yueting YANG Yan WANG Lei GUO Bo TIAN Jian YANG Wenshuo LI Taihang CHEN School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100083China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and EngineeringBeihang UniversityBeijing 100083China Key Laboratory of Big Data-Based Precision Medicine Ministry of Industry and Information TechnologyBeihang UniversityBeijing 100083China Hangzhou Innovation Institute Beihang UniversityBeijing 100083China School of Cyber Science and Technology Beihang UniversityBeijing 100083China

Bioinspired polarized skylight navigation,which can be used in unfamiliar territories,is an important alternative autonomous navigation technique in the absence of Global Navigation Satellite System(GNSS).However,the polarization pattern in night environment with noise effects and model uncertainties is a less explored *** several decades have passed since the first publication about the polarization of the moonlit night sky,the usefulness of nocturnal polarization navigation is only sporadic in previous *** study demonstrates that the nocturnal polarized light is capable of providing accurate and stable navigation information in dim light outdoor *** on the statistical characteristics of Angle of Polarization(Ao P)error,a probability density estimation method is proposed for heading *** illustrate the application potentials,the simulation and outdoor experiments are ***,the proposed method robustly models the distribution of Ao P error and gives accurate heading estimation evaluated by Standard Deviation(STD)which is 0.32°in a clear night sky and 0.47°in a cloudy night sky.

关键词： Nocturnal polarization Moonlit sky Angle of Polarization(AoP) Probability density estimation Navigation

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Review on application progress of federated learning model and security hazard protection

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Digital Communications and Networks 2023年第1期9卷 146-158页

作者： Aimin Yang Zezhong Ma Chunying Zhang Yang Han Zhibin Hu Wei Zhang Xiangdong Huang Yafeng Wu Hebei Engineering Research Center for the Intelligentization of Iron Ore Optimization and Ironmaking Raw Materials Preparation Processes North China University of Science and TechnologyTangshanHebeiChina Hebei Key Laboratory of Data Science and Application North China University of Science and TechnologyTangshanHebeiChina The Key Laboratory of Engineering Computing in Tangshan City North China University of Science and TechnologyTangshanHebeiChina Tangshan Intelligent Industry and Image Processing Technology Innovation Center North China University of Science and TechnologyTangshanHebeiChina College of Science North China University of Science and TechnologyTangshanHebeiChina College of Artificial Intelligence North China University of Science and TechnologyTangshanHebeiChina

Federated learning is a new type of distributed learning framework that allows multiple participants to share training results without revealing their data *** data privacy becomes more important,it becomes difficult to collect data from multiple data owners to make machine learning predictions due to the lack of data *** is forced to be stored independently between companies,creating“data silos”.With the goal of safeguarding data privacy and security,the federated learning framework greatly expands the amount of training data,effectively improving the shortcomings of traditional machine learning and deep learning,and bringing AI algorithms closer to our *** the context of the current international data security issues,federated learning is developing rapidly and has gradually moved from the theoretical to the applied *** paper first introduces the federated learning framework,analyzes its advantages,reviews the results of federated learning applications in industries such as communication and healthcare,then analyzes the pitfalls of federated learning and discusses the security issues that should be considered in applications,and finally looks into the future of federated learning and the application layer.

关键词： data silos Machine learning Federated learning Privacy protection Learning framework

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