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Nano Research 2024年第6期17卷 5179-5187页

作者： Jinlei Qin Rui Wang zilong yuan Pei Xiao Deli Wang Key Laboratory of Material Chemistry for Energy Conversion and Storage Ministry of EducationHubei Key Laboratory of Material Chemistry and Service FailureSchool of Chemistry and Chemical EngineeringHuazhong University of Science and TechnologyWuhan 430074China

Lithium-sulfur(Li-S)batteries have been considered as promising energy storage systems due to the merits of high energy density and low ***,the lithium polysulfides(LiPSs)diffusion and sluggish redox kinetics hamper t... 详细信息

关键词： Li-S batteries nitrogen-doped carbon confinement oxygen vacancies bidirectional Li_(2)S redox

Universal materials model of deep-learning density functional theory Hamiltonian

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Science Bulletin 2024年第16期69卷 2514-2521页

作者： Yuxiang Wang Yang Li Zechen Tang He Li zilong yuan Honggeng Tao Nianlong Zou Ting Bao Xinghao Liang Zezhou Chen Shanghua Xu Ce Bian Zhiming Xu Chong Wang Chen Si Wenhui Duan Yong Xu State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics Tsinghua UniversityBeijing 100084China Institute for Advanced Study Tsinghua UniversityBeijing 100084China Frontier Science Center for Quantum Information Beijing 100084China RIKEN Center for Emergent Matter Science(CEMS) Wako 351-0198Japan School of Materials Science and Engineering Beihang UniversityBeijing 100191China

Realizing large materials models has emerged as a critical endeavor for materials research in the new era of artificial intelligence,but how to achieve this fantastic and challenging objective remains ***,we propose a feasible pathway to address this paramount pursuit by developing universal materials models of deep-learning density functional theory Hamiltonian(Deep H),enabling computational modeling of the complicated structure-property relationship of materials in *** constructing a large materials database and substantially improving the Deep H method,we obtain a universal materials model of Deep H capable of handling diverse elemental compositions and material structures,achieving remarkable accuracy in predicting material *** further showcase a promising application of fine-tuning universal materials models for enhancing specific materials *** work not only demonstrates the concept of Deep H's universal materials model but also lays the groundwork for developing large materials models,opening up significant opportunities for advancing artificial intelligencedriven materials discovery.

关键词： Large materials model Universal materials model Deep-learning density functional theory Artificial intelligence-driven materials discovery

基于MRI肿瘤和瘤周的机器学习模型预测直肠癌新辅助治疗后淋巴结转移的研究

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临床放射学杂志 2024年第8期43卷 1371-1378页

作者：杨倩郭小芳袁子龙聂婷婷刘玉林湖北省肿瘤医院放射科湖北省结直肠癌临床医学研究中心武汉市结直肠癌临床医学研究中心430079

目的探讨基于T_(2)WI肿瘤和直肠系膜的机器学习对直肠癌新辅助治疗后淋巴结转移的预测价值。方法回顾性分析171例直肠癌病例新辅助治疗前的临床影像资料及术后病理资料。依据术后病理结果分为N-(N0)和N+(N1、N2)。统计学分析筛选出与N分... 详细信息

目的探讨基于T_(2)WI肿瘤和直肠系膜的机器学习对直肠癌新辅助治疗后淋巴结转移的预测价值。方法回顾性分析171例直肠癌病例新辅助治疗前的临床影像资料及术后病理资料。依据术后病理结果分为N-(N0)和N+(N1、N2)。统计学分析筛选出与N分期(pN)存在相关性的临床特征(实验室指标及MRI影像学表现)。使用ITK⁃SNAP软件在新辅助治疗前直肠MRI高分辨率T_(2)WI图像上,手动绘制直肠癌整个瘤灶作为感兴趣区(ROI⁃1),直肠系膜区域作为ROI⁃2;从ROI⁃1、ROI⁃2提取所有影像组学特征,保留稳定性较好(ICC≥0.75)的特征。采用最小绝对紧缩与选择算子(LASSO)方法从ROI⁃1、ROI⁃2及融合特征(ROI⁃1+ROI⁃2+临床特征)中筛选出与pN最相关的特征。将筛选得到的四组特征,分别采用支持向量机(SVM)、K最邻近算法(KNN)、随机森林(RF)、极端随机树(ET)、梯度提升决策树(XGBoost)、LightGBM(LGBM)、逻辑回归(LR)七种机器学习算法构建pN的预测模型,使用受试者工作特征曲线(ROC)评估模型的性能。结果171例直肠癌患者,手术结果显示N-组92例,N+组79例。ROI⁃1筛选得到的特征构建的7种模型中,LR模型效能最佳,测试集中受试者工作特征曲线曲线下面积(AUC)0.656、准确性0.714、敏感度0.583、特异度0.783。ROI⁃2中,SVM模型效能最佳,测试集中,AUC、准确性、敏感度、特异度相应为0.721、0.657、0.917、0.522。临床模型中,LR模型效能最佳,相应为0.768、0.771、0.833、0.773。融合模型中,LR模型预测效能最佳,相应为0.866、0.800、0.917、0.739。结论基于机器学习的直肠肿瘤及直肠系膜MRI影像组学分析均能预测直肠癌新辅助治疗后淋巴结转移情况,融合双区域多组学特征采用逻辑回归方法可提高预测模型的准确性。

关键词：磁共振成像影像组学直肠癌机器学习 N分期

Magnetic moment predictions of odd-A nuclei with the Bayesian neural network approach

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Chinese Physics C 2021年第12期45卷 147-154页

作者： zilong yuan Dachuan Tian Jian Li Zhongming Niu College of Physics Jilin UniversityChangchun 130012China School of Physics and Materials Science Anhui UniversityHefei 230601China Institute of Physical Science and Information Technology Anhui UniversityHefei 230601China

The Bayesian neural network approach has been employed to improve the nuclear magnetic moment predictions of odd-A *** Schmidt magnetic moment obtained from the extreme single-particle shell model makes large root-mean-square(rms)deviations from data,i.e.,0.949μN and 1.272μN for odd-neutron nuclei and odd-proton nuclei,*** including the dependence of the nuclear spin and Schmidt magnetic moment,the machine-learning approach precisely describes the magnetic moments of odd-A uclei with rms deviations of 0.036μN for odd-neutron nuclei and 0.061μN for odd-proton ***,the evolution of magnetic moments along isotopic chains,including the staggering and sudden jump trend,which are difficult to describe using nuclear models,have been well reproduced by the Bayesian neural network(BNN)*** magnetic moments of doubly closed-shell±1 nuclei,for example,isoscalar and isovector magnetic moments,have been well studied and compared with the corresponding non-relativistic and relativistic calculations.

关键词： magnetic moment odd-A nuclei Bayesian neural network approach

Prompt learning in computer vision: a survey

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 42-63页

作者： Yiming LEI Jingqi LI zilong LI yuan CAO Hongming SHAN Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200438China Institute of Science and Technology for Brain-Inspired Intelligence Fudan UniversityShanghai 200433China MOE Frontiers Center for Brain Science Fudan UniversityShanghai 200433China Shanghai Center for Brain Science and Brain-Inspired Technology Shanghai 201210China

Prompt learning has attracted broad attention in computer vision since the large pre-trained visionlanguagemodels (VLMs) exploded. Based on the close relationship between vision and language information builtby VLM, prompt learning becomes a crucial technique in many important applications such as artificial intelligencegenerated content (AIGC). In this survey, we provide a progressive and comprehensive review of visual promptlearning as related to AIGC. We begin by introducing VLM, the foundation of visual prompt learning. Then, wereview the vision prompt learning methods and prompt-guided generative models, and discuss how to improve theefficiency of adapting AIGC models to specific downstream tasks. Finally, we provide some promising researchdirections concerning prompt learning.

关键词： Prompt learning Visual prompt tuning(VPT) Image generation Image classification Artificial intelligence generated content(AIGC)

PhaseⅡstudy of induction chemotherapy followed by concurrent chemoradiotherapy with raltitrexed and cisplatin in locally advanced nasopharyngeal carcinoma

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Chinese Journal of Cancer Research 2020年第5期32卷 665-672页

作者： yuan Wu Xueyan Wei zilong yuan Hongbin Xu Yanping Li Ying Li Liu Hu Guang Han Yu Qian Desheng Hu Department of Radiation Oncology Hubei Cancer HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430071China Department of Radiology Hubei Cancer HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430071China Department of Medical Oncology Hubei Cancer HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430071China

Objective:For locally advanced nasopharyngeal carcinoma(LA-NPC)patients,high incidences of distant metastases and severe treatment related toxicities are the main obstacles needed to be ***,a specific thymidylate synthase inhibitor with a convenient administration schedule,has an acceptable and manageable toxicity,and possesses radio-sensitizing *** investigate the efficacy and safety of raltitrexed and cisplatin induction chemotherapy and concurrent chemoradiotherapy(IC+CCRT)in patients with LA-NPC,a phaseⅡclinical study was ***:Sixty eligible patients with LA-NPC were enrolled into this study.A raltitrexed-cisplatin combination was used as part of an IC+CCRT ***-cisplatin IC was given once every 3 weeks(q3 w)for two cycles,followed by raltitrexed-cisplatin based CCRT q3 w for two ***-modulated radiotherapy(IMRT)was given for all enrolled ***:All patients were included in survival analysis according to the intent-to-treat *** objective response rate(ORR)3 months after treatment was 98%.The 2-year overall survival(OS)rate was 92%.The median relapse-free survival(RFS)time was 30.5[95%confidence interval(95%CI),28.4-32.3]*** 2-year RFS rate was 85%.The 2-year local failure-free survival(LFFS)rate was 97%and the 2-year distant metastasis-free survival(DMFS)rate was 88%.Acute toxicities were mostly grade 2 and 3 reactions in bone marrow suppression,gastrointestinal side effect and oropharyngeal *** two patients occurred grade 4 acute toxicities,one was bone marrow suppression and the other was dermatitis ***:The combination of raltitrexed and cisplatin has a comparable efficacy to those in standard firstline therapy.

关键词： Nasopharyngeal carcinoma raltitrexed cisplatin induction chemotherapy concurrent chemoradiotherapy

Computed tomography-based delta-radiomics enabling early prediction ofshort-term responses to concurrent chemoradiotherapy for patients withnon-small cell lung cancer

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Radiation Medicine and Protection 2023年第4期4卷 227-235页

作者： Fengqin Zhou Jianping Bi Shen Wu Yi Ding Jun Chen Mengting yuan Yaoyao He Guang Han zilong yuan Department of Radiology Hubei Cancer HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430079China Department of Radiation Oncology Hubei Cancer HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430079China GE Healthiness Shanghai 200126China

Objective:To explore the potential of computed tomography(CT)-based delta-radiomics in predicting early shortterm responses to concurrent chemoradiotherapy for patients with non-small cell lung cancer(NSCLC),in order to determine the optimal time point for the ***:A total of 20 patients with pathologically confirmed NSCLC were prospectively enrolled in this study,who did not receive surgical treatment between February 2021 and February *** each case,a total of 1,210 radiomic features(RFs)were extracted from both planning CT(pCT)images along with each of the subsequent three weeks of CT ***ΔRFs were selected using intra-class correlation coefficient(ICC)analysis,Pearson's correlation,ANOVA test(or Mann-Whitney U-test),and univariate logistic *** area under the curve(AUC)of the receiver operating characteristic(ROC)curve was used to evaluate the potential to predict short-term responses of different time ***:Among the 1,210ΔRFs for 1-3 weeks,121 common features were retained after processing using ICC analysis and Pearson's *** retained features included 54 and 58 of all time points that differed significantly between the response and non-response groups for the first and third months,respectively(P<0.05).After univariate logistic regression,11 and 44 features remained for the first and third months,***,eightΔRFs(P<0.05,AUC=0.77-0.91)that can discriminate short-term responses in both at 1 and 3 months with statistical accuracy were ***:CT-based delta-radiomics has the potential to provide reasonable biomarkers of short-term responses to concurrent chemoradiotherapy for NSCLC patients,and it can help improve clinical decisions for early treatment adaptation.

关键词： Non-small cell lung cancer Delta-radiomics Short-term response Computed tomography Concurrent chemoradiotherapy

Postsynthetic Crystalline Transformation in Two-Dimensional Perovskites via Organothiol-Based Chemistry

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CCS Chemistry 2022年第3期4卷 855-863页

作者： zilong yuan Liang Zhao Ekadashi Pradhan Ming Lai Tao Zeng Zhenyu Yang MOE Laboratory of Bioinorganic and Synthetic Chemistry Lehn Institute of Functional MaterialsSchool of ChemistrySun Yat-sen UniversityGuangzhouGuangdong 510275 Department of Chemistry York UniversityTorontoON M3J1P3

The first postsynthetic solution-based crystal transformation of two-dimensional metal halide perovskites(2D MHPs)through organothiol-based reactions is *** is well-established that the crystal formation from a solution containing predesigned metal ion and organic cation precursors produces well-defined 2D MHPs with various intercalating organic ***,few reports outlining the postsynthetic crystal transformation of 2D MHPs have ***,we report that,upon organothiol-based redox or condensation reactions,large organic cations in three types of 2D MHPs can interconvert under ambient conditions without damage to the layered inorganic *** swift and complete crystal interconversion has been confirmed using combined techniques including X-ray diffraction and ^(13)C nuclear magnetic resonance(^(13)C NMR)*** structures of the MHPs were investigated using computational chemistry.

关键词： metal halide perovskites reduceddimensionality crystal transformation organothiol single crystal

Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 40-53页

作者： Yiyi yuan Jingbing Li Jing Liu Uzair Aslam Bhatti zilong Liu Yen-wei Chen School of Information and Communication Engineering Hainan UniversityHaikouChina Research Center for Healthcare Data Science Zhejiang LabHangzhouChina Graduate School of Information Science and Engineering Ritsumeikan University ShigaJapan

In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical *** address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic ***,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling *** Daisy descriptor matrix for this point is then ***,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical *** scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image *** embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational *** results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.

关键词： daisy descriptor DCT DWT encryption domain medical image zero-watermarking

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反射波振幅谱特征与地震仪前置放大器设计

仪器仪表学报 2006年第2期27卷 137-140页

作者：袁子龙李婷婷大庆石油学院大庆163318

由于地层吸收衰减及球面扩散,使得深层地震反射波的振幅衰减严重,导致地震仪记录信号的有效动态范围远小于120dB,满足不了高分辨率地震勘探对记录信号动态范围的要求。从视等厚层状吸收介质模型入手,理论计算了地震反射波的振幅谱。其... 详细信息

由于地层吸收衰减及球面扩散,使得深层地震反射波的振幅衰减严重,导致地震仪记录信号的有效动态范围远小于120dB,满足不了高分辨率地震勘探对记录信号动态范围的要求。从视等厚层状吸收介质模型入手,理论计算了地震反射波的振幅谱。其特征分析表明:反射波振幅随深度的增加按指数规律衰减,但衰减主要发生在1.5s前的中浅层。设计了智能程控型前置放大器,它的增益随深度增加自动增大,其值依次为0dB、18dB、24dB、30dB、36dB和42dB,使深浅层地震反射波的振幅在记录前均得到适当补偿,确保了地震仪记录信号的有效动态范围接近120dB,这对高分辨率地震勘探理论和开发新一代地震仪具有重要意义。

关键词：地震反射波振幅谱地层吸收动态范围地震仪前置放大器