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Artificial intelligence-driven radiomics study in cancer:the role of feature engineering and modeling

Military Medical Research 2024年第1期11卷 115-147页

作者： Yuan-Peng zhang xin-yun zhang Yu-Ting Cheng Bing Li xin-Zhi Teng Jiang zhang Saikit Lam Ta Zhou Zong-Rui Ma Jia-Bao Sheng Victor CWTam Shara WYLee Hong Ge Jing Cai Department of Medical Informatics Nantong UniversityNantong 226001JiangsuChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong 999077China The Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen 518000GuangdongChina Department of Radiation Oncology the Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer HospitalZhengzhou 450008China

Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients’***,the interpretation of medical images can be highly subjective and dependent on the expertise of ***,some potentially useful quantitative information in medical images,especially that which is not visible to the naked eye,is often ignored during clinical *** contrast,radiomics performs high-throughput feature extraction from medical images,which enables quantitative analysis of medical images and prediction of various clinical *** have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized ***,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical *** this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with *** focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical ***,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of ***,we offer possible solutions to current challenges in radiomics research.

关键词： Artificial intelligence Radiomics Feature extraction Feature selection Modeling Interpretability Multimodalities Head and neck cancer

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SDCC: software-defined collective communication for distributed training

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Science China(Information Sciences) 2024年第9期67卷 105-125页

作者： xin JIN Zhen zhang yunshan JIA yun MA Xuanzhe LIU School of Computer Science Peking University Department of Computer Science and Technology Johns Hopkins University

Communication is crucial to the performance of distributed training. Today's solutions tightly couple the control and data planes and lack flexibility, generality, and performance. In this study, we present SDCC, a software-defined collective communication framework for distributed training. SDCC is based on the principle of modern systems design to effectively decouple the control plane from the data *** abstracts the operations for collective communication in distributed training with dataflow operations and unifies computing and communication with a single dataflow graph. The abstraction, together with the unification, is powerful: it enables users to easily express new and existing collective communication algorithms and optimizations, simplifies the integration with different computing engines(e.g., Py Torch and Tensor Flow) and network transports(e.g., Linux TCP and kernel bypass), and allows the system to improve performance by exploiting parallelism exposed by the dataflow graph. We further demonstrate the benefits of SDCC in four use cases.

关键词： machine learning systems distributed training deep learning collective communication software-defined networking

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An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

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Petroleum Science 2024年第2期21卷 885-902页

作者： xin zhang yun-Hu Lu Yan Jin Mian Chen Bo Zhou State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum(Beijing)Beijing102249China College of Petroleum Engineering China University of Petroleum(Beijing)Beijing102249China College of Artificial Intelligence China University of Petroleum(Beijing)Beijing102249China PetroChina Tarim Oilfield Company KorlaXinjiang841000China

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum *** deep learning technique has been receiving more interest due to the great potential to deal with pore pressure ***,most of the traditional deep learning models are less efficient to address generalization *** fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic ***,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss *** machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure *** CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few *** validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization *** adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

关键词： Pore pressure prediction Seismic data 1D convolution pyramid pooling Adaptive physics-informed loss function High generalization capability

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Orbit and clock products for quad-system satellites with undifferenced ambiguity fixing approach

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Satellite Navigation 2024年第1期5卷 125-139页

作者： Jiaqi Wu xingxing Li Yongqiang Yuan Keke zhang xin Li Jiaqing Lou yun Xiong School of Geodesy and Geomatics Wuhan University129 Luoyu RoadWuhan430079China Hubei Luojia Laboratory 129 Luoyu RoadWuhan430079China German Research Centre for Geosciences GFZ Telegrafenberg14473PotsdamGermany Technische Universitat Berlin(TUB) Straße Des 17.Juni10623BerlinGermany

Integer Ambiguity Resolution(IAR)can significantly improve the accuracy of GNSS Precise Orbit Determination(POD).Traditionally,the IAR in POD is achieved at the Double Differenced(DD)*** this contribution,we develop an Un-Differenced(UD)IAR method for Global Positioning System(GPS)+BeiDou Navigation Satellite System(BDS)+Galileo navigation satellite system(Galileo)+Global'naya Navigatsionnaya Sputnikovaya Sistema(GLONASS)quad-system POD by calibrating UD ambiguities in the raw carrier phase and generating the so-called carrier *** on this method,we generate the UD ambiguity-fixed orbit and clock products for the Wuhan Innovation Application Center(IAC)of the International GNSS Monitoring and Assessment System(iGMAS).One-year observations in 2020 from 150 stations are employed to investigate performance of orbit and clock ***,the UD Ambiguity Resolution(AR)yields more resolved integer ambiguities than the traditional DD AR,scaling up to 9%,attributable to its avoidance of station baseline *** from the removal of ambiguity parameters,the computational efficiency of parameter estimation undergoes a substantial 70%*** with the float solution,the orbit consistencies of UD AR solution achieve the accuracy of 1.9,5.2,2.8,2.1,and 2.7 cm for GPS,BeiDou-2 Navigation Satellite System(BDS-2),BeiDou-3 Navigation Satellite System(BDS-3),Galileo,and GLONASS satellites respectively,reflecting enhancements of 40%,24%,54%,34%,and 42%.Moreover,the standard deviations of Satellite Laser Ranging(SLR)residuals are spanning 2.5–3.5 cm,underscoring a comparable accuracy to the DD AR solution,with discrepancies below 5%.A notable advantage of UD AR lies in its capability to produce the Integer Recovered Clock(IRC),facilitating Precise Point Positioning(PPP)AR without requiring additional Uncalibrated Phase Delay(UPD)*** assess the performance of quad-system kinematic PPP based on IRC,a network comprising 120 stations is uti

关键词： Multi-GNSS Precise orbit determination Integer recover clock Undifferenced ambiguity resolution iGMAS innovation application center

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Preparation of tungsten-particle-reinforced Zr-based bulk metallic glass composites by two-step spark plasma sintering:microstructure evolution,densification mechanism and mechanical properties

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Rare Metals 2024年第4期43卷 1793-1808页

作者： yun-Fei Ma Pan Gong Mao zhang Hui-EHu Zhen Peng Xiao Xu xin Wang Mehdi Malekan Xue-Feng Tang Lei Deng Jun-Song Jin xin-yun Wang State Key Laboratory of Materials Processing and Die and Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan430074China Research Institute of Huazhong University of Science and Technology in Shenzhen Shenzhen518057China Department of Chemistry and Materials Naval University of EngineeringWuhan430032China School of Materials Science and Engineering Jiangsu UniversityZhenjiang212013China College of Machine Shanghai Dianji UniversityShanghai201306China School of Metallurgy and Materials Engineering College of EngineeringUniversity of TehranTehran 11155-4563Iran

A new two-step spark plasma sintering(TSS)process with low-temperature pre-sintering and high-temperature final sintering has been successfully applied to prepare the tungsten-particle(Wp)-reinforced bulk metallic glass composites(Wp/BMGCs).Compared to normal spark plasma sintering(NS),the densification rate and relative density of Wp/BMGCs can be improved by selecting TSS with appropriate sintering pressure in the low temperature pre-sintering ***,the compressive strength and plastic strain of 30%Wp/BMGCs prepared by TSS are both higher than those of the samples prepared by *** TSS process can significantly enhance the compressive strength of 30%Wp/BMGCs by 12%and remarkably increase the plastic strain by 50%,while the trend is completely opposite for 50%Wp/***-in situ experiments and finite element simulations reveal that uneven temperature distribution among particles during low-temperature pre-sintering causes local overheating at contact points between particles,accelerating formation of sintering neck between particles and plastic deformation of *** the volume fraction of Wp is low,TSS can improve the interface bonding between particles by increasing the number of sintering *** makes the fracture mode of Wp/BMGCs being predominantly transgranular ***,as the volume fraction of Wp increases,the adverse effects of Wp plastic deformation are becoming more and more *** aggregated Wp tends to form a solid"cage structure"that hinders the bonding between particles at the interface;correspondingly,the fracture behavior of Wp/BMGCs is mainly dominated by intergranular ***,reducing the sintering pressure during the low-temperature pre-sintering stage of TSS has been shown to effectively decrease plastic deformation in Wp,resulting in a higher degree of densification and better mechanical properties.

关键词： Bulk metallic glass composites Tungsten particle Two-step spark plasma sintering Densification mechanism Mechanical properties

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Probabilistic seismic inversion based on physics-guided deep mixture density network

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Petroleum Science 2024年第3期21卷 1611-1631页

作者： Qian-Hao Sun Zhao-yun Zong xin Li National Key Laboratory of Deep Oil and Gas China University of Petroleum(East China)Qingdao266580ShandongChina Laoshan Laboratory Qingdao266580ShandongChina CNOOC Research Institute Ltd. Beijing100028China

Deterministic inversion based on deep learning has been widely utilized in model parameters *** by logging data,seismic data,wavelet and modeling operator,deterministic inversion based on deep learning can establish nonlinear relationships between seismic data and model ***,seismic data lacks low-frequency and contains noise,which increases the non-uniqueness of the *** conventional inversion method based on deep learning can only establish the deterministic relationship between seismic data and parameters,and cannot quantify the uncertainty of *** order to quickly quantify the uncertainty,a physics-guided deep mixture density network(PG-DMDN)is established by combining the mixture density network(MDN)with the deep neural network(DNN).Compared with Bayesian neural network(BNN)and network dropout,PG-DMDN has lower computing cost and shorter training time.A low-frequency model is introduced in the training process of the network to help the network learn the nonlinear relationship between narrowband seismic data and low-frequency *** addition,the block constraints are added to the PG-DMDN framework to improve the horizontal continuity of the inversion *** illustrate the benefits of proposed method,the PG-DMDN is compared with existing semi-supervised inversion *** synthetic data examples of Marmousi II model are utilized to quantify the influence of forward modeling part,low-frequency model,noise and the pseudo-wells number on inversion results,and prove the feasibility and stability of the proposed *** addition,the robustness and generality of the proposed method are verified by the field seismic data.

关键词： Deep learning Probabilistic inversion Physics-guided Deep mixture density network

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Value Iteration-Based Cooperative Adaptive Optimal Control for Multi-Player Differential Games With Incomplete Information

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 690-697页

作者： yun zhang Lulu zhang yunze Cai the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240 the Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China

This paper presents a novel cooperative value iteration(VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence *** players are divided into two groups in the learning process and adapt their policies *** method removes the dependence of admissible initial policies,which is one of the main drawbacks of the PI-based ***,this algorithm enables the players to adapt their control policies without full knowledge of others’ system parameters or control *** efficacy of our method is illustrated by three examples.

关键词： Adaptive dynamic programming incomplete information multi-player differential game value iteration

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Limit Properties of One Dimensional Periodic Hopping Model

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Chinese Journal of Chemical Physics 2010年第1期23卷 65-68,I0001,I0002页

作者：张云新上海市现代应用数学重点实验室复旦大学数学科学学院上海200433

One dimensional periodic hopping model is useful to understand the motion of microscopic particles in thermal noise environment. In this research, by formal calculation and based on detailed balance, the explicit expressions of the limits of mean velocity and diffusion constant of this model as the number of internal mechanochemical sates tend to infinity are *** results will be helpful to understand the limit of the one dimensional hopping *** the same time, the work can be used to get more useful results in continuous form from the corresponding ones obtained by discrete models.

关键词： Diffusion constant Mean velocity Hopping model

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Microstructure and mechanical properties of Co-28Cr-6Mo-0.22C investment castings by current solution treatment

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China Foundry 2024年第4期21卷 369-378页

作者： Ze-yu Dan Jun Liu Jian-lei zhang Yan-hua Li Yuan-xin Deng yun-hu zhang Chang-jiang Song Center for Advanced Solidification Technology School of Materials Science and EngineeringShanghai UniversityShanghai 200444China Wuxi CastPro Precision Co. Ltd.Wuxi 214105JiangsuChina

This study examined the impact of current solution treatment on the microstructure and mechanical properties of the Co-28Cr-6Mo-0.22C alloy investment *** findings reveal that the current solution treatment significantly promotes the dissolution of carbides at a lower *** optimal conditions for solution treatment are determined as a solution temperature of 1,125°C and a holding time of 5.0 *** these parameters,the size and volume fraction of precipitated phases in the investment castings are measured as6.2μm and 1.1vol.%.The yield strength,ultimate tensile strength,and total elongation of the Co-28Cr-6Mo-0.22C investment castings are 535 MPa,760 MPa,and 12.6%,*** values exceed those obtained with the conventional solution treatment at 1,200°C for 4.0 *** findings suggest a phase transformation of M_(23)C_(6)→σ+C following the current solution treatment at 1,125°C for 5.0 *** comparison,the traditional solution treatment at 1,200°C for 4.0 h leads to the formation of M_(23)C_(6)and M_(6)C *** is noteworthy that the non-thermal effect of the current during the solution treatment modifies the free energy of both the matrix and precipitation *** modification lowers the phase transition temperature of the M_(23)C_(6)→σ+C reaction,thereby facilitating the dissolution of *** a result,the current solution treatment approach achieves carbide dissolution at a lower temperature and within a significantly shorter time when compared to the traditional solution treatment methods.

关键词： CoCrMo alloy investment castings current solution treatment microstructure mechanical property carbide

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Influencing factors of self-management ability among dry eye patients in west China

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International Journal of Ophthalmology(English edition) 2024年第9期17卷 1621-1627页

作者： Jie Ren xin zhang Ji-Hong Zeng yun-Xia Gao Department of Ophthalmology West China HospitalSichuan University/West China School of NursingSichuan UniversityChengdu 610041Sichuan ProvinceChina

AIM:To investigate the current situation and influencing factors of self-management ability in dry eye patients in west ***:A total of 265 patients clinically diagnosed with dry eye received a convenience survey questionnaire at West China Hospital of Sichuan *** participants completed the rating scale of health self-management skill for adults(AHSMSRS),Huaxi Emotional-Distress Index(HEI),e-health literacy scale(e-HEALS)and Brief Illness Perception Questionnaire(Brief-IPQ).A generalized linear model was employed to establish a multivariate linear model with demographic data,psychological state,e-HEALS,and illness perception as independent variables and health selfmanagement skill score as the dependent ***:The mean score for health self-management skill was 165.58±*** analysis revealed that advanced age,better illness perception and improved psychological state were associated with better health selfmanagement ability among dry eye ***,the health self-management ability of patients with a disease duration less than 1y was found to be higher compared to those with a disease duration exceeding ***:The health self-management ability of dry eye patients in west China is relatively ***,duration of disease,illness perception and psychological state are the influencing factors on the health selfmanagement ability of dry eye patients.

关键词： dry eye self-management ability influencing factors

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