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A particle-resolved heat-particle-fluid coupling model by DEM-IMB-LBM

Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2267-2281页

作者： ming Xia jinlong Fu Y.T.Feng Fengqiang Gong jin yu Hunan Key Laboratory of Geomechanics and Engineering Safety Xiangtan UniversityXiangtan411105China Zienkiewicz Institute for Modelling Data and AISwansea UniversitySwanseaSA18EPUK School of Civil Engineering Southeast UniversityNanjing211189China Fujian Research Center for Tunneling and Urban Underground Space Engineering Huaqiao UniversityXiamen361021China

Multifield coupling is frequently encountered and also an active area of research in geotechnical engineering.In this work,a particle-resolved direct numerical simulation(PR-DNS)technique is extended to simulate particle-fluid interaction problems involving heat transfer at the grain level.In this extended technique,an immersed moving boundary(IMB)scheme is used to couple the discrete element method(DEM)and lattice Boltzmann method(LBM),while a recently proposed Dirichlet-type thermal boundary condition is also adapted to account for heat transfer between fluid phase and solid particles.The resulting DEM-IBM-LBM model is robust to simulate moving curved boundaries with constant temperature in thermal flows.To facilitate the understanding and implementation of this coupled model for non-isothermal problems,a complete list is given for the conversion of relevant physical variables to lattice units.Then,benchmark tests,including a single-particle sedimentation and a two-particle drafting-kissing-tumbling(DKT)simulation with heat transfer,are carried out to validate the accuracy of our coupled technique.To further investigate the role of heat transfer in particle-laden flows,two multiple-particle problems with heat transfer are performed.Numerical examples demonstrate that the proposed coupling model is a promising high-resolution approach for simulating the heat-particle-fluid coupling at the grain level.

关键词： Particle-fluid interaction Heat transfer Discrete element method(DEM) Lattice Boltzmann method(LBM) Dirichlet-type thermal boundary Direct numerical simulation

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Preoperative blood markers and intra-abdominal infection after colorectal cancer resection

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World Journal of Gastrointestinal Surgery 2024年第2期16卷 451-462页

作者： Chang-Qing Liu Zhong-Bei yu jin-Xian Gan Tian-ming Mei Department of Gastrointestinal Anorectal Surgery Suzhou Hospital Affiliated to Anhui Medical UniversitySuzhou 234000Anhui ProvinceChina

BACKGROUND Colorectal cancer(CRC)has one of the highest morbidity and mortality rates among digestive tract tumors.Intra-abdominal infection(IAI)is a common postoperative complication that affects the clinical outcomes of patients with CRC and hinders their rehabilitation process.However,the factors influencing abdominal infection after CRC surgery remain unclear;further,prediction models are rarely used to analyze preoperative laboratory indicators and postoperative complications.AIM To explore the predictive value of preoperative blood markers for IAI after radical resection of CRC.METHODS The data of 80 patients who underwent radical resection of CRC in the Anorectal Surgery Department of Suzhou Hospital affiliated with Anhui Medical University were analyzed.These patients were categorized into IAI(n=15)and non-IAI groups(n=65)based on whether IAI occurred.Influencing factors were compared;general data and laboratory indices of both groups were identified.The relationship between the indicators was assessed.Further,a nomogram prediction model was developed and evaluated;its utility and clinical applic-ability were assessed.RESULTS The risk factors for IAI after radical resection of CRC were neutrophil-lymphocyte ratio(NLR),platelet-lymphocyte ratio(PLR),systemic immune-inflammation index(SII),and carcinoembryonic antigen(CEA)levels.NLR was correlated with PLR and SII(r=0.604,0.925,and 0.305,respectively),while PLR was correlated with SII(r=0.787).The nomogram prediction model demonstrated an area under the curve of 0.968[95%confidence interval(CI):0.948-0.988]in the training set(n=60)and 0.926(95%CI:0.906-0.980)in the validation set(n=20).The average absolute errors of the calibration curves for the training and validation sets were 0.032 and 0.048,respectively,indicating a good model fit.The decision curve analysis curves demonstrated high net income above the 5%threshold,indicating the clinical practicality of the model.CONCLUSION The nomogram model constructed using NLR,PLR,SII,and CEA levels had good accur

关键词： Radical resection of colorectal cancer Inflammatory factors Intra-abdominal infection Predictive model Blood markers

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Even Search in a Promising Region for Constrained Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 474-486页

作者： Fei ming Wenyin Gong Yaochu jin School of Computer Science China University of GeosciencesWuhan 430074China IEEE Faculty of Technology Bielefeld UniversityNorth Rhine-Westphalia 33619Germany School of Engineering Westlake UniversityHangzhou 310030China

In recent years, a large number of approaches to constrained multi-objective optimization problems(CMOPs) have been proposed, focusing on developing tweaked strategies and techniques for handling constraints. However, an overly finetuned strategy or technique might overfit some problem types,resulting in a lack of versatility. In this article, we propose a generic search strategy that performs an even search in a promising region. The promising region, determined by obtained feasible non-dominated solutions, possesses two general properties.First, the constrained Pareto front(CPF) is included in the promising region. Second, as the number of feasible solutions increases or the convergence performance(i.e., approximation to the CPF) of these solutions improves, the promising region shrinks. Then we develop a new strategy named even search,which utilizes the non-dominated solutions to accelerate convergence and escape from local optima, and the feasible solutions under a constraint relaxation condition to exploit and detect feasible regions. Finally, a diversity measure is adopted to make sure that the individuals in the population evenly cover the valuable areas in the promising region. Experimental results on 45 instances from four benchmark test suites and 14 real-world CMOPs have demonstrated that searching evenly in the promising region can achieve competitive performance and excellent versatility compared to 11 most state-of-the-art methods tailored for CMOPs.

关键词： Constrained multi-objective optimization even search evolutionary algorithms promising region real-world problems

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Development and validation of a machine learning-based early prediction model for massive intraoperative bleeding in patients with primary hepatic malignancies

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World Journal of Gastrointestinal Oncology 2024年第1期16卷 90-101页

作者： jin Li yu-ming Jia Zhi-Lei Zhang Cheng-yu Liu Zhan-Wu Jiang Zhi-Wei Hao Li Peng Department of Hepatological Surgery The Fourth Hospital of Hebei Medical UniversityShijiazhuang 050011Hebei ProvinceChina Department of General Surgery II Baoding First Central HospitalBaoding 071000Hebei ProvinceChina

BACKGROUND Surgical resection remains the primary treatment for hepatic malignancies,and intraoperative bleeding is associated with a significantly increased risk of death.Therefore,accurate prediction of intraoperative bleeding risk in patients with hepatic malignancies is essential to preventing bleeding in advance and providing safer and more effective treatment.AIM To develop a predictive model for intraoperative bleeding in primary hepatic malignancy patients for improving surgical planning and outcomes.METHODS The retrospective analysis enrolled patients diagnosed with primary hepatic malignancies who underwent surgery at the Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University between 2010 and 2020.Logistic regression analysis was performed to identify potential risk factors for intraoperative bleeding.A prediction model was developed using Python programming language,and its accuracy was evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS Among 406 primary liver cancer patients,16.0%(65/406)suffered massive intraoperative bleeding.Logistic regression analysis identified four variables as associated with intraoperative bleeding in these patients:ascites[odds ratio(OR):22.839;P<0.05],history of alcohol consumption(OR:2.950;P<0.015),TNM staging(OR:2.441;P<0.001),and albumin-bilirubin score(OR:2.361;P<0.001).These variables were used to construct the prediction model.The 406 patients were randomly assigned to a training set(70%)and a prediction set(30%).The area under the ROC curve values for the model’s ability to predict intraoperative bleeding were 0.844 in the training set and 0.80 in the prediction set.CONCLUSION The developed and validated model predicts significant intraoperative blood loss in primary hepatic malignancies using four preoperative clinical factors by considering four preoperative clinical factors:ascites,history of alcohol consumption,TNM staging,and albumin-bilirubin score.Consequently,this model holds promise for enhancing individ

关键词： Primary liver cancer Intraoperative bleeding Machine learning Model

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Self-adaptive gas flow and phase change behaviors during hydrate exploitation by alternate injection of N2 and CO2

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Petroleum Science 2024年第3期21卷 2120-2129页

作者： Bo-Jian Cao Yi-Fei Sun Hong-Nan Chen jin-Rong Zhong ming-Long Wang ming Wang Chang-yu Sun Guang-jin Chen State Key Laboratory of Heavy Oil Processing China University of Petroleum School of Chemistry and Chemical Engineering Changsha University of Science & Technology

Since hydrate resources play a part of the stratigraphic framework structure in sediments,establishing a safe and economic method for hydrates exploitation remains the primary challenge to this day.Among the proposed methods,the spontaneous displacement of CH4from hydrate cages by CO2seems to be a perfect mechanism to address gas production and CO2storage,especially in today's strong demand for carbon reduction and replacing clean energy.After extensive lab researches,in the past decade,injecting a mixture of CO2and small molecule gas has become a key means to enhance displacement efficiency and has great potential for application.However,there is a lack of in-depth research on gas flow in the reservoir,while the injected gas always passes through low-saturated hydrate areas with high permeability and then occurs gas channel in a short term,finally resulting in the decreases in gas production efficiency and produced gas quality.Therefore,we explored a new injection-production mode of alternate injection of N2and CO2in order to fully coordinate the advantages of N2in enhanced hydrate decomposition and CO2in solid storage and heat compensation.These alternate "taking" and "storing" processes perfectly repair the problem of the gas channel,achieving self-regulation effect of CH4recovery and CO2storage.The 3-D experimental results show that compared to the mixed gas injection,CH4recovery is increased by>50% and CO2storage is increased by>70%.Additionally,this alternate injection mode presented a better performance in CH4concentration of produced gas and showed outstanding N2utilization efficiency.Further,we analyzed its self-adaptive gas flow mechanism and proposed an application model of "one injection and multiple production".We look forward to this study accelerating the application of CO2-CH4replacement technology.

关键词： Hydrate Replacement CH 4 recovery CO 2 storage Reservoir remediation

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Oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions via Prufer transformation

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 191-200页

作者： LI Zhi-yu LI Kun CAI jin-ming QIN Jian-fang ZHENG Zhao-wen School of Mathematical Sciences Qufu Normal UniversityQufu 273165China College of Mathematics and Systems Science Guangdong Polytechnic Normal UniversityGuangzhou 510665China

A class of Sturm-Liouville problems with discontinuity is studied in this paper.The oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions are obtained.The main method used in this paper is based on Prufer transformation,which is different from the classical ones.Moreover,we give two examples to verify our main results.

关键词： Sturm-Liouville problem interface condition oscillatory solution

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Kinesin 26B modulates M2 polarization of macrophage by activating cancer-associated fibroblasts to aggravate gastric cancer occurrence and metastasis

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World Journal of Gastroenterology 2024年第20期30卷 2689-2708页

作者： Lian-Meng Huang ming-jin Zhang Department of General Surgery The 901st Hospital of PLAHefei 230031Anhui ProvinceChina

BACKGROUND The regulatory effects of KIF26B on gastric cancer(GC)have been confirmed,but the specific mechanism still needs further exploration.Pan-cancer analysis shows that the KIF26B expression is highly related to immune infiltration of cancerassociated fibroblasts(CAFs),and CAFs promote macrophage M2 polarization and affect cancers’progression.AIM To investigate the regulatory functions of KIF26B on immune and metastasis of GC.METHODS We analyzed genes’mRNA levels by quantitative real-time polymerase chain reaction.Expression levels of target proteins were detected by immunohistochemistry,ELISA,and Western blotting.We injected AGS cells into nude mice for the establishment of a xenograft tumor model and observed the occurrence and metastasis of GC.The degree of inflammatory infiltration in pulmonary nodes was observed through hematoxylin-eosin staining.Transwell and wound healing assays were performed for the evaluation of cell invasion and migration ability.Tube formation assay was used for detecting angiogenesis.M2-polarized macrophages were estimated by immunofluorescence and flow cytometry.RESULTS KIF26B was significantly overexpressed in cells and tissues of GC,and the higher expression of KIF26B was related to GC metastasis and prognosis.According to in vivo experiments,KIF26B promoted tumor formation and metastasis of GC.KIF26B expression was positively associated with CAFs’degree of infiltration.Moreover,CAFs could regulate M2-type polarization of macrophages,affecting GC cells’migration,angiogenesis,invasion,and epithelial-mesenchymal transition process.CONCLUSION KIF26B regulated M2 polarization of macrophage through activating CAFs,regulating the occurrence and metastasis of GC.

关键词： metastasis invasion macrophage

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Visible Light-Induced[3+2]Annulation Reaction of Alkenes with Vinyl Azides:Direct Synthesis of Functionalized Pyrroles

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Chinese Journal of Chemistry 2024年第2期42卷 151-156页

作者： ming Yang Xin-yu Wang Jie Wang yu-Long Zhao Jilin Province Key Laboratory of Organic Functional Molecular Design&Synthesis Faculty of ChemistryNortheast Normal UniversityChangchunJilin 130024China

A photocatalytic[3+2]annulation of alkenes with vinyl azides was developed under irradiation by visible light in the presence of organic dye photocatalysts.Broad substrate scope and high functional group tolerance were demonstrated by more than 50 examples.The reaction provides a novel and efficient method for the synthesis of polyfunctionalized pyrroles under very mild metal-free conditions without other additives.

关键词： Photocatalysis Vinyl azides Alkenes Pyrroles Annulation Radical reactions

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Global Zero-relaxation Limit Problem of the Electro-diffusion Model Arising in Electro-Hydrodynamics

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 241-268页

作者： ming-hua Yang Si-ming Huang jin-yi Sun Department of Mathematics Jiangxi University of Finance and EconomicsNanchang330032China School of Public Administration Guangdong University of Foreign StudiesGuangzhou510006China College of Mathematics and Statistics Northwest Normal UniversityLanzhou730070China

In this paper,we study a global zero-relaxation limit problem of the electro-diffusion model arising in electro-hydrodynamics which is the coupled Planck-Nernst-Poisson and Navier-Stokes equations.That is,the paper deals with a singular limit problem of{u^(∈)_(t)+u^(∈)·▽u^(∈)-Δu^(∈)+▽P^(∈)=Δφ^(∈)▽φ^(∈),in R^(3)×(0,∞),▽·u^(∈)=0,in R^(3)×(0,∞),n^(∈)_(t)+u^(∈)·▽n^(∈)-Δn^(∈)=-▽·(n^(∈)▽φ^(∈)),in R^(3)×(0,∞),ct+u^(∈)·▽c^(∈)-Δc^(∈)=▽·(c^(∈)▽φ^(∈)),in R^(3)×(0,∞),∈^(-1)φ^(∈)_(t)=Δφ^(∈)-n^(∈)+c^(∈),in R^(3)×(0,∞),(u^(∈),n^(∈),c^(∈),φ^(∈))|t=0=(u0,n0,c0,φ0),in R^(3) involving with a positive,large parameter^(∈).The present work show a case that(u^(∈),n^(∈),c^(∈))stabilizes to(u^(∞),n∞,c∞):=(u,n,c)uniformly with respect to the time variable as^(∈)→+∞with respect to the strong topology in a certain Fourier-Herz space.

关键词： fourier-Herz space littlewood-Paley decomposition stability limit dissipative system

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Constrained Multi-Objective Optimization With Deep Reinforcement Learning Assisted Operator Selection

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 919-931页

作者： Fei ming Wenyin Gong Ling Wang Yaochu jin the School of Computer Science China University of GeosciencesWuhan 430074China the Department of Automation Tsinghua UniversityBeijing 100084China the Faculty of Technology Bielefeld UniversityNorth Rhine-Westphalia33619 BielefeldGermany

Solving constrained multi-objective optimization problems with evolutionary algorithms has attracted considerable attention.Various constrained multi-objective optimization evolutionary algorithms(CMOEAs)have been developed with the use of different algorithmic strategies,evolutionary operators,and constraint-handling techniques.The performance of CMOEAs may be heavily dependent on the operators used,however,it is usually difficult to select suitable operators for the problem at hand.Hence,improving operator selection is promising and necessary for CMOEAs.This work proposes an online operator selection framework assisted by Deep Reinforcement Learning.The dynamics of the population,including convergence,diversity,and feasibility,are regarded as the state;the candidate operators are considered as actions;and the improvement of the population state is treated as the reward.By using a Q-network to learn a policy to estimate the Q-values of all actions,the proposed approach can adaptively select an operator that maximizes the improvement of the population according to the current state and thereby improve the algorithmic performance.The framework is embedded into four popular CMOEAs and assessed on 42 benchmark problems.The experimental results reveal that the proposed Deep Reinforcement Learning-assisted operator selection significantly improves the performance of these CMOEAs and the resulting algorithm obtains better versatility compared to nine state-of-the-art CMOEAs.

关键词： Constrained multi-objective optimization deep Qlearning deep reinforcement learning(DRL) evolutionary algorithms evolutionary operator selection

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