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Partial Linear Model Averaging Prediction for Longitudinal Data

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Journal of Systems Science & Complexity 2024年第2期37卷 863-885页

作者： LI Na fei yu ZHANG Xinyu Faculty of Science Kunming University of Science and TechnologyKunming 650500China School of Statistics and Mathematics Yunnan University of Finance and EconomicsKunming 650221China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China

Prediction plays an important role in data analysis.Model averaging method generally provides better prediction than using any of its components.Even though model averaging has been extensively investigated under independent errors,few authors have considered model averaging for semiparametric models with correlated errors.In this paper,the authors offer an optimal model averaging method to improve the prediction in partially linear model for longitudinal data.The model averaging weights are obtained by minimizing criterion,which is an unbiased estimator of the expected in-sample squared error loss plus a constant.Asymptotic properties,including asymptotic optimality and consistency of averaging weights,are established under two scenarios:(i)All candidate models are misspecified;(ii)Correct models are available in the candidate set.Simulation studies and an empirical example show that the promise of the proposed procedure over other competitive methods.

关键词： Asymptotic optimality longitudinal data model averaging estimator partially linear model prediction

A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

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Petroleum Science 2024年第1期21卷 535-550页

作者： Song Deng Hao-yu Pan Hai-Ge Wang Shou-Kun Xu Xiao-peng Yan Chao-Wei Li Ming-Guo peng Hao-Ping peng Lin Shi Meng Cui fei Zhao School of Petroleum and Natural Gas Engineering Changzhou UniversityChangzhou213164JiangsuChina Tubular Goods Research Institute of CNPC Beijing102249China CNPC Engineering Technology R&D Company Limited Beijing102206China

Pore pressure is essential data in drilling design,and its accurate prediction is necessary to ensure drilling safety and improve drilling efficiency.Traditional methods for predicting pore pressure are limited when forming particular structures and lithology.In this paper,a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore pressure.This study collects data from three wells.Well 1 had 881 data sets for model training,and Wells 2 and 3 had 538 and 464 data sets for model testing.In this paper,support vector machine(SVM),random forest(RF),extreme gradient boosting(XGB),and multilayer perceptron(MLP)are selected as the machine learning algorithms for pore pressure modeling.In addition,this paper uses the grey wolf optimization(GWO)algorithm,particle swarm optimization(PSO)algorithm,sparrow search algorithm(SSA),and bat algorithm(BA)to establish a hybrid machine learning optimization algorithm,and proposes an improved grey wolf optimization(IGWO)algorithm.The IGWO-MLP model obtained the minimum root mean square error(RMSE)by using the 5-fold cross-validation method for the training data.For the pore pressure data in Well 2 and Well 3,the coefficients of determination(R^(2))of SVM,RF,XGB,and MLP are 0.9930 and 0.9446,0.9943 and 0.9472,0.9945 and 0.9488,0.9949 and 0.9574.MLP achieves optimal performance on both training and test data,and the MLP model shows a high degree of generalization.It indicates that the IGWO-MLP is an excellent predictor of pore pressure and can be used to predict pore pressure.

关键词： Pore pressure Grey wolf optimization Multilayer perceptron Effective stress Machine learning

Deep Reinforcement Learning Based Green Resource Allocation Mechanism in Mobile Edge Network for Ubiquitous Power IoT

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Deep Reinforcement Learning Based Green Resource Allocation ...

MACS-W:A modified optical clearing agent for imaging 3D cell cultures

作者： Mo YANG Xiu-li HUANG Wei-wei MIU peng-fei yu Wei LI Ru-xia YANG State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Global Energy Interconnection Research Institute Co. Ltd Communication branch State Grid Jiangsu Electric Power Co. Ltd

Ubiquitous Power IoT is an important part of smart grid or energy internet. Edge network is a key component of smart grid and future energy Internet. IoT contains various terminals, diverse access networks and equipment. The allocation of energy-efficient resources under QoS guarantee is an effective means to ensure the reliable operation of the network. Due to the heterogeneity of the services carried and in order to reduce business operation risks and impact on the power grid, it is necessary to provide highly reliable resource allocation method to the ubiquitous power IoT business for the energy Internet. Edge network can reduce end-to-end latency and reduce backhaul link traffic. However, mobile edge networks moving the function of storage and computing down to the edge nodes of network, which makes resource management more complex. Moreover, the computing resources in the edge network is limited and the effect to the ecological environment and economic cost should also be considered. So how to allocate resources such as bandwidth and power more effectively while meeting the needs of users becomes an important issue. Even if the Deep Reinforcement Learning（DRL） algorithm has been used to a lot of the work which are correlated to edge networks, there lacks the applications for green resource allocation. In this paper, a mechanism based on Deep Reinforcement Learning（DRL） for the resource allocation problem is proposed oriented to edge networks. The mechanism aims at how to allocate resources more efficiently and energy-saving while satisfying the requirements of each user. The simulation results show that the energy efficiency value could be obtained when the algorithm converges and stabilizes. The Energy Efficiency（EE） of the proposed mechanism and the productiveness in satisfying user requirements and implementing green resource allocation are validated.

关键词： Deep Reinforcement Learning Green Resource Allocation Mobile Edge Network

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Journal of Innovative Optical Health Sciences 2024年第2期17卷 24-34页

作者： Xiang Zhong Chao Gao Hui Li yuening He peng fei Zaozao Chen Zhongze Gu Dan Zhu Tingting yu Britton Chance Center for Biomedical Photonics-MoE Key Laboratory for Biomedical Photonics Huazhong University of Science and Technology Wuhan Hubei 430074P.R.China Wuhan National Laboratory for Optoelectronics-Advanced Biomedical Imaging Facility Huazhong University of Science and Technology Wuhan Hubei 430074P.R.China School of Optical and Electronic Infrmation Huazhong University of Science and Technology Wuhan Hubei 430074P.R.China State Key Laboratory of Bioelectronics School of Biological Science and Medical Engineering Southeast University NanjingJiangsu 210096P.R.China Institute of Biomaterials and Medical Devices Southeast University Suzhou Jiangsu 215163P.R.China

Three-dimensional(3D)cell cultures have contributed to a variety of biological research fields by filling the gap between monolayers and animal models.The modern optical sectioning microscopic methods make it possible to probe the complexity of 3D cell cultures but are limited by the inherent opaqueness.While tissue optical clearing methods have emerged as powerful tools for investigating whole-mount tissues in 3D,they often have limitations,such as being too harsh for fragile 3D cell cultures,requiring complex handling protocols,or inducing tissue deformation with shrinkage or expansion.To address this issue,we proposed a modified optical clearing method for 3D cell cultures,called MACS-W,which is simple,highly efficient,and morphology-preserving.In our evaluation of MACS-W,we found that it exhibits excellent clearing capability in just 10 min,with minimal deformation,and helps drug evaluation on tumor spheroids.In summary,MACS-W is a fast,minimally-deformative and fluorescence compatible clearing method that has the potential to be widely used in the studies of 3D cell cultures.

关键词： Tissue optical clearing 3D cell cultures imaging

Colonoscopy plays an important role in detecting colorectal neoplasms in patients with gastric neoplasms

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World Journal of Gastrointestinal Oncology 2024年第1期16卷 133-143页

作者： Xu-Rui Liu Ze-Lin Wen fei Liu Zi-Wei Li Xiao-yu Liu Wei Zhang Dong peng Department of Gastrointestinal Surgery The First Affiliated Hospital of Chongqing Medical UniversityChongqing 400016China Department of Gastrointestinal Surgery Yongchuan Hospital of Chongqing Medical UniversityChongqing 402160China

BACKGROUND Gastric cancer(GC)and colorectal cancer(CRC)are the fifth and third most common cancer worldwide,respectively.Nowadays,GC is reported to have a potential predictive value for CRC,especially for advanced CRC.AIM To evaluate the necessity of colonoscopy for gastric neoplasm(GN)patients.METHODS Four databases,including PubMed,EMBASE,the Cochrane Library,and Ovid,were used to perform the search strategy on May 2,2023.The prevalence of colorectal neoplasms(CRN)and baseline characteristics were compared between the neoplasm group and the control group.Continuous variables are expressed as the mean difference and standard deviation.Relationships of categorical variables in the two groups are expressed as odds ratios(OR)and 95%confidence intervals(95%CIs).Subgroup analysis according to different kinds of GNs was conducted for more in-depth analysis.The results of this study are represented by forest plots.Publication bias was evaluated by a funnel plot.All data analyses were performed by STATA SE 16.0 software.RESULTS A total of 3018 patients with GNs and 3905 healthy controls(age and sex matched)were enrolled for analysis.After comparing the prevalence of CRNs between the two groups,CRNs were detected significantly more frequently in GN patients than in controls(OR=1.69,95%CI=1.28 to 2.23,I^(2)=85.12%,P=0.00),especially in patients with GC(OR=1.80,95%CI=1.49 to 2.18,I^(2)=25.55%,P<0.1).Moreover,other risk factors including age(OR=1.08,95%CI=1.00 to 1.17,I^(2)=90.13%,P=0.00)and male sex(OR=2.31,95%CI=1.26 to 4.22,I^(2)=87.35%,P=0.00),were related to the prevalence of CRNs.For patients in the GN group,body mass index(BMI,OR=0.88,95%CI=0.80 to 0.98,I^(2)=0.00%,P=0.92)and smoking(OR=1.03,95%CI=1.01 to 1.05,I^(2)=0.00%,P=0.57)were protective and risk factors for CRNs,respectively.CONCLUSION Patients are recommended to undergo colonoscopy when diagnosed with GNs,especially GC patients with a low BMI and a history of smoking.

关键词： Gastric neoplasm Gastric cancer Colorectal neoplasm Colonoscopy

Changes of coastline and tidal flat and its implication for ecological protection under human activities: Take China’s Bohai Bay as an example

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China Geology 2024年第1期7卷 26-35页

作者： Yong Li Ming-zheng Wen Heng yu peng Yang fei-cui Wang Fu Wang Tianjin Center China Geological SurveyMinistry of Natural ResourcesTianjin 300170China Key Laboratory of Coast Geo-environment China Geological SurveyMinistry of Natural ResourcesTianjin 300170China Tianjin Key Laboratory of Coast Geological Processes and Environmental Safety Tianjin 300170China Hebei University of Environmental Engineering Qinhuangdao 066102China Hebei Engineering Research Center for Ecological Restoration of seaward Rivers and Coastal Waters Qinhuangdao 066102China Department of Earth and Environment Boston UniversityBoston 02215USA

The change processes and trends of shoreline and tidal flat forced by human activities are essential issues for the sustainability of coastal area,which is also of great significance for understanding coastal ecological environment changes and even global changes.Based on field measurements,combined with Linear Regression(LR)model and Inverse Distance Weighing(IDW)method,this paper presents detailed analysis on the change history and trend of the shoreline and tidal flat in Bohai Bay.The shoreline faces a high erosion chance under the action of natural factors,while the tidal flat faces a different erosion and deposition patterns in Bohai Bay due to the impact of human activities.The implication of change rule for ecological protection and recovery is also discussed.Measures should be taken to protect the coastal ecological environment.The models used in this paper show a high correlation coefficient between observed and modeling data,which means that this method can be used to predict the changing trend of shoreline and tidal flat.The research results of present study can provide scientific supports for future coastal protection and management.

关键词： Shoreline Tidal flat Erosion deposition patterns Changing trend Ecological protection Human activity Linear regression model Inverse distance weighing method Prediction Bohai Bay

Molecular surface functionalization of In_(2)O_(3) to tune interfacial microenvironment for enhanced catalytic performance of CO_(2) electroreduction

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Nano Research 2024年第3期17卷 1242-1250页

作者： Suwen WangQiang GaoCui Xu Shuai Jiang Mengyang Zhang Xianjun Yin Hui-Qing peng Bin Liu yu-fei Song State Key Laboratory of Chemical Resource Engineering Beijing Advanced Innovation Center for Soft Matter Science and EngineeringCollege of ChemistryBeijing University of Chemical TechnologyBeijing 100029China

Indium-based materials(e.g.,In_(2)O_(3))are a class of promising non-noble metal-based catalysts for electroreduction of carbon dioxide(CO_(2)).However,competitive hydrogen reduction reaction(HER)on indium-based catalysts hampers CO_(2) reduction reaction(CO_(2)RR)process.We herein tune the interfacial microenvironment of In_(2)O_(3) through chemical graft of alkyl phosphoric acid molecules using a facile solution-processed strategy for the first time,which is distinguished from other researches that tailor intrinsic activity of In_(2)O_(3) themselves.The surface functionalization of alkyl phosphoric acids over In_(2)O_(3) is demonstrated to remarkably boost CO_(2) conversion.For example,octadecylphosphonic acid modified In_(2)O_(3) exhibits Faraday efficiency for H_(2) H_(2) H_(2)(FE)of as low as 6.6%and FEHCOOH of 86.5%at-0.67 V vs.RHE,which are far superior to parent In_(2)O_(3) counterparts(FE of 24.0%and FEHCOOH of 63.1%).Moreover,the enhancing effect of alkyl phosphoric acid functionalization is found to be closely related to the length of alkyl chains.By virtue of comprehensive experimental characterizations and molecular dynamics simulations,it is revealed that the modification of alkyl phosphoric acids significantly alters the interface microenvironment of the electrocatalyst,which changes the electrocatalyst surface from hydrophilic and aerophobic to hydrophobic and aerophilic.In this case,the water molecules are pushed away and more CO_(2) molecules are trapped,increasing local CO_(2) concentration at In_(2)O_(3) active sites,thus leading to the significantly enhanced CO_(2)RR and suppressed HER.This work highlights the importance of regulating the interfacial microenvironment of inorganic catalysts by molecular surface functionalization as a means for promoting the electrochemical performance in electrosynthesis and beyond.

关键词： carbon dioxide(CO_(2))electroreduction interfacial microenvironment molecular surface functionalization In_(2)O_(3)catalyst water and CO_(2)diffusion

Kinetic-Thermodynamic Promotion Engineering toward High-Density Hierarchical and Zn-Doping Activity-Enhancing ZnNiO@CF for High-Capacity Desalination

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Nano-Micro Letters 2024年第8期16卷 35-50页

作者： Jie Ma Siyang Xing Yabo Wang Jinhu Yang fei yu College of Marine Ecology and Environment Shanghai Ocean University201306 ShanghaiPeople’s Republic of China School of Civil Engineering Kashi University844000 KashiPeople’s Republic of China Research Center for Environmental Functional Materials College of Environmental Science and EngineeringTongji University1239 Siping Road200092 ShanghaiPeople’s Republic of China School of Chemical Science and Engineering Tongji University1239 Siping Road200092 ShanghaiPeople’s Republic of China Department of Energy Environmental&Chemical EngineeringWashington University in St.LouisSt.LouisMO 63130USA

Despite the promising potential of transition metal oxides(TMOs)as capacitive deionization(CDI)electrodes,the actual capacity of TMOs electrodes for sodium storage is significantly lower than the theoretical capacity,posing a major obstacle.Herein,we prepared the kinetically favorable Zn_(x)Ni_(1−x)O electrode in situ growth on carbon felt(Zn_(x)Ni_(1−x)O@CF)through constraining the rate of OH^(−)generation in the hydrothermal method.Zn_(x)Ni_(1−x)O@CF exhibited a high-density hierarchical nanosheet structure with three-dimensional open pores,benefitting the ion transport/electron transfer.And tuning the moderate amount of redox-inert Zn-doping can enhance surface electroactive sites,actual activity of redox-active Ni species,and lower adsorption energy,promoting the adsorption kinetic and thermodynamic of the Zn_(0.2)Ni_(0.8)O@CF.Benefitting from the kinetic-thermodynamic facilitation mechanism,Zn_(0.2)Ni_(0.8)O@CF achieved ultrahigh desalination capacity(128.9 mgNaCl g^(-1)),ultra-low energy consumption(0.164 kW h kgNaCl^(-1)),high salt removal rate(1.21 mgNaCl g^(-1) min^(-1)),and good cyclability.The thermodynamic facilitation and Na^(+)intercalation mechanism of Zn_(0.2)Ni_(0.8)O@CF are identified by the density functional theory calculations and electrochemical quartz crystal microbalance with dissipation monitoring,respectively.This research provides new insights into controlling electrochemically favorable morphology and demonstrates that Zn-doping,which is redox-inert,is essential for enhancing the electrochemical performance of CDI electrodes.

关键词： Zinc-nickel metal oxide High-density hierarchical Capacitive deionization Zinc-doping

Homer1a reduces inflammatory response after retinal ischemia/reperfusion injury

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Neural Regeneration Research 2024年第7期19卷 1608-1617页

作者： Yanan Dou Xiaowei fei Xin He yu Huan Jialiang Wei Xiuquan Wu Weihao Lyu Zhou fei Xia Li fei fei Department of Neurosurgery Xijing HospitalAir Force Military Medical UniversityXi’anShaanxi ProvinceChina Department of Ophthalmology Xijing HospitalAir Force Military Medical UniversityXi’anShaanxi ProvinceChina

Elevated intraocular pressure(IOP)is one of the causes of retinal ischemia/reperfusion injury,which results in NRP3 inflammasome activation and leads to visual damage.Homerla is repo rted to play a protective role in neuroinflammation in the cerebrum.However,the effects of Homerla on NLRP3inflammasomes in retinal ischemia/reperfusion injury caused by elevated IOP remain unknown.In our study,animal models we re constructed using C57BL/6J and Homer1^(flox/-)/Homerla^(+/-)/Nestin-Cre^(+/-)mice with elevated IOP-induced retinal ischemia/repe rfusion injury.For in vitro expe riments,the oxygen-glucose deprivation/repe rfusion injury model was constructed with M uller cells.We found that Homerla ove rexpression amelio rated the decreases in retinal thickness and Muller cell viability after ischemia/reperfusion injury.Furthermore,Homerla knockdown promoted NF-κB P65^(Ser536)activation via caspase-8,NF-κB P65 nuclear translocation,NLRP3 inflammasome formation,and the production and processing of interleukin-1βand inte rleukin-18.The opposite results we re observed with Homerla ove rexpression.Finally,the combined administration of Homerla protein and JSH-23 significantly inhibited the reduction in retinal thickness in Homer1^(flox/-)Homer1a^(+/-)/Nestin-Cre^(+/-)mice and apoptosis in M uller cells after ischemia/reperfusion injury.Taken together,these studies demonstrate that Homer1a exerts protective effects on retinal tissue and M uller cells via the caspase-8/NF-KB P65/NLRP3 pathway after I/R injury.

关键词： caspase-8 Homer1a interleukin-18 interleukin-1β intraocular pressure ischemia/reperfusion injury JSH-23 Müller cells NLRP3 nuclear factor-kB p65 retina