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Genetic Variations and Nonalcoholic Fatty Liver Disease:Field Synopsis,Systematic Meta-Analysis,and Epidemiological Evidence

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Biomedical and Environmental Sciences 2024年第7期37卷 762-773页

作者： Yamei Li Xiang Xiao Jie Wang Yixu Liu Xiongfeng Pan Haibin Yu Jiayou Luo Miyang Luo department of Epidemiology and health statistics School of Public HealthUniversity of South ChinaHengyang 421001HunanChina department of Maternal and Child health Xiangya School of Public HealthCentral South UniversityChangsha 410008HunanChina Supervision and Inspection department of Shanghai healthcare Security Bureau Shanghai 200003China department of Epidemiology and health statistics Xiangya School of Public HealthCentral South UniversityChangsha 410008HunanChina

Objective To systematically summarize the published literature on the genetic variants associated with nonalcoholic fatty liver disease(NAFLD).Methods Literature from Web of Science,PubMed,and Embase between January 1980 and September 2022 was systematically ***-analyses of the genetic variants were conducted using at least five data *** epidemiologic credibility of the significant associations was graded using the Venice *** Based on literature screening,399 eligible studies were included,comprising 381 candidate gene association,16 genome-wide association,and 2 whole-exome sequencing *** identified 465 genetic variants in 173 genes in candidate gene association studies,and 25 genetic variants in 17 genes were included in the *** meta-analysis identified 11 variants in 10 genes that were significantly associated with NAFLD,with cumulative epidemiological evidence of an association graded as strong for two variants in two genes(HFE,TNF),moderate for four variants in three genes(TM6SF2,GCKR,and ADIPOQ),and weak for five variants in five genes(MBOAT7,PEMT,PNPLA3,LEPR,and MTHFR).Conclusion This study identified six variants in five genes that had moderate to strong evidence of an association with NAFLD,which may help understand the genetic architecture of NAFLD risk.

关键词： Nonalcoholic fatty liver disease Genetic association study Genetic variant Systematic review Meta-analysis

Optimal Model Average Prediction in Orthogonal Kriging Models

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Journal of Systems Science & Complexity 2024年第3期37卷 1080-1099页

作者： WANG Jun HE Jiabei LIANG Hua LI Xinmin School of Mathematics and statistics Qingdao UniversityQingdao 266071China department of statistics George Washington UniversityWashington DC 20052USA

The main objective of this paper is to consider model averaging methods for kriging *** paper proposes a Mallows model averaging procedure for the orthogonal kriging model and demonstrate the asymptotic optimality of the model averaging estimators in terms of mean square *** studies are conducted to evaluate the performance of the proposed method and compare it with the competitors to demonstrate its *** authors also analyse a real dataset for an illustration.

关键词： Asymptotic optimality Mallows criterion optimal model averaging orthogonal kriging model

The Lambert-G Family:Properties,Inference,and Applications

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 513-536页

作者： Jamal N.Al Abbasi Ahmed Z.Afify Badr Alnssyan Mustafa S.Shama accounting department Ashur UniversityBaghdad10011Iraq department of statistics Mathematics and InsuranceBenha UniversityBenha13511Egypt department of Management Information Systems and Production Management College of Business and EconomicsQassim UniversityBuraydah51452Saudi Arabia department of Basic Sciences Common First Year(CFY)King Saud UniversityRiyadh11362Saudi Arabia department of Mathematics and statistics Osim Higher Institute of Administrative ScienceOsim12961Egypt

This study proposes a new flexible family of distributions called the Lambert-G *** Lambert family is very flexible and exhibits desirable *** three-parameter special sub-models provide all significantmonotonic and non-monotonic failure rates.A special sub-model of the Lambert family called the Lambert-Lomax(LL)distribution is *** expressions for the LL statistical properties are *** of the LL distribution are addressed mathematically based on its hazard *** estimation of the LL parameters is discussed using six estimation *** performance of this estimation method is explored through simulation *** usefulness and flexibility of the LL distribution are demonstrated empirically using two real-life data *** LL model better fits the exponentiated Lomax,inverse power Lomax,Lomax-Rayleigh,power Lomax,and Lomax distributions.

关键词： Lambert function Lomax distribution maximum likelihood hazard function statistical model simulation

Construction of Optimal Mixed-Level Uniform Designs

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Journal of Systems Science & Complexity 2024年第2期37卷 841-862页

作者： CHATTERJEE Kashinath LIU Min-Qian QIN Hong YANG Liuqing department of Population health Sciences Division of Biostatistics and Data ScienceAugusta UniversityGA 30912USA NITFID LPMC&KLMDASRSchool of Statistics and Data ScienceNankai UniversityTianjin 300071China School of statistics and Mathematics Zhongnan University of Economics and LawWuhan 430073China

The theory of uniform design has received increasing interest because of its wide application in the field of computer *** generalized discrete discrepancy is proposed to evaluate the uniformity of the mixed-level factorial *** this paper,the authors give a lower bound of the generalized discrete discrepancy and provide some construction methods of optimal mixed-level uniform designs which can achieve this lower *** methods are all deterministic construction methods which can avoid the complexity of stochastic *** saturated mixed-level uniform designs and supersaturated mixed-level uniform designs can be obtained with these ***,the resulting designs are also χ^(2)-optimal and minimum moment aberration designs.

关键词： Generalized discrete discrepancy Hadamard matrix mixed-level design orthogonal array supersaturated design

Character Sheaves for Classical Graded Lie Algebras

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Acta Mathematica Sinica,English Series 2024年第3期40卷 870-884页

作者： Ting XUE School of Mathematics and statistics University of MelbourneVIC 3010Australia department of Mathematics and statistics University of HelsinkiHelsinki 00014Finland

In this note we study character sheaves for graded Lie algebras arising from inner automorphisms of special linear groups and Vinberg’s type Ⅱ classical graded Lie algebras.

关键词： Graded Lie algebras character sheaves Fourier transform nilpotent orbits

Double Moving Extremes Ranked Set Sampling Design

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Acta Mathematicae Applicatae Sinica 2024年第1期40卷 75-90页

作者： Meng Chen Wang-xue Chen Rui Yang department of Mathematics and statistics Jishou UniversityJishou416000China

The traditional simple random sampling(SRS)design method is inefficient in many *** proposed some new designs to increase *** this paper,as a variation of moving extremes ranked set sampling(MERSS),double MERSS(DMERSS)is proposed and its properties for estimating the population mean are *** turns out that,when the underlying distribution is symmetric,DMERSS gives unbiased estimators of the population ***,it is found that DMERSS is more efficient than the SRS and MERSS methods for usual symmetric distributions(normal and uniform).For asymmetric distributions considered in this study,the DMERSS has a small bias and it is more efficient than SRS for usual asymmetric distribution(exponential)for small sample sizes.

关键词： double moving extremes ranked set sampling symmetric distribution efficiency

Applying Machine Learning Approach to Explore Childhood Circumstances and Self-Rated health in Old Age-China and the US,2020-2021

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China CDC weekly 2024年第11期6卷 213-218,I0008-I0013页

作者： Shutong Huo Derek Feng Thomas M.Gill Xi Chen department of health Society&BehaviorPublic HealthUniversity of CaliforniaIrvineCAUSA department of statistics and Data Science Yale UniversityNew HavenCTUS department of Internal Medicine Yale School of MedicineNew HavenCTUS department of health Policy and Management Yale School of Public HealthNew HavenCTUS department of Economics Yale UniversityNew HavenCTUS.

Introduction:Childhood circumstances impact senior health,prompting the introduction of machine learning methods to assess their individual and collective contributions to senior ***:Using health and retirement study(HRS)and China health and Retirement Longitudinal Study(CHARLS),we analyzed 2,434 American and 5,612 Chinese participants aged 60 and *** inference trees and forests were employed to estimate the influence of childhood circumstances on self-rated health(SRH).Results:The conventional method estimated higher inequality of opportunity(IOP)values in both China(0.039,accounting for 22.67%of the total Gini coefficient 0.172)and the US(0.067,accounting for 35.08%of the total Gini coefficient 0.191).In contrast,the conditional inference tree yielded lower estimates(China:0.022,accounting for 12.79%of 0.172;US:0.044,accounting for 23.04%of 0.191),as did the forest(China:0.035,accounting for 20.35%of 0.172;US:0.054,accounting for 28.27%of 0.191).Childhood health,financial status,and regional differences were key determinants of senior *** conditional inference forest consistently outperformed others in predictive accuracy,as demonstrated by lower out-of-sample mean squared error(MSE).Discussion:The findings emphasize the need for early-life interventions to promote health equity in aging *** learning showcases the potential in identifying contributing factors.

关键词： collective inequality estimates

Asymptotics for the joint tail probability of bidimensional randomly weighted sums with applications to insurance

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Science China Mathematics 2024年第1期67卷 163-186页

作者： Yang Yang Shaoying Chen Kam Chuen Yuen School of statistics and Data Science Nanjing Audit UniversityNanjing 211815China department of statistics and Actuarial Science The University of Hong KongHong Kong 999077China

This paper studies the joint tail behavior of two randomly weighted sums∑_(i=1)^(m)Θ_(i)X_(i)and∑_(j=1)^(n)θ_(j)Y_(j)for some m,n∈N∪{∞},in which the primary random variables{X_(i);i∈N}and{Y_(i);i∈N},respectively,are real-valued,dependent and heavy-tailed,while the random weights{Θi,θi;i∈N}are nonnegative and arbitrarily dependent,but the three sequences{X_(i);i∈N},{Y_(i);i∈N}and{Θ_(i),θ_(i);i∈N}are mutually *** two types of weak dependence assumptions on the heavy-tailed primary random variables and some mild moment conditions on the random weights,we establish some(uniformly)asymptotic formulas for the joint tail probability of the two randomly weighted sums,expressing the insensitivity with respect to the underlying weak dependence *** applications,we consider both discrete-time and continuous-time insurance risk models,and obtain some asymptotic results for ruin probabilities.

关键词： asymptotic joint tail behavior randomly weighted sum heavy-tailed distribution dependence insurance risk model

Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting

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Computers, Materials & Continua 2024年第3期78卷 3529-3549页

作者： Ying Su Morgan C.Wang Shuai Liu department of statistics and Data Science University of Central FloridaOrlandoFL32816-2370USA School of Mathematics and statistics Beijing Technology and Business UniversityBeijing100048China

Long-term time series forecasting stands as a crucial research domain within the realm of automated machine learning(AutoML).At present,forecasting,whether rooted in machine learning or statistical learning,typically relies on expert input and necessitates substantial manual *** manual effort spans model development,feature engineering,hyper-parameter tuning,and the intricate construction of time series *** complexity of these tasks renders complete automation unfeasible,as they inherently demand human intervention at multiple *** surmount these challenges,this article proposes leveraging Long Short-Term Memory,which is the variant of Recurrent Neural Networks,harnessing memory cells and gating mechanisms to facilitate long-term time series ***,forecasting accuracy by particular neural network and traditional models can degrade significantly,when addressing long-term time-series ***,our research demonstrates that this innovative approach outperforms the traditional Autoregressive Integrated Moving Average(ARIMA)method in forecasting long-term univariate time *** is a high-quality and competitive model in time series prediction,and yet it requires significant preprocessing *** multiple accuracy metrics,we have evaluated both ARIMA and proposed method on the simulated time-series data and real data in both short and long ***,our findings indicate its superiority over alternative network architectures,including Fully Connected Neural Networks,Convolutional Neural Networks,and Nonpooling Convolutional Neural *** AutoML approach enables non-professional to attain highly accurate and effective time series forecasting,and can be widely applied to various domains,particularly in business and finance.

关键词： Automated machine learning autoregressive integrated moving average neural networks time series analysis