A Bayesian multi-model inference methodology for imprecise momentindependent global sensitivity analysis of rock structures

Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(i.e.type of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model response.This paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input data.The methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input properties.The estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic models.The proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of India.The proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of properties.Imprecise Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection efforts.Analyses performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample sizes.The accurate importance ranking of properties was only possible via samples of large sizes.Further,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.

Transitivity Analysis of the Energy in China’s New Era

At present,with the steady development of the global economy,more and more countries begin to pay attention to the impact of ecological environment on economic development and human society,so the ecological environment has become a global issue that cannot be ignored in today’s era.Therefore,from the perspective of the ecological philosophy of Diversity&Harmony as well as Interaction&Co-existence,this paper will conduct ecological discourse analysis on the Energy in China’s New Era based on the transitivity system of systemic-functional grammar,and use the Corpus analysis software UAM Corpus Tool 3.3x to label and make statistics on the transitivity system,aiming to explore the distribution characteristics of the transitivity system in this white paper.Through the transitivity analysis of the white paper,this study helps readers to have a deeper understanding of the positive significance contained in the white paper.To a certain extent,it enables readers at home and abroad to understand China’s stance on energy issues and the positive image of China in energy ecology.It also awaken readers’awareness of environmental protection and acquire good habits of resource conservation to be in harmony between human and nature for sustainable development.

Conceptual Analysis of Self-Management in Patients with Hypertension

Objective:To clarify the concept of self-management in hypertensive patients by analyzing the definition,attributes,and measurement tools through a literature review.Methods:An Internet-based search of the databases was conducted using Academic Search Complete,Medical Line,CINAHL,Health Source:Nursing/Scholarly Edition,and Google Scholar.In the search process,keywords or free text were combined by using Boolean operators,with the search terms“self of management”or“self-management,”“concept*analysis”or“concept*definition,”and Walker and Avant’s concept analysis method was used.Results:Analysis of relevant literature summarized the conceptual attributes of self-management in hypertensive patients as the active participation of patients in the treatment process;the presence of interaction provided by patients and health care providers;the use of certain health management tools;and the aim of maintaining and improving the health status and living capacity of hypertensive patients.Conclusion:The concept of self-management for hypertensive patients was clarified,which helps to promote the application of hypertensive self-management in clinical work and improve outcomes and quality of life for patients with hypertension.

Comparison of R and Excel in the Field of Data Analysis

This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and its powerful data management and analysis tools make it suitable for handling complex data analysis tasks.It is also highly customizable,allowing users to create custom functions and packages to meet their specific needs.Additionally,R language provides high reproducibility,making it easy to replicate and verify research results,and it has excellent collaboration capabilities,enabling multiple users to work on the same project simultaneously.These advantages make R language a more suitable choice for complex data analysis tasks,particularly in scientific research and business applications.The findings of this study will help people understand that R is not just a language that can handle more data than Excel and demonstrate that r is essential to the field of data analysis.At the same time,it will also help users and organizations make informed decisions regarding their data analysis needs and software preferences.

Discourse Analysis of the Belt and Road Initiative From the Perspective of Central Asian Countries: A Case Study of the Republic of Kazakhstan

This study employs Norman Fairclough’s Critical Discourse Analysis(CDA)three-dimensional model,using the Republic of Kazakhstan as a case study,to delve into the discourse construction of China’s Belt and Road Initiative(BRI)in Central Asian countries.Through detailed analysis of policy documents,media reports,and public discussions in Central Asian countries,this paper reveals how the BRI constructs specific social practices,discourse events,and textual meanings within these nations.The findings indicate that through this global development strategy,China has not only strengthened its economic ties with Central Asian countries but has also exerted profound influences on political,cultural,and social levels.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

R.S.托马斯诗歌中的反田园书写

R.S.托马斯的诗歌展现了威尔士乡村一系列反田园特质,包括几乎绝望的风景、花园里的机器和自然界弱肉强食的暴力法则。这种现实主义的反田园书写反映了托马斯的民族主义情结、反现代主义和生态主义的立场。通过探讨田园与反田园的含义,分析托马斯诗歌中的反田园书写及其现实关怀,有助于挖掘他积极的入世态度和道德情怀。

基于S-O-R模型的视觉营销对消费者购买意愿的影响研究——以红色文创网店为例

为提高红色文创网店的点击转化率,文章从消费者视角出发,研究影响消费者购买意愿的视觉因素。基于S-O-R模型理论,构建红色文创网店视觉营销对消费者购买意愿因素的理论模型。利用S-O-R模型分析了红色文创网店视觉营销中的商品形象、界面形象以及品牌视觉形象对顾客感知价值及顾客购买意向的影响。通过设计量表和调查问卷进行实证研究,并结合结构方程模型加以论证,得出品牌视觉形象和界面形象是影响消费者购买意愿的关键因素,为设计师和红色文创品牌进行网店设计提供了一定的理论参考和建议。

上海青浦CINRAD/SAD雷达和南汇WSR-88D雷达数据对比分析

上海青浦CINRAD/SAD雷达和南汇WSR-88D雷达型号不同,并且采用不同的双偏振技术升级方案,实际业务运行中2部雷达存在一定的数据偏差。为了对雷达的探测性能进行定量评估,在共同探测区域遴选2022年7—9月及2023年6月共30个过程3933个时次数据,以稳定性降水与对流性降水分类并按强度分级进行对比,评估了反射率因子Z_(H),差分反射率Z_(DR),相关系数C_(C)和差分传播相移Φ_(DP)的水平分布特征及随方位变化趋势,雷达灵敏度随仰角变化趋势以及Z_(H)和Z_(DR)偏差的定量统计。结果表明:2部雷达Z_(H)的观测结果接近,青浦CINRAD/SAD雷达的Z_(H),C_(C)和Φ_(DP)受地物及避雷针影响较大,随方位变化不稳定,青浦CINRAD/SAD雷达在低层的非气象回波滤除效果较南汇WSR-88D雷达差。2部雷达Z_(H)和Z_(DR)的偏差在Z_(H)大于40 dBz的区域较大,Z_(H)平均偏差为0.9 dB,Z_(DR)为-0.14 dB。本文基于台风、冰雹、短时强降水和梅雨降水数据,定量化评估了上海2部S波段双偏振天气雷达数据之间的差异,为后续算法改进以及数据订正提供参考。

Benthodytes occidentpalauta sp.nov.,a new species of deep-sea holothuroid(Elasipodida:Psychropotidae)from the west of Kyushu-Palau Ridge in the Western Pacific Ocean

Benthodytes occidentpalauta sp.nov.was collected from the Kyushu-Palau Ridge at a depth of 5481 m in 2021.This new species is characterized by a gelatinous body wall,violet skin,six pairs of dorsal papillae,and a rough mid-ventral surface without tube feet.The dorsal deposits are rod-shaped and tripartite.Two types of papillae deposits as crosses with four arms with central bipartite apophyses.Ventral deposits are rods.Tentacle ossicles are rod-shaped with end protrusions.Gonad deposits are rodshaped,tripartite,and cross-shaped.The phylogenetic analyses based on cytochrome oxidase subunit 1(COI)and 16S individually and a concatenated dataset of COI and 16S genes of this species support that B.occidentpalauta sp.nov.belongs to Benthodytes.

Proximity to corridors benefits bird communities in vegetated interrow vineyards in Mendoza, Argentina

Management under ecological schemes and increasing habitat heterogeneity,are essential for enhancing biodiversity in vineyards.Birds provide several contributions to agriculture,for example pest control,recreation and enhancing human mental health,and have intrinsic value.Birds are also ideal model organisms because they are easy to survey,and species respond differently to agricultural land use at different scales.Vegetated borders of crops are key for many species of birds,and distance to the border have been found to be an important factor in vineyard-dominated agroecosystems.We evaluate if there are differences in the bird assemblage,between the interior compared to borders within vineyards,using a hierarchical community occupancy model.We hypoth-esized that occupancy of birds is greater in environments with greater heterogeneity,which in this study was considered to be contributed by the proximity to vegetated corridors.We expected that vineyard borders close to corridors will have higher bird occupancy than the center of the vineyard.The research was conducted in three vineyards with biodiversity-friendly management practices,in Gualtallary,Mendoza,Argentina.Bird surveys were conducted over three breeding seasons from 2018 to 2020.Occupancy and richness of the bird community was more closely associated with the borders adjacent to the corridors than with the interior of the vineyards,as we initially predicted,although the assemblage of birds did not differ much.More than 75%of the registered species consume exclusively or partially invertebrates.Biodiversity-friendly management and ecological schemes,together with vegetated corridors provide multiple benefits for biodiversity conservation.These ap-proaches not only minimize the use of agrochemicals but also prioritize soil cover with spontaneous vegetation,which supports a diverse community of insectivorous bird species,potentially contributing to pest control.

Association between childhood obesity and gut microbiota:16S rRNA gene sequencing-based cohort study

BACKGROUND This study aimed to identify characteristic gut genera in obese and normal-weight children(8-12 years old)using 16S rDNA sequencing.The research aimed to provide insights for mechanistic studies and prevention strategies for childhood obesity.Thirty normal-weight and thirty age-and sex-matched obese children were included.Questionnaires and body measurements were collected,and fecal samples underwent 16S rDNA sequencing.Significant differences in body mass index(BMI)and body-fat percentage were observed between the groups.Analysis of gut microbiota diversity revealed lowerα-diversity in obese children.Differences in gut microbiota composition were found between the two groups.Prevotella and Firmicutes were more abundant in the obese group,while Bacteroides and Sanguibacteroides were more prevalent in the control group.AIM To identify the characteristic gut genera in obese and normal-weight children(8-12-year-old)using 16S rDNA sequencing,and provide a basis for subsequent mechanistic studies and prevention strategies for childhood obesity.METHODS Thirty each normal-weight,1:1 matched for age and sex,and obese children,with an obese status from 2020 to 2022,were included in the control and obese groups,respectively.Basic information was collected through questionnaires and body measurements were obtained from both obese and normal-weight children.Fecal samples were collected from both groups and subjected to 16S rDNA sequencing using an Illumina MiSeq sequencing platform for gut microbiota diversity analysis.RESULTS Significant differences in BMI and body-fat percentage were observed between the two groups.The Ace and Chao1 indices were significantly lower in the obese group than those in the control group,whereas differences were not significant in the Shannon and Simpson indices.Kruskal-Wallis tests indicated significant differences in unweighted and weighted UniFrac distances between the gut microbiota of normal-weight and obese children(P<0.01),suggesting substantial disparities in both the species and quantity of gut microbiota between the two groups.Prevotella,Firmicutes,Bacteroides,and Sanguibacteroides were more abundant in the obese and control groups,respectively.Heatmap results demonstrated significant differences in the gut microbiota composition between obese and normal-weight children.CONCLUSION Obese children exhibited lowerα-diversity in their gut microbiota than did the normal-weight children.Significant differences were observed in the composition of gut microbiota between obese and normal-weight children.

Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019

Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.

A gated recurrent unit model to predict Poisson’s ratio using deep learning

Static Poisson’s ratio(vs)is crucial for determining geomechanical properties in petroleum applications,namely sand production.Some models have been used to predict vs;however,the published models were limited to specific data ranges with an average absolute percentage relative error(AAPRE)of more than 10%.The published gated recurrent unit(GRU)models do not consider trend analysis to show physical behaviors.In this study,we aim to develop a GRU model using trend analysis and three inputs for predicting n s based on a broad range of data,n s(value of 0.1627-0.4492),bulk formation density(RHOB)(0.315-2.994 g/mL),compressional time(DTc)(44.43-186.9 μs/ft),and shear time(DTs)(72.9-341.2μ s/ft).The GRU model was evaluated using different approaches,including statistical error an-alyses.The GRU model showed the proper trends,and the model data ranges were wider than previous ones.The GRU model has the largest correlation coefficient(R)of 0.967 and the lowest AAPRE,average percent relative error(APRE),root mean square error(RMSE),and standard deviation(SD)of 3.228%,1.054%,4.389,and 0.013,respectively,compared to other models.The GRU model has a high accuracy for the different datasets:training,validation,testing,and the whole datasets with R and AAPRE values were 0.981 and 2.601%,0.966 and 3.274%,0.967 and 3.228%,and 0.977 and 2.861%,respectively.The group error analyses of all inputs show that the GRU model has less than 5% AAPRE for all input ranges,which is superior to other models that have different AAPRE values of more than 10% at various ranges of inputs.

Targeted metabolomics study of fatty-acid metabolism in lean metabolic-associated fatty liver disease patients

BACKGROUND The annual incidence of metabolic-associated fatty liver disease(MAFLD)in China has been increasing and is often overlooked owing to its insidious charac-teristics.Approximately 50%of the patients have a normal weight or are not obese.They are said to have lean-type MAFLD,and few studies of such patients are available.Because MAFLD is associated with abnormal lipid metabolism,lipid-targeted metabolomics was used in this study to provide experimental evidence for early diagnosis and pathogenesis.MAFLD and analyze metabolic pathways.UPLC-Q-Orbitrap/MS content determination was used to determine serum palmitic acid(PA),oleic acid(OA),linoleic acid(LA),and arachidonic acid(AA)levels in lean-type MAFLD patients.RESULTS Urea nitrogen and uric acid levels were higher in lean-type MAFLD patients than in healthy individuals(P<0.05).Alanine transaminase and cholinesterase levels were higher in lean-type MAFLD patients than in healthy indi-viduals(P<0.01).The expression of high-density lipoprotein and apolipoprotein A-1 were lower in lean-type MAFLD patients than in healthy individuals(P<0.05)and the expression of triglycerides and fasting blood glucose were increased(P<0.01).A total of 65 biomarkers that affected the synthesis and metabolism of fatty acids were found with P<0.05 and variable importance in projection>1.The levels of PA,OA,LA,and AA were significantly increased compared with healthy individuals.CONCLUSION The metabolic profiles of lean-type MAFLD patients and healthy participants differed significantly,yielding 65 identified biomarkers.PA,OA,LA,and AA exhibited the most significant changes,offering valuable clinical guidance for prevention and treatment of lean-type MAFLD.

New Asymptotic Results on Fermat-Wiles Theorem

We analyse the Diophantine equation of Fermat xp yp = zp with p > 2 a prime, x, y, z positive nonzero integers. We consider the hypothetical solution (a, b, c) of previous equation. We use Fermat main divisors, Diophantine remainders of (a, b, c), an asymptotic approach based on Balzano Weierstrass Analysis Theorem as tools. We construct convergent infinite sequences and establish asymptotic results including the following surprising one. If z y = 1 then there exists a tight bound N such that, for all prime exponents p > N , we have xp yp zp.

航天器S4R电源技术在公路零碳中的应用

空间电源S4R控制技术在有效利用光伏阵列,提高电能的高效控制和转换方面,尤其是在高可靠性、模块化、高可扩展性电源供应方面的优点,与高速公路数字转型和智慧升级及“双碳”策略带来的沿线设备电力供应新的需求相匹配。本文介绍了一套将S4R功率调节技术用于高速公路供电的新型拓扑,实现用电点能源自洽,满足数字化、零碳化和智慧升级的需求。

基于NAR神经网络和R/S分析法的隧道围岩变形预测分析

为研究隧道围岩变形非线性特点,采用NAR神经网络和R/S分析法,对隧道围岩变形量和变形趋势进行分析。通过NAR神经网络对变形监测样本进行误差分析,认为NAR神经网络对围岩变形短期预测时的误差小精度高。运用R/S分析法对各变形时间序列进行重标极差分析,获得各时序的Hurst指数,分析其与围岩变形趋势的关系,并通过Hurst指数对隧道围岩变形趋势进行判定。结果表明:算例中的断面围岩变形仍然会呈增长趋势,但增长幅度在减小,且水平收敛的趋势性强于拱顶沉降,说明前者受随机扰动影响较小,后期稳定性相对更高。通过运用R/S分析法进行时间序列分析,不仅为围岩变形趋势预判提供了Hurst指数判据,同时也为围岩稳定性分析及治理提供了一种依据。

Statistical Approach to Basketball Players’Skill Level

In basketball, each player’s skill level is the key to a team’s success or failure, the skill level is affected by many personal and environmental factors. A physics-informed AI statistics has become extremely important. In this article, a complex non-linear process is considered by taking into account the average points per game of each player, playing time, shooting percentage, and others. This physics-informed statistics is to construct a multiple linear regression model with physics-informed neural networks. Based on the official data provided by the American Basketball League, and combined with specific methods of R program analysis, the regression model affecting the player’s average points per game is verified, and the key factors affecting the player’s average points per game are finally elucidated. The paper provides a novel window for coaches to make meaningful in-game adjustments to team members.

不同下壁导联室性早搏R/S波比值的慢性心力衰竭患者近期预后随访分析

目的对不同下壁导联室性早搏R/S波比值的慢性心力衰竭患者近期预后随访进行分析。方法选择2020年3月~2022年3月本院收治的93例动态心电图检查存在室性早搏的CHF患者93例。所有患者完善24h动态心电图检查,随访一年。依照近期预后进行分组,将出现急性心肌梗死、恶性心律失常等不良心脏事件纳入预后不良组(n=37),其余未出现心脏不良事件的患者纳入预后良好组(n=56)。比较两组不同下壁导联室性早搏R/S波比值的预后。结果两组在年龄、BMI、吸烟、高血压、糖尿病、LVEF、利尿剂、地高辛方面差异无统计学意义(P>0.05);两组在性别、NYHA分级上差异有统计学意义(P<0.05);预后良好组R/S比值≥1例数比率高于预后不良组,R/S比值<1例数比例低于预后不良组,差异有统计学意义(P<0.05)。Logistic回归分析显示,R/S比值<1与性别、NYHA分级均是CHF患者近期预后不良的独立危险因素(P<0.05)。结论不同下壁导联的室性早搏R/S比值与其预后具有相关性,R/S比值<1是其不良预后的预测因素。