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.

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.

Shear wave splitting analysis of local earthquakes from dense arrays in Shimian,Sichuan

The Shimian area of Sichuan sits at the junction of the Bayan Har block.Sichuan-Yunnan rhombic block,and Yangtze block,where several faults intersect.This region features intense tectonic activity and frequent earthquakes.In this study,we used local seismic waveform data recorded using dense arrays deployed in the Shimian area to obtain the shear wave splitting parameters at 55 seismic stations and thereby determine the crustal anisotropic characteristics of the region.We then analyzed the crustal stress pattern and tectonic setting and explored their relationship in the study area.Although some stations returned a polarization direction of NNW-SSE.a dominant polarization direction of NW-SE was obtained for the fast shear wave at most seismic stations in the study area.The polarization directions of the fast shear wave were highly consistent throughout the study-area.This orientation was in accordance with the direction of the regional principal compressive stress and parallel to the trend of the Xianshuihe and Daliangshan faults.The distribution of crustal anisotropy in this area was affected by the regional tectonic stress field and the fault structures.The mean delay time between fast and slow shear waves was 3.83 ms/km.slightly greater than the values obtained in other regions of Sichuan.This indicates that the crustal media in our study area had a high anisotropic strength and also reveals the influence of tectonic complexity resulting from the intersection of multiple faults on the strength of seismic anisotropy.

The Application of Deep Brain Stimulation for Parkinson’s Disease on the Motor Pathway:A Bibliometric Analysis across 10 Years

Background and Objective Since its initial report by James Parkinson in 1817,Parkinson’s disease(PD)has remained a central subject of research and clinical advancement.The disease is estimated to affect approximately 1%of adults aged 60 and above.Deep brain stimulation,emerging as an alternative therapy for end-stage cases,has offered a lifeline to numerous patients.This review aimed to analyze publications pertaining to the impact of deep brain stimulation on the motor pathway in patients with PD over the last decade.Methods Data were obtained from the Web of Science Core Collection through the library of Huazhong University of Science and Technology(China).The search strategy encompassed the following keywords:“deep brain stimulation”,“Parkinson’s disease”,“motor pathway”,and“human”,from January 1,2012,to December 1,2022.Additionally,this review visualized the findings using the Citespace software.Results The results indicated that the United States,the United Kingdom,Germany,and China were the primary contributors to this research field.University College London,Capital Medical University,and Maastricht University were the top 3 research institutions in the research area.Tom Foltynie ranked first with 6 publications,and the journals of Brain and Brain Stimulation published the greatest number of relevant articles.The prevailing research focal points in this domain,as determined by keywords“burst analysis”,“encompassed neuronal activity”,“nucleus”,“hyper direct pathway”,etc.Conclusion This study has provided a new perspective through bibliometric analysis of the deep brain stimulation therapy for treating patients with PD,which can shed light on future research to advance our comprehension of this particular field of study.

Failure analysis of the needle valve body of R18CrNi8 steel

A needle valve is a key component of a diesel injector.The needle valve body of the diesel engine, made of R18CrNi8 steel, cracked and failed during the working process.The cracking failure reasons for the carburized injector valve body through chemical composition analysis, metallographic examination, scanning electron microscope(SEM) analysis, and energy spectrum analysis, were investigated.The results reveal that the original material of the needle valve is in conformity with the manufacturing requirement.Due to the high carburizing quenching temperature, the best carburized layer structure was not obtained, and the machining defect from which the crack emanated was not identified.The cracks expanded and eventually led to fracture under the action of altered stress and the high-temperature combustion environment during the operation of the engine.

Sensor-Based Gait Analysis for Parkinson’s Disease Prediction

Parkinson’s disease is identified as one of the key neurodegenerative disorders occurring due to the damages present in the central nervous system.The cause of such brain damage seems to be fully explained in many research studies,but the understanding of its functionality remains to be impractical.Specifically,the development of a quantitative disease prediction model has evolved in recent decades.Moreover,accelerometer sensor-based gait analysis is accepted as an important tool for recognizing the walking behavior of the patients during the early prediction and diagnosis of Parkinson’s disease.This type of minimal infrastructure equipment helps in analyzing the Parkinson’s gait properties without affecting the common behavioral patterns during the clinical practices.Therefore,the Accelerometer Sensor-based Parkinson’s Disease Identi-fication System(ASPDIS)is introduced with a kernel-based support vector machine classifier model to make an early prediction of the disease.consequently,the proposed classifier can easily predict various severity levels of Parkinson’s disease from the sensor data.The performance of the proposed classifier is com-pared against the existing models such as random forest,decision tree,and k-near-est neighbor classifiers respectively.As per the experimental observation,the proposed classifier has more capability to differentiate Parkinson’s from non-Parkinson patients depending upon the severity levels.Also,it is found that the model has outperformed the existing classifiers concerning prediction time and accuracy respectively.

A Comprehensive Bibliometric Analysis of China’s Free Trade Zones:Status and Evolutionary Trends

The China free trade zone,crucial for advancing a new open economy,has gained significant attention lately.We analyzed 885 papers from Peking University Core and CSSCI journals(2012-2023)using CiteSpace for visualization.Our research results indicate that the literature on China’s free trade zone peaked with 171 articles in 2015,and gradually returned to an average of 45 articles per year.The main research focuses in this field include“institutional innovation”,“negative list”,“financial innovation”,“financial openness”,“opening up to the outside world”,and“economic growth”.In addition,cutting-edge analysis indicates that“dual circulation”and“blockchain”are future research trends.The main authors of the literature include Yang Bin,Zhu Xiaolin,Yuan Bo,Li Meng,Zhao Liang,and others.Their affiliated institutions,research institutes,and universities have not yet formed a clear core circle of authors;The top three research institutions with the highest number of publications are the International Trade and Economic Cooperation Research Institute of the Ministry of Commerce,Kaiyuan Law School of Shanghai Jiao Tong University,and the Comprehensive Research Institute of the Free Trade Zone of Sun Yatsen University.This article delves into the current hot topics and progress in the research of China’s free trade zones,providing important references and inspirations for future scholars in this field.

Diagnostic performance of texture analysis in the differential diagnosis of perianal fistulising Crohn’s disease and glandular anal fistula

BACKGROUND Perianal fistulising Crohn's disease(PFCD)and glandular anal fistula have many similarities on conventional magnetic resonance imaging.However,many patients with PFCD show concomitant active proctitis,but only few patients with glandular anal fistula have active proctitis.AIM To explore the value of differential diagnosis of PFCD and glandular anal fistula by comparing the textural feature parameters of the rectum and anal canal in fat suppression T2-weighted imaging(FS-T2WI).METHODS Patients with rectal water sac implantation were screened from the first part of this study(48 patients with PFCD and 22 patients with glandular anal fistula).Open-source software ITK-SNAP(Version 3.6.0,http://www.itksnap.org/)was used to delineate the region of interest(ROI)of the entire rectum and anal canal wall on every axial section,and then the ROIs were input in the Analysis Kit software(version V3.0.0.R,GE Healthcare)to calculate the textural feature parameters.Textural feature parameter differences of the rectum and anal canal wall between the PFCD group vs the glandular anal fistula group were analyzed using Mann-Whitney U test.The redundant textural parameters were screened by bivariate Spearman correlation analysis,and binary logistic regression analysis was used to establish the model of textural feature parameters.Finally,diagnostic accuracy was assessed by receiver operating characteristic-area under the curve(AUC)analysis.RESULTS In all,385 textural parameters were obtained,including 37 parameters with statistically significant differences between the PFCD and glandular anal fistula groups.Then,16 texture feature parameters remained after bivariate Spearman correlation analysis,including one histogram parameter(Histogram energy);four grey level co-occurrence matrix(GLCM)parameters(GLCM energy_all direction_offset1_SD,GLCM entropy_all direction_offset4_SD,GLCM entropy_all direction_offset7_SD,and Haralick correlation_all direction_offset7_SD);four texture parameters(Correlation_all direction_offset1_SD,cluster prominence_angle 90_offset4,Inertia_all direction_offset7_SD,and cluster shade_angle 45_offset7);five grey level run-length matrix parameters(grey level nonuniformity_angle 90_offset1,grey level nonuniformity_all direction_offset4_SD,long run high grey level emphasis_all direction_offset1_SD,long run emphasis_all direction_offset4_SD,and long run high grey level emphasis_all direction_offset4_SD);and two form factor parameters(surface area and maximum 3D diameter).The AUC,sensitivity,and specificity of the model of textural feature parameters were 0.917,85.42%,and 86.36%,respectively.CONCLUSION The model of textural feature parameters showed good diagnostic performance for PFCD.The texture feature parameters of the rectum and anal canal in FS-T2WI are helpful to distinguish PFCD from glandular anal fistula.

A Survey of English Translation Studies of Lu You’s Poetry Based on the Data Analysis of Domestic Academic Journals (2001-2022)

This article presents a comprehensive analysis of the current state of research on the English translation of Lu You’s poetry, utilizing a data sample comprising research papers published in the CNKI Full-text Database from 2001 to 2022. Employing rigorous longitudinal statistical methods, the study examines the progress achieved over the past two decades. Notably, domestic researchers have displayed considerable interest in the study of Lu You’s English translation works since 2001. The research on the English translation of Lu You’s poetry reveals a diverse range of perspectives, indicating a rich body of scholarship. However, several challenges persist, including insufficient research, limited translation coverage, and a noticeable focus on specific poems such as “Phoenix Hairpin” in the realm of English translation research. Consequently, there is ample room for improvement in the quality of research output on the English translation of Lu You’s poems, as well as its recognition within the academic community. Building on these findings, it is argued that future investigations pertaining to the English translation of Lu You’s poetry should transcend the boundaries of textual analysis and encompass broader theoretical perspectives and research methodologies. By undertaking this shift, scholars will develop a more profound comprehension of Lu You’s poetic works and make substantive contributions to the field of translation studies. Thus, this article aims to bridge the gap between past research endeavors and future possibilities, serving as a guide and inspiration for scholars to embark on a more nuanced and enriching exploration of Lu You’s poetry as well as other Chinese literature classics.

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.

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.

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。