Correlation between the rock mass properties and maximum horizontal stress:A case study of overcoring stress measurements

Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.

Resilience based importance measure analysis for SoS

In a system of systems(SoS),resilience is an important factor in maintaining the functionality,stability,and enhancing the operation effectiveness.From the perspective of resilience,this paper studies the importance of the SoS,and a resilience-based importance measure analysis is conducted to provide suggestions in the design and optimization of the structure of the SoS.In this paper,the components of the SoS are simplified as four kinds of network nodes:sensor,decision point,influencer,and target.In this networked SoS,the number of operation loops is used as the performance indicator,and an approximate algorithm,which is based on eigenvalue of the adjacency matrix,is proposed to calculate the number of operation loops.In order to understand the performance change of the SoS during the attack and defense process in the operations,an integral resilience model is proposed to depict the resilience of the SoS.From different perspectives of enhancing the resilience,different measures,parameters and the corresponding algorithms for the resilience importance of components are proposed.Finally,a case study on an SoS is conducted to verify the validity of the network modelling and the resiliencebased importance analysis method.

Integrated importance measure for multi-state coherent systems of k level

To verify the effectiveness of the integrated importance measure （IIM） for multi-state coherent systems of k level, the definition and physical meaning of IIM are demonstrated. Then, the improvement potential and Δ-importance measures are generalized to multi-state coherent systems based on the system performance level, and the relationships between IIM and traditional importance measures are discussed. The characteristics of IIM are demonstrated in both series and parallel systems. Also, an application to an oil transportation system is given. The comparison results show that： （i） IIM has some useful properties that are not possessed by traditional importance measures; （ii） IIM is effective in evaluating the component role in multi-state systems when the component reliability and the failure rate are simultaneously considered.

Importance of fatigue and its measurement in chronic liver disease

The mechanisms of fatigue in the group of people with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis are protean. The liver is central in the pathogenesis of fatigue because it uniquely regulates much of the storage, release and production of substrate for energy generation. It is exquisitely sensitive to the feedback controlling the uptake and release of these energy generation substrates. Metabolic contributors to fatigue, beginning with the uptake of substrate from the gut, the passage through the portal system to hepatic storage and release of energy to target organs (muscle and brain) are central to understanding fatigue in patients with chronic liver disease. Inflammation either causing or resulting from chronic liver disease contributes to fatigue, although inflammation has not been demonstrated to be causal. It is this unique combination of factors, the nexus of metabolic abnormality and the inflammatory burden of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis that creates pathways to different types of fatigue. Many use the terms central and peripheral fatigue. Central fatigue is characterized by a lack of self-motivation and can manifest both in physical and mental activities. Peripheral fatigue is classically manifested by neuromuscular dysfunction and muscle weakness. Therefore, the distinction is often seen as a difference between intention (central fatigue) versus ability (peripheral fatigue). New approaches to measuring fatigue include the use of objective measures as well as patient reported outcomes. These measures have improved the precision with which we are able to describe fatigue. The measures of fatigue severity and its impact on usual daily routines in this population have also been improved, and they are more generally accepted as reliable and sensitive. Several approaches to evaluating fatigue and developing endpoints for treatment have relied of biosignatures associated with fatigue. These have been used singly or in combination and include: physical performance measures, cognitive performance measures, mood/behavioral measures, brain imaging and serological measures. Treatment with non-pharmacological agents have been shown to be effective in symptom reduction, whereas pharmacological agents have not been shown effective.

Importance measure of system reliability upgrade for multi-state consecutive k-out-of-n systems

Importance measures in reliability systems are used to identify weak components in contributing to a proper function of the system. Traditional importance measures mainly concerned the changing value of the system reliability caused by the change of the reliability of the component, and seldom considered the joint effect of the probability distribution, improvement rate of the object component. This paper studies the rate of the system reliability upgrading with an improvement of the component reliability for the multi-state consecutive k-out-of-n system. To verify the multi-state consecutive k-out-of-n system reliability upgrading by improving one component based on its improvement rate, an increasing potential importance （IPI） and its physical meaning are described at first. Secondly, the relationship between the IPI and Birnbaum importance measures are discussed. And the IPI for some different improvement actions of the component is further discussed. Thirdly, the characteristics of the IPI are analyzed. Finally, an application to an oil pipeline system is given.

Possibilistic entropy-based measure of importance in fault tree analysis

With respect to the subjective factors and nonlinear characteristics inherent in the important identification of fault tree analysis （FTA）, a new important measure of FTA is proposed based on possibilistic information entropy. After investigating possibilistic information semantics, measure-theoretic terms, and entropy-like models, a two-dimensional framework has been constructed by combining both the set theory and the measure theory. By adopting the possibilistic assumption in place of the probabilistic one, an axiomatic index of importance is defined in the possibility space and then the modelling principles are presented. An example of the fault tree is thus provided, along with the concordance analysis and other discussions. The more conservative numerical results of importance rankings, which involve the more choices can be viewed as “soft” fault identification under a certain expected value. In the end, extension to evidence space and further research perspectives are discussed.

Dependency-based importance measures of components in mechatronic systems with complex network theory

To compensate for the limitations of previous studies,a complex network-based method is developed for determining importance measures,which combines the functional roles of the components of a mechatronic system and their topological positions.First,the dependencies among the components are well-represented and well-calculated.Second,a mechatronic system is modeled as a weighted and directional functional dependency network(FDN),in which the node weights are determined by the functional roles of components in the system and their topological positions in the complex network whereas the edge weights are represented by dependency strengths.Third,given that the PageRank algorithm cannot calculate the dependency strengths among components,an improved PageRank importance measure(IPIM)algorithm is proposed,which combines the node weights and edge weights of complex networks.IPIM also considers the importance of neighboring components.Finally,a case study is conducted to investigate the accuracy of the proposed method.Results show that the method can effectively determine the importance measures of components.

Hierarchical Modeling by Recursive Unsupervised Spectral Clustering and Network Extended Importance Measures to Analyze the Reliability Characteristics of Complex Network Systems

The complexity of large-scale network systems made of a large number of nonlinearly interconnected components is a restrictive facet for their modeling and analysis. In this paper, we propose a framework of hierarchical modeling of a complex network system, based on a recursive unsupervised spectral clustering method. The hierarchical model serves the purpose of facilitating the management of complexity in the analysis of real-world critical infrastructures. We exemplify this by referring to the reliability analysis of the 380 kV Italian Power Transmission Network (IPTN). In this work of analysis, the classical component Importance Measures (IMs) of reliability theory have been extended to render them compatible and applicable to a complex distributed network system. By utilizing these extended IMs, the reliability properties of the IPTN system can be evaluated in the framework of the hierarchical system model, with the aim of providing risk managers with information on the risk/safety significance of system structures and components.

Availability Importance Measures for Virtualized System with Live Migration

This paper presents component importance analysis for virtualized system with live migration. The component importance analysis is significant to determine the system design of virtualized system from availability and cost points of view. This paper discusses the importance of components with respect to system availability. Specifically, we introduce two different component importance analyses for hybrid model (fault trees and continuous-time Markov chains) and continuous-time Markov chains, and show the analysis for existing probabilistic models for virtualized system. In numerical examples, we illustrate the quantitative component importance analysis for virtualized system with live migration.

Characteristics of Integrated Importance Measure for Whole Lifetime-Oriented System Performance Evaluation

Importance measures are being widely used to characterize the importance of component in systems.Focus on the integrated importance measure(IIM)of the whole lifetime measure based on the transition rates of component states.To describe the impact of each component in whole lifetime,the IIM is generalized in nonrepairable and repairable systems at first.Then,their formulas are computed in series and parallel systems.Finally,the characteristics of generalized IIM in typical series systems and parallel systems are analyzed.The results show that the generalized IIM of component can evaluate the expected effect of component state on the system performance in whole lifetime.

Importance Measure Analysis for Use in Dynamic Performance Design of a Co-cured Composite Damping Instrument Panel

For the best dynamic performance of a co-cured composite damping instrument panel with light weight and high strength, a multilayer sandwich structure with polymethaerylimide （PMI） foam combined with embedded and co-cured composite damping structure is proposed. The struetue can maintain the excellent mechanical properties of composite materials, and achieve the damping and light effect at the same time. Input variables which may affect the dynamic performance of the instrument panel were selected and variance based importance measure was analyzed through multi- finite element method （FEM） analysis. Using the results of the importance measure analysis, with other design requirements, the important design variable was optimized and an instrument panel with the best dynamic performance under the requirements of light weight and high strength was obtained. The structure of the instrument panel can provide reference for the design of precision, high speed, and dynamic composite component. The importance measure analysis of dynamic performance of the instrument panel can provide a reference for relative design.

Variable Importance Measure System Based on Advanced Random Forest

The variable importance measure(VIM)can be implemented to rank or select important variables,which can effectively reduce the variable dimension and shorten the computational time.Random forest(RF)is an ensemble learning method by constructing multiple decision trees.In order to improve the prediction accuracy of random forest,advanced random forest is presented by using Kriging models as the models of leaf nodes in all the decision trees.Referring to the Mean Decrease Accuracy(MDA)index based on Out-of-Bag(OOB)data,the single variable,group variables and correlated variables importance measures are proposed to establish a complete VIM system on the basis of advanced random forest.The link of MDA and variance-based sensitivity total index is explored,and then the corresponding relationship of proposed VIM indices and variance-based global sensitivity indices are constructed,which gives a novel way to solve variance-based global sensitivity.Finally,several numerical and engineering examples are given to verify the effectiveness of proposed VIM system and the validity of the established relationship.

Importance measure based optimal maintenance policy for deteriorating components

An optimal maintenance policy tor deteriorating components based on quasi renew-process model is presented. In this policy, the first N - 1 failures of a component are maintained by repairs and the N＇h failure is maintained by replacement. The policy takes replacement actions at component lev- el by considering the fact that more and more components are designed to be field replaceable and maintenance activities are setting free from system halt. Concerning system structure impact, impor- tance measure is employed in the optimization procedure which aims at maximizing the long-rnn prof- it per unit time. Two example series parallel systems are taken to illustrate the policy and it is proved to work well. According to importance analysis, components are classified into important ones and unimportant ones based on the system behavior under their failures. Simulation results show that the presented policy makes a clear distinction between them and takes effective mainte- nance actions to compensate the deteriorating of components.

Measurement of Nodes Importance for Complex Networks Structural-Holes-Oriented

Mining important nodes in the complex network should not only consider the core nodes, but also consider the locations of the nodes in the network. Despite many researches on discovering important nodes, the importance of nodes in the structural holes is still ignored easily. Therefore, this paper proposes a method of local centrality measurement based on structural holes, which evaluates the nodes importance both by direct and indirect constraints caused by the lack of structural holes around the nodes. In this method, the attributes and locations of the nodes and their first-order and second-order neighbors are taken into account simultaneously. Deliberate attack simulation is carried out through selective deletion in a certain proportion of network nodes. Calculating the decreased ratio of network efficiency is to quantitatively describe the importance of nodes in before-and-after attacks. Experiments indicate that this method has more advantages to mine important nodes compared to clustering coefficient and k-shell decomposition method. And it is suitable for the quantitative analysis of the nodes importance in large scale networks.

An Importance Segregation Based Multi-Objective Optimization Model for Traffic Safety Improvement Countermeasure Selection

This paper presents a multi-objective optimization model to decide effective and beneficial portfolio for implementing traffic safety improvements under budgetary constraints.Different from the conventional multi-objective approaches,the proposed model segregates decision criteria into different importance levels and designs a successive optimization approach to obtain the final solution(s).Such modeling features offer the advantages to:1)prevent the arbitrariness for transportation agencies to determine weights for decision criteria;2)remedy the deficiency of over-weighting less important criteria in the traditional multi-objective optimization approach;and 3)minimize the number of potential solutions for final decision by transportation agencies with enhanced screening of the sub-optimal solutions.Case study results reveal that the proposed model is efficient not only for deciding the most suitable traffic safety countermeasure for a specific site,but also for determining the plans for implementing multiple countermeasures among multiple sites given the budget constraint.Comparative study results have also indicated that the proposed model outperforms the traditional criteria in objectively selecting traffic safety improvements in a multi-criteria decision-making process.The clarity of model inputs and the interpretation of results with respect to different selection criteria offer its best potential to be used as an effective decision-support tool for transportation authorities to assess and refine their safety improvement investments.

Analysis on the Epidemic Situation of Intercepted Alien Pests from Imported Hides in Hebei and the Countermeasures during 2013-2014

The situation of intercepted alien pests from imported hides in Hebei during 2013-2014 was systematically analyzed. The results showed that 163 batches of alien pests were intercepted, including 2 batches of quarantine weeds and they both were Italian cocklebur. According to the statistics of original countries, the intercepted hides from 21 countries all had alien pests, in which Australia was the largest number of batches and species of alien pests. The analysis results showed that there was severe risk in the imported hides carrying alien pests, thus to effectively prevent the invasion of alien pests to our country, several quarantine measures should be taken in the future, such as enhancing the quarantine inspection in ports, and promoting the personnel ability of interception and species identification of alien pests.

HealthMeasures患者报告结局报告清单的解读

美国匹兹堡大学和HealthMeasures指导委员会及PROMIS健康组织标准委员会共同发表了HealthMeasures患者报告结局报告清单,旨在促进不同患者报告结局测量工具的标准化报告,帮助研究人员提高工具报告质量及结果解释的准确性,进一步改善跨研究间的比较分析。本文对HealthMeasures患者报告结局报告清单的主要内容进行介绍和解读,以期为中国患者报告结局研究者提供参考和借鉴。

Research on a Monte Carlo global variance reduction method based on an automatic importance sampling method

Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS method for the global variance reduction problem based on the AIS method,which was implemented in the Monte Carlo program MCShield.The proposed method was validated using the VENUS-Ⅲ international benchmark problem and a self-shielding calculation example.The results from the VENUS-Ⅲ benchmark problem showed that the grid-AIS method achieved a significant reduction in the variance of the statistical errors of the MESH grids,decreasing from 1.08×10^(-2) to 3.84×10^(-3),representing a 64.00% reduction.This demonstrates that the grid-AIS method is effective in addressing global issues.The results of the selfshielding calculation demonstrate that the grid-AIS method produced accurate computational results.Moreover,the grid-AIS method exhibited a computational efficiency approximately one order of magnitude higher than that of the AIS method and approximately two orders of magnitude higher than that of the conventional Monte Carlo method.

基于Null Importance和Stacking模型的知识追踪研究

为应对基于游戏的学习平台在知识追踪应用方面的不足,本研究利用Field Day Lab提供的教育游戏用户日志进行深入分析。采用方差法和Null Importance方法对数据集进行降维处理,并结合K折交叉验证与LightGBM算法,建立了一个高效的预测模型。此外,通过集成Logistic模型,构建起Stacking模型。研究表明,该模型在验证集上的Macro-F1值显著提升至0.699,同时也在测试集上显示出优异的泛化能力。本研究为教育游戏领域的知识追踪提供了创新方法,并为游戏开发与教育实践提供了宝贵参考,支持教育游戏的开发者为学生创造更有效的学习体验。

Establishing minimum clinically important difference values for the Patient-Reported Outcomes Measurement Information System Physical Function, hip disability and osteoarthritis outcome score for joint reconstruction, and knee injury and osteoarthritis out

AIM To establish minimum clinically important difference(MCID) for measurements in an orthopaedic patient population with joint disorders.METHODS Adult patients aged 18 years and older seeking care for joint conditions at an orthopaedic clinic took the Patient-Reported Outcomes Measurement Information System Physical Function(PROMIS~? PF) computerized adaptive test(CAT), hip disability and osteoarthritis outcome score for joint reconstruction(HOOS JR), and the knee injury and osteoarthritis outcome score for joint reconstruction(KOOS JR) from February 2014 to April 2017. MCIDs were calculated using anchorbased and distribution-based methods. Patient reports of meaningful change in function since their first clinic encounter were used as an anchor.RESULTS There were 2226 patients who participated with a mean age of 61.16(SD = 12.84) years, 41.6% male, and 89.7% Caucasian. Mean change ranged from 7.29 to 8.41 for the PROMIS~? PF CAT, from 14.81 to 19.68 for the HOOS JR, and from 14.51 to 18.85 for the KOOS JR. ROC cut-offs ranged from 1.97-8.18 for the PF CAT, 6.33-43.36 for the HOOS JR, and 2.21-8.16 for the KOOS JR. Distribution-based methods estimated MCID values ranging from 2.45 to 21.55 for the PROMIS~? PF CAT; from 3.90 to 43.61 for the HOOS JR, and from 3.98 to 40.67 for the KOOS JR. The median MCID value in the range was similar to the mean change score for each measure and was 7.9 for the PF CAT, 18.0 for the HOOS JR, and 15.1 for the KOOS JR.CONCLUSION This is the first comprehensive study providing a wide range of MCIDs for the PROMIS? PF, HOOS JR, and KOOS JR in orthopaedic patients with joint ailments.