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The question is whether debt market investors see through managers' attempts to hide their pension obligations. The authors establish a robust relation between understated pension liabilities and corporate bond yield spreads after controlling for factors that have been previously identified as having a significant impact on firms' cost of borrowing. The results support the idea that bond market investors are not being misled by the use of high pension liability discount rates by some companies to lower their reported pension obligations. For a small fraction of debt issuers, the reported pension liabilities are larger than the pension liabilities valued at the stipulated interest rate benchmarks. For these issuers with overstated pension liabilities, bond investors adjust their borrowing costs downward.

The authors investigate the relation between corporate bond yield spreads and understated pension liabilities relative to long-term Treasury and high-grade corporate bond yields. They aim to answer two questions. First, what are the sizes of over or understated pension liabilities relative to guideline benchmarks? Second, do debt market investors see through the potential management manipulation of pension discount rates? The authors find that firms with large understated pension liabilities face higher marginal borrowing costs after taking into account issue-specific features, firm characteristics, macroeconomic conditions and other pension information such as funded status and mandatory contributions.

The average understated projected benefit obligations (PBOs) are understated by $394.3 and $335.6, equivalent to 3.5 and 3.0% of the beginning of the fiscal year market value, respectively. The average understated accumulated benefit obligations (ABOs) are understated by $359.3 and $305.3 million, equivalent to 3.1 and 2.6%, of the beginning of the fiscal year market value, respectively. Relative to AA-grade corporate bond yields, the average difference between firm pension discount rates and benchmark yields becomes much smaller; the percentage of firm pension discount rates higher than benchmark yields is also much smaller. As a result, understated pension liabilities become negligible. The authors establish a robust relation between corporate bond yield spreads and measures of understated pension liabilities after controlling for issue-specific features, firm characteristics, other pension information (funded status and mandatory contributions), macroeconomic conditions, calendar effects and industry effects.

S&P Rating Services recognizes the issue that there is considerably more variability in discount rate assumptions among companies than in workforce demographics or the interest rate environment in which firms operate (Standard and Poor's, 2006). S&P also indicates that it would be desirable to normalize different discount rate assumptions but acknowledges that it is difficult to do so. In practice, S&P Rating Services conducts periodic surveys to see whether firms' assumed discount rates conform to the normal standard. The paper makes an initial attempt to quantify the size of understated pension liabilities and their impact on corporate bond yield spreads. This approach can be extended to study firms' costs of equity capital, the pricing of seasoned equity offerings and the pricing of merger and acquisition transaction deals, among other questions.

This paper aims to analyze the dominant stray parameters of the DC bus bar and focus on weakening the influence of the stray parameters instead of reducing the value of the stray parameters in DC bus bar while switching. By finding the mechanisms to reduce the effects of stray parameters on switching transient, the simple and straightforward optimization methods could be given for the engineering designer.

The investigations are focused on the equivalent circuit by segmented impedance evaluation in the low-frequency band and the energy propagation by wave impedance evaluation in the high frequency band. This paper proposes an equivalent impedance calculation model to locate the dominant stray parameters in the DC bus bar and takes the energy propagation characteristics using wave impedance into consideration, which can simplify the optimization design of DC bus bar.

According to the equivalent circuit and electromagnetic field analysis, this paper proves the existence of the dominant stray parameters in DC bus bar that is widely used on high-power converters and certifies that not all the stray parameters in different areas of DC bus bar have the same effects on switching process, which can give a good guidance for the optimization design of DC bus bar.

The positions of DC-link capacitors, resulting in only part of stray parameters in DC bus bar has more impact during switching, are significant to the DC bus bar optimization design. These stray parameters named dominant stray parameters in this paper play a leading role in the switching transient process. The area of DC bus bar, which is close to IGBTs and far from DC-link capacitors, contains the dominant stray parameters in the switching transient process. Therefore, the distance between DC-link capacitors and IGBTs should be shortened as much as possible. Based on the results, the efficiency for the DC bus bar optimization design could be improved by weakening the influence of the stray parameters, such as reducing the dominant stray parameters only. Therefore, it can save the cost and time of DC bus bar optimization design.

The purpose of this paper is to present a modified firefly algorithm (FA) considering the population diversity to avoid local optimum and improve the algorithm’s precision.

When the population diversity is below the given threshold value, the fireflies’ positions update according to the modified equation which can dynamically adjust the fireflies’ exploring and exploiting ability.

A novel metaheuristic algorithm called FA has emerged. It is inspired by the flashing behavior of fireflies. In basic FA, randomly generated solutions will be considered as fireflies, and brightness is associated with the objective function to be optimized. However, during the optimization process, the fireflies become more and more similar and gather into the neighborhood of the best firefly in the population, which may make the algorithm prematurely converged around the local solution.

Due to different dimensions and different ranges, the population diversity is different undoubtedly. And how to determine the diversity threshold value is still required to be further researched.

This paper presents a modified FA which uses a diversity threshold value to guide the algorithm to alternate between exploring and exploiting behavior. Experiments on 17 benchmark functions show that the proposed algorithm can improve the performance of the basic FA.

The purpose of this paper is to reduce the computational burden and improve the precision of the parameter optimization in the convection-diffusion equation, a new algorithm, the refined gray-encoded evolution algorithm (RGEA), is proposed.

In the new algorithm, the differential evolution algorithm (DEA) is introduced to refine the solutions and to improve the search efficiency in the evolution process; the rapid cycle operation is also introduced to accelerate the convergence rate. The authors apply this algorithm to parameter optimization in convection-diffusion equations.

Two cases for parameter optimization in convection-diffusion equations are studied by using the new algorithm. The results indicate that the sum of absolute errors by the RGEA decreases from 74.14 to 99.29 percent and from 99.32 to 99.98 percent, respectively, compared to those by the gray-encoded genetic algorithm (GGA) and the DEA. And the RGEA has a faster convergent speed than does the GGA or DEA.

A more complete convergence analysis of the method is under investigation. The authors will also explore the possibility of adapting the method to identify the initial condition and boundary condition in high-dimension convection-diffusion equations.

This paper will have an important impact on the applications of the parameter optimization in the field of environmental flow analysis.

This paper will have an important significance for a sustainable social development.

The authors establish a new RGEA algorithm for parameter optimization in solving convection-diffusion equations. The application results make a valuable contribution to the parameter optimization in the field of environmental flow analysis.

The purpose of this paper is to test the density dependence theory and explain the deep changes that the Chinese construction industry is experiencing. Focusing on both organizational level and industry level, it aims to identify the factors and to show how these factors affect the mortality of the Chinese construction companies.

The Jiangsu construction industry is chosen as a proxy of the Chinese market. With the event history analysis method and life history data on all companies known to have operated during the period 1989‐2007 in Jiangsu, an expanded Cox model is established to achieve the purpose.

The construction industry level evolution plays an important role on exit rate of construction companies; however, this effect does not conform with density dependence as expected, and it interacts with organizational age. Besides, age and size of organizational level, and macro environment also act on mortality.

Owing to the difficulty in data acquisition, only 19 years of the Jiangsu construction industry have been reported here, which may not provide the whole picture of the evolution process. Furthermore, the different ending events, such as disbanding and merge, have not been identified, which may affect the results to some extent.

The paper provides a new perspective to analyze the evolution of the Chinese construction industry and the mortality of construction companies.

This is the first article that applies the density dependence theory to analyze the evolution process of the construction industry. It is also the first attempt to analyze the interaction of density, macro factors and organizational age, which is a contribution to the organizational ecology theory and the study of construction industry development.

The purpose of this paper is to critically review the literature of performance measurement both in general and in the construction industry in particular. By doing so, it seeks to provide valuable insights into how to construct a comprehensive performance measurement model for the construction industry.

Based on a comprehensive literature review on performance measurement, the paper presents a critical review of the development of performance measurement, with a special focus on the construction sector. The strengths and weaknesses of most previous measurement frameworks and techniques are investigated. Performance information that each can generate is analyzed in the context of the construction industry.

The research findings showed that performance measurement studies in construction can be divided into three levels: project, organizational, and stakeholder levels. In addition, the major frameworks of performance measurement in construction were found to be: European Foundation for Quality Management excellence model, balanced scorecard model, and key performance indicators model. The most frequently applied research techniques of performance measurement in construction included: gap analysis, integrated performance index, statistical methods, and data envelopment analysis method. The performance information generated from the measurement encompasses frameworks and hierarchical indicators, and functions and score.

The research focuses on the performance measurement of construction. Further research work should be conducted to cover other industries.

The paper provides an innovative and useful approach to defining the process of performance measurement in construction, which can be of great use to both the research community and industrial practitioners.

The paper summarizes the recent performance measurement research studies in construction, integrates the whole process of the performance measurement, and offers useful insights into future areas of research in this field.

The prerequisite for most traditional visual simultaneous localization and mapping (V-SLAM) algorithms is that most objects in the environment should be static or in low-speed locomotion. These algorithms rely on geometric information of the environment and restrict the application scenarios with dynamic objects. Semantic segmentation can be used to extract deep features from images to identify dynamic objects in the real world. Therefore, V-SLAM fused with semantic information can reduce the influence from dynamic objects and achieve higher accuracy. This paper aims to present a new semantic stereo V-SLAM method toward outdoor dynamic environments for more accurate pose estimation.

First, the Deeplabv3+ semantic segmentation model is adopted to recognize semantic information about dynamic objects in the outdoor scenes. Second, an approach that combines prior knowledge to determine the dynamic hierarchy of moveable objects is proposed, which depends on the pixel movement between frames. Finally, a semantic stereo V-SLAM based on ORB-SLAM2 to calculate accurate trajectory in dynamic environments is presented, which selects corresponding feature points on static regions and eliminates useless feature points on dynamic regions.

The proposed method is successfully verified on the public data set KITTI and ZED2 self-collected data set in the real world. The proposed V-SLAM system can extract the semantic information and track feature points steadily in dynamic environments. Absolute pose error and relative pose error are used to evaluate the feasibility of the proposed method. Experimental results show significant improvements in root mean square error and standard deviation error on both the KITTI data set and an unmanned aerial vehicle. That indicates this method can be effectively applied to outdoor environments.

The main contribution of this study is that a new semantic stereo V-SLAM method is proposed with greater robustness and stability, which reduces the impact of moving objects in dynamic scenes.

The purpose of this paper is to investigate the local feature of driven granular gases in event-driven molecular dynamic simulation, in order to achieve spatial profiles of local velocity distribution and granular temperature, and the local state with various coefficients of restitution.

Event-driven molecular dynamic simulation is performed to study a vibro-fluidized granular gas system. Triangular-wave vibration is adopted in the simulation. The authors focus on the steady state of a driven granular gas.

The simulation finds the local velocity distribution is asymmetric along vibration direction in this driven granular gas system, which agrees with the experimental results obtained in micro-gravity. A nonlinear spatial profile of the skewness of local velocity distribution in vibration direction is found in the simulation. Furthermore, it is found that the value of skewness increases with the system dissipation. It is also found that the two temperature components T+ and T− differ from each other. This shows breakdown of energy equipartition. The ratio between them drops exponentially along y direction in various coefficients of restitution. All results confirm that the bulk boundary effect relates to the dissipation properties of granular gases.

This is the first MD simulation that investigates the bulk boundary effect to the local velocity distribution. The spatial profiles of the skewness of local velocity distribution are also investigated when changing the coefficient of restitution to study the influence of the system dissipative nature.

Gas pipelines are facing serious risk because of the factors such as long service life, complex working condition and most importantly, corrosion. As one of the main failure reasons of gas pipeline, corrosion poses a great threat to its stable operation. Therefore, it is necessary to analyze the reliability of gas pipelines with corrosion defect. This paper uses the corresponding methods to predict the residual strength and residual life of pipelines.

In this paper, ASME-B31G revised criteria and finite element numerical analysis software are used to analyze the reliability of a special dangerous section of a gas gathering pipeline, and the failure pressure and stress concentration of the pipeline under three failure criteria are obtained. Furthermore, combined with the predicted corrosion rate of the pipeline, the residual service life of the pipeline is calculated.

This paper verifies the feasibility of ASME-B31G revised criteria and finite element numerical analysis methods for reliability analysis of gas pipelines with corrosion defect. According to the calculation results, the maximum safe internal pressure of the pipeline is 9.53 Mpa, and the residual life of the pipeline under the current operating pressure is 38.41 years, meeting the requirements of safe and reliable operation.

The analysis methods and analysis results provide reference basis for the reliability analysis of corroded pipelines, which is of great practical engineering value for the safe and stable operation of natural gas pipelines.

Although China has instituted compulsory education through Grade 9, it is still unclear whether students are, in fact, staying in school. In this paper, the authors use a multi-year (2003–2011) longitudinal survey data set on rural households in 102–130 villages across 30 provinces in China to examine the extent to which students still drop out of school prior to finishing compulsory education.

To examine the correlates of dropping out, the study uses ordinary least squares and multivariate probit models.

Dropout rate from junior high school was still high (14%) in 2011, even though it fell across the study period. There was heterogeneity in the measured dropout rate. There was great variation among different regions, and especially among different villages. In all, 10% of the sample villages showed extremely high rates during the study period and actually rose over time. Household characteristics associated with poverty and the opportunity cost of staying in school were significantly and negatively correlated with the completion of nine years of schooling.

The findings of this study suggest that China needs to take additional steps to overcome the barriers keeping children from completing nine years of schooling if they hope to either achieve their goal of having all children complete nine years of school or extend compulsory schooling to the end of twelfth grade.

The authors seek to measure the prevalence of both compulsory education rates of dropouts and rates of completion in China. The study examines the correlates of dropping out at the lower secondary schooling level as a way of understanding what types of students (from what types of villages) are not complying with national schooling regulations. To overcome the methodological shortcomings of previous research on dropout in China, the study uses a nationally representative, longitudinal data set based on household surveys collected between 2003 and 2011.