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Distribution of long-haul goods could be managed via multimodal transportation networks where decision-maker has to consider these factors including the uncertainty of transportation time and cost, the timetable limitation of selected modes and the storage cost incurred in advance or delay arriving of the goods. Considering the above factors comprehensively, this paper establishes a multimodal multi-objective route optimization model which aims to minimize total transportation duration and cost. This study could be used as a reference for decision-maker to transportation plans.

Monte Carlo (MC) simulation is introduced to deal with transportation uncertainty and the NSGA-II algorithm with an external archival elite retention strategy is designed. An efficient transformation method based on data-drive to overcome the high time-consuming problem brought by MC simulation. Other contribution of this study is developed a scheme risk assessment method for the non-absolutely optimal Pareto frontier solution set obtained by the NSGA-II algorithm.

Numerical examples verify the effectiveness of the proposed algorithm as it is able to find a high-quality solution and the risk assessment method proposed in this paper can provide support for the route decision.

The impact of timetable on transportation duration is analyzed and making a detailed description in the mathematical model. The uncertain transportation duration and cost are represented by random number that obeys a certain distribution and designed NSGA-II with MC simulation to solve the proposed problem. The data-driven strategy is adopted to reduce the computational time caused by the combination of evolutionary algorithm and MC simulation. The elite retention strategy with external archiving is created to improve the quality of solutions. A risk assessment approach is proposed for the solution scheme and in the numerical simulation experiment.

The influence of Zn concentration on microstructure and corrosion performance of the Mg–xZn alloys microalloyed with Ca and Ce was investigated through optic microscopy, scanning electron microscopy, hydrogen evolution, dynamic polarization and electrochemical impedance spectroscopy experiments.

In this paper, Mg–xZn alloys (x = 0.5∼2.0 Wt.%) microalloyed with Ca and Ce (0.2 Wt.% each) were prepared.

As the increase of Zn concentration, the number of second phase particles (Mg-Zn-Ca, Mg-Zn-Ce and Mg-Ce phases) increased, and when the Zn concentration increased to 2.0 Wt.%, the new second phase Mg-Zn phase was precipitated.

The influence of Zn concentration on corrosion mechanism of Mg-xZn alloys microalloyed with Ca and Ce was revealed. Increasing of the Zn concentration resulted in the intensification of galvanic corrosion. When Zn concentration was 0.5 Wt.%, the alloy showed the lowest corrosion rate (0.61 mm y-1), which was about 1/2 of that of Mg-2.0Zn-0.2Ca-0.2Ce alloy.

The purpose of this study is to reveal the lead–lag structure between international crude oil price and stock markets.

The methods used for this study are as follows: empirical mode decomposition; shift-window-based Pearson coefficient and thermal causal path method.

The fluctuation characteristic of Chinese stock market before 2010 is very similar to international crude oil prices. After 2010, their fluctuation patterns are significantly different from each other. The two stock markets significantly led international crude oil prices, revealing varying lead–lag orders among stock markets. During 2000 and 2004, the stock markets significantly led international crude oil prices but they are less distinct from the lead–lag orders. After 2004, the effects changed so that the leading effect of Shanghai composite index remains no longer significant, and after 2012, S&P index just significantly lagged behind the international crude oil prices.

China and the US stock markets develop different pattens to handle the crude oil prices fluctuation after finance crisis in 1998.

This paper aims to examine the effect of new product launch actions and firm reputation on firm performance in the Chinese auto industry.

This analysis adopts empirical data from 66 auto firms in China’s auto market from 2007 to 2012 to explore how new product launch actions undertaken by a firm can contribute to achieving superior performance and to investigate the relationships between new product launch actions and firm performance. Moreover, how firm reputation interacts with new product launch actions to affect firm performance is also investigated. Fixed effects regression model following the Hausman specification test was used to quantitatively examine the relationship.

It was concluded that the focal firm’s new product launch actions, including new product launch breadth, complexity and heterogeneity of its new repertoire of product launch actions, and firm reputation can impact its performance. Firm reputation can impact the signaling process and the capability of firms to enhance their performance via new product launch movements.

This research contributes to new product launch research by providing a more comprehensive view of competitive dynamic actions by which a firm’s performance is strengthened by examining the effects of two factors that affect performance. These factors are as follows: the characteristics in terms of breadth, complexity, and heterogeneity of new product launch actions undertaken by a firm and the characteristic of firm reputation.

The purpose of this paper is to assess the performance of the stabilised moving least squares (MLS) scheme in the meshless local Petrov–Galerkin (MLPG) method for heat conduction method.

In the current work, the authors extend the stabilised MLS approach to the MLPG method for heat conduction problem. Its performance has been compared with the MLPG method based on the standard MLS and local coordinate MLS. The patch tests of MLS and modified MLS schemes have been presented along with the one- and two-dimensional examples for MLPG method of the heat conduction problem.

In the stabilised MLS, the condition number of moment matrix is independent of the nodal spacing and it is nearly constant in the global domain for all grid sizes. The shifted polynomials based MLS and stabilised MLS approaches are more robust than the standard MLS scheme in the MLPG method analysis of heat conduction problems.

The MLPG method based on the stabilised MLS scheme.

Adaptive slicing is a key step in three-dimensional (3D) printing as it is closely related to the building time and the surface quality. This study aims to develop a novel adaptive slicing method based on ameliorative area ratio and accurate cusp height for 3D printing using stereolithography (STL) models.

The proposed method consists of two stages. In the first stage, the STL model is sliced with constant layer thickness, where an improved algorithm for generating active triangular patches, the list is developed to preprocess the model faster. In the second stage, the model is first divided into several blocks according to the number of contours, then an axis-aligned bounding box-based contour matching algorithm and a polygons intersection algorithm are given to compare the geometric information between several successive layers, which will determine whether these layers can be merged to one.

Several benchmarks are applied to verify this new method. Developed method has also been compared with the uniform slicing method and two existing adaptive slicing methods to demonstrate its effectiveness in slicing.

Compared with other methods, the method leads to fewer layers whilst keeping the geometric error within a given threshold. It demonstrates that the proposed slicing method can reach a trade-off between the building time and the surface quality.

The purpose of this paper is to examine the important role played by corporate governance in de facto International Financial Reporting Standards (IFRS) convergence, and to provide empirical evidence that audit quality mediates the degree of IFRS convergence.

The paper develops a model showing the role of corporate governance in converging national accounting standards with the IFRS, and empirically tests the model using a sample of Chinese listed companies with B‐shares. Both analysis of variance and multiple regressions are employed to test the hypotheses.

Effective internal corporate governance helps companies to be more aligned with IFRS and thus provide high quality financial information. Furthermore, audit quality as an external governance factor mediates the relationship between internal corporate governance and IFRS convergence.

The paper extends research findings, as shown in the literature, by showing the role of corporate governance in the IFRS convergence, especially the mediating effect of audit quality. In addition to accounting standards, global convergence of auditing standards and corporate governance is imperative if de facto convergence of accounting standards is to be achieved.

The paper highlights the effect of corporate governance and the interaction between internal and external corporate governance in achieving IFRS convergence, which has been largely ignored in the literature. Based on the results, the paper proposes an explanation for the mixed results shown in the literature.

The goal of this study is to explore the effect of two-sided lateral gap with uncertain velocity on the stability of traffic flow on a curved road.

In this paper, an extended car-following model considering the effect of two-sided lateral gap with uncertain velocity on a curved road is proposed. The effects of different lateral positions and radius of different sizes can be considered as control signals. The stability condition of the new model is obtained by the control theory. The numerical simulations are carried out to analyze how the control signal and lateral positions and radius of curved road affect traffic flow stability. The results show that driving between two lanes and inaccurate speed estimates both have a negative effect on traffic flow stability, and the stability also decreases with the increase in the radius of curved road.

(1) Simulation of influencing factors of vehicle lateral position indicates that if the driver drives between two lanes, it would have a negative impact on traffic flow. (2) When the speed is fixed, the traffic flow becomes more and more unstable with the increase in the radius of the curve. (3) The stability of traffic flow will be affected when the driver estimates the speed of the vehicle ahead. Therefore, whether it is manual driving or future intelligent vehicle driving, it is necessary to accurately judge the speed of the front vehicle.

There is little research on two-sided lateral gap with uncertain velocity for the stability of traffic flow on a curved road. The enhanced model constructed in this study can better reflect the real traffic, which can also give some theoretical reference for the development of connected and autonomous vehicles (CAVs).

Frequency diverse array (FDA) radar with uniform frequency offset between antenna elements has been proposed and investigated, which exhibits a range-angle-dependent beampattern. Nevertheless, because of the coupling in range and angle responses, it cannot estimate directly both the range and angle information of a target.The purpose of this paper is to consider a sub-array scheme of range-angle joint estimation of a target for frequency diverse array (FDA) radar.

First, The entire array is divided into two sub-arrays, which employs two different frequency offsets. For aperture extension, each sub-array adopts difference co-array structure . Therefore, the targets range and angle can be estimated directly with the subspace-based multiple signal classification algorithms for the decoupling capability of distance and angle dimensional. The estimation performance is examined by analyzing the Cramer-Rao lower bound (CRLB) versus signal-to-noise ratio (SNR).

Each sub-array adopts difference co-array structure to provide degrees of freedom by only physical sensors when the second-order statistics of the received data is used. And the sub-array is equivalent to two sets of equations to solve two unknown quantities, and the closed solution of the unknown quantity can be directly determined, which cannot be gained by the phase-array radar and basic ULA FDA radar. Finally, numerical simulation results verify the validity of the proposed method.

In this paper, we devise a subarray scheme on FDA radar for range and angle estimation. In order to aperture extension, difference co-array is employed in each subarrays, and more targets can be distinguished than the physical sensors. The range and angle estimation performance is examined by analyzing the CRLB.

While several studies have examined the roles of husbands and wives in making decisions about products, few have examined the impact of children. This article reports the results of a 1985 study of the influence of children on families. The study examines children's influence in each of four stages of the purchase decision, for 25 products, and by age of the children. For child‐centered (e.g., toys, children's clothing, food) and child‐used products or services (e.g., vacations, restaurant choices, outside entertainment), the study shows that children are perceived as influential by most households. Older children are perceived as more influential than younger children for nearly all the products studied. The study concludes that “family” decision making is quite different from “husband‐wife” decision making.