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Prior studies document increased share repurchase activity after the temporary tax holiday under the American Jobs Creation Act (AJCA) of 2004. Our study examines the moderating effect of financial statement readability on share repurchases in response to a temporary reduction in repatriation tax. Building on prior literature, we argue that firms with excess cash overseas, despite the lack of investment opportunities, produce less readable financial statements to hide bad news. We find that firms with less readable financial statements initiated higher levels of share repurchases after the AJCA. Our results contribute to the existing literature showing (1) firms hold excess cash overseas mainly for tax reasons rather than for nontax reasons such as precautionary motives or empire-building concerns and (2) firms return excess funds to investors rather than squander the funds once the tax cost of repatriation is reduced. Firms that suffer from the overinvestment problem using hard-to-read financial statements to hide the bad news of a lack of investment opportunities are more likely to benefit from the tax cut. Our study provides timely evidence of potential firm response to the 2017 Tax Cut and Jobs Act, which permanently removes the repatriation tax.

Mechanical products usually require deterministic finite element analysis in the design phase to determine whether their structures meet the requirements. However, deterministic design ignores the influence of uncertainties in the design and manufacturing process of mechanical products, leading to the problem of a lack of design safety or excessive redundancy in the design. In order to improve the accuracy and rationality of the design results, a robust design method for structural reliability based on an active-learning marine predator algorithm (MPA)–backpropagation (BP) neural network is proposed.

The MPA was used to obtain the optimal weights and thresholds of a BP neural network, and an active-learning function applicable to neural networks was proposed to efficiently improve the prediction performance of the BP neural network. On this basis, a robust optimization design method for mechanical product reliability based on the active-learning MPA-BP model was proposed. Random moving quadrilateral sampling was used to obtain the sample points required for training and testing of the neural network, and the reliability sensitivity corresponding to each sample point was calculated by subset simulated significant sampling (SSIS). The total mass of the mechanical product and the structural reliability sensitivity of the trained active-learning MPA-BP model output were taken as the optimization objectives, and a multi-objective reliability-robust optimization design model was constructed, which was solved by the second-generation non-dominated ranking genetic algorithm (NSGA-II). Then, the dominance function was used in the obtained Pareto solution set to make a dominance-seeking decision to obtain the final reliability-robust optimization design solution. The feasibility of the proposed method was verified by a reliability-robust optimization design example of the bogie frame.

The prediction error of the active-learning MPA-BP neural network was smaller than those of the particle swarm optimization (PSO)-BP, marine predator algorithm (MPA)-BP and genetic algorithm (GA)-BP neural networks under the same basic parameter settings of the algorithm, which indicated that the improvement strategy proposed in this paper improved the prediction accuracy of the BP neural network. To ensure the reliability of the bogie frame, the reliability sensitivity and total mass of the bogie frame were reduced, which not only realized the lightweight design of the bogie frame, but also improved the reliability and robustness of the bogie.

The MPA algorithm with a higher optimization efficiency was introduced to find the weights and thresholds of the BP neural network. A new active-learning function was proposed to improve the prediction accuracy of the MPA-BP neural network.

The vibration of the rails is a significant source of railway rolling noise, often forming the dominant component of noise in the important frequency region between 400 and 2000 Hz. The purpose of the paper is to investigate the influence of the ground profile and the presence of the train body on the sound radiation from the rail.

Two-dimensional boundary element calculations are used, in which the rail vibration is the source. The ground profile and various different shapes of train body are introduced in the model, and results are observed in terms of sound power and sound pressure. Comparisons are also made with vibro-acoustic measurements performed with and without a train present.

The sound radiated by the rail in the absence of the train body is strongly attenuated by shielding due to the ballast shoulder. When the train body is present, the sound from the vertical rail motion is reflected back down toward the track where it is partly absorbed by the ballast. Nevertheless, the sound pressure at the trackside is increased by typically 0–5 dB. For the lateral vibration of the rail, the effects are much smaller. Once the sound power is known, the sound pressure with the train present can be approximated reasonably well with simple line source directivities.

Numerical models used to predict the sound radiation from railway rails have generally neglected the influence of the ground profile and reflections from the underside of the train body on the sound power and directivity of the rail. These effects are studied in a systematic way including comparisons with measurements.

The study of the character of structural hysteretic energy under earthquake is an essential foundation for energy-based seismic design and evaluation method. The purpose of this paper is to explore the distribution law of the accumulative irrecoverable hysteretic energy for MDOF structures, a formula of the accumulated irrecoverable hysteretic energy ratio along the layers is derived.

The procedure is based on the energy balance principle and the concept of the equivalent single-degree-of-freedom system. Furthermore, sensitivity analysis is carried out for 16 working conditions, considering all these possibilities of local failure or damage. And then the sensitivity influencing rule is obtained and the proposed formula is simplified.

Finally, the validation of the proposed formula is investigated through comparisons with the nonlinear time-history analysis results.

The proposed formula can be effectively to estimate the distribution of the hysteretic energy under a given ground motion.

With the rapid development of China’s urbanisation and market economy, municipal solid waste (MSW) generation is increasing dramatically. In response to the threat of environmental pollution and the potential value of converting waste into energy, both the government and the public are now paying more attention to MSW treatment and disposal methods. In 2014, 178.6 million tonnes of MSW was collected at a safe treatment rate of 84.8%. However, the treatment methods and the composition of MSW are influenced by the collection area, its gross domestic product, population, rainfall and living conditions. This chapter analysed the MSW composition properties of Lhasa, Tibet, compared with other cities, such as Beijing, Guangzhou and so forth. The research showed that the moisture content of MSW in Lhasa approaches 31%, which is much lower than the other cities mentioned previously. The proportion of paper and plastics (rubbers) collected was 25.67% and 19.1%, respectively. This was 1.00–3.17 times and 0.75–2.44 times more than those found in Beijing and Guangzhou, respectively. Non-combustibles can reach up to 22.5%, which was 4.03–9.11 times that of Beijing and Guangzhou, respectively. The net heating values could reach up to 6,616 kilojoule/kilogram. The food residue was only half the proportion found in other cities. Moreover, the disposal method applied in each city has also been studied and compared.

This study aims to examine the role of authenticity in tourists’ destination selection, analyze the factors that influence tourists to form their initial opinions and explore how tourists construct the authenticity of traditional villages. The authors selected Chengkan village in Huizhou district, Huangshan city, as a case. In the study, the authors constructed an attribute-hardware-software research framework and analyzed tourists’ authentic emic experiences from the perspective of constructivism. The findings of this study suggest that tourists’ destination selection is influenced by authenticity. The destination culture brokers who interact with tourists play an essential role in forming authentic experiences. According to differences in how tourists construct authenticity, the study divided tourists into three types: primitive imagination, aesthetic reality and rational cognition. The results of this study provide a deeper understanding of various viewpoints about authenticity research and contribute to the academic discussion on how to understand the authenticity of unique cultural heritage sites such as traditional villages in the context of tourism development.

The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

Based on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by training the delicately designed neural network structure with bearing qualitative comparison data between different health statuses. The remaining useful life is then predicted using the bearing health evaluation model and the degradation tolerance threshold. To validate the feasibility, efficiency and superiority of the proposed method, comparison experiments are designed and carried out on a widely used bearing dataset.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

Based on the character of R‐C frame, the calculation formula of VED is derived from the sub‐structure plan of lateral resistant force, the definition of equivalent stiffness matrix and equivalent additional viscoelastic force vector of VED is given and the seismic dynamic equation of R‐C frame controlled by VED is set up, the viscoelastic additional force vector of VED should be considered as outside load of structure and be calculated through the pseudo‐loading method, the programs of calculating the dynamic characteristic, calculating the elastic seismic response and calculating the elastic‐plastic seismic response of R‐C frame controlled by VED are compiled. Through the calculation of a inclined crossed R‐C frame, the results show that VED is effective in controlling the seismic response of frame and the pseudo‐loading method is reliable in the calculation.

The effect of tax policy on the repatriation of foreign earnings is a topic of ongoing discussion among policymakers, academics, and the popular press. It has become more salient due to the 2017 Tax Cuts and Jobs Act (TCJA), which permanently removed repatriation tax. This paper synthesizes the academic literature examining US multinational firms’ responses to the repatriation tax holiday initiated by the 2004 American Jobs Creation Act (AJCA), which temporarily reduced the tax on the repatriation of foreign earnings. By synthesizing firm responses to the temporary tax reduction, we identify similarities and differences in: (1) theories about why and when repatriation tax affects firms’ repatriation decisions; (2) empirical evidence of whether repatriation tax affects firms’ repatriation decisions; and (3) empirical evidence of whether repatriation tax affects firms’ investment decisions. The analyses provide insights into the effect of the permanent removal of repatriation tax under the TCJA and explore avenues for future research. This synthesis of the AJCA literature informs tax research and practice as well as policymaking.

The aim of this paper is to introduce an accurate asymmetric fault index for the diagnosis of the faulty linear permanent magnet Vernier machine (LPMVM).

Three-dimensional finite element method is applied to model the LPMVM. The geometrical and physical properties of the machine, the effect of stator and translator teeth, magnetic saturation of core and nonuniform air gap due to asymmetric fault are taken into account in the simulation. The air gap asymmetric fault is proposed. This analytical method estimates the air gap flux density of an LPMVM.

This paper presents an analytical method to predict the performance of a healthy and faulty LPMVM. The introduced index is based on the frequency patterns of the stator current. Besides, the robustness of the index in different loads and fault severity is addressed.

Introducing index for air gap asymmetry fault diagnosis of LPMVM.