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The purpose of this study is to set up a dynamic model of material extrusion (ME) additive manufacturing plates for the prediction of their dynamic behavior (i.e. dynamic inherent characteristic, resonant response and damping) and also carry out its experimental validation and sensitivity analysis.

Based on the classical laminated plate theory, a dynamic model is established using the orthogonal polynomials method, taking into account the effect of lamination and orthogonal anisotropy. The dynamic inherent characteristics of the ME plate are worked out by Ritz method. The frequency-domain dynamic equations are then derived to solve the plates’ resonant responses, with which the damping ratio is figured out according to the half-power bandwidth method. Subsequently, a series of experimental tests are performed on the ME samples to obtain the measured data.

It is shown that the predictions and measurements in terms of dynamic behavior are in good agreement, validating the accuracy of the developed model. In addition, sensitivity analysis shows that increasing the elastic modulus or Poisson’s ratio will increase the corresponding natural frequency of the ME plate but decrease the resonant response. When the density is increased, both the natural frequency and resonant response will be decreased.

Future research can be focused on using the proposed model to investigate the effect of processing parameters on the ME parts’ dynamic behavior.

This study shows theoretical basis and technical insight into improving the forming quality and reliability of the ME parts.

A novel reliable dynamic model is set up to provide theoretical basis and principle to reveal the physical phenomena and mechanism of ME parts.

When bending a large diameter thin-walled tube, the thickn ess of outer side wall will reduce greatly, which leads to a decrease of structural strength of the tube. To solve this problem, this paper investigated the deformation principles of an eccentric tube in the rotary draw bending process, trying to find a way to reduce the wall thickness difference between inner and outer diameters.

An finite element model is established for analyzing the deformation of an eccentric tube in rotary draw bending process. The wall thickness distribution of the formed pipe was analyzed along the axis and diameter, respectively.

It is found that there exists an optimal eccentricity between the inner and outer circle center of the tube cross-section. If the eccentricity of the tube is chosen properly, it is possible to get a bent tube with equal thickness of inner and outer side walls. In addition, it is also found the optimal eccentricity on the cross-section can be influenced by bending radius, wall thickness, diameter and bending angle. The optimal eccentricity increases greatly with the decreasing of bending radius, the increase of outer diameter and the increase of wall thickness. The influence of bending angle on the optimal eccentricity can be divided into two situations. When the bending angle is small, the optimal eccentricity increases with the increase of bending angle. When the bending angle exceeds a certain value, the pipe enters a stable forming state. The optimal eccentricity of the stable forming region does not change with the bending angle.

Such a research is beneficial for reducing the thickness difference between inner and outer side walls in the rotary draw bending process.

The aim of this study is to examine the significant factors to improve the green nuclear energy investments in the emerging economies. For this purpose, balanced scorecard-based criteria are weighted with DEMATEL methodology. The findings demonstrate that technological improvement and financial issues are the most important issues for the improvement of the green nuclear energy investments in these countries. Nuclear energy working with thorium can also be obtained with proton accelerator technology that is currently quite expensive. Because of this problem, the investors are not willing to make investments for green nuclear energy projects. Hence, emerging countries should make the necessary technological investments to have proton accelerator technologies. With the help of this condition, it will be possible to reduce the cost of green nuclear energy projects which attracts the attention of the investors. This situation has a powerful contribution for the sustainable economic development of these countries.

In this chapter, we summarize and build on the current state of the customer mistreatment literature in an effort to further future research on this topic. First, we detail the four primary conceptualizations of customer mistreatment. Second, we present a multilevel model of customer mistreatment, which distinguishes between the unfolding processes at the individual employee level and the service encounter level. In particular, we consider the antecedents and outcomes unique to each level of analysis as well as mediators and moderators. Finally, we discuss important methodological concerns and recommendations for future research.

Traditional Chinese Medicine (TCM) is a complete medical healthcare system that encompasses acupuncture, acupressure, moxibustion, herbal medicine, diet, tui na massage, and exercises (tai chi and qigong) among other traditional therapies. It uses herbs and natural resources to produce the traditional medicines and focuses on maintaining the balance between body and mind. As such, many aspects of TCM can be considered as green and sustainable. While there is market demand for TCM in some countries and among some communities, some others are still not aware of TCM. Moreover, there are fewer discussions in the academic platforms on TCM. This case highlights the scenario of TCM based on Malaysia’s perspective and discusses its challenges and prospects.

This paper proposes that if a political system is more like to facilitate a unified government, to establish a strong executive body and to respond to the needs of the majority, financial reforms are more likely to emerge from the policymaking process and produce positive results. On the contrary, political systems that discourage those governing features are less likely to produce reforms. This chapter compares financial reform processes in China, Taiwan and New Zealand. All of them performed low level of financial reforms in the early 1980s but resulted in different situations later. In the mid-2000s, New Zealand heralded the most efficient and stable financial system; while Taiwan lagged behind and China performed the worst. Evidence showed that China’s authoritarian system may be the most superior in forming a unified government with a strong executive, but the policy priority often responds more to the interests of a small group of power elites; therefore the result of financial reform can be limited. Taiwan’s presidential system can produce greater financial reform when the ruling party controls both executive and legislative bodies, but legislative obstructions may occur under a divided government. New Zealand's Westminster system produces the most effective and efficient financial reform due to its unified government and a strong executive branch with consistent and stable supports from the New Zealand Parliament.

Autonomous driving depends on the collection, processing and analysis of environmental information and vehicle information. Environmental perception and processing are important prerequisite for the safety of self-driving of vehicles; it involves road boundary detection, vehicle detection, pedestrian detection using sensors such as laser rangefinder, video camera, vehicle borne radar, etc.

Subjected to various environmental factors, the data clock information is often out of sync because of different data acquisition frequency, which leads to the difficulty in data fusion. In this study, according to practical requirements, a multi-sensor environmental perception collaborative method was first proposed; then, based on the principle of target priority, large-scale priority, moving target priority and difference priority, a multi-sensor data fusion optimization algorithm based on convolutional neural network was proposed.

The average unload scheduling delay of the algorithm for test data before and after optimization under different network transmission rates. It can be seen that with the improvement of network transmission rate and processing capacity, the unload scheduling delay decreased after optimization and the performance of the test results is the closest to the optimal solution indicating the excellent performance of the optimization algorithm and its adaptivity to different environments.

In this paper, the results showed that the proposed method significantly improved the redundancy and fault tolerance of the system thus ensuring fast and correct decision-making during driving.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

The study aims to compare tribological properties between laser dimple textured surface and drilled dimple textured surface, and to analyze the influence of dimple hardened edges and ability of trapping wear debris on wear properties of dimple textured surfaces.

Circular textured dimples were produced on AISI 1,045 specimen surfaces using laser surface texturing (LST) and drilled surface texturing (DST) methods. Tribological behaviors of LST, DST and non-textured specimens were studied using ball-on-disc tribo-tester. Metallographic structures, dimples and worn surface morphologies were observed using a three-dimensional digital microscope. Hardnesses of substrate and dimple edges were measured.

There was no obvious difference in wear and friction coefficients between LST and DST specimens. Hardnesses of laser dimple edges were much higher than that of drilled dimple edges and specimen substrate. The hardened materials of laser dimple edge included recast zone and heat affect zone. Laser dimple was cone-shaped and drilled dimple was cylinder-shaped. Drilled dimple had a better ability of trapping wear debris than laser dimple. Non-uniform wear phenomenon occurred on worn surfaces of LST dimple specimens.

The ability of textured dimples to trap wear debris is affected by single dimple volume. Hardened edges of dimples cause non-uniform wear on worn surfaces of LST specimens.

The purpose of this paper is to investigate if the fibers obtained from chicken feathers have a possibility to be used or not used in Winter outerwears as a filling material in terms of thermal insulation parameters.

In the study, thermal properties of the heat-resistant interlining samples produced from the chicken feathers fibers were analyzed in comparison with the samples produced from the industrial filling materials.

In the study, it was revealed that the use of chicken feathers fibers as filling material in Winter outerwears was possible.

The use of chicken feather fibers in Winter outerwears as a filling material will be an extremely low-cost alternative to pile flies of water birds which are sufficiently expensive filling materials.

A significant portion of the chicken feather, which is released as a by-product in the production of chicken meat, is destroyed as industrial waste by digging or burning. Some of this product is used in the production of such cheap products as poultry feed. In the case of the production of fibers from the chicken feather, the use of these fibers as a filler in Winter clothing along with environmental protection will allow the use of this product for the production of products of higher cost.

The use of feathers’ material as a filling material in Winter outerwears has been known since ancient times. Due to the rough structure and low elasticity of chicken feathers, chicken feathers are not the best raw material for this purpose. This study revealed that it is possible to use chicken feathers as a filling material in terms of heat protection. The study is original in this respect.