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Confronting the unveiled sophisticated structural and physical characteristics of permanent magnets, notably the samarium–cobalt (Sm-Co) alloy, This work aims to introduce a simulation scheme that can link physics-based micromagnetics on the nanostructures and magnetostatic homogenization on the mesoscale polycrystalline structures.

The simulation scheme is arranged in a multiscale fashion. The magnetization behaviors on the nanostructures examined with various orientations are surrogated as the micromagnetic-informed hysterons. The hysteresis behavior of the mesoscale polycrystalline structures with micromagnetic-informed hysterons is then evaluated by computational magnetostatic homogenization.

The micromagnetic-informed hysterons can emulate the magnetization reversal of the parameterized Sm-Co nanostructures as the local hysteresis behavior on the mesostructures. The simulation results of the mesoscale polycrystal demonstrate that the demagnetization process starts from the grain with the largest orientation angle (a) and then propagates to the surrounding grains.

The presented scheme depicts the demand for integrating data-driven methods, as the parameters of the surrogate hysteron intrinsically depend on the nanostructure and its orientation. Further hysteron parameters that help the surrogate hysteron emulate the micromagnetic-simulated magnetization reversal should be examined.

This work provides a novel multiscale scheme for simulating the polycrystalline permanent magnets’ hysteresis while recapitulating the nanoscale mechanisms, such as the nucleation of domains, and domain wall migration and pinning. This scheme can be further extended to simulate the part-level hysteresis considering the mesoscale features.

The purpose of this paper is to investigate the effect of selective laser sintering (SLS) method on morphology and performance of polyamide 12.

Crystallization behavior is critical to the properties of semi-crystalline polymers. The crystallization condition of SLS process is much different from others. The morphology of polyamide 12 produced by SLS technology was investigated using scanning electron microscopy, polarized light microscopy, differential scanning calorimetry, X-ray diffraction and wide-angle X-ray diffraction.

Too low fill laser power brought about bad fusion of powders, while too high energy input resulted in bad performance due to chain scission of macromolecules. There were three types of crystal in the raw powder material, denoted as overgrowth crystal, ring-banded spherulite and normal spherulite.

In this work, SLS samples with different sintering parameters, as well as compression molding sample for the purpose of comparison, were made to study the morphology and crystal structure of sintered PA12 in detail.

This paper aims to develop an integrated and portable desktop 3D printer using direct extruding technology to expand applied material field. Different from conventional fused deposition modeling (FDM) which uses polymer filaments as feedstock, the developed system can fabricate products directly using polymer pellets. And its printing properties are also investigated.

A conical screw-based extrusion deposition (CSBED) system was developed with a large taper conical screw to plasticize and extrude fed materials. The 3D printer was developed with assistance of precision positioning and controlling system. Biocompatible thermoplastic polyurethane (TPU) pellets were selected as raw materials for experiments. The influences of four processing parameters: nozzle temperature, fill vector orientation, layer thickness and infill density on the product’s internal structure and tensile properties were investigated.

It is concluded that the customized system has a high manufacturing accuracy with a diminutive global size and is suitable for printing soft materials such as TPU. Theoretical calculation shows the developed conical screw is more effective in plasticizing and extruding compared with conventional screw. Printed samples can achieve applicable tensile properties under harmonious parameter cooperation. Deposited materials are found to have voids among adjacent roads under unbefitting parameters.

The developed system efficiently improves material limitations compared to commercial FDM systems and exhibits great potential in medical field because soft materials such as biocompatible TPU pellets can be directly used.

The purpose of this paper is to propose a robotic system for percutaneous surgery. The key component in the system, a robotic arm that can manipulate a puncture needle is presented. The mechanical design, the motion control and the force control method of the robotic arm are discussed in the paper.

The arm with an arc mechanism placed on a 3D Cartesian stage is developed as a puncture needle manipulator to locate the position of the needle tip, tune the needle’s posture and actuate the puncture motion under the visual guidance of two orthogonal X-ray images of a patient by a surgeon. A focusing method by using two laser spots is proposed to automatically move the needle tip to a surgery entry point on the skin. A dynamics model is developed to control the position of the needle mechanism and an explicit force control strategy is utilized to perform the needle insertion.

With the surgical system, a surgeon can easily perform puncture operation by taking two orthogonal real-time X-ray images as a visual feedback and accurately navigating the needle insertion. The laser-guided focusing method is efficient in placement of the needle tip. The explicit force control strategy is proved to be effective for holding constant and stable puncture force in experiments.

The robotic arm has an advantage in easy redirection of the needle because the rotation and the translation are decoupled in the mechanism. By adopting simple laser pens and a well-developed kinematics model, the system can handle the entry point, locating task automatically. The focusing method and the force control method proposed in the paper are useful for the present system and could be intuitive for similar surgical robots.

Research analyzing online travelers’ reviews has boomed over the past years, but it lacks efficient methodologies that can provide useful end-user value within time and budget. This study aims to contribute to the field by developing and testing a new methodology for sentiment analysis that surpasses the standard dictionary-based method by creating two hotel-specific word lexicons.

Big data of hotel customer reviews posted on the TripAdvisor platform were collected and appropriately prepared for conducting a binary sentiment analysis by developing a novel bag-of-words weighted approach. The latter provides a transparent and replicable procedure to prepare, create and assess lexicons for sentiment analysis. This approach resulted in two lexicons (a weighted lexicon, L1 and a manually selected lexicon, L2), which were tested and validated by applying classification accuracy metrics to the TripAdvisor big data. Two popular methodologies (a public dictionary-based method and a complex machine-learning algorithm) were used for comparing the accuracy metrics of the study’s approach for creating the two lexicons.

The results of the accuracy metrics confirmed that the study’s methodology significantly outperforms the dictionary-based method in comparison to the machine-learning algorithm method. The findings also provide evidence that the study’s methodology is generalizable for predicting users’ sentiment.

The study developed and validated a methodology for generating reliable lexicons that can be used for big data analysis aiming to understand and predict customers’ sentiment. The L2 hotel dictionary generated by the study provides a reliable method and a useful tool for analyzing guests’ feedback and enabling managers to understand, anticipate and re-actively respond to customers’ attitudes and changes. The study also proposed a simplified methodology for understanding the sentiment of each user, which, in turn, can be used for conducting comparisons aiming to detect and understand guests’ sentiment changes across time, as well as across users based on their profiles and experiences.

This study contributes to the field by proposing and testing a new methodology for conducting sentiment analysis that addresses previous methodological limitations, as well as the contextual specificities of the tourism industry. Based on the paper’s literature review, this is the first research study using a bag-of-words approach for conducting a sentiment analysis and creating a field-specific lexicon.

论可推广性的情感分析法以创建酒店字典：以TripAdvisor酒店评论为样本的大数据分析

对于在线游客评论的研究在过去的几年中与日俱增, 但是仍缺乏有效方法能在有限的时间喝预算内提供终端用户价值。本论文开发并测试了一套情感分析的新方法, 创建两套酒店相关的词库, 此方法超越了标准词典式分析法。

研究样本为TripAdvisor酒店客户评论的大数据, 通过开发崭新的有配重的词库法, 来开展两极式情感分析。这个崭新的具有配重的词库法能够呈现透明化和可复制的程序, 准备、创建、并检验情感分析的词条。这个方法用到了两种词典（有配重的词典L1和手动选择的词典L2）, 本论文通过对TripAdvisor大数据进行使用词类划分精准度, 来检测和验证这两种词典。本论文采用两种热门方法（公共词典法和复杂机器学习算法）来对比词典的准确度。

精确度对比结果证实了本论文的方法, 相较于机器学习算法, 显著地超越了以字典为基础的方法。研究结果还表明, 本论文的方法可以就预测用户情感趋势进行推广。

本论文开发并验证了一项方法, 这种方法通过创建可信的词典进行大数据分析, 以判定用户情感。本论文创建的L2酒店词库对分析客人反馈是可靠有用的工具, 这个词库还能帮助酒店经理了解、预测、以及积极相应客人的态度和改变。本论文还提出了一项可以了解每个用户情感的简易方法, 这项方法可以通过对比的方式来检测和了解客人不同时间的情感变化, 以及根据其不同背景和经历的不同用户之间的变化。

本论文提出并检测了一项新方法, 这项情感分析方法可以解决之前方法的局限并立脚于旅游行业。基于文献综述, 本论文是首篇研究, 使用词库法来进行情感分析和创建特别领域词典的方式。

Hotel employees’ occupational stigma is often overlooked. Exploration of hotel employees’ occupational stigma representations, perception pathways and destigmatization provides an empirical basis for positive organizational behavior and psychology in the hotel industry. Therefore, this study aims to better understand the mechanism underlying inherent of occupational stigma.

This study adopts a five-factor narrative analysis involving stigma narrative interviews with a purposed sampling of hotel employees (n = 18). Based on occupational stigma and resource conservation theories, this study designed a five-factor narrative analysis structure chart as the basis for data analysis.

Findings indicate the existence of four quadrants of perceived occupational stigma attribute distribution, two paths of perceived occupational stigma formation and a more systematic occupational destigmatization mechanism path.

The occupational destigmatization path and countermeasures proposed in this study can resolve talent drain and eliminate stereotyping in the hotel industry, which promote the industry’s rapid recovery and sustainable healthy development, providing the practical management guidelines for public communication via social media, and offer practical significance for existing hotel human resource management in modules such as organizational culture and training.

This study broadens investigations of occupational stigma in a single, static context and explains the relationship between hotel employees’ stigma perceptions and destigmatization paths. Further, the mechanism of emotional energy distribution on spatial stigma was identified. These results have practical implications for organizational culture, training and employee care in hotel human resource management.

Software vulnerabilities have been the greatest threat to the software industry for a long time. Many detection techniques have been developed to address this kind of issue, such as Fuzzing, but mere Fuzz Testing is not good enough, because the Fuzzing only alters the input of program randomly, and does not consider the basic semantics of the target software. The purpose of this paper is to introduce a new vulnerability exploring system, called “SEVE” to explore the target software more deeply and to generate more test cases with more accuracy.

Symbolic execution is the core technique of SEVE. The user can just input a standard input, and the SEVE system will record the execution path, alter the critical branches of it, and generate a totally different test case which will make the software under test execute a different path. In this way, some potential bugs or defects, even the exploitable vulnerabilities will be discovered. To alleviate path explosion, the authors propose heuristic method and function abstraction, which in turn improve the performance of SEVE even further.

We evaluate SEVE system to record critical data about its efficiency and performance. We have tested some real‐world vulnerabilities, from which the underlying file‐input programs suffer. After that, the results show that SEVE is not only re‐creating the discovery of these vulnerabilities, but also at a higher performance level than traditional techniques.

The paper proposes a new vulnerability exploring system, called “SEVE” to explore the target software and generate test cases automatically and also heuristic method and function abstraction to handle path explosion.

Discussion of China's one-child policy generally centres on its demographic effects. Bereavement among parents of singleton children and the role of social capital in the bereavement process have been under-explored. The purpose of this paper is to focus on mothers who lost their only children during the Sichuan earthquake in 2008. The paper aims to discuss the under-explored yet crucial issues of the one-child policy – the ways in which Chinese bereaved mothers handle the death of their singleton children – and the roles that social capital can play in their bereavement process.

The author conducted eight case studies on bereaved mothers through home visits, semi-structured interviews and participation in public activities during August 2010 and May 2011. In-depth interviews were used to collect information from these bereaved mothers in Sichuan, China.

The case studies reveal two major experiences of bereaved mother whose familial support varies substantially. One major experience is shared by those who had received emotional support from husband (who offered bonding social capital), and were able to get through the psychological pain. Another experience is shared by bereaved mothers who lost their familial relations. Weak social ties (i.e. an NGO which offered bridging social capital) remained the only source of support. Policies can target at the latter group of mothers by helping them to organise themselves into community-based groups and help to relieve their frustration and grief.

These research findings have implications for the development of NGOs, as well as complementary support for community-based bereavement counselling and community care in China.

Reverse supply chain (RSC) is one of the ways to handle product returns efficiently. Recovery of residual value from product returns also helps in achieving sustainability. Its successful implementation requires coordination among all the channel members involved in the activities, from the acquisition to collection to the disposition of returned products. This article aims to review the literature about coordination issues in the RSC.

A systematic literature review of 151 articles published during 2004–2021 is carried out. Theory, context and methodology (TCM) framework of the literature review is used to identify the research gaps for future research directions.

This study identifies the characteristics of RSC coordination. It includes channel structures; coordination mechanisms; performance measuring parameters; the methodology applied and explored industries. The review shows that game-theoretical modeling in RSC coordination is the most commonly used method to coordinate the channels. It was found that issues like disruption, fairness and corporate social responsibility are not explored in-depth and offer much potential for future research.

There are very limited studies on coordination issues in the RSC. The proposed articles add value by considering RSC issues from different strategic, government, consumers' behavior and functionality decision-making point of view.