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As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

Relying on a multilevel approach, this paper investigates the day-to-day variations in family-supportive supervisor behaviors influencing subordinates' job stress, as well as the mediating role of positive emotions and the moderating role of ethical leadership.

Using the experience-sampling methodology, the study collected the data from 137 civil servants in China who responded to one daily survey for 10 working days.

With a total of 1,370 surveys, results supported the hypothesized model linking daily family-supportive supervisor behaviors to daily job stress via subordinates' daily positive emotions. In addition, the study found a moderating effect for ethical leadership positively in the indirect relationship between family-supportive supervisor behaviors and job stress.

The findings in this study serve practitioners in organizational and leadership development. For one thing, this study contributes to raising awareness about the importance of improving family-related support in the workplace in generating subordinates' positive emotions and relieving their job stress. For another, the findings highlight the necessity of cultivating ethical leadership for leaders.

This study fulfills an identified need to clarify how and when daily family supportive supervisor behaviors influence subordinates' daily job stress. This study moves beyond previous research by adopting the experience sampling method and demonstrating important cross-level effects of ethical leadership on the within-individual relationship between family supportive supervisor behaviors and job stress.

This study aims to examine the empirical linkages among emotional experiences, national identity and behavioural intentions for red tourism in China.

Partial least squares structural equation modelling was applied to data from two rounds of surveys of 1,095 on-site visitors to Zunyi and Yan’an, two well-known red tourism cities in China.

Emotional experiences significantly affect national identity, with positive emotions significantly affecting national identity. Positive emotions also significantly influenced behavioural intentions, national identity positively influenced behavioural intentions and national pride mediated the relationship of “positive emotion → behavioural intentions”. In addition, previous experience played a moderating role in the relationship of “positive emotion → national pride”.

This research produced new insights on red tourism emotional experiences by clarifying its types, connotations and influences. It contributes to a better understanding of national identity antecedents and outcomes in red tourism. Findings revealed the significant role of red tourism in cultivating national identity and provide implications for academic research and practical development of red tourism.

本研究旨在考察中国红色旅游者的情绪体验、国家认同和行为意向之间的影响关系及其作用机制。

采用偏最小二乘法结构方程模型(PLS-SEM), 对来自中国红色旅游圣地——遵义和延安的1095名现场游客的问卷调查数据进行了统计分析。

情绪体验对国家认同会产生显著影响。其中, 积极情感会显著正向影响国家认同。同时, 积极情感也会对行为意向产生显著正向影响。此外, 国家认同对行为意向具有积极影响, 且国家自豪感在“积极情感→行为意图”的影响关系中充当中介作用。最后, 研究还发现旅游经历在“积极情感→国家自豪感”的影响关系中具有显著的调节作用。

本研究通过阐明红色旅游情绪体验的类型、内涵及其影响关系, 为深入理解红色旅游情绪体验提供了一个全新的视角。同时, 文章还进一步厘清了红色旅游情境中国家认同感的形成前因和影响结果的作用机理。研究结论揭示了红色旅游在培育国家认同感方面的重要价值, 并为红色旅游的学术研究和实践发展提供了重要启示。

Esta investigación examinó los vínculos empíricos entre las experiencias emocionales, la identidad nacional y las intenciones de comportamiento para del turismo rojo en China.

Se aplicó el análisis de ecuaciones estructurales basado en mínimos cuadrados parciales (PLS - SEM) a los datos recogidos mediante dos rondas de encuestas realizadasa 1.095 visitantes in situ en Zunyi y Yan'an, dos conocidas ciudades de turismo rojo de China.

Las experiencias emocionales afectan significativamente a la identidad nacional, y las emociones positivas influyen significativamente en la identidad nacional. Las emociones positivas también influyeron significativamente en las intenciones de comportamiento; la identidad nacional influyó positivamente en las intenciones de comportamiento y el orgullo nacional medió la relación “emoción positiva → intenciones de comportamiento”. Además, la experiencia previa desempeñó un papel moderador en la relación “emoción positiva → orgullo nacional”.

Esta investigación aportó nuevos hallazgos sobre las experiencias emocionales del turismo rojo al aclarar sus tipos, connotaciones e influencias. Contribuye a una mejor comprensión de los antecedentes y resultados de la identidad nacional en el turismo rojo. Los resultados de la investigación revelan el importante papel del turismo rojo en el cultivo de la identidad nacional y ofrecen implicaciones para la investigación académica y el desarrollo práctico del turismo rojo.

The purpose of this paper is to propose a multivariate-based method to classify products in replenishment categories based on principal component analysis (PCA) along with two classification algorithms, k-nearest neighbor (KNN) and linear discriminant analysis (LDA).

In the propositions, PCA is applied to data describing products’ features and demand behavior, and a variable importance index (VII) is derived based on PCA parameters. Next, products are allocated to inventory replenishment models applying the KNNs to all original variables; the classification accuracy is then assessed. The variable with the smallest VII is removed and a new classification is carried out; this iterative procedure is performed until a single variable is left. The subset yielding the maximum classification accuracy is recommended for future classification. The aforementioned procedure is repeated replacing the KNN by the LDA.

When applied to real data from a consulting company, the KNN classification technique led to higher performance levels than LDA, yielding 89.4 percent average accuracy and retaining about 80 percent of the original variables. On the other hand, LDA reached 87.1 percent average accuracy and retained 95 percent of the variables. Based on such results, the authors’ findings suggest that 14 out of the 24 variables are crucial in determining an inventory replenishment model for a product in a specific location replacement. Several of the retained variables were typically used in reorder point estimation or associated to market profile in specific locals.

The idea of this paper is to remove irrelevant and noisy market metrics that jeopardize the correct allocation of products to the most appropriate replenishment model.