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Brief loving-kindness meditation (LKM) is introduced here as a valid social marketing intervention. LKM positively influences prosocial cognitions and affects. However, it remains unclear whether brief meditation interventions can influence prosocial behavior. This study aims to provide evidence of the effects of short LKM on prosocial behavior.

This study reports the results of three experiments examining the effects of brief LKM on donations to unknown others. The results are then integrated with the results of seven other studies testing the effects of brief LKM on prosocial behavior using a meta-analysis (n = 683).

LKM increased love more than the control group (focused breathing) in the three experiments; however, its effects on donations were mixed. The meta-analysis shows that LKM has a small-to-medium significant effect compared to active control groups (d = 0.303); moreover, age and type of prosocial measure used moderate the effects.

Results suggest that LKM can nurture prosocial emotions such as love and lead young individuals to donate. However, these emotions may not be sufficient to lead adult meditators to share their resources with unknown others. This study presents the first meta-analysis of brief LKM and provides insights into the use of meditation in social marketing programs.

Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

This paper aims to present a set of processes for obtaining the global spraying trajectory of a cold spraying robot on a complex surface.

The complex workpiece surfaces in the project are first divided by triangular meshing. Then, the geodesic curve method is applied for local path planning. Finally, the subsurface trajectory combination optimization problem is modeled as a GTSP problem and solved by the ant colony algorithm, where the evaluation scores and the uniform design method are used to determine the optimal parameter combination of the algorithm. A global optimized spraying trajectory is thus obtained.

The simulation results show that the proposed processes can achieve the shortest global spraying trajectory. Moreover, the cold spraying experiment on the IRB4600 six-joint robot verifies that the spraying trajectory obtained by the processes can ensure a uniform coating thickness.

The proposed processes address the issue of different parameter combinations, leading to different results when using the ant colony algorithm. The two methods for obtaining the optimal parameter combinations can solve this problem quickly and effectively, and guarantee that the processes obtain the optimal global spraying trajectory.

This paper delves into cross-border E-business, unraveling its intricate dynamics and forecasting its future trajectory.

This paper projects the prospective market size of cross-border E-business in China for the year 2023 using the GM (1,1) gray forecasting model. Furthermore, to enhance the analysis, the paper attempts to simulate and forecast the size of China’s cross-border E-business sector using the GM (1,3) gray model. This extended model considers not only the historical trends of cross-border E-business but also the growth patterns of GDP and the digital economy.

The forecast indicates a market size of 18,760 to 18,934 billion RMB in 2023, aligning with the consistent growth observed in previous years. This suggests a sustained positive trajectory for cross-border E-business.

Cross-border e-commerce critically shapes China’s global integration and traditional industry development. The research in this paper provides insights beyond statistical trends, contributing to a nuanced understanding of the pivotal role played by cross-border e-commerce in shaping China’s economic future.

The purpose of this paper is to examine the consumer response to brands offering gendered product differentiation (i.e. products “for her” or “for him”).

Across three experiments, the effect of gendered (vs gender-unrelated) product differentiation on perceived brand sexism and word-of-mouth intention was tested. The moderating effects of feminist identity (Studies 1 and 2), endorsement of sexist beliefs (Study 2) and basis (stereotypical vs biological) for product differentiation (Study 3) were also tested.

Consumers perceive brands that offer gendered product differentiation as sexist, which in turn leads to negative word-of-mouth intention. Moreover, consumers with a strong feminist identity are more likely to perceive brands that offer gendered product differentiation as sexist, whereas consumers who endorse sexist beliefs are less likely to do so. Finally, consumers respond negatively when the gendered product differentiation is based on a gender stereotype, but much less so when it seems based on a biological difference between sexes.

Although multiple brands offering gendered products have been denounced by consumers as sexist, no research has examined this phenomenon. This paper pioneers in examining the consumer response to brands offering gendered product differentiation and in demonstrating that consumers perceive such brands as sexist.

The purpose of this study is to examine approaches used by university libraries to enhance the visibility and utilization of research support services (RSSs) among doctoral students and to assess the competencies of library staff in delivering research support services.

This study used qualitative design approach, purposively sampled 40 librarians (8 university librarians and 32 librarians) in charge of RSSs and use of structured interview.

The findings of this study revealed three major themes: offline and online strategies, the need for upskilling and professional development programs and proactive empowerment.

This study focused on research support services in chartered public universities in Kenya; private universities were not included.

The need to enhance library staff's ongoing professional development programs, increasing funding to university libraries and proactivity by the libraries to improve the provision and promotion of RSSs to doctoral students in Kenya.

There are limited existing literature in the Kenyan context. This study will fill a knowledge gap and contribute to the literature on academic libraries support and doctoral students experience in Kenyan context.

Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

To extend research into sport consumer behaviors related to online sports betting, this study is designed to identify and examine the relationship between online sports betting motivations and online sports betting intentions. By applying a push-pull framework from online sport consumption and gambling studies, nine motivations to engage in online sports betting were identified. These motivations were hypothesized to motivate online sports betting intentions.

A quota sampling technique based on the sports bettor demographics available in the American Gaming Association (AGA, 2019) and the Pew Research Center (2022) obtained a total of 550 completed surveys that met the inclusion and exclusion criteria. For data analyses, confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to examine the measurement model and the hypothesized model, respectively.

The results revealed that four motivations (i.e. monetary gain, excitement, convenience and negative technology-readiness) were related to online sports betting intention, while five motivations (i.e. sport fandom, positive technology-readiness, impulsivity, socialization and promotion) were not.

The results provide foundational theoretical knowledge of what motivates sports fans to participate in online sports betting. Furthermore, the findings assist practitioners in their allocation of resources by enhancing their understanding of online sports betting motivations.

Vietnam has repositioned itself from a war-torn country to a popular tourist destination. Although research on Vietnam tourism has grown in number, a macro analysis of national tourism governance and policies has largely been missing.

This synthesis paper offers a systemic analysis of Vietnam’s tourism accommodating intensified government intervention and dramatic market changes in recent decades. The authors offer a chronological analysis of tourism development along with the major political and economic turns of the country.

The patterns of tourism development reflect a compromise between centralization and decentralization of the governance system and a trade-off between economic and social objectives of development. Balancing these opposites, the internal strength of the domestic market and the resilience of communities and businesses become key assets for growth in circumstances where the socialist market economy continues to inform the current and future development of the industry.

Although the case of Vietnam is unique, the adaptive mechanism of the tourism industry highlighted in this paper offers a useful lesson for other developing countries. The research addresses tourism in the political economy in developing countries, which is valuable for researchers, policy analysts as well as practitioners in tourism.

The practical contribution of the study is derived from authors’ academic and industrial backgrounds. Findings from the study serve as a useful reference for those who embark on the study of tourism governance and policy-making in developing countries and problems associated with the economic transitional process. Those problems of the disparity between centralization and decentralization of the political system might not be only significant in Vietnam, but also prevail in developing countries. Thus, this study offers a point of departure for future empirical and comparative research on the kindship of tourism and political economy in a full scale.

The transitional economy as viewed through the tourism industry is prominently presented in the “evolutionary” approach to the transitional economy, which exhibits several unique features: the transition from a centrally planned (command) economy to a market economy and the manifestations of a socialist orientation in the modern economic management system (Vuong et al., 2019). While data from this study is mainly illustrative of the first point, the transition from a planned economy to a market economy, the second characteristic, the manifestation of a social orientation has only slightly been addressed and will need further elaboration in a future study. While Vietnam’s tourism positions itself in a socialist market-oriented economy might set a unique case, the study highlights the politics of tourism is shaped by the politico-economic system. The authors conclude that the adaptation of Vietnam tourism to a socialist market-orientated economy is better perceived as a social evolution achievement rather than a feature of capitalism.

The latest study on tourism governance (Bui et al., 2022) has outlined the evolution of the tourism administrative system and markets in the country; however, linkages of tourism to the broader political economic system have yet to be addressed. Addressing this gap, the authors carry out analysis of policies and governance from the insider’s viewpoint, when team members have been involved in numerous tourism planning and development projects, both on international and national scales. The practical experience along with thorough review of literature and statistical data contributes to shaping a fresh understanding of tourism in a transitional economy.

这篇综述对越南旅游业进行了系统分析, 包括近几十年来不断增强的政府干预以及巨大的市场变化。作者根据时间顺序分析了旅游业的发展以及该国的主要政治及经济的转变。此外, 政策文件的内容分析及旅游市场分析进一步说明了政治经济体系对旅游治理及政策的影响。

越南已将自己从一个饱受战争的国家重新定位成备受欢迎的旅游目的地。尽管对越南旅游业的研究不断增多, 但对国家旅游治理和政策的宏观分析却被之前的探究所忽略。此研究通过展示越南转型经济中的旅游治理模式连接了两个学科, 并且丰富了政治经济学和旅游学的文献。

旅游政策和市场分析反应了治理体系集权与分权之间的折中以及经济和社会发展目标之间的权衡。国内市场的内在优势以及社区及企业的韧性可以成为成长的关键资产来平衡这些对立面, 同时社会主义市场经济将继续影响产业的当前及未来的发展。因此我们的结论是, 越南旅游业适应社会主义市场经济应该被视为社会进化的成就, 而不是资本主义的特征。

考虑到一篇文章所能解决的问题有限, 作者无法就转型经济与中国进行比较研究。我们的研究为未来亚洲旅游与政治经济之间联系的实证和比较研究提供了一个出发点。

研究结果为发展中国家旅游治理和政策制定研究提供了有益的参考。

研究结果对于发展中国家旅游治理及政策制定研究具有重要参考意义。这项研究的成果对于发展中国家的旅游政策分析师, 特别是亚洲的研究人员来说很有价值。

当前的研究弥补了政治经济学中的一个研究不足, 即马克思主义学说及其与旅游业的对话。知识转移是本研究的一个亮点, 它源自对国家政治经济议程中的旅游治理的批判性分析。

Vietnam ha pasado de ser un país devastado por la guerra a convertirse en un popular destino turístico. Aunque la investigación sobre el turismo en Vietnam ha crecido en número, ha faltado en gran medida un macroanálisis de la gobernanza y las políticas turísticas nacionales. Nuestra investigación ha enriquecido la literatura tanto de la economía política como del turismo tendiendo un puente entre ambas disciplinas al presentar las pautas de la gobernanza del turismo en la economía de transición de Vietnam.

Este documento de síntesis ofrece un análisis sistemático del turismo de Vietnam que abarca la intensificación de la intervención gubernamental y los drásticos cambios del mercado en las últimas décadas. Los autores ofrecen un análisis cronológico del desarrollo del turismo junto con los principales giros políticos y económicos del país. Además, el análisis del contenido de los documentos políticos y el análisis del mercado turístico ilustran mejor las repercusiones de los sistemas político-económicos en la gobernanza y las políticas turísticas.

Las políticas turísticas y el análisis del mercado revelan un compromiso entre la centralización y la descentralización del sistema de gobernanza y un compromiso entre los objetivos económicos y sociales del desarrollo. Al equilibrar estos opuestos, la fuerza interna del mercado nacional y la resistencia de las comunidades y las empresas se convierten en activos clave para el crecimiento en unas circunstancias en las que la economía de mercado socialista sigue informando el desarrollo actual y futuro de la industria. Concluimos que la adaptación del turismo vietnamita a una economía socialista orientada al mercado se percibe mejor como un logro de la evolución social que como una característica del capitalismo.

Dentro del limitado abanico de cuestiones que podrían abordarse en un solo artículo, los autores no pueden establecer un estudio comparativo con China, en lo que respecta a la economía de transición. Nuestro estudio ofrece un punto de partida para futuras investigaciones empíricas y comparativas sobre la conexión entre turismo y economía política en Asia.

Las conclusiones del estudio sirven de referencia útil para quienes se embarcan en el estudio de la gobernanza y la formulación de políticas turísticas en los países en desarrollo.

Los resultados de la investigación son valiosos para los investigadores del sudeste asiático en particular y para los analistas de la política turística del mundo en desarrollo en general.

La presente investigación contribuye a un área poco investigada de la economía política, a saber, la doctrina marxista y su diálogo con el turismo. La transferencia de conocimientos es un aspecto destacado de esta investigación, que se ha derivado de un análisis crítico de la gobernanza del turismo en la agenda económica política nacional.