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Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

Because of the advantages of high deposition efficiency and low manufacturing cost compared with other additive technologies, robotic wire arc additive manufacturing (WAAM) technology has been widely applied for fabricating medium- to large-scale metallic components. The additive manufacturing (AM) method is a relatively complex process, which involves the workpiece modeling, conversion of the model file, slicing, path planning and so on. Then the structure is formed by the accumulated weld bead. However, the poor forming accuracy of WAAM usually leads to severe dimensional deviation between the as-built and the predesigned structures. This paper aims to propose a visual sensing technology and deep learning–assisted WAAM method for fabricating metallic structure, to simplify the complex WAAM process and improve the forming accuracy.

Instead of slicing of the workpiece modeling and generating all the welding torch paths in advance of the fabricating process, this method is carried out by adding the feature point regression branch into the Yolov5 algorithm, to detect the feature point from the images of the as-built structure. The coordinates of the feature points of each deposition layer can be calculated automatically. Then the welding torch trajectory for the next deposition layer is generated based on the position of feature point.

The mean average precision score of modified YOLOv5 detector is 99.5%. Two types of overhanging structures have been fabricated by the proposed method. The center contour error between the actual and theoretical is 0.56 and 0.27 mm in width direction, and 0.43 and 0.23 mm in height direction, respectively.

The fabrication of circular overhanging structures without using the complicate slicing strategy, turning table or other extra support verified the possibility of the robotic WAAM system with deep learning technology.

This paper aims to review norms and their relationship with consumer behavior in the tourism sector. The review aims to identify gaps in relation to various norms and their impact on the literature to provide future research recommendations.

A systematic literature review method was used to analyze norms in consumer behavior research within the context of tourism and hospitality. The review focused on the research context, conceptualizations, roles, measurements, theoretical backgrounds and the major findings.

The review reveals that the conceptualizations and dimensionality of norms in the existing studies are inconsistent, and most research in the tourism context only adopted the concept partially without capturing the totality of the concept. The theoretical gaps and measurement of norms were also identified for future research.

This study contributes to a better understanding of the role of norms in shaping tourist behavior and can guide practitioners in developing effective marketing strategies. The findings suggest the need for a more comprehensive understanding of the concept of norms in tourism in relation to theoretical underpinnings, measurement and application. The recommendations provided in this study can guide future research on norms and tourist behavior.

Norms have been extensively discussed in the literature. This paper is the first to systematically review norms and their influence on consumer behavior in the tourism sector.

本文审视规范及其与旅游业消费者行为的关系。此审查旨在确定关于各种规范及其对文献的影响的差距, 并提供未来研究建议。

采用系统文献综述方法, 分析了旅游和酒店消费者行为研究中的规范。审查侧重于研究背景、概念化、角色、测量方法、理论背景和主要发现。

审查发现现有研究中规范的概念化和维度存在不一致性, 而大多数旅游环境下的研究只部分采用了该概念, 未能完整捕捉概念的整体。还确定了未来研究中规范的理论差距和测量问题。

本研究有助于更好地理解规范在塑造游客行为中的作用, 并可以指导从业者制定有效的营销策略。研究结果表明, 需要更全面地理解规范概念在旅游中的理论基础、测量和应用。本研究提供的建议可以指导未来关于规范和游客行为的研究。

规范在文献中已经广泛讨论。本文是第一个系统地审查规范及其对旅游业消费者行为的影响。

Este artículo examina las normas y su relación con el comportamiento del consumidor en el sector turístico. El objetivo de la revisión es identificar brechas con relación a diversas normas y su impacto en la literatura, para proporcionar recomendaciones en futuras investigaciones.

Se empleó un método de revisión sistemática de la literatura para analizar las normas en la investigación del comportamiento del consumidor en el contexto del turismo y hostelería. La revisión se centró en el contexto de investigación, conceptualizaciones, roles, medidas, fundamentos teóricos y los principales hallazgos.

La revisión revela que las conceptualizaciones y la dimensionalidad de las normas en los estudios previos son inconsistentes, y la mayoría de las investigaciones en el contexto del turismo solo adoptaron parcialmente el concepto sin capturar la totalidad de este. También se identificaron lagunas teóricas y medición de las normas para futuras investigaciones.

Este estudio contribuye a una mejor comprensión del papel de las normas en la formación del comportamiento turístico y puede orientar a los profesionales en el desarrollo de estrategias de marketing efectivas. Los resultados sugieren la necesidad de una comprensión más holística del concepto de normas en el turismo en relación con los fundamentos teóricos, la medición y la aplicación. Las recomendaciones proporcionadas en este estudio pueden guiar futuras investigaciones sobre normas y comportamiento turístico.

Las normas han sido ampliamente discutidas en la literatura. Este artículo es el primero en revisar sistemáticamente las normas y su influencia en el comportamiento del consumidor en el sector turístico.

The present research investigates the effects of green supply chain management (GSCM) practices on customer behavioural intentions (e.g. word of mouth [WOM], willingness to pay [WTP] and revisit intention [RI]) and the mediating role of customer satisfaction (CS) in the hospitality industry in Bangladesh.

The authors applied a convenience sampling approach to distribute questionnaires and collect opinions from 404 customers who stayed in Bangladesh's five- and four-star hotels. SmartPLS was applied to examine the proposed hypothesised model.

GSCM practices have positive and significant impacts on CS and behavioural intentions of customers' WOM, WTP and RI. Additionally, CS mediates the association between GSCM practices and three behavioural intentions.

To boost their hotel's financial performance, hoteliers should allocate more resources to improving environmental sustainability practices in supply chain management.

This study's novel contribution to the literature rests in the findings regarding the mediating effect of CS. This adds value to the theory of planned behaviour. Another unique contribution of this study is that it combines three behavioural intentions (willingness to pay, RI and WOM).

This paper aims to present the fabrication of 6061 aluminum alloy (AA6061) using a promising laser additive manufacturing process, called the laser-foil-printing (LFP) process. The process window of AA6061 in LFP was established to optimize process parameters for the fabrication of high strength, dense and crack-free parts even though AA6061 is challenging for laser additive manufacturing processes due to hot-cracking issues.

The multilayers AA6061 parts were fabricated by LFP to characterize for cracks and porosity. Mechanical properties of the LFP-fabricated AA6061 parts were tested using Vicker’s microhardness and tensile testes. The electron backscattered diffraction (EBSD) technique was used to reveal the grain structure and preferred orientation of AA6061 parts.

The crack-free AA6061 parts with a high relative density of 99.8% were successfully fabricated using the optimal process parameters in LFP. The LFP-fabricated parts exhibited exceptional tensile strength and comparable ductility compared to AA6061 samples fabricated by conventional laser powder bed fusion (LPBF) processes. The EBSD result shows the formation of cracks was correlated with the cooling rate of the melt pool as cracks tended to develop within finer grain structures, which were formed in a shorter solidification time and higher cooling rate.

This study presents the pioneering achievement of fabricating crack-free AA6061 parts using LFP without the necessity of preheating the substrate or mixing nanoparticles into the melt pool during the laser melting. The study includes a comprehensive examination of both the mechanical properties and grain structures, with comparisons made to parts produced through the traditional LPBF method.

The aim of this paper is to solve the toxic and harmful problems caused by traditional volatile corrosion inhibitor (VCI) and to analyze the effect of the layered structure on the enhancement of the volatile corrosion inhibition prevention performance of amino acids.

The carbon dots-montmorillonite (DMT) hybrid material is prepared via hydrothermal process. The effect of the DMT-modified alanine as VCI for mild steel is investigated by volatile inhibition sieve test, volatile corrosion inhibition ability test, electrochemical measurement and surface analysis technology. It demonstrates that the DMT hybrid materials can improve the ability of alanine to protect mild steel against atmospheric corrosion effectively. The presence of carbon dots enlarges the interlamellar spacing of montmorillonite and allows better dispersion of alanine. The DMT-modified alanine has higher volatilization ability and an excellent corrosion inhibition of 85.3% for mild steel.

The DMT hybrid material provides a good template for the distribution of VCI, which can effectively improve the vapor-phase antirust property of VCI.

The increased volatilization rate also means increased VCI consumption and higher costs.

Provides a new way of thinking to replace the traditional toxic and harmful VCI.

For the first time, amino acids are combined with nano laminar structures, which are used to solve the problem of difficult volatilization of amino acids.

The paper aims to present an experimental and numerical investigation of the load–settlement behavior of soil reinforced by stone column, as well as to evaluate the plane strain unit cell model for the analysis of stone columns.

The numerical analysis was done using both axisymmetric and plane strain models. The elastic perfectly plastic behavior of Mohr–Coulomb was adopted for both soil and column material. The numerical results of this study were validated by the comparison with the in-situ measurements of a full-scale loading test on a stone column. This study also evaluated the effect of different parameters involved in the design of a stone column, including Young’s modulus of the column material, column diameter, spacing between the stone columns and Poisson’s ratio of the column material.

After the numerical simulation, the results from both axisymmetric and plane strain models are quite comparable. In addition, the numerical results revealed that the stone column with low spacing, a large diameter and a high Young’s modulus indicated better behavior against the settlement.

The axisymmetric unit cell model was used in many numerical studies on the behavior of stone columns. In the present work, a field load test on stone column was simulated using a plane strain unit cell model. This research adds that the plane strain unit cell model can be used to predict the settlement of reinforced soil with stone columns.

This study aims to extend the literature on psychological contracts, employee mental health, self-control and equity sensitivity among employees in Ghana.

Data for this study came from a sample of 484 employees from an organisation in the telecommunication sector of Ghana. The details of the study were discussed with employees after which they were given the choice to participate in the study.

The present study found that psychological contract breach is directly associated with mental health and indirectly related to mental health through equity sensitivity and self-control.

The findings suggest that psychological contracts are important aspects of the employment relationship that could be used to enhance employee mental health. Furthermore, enhancing employees’ self-control and resolving issues of individuals high on equity sensitivity are effective ways that organisations can deploy to sustain mental health in the face of psychological contract breaches.

Strategic flexibility (SF) has become increasingly important for firms because of the fast changes in the external environment. In line with the practical importance of SF, an emerging research field has developed around it that has attempted to understand the nature of SF and the key relationships. The aim of this study is to unveil the semantic structure of the recent literature on SF and to suggest new promising areas for future research.

The authors conduct a systematic literature review with a bibliographic analysis technique, which allows authors to identify the main recent streams in the literature, as well as offer reflections and suggestions for future research.

The authors uncover three main emerging areas in the research on SF, namely SF as a dynamic capability, the role of knowledge management for SF and the relationship between a firm SF and the external environment. The authors put forward three avenues for future research on SF: Avenue 1. SF, business model innovation (BMI) and other dynamic capabilities (DC), Avenue 2. Digital technologies and SF/organizational agility and Avenue 3. SF and sustainability. Articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2, thus paving the way for filling some of the identified gaps regarding the relationship between SF and digitalization.

To the best of authors’ knowledge, this is the first literature review on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. The review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time, as well as by presenting three main avenues for further developing authors’ knowledge around SF.

This study aims to explore the impact of systematic liquidity risk on the averaged cross-sectional equity return of the Indian equity market. It also examines the effects of illiquidity and decomposed illiquidity on the conditional volatility of the equity market.

The present study employs the Liquidity Adjusted Capital Asset Pricing Model (LCAPM) for pricing systematic liquidity risk using the Fama & MacBeth cross-sectional regression model in the Indian stock market from January 1, 2012, to March 31, 2021. Further, the study employed an exponential generalized autoregressive conditional heteroscedastic (1,1) model to observe the impact of decomposed illiquidity on the equity market’s conditional volatility. The study also uses the Ordinary Least Square (OLS) model to illuminate the return-volatility-liquidity relationship.

The study’s findings indicate that the commonality between individual security liquidity and aggregate liquidity is positive, and the covariance of individual security liquidity and the market return negatively affects the expected return. The study’s outcome specifies that illiquidity time series analysis exhibits the asymmetric effect of directional change in return on illiquidity. Further, the study indicates a significant impact of illiquidity and decomposed illiquidity on conditional volatility. This suggests an asymmetric effect of illiquidity shocks on conditional volatility in the Indian stock market.

This study is one of the few studies that used the World Uncertainty Index (WUI) to measure liquidity and market risks as specified in the LCAPM. Further, the findings of the reverse impact of illiquidity and decomposed higher and lower illiquidity on conditional volatility confirm the presence of price informativeness and its immediate effects on illiquidity in the Indian stock market. The study strengthens earlier studies and offers new insights into stock market liquidity to clarify the association between liquidity and stock return for effective policy and strategy formulation that can benefit investors.