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Bolted joint is the most important connection method in aircraft composite/metal stacked connections due to its large load transfer capacity and high manufacturing reliability. Aircraft components are subjected to complex hybrid variable loads during service, and the mechanical properties of composite/metal bolted joint directly affect the overall safety of aircraft structures. Research on composite/metal bolted joint and their mechanical properties has also become a topic of general interests. This article reviews the current research status of aeronautical composite/metal bolted joint and its mechanical properties and looks forward to future research directions.

This article reviews the research progress on static strength failure and fatigue failure of composite/metal bolted joint, focusing on exploring failure analysis and prediction methods from the perspective of the theoretical models. At the same time, the influence and correlation mechanism of hole-making quality and assembly accuracy on the mechanical properties of their connections are summarized from the hole-making processes and damage of composite/metal stacked structures.

The progressive damage analysis method can accurately analyze and predict the static strength failure of composite/metal stacked bolted joint structures by establishing a stress analysis model combined with composite material performance degradation schemes and failure criteria. The use of mature metal material fatigue cumulative damage models and composite material fatigue progressive damage analysis methods can effectively predict the fatigue of composite/metal bolted joints. The geometric errors such as aperture accuracy and holes perpendicularity have the most significant impact on the connection performance, and their mechanical responses mainly include ultimate strength, bearing stiffness, secondary bending effect and fatigue life.

Current research on the theoretical prediction of the mechanical properties of composite/metal bolted joints is mainly based on ideal fits with no gaps or uniform gaps in the thickness direction, without considering the hole shape characteristics generated by stacked drilling. At the same time, the service performance evaluation of composite/metal stacked bolted joints structures is currently limited to static strength and fatigue failure tests of the sample-level components and needs to be improved and verified in higher complexity structures. At the same time, it also needs to be extended to the mechanical performance research under more complex forms of the external loads in more environments.

The mechanical performance of the connection structure directly affects the overall structural safety of the aircraft. Many scholars actively explore the theoretical prediction methods for static strength and fatigue failure of composite/metal bolted joints as well as the impact of hole-making accuracy on their mechanical properties. This article provides an original overview of the current research status of aeronautical composite/metal bolted joint and its mechanical properties, with a focus on exploring the failure analysis and prediction methods from the perspective of theoretical models for static strength and fatigue failure of composite/metal bolt joints and looks forward to future research directions.

Entrepreneurship as a development engine has a distinct character in the economic growth of countries. Therefore, governments must support entrepreneurship in order to succeed in the future. The best way to improve the performance of this entrepreneurial advocacy is through efficient measurement methods. For this reason, the purpose of this paper is to propose a new integrated dynamic multi-attribute decision-making (MADM) model based on neutrosophic set (NS) for assessment of the government entrepreneurship support.

Due to the nature of entrepreneurship issues, which are multifaceted and full of uncertain, indeterminate and ambiguous dimensions, this measurement requires multi-criteria decision-making methods in spaces of uncertainty and indeterminacy. Also, due to the change in the size of indicators in different periods, researchers need a special type of decision model that can handle the dynamics of indicators. So, in this paper, the authors proposed a dynamic neutrosophic weighted geometric operator to aggregate dynamic neutrosophic information. Furthermore, in view of the deficiencies of current dynamic neutrosophic MADM methods a compromised model based on time degrees was proposed. The principle of time degrees was introduced, and the subjective and objective weighting methods were synthesized based on the proposed aggregated operator and a nonlinear programming problem based on the entropy concept was applied to determine the attribute weights under different time sequence.

The information of ten countries with the indicators such as connections (C), the country's level of education and experience (EE), cultural aspects (CA), government policies (GP) and funding (F) over four years was gathered and the proposed dynamic MADM model to assess the level of entrepreneurial support for these countries. The findings show that the flexibility of the model based on decision-making thought and we can see that the weights of the criteria have a considerable impact on the final evaluations.

In many decision areas the original decision information is usually collected at different periods. Thus, it is necessary to develop some approaches to deal with these issues. In the government entrepreneurship support problem, the researchers need tools to handle the dynamics of indicators in neutrosophic environments. Given that this issue is very important, nonetheless as far as is known, few studies have been done in this area. Furthermore, in view of the deficiencies of current dynamic neutrosophic MADM making methods a compromised model based on time degrees was proposed. Moreover, the presented neutrosophic aggregation operator is very suitable for aggregating the neutrosophic information collected at different periods. The developed approach can solve the several problems where all pieces of decision information take the form of neutrosophic information collected at different periods.

The US Department of Energy has a goal to make ethanol from biomass cost competitive with petroleum by 2012. Feedstock procurement is expected to represent a significant portion of the operating costs for a refinery that produces ethanol from biomass such as switchgrass. Thus, cost‐effective feedstock logistics will be a key factor for the future development of a capital intensive cellulosic ethanol industry. The purpose of this paper is to analyze the cost of various logistic methods of switchgrass production, harvesting, storing, and transportation.

This study applied enterprise budgeting and geographical information system (GIS) software to analyze the costs of three logistic methods of acquiring switchgrass feedstock for a 25 million gallon per year refinery. Procurement methods included traditional large round and rectangular bale harvest and storage systems and satellite preprocessing facilities using field‐chopped material. The analysis evaluated tradeoffs in operating costs, dry matter losses during storage, and investment requirements among the three systems.

Results suggest that the preprocessing system outperformed the conventional bale harvest methods in the delivered costs of switchgrass.

The cost savings in harvest, transportation, and dry matter losses for the preprocessing system offset their extensive capital costs and generated cost advantages over the conventional methods.

The traditional round bale system has a higher overall investment cost, may not be the most cost‐effective way to procure switchgrass feedstock for a refinery, and may limit farmer participation in the feedstock value chain.

GIS methods combined with enterprise budgeting can be useful tools for evaluating investment in feedstock supply chain infrastructure.

The purpose of this paper is to study the controller design of flexible manipulator. Flexible manipulator system is a nonlinear, strong coupling, time-varying system, which is introduced elastodynamics in the study and complicated to control. However, due to the flexible manipulator, system has a significant advantage in response speed, control accuracy and load weight ratio to attract a lot of researchers.

Since the order of flexible manipulator system is high, designing controller process will be complex, and have a large amount of calculation, but this paper will use the dynamic surface control method to solve this problem.

Dynamic surface control method as a controller design method which can effectively solve the problem with the system contains nonlinear and reduced design complexity.

The authors assume that the dynamic parameters of flexible manipulator system are unknown, and use Radial Basis Function neural network to approach the unknown system, combined with the dynamic surface control method to design the controller.

Following the standard practice of using nutrition claims to denote food functionality, this study empirically explores Chinese consumers’ willingness-to-pay for functional processed meat products by using three nutrition claims (namely “increased calcium,” “containing omega-3”, and “reduced salt”) made on pork sausages. It also aims to outline the typical characteristics of Chinese consumer segments based on preferences.

A choice-based choice experiment is utilized to investigate Chinese consumers’ valuation on attributes of interest regarding functional sausage products. First-hand data was collected in the two cities of Xi'an and Beijing.

There are market potentials for domestic and/or imported functional processed meat products among Chinese consumers. Nutrition claims made on pork sausages are appealing to Chinese consumers, and therefore, monetarily rewarded by them. Being imported from a more developed country of origin could both positively and negatively impact consumers’ WTP for nutrition claims made on pork sausages. Furthermore, specific functional modification strategies should be taken into account when addressing different segments of the Chinese market. In addition, regional impacts between Xi'an and Beijing are implied in terms of consumers’ valuation for functional pork sausages.

Limitations in the current study are mainly two folds. First, the WTP estimation magnitudes are subject to a hypothetical bias by using a stated preference approach. Second, this study only focuses on pork sausages to explore consumers’ perceptions and selects three nutrition claims among many other relevant options.

Implications are provided for meat marketers and for Chinese official food policymakers, such that promoting meat products with a nutrition claim is an attractive marketing strategy for foreign food manufacturers in China, and more reformulated meat products with better nutritional compositions should be allowed in the Chinese market.

To the best of the author’s knowledge, this research is the first to fill in the literature blank on investigating the consumers’ valuation for functional meat in the emerging market of China. Because when taking Chinese consumers as a target market and evaluating their perceptions of food quality-related labeling and certifications, the existing literature is mainly limited to topics of product safety, organic/green products, and geographical origins. However, nutrition claims, as marketable credence attributes that associate closely to the main characteristics of the functional food products, have been explored to a much lesser extent among Chinese consumers.

Continuing economic growth in emerging markets offers large market opportunities to producers and marketers worldwide; however, market failures due to asymmetric information are often seen when high-quality products enter these “new markets” where recognition rates among consumers are low. The use of “geographical origin” labels as quality signals to overcome asymmetric information problem plays an important role. The purpose of this paper is to compare consumers’ perception and willingness to pay (WTP) for different levels of geographic origin labels to provide insights to the strategic use of origin labels in emerging markets.

A consumer survey on geographic labeling for imported dairy products was carried out in Beijing, China in May 2015. Under the “products of European Union (EU)” range, the authors used “product of Ireland” as a case study for the country-specific origin label. Information on consumer demographic, dairy consumption, safety perceptions, knowledge on Ireland and Irish products, as well as WTP for different geographic labeling and product attributes were collected from 307 face-to-face interviews. WTP was elicited using double-bounded contingent valuation method, and estimated with maximum log-likelihood function.

The authors found that consumers are willing to pay premium prices for both of these geographical origin indicators, but the EU label had slightly higher WTP results. However, the controversial situation is that although the EU label has a better chance than the country-specific label in signaling premium quality to Chinese consumers, EU labeling at its best signals an average quality across the EU counties. For premium products with above average quality, using generic EU labeling has a potential drawback to the establishment of product differentiation.

This study is the first to evaluate Chinese consumers’ WTP for EU generic origin label for dairy products in comparison to country-specific origin label. Findings of the study have immediate policy and marketing implications in emerging markets.

The study aims to explore how young consumers perceive and adopt the online e-waste collection platform, by developing a conceptual framework that integrates the theory of planned behavior, the technology acceptance model and the perceived risk. Based on conceptual framework, the study further identifies factors that positively or negatively influence the Chinese millennials' decision on the use of online collection platform.

The study conducts a questionnaire survey from 807 Chinese millennials living in urban and rural areas. Based on the collected data, the partial least squares structural equation modeling (PLS-SEM) is employed to conduct PLS path modeling and multi-group analysis.

The study results support the proposed conceptual framework and confirm its robustness in investigating Chinese millennials' intentions to adopt online e-waste collection platform. The findings suggest that the perceived usefulness, perceived ease of use, attitude, subjective norms and perceived behavioral control have positive impact, while perceived risk has negative impact on the behavioral intentions of millennials on the adoption of the platform.

With the emergence of Internet technology, online e-waste collection platform has arisen as an innovative and alternative solution to improve environmental sustainability by encouraging e-waste collection through formal recycling channels in China. In order to divert the consumers from informal recycling channels to online e-waste collection platform, it is necessary to understand what factors impact the adoption of this platform among consumers. The study provides theoretical contribution and practical implications relevant to regulators and practitioners to encourage the adoption of online e-waste collection platform.

The purpose of this paper is to review recent studies published from 2007 to 2015 on tourism and hotel demand modeling and forecasting with a view to identifying the emerging topics and methods studied and to pointing future research directions in the field.

Articles on tourism and hotel demand modeling and forecasting published mostly in both science citation index and social sciences citation index journals were identified and analyzed.

This review finds that the studies focused on hotel demand are relatively less than those on tourism demand. It is also observed that more and more studies have moved away from the aggregate tourism demand analysis, whereas disaggregate markets and niche products have attracted increasing attention. Some studies have gone beyond neoclassical economic theory to seek additional explanations of the dynamics of tourism and hotel demand, such as environmental factors, tourist online behavior and consumer confidence indicators, among others. More sophisticated techniques such as nonlinear smooth transition regression, mixed-frequency modeling technique and nonparametric singular spectrum analysis have also been introduced to this research area.

The main limitation of this review is that the articles included in this study only cover the English literature. Future review of this kind should also include articles published in other languages. The review provides a useful guide for researchers who are interested in future research on tourism and hotel demand modeling and forecasting.

This review provides important suggestions and recommendations for improving the efficiency of tourism and hospitality management practices.

The value of this review is that it identifies the current trends in tourism and hotel demand modeling and forecasting research and points out future research directions.

Visual simultaneous localization and mapping (SLAM) has limitations such as sensitivity to lighting changes and lower measurement accuracy. The effective fusion of information from multiple modalities to address these limitations has emerged as a key research focus. This study aims to provide a comprehensive review of the development of vision-based SLAM (including visual SLAM) for navigation and pose estimation, with a specific focus on techniques for integrating multiple modalities.

This paper initially introduces the mathematical models and framework development of visual SLAM. Subsequently, this paper presents various methods for improving accuracy in visual SLAM by fusing different spatial and semantic features. This paper also examines the research advancements in vision-based SLAM with respect to multi-sensor fusion in both loosely coupled and tightly coupled approaches. Finally, this paper analyzes the limitations of current vision-based SLAM and provides predictions for future advancements.

The combination of vision-based SLAM and deep learning has significant potential for development. There are advantages and disadvantages to both loosely coupled and tightly coupled approaches in multi-sensor fusion, and the most suitable algorithm should be chosen based on the specific application scenario. In the future, vision-based SLAM is evolving toward better addressing challenges such as resource-limited platforms and long-term mapping.

This review introduces the development of vision-based SLAM and focuses on the advancements in multimodal fusion. It allows readers to quickly understand the progress and current status of research in this field.

This paper aims to provide a comprehensive analysis of the state of the art in energy efficiency for autonomous mobile robots (AMRs), focusing on energy sources, consumption models, energy-efficient locomotion, hardware energy consumption, optimization in path planning and scheduling methods, and to suggest future research directions.

The systematic literature review (SLR) identified 244 papers for analysis. Research articles published from 2010 onwards were searched in databases including Google Scholar, ScienceDirect and Scopus using keywords and search criteria related to energy and power management in various robotic systems.

The review highlights the following key findings: batteries are the primary energy source for AMRs, with advances in battery management systems enhancing efficiency; hybrid models offer superior accuracy and robustness; locomotion contributes over 50% of a mobile robot’s total energy consumption, emphasizing the need for optimized control methods; factors such as the center of mass impact AMR energy consumption; path planning algorithms and scheduling methods are essential for energy optimization, with algorithm choice depending on specific requirements and constraints.

The review concentrates on wheeled robots, excluding walking ones. Future work should improve consumption models, explore optimization methods, examine artificial intelligence/machine learning roles and assess energy efficiency trade-offs.

This paper provides a comprehensive analysis of energy efficiency in AMRs, highlighting the key findings from the SLR and suggests future research directions for further advancements in this field.