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Found 6374 publications
Who, What for Whom IAST Scholars Publish?—A Bibliometric and Science Mapping Analysis of Leading Tourism Scholars
Publication Name: Journal of Sustainability Research
Publication Date: 2025-09-01
Volume: 7
Issue: 3
Page Range: Unknown
Description:
Background: The International Academy for the Study of Tourism (IAST) has undeniably contributed to tourism research. However, the evolution of its members’ research outcomes remains underexplored. Additionally, understanding the academic community’s focus is key to assessing its contribution to knowledge development. This paper, therefore, seeks to examine the scientific publications, publication trends, and metrics of IAST scholars. Methods: The publication patterns of ninety IAST scholars were systematically investigated through a bibliometric and advanced science mapping analysis. This research utilized VOSviewer and the Biblioshiny-R-Studio package for data processing and visualization. Results: This study uncovers dynamic publication trends over the last five years, marked by an acceleration in scholarly production from 2001 to 2012, with an anomalous decrease in 2010. These contributions are widely disseminated across leading academic journals, reflecting a significant intellectual influence through high citation indices and their role as foundational references. Thematically, these scholars consistently foreground central issues such as sustainable tourism development and the protection of vulnerable regions, encompassing cultural and natural heritage. The spectrum of investigated topics spans all levels—from global to local scales—with a multidisciplinary emphasis on tourism economics, governance, tourist consumer behavior, stakeholder roles, and the marketing and sustainability aspects of tourism. Conclusions: IAST scholars’ publications clearly demonstrated trends, impact, and significant terminology in tourism studies. Therefore, academic communities, among others, should broaden their focus, with IAST serving as an example of a community—where scholars produce knowledge-based from diverse perspectives.
Open Access: Yes
DOI: 10.20900/jsr20250052
Optimisation of island integrated energy system based on marine renewable energy
Publication Name: Fundamental Research
Publication Date: 2025-09-01
Volume: 5
Issue: 5
Page Range: 2161-2179
Description:
Integrating marine renewable energy (MRE) with conventional energy sources and logically constructing island energy systems is crucial for alleviating island energy supply challenges and helping coastal energy systems achieve a sustainable, low-carbon transition. In this study, the status of marine energy utilisation technologies is reviewed, with a focus on advancements in energy conversion equipment, grid integration, and energy storage. The economic feasibility and environmental sustainability of marine energy systems are comparatively analysed to enhance the development and utilisation of marine energy technology while reducing the economic cost of power generation. Suitable equipment is highlighted for islands, with efficient energy generation strategies proposed to achieve cleaner, localised, and cost-effective island integrated energy system (IIES) design. Island energy facilities vary, and integrated development is crucial for building new energy systems. Based on the types and resources of island energy, IIESs are constructed for hierarchical energy utilisation and multi-energy coupling, coordinating resources to achieve source–grid–load–storage integration. The optimisation of IIESs is reviewed, with a focus on modelling methods, intelligent algorithm development, and system simulation. This study differs from previous research as it considers the integration of marine energy into existing systems to achieve comprehensive integration of multiple energy sources. Additionally, optimisation and solution methods for IIES models are summarised. To integrate complex, multivariable energy systems and create stable and predictable outputs, marine energy and load forecasting methods are explored. Overall, this study supports the advancement of marine energy utilisation, focusing on its progressive integration into island energy systems as the efficiency of marine energy improves. This work aims to inspire the development of new functions and modules based on existing system optimisation and forecasting techniques.
Open Access: Yes
The Role of Domain Size and Boundary Conditions in Mathematical Modeling of Railway Tracks
Publication Name: Applied Mechanics
Publication Date: 2025-09-01
Volume: 6
Issue: 3
Page Range: Unknown
Description:
In developing a mathematical model of a railway track, the question of determining the dimensions of the modeling domain inevitably arises. If the modeling area is too small, boundary effects may significantly influence the results, reducing their accuracy. Conversely, excessively large areas can increase computational complexity without substantial improvements in accuracy. An optimal choice of dimensions enables the balancing of computational costs and accuracy. Solving this problem is non-trivial, as it depends on numerous factors, primarily the type of mathematical model and the problem being addressed. In most cases, preference is given to minimal domain sizes that ensure the approach’s adequacy. The aim of this study is to justify the dimensions of the modeling domain by addressing such tasks as load scaling, introducing additional boundary conditions, and making relevant assumptions. The main object of the study is the minimum adequate longitudinal length of the track for the spatial model. The research is based on the analytical application of modern approaches in the theory of elasticity. The results are analyzed using mathematical methods, such as modeling the railway track through the propagation of elastic waves and finite element modeling. These findings can be applied to a wide range of problems related to the mathematical modeling of the stress–strain state of railway tracks.
Open Access: Yes
Influence of Cyclic Loading on the Removal Torque of Unique Subperiosteal Implant Screws
Publication Name: Journal of Functional Biomaterials
Publication Date: 2025-09-01
Volume: 16
Issue: 9
Page Range: Unknown
Description:
During the investigation, the effect of screw tightening torque on the potential loosening of screws under load was examined in the case of custom-made subperiosteal implants. The study focused on the connection screws between the implant components, testing the commonly applied tightening torques of 15 Ncm and 30 Ncm. Mastication was simulated using a custom-designed, PLC-controlled testing device, which allowed for the reproduction of variable numbers, forces, and speeds of bite cycles. With this device, six different scenarios were tested, including 500, 2000, and 10,000 bite cycles, under both constant and variable bite forces. A caliper was used to record potential length changes of the screws, force sensors measured the bite forces, and calibrated torque screwdrivers were used to verify the loosening torques. Based on the analysis of the measured data, it was concluded that for the M1.8 screws tested, a tightening torque of 15 Ncm does not provide sufficient resistance against loosening, whereas 30 Ncm offers adequate stability.
Open Access: Yes
DOI: 10.3390/jfb16090306
Innovative computer vision methods for tomato (Solanum Lycopersicon) detection and cultivation: a review
Publication Name: Discover Applied Sciences
Publication Date: 2025-09-01
Volume: 7
Issue: 9
Page Range: Unknown
Description:
In recent years, machine vision, deep learning, and artificial intelligence have garnered significant research interest in precision agriculture. This article aims to provide a comprehensive review of the latest advancements in machine vision application in tomato cultivation. This study explores integrating cognitive technologies in agriculture, particularly in tomato production. The review covers various studies on tomatoes and machine vision that support tomato harvesting, such as classification, fruit counting, and yield estimation. It addresses plant health monitoring approaches, including detecting weeds, pests, leaf diseases, and fruit disorders. The paper also examines the latest research efforts in vehicle navigation systems and tomato-harvesting robots. The primary objective of this article was to present a thorough analysis of the image processing algorithms utilized in research over the past two years, along with their outcomes.
Open Access: Yes
Unveiling the mechanisms and implications: how artificial intelligence drives green growth in China’s Huaihe River Ecological Economic Belt under the carbon neutrality agenda
Publication Name: Carbon Footprints
Publication Date: 2025-09-01
Volume: 4
Issue: 3
Page Range: Unknown
Description:
Amidst the backdrop of global climate warming and China’s proactive chase of its carbon peak and carbon neutrality goals, the Huaihe River Basin (HRB), a region of significant strategic importance in the heartland and eastern expanse of the nation is confronted with formidable challenges, including high energy consumption and severe environmental pollution. Despite its substantial contributions to economic development, the traditional development model of the HRB conflicts with the principles of green development, necessitating the urgent exploration of innovative pathways to sustainable progress. Through a comprehensive review of scholarly literature and rigorous theoretical analysis, this study demonstrates that artificial intelligence (AI) can significantly drive green development by enhancing eco-innovation and optimizing industrial structures. Using a panel dataset from 27 cities in the Huaihe River Ecological Economic Belt (HEB) from 2010 to 2022, this study employs a bidirectional fixed-effects model to analyze the repercussions of AI on green development. The baseline regression results show that for every one-unit increase in AI development level (AIDL), HEB’s urban green development level significantly increases by 0.087. This positive influence is further confirmed through robustness tests. We found that AI can indirectly influence the mechanism and pathway of green development through intermediate variables. AI drives green development indirectly through two pathways: green technology innovation and the rationalization of the industrial structure, with a total explanatory power of 56.7% (R2 = 0.812). Based on these findings, we propose vigorously promoting the green effects of AI, refining industrial structures, and leveraging mediating effects to foster sustainable regional development. These insights offer novel perspectives for the green development of the HRB but also provide valuable references for the green transformation of other areas with similar challenges.
Open Access: Yes
DOI: 10.20517/cf.2025.9
A Perspective on Artificial Intelligence for Process Manufacturing
Publication Name: Engineering
Publication Date: 2025-09-01
Volume: 52
Issue: Unknown
Page Range: 60-67
Description:
To achieve sustainable development goals and the requirements of a circular economy, a new class of intelligent computer-aided methods and tools is needed. Artificial intelligence (AI) techniques have been gaining much attention due to their ability to provide options to tackle the challenges we are currently facing. However, the successful application of AI to solve problems of current interest requires AI to be integrated with associated process systems engineering methods and tools that are already available or being developed. In this perspective paper, we highlight the use of a collection of process systems engineering methods and tools augmented by AI techniques to solve problems related to process manufacturing, with a focus on chemical product design, process synthesis and design, process control, and process safety and hazards.
Open Access: Yes
Uncovering the themes and trends in crowdfunding research using Latent Dirichlet Allocation
Publication Name: Management Review Quarterly
Publication Date: 2025-09-01
Volume: 75
Issue: 3
Page Range: 2033-2066
Description:
Crowdfunding (CF) has become a significant force in the entrepreneurial landscape, offering an innovative alternative to traditional financing channels for startups and projects. As the field expands, it is crucial to systematically analyze the existing literature to identify key themes, patterns, and emerging areas of interest. To achieve this goal, this study investigates the CF literature using latent Dirichlet allocation (LDA)-based topic modeling based on 1,678 publications extracted from the Scopus database. The review reveals significant growth in CF research, with top journals spanning diverse disciplines. Eight main topics are identified, including CF campaign success and financing, donation-based CF, social effects of CF, entrepreneurial projects and rewards in CF, financial and fintech aspects of CF, CF project success and performance, P2P lending models and credit risk assessment, and equity CF and venture capital. Several research directions are suggested for each topic to advance the CF field. The theoretical and practical implications are also discussed. To the authors’ best knowledge, this study represents the first systematic analysis of the CF literature using the LDA approach, offering a comprehensive and up-to-date overview of this field and highlighting emerging areas of interest and potential research directions.
Open Access: Yes
A Life Cycle Assessment Framework for Evaluating the Climate Impact of Hydrogen-Based Passenger Vehicle Technologies Toward Sustainable Mobility
Publication Name: Hydrogen Switzerland
Publication Date: 2025-09-01
Volume: 6
Issue: 3
Page Range: Unknown
Description:
Hydrogen-based mobility solutions could offer viable technology for sustainable transportation. Current research often examines single pathways, leaving broader comparisons unexplored. This comparative life cycle assessment (LCA) evaluates which vehicle type achieves the best environmental performance when using hydrogen from grey, blue, and green production pathways, the three dominant carbon-intensity variants currently deployed. This study examines seven distinct vehicle configurations that rely on hydrogen-derived energy sources across various propulsion systems: a hydrogen fuel cell electric vehicle (H2 FCEV), hydrogen internal combustion engine vehicle (H2 ICEV), methanol flexible fuel vehicle (MeOH FFV), ethanol flexible vehicle (EtOH FFV), Fischer-Tropsch (FT) diesel internal combustion vehicle (FTD ICEV) and renewable compressed natural gas vehicle (RNGV). Via both grey and blue hydrogen production, H2 FCEVs are the best options from the viewpoint of GWP, but surprisingly, in the green category, FT-fueled vehicles take over both first and second place, as they produce nearly half the lifetime carbon emissions of purely hydrogen-fueled vehicles. RNGV also emerges as a promising alternative, offering optimal engine properties in a system similar to H2 ICEVs, enabling parallel development and technological upgrades. These findings not only highlight viable low-carbon pathways but also provide clear guidance for future targeted, detailed, applied research.
Open Access: Yes
