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In this work, the thickness-dependent size effect on nonlinear free vibration response of a Porous Functionally Graded (PFG) nanobeam in a hygrothermal environment is examined via nonlocal strain gradient theory (NSGT). Through the depth of the beam, hygro-thermal loadings are uniformly distributed. The mechanical properties of the beam are assumed to vary continuously in the thickness direction according to the power law expression. The equations of motion are derived using Hamilton's principle with consideration of von-Kármán nonlinearity. The nanobeam vibration responses are obtained with the aid of the Galerkin technique and the Hamiltonian approach. A vital point of this work is to explore the effects of power law index, slenderness ratio, porosity volume fraction, and hygrothermal changes on the vibration behavior of PFG nanobeams. The results indicate how the thickness effect and porosity volume fraction significantly change the size-dependent vibration response of the FG nanobeam under hygrothermal conditions. The paper findings can be applied to improve the mechanical performance of PFG nanobeams. [ABSTRACT FROM AUTHOR]

Geographic Information Systems (GIS) are frequently used when conducting site suitability and site selection studies for aquaculture because the factors influencing the suitability of an area typically contain a spatial element. Multi-criteria evaluation (MCE), often based on the Weighted Linear Combination (WLC) method, is commonly used in aquaculture as it allows the combination of numerous and often conflicting interdisciplinary criteria and the evaluation of the trade-offs between them. GIS-based MCE models can be implemented in different ways according to the modelling objectives, but a lack of transparency and unclear information on characteristics of the model and output(s) can affect their use in real-world decisions. This study analysed 71 scientific articles that developed and used GIS-based MCE for aquaculture site selection and site suitability modelling. The articles were identified using the PRISMA systematic review protocol and covered a wide range of locations, species, and production systems. Data on the reported model characteristics were extracted from the scientific articles and analysed to identify trends, similarities, and differences in the information provided within the studies. The analysis revealed inconsistencies in how models were described, with some articles missing important information that could limit their use for many aquaculture planning decisions. Based on these findings, a checklist and reporting framework were produced that can be used to ensure important information is easily accessible alongside GIS-based MCE models and their outputs. The checklist and reporting framework can act as a template to provide clear and consistent documentation that will facilitate the use of models and outputs by end users who may not have been involved in the modelling process and are unfamiliar with the technical aspects. Author summary: The need for sustainable food production is a major societal challenge and transformative changes are urgently required across the world to meet accelerating demands for affordable and nutritious food. Aquaculture has been highlighted as a key route to increased food production, but expansion of the sector will depend on the availability of suitable sites. Models developed using Geographic Information Systems (GIS) are often used to assess the suitability of a location for aquaculture development. However, in this study, following analysis of 71 published articles, we show that there are many ways of reporting model structures and results, which could affect usability of model outputs and limit potential knowledge exchange. To bridge the gap between research and real-world applications, we have developed a checklist and reporting framework that can support a more standardised approach to communication and documentation. Our work encourages a more transparent approach to data-driven aquaculture planning that would minimise conflicts with other users and resources by using clear and consistent reporting, ensuring information is easily accessible. This work is significant since transformative actions will involve complex decisions so there must be clear evidence that shows the route behind choices. [ABSTRACT FROM AUTHOR]

The tetrahedron equation introduced by Zamolodchikov is a three-dimensional generalization of the Yang–Baxter equation. Several types of solutions to the tetrahedron equation that have connections to quantum groups can be viewed as q -oscillator valued vertex models with matrix elements of the L -operators given by generators of the q -oscillator algebra acting on the Fock space. Using one of the q = 0-oscillator valued vertex models introduced by Bazhanov–Sergeev, we introduce a family of partition functions that admits an explicit algebraic presentation using Schur functions. Our construction is based on the three-dimensional realization of the Zamolodchikov–Faddeev algebra provided by Kuniba–Maruyama–Okado. Furthermore, we investigate an inhomogeneous generalization of the three-dimensional lattice model. We show that the inhomogeneous analog of (a certain subclass of) partition functions can be expressed as loop elementary symmetric functions. [ABSTRACT FROM AUTHOR]

Context: Underwater acoustic tomography (UAT) is a powerful tool for monitoring oceans, seas and inland waters. Aims: This study presents a scientometric analysis of UAT and examines future research trends. Methods: A comprehensive analysis of 449 Scopus-indexed publications across 135 journals from 1979 to 2023 was conducted to provide an in-depth examination of UAT. Results: More than 760 researchers from 18 countries have contributed to UAT research, resulting in ~40 distinct applications (e.g. four-dimensional (3-D + time) measurement of sound speed, temperature and flow velocity, as well as the localisation of autonomous underwater vehicles). The Journal of the Acoustical Society of America accounts for nearly 30% of these publications. Four major organisations have provided ~80% of the funding for the UAT research, namely, the US Office of Naval Research (31%), the National Natural Science Foundation of China (25%), the Japan Society for the Promotion of Science (13%) and the Russian Foundation for Basic Research (11%). Conclusions: Despite its unique capabilities, UAT technique still faces significant challenges to widespread adoption. Implications: Overcoming obstacles such as mass production, the development of high-frequency systems (exceeding 60 kHz) for laboratory-scale experiments and the creation of user-friendly software is essential for advancing UAT technology. Underwater acoustic tomography (UAT) is a technique used to monitor waterbodies. From 1979 to 2023, 720 researchers published 449 UAT-related articles in 135 journals. UAT, divided into Ocean Acoustic Tomography (OAT), Coastal Acoustic Tomography (CAT) and Fluvial Acoustic Tomography (FAT), faces adoption barriers, including high costs, limited collaboration and a lack of user-friendly software and educational resources. Recommendations include fostering collaboration, developing educational resources, promoting knowledge transfer, facilitating international exchange, commercialising systems, establishing online resources and designing user-friendly software. [ABSTRACT FROM AUTHOR]

Marine fisheries constitute a crucial component of global green development, where artificial intelligence (AI) plays an essential role in enhancing green economic efficiency associated with marine fisheries. This study utilizes panel data from 11 coastal provinces and municipalities in China from 2009 to 2020, employing the entropy method and the super-efficiency EBM model to calculate the AI index and the green economic efficiency of marine fisheries. Based on these calculations, we utilize fixed effects models, moderation effect models, and panel threshold models to examine the impact of AI on the green economic efficiency of marine fisheries. The study reveals that: (i) From 2009 to 2020, AI has significantly improved overall, while the green economic efficiency of marine fisheries has shown a fluctuating trend, with substantial regional disparities. (ii) AI significantly enhances the green economic efficiency of marine fisheries. (iii) Green finance, trade openness, and R&D investment act as crucial moderating variables, accelerating AI development and further improving the green economic efficiency of marine fisheries. (iv) The impact of AI on green economic efficiency varies across different intervals of green finance, trade openness, and R&D investment. These findings are crucial for understanding and advancing the informatization strategy of marine fisheries and hold significant implications for the sustainable development of global marine fisheries. [ABSTRACT FROM AUTHOR]

The construction of cruise ship hulls is a complex process that involves various stages: it begins with the fabrication of panels, which involves marking, cutting, and shaping metal plates of considerable length, followed by the welding of rigid structural components onto these panels. To minimize delays and cost overruns, it is crucial to detect any anomalies early on and rectify them through appropriate repair work. Therefore, real-time conformity verifications and effective Statistical Quality Control (SQC) methodologies are necessary. This paper proposes a novel SQC methodology, specifically tailored for monitoring the panel line in cruise-ship shipyards. This methodology, while adopting a traditional standardized p control chart with samples of variable size, integrates two original aspects: (i) it accounts for the significant level of customization and specific quality characteristics inherent in the different panels and (ii) it rigorously considers the measurement uncertainty associated with the large-volume metrology instruments (such as state-of-the-art total stations, laser trackers or laser scanners) used for conformity verification, following the ISO 14253-1:2017 standard. The methodology is exemplified through a real-world case study, providing practical insights into its application. [ABSTRACT FROM AUTHOR]

Bladeless wind turbines face operational limitations due to the lock-in phenomenon. This study introduces two novel mechanisms for designing bladeless wind turbines to address this issue, enabling operation across a broad wind speed range from 2 to 10 m/s while ensuring that lock-in conditions are satisfied at any wind speed within this range. The study aims to maintain optimal performance without any decline that is observed in conventional bladeless wind turbines by controlling the turbine's natural frequency through implementing these mechanisms, either by adjusting the effective length of the stand or by incorporating an additional mass in the hollow mast, or both. A mathematical model including dynamic analysis is constructed to adjust natural frequency to match the shedding frequency at the specified wind speed. Validation of our model shows high accuracy. Numerical results demonstrate that applying these mechanisms ensures the turbine is optimally designed across varying parameters. Findings reveal that for lower flexural modulus values, the first mechanism alone can achieve a 99.2% increase in mechanical efficiency at 7 m/s. For higher flexural modulus values, incorporating the second mechanism is essential to reduce the turbine's overall size. This integrated approach improves efficiency with a 55.7% increase., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

This study presents a novel optimization method based on the sand cat swarm optimization (SCSO) algorithm for the pattern synthesis of linear antenna-array (LAA), aiming to obtain the high gain and low sidelobe level (SLL). The innovation of the proposed method consists in efficiently regulating the radiation characteristics of the LAA by optimizing the geometric and electrical parameters including the phase, amplitude, rotation and position based on the SCSO algorithm to achieve the desired radiation performances. The full-wave method of moments (MoM) is adopted to rigorously consider the mutual coupling effect among the array elements to guarantee the design accuracy. To demonstrate the feasibility and effectiveness of the SCSO algorithm, the proposed method is compared with three typical algorithms, including the Genetic Algorithm (GA), the Gray Wolf (GWO) algorithm, and the Particle Swarm Optimization (PSO). The results show that the SCSO algorithm demonstrates superior convergence capabilities while maintaining the high gain and low SLL, highlighting the potential as a robust method for the LAA. [ABSTRACT FROM AUTHOR]