Search Results (4,050)

Technological innovation is essential to promoting sustainable development in emerging economies as it drives regional coordination and industry upgrading. In order to address the understudied connection between regional coordination and industrial structural transformation, this study examines the spatial dynamics of technological innovation efficiency (TIE) in China’s advanced manufacturing industry (AMI) along the Yangtze River Economic Belt (YREB) from 2007 to 2022. Through a Data Envelopment Analysis (DEA) and Spatial Durbin Model (SDM), we systematically evaluated TIE patterns using panel data from 11 provinces. Our empirical analysis reveals three key findings. (1) The temporal distribution of TIE in AMI in the YREB showed an annual increasing trend. The spatial distribution characteristics showed a gradient distribution disparity between the eastern, central, and western regions, but the regional gap of TIE in AMI is gradually closing. (2) Through the examination of Moran’s I, the spatial spillover effect of TIE in AMI was observed, that is, the TIE is spreading from high-performance provinces to other regions, suggesting that interregional collaboration and knowledge exchange may be beneficial. (3) According to the factor identification study, the main factors affecting the spatial distribution of TIE in AMI are industrialization, human capital, and innovation capability. Interestingly, the effects of information technology and economic progress are not statistically significant, suggesting that cautious government actions are required. By optimizing technological innovation processes and spatial arrangements, this study adds to the expanding body of knowledge on the spatial aspects of technological innovation and provides valuable insights for policymakers looking to enhance global competitiveness and foster sustainable economic growth in the AMI. The findings advance our knowledge of how to support sustainable economic development in emerging nations by highlighting the critical role that innovation and technology management play in removing regional development obstacles and encouraging the modernization of industrial structures. Full article

Water is one of humanity’s most fundamental needs. The demand for freshwater rises in tandem with population expansion. Only 0.01 percent of freshwater is available as surface water in lakes, wetlands, and rivers. As a result, the only choice is to extract water from the oceans. Desalination is an effective option for this. This study focused on the multi-objective design optimization, fabrication, and thermal evaluation of an integrated desalination system combining a solar still with a flat plate collector (SS-FPC). The study investigated the trade-off between two competing objectives: maximizing the efficiency of the SS-FPC system while minimizing its total cost. A numerical code is written in MATLAB to simulate the influence of changing design parameters (DPs) on the SS-FPC performances. The optimal SS-FPC design, offering low costs and a high thermal efficiency, was identified using the multi-objective colonial competitive algorithm (MOCCA). This design was subsequently fabricated and experimentally evaluated under the climatic conditions of Unaizah in Al Qassim, Saudi Arabia. The optimal numerical results were compared with both the literature values and experimental measurements. The comparison revealed strong agreement with the experimental data, with a maximum relative error of 4%. Moreover, the obtained results indicate that the optimized SS-FPC design is capable of achieving a 31% increase in efficiency and a 49% reduction in total cost relative to those reported in the literature. Full article

The agricultural equipment market has the characteristics of rapid demand changes and high demand for machine models, etc., so multi-variety, small-batch, and customized production methods have become the mainstream of agricultural machinery enterprises. The flexible job shop scheduling problem (FJSP) in the context of agricultural machinery and equipment manufacturing is addressed, which involves multiple resources including machines, workers, and automated guided vehicles (AGVs). The aim is to optimize two objectives: makespan and the maximum continuous working hours of all workers. To tackle this complex problem, a Multi-Objective Discrete Grey Wolf Optimization (MODGWO) algorithm is proposed. The MODGWO algorithm integrates a hybrid initialization strategy and a multi-neighborhood local search to effectively balance the exploration and exploitation capabilities. An encoding/decoding method and a method for initializing a mixed population are introduced, which includes an operation sequence vector, machine selection vector, worker selection vector, and AGV selection vector. The solution-updating mechanism is also designed to be discrete. The performance of the MODGWO algorithm is evaluated through comprehensive experiments using an extended version of the classic Brandimarte test case by randomly adding worker and AGV information. The experimental results demonstrate that MODGWO achieves better performance in identifying high-quality solutions compared to other competitive algorithms, especially for medium- and large-scale cases. The proposed algorithm contributes to the research on flexible job shop scheduling under multi-resource constraints, providing a novel solution approach that comprehensively considers both workers and AGVs. The research findings have practical implications for improving production efficiency and balancing multiple objectives in agricultural machinery and equipment manufacturing enterprises. Full article

Understanding predator–prey and predator–predator interactions is essential for evaluating the effectiveness of biocontrol agents and developing efficient pest management strategies. This study investigates the effects of prey species, predator life stage, and predator density on the predatory efficiency of the generalist predator Rhynocoris fuscipes (Fabricius) under semi-field conditions. Both the nymphs and adults of R. fuscipes consumed significantly more second-instar larvae of S. frugiperda than larvae of S. litura or M. separata. Notably, fifth-instar nymphs and adults exhibited higher predation capacity (11.75 ± 0.37 and 10.90 ± 0.40 larvae) than fourth-instar nymphs (9.05 ± 0.29 larvae) on S. frugiperda. R. fuscipes demonstrated a Type II functional response at all developmental stages toward each prey species, and fifth-instar nymphs revealed higher attack rates (a = 1.5205 ± 0.0544) on S. frugiperda; additionally, the handling time did not significantly differ among three prey species. It suggests that this predator may be more effective at controlling noctuid populations at low prey densities. As predator age and density increased, intraspecific competition among R. fuscipes also intensified. In a multi-prey system, R. fuscipes showed a marked preference for S. frugiperda over the other two prey species. These findings indicate that the fifth-instar nymphs and adults of R. fuscipes are particularly effective in suppressing early-instar larvae of the three noctuid pests, especially S. frugiperda, at low densities. This study enhances our understanding of the predation capacity and prey preference of R. fuscipes towards the three noctuid pests and provides a foundation for the development of more targeted and efficient pest management strategies using this predator. Full article

Smart cities aim to enhance the quality of life by advancing infrastructure, leveraging technology, and promoting sustainability, balancing environmental, societal, and economic needs for long-term efficiency. Given resource scarcity and environmental regulations, advanced supply chains play a crucial role in developing smart cities by adopting the circular economy concept, which emphasizes maximizing resource efficiency through recycling and remanufacturing. This study delves into the competition between two types of supply chains in the context of reverse logistics: the hybrid supply chain, which utilizes a dual channel including traditional and e-channels for collecting used products, and the traditional supply chain, which relies solely on a traditional channel. Both supply chain models are actively involved in remanufacturing and recycling used products, and each considers varied policies, including incentive-based policies, advertising investments, the acceptance return quality level, the return processing time, and transportation investments, to enhance their performance. Specifically, this research has two primary objectives: (1) evaluating the economic and environmental outcomes across three competitive scenarios, and (2) analyzing the impact of varied policy settings on these outcomes. These objectives frame the analysis of optimal incentive values, return rates, and profitability across the Nash equilibrium and Nash–Stackelberg structures, providing insights into both the strategic and policy dimensions of supply chain operations. The findings indicate that a hybrid supply chain in this case achieves higher return rates and profitability, highlighting the success of its dual-channel strategy and associated policies. Regarding economic goals, both supply chains achieve the highest profits under the Nash–Stackelberg traditional supply chain leadership structure. However, for environmental goals, the traditional supply chain favors Nash equilibrium for higher return rates, while the hybrid supply chain prefers Nash–Stackelberg with traditional leadership. These scenario-specific results emphasize the importance of aligning economic and environmental goals through tailored strategies. A sensitivity analysis, supported by Pareto prioritization, identifies the return quality level and processing time as critical for the hybrid supply chain, and advertisement investments and the return processing time as key for the traditional supply chain. These insights suggest that H-SCs should prioritize stricter quality standards, efficient inspection protocols, and automation (e.g., AI or optical scanning) to improve the quality and processing time efficiency. Meanwhile, T-SCs should focus on advertising traditional channels by emphasizing faster processing time and less restrictive quality standards, while adopting automated time management strategies similar to H-SCs to enhance engagement and profitability. These findings show that by integrating smart city internet-based initiatives and managing related policies, supply chains can enhance circular economy objectives by optimizing both the economic and environmental performance, ultimately fostering more resilient and sustainable supply chains. Full article

Tourism is a critical economic sector for many countries, making substantial contributions to GDP and job creation. Analyzing performance in this domain has become indispensable for understanding and enhancing its economic, social, and environmental impact while promoting the sustainability and competitiveness of tourist destinations. In the context of the prolonged coronavirus pandemic, the tourism field suffered the effects of a weakened economy and a heavily affected society. For this reason, countries and their tourism industries have been looking for ways to improve performance in this sector by trying to address salient determinants related to investments in this industry. This study employs the input-oriented DEA-CRS (Data Envelopment Analysis–Constant Returns to Scale) model to assess Romania’s tourism performance in comparison to 11 other Central and Eastern European (CEE) countries. This analysis utilizes a dataset comprising three input variables and two output variables, with data corresponding to the year 2023. Half of the countries studied are deemed efficient, while only one is found to have a low level of efficiency in the tourism field. Following the analysis of the obtained results, four reference countries were identified, namely, Estonia, Croatia, Poland, and Slovenia. Practically, within the analyzed model, these four countries represent examples of good practices in the efficiency of the tourism industry for the other eight CEE countries. Full article

Gaze estimation is increasingly pivotal in applications spanning virtual reality, augmented reality, and driver monitoring systems, necessitating efficient yet accurate models for mobile deployment. Current methodologies often fall short, particularly in mobile settings, due to their extensive computational requirements or reliance on intricate pre-processing. Addressing these limitations, we present Mobile-GazeCapsNet, an innovative gaze estimation framework that harnesses the strengths of capsule networks and integrates them with lightweight architectures such as MobileNet v2, MobileOne, and ResNet-18. This framework not only eliminates the need for facial landmark detection but also significantly enhances real-time operability on mobile devices. Through the innovative use of Self-Attention Routing, GazeCapsNet dynamically allocates computational resources, thereby improving both accuracy and efficiency. Our results demonstrate that GazeCapsNet achieves competitive performance by optimizing capsule networks for gaze estimation through Self-Attention Routing (SAR), which replaces iterative routing with a lightweight attention-based mechanism, improving computational efficiency. Our results show that GazeCapsNet achieves state-of-the-art (SOTA) performance on several benchmark datasets, including ETH-XGaze and Gaze360, achieving a mean angular error (MAE) reduction of up to 15% compared to existing models. Furthermore, the model maintains a real-time processing capability of 20 milliseconds per frame while requiring only 11.7 million parameters, making it exceptionally suitable for real-time applications in resource-constrained environments. These findings not only underscore the efficacy and practicality of GazeCapsNet but also establish a new standard for mobile gaze estimation technologies. Full article

This study explores the optimization of rigid polyisocyanurate (PIR) foam formulations, focusing on foaming kinetics that significantly influence the foam’s microstructure and thermal insulation properties. By systematically altering components such as isocyanate, polyols, catalysts, blowing agents, and additives, this research investigates their effects on key characteristics including cell density, mechanical strength, and thermal conductivity. A statistical approach known as response surface modeling (RSM) was employed to identify relationships between formulation variables and performance metrics. The optimization aimed to enhance thermal insulation while ensuring feasibility for industrial-scale production, particularly for sandwich-type PIR panels. Two distinct formulations, with isocyanate indices of 335 and 400, were developed to assess the impact of various parameters on properties like foaming start time, gel time, and density. The results indicated that the choice of blowing agents and catalysts played a pivotal role in controlling foaming kinetics and final mechanical properties. The optimized formulations exhibited competitive thermal conductivity values (around 23.7 mW/(m·K)) and adequate compression strength (0.32 MPa), aligning closely with commercially available materials. These findings affirm the potential for enhancing production efficiency and performance consistency in the manufacturing of rigid PIR foams for insulation applications. Full article

This study analyzes, quantifies, and maps, from a bibliometric perspective, scientific production, bioeconomy and computational simulations regarding avocado use in the timeframe of 2004–2023 in Scopus. To categorize and evaluate the contributions of authors, countries, institutions, and journals, Biblioshiny software in RStudio was used. Their collaborative networks were also visualized using VOSviewer. The analysis reveals an exponential increase in scientific output, especially from 2019 onwards, driven by the growing importance of sustainable avocado use in bioeconomy models. The main findings highlight the valorization of avocado waste for producing biofuels, cosmetics, pharmaceuticals, and food. In addition, the use of computational tools such as Aspen Plus, ArcGIS Pro, Unscrambler-X, SIMCA, and DOCK-6 to optimize conversion processes, model climate change effects, perform chemometrics, and conduct multivariate analyses, and molecular docking, respectively, is discussed. This knowledge highlights potential uses of avocado waste and computational modeling tools for stakeholders in the avocado industry, reinforcing their value chain through bioeconomy models and strengthening their competitiveness by promoting more efficient and sustainable processes. This work provides a comprehensive overview of the avocado-based bioeconomy, serving as a reference for future studies that integrate process simulation in the valorization of agro-industrial waste. Full article

Montmorillonite (Mont) is a natural two-dimensional material with a 2:1 layered silicate crystal structure. It possesses abundant surface groups, cation exchange capacity, and adsorption performance. In addition, it has other advantages such as abundant reserves, environmental friendliness, strong mechanical stability, and a large specific surface area. As such, it shows excellent potential for application in environmental remediation. In the following paper, we focus on the removal of TCS (triclosan) from an aqueous environment by utilizing montmorillonite-supported bimetallic Fe/Ag particles. We use scanning electron microscopy, X-ray diffraction patterns, Fourier-transform infrared spectra, and specific surface area to analyze the structure, morphology, and composition of these nanocomposites. The effects of the pH, different materials, contact time, and different initial concentrations on the degradation efficiency of TCS were studied systematically. Based on the results of our study, montmorillonite-supported bimetallic Fe/Ag nanoparticles (Fe/Ag-Mont) should be categorized as a type of mesoporous material of high uniformity because the pore size of all its catalysts ranges from 10 to 20 nm, and they are well-distributed. The Si-O stretching vibrations of montmorillonite can be changed by adding Fe/Ag. We found that Fe or Ag combined with -O to form a new bond and interacted with Si-O, and the incorporation of Fe/Ag-Mont nanoparticles removed TCS with better reduction rates. By enhancing reduction capacity, the pH was below 4 due to H• species generation by Fe/Ag. H• was the main factor enhancing the redox reaction in reducing TCS. The pH controlled the competition between Fe corrosion and silver formation, which enabled the system to self-regulate. In addition, this study provided a suitable method of efficiently synthesizing clay-supported bimetallic nano-system materials for reduction. Full article

This study evaluates the performance of China Taipei firms in the global business environment, focusing on the role of firm-level factors, the geographical setting context, internationalization, and product diversification. These variables are chosen for their potential to enhance resilience and bring firms into global competitiveness. This study performs a generalized least squares (GLS) and curved relationship analysis of 2160 observation samples in the panel analysis, based on a sample of 360 firms across eight industries. The analysis reveals positive correlations between non-labor-intensive operations and effective supply chain management and firms’ overall performance, while dependency on China negatively impacts performance. Notably, the degree of internationalization and product diversification significantly influences the correlations between the key predictors and geographical diversification. A highlight of this study is the application of a curvilinear relationship analysis (non-linear analysis) to assess the real assumptions, providing insight into how these factors interact to affect firm performance. This study stresses the importance of diversifying supply chains, reducing reliance on single markets like China, and enhancing supply chain efficiency through non-labor-intensive operations. This study highlights the need for supportive policies that encourage global expansion, product diversification, and competitiveness in the global business environment. Full article

Camels, with the ability to survive under drought and chronic hunger, developed exceptional efficient lipid reserves and energy substance metabolic characteristics. Fibroblast growth factor (FGF) 21 is a hormone that regulates important metabolic pathways and energy homeostasis. However, the absence of a specific detection method for camel FGF21 impacts research on camels’ metabolic regulation. This study established a direct competition ELISA assay for detecting camel FGF21. Camel FGF21 antigen was expressed and purified through prokaryotic expression system. Polyclonal antibody was produced and purified via immunizing guinea pigs and affinity chromatography assay. Biotin-labeled FGF21 was synthesized artificially as the competitive antigen. After the determination of optimal conditions, including the working concentrations of the antibody and antigen, blocking solution, dilution buffer, and the competition reaction time, the standard curve with a typical “S” shape was generated using GraphPad Prism. The regression equation was Y = 0.1111 + (X^−0.7894) × (2.162 − 0.1111)/(X^−0.7894 + 15.76^−0.7894), with the IC₅₀ 15.59 ng/mL, the limit of detection (LOD) 0.024 ng/mL, the limit of quantification (LOQ) 1.861 ng/mL, and the linear range IC₂₀~IC₈₀ 2.0~119.22 ng/mL. The verification test showed that the recovery rate ranged from 91.34% to 98.9%, and the coefficients of variation for the intra- and inter-plate both were less than 10%, indicating that the ELISA method had high accuracy, good repeatability, and high stability. In addition, this ELISA method had the potential to detect FGF21 secretion levels in other species such as mouse, human, and pig. This study provided a rapid quantitative tool for conducting research on the FGF21 factor in camels. Full article

Climate change has led to the need to transition to clean technologies, which depend on an number of critical metals. These metals, such as nickel, lithium, and manganese, are essential for developing batteries. However, the scarcity of these elements and the risks of disruptions to their supply chain have increased interest in exploiting resources on the deep seabed, particularly polymetallic nodules. As the identification of these nodules must be efficient to minimize disturbance to the marine ecosystem, deep learning techniques have emerged as a potential solution. Traditional deep learning methods are based on the use of convolutional layers to extract features, while recent architectures, such as transformer-based architectures, use self-attention mechanisms to obtain global context. This paper evaluates the performance of representative models from both categories across three tasks: detection, object segmentation, and semantic segmentation. The initial results suggest that transformer-based methods perform better in most evaluation metrics, but at the cost of higher computational resources. Furthermore, recent versions of You Only Look Once (YOLO) have obtained competitive results in terms of mean average precision. Full article

Eco-design is an innovative design methodology that focuses on minimizing the environmental footprint of industries, including aviation, right from the conceptual and development stages. However, rising industrial demand calls for a more comprehensive strategy wherein, beyond environmental considerations, competitiveness becomes a critical factor, supported by additional pillars of sustainability such as economic viability, circularity, and social impact. By incorporating sustainability as a primary design driver at the initial design stages, this study suggests a shift from eco-driven to sustainability-driven design approaches for aircraft components. This expanded strategy considers performance and safety goals, environmental impact, costs, social factors, and circular economy considerations. To provide the most sustainable design that balances all objectives, these aspects are rigorously quantified and optimized during the design process. To efficiently prioritize different variables, methods such as multi-criteria decision-making (MCDM) are employed, and a sustainability index is developed in this framework to assess the overall sustainability of each design alternative. The most sustainable design configurations are then identified through an optimization process. A typical aircraft component, namely a hat-stiffened panel, is selected to demonstrate the proposed approach. The study highlights how effectively sustainability considerations can be integrated from the early stages of the design process by exploring diverse material combinations and geometric configurations. The findings indicate that the type of fuel used, and the importance given to the sustainability pillars—which are ultimately determined by the particular requirements and goals of the user—have a significant impact on the sustainability outcome. When equal prioritization is given across the diverse dimensions of sustainability, the most sustainable option appears to be the full thermoplastic component when kerosene is used. Conversely, when hydrogen is considered, the full aluminum component emerges as the most sustainable choice. This trend also holds when environmental impact is prioritized over the other aspects of sustainability. However, when costs are prioritized, the full thermoplastic component is the most sustainable option, whether hydrogen or kerosene is used as the fuel in the use phase. This innovative approach enhances the overall sustainability of aircraft components, emphasizing the importance and benefits of incorporating a broader range of sustainability factors at the conceptual and initial design phases. Full article

This paper is aimed at understanding the possibility of applying ergonomics in the reorganisation of the work environment with the aim to improve working conditions and to increase the productivity of the examined workplace in an industrial company. Due to constant changes in markets, industrial companies are forced to seek new methods and paradigms for planning and managing innovations in order to ensure their competitiveness. An essential part of this process is the emphasis on improving production processes, where various methods with different focuses can be used. These methods not only optimise work processes, but also allow companies to minimise the resources needed for production and increase overall productivity. Another useful tool for industrial enterprises can be ergonomic rationalisation. The importance of ergonomics in improving employee working conditions and production process efficiency has been the subject of studies promoting various concepts. This study focuses in particular on examining the possibility of extending the outputs obtained by the REFA method to outputs obtained through ergonomic analysis. To achieve the objectives of the paper, the case study method was chosen, given that it was necessary to apply the REFA method in combination with ergonomic rationalisation in the specific conditions of the industrial company for the possibility of identifying bottlenecks in the production process from the point of view of its productivity, efficiency, and workforce involvement. Based on the results, it was possible to propose measures to increase the efficiency of the production process while respecting the principles of ergonomics. As part of the solution, the author team concluded that the findings obtained by combining both methods do not show significant differences, but rather complement each other and provide a broader view of the issue under study. At the same time, it can be stated that the solution cannot be considered definitive due to possible dynamic changes in the industrial environment (changes in the composition of the workforce and the scale of production and evolving technology, e.g., AI). The subject of future research will be to adapt the applied combination of methods so that it is universally applicable to any industrial sector, with minimal required adjustments to meet the specifics of individual industries. Full article