Search Results (114,554)

Micro-crack defects on the surfaces of plate heat exchanger sheets often exhibit a linear grayscale pattern when clustered. In defect detection, traditional methods are more suitable than deep learning models in controlled production environments with limited computing resources to meet stringent national standards, which require low miss rates. However, deep learning models commonly suffer feature loss when detecting individual, small-scale defects, leading to higher leak detection rates. Moreover, in grayscale image line detection using traditional methods, the varying direction, width, and asymmetric grayscale profiles of defects can result in filled grayscale valleys due to width-adaptive smoothing coefficients, complicating accurate defect extraction. To address these issues, this study establishes a theoretical foundation for parameter selection in variable-width defect detection. We propose a directional gradient-based algorithm that mathematically constrains the Gaussian template width to cover variable-width defects with a fixed σ, reframing the detection defect from ridge edges to centrally symmetric double-ridge edges in gradient images. Experimental results show that, when tested in the defective boards library and under simulated factory CPU conditions, this algorithm achieves a miss detection rate of 14.55%, a false detection rate of 21.85%, and an 600 × 600 pixel image detection time of 0.1402 s. Compared to traditional line detection and deep learning object detection methods, this algorithm proves advantageous for detecting micro-crack defects on plate heat exchanger sheets in industrial production, particularly in data-scarce and resource-limited scenarios. Full article

The increasing use of carbon fiber reinforced polymer (CFRP) composites in industries such as aerospace, due to its high strength-to-weight ratio, durability, and resistance to corrosion has led to a growing demand for more efficient machining processes. However, the multilayered structure of CFRP composites, composed of densely packed fibers, presents significant challenges during machining. Additionally, when cutting fluids are used to improve effective cooling and lubrication, the material tends to absorb the fluid, causing damage and leading to problem of weaking of composite structure. To address these issues, this study compares ultrasonic-assisted drilling (UAD) and minimum quantity lubrication (MQL) techniques with conventional drilling (CD) and dry cutting to improve the performance of CFRP composite drilling. The results show that using UAD and MQL together reduced thrust force by up to 27%, improved surface roughness inside the holes by up to 31%, reduced improved hole diameter, cylindricity, roundness, and delamination. Full article

Drawing on panel data for eight major citrus-producing provinces in China from 2008 to 2021, this study employs the super-efficiency EBM model—which incorporates both radial proportion and non-radial slack variables—to measure citrus green total factor productivity (GTFP). Temporal changes are investigated via the GML index, while regional disparities and convergence patterns are examined through a series of complementary techniques, thereby offering a comprehensive view of the sector’s green and coordinated development. The results reveal that, from a static perspective, the technical efficiency of most citrus-producing provinces remains below the production frontier. Dynamically, regional GTFP diverged markedly over the study period, with technical efficiency serving as the principal driver of growth. Convergence tests show no evidence of σ-convergence for the nation as a whole or for any of the three major producing regions. Absolute and conditional β-convergence coexist at the national level and in the upper–middle Yangtze region; the Zhejiang–Fujian hills exhibit no β-convergence, whereas the Guangdong–Guangxi hills display conditional β-convergence only. The findings indicate substantial room for improvement in China’s citrus GTFP. We therefore recommend that each region (1) accelerates green-technology innovation, (2) designs differentiated yet coordinated regional strategies, (3) institutionalizes long-term safeguards for green development, and (4) deepens international cooperation to enhance global competitiveness. Full article

Interest in surface integrity has grown in the manufacturing industry; indeed, it has become an integral part of the industry. It can be studied by examining surface roughness parameters, hardness variations, and microstructure. However, evaluating all these parameters together can be a challenging task. To address this multi-criteria decision-making model (MCDM), techniques such as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Grey Relational Analysis (GRA) provide a suitable solution for optimizing the machining parameters that lead to improved product quality. This work investigated surface roughness parameters, including arithmetic average surface roughness (2D) (Ra), mean surface roughness depth (2D) (Rz), area arithmetic mean height (3D) (Sa), and maximum surface height (3D) (Sz), in conjunction with Vickers macrohardness (HV) and optical micrographs, to analyze machined surfaces during the turning of X5CrNi18-10 steel. The results suggest that machining with a spindle speed (N) of 2000 rpm or v_c of 282.7 m/min, a feed rate (f) of 0.1 mm/rev, and a depth of cut of 0.5 mm yields the best surface, achieving an “A” class surface finish. These parameters can be applied in manufacturing industries that utilize chromium–nickel alloys. Additionally, the method used can be applied to rank the quality of the product. Full article

Background: Managing multiproduct pipeline systems is a complex task of critical importance in the petroleum industry. Experts frequently rely on simulation tools to design and validate pumping operation schedules. However, existing tools are often problem-specific and too slow to be effectively used for optimization purposes. Methods: In this paper, a new scheduling model is introduced, which inherently eliminates all conflicts except for tank overflows and underflows. A Discrete-Event Simulation algorithm was developed, capable of handling mesh-like pipeline topologies, reverse flows, and interface tracking. The computational performance of the new method is demonstrated using three local search-based optimization variants, including a simulated annealing metaheuristic. Results: A case study was made involving four problems, with 4–6 sites and 5–7 products in mesh-like and straight topologies, respectively, and a large-scale instance. Scheduling horizons of 2–28 days were used. The proposed simulation algorithm significantly outperforms a prior approach in speed, and the optimization algorithms effectively converged to feasible, high-quality schedules for most instances. Conclusions: This paper proposes a novel simulation technique for multiproduct pipeline scheduling along with three local search algorithm variants that demonstrate optimization capabilities. Full article

The comprehensive integration of modern technologies, such as artificial intelligence and big data, into the financial sector in recent years has profoundly transformed the operating model of the traditional financial industry. These technologies not only redefine the operating mechanisms of the financial industry but also significantly reshape the competitive landscape and strategic development of commercial banks. To investigate the impact of FinTech on the overall profitability of commercial banks, this study utilizes a balanced panel dataset comprising 50 listed commercial banks in China from 2012 to 2023 and conducts an empirical analysis based on a fixed-effects model. The findings reveal that, from a dynamic perspective, there exists a significant U-shaped relationship between FinTech and the comprehensive profitability of commercial banks, with a development threshold of 2.86. When the level of FinTech development falls below this critical threshold, its impact on the profitability of commercial banks is predominantly negative. However, once FinTech development surpasses this threshold, its positive effects on enhancing the profitability of commercial banks gradually emerge. Therefore, the government should provide phased policy support to achieve both short-term burden reduction and long-term innovation, and commercial banks should adopt FinTech development as a long-term strategic priority. Full article

Bats have decreasing population trends around the world, and knowledge on the causes for this decline is the first step to improving conservation and management strategies to restore their populations. An important source of data for the study of the causes of bat mortality is the admissions to rescue centres. The aim of this work was to identify the different causes of bat admissions to rescue centres in Castilla y León (Spain) over more than 30 years, analyzing the importance of the threats for different species, as well as the tendency of anthropogenic causes over the years, such as the increase in industrial wind-power facilities. The dataset included 791 bats (568 dead and 223 injured). The species with the largest number of entries was Pipistrellus pipistrellus at 451, followed by 82 Hypsugo savii, 64 Plecotus sp., 63 Tadarida teniotis, 42 Eptesicus serotinus and 24 Nyctalus lasiopterus. The most important known causes of entry for these selected species were collisions with wind turbines (n = 160); immaturity-related causes (e.g., orphan individuals with insufficient foraging and flight skills prone to injury or starvation) (n = 93); weakness due to starvation (n = 75); trauma: blow of unknown origin (n = 69); shooting: vandalism with a gun (n = 15); carnivore bite: predation (n = 8); road kill: road accident (n = 3); and disease: sickness (n = 3). In addition, there were many admissions which lacked a known cause (n = 294). The species with the most carcasses for collisions with wind turbines was Pipistrellus pipistrellus at 100, followed by 40 Hypsugo savii and 15 Nyctalus lasiopterus. As expected, the number of bats that collided with wind turbines showed a significant temporal correlation with the number of wind farms deployed in the territory, and they mainly occurred in September and October, as has also been found in other studies. Full article

The manufacture of industrial parts using silicone molds is becoming more frequent due to their versatility, durability, and precision, particularly in the production of complex components. One specific application is the manufacture of gears, which play a fundamental role in high-performance mechanical systems, where geometric accuracy is essential. Gears produced from resins offer several advantages such as efficient tribological performance, load resistance, noise reduction, and non-magnetic properties. The main goal of this paper is to determine the main factors affecting the final quality of resin gears by analyzing two principal gear quality parameters: teeth profile (ff$\alpha$) and helix deviation (ff $\beta$). This work includes a global analysis of all contributing factors influencing the final quality of gears manufactured. One of the main conclusions obtained is that gear quality depends on a combination of factors, such as mold properties, choice of resin, the manufacturing process, and the quality of the original model. As a result, two regression equations have been developed, relating all influencing factors to the two gear quality parameters (ff$\alpha$ and ff $\beta$). Different response surfaces have been obtained, enabling the definition of the required quality level of the model to achieve reproductions with certain ff$\alpha$ and ff $\beta$ values suitable for the intended application conditions. Full article

Higher education institutions have undergone essential transformations in recent decades, driven by legislative reforms and changes in social and economic demands. This study examines the factors that influence the continuous improvement of educational quality in Ecuador’s private higher education institutions (HEIs). A quantitative, cross-sectional, descriptive–correlational study was conducted to analyze the adaptation of HEIs to new realities, student mobility, technological development, sustainability practices, and innovation. The results indicate that technological development and environmental sustainability are key elements. There is a strong correlation between technological development and adaptation to the world of work. This suggests that integrating sustainable practices and university–industry cooperation is critical in improving the quality of higher education in Ecuador. In addition, student mobility and graduate follow-up programs are positively related to labor market adaptation and internationalization. These findings suggest the need for a holistic approach to quality assurance and provide practical guidelines for Ecuadorian HEIs to improve their performance in a rapidly changing context. Full article

The integration of 3D printing into the development of potentiometric sensors has revolutionized sensor fabrication by enabling customizable, low-cost, and rapid prototyping of analytical devices. Techniques like fused deposition modeling (FDM) and stereolithography (SLA) allow researchers to produce different sensor parts, such as electrode housings, solid contacts, reference electrodes, and even microfluidic systems. This review explains the basic principles of potentiometric sensors and shows how 3D printing helps solve problems faced in traditional sensor manufacturing. Benefits include smaller size, flexible shapes, the use of different materials in one print, and quick production of working prototypes. However, some challenges still exist—like differences between prints, limited chemical resistance of some materials, and the long-term stability of sensors in real-world conditions. This paper overviews recent examples of 3D-printed ion-selective electrodes and related components and discusses new ideas to improve their performance. It also points to future directions, such as better materials and combining different manufacturing methods. Overall, 3D printing is a powerful and growing tool for developing the next generation of potentiometric sensors for use in healthcare, environmental monitoring, and industry. Full article

This paper presents an innovative multi-criteria visual quality control algorithm designed for deployment on cost-effective Edge devices within the Industrial Internet of Things environment. Traditional industrial vision systems are typically associated with high acquisition, implementation, and maintenance costs. The proposed solution addresses the need to reduce these costs while maintaining high defect detection efficiency. The developed algorithm largely eliminates the need for time- and energy-intensive neural network training or retraining, though these capabilities remain optional. Consequently, the reliance on human labor, particularly for tasks such as manual data labeling, has been significantly reduced. The algorithm is optimized to run on low-power computing units typical of budget industrial computers, making it a viable alternative to server- or cloud-based solutions. The system supports flexible integration with existing industrial automation infrastructure, but it can also be deployed at manual workstations. The algorithm’s primary application is to assess the spread quality of thick liquid mold filling; however, its effectiveness has also been demonstrated for 3D printing processes. The proposed hybrid algorithm combines three approaches: (1) the classical SSIM image quality metric, (2) depth image measurement using Intel MiDaS technology combined with analysis of depth map visualizations and histogram analysis, and (3) feature extraction using selected artificial intelligence models based on the OpenCLIP framework and publicly available pretrained models. This combination allows the individual methods to compensate for each other’s limitations, resulting in improved defect detection performance. The use of hybrid metrics in defective sample selection has been shown to yield superior algorithmic performance compared to the application of individual methods independently. Experimental tests confirmed the high effectiveness and practical applicability of the proposed solution, preserving low hardware requirements. Full article

The Sixth Assessment Report of the IPCC highlights that global surface temperatures have risen by 1.1 °C above pre-industrial levels, with a marked increase in the frequency and intensity of extreme heat events in hot–humid regions. Buildings in these areas urgently require passive design strategies to enhance climate adaptability. Employing Zhupu Ancient Village in Chaoshan region in China as an example, this study analyzes and evaluates the wind-driven ventilation archetype and buoyancy-driven ventilation archetype of the village through integrated meteorological data analysis (ECMWF) and computational fluid dynamics (CFD) simulations. The results indicate that the traditional climate-adaptive archetype facilitates wind speeds exceeding 0.5 m/s in over 80% of outdoor areas, achieving unobstructed airflow and a discernible stack ventilation effect. Through archetype translation, the visitor center design incorporates open alleyway systems and water-evaporative cooling strategies, demonstrating that over 80% of outdoor areas attain wind speeds of 0.5 m/s during summer, thereby achieving enhanced ventilation performance. The research provides a climate-response-archetype translation-performance validation framework and practical case studies for climate-adaptive design of public buildings in hot–humid regions. Full article

Chile is the second-largest producer of Atlantic salmon (Salmo salar), a key industry facing challenges such as infestations by Caligus rogercresseyi, which cause significant economic losses. However, there are no studies exploring how environmental variables in marine culture centers affect salmon’s immune response, considering their poikilothermic characteristics. This study analyzed the effect of the seasonal temperature on the skin transcriptome of Atlantic salmon infested with C. rogercresseyi in fjord-based farms in the Aysén Region during autumn and spring. Two different centers were analyzed (autumn: Farm-A; spring: Farm-S) to ensure the same age of the fish sampled in each season. RNA sequencing (RNA-seq) and functional network analysis revealed notable seasonal transcriptomic differences. In autumn, 253 differentially expressed genes (DEGs) were found, primarily associated with stress response and negative regulation of T-cell proliferation, suggesting an impaired response against the ectoparasite. In spring, 103 DEGs were detected, associated with protein synthesis and the activation of immune mechanisms, including complement activation, granulocyte chemotaxis, and antigen presentation. This is the first study to evaluate the transcriptomic response of healthy skin in C. rogercresseyi-infested salmon under farming conditions, highlighting the importance of considering seasonal variations for the development of more effective management strategies in the aquaculture industry. Full article

Almond skin (AS) from industrial almond peeling is considered an agri-food waste with adequate composition to obtain composite films for food packaging due to its richness in polysaccharides, proteins, and phenolic compounds. Composite films based on amorphous polylactic acid (PLA) or partially acetylated polyvinilalcohol (PVA) were obtained by melt blending and compression moulding, incorporating different ratios of defatted AS powder (0, 5, 10, and 15 wt.%). The filler was better integrated in the polar PVA matrix, where more interactions were detected with the filler compounds, affecting glass transition and crystallization of the polymer. The AS particles provided the films with the characteristic colour of the powder and strong UV light-blocking effect, while improving the oxygen barrier capacity of both polymeric matrices (24% in PLA with 15% AS and 42% in PVA with 10% AS). The water vapour permeability increased in PLA (by 192% at 15% AS), but decreased in PVA films, especially with low AS content (by 19% with 5% particles). The filler also provided the PLA and PVA films with antioxidant properties due to its phenolic richness, improving the oxygen barrier capacity of the materials and delaying the unsaturated oil oxidation. This was reflected in the lower peroxide and conjugated dienes and trienes values of the sunflower oil packaged in single-dose bags of the different materials. The high oxygen barrier capacity of the PVA bags mainly controlled the preservation of the oil, which made the effect of the antioxidant AS powder less noticeable. Full article

Bigeye grunt (Brachydeuterus auritus) is a dominant fish species and mostly a major target species in both artisanal and industrial fisheries in the coastal waters of Sierra Leone. It was listed as near threatened in 2015 by the International Union for Conservation of Nature (IUCN) Red List. Although this species has been repeatedly assessed as overexploited by the Fishery Committee for the Eastern Central Atlantic (CECAF) in the majority of its range in the Eastern Central Atlantic, there have never been studies of stock assessment in the coastal waters of Sierra Leone. We conducted a study on the population dynamics of bigeye grunt in the coastal waters of Sierra Leone, which is crucial for completing the resource status of this species in the Eastern Central Atlantic. The results showed that the bigeye grunt had a wide distribution in the coastal waters of Sierra Leone, with significant spatiotemporal variation characteristics in biomass and abundance. The growth parameters of bigeye grunt varied across different months, but all E values were below 0.5, indicating that no overfishing occurred. These findings were further corroborated by the results of the Length-Based Bayesian Biomass Estimation method (LBB). The results of the Generalized Additive Model (GAM) show that there is a certain nonlinear relationship between the resource abundance of the bigeye grunt and both environmental factors and geographical locations, among which the influence of latitude is the greatest. This study posits that the bigeye grunt in Sierra Leone’s coastal waters exhibits moderate exploitation potential. The findings are anticipated to provide a scientific framework for informing evidence-based management strategies for this fishery resource. Full article