Search Results (843)

Background and Objectives: Asthma, COPD, and asthma–COPD overlap are obstructive lung diseases with inflammation at their core. Oxidative stress and impaired antioxidant balance play a significant role in etiopathogenesis. This study aimed to determine whether there are differences in total antioxidant capacity (TAC) between asthma, COPD, and asthma–COPD overlap. Materials and Methods: A total of 76 patients participated in this prospective cross-sectional study. TAC levels in fasting venous blood samples were measured using a biochemistry analyzer and the total antioxidant activity method (Architect C1600, Abbott Laboratories, IL, USA). Results: TAC levels were lower in COPD patients compared to asthma and ACO patients (p = 0.049 and 0.026, respectively). TAC levels were lower in current and former smokers compared to never smokers (p = 0.033). There was no significant correlation between TAC level and eosinophil count (p = 0.597) and FEV1 and FEV1/FVC (p = 0.372 and p = 0.189). Conclusions: Our results suggest that TAC levels may serve as a marker to differentiate COPD from asthma or ACO. Full article

Background/Objectives: This paper presents a medical image analysis application designed to facilitate advanced edge detection and fuzzy processing techniques within an intuitive, modular graphical user interface. Methods: Key functionalities include classical edge detection, Ant Colony Optimization (ACO)-based edge extraction, and fuzzy edge generation, which offer improved boundary representation in images where uncertainty and soft transitions are prevalent. Results: One of the main novelties in contrast to the initial innovative Medical Image Analyzer, iMIA, is the fact that the system includes fuzzy C-means clustering to support tissue classification and unsupervised segmentation based on pixel intensity distribution. The application also features an interactive zooming and panning module with the option to overlay edge detection results. As another novelty, fuzzy performance metrics were added, including fuzzy false negatives, fuzzy false positives, fuzzy true positives, and the fuzzy index, offering a more comprehensive and uncertainty-aware evaluation of edge detection accuracy. Conclusions: The application executable file is provided at no cost for the purposes of evaluation and testing. Full article

Anthocyanins are important phenolic compounds in grape skins, affecting the color, oxidation resistance, and aging ability of red wine. In recent years, global warming has had a negative effect on anthocyanin biosynthesis in grape berries. Ethylene serves as a crucial phytohormone regulating the development and ripening processes of fruit; however, the specific molecular mechanism and the regulatory network between ethylene signaling and the anthocyanin biosynthesis pathway remain incompletely understood. In this study, 400 mg/L ethephon (ETH) solution was sprayed onto the surface of grape berries at the lag phase (EL-34), and the changes in anthocyanin-related genes and metabolites were explored through transcriptomic and metabolomic analysis. The results showed that ETH treatment increased Brix and pH in mature berries. In total, 35 individual anthocyanins were detected, in which 21 individual anthocyanins were enhanced by ETH treatment. However, the anthocyanin profile was not affected by exogenous ethylene. Transcriptomics analysis showed that there were a total of 825 and 1399 differentially expressed genes (DEGs) 12 h and 24 h after treatment. Moreover, key structural genes in the anthocyanin synthesis pathway were strongly induced, including VvPAL, VvCHS, VvF3H, VvF3′5′H, VvDFR and VvUFGT. At the maturity stage (EL-38), the expression levels of these genes were still higher in EHT-treated berries than in the control. ETH treatment also influenced the expression of genes related to hormone biosynthesis and signal transduction. The ethylene biosynthesis gene (VvACO), ethylene receptor genes (VvETR2, VvERS1 and VvEIN4), ABA biosynthesis gene (VvNCED2), and ABA receptor gene (VvPYL4) were up-regulated by ETH treatment, while the auxin biosynthesis gene (VvTAA3) and seven genes of the auxin-responsive protein were inhibited by exogenous ethylene. Meanwhile, ETH treatment promoted the expression of the sugar transporter gene (VvEDL16) and two sucrose synthase genes (VvSUS2 and VvSUS6). In EHT-treated berries, 19 MYB and 23 ERF genes were expressed differently compared with the control (p < 0.05). This study provides the theoretical foundation and technical support for the regulation of anthocyanin synthesis in non-climacteric fruit. Full article

The swift expansion of China’s automotive manufacturing industry has spurred a constant rise in the demand for automotive parts production and distribution, making the optimization of distribution routes in complex environments a crucial research topic. Efficiently optimizing these routes not only boosts production efficiency and cuts costs for automotive manufacturers but also enhances supply chain management and advances sustainable development. This study focuses on the optimization of automotive parts distribution routes under a multi-manufacturer collaboration framework. An optimization model is proposed to minimize the total operational costs within a joint distribution system, incorporating an improved Ant Colony Optimization (ACO) algorithm to formulate an effective solution approach. The model considers complex factors such as dynamic demand, time-window constraints, and periodic distribution. A PIVNS algorithm integrating a virtual distribution center with an enhanced variable neighborhood search is designed to efficiently address the problem. The efficacy of the proposed model and algorithm is substantiated through extensive experiments grounded in real-world case studies. The results confirm the high computational efficiency of the proposed approach in solving large-scale problems, which significantly reduces distribution costs while improving overall supply chain performance. Specifically, the PIVNS algorithm achieves an average travel distance of 2020.85 km, an average runtime of 112.25 s, a total transportation cost of CNY 12,497.99, and a loading rate of 86.775%. These findings collectively highlight the advantages of the proposed method in enhancing efficiency, reducing costs, and optimizing resource utilization. Overall, this study provides valuable insights for logistics optimization in automotive manufacturing and offers a significant reference for future research and practical applications in the field. Full article

Grafting involves complex hormonal interactions at graft interfaces that are not yet fully understood. In this study, we analyzed hormone fluctuations and gene expression during callus proliferation and vascular tissue differentiation in hickory (Carya cathayensis Sarg.) grafts. Cytokinin and ethylene precursor ACC levels steadily increased after grafting. The biosynthetic genes for these hormones (IPT3, ACS1, ACO1, and ACO5) exhibited heightened expression. Genes related to cytokinin signaling (RR3, ARR4, and ZFP5) and ethylene signaling (MKK9, ESE1, and ESE3) were similarly upregulated. Conversely, genes associated with jasmonic acid, abscisic acid, and strigolactone pathways were downregulated, including synthesis genes (AOC4 and AOS) and those involved in signal transduction (NAC3, WRKY51, and SMAX1). Correspondingly, JA-Ile and 5-deoxystrigol levels significantly decreased. Indole-3-acetic acid (IAA) levels also dropped during the early stages of graft union formation. These results suggest that low auxin concentrations may be essential in the initial stages after grafting to encourage callus proliferation, followed by an increase at later stages to facilitate vascular bundle differentiation. These findings imply that maintaining a balance between low auxin levels and elevated cytokinin and ethylene levels may be critical to support cell division and callus formation during the initial proliferation phase. Later, during the vascular differentiation phase, a gradual rise in auxin levels, accompanied by elevated ethylene, may facilitate the differentiation of vascular bundles in hickory grafts. Full article

Path planning for picking safflowers is a key component in ensuring the efficient operation of robotic safflower-picking systems. However, existing single-arm picking devices have become a bottleneck due to their limited operating range, and a breakthrough in multi-arm cooperative picking is urgently needed. To address the issue of inadequate adaptability in current path planning strategies for dual-arm systems, this paper proposes a novel path planning method for dual-arm picking (LTSACO). The technique centers on a dynamic-weight heuristic strategy and achieves optimization through the following steps: first, the K-means clustering algorithm divides the target area; second, the heuristic mechanism of the Ant Colony Optimization (ACO) algorithm is improved by dynamically adjusting the weight factor of the state transition probability, thereby enhancing the diversity of path selection; third, a 2-OPT local search strategy eliminates path crossings through neighborhood search; finally, a cubic Bézier curve heuristically smooths and optimizes the picking trajectory, ensuring the continuity of the trajectory’s curvature. Experimental results show that the length of the parallelogram trajectory, after smoothing with the Bézier curve, is reduced by 20.52% compared to the gantry trajectory. In terms of average picking time, the LTSACO algorithm reduces the time by 2.00%, 2.60%, and 5.60% compared to DCACO, IACO, and the traditional ACO algorithm, respectively. In conclusion, the LTSACO algorithm demonstrates high efficiency and strong robustness, providing an effective optimization solution for multi-arm cooperative picking and significantly contributing to the advancement of multi-arm robotic picking systems. Full article

Sulfur hexafluoride (SF₆), an extraordinary gas insulation medium, must be replaced by environmentally friendly gas in electric equipment because of its high global warming potential (GWP). In this research work, the DC breakdown properties of R404a gas and its mixtures with N₂ and CO₂ are studied under a sphere–sphere electrode configuration and uniform field conditions. The GWP of R404a is 16% of SF₆ and its liquefaction temperature is also in the suitable range for practical applications. Nitrogen and carbon dioxide are mixed with R404a to reduce its boiling point and GWP. Other important parameters such as the self-recoverability, liquefaction temperature, GWP, and synergistic effect of R404a/CO₂ and R404a/N₂ were also studied to complement the insulation performance and the results are comparable to other gas mixtures. As a result, it was found that both the mixtures containing 80% R404a and 20% N₂ or 20% CO₂ possess a breakdown strength of 0.83 times that of SF₆. Mixtures containing an 80% concentration of R404a possess a GWP equal to only 15% of SF₆. These properties make gaseous mixtures containing 80% R404a and 20% N₂ or CO₂ a suitable alternative to SF₆ in medium-voltage gas-insulated equipment. Full article

This study addresses the Plug-in Hybrid Electric Vehicle Routing Problem (PHEVRP), an extension of the classical VRP that incorporates energy mode switching and partial charging strategies. We propose a novel routing model that integrates three energy modes—fuel-only, electric-only, and hybrid—along with partial recharging decisions to enhance energy flexibility and reduce operational costs. To overcome the computational challenges of large-scale instances, a Dantzig–Wolfe decomposition algorithm is designed to efficiently reduce the solution space via column generation. Experimental results demonstrate that the hybrid-mode with partial charging strategy consistently outperforms full-charging and single-mode approaches, especially in clustered customer scenarios. To further evaluate algorithmic performance, an Ant Colony Optimization (ACO) heuristic is introduced for comparison. While the full model fails to solve instances with more than 30 customers, the DW algorithm achieves high-quality solutions with optimality gaps typically below 3%. Compared to ACO, DW consistently provides better solution quality and is faster in most cases, though its computation time may vary due to pricing complexity. Full article

In the shift toward sustainable and resource-efficient manufacturing, Artificial Intelligence (AI) is playing a transformative role in overcoming the limitations of traditional production scheduling methods. This study, based on a Systematic Literature Review (SLR), explores how AI techniques enhance Advanced Planning and Scheduling (APS) systems, particularly under finite-capacity constraints. Traditional scheduling models often overlook real-time resource limitations, leading to inefficiencies in complex and dynamic production environments. AI, with its capabilities in data fusion, pattern recognition, and adaptive learning, enables the development of intelligent, flexible scheduling solutions. The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. These AI-powered APS systems enhance scheduling accuracy, reduce lead times, improve resource utilization, and enable the proactive identification of production bottlenecks. Especially relevant in high-variability sectors like fashion, these approaches support Industry 5.0 goals by enabling agile, sustainable, and human-centered manufacturing systems. The findings have been highlighted in a structured framework for AI-based APS systems supported by metaheuristics that compares the Industry 4.0 and Industry 5.0 perspectives. The study offers valuable implications for both academia and industry: academics can gain a synthesized understanding of emerging trends, while practitioners are provided with actionable insights for deploying intelligent planning systems that align with sustainability goals and operational efficiency in modern supply chains. Full article

This study introduces an advanced automated guided vehicle (AGV) specifically designed for application in recirculating aquaculture systems (RASs). The proposed AGV seamlessly integrates automated feeding, real-time monitoring, and an intelligent path-planning system to enhance operational efficiency. To achieve optimal and adaptive navigation, a hybrid algorithm is developed, incorporating Newton–Raphson-based optimisation (NRBO) alongside ant colony optimisation (ACO). Additionally, dueling deep Q-networks (dueling DQNs) dynamically optimise critical parameters, thereby improving the algorithm’s adaptability to the complexities of RAS environments. Both simulation-based and real-world experiments substantiate the system’s effectiveness, demonstrating superior convergence speed, path quality, and overall operational efficiency compared to traditional methods. The findings of this study highlight the potential of AGV to enhance precision and sustainability in recirculating aquaculture management. Full article

Efficient logistics and transport infrastructure are critical in contemporary urban and interurban scenarios due to their impact on economic development, environmental sustainability, and quality of life. This study explores the use of the Ant Colony Optimization (ACO) metaheuristic applied to the Vehicle Routing Problem (VRP) and the strategic positioning of service stations along major highways. Through a systematic mapping of the literature and practical application to a real-world scenario—specifically, a case study on the Bandeirantes Highway (SP348), connecting Limeira to São Paulo, Brazil—the effectiveness of ACO is demonstrated in addressing complex logistical challenges, including capacity constraints, route optimization, and resource allocation. The proposed method integrates graph theory principles, entropy concepts from information theory, and economic analyses into a unified computational model implemented using Python (version 3.12), showcasing its accessibility for educational and practical business contexts. The results highlight significant improvements in operational efficiency, cost reductions, and optimized service station placement, emphasizing the algorithm’s robustness and versatility. Ultimately, this research provides valuable insights for policymakers, engineers, and logistics managers seeking sustainable and cost-effective solutions in transport infrastructure planning and management. Full article

Multistatic sonar networks (MSNs) have emerged as a powerful approach for enhancing underwater surveillance capabilities. Different from monostatic sonar systems which use collocated sources and receivers, MSNs consist of spatially distributed and independent sources and receivers. In this work, we address the problem of determining the optimal route for a mobile multistatic active sonar source to maximize area coverage, assuming all receiver locations are known in advance. For this purpose, we first develop a Mixed Integer Linear Program (MILP) formulation that determines the route for a single source within a field discretized using a hexagonal grid structure. Next, we propose an Ant Colony Optimization (ACO) heuristic to efficiently solve large problem instances. We perform a series of numerical experiments and compare the performance of the exact MILP solution with that of the proposed ACO heuristic. Full article

Elevated [CO₂] enhances light interception and carboxylation efficiency in plants. The combined effects of [CO₂] and photosynthetic photon flux density (PPFD) on stomatal morphology, leaf anatomy, and photosynthetic capacity in tomato seedlings remain unclear. This study subjected tomato seedlings (Solanum lycopersicum Mill. cv. Jingpeng No.1) to two [CO₂] (ambient [a[CO₂], 400 µmol·mol⁻¹] and enriched [e[CO₂], 800 µmol·mol⁻¹]) and three PPFD levels (L; low[Ll: 200 µmol·m⁻²·s⁻¹], moderate[Lm: 300 µmol·m⁻²·s⁻¹], and high[Lh: 400 µmol·m⁻²·s⁻¹]) to assess their interactive impacts. Results showed that e[CO₂] and increased PPFD synergistically improved relative growth rate and net assimilation rate while reducing specific leaf area and leaf area ratio. Notably, e[CO₂] decreased stomatal aperture (−13.81%) and density (−27.76%), whereas elevated PPFD promoted stomatal morphological adjustments. Additionally, Leaf thickness increased by 72.98% under e[CO₂], with Lm and Lh enhancing this by 10.79% and 41.50% compared to Ll. Furthermore, photosynthetic performance under e[CO₂] was further evidenced by improved chlorophyll fluorescence parameters (excluding non-photochemical quenching). While both e[CO₂] and increased PPFD Photosynthetic performance under e[CO₂] was further evidenced by improved chlorophyll fluorescence parameters (excluding non-photochemical quenching). Moreover, e[CO₂]-Lh treatment maximized total dry mass and seedling health index. Correlation analysis indicated that synergistic optimization of stomatal traits and leaf structure under a combination of e[CO₂] and increased PPFD enhanced light harvesting and CO₂ diffusion, thereby promoting carbon assimilation. These findings highlight e[CO₂]-Lh as an optimal strategy for tomato seedling growth, providing empirical guidance for precision CO₂ fertilization and light management in controlled cultivation. Full article

The interactive effects between nano-silicon dioxide (n-SiO₂) and elevated CO₂ (eCO₂; 645 ppm) on soybean physiology, nitrogen fixation, and nutrient dynamics under climate stress remain underexplored. This study elucidates their combined effects under ambient (aCO₂; 410 ppm) and eCO₂ conditions. eCO₂ + n-SiO₂ synergistically enhanced shoot length (30%), total chlorophyll (112.15%), and photosynthetic rate (103.23%), alongside improved stomatal conductance and intercellular CO₂ (17.19%), optimizing carbon assimilation. Nodulation efficiency increased, with nodule number and biomass rising by 48.3% and 53.6%, respectively, under eCO₂ + n-SiO₂ versus aCO₂. N-assimilation enzymes (nitrate reductase, nitrite reductase, glutamine synthetase, glutamate synthase) surged by 38.5–52.1%, enhancing nitrogen metabolism. Concurrently, phytohormones (16–21%) and antioxidant activities (15–22%) increased, reducing oxidative markers (18–22%), and bolstering stress resilience. Nutrient homeostasis improved, with P, K, Mg, Cu, Fe, Zn, and Mn elevating in roots (13–41%) and shoots (13–17%), except shoot Fe and Zn. These findings demonstrate that n-SiO₂ potentiates eCO₂-driven benefits, amplifying photosynthetic efficiency, nitrogen fixation, and stress adaptation through enhanced biochemical and nutrient regulation. This synergy underscores n-SiO₂ role in optimizing crop performance under future CO₂-rich climates, advocating nano-fertilizers as sustainable tools for climate-resilient agriculture. Full article

Rationally designing and synthesizing chemosensors capable of simultaneously detecting both anions and cations via water content modulation is challenging. In this study, we synthesized and characterized a novel triazine calixarene derivative-based iodide and copper ion-selective fluorescent “turn-off” sensor. This dual-channeled fluorescent probe is able to recognize Cu²⁺ and I⁻ ions simultaneously in aqueous systems. The fluorescent sensor s4 was synthesized by displacement reaction of acridine with 1, 3-bis (dichloro-mono-triazinoxy) benzene in acetonitrile. Mass spectrometry (MS), UV-vis, and fluorescence spectra were acquired to characterize the fluorescence response of s4 to different cations and anions, while infrared (IR) spectroscopy and isothermal titration calorimetry (ITC) were employed to study the underlying selectivity mechanism of s4 to Cu²⁺ and I⁻. In detail, s4 displayed extremely high sensitivity to Cu²⁺ with over 80% fluorescence decrement caused by the paramagnetic nature of Cu²⁺ in the aqueous media. The reversible fluorescence response to Cu²⁺ and the responses to Cu²⁺ in the solution of other potential interferent cations, such as Li⁺, Na⁺, K⁺, Ca²⁺, Cd²⁺, Zn²⁺, Sr²⁺, Ni²⁺, Co²⁺ were also investigated. Probe s4 also exhibited very good fluorescence selectivity to iodide ions under various anion (F⁻, Cl⁻, Br⁻, NO₃⁻, HSO₄⁻, ClO₄⁻, PF₆⁻, AcO⁻, H₂PO₄⁻) interferences. In addition to the fluorescent response to I⁻, s4 showed a highly selective naked-eye-detectable color change from colorless to yellow with the other tested anions. Full article