Search Results (6,565)

Traditional Case-Based Reasoning (CBR) methods face significant methodological challenges, including limited information resources in case databases, methodologically inadequate similarity calculation approaches, and a lack of standardized case revision mechanisms. These limitations lead to suboptimal case matching and insufficient solution adaptation, highlighting critical gaps in the development of CBR methodologies. This paper proposes a novel CBR framework enhanced by generative AI, aiming to improve and innovate existing methods in three key stages of traditional CBR, thereby enhancing the accuracy of retrieval and the scientific nature of corrections. First, we develop an ontology model for comprehensive case representation, systematically capturing scenario characteristics, risk typologies, and strategy frameworks through structured knowledge representation. Second, we introduce an advanced similarity calculation method grounded in triangle theory, incorporating three computational dimensions: attribute similarity measurement, requirement similarity assessment, and capability similarity evaluation. This multi-dimensional approach provides more accurate and robust similarity quantification compared to existing methods. Third, we design a generative AI-based case revision mechanism that systematically adjusts solution strategies based on case differences, considering interdependence relationships and mutual influence patterns among risk factors to generate optimized solutions. The methodological framework addresses fundamental limitations in existing CBR approaches through systematic improvements in case representation, similarity computation, and solution adaptation processes. Experimental validation using actual case data demonstrates the effectiveness and scientific validity of the proposed methodological framework, with applications in risk assessment and emergency response scenarios. The results show significant improvements in case-matching accuracy and solution quality compared to traditional CBR approaches. This method provides a robust methodological foundation for CBR-based decision-making systems and offers practical value for risk management applications. Full article

Background/Objectives: Oral health plays a crucial role in the physical, emotional, and social well-being of children. Data from 2019 indicate that oral diseases remain a major concern in the Italian paediatric population, affecting not only children’s health but also caregivers’ well-being. This study aimed to assess the importance attributed by Italian families to their children’s oral health and correlate parents’ perceptions with children’s actual oral health status. Methods: A total of 131 children aged 0–12 years, admitted to the IRCCS Giannina Gaslini Children’s Hospital (Genoa, Italy) for reasons other than dental problems, were enroled between January 1 and December 31, 2024. Parents completed validated questionnaires (ECOHIS or PCPQ + FIS) based on their child’s age, along with supplementary questions on socio-demographic background and dental history. Oral examination was performed to assess dmft/DMFT scores, the Index of Orthodontic Treatment Need (IOTN), and the Modified Gingival Index (MGI). Results: In younger children (0–5 years), oral health was generally good, but the presence of caries negatively impacted the family’s quality of life. Older children (6–12 years) showed higher rates of caries and gingival inflammation, affecting their daily functioning and emotional well-being. Poor oral health was more common among children of non-European backgrounds and those with lower parental education. Early dental visits, within the recommended 24 months of age, were rare. Conclusions: Despite clear international recommendations, early dental visits remain uncommon, and many children experience preventable oral health issues. These findings highlight the urgent need to improve caregiver education and public health strategies to promote early preventive dental care. Full article

Accurate postharvest quality evaluation of soybeans is essential for preserving product value and meeting industry standards. Traditional inspection methods are often inconsistent, labor-intensive, and unsuitable for high-throughput operations. This study presents a non-destructive soybean classification approach using a simplified reflectance-mode hyperspectral imaging system equipped with a single light source, eliminating the complexity and maintenance demands of dual-light configurations used in prior studies. A spectral–spatial data fusion strategy was developed to classify harvested soybeans into four categories: normal, split, diseased, and foreign materials such as stems and pods. The dataset consisted of 1140 soybean samples distributed across these four categories, with spectral reflectance features and spatial texture attributes extracted from each sample. These features were combined to form a unified feature representation for use in classification. Among multiple machine learning classifiers evaluated, Linear Discriminant Analysis (LDA) achieved the highest performance, with approximately 99% accuracy, 99.05% precision, 99.03% recall and 99.03% F1-score. When evaluated independently, spectral features alone resulted in 98.93% accuracy, while spatial features achieved 78.81%, highlighting the benefit of the fusion strategy. Overall, this study demonstrates that a single-illumination HSI system, combined with spectral–spatial fusion and machine learning, offers a practical and potentially scalable approach for non-destructive soybean quality evaluation, with applicability in automated industrial processing environments. Full article

Natural bioactive compounds found in Momordica charantia including polysaccharides, saponins, polyphenols, alkaloids, and notably polypeptide-p (often referred to as “plant insulin”)—have shown promising potential in shaping nutritional and therapeutic strategies for managing diabetes, metabolic disorders, and other nutrition-related diseases. Both retrospective and prospective analyses of bitter gourd’s functional properties such as its antioxidant, antitumor, immunomodulatory, and antibacterial effects highlight its innovative use as a food ingredient in developing targeted nutritional therapies. Assessing its applicability in the food industry, particularly through the fortification of products with bitter gourd powders, pulp, juice, or extracts, could enhance consumer acceptance and elevate the perceived quality of nutritionally superior foods. The nutrifunctional attributes revealed by its nutritional profile support the strategic integration of bitter gourd into various food formulations, contributing to a broader and more diverse range of dietary options. This diversification is especially valuable in addressing the dietary monotony often associated with diabetic nutrition plans, which continue to present significant challenges. The foundation laid by this review drawing on both theoretical insights and practical applications serves as a springboard for future research into the fortifying potential of bitter gourd-based preparations. Ultimately, such products may be recommended not only as nutritional supplements but also as part of clinical and hygienic-dietetic practices. Full article

Prunus humilis is rich in various minerals, organic acids, proteins, and carbohydrates, but its sour taste limits fresh consumption and industry growth. Methyl jasmonate, a plant growth regulator known to enhance fruit quality, has been studied in other fruits, but research on its effects on P. humilis has not yet been reported. This experiment used the P. humilis cultivar ‘Nongda No. 4’ as the material. During the fruit development stages (the pre-young fruit stage and pre-coloring and enlargement stage), the fruiting branches were sprayed with a 20 mg/L methyl jasmonate solution four times. The results indicate that exogenous methyl jasmonate increases the content of various sugar components in P. humilis fruits throughout their development, with a particularly strong effect in the later stages of fruit development. It effectively reduces the content of malic acid and citric acid in these later stages while significantly enhancing flavor-related attributes such as the sweetness, sugar–acid ratio, and sweetness–acid ratio. Moreover, methyl jasmonate markedly promoted the accumulation of different forms of calcium in the fruit. Specifically, at the fully ripe stage, the total sugar content increased significantly by 18.64% (p < 0.05), the total acid content decreased by 15.95% (p < 0.05), and the total calcium content increased by 55.98% (p < 0.05). Correlation and principal component analyses revealed that sugars, acids, and calcium are closely linked in P. humilis, and exogenous treatment with methyl jasmonate effectively improved the overall quality score of sugars, acids, and calcium in the fruit throughout its development. In conclusion, exogenous methyl jasmonate can effectively improve the sugar–acid quality, flavor, and calcium content of P. humilis fruits. This provides a theoretical foundation for cultivation management, quality enhancement, and the breeding of fresh-eating cultivars. Full article

Accurate assessment of protein content in Foods for Special Medical Purposes (FSMPs) is critical for patients with chronic kidney disease, who require tightly regulated protein intake. This study aimed to develop and apply a rapid, low-volume, and reproducible microchip-based gel electrophoresis method for analyzing total nitrogen (TN) content and electrophoretic profiles in FSMPs. Products of different consistencies (powder, liquid, yoghurt-like) were tested to evaluate the influence of common additives (e.g., milk proteins, stabilizers, sweeteners) on TN levels and protein patterns. The results revealed considerable variation in fractions among brands, largely attributable to additive composition. Notably, TN levels often exceeded the declared protein content, potentially leading to unintended nitrogen overconsumption in clinical settings. Statistical analysis identified significant TN differences between infant and adult FSMPs in liquid formulations, while powdered forms showed no such distinction. These findings highlight the clinical importance of precise analytical monitoring, as discrepancies between measured TN and labeled protein content could compromise dietary management in vulnerable populations. The proposed method provides a reliable tool for FSMP quality control and supports safer nutritional planning in therapeutic diets. Full article

A comprehensive overview is provided on factors and processes influencing the final quality of a cup of coffee, with an emphasis on the brewing method’s central role. Coffee quality assessment, both at the bean and cup level, combines objective parameters (color, moisture, bean defects, density) with a notable degree of subjectivity, as consumer sensory perception is ultimately decisive. The brewing technique is described as a critical determinant of the final chemical, physical, and sensory attributes. Key parameters such as aroma profile, pH, titratable acidity, total and filtered solids, lipid and fatty acid content, viscosity, foam (crema), and colorimetric indices are detailed as essential metrics in coffee quality evaluation. Roasting creates most of coffee’s key aroma compounds. The brewing method further shapes the extraction of both volatile and other bioactive compounds like caffeine, chlorogenic acids, and lipids. Brewing methods significantly affect acidity, “body,” and crema stability, while water quality, temperature, and pressure are shown to impact extraction results and sensory properties. Attention is paid to how methods such as Espresso, filter, French press, and cold brew yield distinct physicochemical and sensory profiles in the cup. Overall, the review highlights the multifaceted nature of coffee cup quality and the interplay between raw material, processing, and preparation, ultimately shaping the coffee sensory experience and market value. Full article

This study aimed to evaluate the effects of controlled atmosphere (CA) treatment on the postharvest quality of strawberries harvested at different 50% and 80% maturity under export shipping conditions. The strawberries were subjected to CA and refrigerated container (Reefer) environments at 10 °C, and their quality attributes were then analyzed. Metabolomic profiling revealed significant variations in primary and secondary metabolites and volatile organic compounds (VOCs). A pathway analysis revealed that CA conditions altered metabolic pathways related to sugar, amino acid, and energy metabolism during storage. CA treatment effectively delayed the accumulation of anthocyanins and enhanced the levels of specific amino acids and VOCs essential for the flavor and aroma of strawberries. Bioluminescence imaging revealed that CA treatment effectively reduced lipid peroxidation. A correlation analysis showed that certain VOCs and secondary metabolites significantly correlated with lipid peroxidation, indicating their role in enhancing antioxidant activity and reducing oxidative stress. These results suggest that CA conditions are associated with significantly reduced weight loss, the maintenance of firmness, and lower respiration rates in strawberries, particularly in those harvested at 80% maturity, extending the shelf life and improving the sensory quality of strawberries. Therefore, CA treatment is an effective method for long-term export. Full article

Open-vocabulary object detection (OVOD) aims to localize and recognize objects in images by leveraging category-specific textual inputs, including both known and novel categories. While existing methods excel in general scenarios, their performance significantly deteriorates in domain-specific fine-grained detection because of their heavy reliance on high-quality textual descriptions. In specialized domains, such textual descriptions are often affected by newly introduced terms or subjective human biases, limiting their applicability. In this paper, we propose an attribute decomposition–aggregation approach for the OVOD to address these challenges. By decomposing categories into fine-grained attributes and learning them in a multi-label manner, our method mitigates text quality issues caused by novel terms and human bias. During inference, unseen fine-grained category texts can be effectively represented by combining the decomposed attributes for detection. Even if the model learns the attributes, a key limitation of current methods is the insufficient utilization of textual attributes. To mitigate this issue, we propose an attribute-aggregation module that enhances the discriminative capability by emphasizing critical attributes for distinguishing target objects from foreground elements. To demonstrate the effectiveness of our OVOD framework, we evaluate our method on both our newly constructed military dataset and the public LAD dataset. Experimental results demonstrate that our method outperforms existing methods in domain-specific fine-grained open-vocabulary detection tasks. Full article

This study addresses this gap by proposing a multilevel fuzzy evaluation model combined with an analytic hierarchy process (AHP) to quantify the greenness of furniture products across their entire lifecycle. Focusing on an office desk as a case study, we developed an indicator system encompassing environmental attributes, resource efficiency, energy consumption, economic costs, and quality performance. Weighting results revealed that environmental attributes (27.2%) and resource efficiency (27.2%) dominated the greenness evaluation, with material recycling rate (33.5%) and solid waste pollution (24.3%) as critical sub-indicators. The prototype achieved a moderate greenness score of 70.38/100, highlighting optimization potential in renewable material adoption (10% current rate) and modular design for disassembly. Mechanically recycled materials could reduce lifecycle emissions by 18–25% in key categories. The model demonstrates scalability for diverse furniture types and informs policy-making by prioritizing high-impact areas such as toxic material reduction and energy-efficient manufacturing, thus amplifying its global and interdisciplinary multiplier effects. Full article

Natural resource assets inherently integrate tripartite synthesis of legal, economic, and ecological attributes. They serve dual critical functions as foundational elements supporting the evolution of new-quality productive forces and pivotal mechanisms safeguarding ecosystemic integrity. It has become a global consensus and direction of action to advance comprehensive supervision of natural resource assets and practice the concept of “Community of Life for Human and Nature”. Under the background of the super-ministry system restructuring in China, comprehensive supervision of natural resource assets remains challenged by system fragmentation in supervision objectives and multifaceted interest conflicts among stakeholders. In light of this, this research focuses on the theoretical justification and system optimization of the comprehensive supervision of natural resource assets in China. Using comparative analysis and normative analysis methods, we validate the system’s function on the comprehensive supervision of natural resource assets, summarize foreign experiences, and ultimately aim to explore the optimization pathway of the legal system for the comprehensive supervision of natural resource assets. The results show the following: (1) The choice of the legal system for the comprehensive supervision of natural resource assets emerges as the functional product aligning societal objectives, the rational paradigm for achieving efficient resource allocation, and the adaptive response to the external effects of common property. (2) The system supply of comprehensive supervision of natural resource assets in foreign countries is characterized by normative convergence in conceptual elements and typological categorization in objectives and objects. Therefore, this research recommends that, in order to optimize the system of the comprehensive supervision of natural resource assets in China, (1) in terms of protection of source, natural resource assets should be categorized, with operational natural resource assets focusing on management and public welfare natural resource assets focusing on conservation. (2) In terms of valuation, the economic valuation of natural resource assets should be integrated with ecosystem service assessments to enhance fair market equity. (3) In terms of method, the big data center should be established to enable the synergistic integration of technological innovation and system reforms. (4) In terms of subject, requiring the participation of various government departments, non-governmental organizations, the general public, and other parties could realize the connection of different legal bases for the comprehensive supervision of natural resource assets and the balance of multiple rights and interests, which should help to achieve balanced resource efficiency and biodiversity conservation and safeguard national ecological security. Full article

Green mold formed by Penicillium digitatum is a major disease that limits the yield and overall value of postharvest citrus fruits. The antifungal activity of sodium cuminate (SC) against P. digitatum and the corresponding mechanism were explored in this research. The minimal inhibitory concentration (MIC) and minimal fungicidal concentration (MFC) of SC against P. digitatum were 0.4 and 0.8 g L⁻¹, respectively. SC (8× MFC) reduced the incidence of disease in Ponkan fruits without compromising their quality. The results of CFW staining and extracellular alkaline phosphatase assays revealed that 1/2MIC SC for 30 min had no impact on the cell wall integrity of P. digitatum. In contrast, 1/2MIC SC apparently destroyed cell membrane integrity, as shown by the increase in the content of reactive oxygen species (ROS), malondialdehyde, and H₂O₂. The addition of exogenous cysteine (Cys) or diphenyleneiodonium chloride (DPI) significantly mitigated the cytotoxic effects of SC. At the same time, mitochondrial membrane potential was significantly decreased by 1/2MIC SC, and the addition of exogenous Cys or DPI restored it to normal levels. In summary, the antifungal capacity of SC might be attributable to membrane damage in P. digitatum caused by oxidative stress. Full article

MRNA-based therapeutics and vaccines represent a rapidly expanding frontier in biomedical innovation, with lipid nanoparticles (LNPs) serving as a clinically validated delivery platform. This study explores critical quality attributes of LNP-mRNA formulations, with a particular focus on in vitro biological activity, a key quality attribute of vaccine activity and batch-to-batch consistency. We discuss the importance of optimizing both LNP components and mRNA structure, highlighting recent advances in formulation strategies. Furthermore, we examine the influence of factors such as cell-line selection, experimental design, storage conditions, and targeted cellular delivery on transduction efficiency. Our findings underscore the need for standardized in vitro assays and process-integrated monitoring to support the scalable development and regulatory assessment of mRNA-based therapies. Full article

The fabrication of WC-based cemented carbides faced challenges including inhomogeneous composition and grain coarsening. To solve these problems, WC–Co cemented carbides were fabricated via spark plasma sintering (SPS) using core–shell WC–Co powders prepared by an electroless plating method. The effects of sintering pressure and Co content on the microstructure and mechanical properties of the cemented carbides were investigated. The results showed that, with increasing sintering pressure, the relative density of the sintered samples was improved (98.4–99.6%) while the grains were coarsened (0.94–1.07 μm). The optimal properties (fracture toughness 11.11 MPa·m^1/2, and hardness 2100.3 HV30) were obtained when sintered with a pressure of 20 MPa. Grain coarsening at higher pressure (30 MPa) reduced the toughness of the cemented carbides. When the Co content was increased from 3 wt.% to 8 wt.%, fracture toughness was improved while the hardness of the cemented carbides was reduced, attributed to the intrinsic high toughness and low hardness of the Co phase. The WC–8 wt.% Co cemented carbides exhibited optimized synergic mechanical performance (hardness of 1874.2 HV30 and fracture toughness of 13.77 MPa·m^1/2). This work elucidated the relationship between the key sintering parameters (pressure and Co content) and the microstructure and mechanical properties of the cemented carbides. The achievements obtained provide a theoretical foundation for high-quality fabrication of the WC–Co cemented carbides. Full article

As mental health issues such as stress, anxiety, and depression become increasingly prevalent in urban populations, there is a critical need to embed restorative functions into the built environment. Urban parks, as integral components of ecological infrastructure, play a vital role in promoting psychological well-being. This study explores how diverse park environments facilitate mental health recovery through multi-sensory engagement, using integrated psychophysiological assessments in a wetland park in Zhengzhou, China. Electroencephalography (EEG) and perceived restoration scores were employed to evaluate recovery outcomes across four environmental types: waterfront, wetland, forest, and plaza. Key perceptual factors—including landscape design, spatial configuration, biodiversity, and facility quality—were validated and analyzed for their roles in shaping restorative experiences. Results reveal significant variation in recovery effectiveness across environments. Waterfront areas elicited the strongest physiological responses, while plazas demonstrated lower restorative benefits. Two recovery pathways were identified: a direct, sensory-driven process and a cognitively mediated route. Biodiversity promoted physiological restoration only when mediated by perceived restorative qualities, whereas landscape and spatial attributes produced more immediate effects. Facilities supported psychological recovery mainly through cognitive appraisal. The study proposes a smart park framework that incorporates environmental sensors, adaptive lighting, real-time biofeedback systems, and interactive interfaces to enhance user engagement and monitor well-being. These technologies enable urban parks to function as intelligent, health-supportive infrastructures within the broader built environment. The findings offer evidence-based guidance for designing responsive green spaces that contribute to mental resilience, aligning with the goals of smart city development and healthy life-building environments. Full article