Search Results (5,022)

The realization of agricultural modernization inevitably requires the improvement of agricultural land productivity. Rural public science and technology services is an important driving force to improve agricultural land productivity. However, can rural public science and technology services accelerate the process of agricultural modernization by improving land productivity? This paper innovatively constructs an evaluation index system and an mediating mechanism model, measures the comprehensive index of agricultural modernization and rural public science and technology services through the global entropy method, and empirically tests the mediating effect of the mechanism of “land productivity” with the help of measurement methods such as the Sobel–Goodman test and Bootstrap test. The research results find that rural public science and technology services can positively promote agricultural modernization and pass the 1% significance level test. There is a significant mediating effect of “increasing production” in the impact of rural public science and technology services on agricultural modernization, that is, rural public science and technology services can significantly promote agricultural modernization through the mechanism of “improving land productivity”. Government intervention and economic growth are significantly positive, which can significantly promote agricultural modernization. These findings have clear policy implications: Chinese government should accelerate the filling of gaps in rural public technology services between urban and rural areas in the southwest region, empower land productivity through science and technology, and promote the transformation of agricultural scientific and technological achievements into real productive forces. This research is helpful to provide policy reference and case experience for similar areas to speed up agricultural modernization by giving full play to the mechanism of “improving land productivity” of agricultural science and technology services. Full article

Artificial intelligence (AI) and machine learning (ML) are increasingly transforming the landscape of cosmetic formulation, enabling the development of safer, more effective, and personalized products. This article explores how AI-driven predictive modeling is applied across various components of cosmetic products, including surfactants, polymers, fragrances, preservatives, antioxidants, and prebiotics. These technologies are employed to forecast critical properties such as texture, stability, and shelf-life, optimizing both product performance and user experience. The integration of computational toxicology and ML algorithms also allows for early prediction of skin sensitization risks, including the likelihood of adverse events such as allergic contact dermatitis. Furthermore, AI models can support efficacy assessment, bridging formulation science with dermatological outcomes. The article also addresses the ethical, regulatory, and safety challenges associated with AI in cosmetic science, underlining the need for transparency, accountability, and harmonized standards. The potential of AI to reshape dermocosmetic innovation is vast, but it must be approached with robust oversight and a commitment to user well-being. Full article

Many recent discoveries highlight the existence of a robust bidirectional link between nutrition and psychological processes. Despite these developments, the systematic and formalized study of this connection is only beginning to be undertaken, and nutritional psychology is not yet considered a formal area of study within the psychological sciences. This paper defines the scope of nutritional psychology through 6 core areas of conceptualization, each informed by an interdisciplinary and growing body of evidence spanning the psychological and nutritional sciences. These include the diet-conative/affective, diet-cognitive, diet-sensory/perception, diet-interoceptive, diet-psychosocial, and diet-environmental relationships. Introducing these conceptualizations contributes to the development of innovative interdisciplinary language, method, and conceptualization of the diet-mental health relationship within nutritional psychology. Full article

Target tracking is a representative task in multi-agent reinforcement learning (MARL), where agents must collaborate effectively in environments with dense obstacles, evasive targets, and high-dimensional observations—conditions that often lead to local optima and training inefficiencies. To address these challenges, this paper proposes a collaborative tracking algorithm for UAVs that integrates behavior cloning with temporal difference (BCTD) and multi-agent proximal policy optimization (MAPPO). Expert trajectories are generated using the artificial potential field (APF), followed by policy pre-training via behavior cloning and TD-based value optimization. MAPPO is then employed for dynamic fine-tuning, enhancing robustness and coordination. Experiments in a simulated environment show that the proposed MAPPO+BCTD framework outperforms MAPPO, QMIX, and MADDPG in success rate, convergence speed, and tracking efficiency. The proposed method effectively alleviates the local optimization problem of APF and the training inefficiency problem of RL, offering a scalable and reliable solution for dynamic multi-agent coordination. Full article

This paper presents the development, implementation, and outcomes of the ELEVATE-US-UP (Engaging Learners through Exploration of Visionary Academic Thought and Empowerment in UnderServed and UnderPrivileged communities) teaching methodology, an equity-centered, culturally responsive pedagogical framework designed to enhance student engagement, academic performance, and science identity among underrepresented learners. This framework was piloted at Northern New Mexico College (NNMC), a Hispanic- and minority-serving rural institution. ELEVATE-US-UP reimagines science education as a dynamic, inquiry-driven, and contextually grounded process that embeds visionary scientific themes, community relevance, trauma-informed mentoring, and authentic assessment into everyday instruction. Drawing from culturally sustaining pedagogy, experiential learning, and action teaching, the methodology positions students not as passive recipients of content but as knowledge-holders and civic actors. Implemented across upper-level environmental science courses, the method produced measurable gains: class attendance rose from 67% to 93%, average final grades improved significantly, and over two-thirds of students reported a stronger science identity and a newfound confidence in their academic potential. Qualitative feedback highlighted increased perceptions of classroom inclusivity, community relevance, and instructor support. By centering on cultural context, student voice, and place-based application, the ELEVATE-US-UP framework offers a replicable and scalable model for educational transformation in underserved regions. Full article

This study delivers a rigorous and in-depth bibliometric examination of 693 scholarly publications addressing the intersection of metaverse technologies and banking, retrieved from the Web of Science Core Collection. Through advanced scientometric tools, including VOSviewer and Bibliometrix, the research systematically unpacks the evolving intellectual and thematic contours of this interdisciplinary frontier. The co-occurrence analysis of keywords reveals a landscape shaped by seven core thematic clusters, encompassing immersive user environments, digital infrastructure, experiential design, and ethical considerations. Factorial analysis uncovers a marked bifurcation between experience-driven narratives and technology-centric frameworks, with integrative concepts such as technology, information, and consumption serving as conceptual bridges. Network visualizations of authorship patterns point to the emergence of high-density collaboration clusters, particularly centered around influential contributors such as Dwivedi and Ooi, while regional distribution patterns indicate a tri-continental dominance led by Asia, North America, and Western Europe. Temporal analysis identifies a significant surge in academic interest beginning in 2022, aligning with increased institutional and commercial experimentation in virtual financial platforms. Our findings argue that the incorporation of metaverse paradigms into banking is not merely a technological shift but a systemic transformation in progress—one that blurs the boundaries between speculative innovation and tangible implementation. This work contributes foundational insights for future inquiry into digital finance systems, algorithmic governance, trust architecture, and the wider socio-economic consequences of banking in virtualized environments. Whether a genuine leap toward financial evolution or a sophisticated illusion, the metaverse in banking must now be treated as a systemic phenomenon worthy of serious scrutiny. Full article

The United Nations’ 2030 Agenda for Sustainable DeveTablelopment centers on the 17 Sustainable Development Goals (SDGs). Among these goals, two address climate change education: Goal 13, Climate Action, and Goal 4, Quality Education. In order to build a more sustainable future, climate change education is critical. In 2022, New Jersey became the first state in the US to integrate climate change into learning standards across subjects and grade levels K-12. In an effort to better understand the way in which teachers began to include climate change in their instruction, 50 teachers were observed implementing a lesson of their choosing that included climate change throughout the 2023–2024 academic year. Though most of the observed lessons featured science, many subject areas were included in the dataset, such as art, technology, history, and physical education. Teachers engaging in climate change instruction tended to use a variety of instructional practices. In nearly all cases, a multitude of methodologies were used in each lesson. However, small group instruction was featured in nearly all observed lessons. Quantitative descriptions of the findings are followed by three vignettes of exemplar instruction to provide a clearer understanding of the context of this work. These findings provide a scope for how climate change can be integrated in instructional settings at scale and suggestions for leveraging the experiences of early adopters of this innovation to support widespread implementation. Full article

Plant flowers are recognized as a rich source of bioactive phenolic compounds. In this study, for the first time, the recovery of antioxidant phenolic compounds from Cytisus striatus flowers (CF) was optimized using microwave-assisted extraction (MAE). The variables (% of ethanol, temperature, and time) were studied using a response surface methodology (RSM). Extraction efficiency was assessed by total phenol content, total flavonoid content, and the antioxidant capacity through DPPH, ABTS, FRAP, and CUPRAC assays. Additionally, cytotoxicity and anti-inflammatory properties were evaluated in different cell lines. The optimal extraction conditions (87.6% ethanol, 160.8 °C and 8.76 min) yielded extracts rich in phenolics (85.9 mg GAE/g CF) and flavonoids (120.3 mg RE/g CF), with strong antioxidant capacity. LC-MS/MS analysis identified 27 phenolic compounds, including chrysin, apigenin, and quercetin derivatives. Cytotoxicity tests showed that CF extract maintained high viability (>80%) in human embryonic kidney (HEK293T) and human lung adenocarcinoma (A549) cells up to 2000 µg/mL, indicating low cytotoxicity. The anti-inflammatory potential was evidenced by a decrease in IL-1β levels and an increase in IL-10 cytokine production in LPS-stimulated macrophages. These results highlight the great potential of CF as a promising bioresource to obtain value-added compounds for the development of functional foods, nutraceuticals, and cosmetic products. Full article

Medical education is the paradigm of 21st century education and the current changes involve the adoption of integrative and comprehensive patient-centered teaching and learning approaches. Thus, curricular developers from George Emil Palade University of Medicine, Pharmacy, Sciences, and Technology of Targu Mures (G.E. Palade UMPhST of Targu Mures) have recently designed and implemented an innovative medical curriculum, as well as two valuable assessment tools for both theoretical knowledge and practical skills. Thus, during the first three preclinical years, the students will benefit from an organ- and system-centered block teaching approach, while the clinical years will focus on enabling students to achieve the most important practical skills in clinical practice, based on a patient bedside teaching system. In terms of theoretical knowledge assessment, the UNiX center at G.E. Palade UMPhST of Targu Mures, a recently designed center endowed with the latest next-generation technology, enables individualized, secured multiple-choice question-based assessments of the student’s learning outcomes. Moreover, an intelligent assessment tool for practical skills was also recently implemented in our branch in Hamburg, the Objective Structured Clinical Examination (O.S.C.E). This system uses direct observations for testing the student’s practical skills regarding anamnesis, clinical exams, procedures/maneuvers, the interpretation of laboratory tests and paraclinical investigations, differential diagnosis, management plans, communication, and medical counselling. The integrative, comprehensive, patient-centered curriculum and the intelligent assessment system, implemented in G.E Palade UMPhST of Targu Mures, help define innovation in education and enable the students to benefit from a high-quality medical education. Full article

Vibrio parahaemolyticus is the leading cause of bacterial diarrhea in humans from shellfish consumption. In Thailand, blood clam is a popular shellfish, but homemade cooking often results in insufficient heating. Therefore, consumers may suffer from food poisoning due to Vibrio infection. This study aimed to determine the effect of chitooligosaccharide conjugated with epigallocatechin gallate (COS-EGCG) at different concentrations (200 and 400 ppm) combined with high-voltage atmospheric cold plasma (HVACP) on inhibiting V. parahaemolyticus in vitro and in challenged blood clam meat. Firstly, HVACP conditions were optimized for gas composition and treatment time (20 and 60 s); a 70% Ar and 30% O₂ gas mixture resulted in the highest ozone formation and a treatment time of 60 s was used for further study. COS-EGCG conjugate at 400 ppm with HVACP (ACP-CE400) completely killed V. parahaemolyticus after incubation at 37 °C for 6 h. Furthermore, an antibacterial ability of ACP-CE400 treatment against bacterial cells was advocated due to the increased cell membrane damage, permeability, and leakage of proteins and nucleic acids. Scanning electron microscopy (SEM) showed cell elongation and pore formation, while confocal microscopy revealed disrupted biofilm formation. Additionally, the shelf life of challenged blood clam meat treated with ACP-CE400 was extended to nine days. SEM analysis revealed damaged bacterial cells on the meat surface after ACP-CE400 treatment, indicating the antibacterial activity of the combined treatment. Thus, HVACP combined with COS-EGCG conjugate, especially at a highest concentration (400 ppm), effectively inhibited microbial growth and extended the shelf life of contaminated blood clam meat. Full article

Design and use of wearable technology have grown exponentially, particularly in consumer products and service sectors, e.g., healthcare. However, there is a lack of a comprehensive understanding of wearable technology in consumer acceptance. This systematic review utilized a PRISMA on peer-reviewed articles published between 2014 and 2024 and collected on WoS, Scopus, and ScienceDirect. A total of 38 full-text articles were systematically reviewed and analyzed using bibliometric, thematic, and descriptive analysis to understand the technical functions of digital wearable products (DWPs) in consumer acceptance. The findings revealed four key functions: (i) wearable technology, (ii) appearance and design, (iii) biomimetic innovation, and (iv) security and privacy, found in eight types of DWPs, among them smartwatches, medical robotics, fitness devices, and wearable fashions, significantly predicted the customers’ acceptance moderated by the behavioral factors. The review also identified five key outcomes: health and fitness, enjoyment, social value, biomimicry, and market growth. The review proposed a comprehensive acceptance model that combines biomimetic principles and AI-driven features into the technical functions of the technical function model (TAM) while addressing security and privacy concerns. This approach contributes to the extended definition of TAM in wearable technology, offering new pathways for biomimetic research in smart devices and robotics. Full article

This study investigates the effects of sodium sulfate (Na₂SO₄) dosage, reaction temperature, and processing time on the structural decomposition of complex compounds in copper slag. Experimental results demonstrated that applying 20% Na₂SO₄ achieves an impressive decomposition rate of 89%, highlighting its effectiveness in liberating valuable metals from the slag matrix. The optimal temperature for maximizing fayalite decomposition is determined to be 900 °C, which significantly enhances reaction kinetics and efficiency. Furthermore, extending the reaction time to 90 min resulted in the highest observed decomposition efficiency. Subsequent leaching experiments in sulfuric acid confirmed that the liberated metal transitioned into the solution phase was very effective, ensuring high metal recovery rates. The treated samples demonstrated metal recovery rates of 97% for copper (Cu), 96% for iron (Fe), and 93% for zinc (Zn). In contrast, the untreated samples exhibited considerably lower recovery rates, with copper at 61%, iron at 59%, and zinc at 65%. Additionally, this approach mitigates filtration challenges by preventing the formation of silica gel. These findings provide key operational parameters for optimizing metal recovery from copper slag and establish a solid foundation for advancing sustainable and efficient resource extraction research. Full article

Mammography is the main method for early detection of breast cancer, which is still a major global health concern. However, inter-reader variability and the inherent difficulty of interpreting subtle radiographic features frequently limit the accuracy of diagnosis. A thorough assessment of deep convolutional neural networks (CNNs) for automated mammogram classification is presented in this work, along with the introduction of two innovative multi-view integration techniques: Dual-Branch Ensemble (DBE) and Merged Dual-View (MDV). By setting aside two datasets for out-of-sample testing, we evaluate the generalizability of the model using six different mammography datasets that represent various populations and imaging systems. We compare a number of cutting-edge architectures on both individual and combined datasets, including ResNet, DenseNet, EfficientNet, MobileNet, Vision Transformers, and VGG19. Both MDV and DBE strategies improve classification performance, according to experimental results. VGG19 and DenseNet both obtained high ROC AUC scores of 0.9051 and 0.7960 under the MDV approach. DenseNet demonstrated strong performance in the DBE setting, achieving a ROC AUC of 0.8033, while ResNet50 recorded a ROC AUC of 0.8042. These enhancements demonstrate how beneficial multi-view fusion is for boosting model robustness. The impact of domain shift is further highlighted by generalization tests, which emphasize the need for diverse datasets in training. These results offer practical advice for improving CNN architectures and integration tactics, which will aid in the creation of trustworthy, broadly applicable AI-assisted breast cancer screening tools. Full article

Historical districts are the mark of the continuity of urban history and are non-renewable. Typhoon disasters rank among the most serious and frequent natural threats to China’s coastal regions. Improving the wind resilience of China’s coastal historical districts is of great significance for their protection and inheritance. Accurately analyzing the different characteristics of the influencing factors of wind resilience in China’s coastal historical districts can provide a theoretical basis for alleviating the damage caused by typhoons and formulating disaster prevention measures. This paper accurately identifies the main influencing factors of wind resilience in China’s coastal historical districts and constructs an influencing factor system from four aspects: block level, building level, typhoon characteristics, and emergency management. An IIM model for the systematic analysis of influencing factors of wind resilience in China’s coastal historical districts based on the Improved Decision Making Trial and Evaluation Laboratory (IDEMATEL), Interpretive Structural Modeling (ISM), and Matrices Impacts Croises-Multiplication Appliance Classement (MICMAC) methods is established. This allows us to explore the mechanism of action of internal influencing factors of typhoon disasters and construct an influencing factor system, in order to propose prevention measures from the perspective of typhoon disaster characteristics and the overall perspective of China’s coastal historical districts. The results show that the driving force of a building’s windproof design in China’s coastal historical districts is low, but its dependence is strong; the driving forces of block morphology, typhoon level, and emergency plan are strong, but their dependence is low. A building’s windproof design is a direct influencing factor of the wind resilience of China’s coastal historical districts; block morphology, typhoon level, and emergency plan are the most fundamental and key influencing factors of the wind resilience of China’s coastal historical districts. Full article