Parthenope University of Naples
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Citrus limon Peel Extract Modulates Redox Enzymes and Induces Cytotoxicity in Human Gastric Cancer Cells
No full textGastric cancer remains a leading cause of cancer-related mortality worldwide. Citrus fruits are rich in polyphenols, exerting antioxidant and chemo-preventive activities, and lemon peel represents a valuable source of such bioactive compounds. Previous studies showed that Citrus limon peel extracts (LPE) inhibited the activity of some enzymes of the antioxidant system and reduced the interleukin-6-dependent invasiveness of gastric and colon cancer cells. In the present study, we have investigated the effects of LPE on the human gastric adenocarcinoma AGS and MKN-28 cells and on the activity of a crucial redox enzyme, catalase (CAT). Indeed, LPE significantly reduced the cell viability and clonogenic potential of the gastric cancer cells and induced morphological changes indicative of cytotoxicity. Moreover, LPE modulated the intracellular redox homeostasis by decreasing levels of the hydrogen peroxide-related reactive oxygen species (ROS) while increasing those of superoxide anions and decreasing levels of superoxide dismutases (SODs). Western blotting analysis revealed that LPE downregulated CAT, SOD-1, SOD-2, and monoamine oxidase A (MAO-A) protein expression level in both cell lines. Finally, the extract inhibited CAT activity in a dose-dependent manner (IC50 = 0.008 ± 0.003 mg/mL; Ki = 0.012 ± 0.002 mg/mL). These findings indicate that LPE exerts cytotoxic and redox-modulating effects through the inhibition of antioxidant enzymes and the alteration of ROS balance. Therefore, the agro-industrial by-product LPE could be considered as a promising natural source of polyphenolic compounds with potential applications in the prevention and therapy of gastric cancer
An Enhanced Deep Neural Network Framework for Accurate Tomato Disease Recognition in Real-time Environment
No full textAgricultural production is a critical sector that directly impacts the financial and social well-being of a society. The identification of plant diseases in a real-time environment is a significant challenge for agriculture production. Conventional disease detection methods, which depend significantly on manual inspection, are time-consuming, labour-intensive, and susceptible to human error. Furthermore, many recently developed models struggle in real-time scenarios because their accuracy is compromised when trained on isolated leaf images but then used to analyse entire plants. To tackle these issues, this research offers an advanced, automated system from tomato leaf segmentation and disease detection to the automatic spray prescription in real-time environment. This research presents an integrated system to address these issues, focusing on tomato plants. In first part of the research after deeply analysing the YOLO (You Only Look Once) models we integrate two models, the YOLOv8 with SAM (Segment Anything Model), for leaf detection and masking in the tomato plants, and extraction of the individual leaves in a real-time environment for improving the performance of leaf disease detection. For leaf detection, the modified YOLOv8 is used, and for masking and extraction of the individual leaves, the SAM is used. The individual leaves are then, provided to the custom deep neural network for further disease detection. This ensures that subsequent disease detection is performed on isolated leaves, improving accuracy. We investigated deep learning models for precise and efficient tomato plant disease detection. All the models were trained and validated on individual and merged dataset of over 18000 and 25,000 images, encompassing 10 distinct classes (9 diseases and healthy plants). The performance of our custom CNNs (Convolutional Neural Networks) model was significant, achieving an accuracy of over 99%. Furthermore, it revealed higher efficiency, requiring less training time and computational resources than leading architectures such as VGG (Visual Geometry Group), ResNet (Residual Network), and DenseNet (Densely Connected Convolutional Network), making it a promising tool for real-world applications. In second part of this research work, we have designed, an automated system for tomato disease detection and spray prescription using an enhanced YOLOv9 model. By leveraging advance deep learning techniques, the proposed system accurately identifies and detect the nine tomato leaf disease in real-time by making efficient, precise and accurate decision including healthy leaves. This YOLOv9 model is modified for detecting tomato leaf diseases and optimized for getting higher accuracy and efficiency. Once disease is identified, the system automatically recommends a spray depending on the detected disease, which helps in reducing the pesticide use along with the environmental impact. This system helps in maximizing crop health and yield. After testing the system on the test dataset and real-time images demonstrates the system accuracy and efficiency, achieving detection accuracy of 97% and spray prescription accuracy of 94%. Integrating a YOLOv9 with spray prescription system provides a sustainable, cost-effective solution for managing tomato plant diseases. This thesis illustrates the efficacy of deep learning in the efficient and precise identification of tomato plant diseases, along with automated spray recommendations, thereby benefiting farmers and enhancing agricultural productivity. The effective performance observed in this thesis makes it promising for real-world agricultural applications
Artificial knowledge generation: investigating the revolutionary role of generative AI in knowledge management
No full textGenerative artificial intelligence (GenAI), with its potential to autonomously generate new content in the form of
text, video, audio and code, holds disruptive potential to revolutionize knowledge management (KM) processes.
An enormous number of studies have been published in recent years on the application of GenAI and this number
is expected to increase further. Nevertheless, there are relatively few studies that systematize this research
domain, and they are scarce from a KM perspective. For this reason, this study intends to bridge the current gap
by offering both qualitative and quantitative insights in this research field using a bibliometric literature review,
combining descriptive analysis with science mapping techniques, to analyse the impact GenAI has on KM processes.
In particular, the aims of this paper are to provide a structured overview of how GenAI research contributes
to the evolution of KM, to identify inconsistencies in the understanding of GenAI’s role in knowledge
creation, and to propose directions for future theoretical and empirical research. In addition, our contribution
proposes both the introduction of a new conceptual dimension, namely the machine dimension, which may extend traditional knowledge generation models, and a conceptual taxonomy for analysing GenAI readiness that is useful for managers and practitioners
Women’s health entrepreneurship for net-zero energy through Metaverse and Digital Twin
No full textThis chapter examines the potential role of Metaverse and Digital Twin technologies in supporting women’s entrepreneurship in the healthcare sector, with specific attention to net-zero energy trajectories and SDG 5. The discussion outlines the main conceptual links between digitalisation, entrepreneurial decision-making, and sustainability-oriented business models, drawing on innovation-related perspectives and stakeholder-based considerations. The chapter identifies key enabling conditions and constraints, including digital capabilities, access to resources, and governance issues. It also highlights implications related to data management, ethics, and digital inequality, and delineates avenues for future research and practice
Consumer preferences for alternative eco-packaging: A field experiment on wine
No full textFood packaging is rapidly evolving, constantly urged by environmental protection pressures and new consumer needs. However, the wine sector is generally extremely conservative, particularly in traditional producing countries such as Italy. To investigate consumer responses to sustainable packaging innovations, such as wine in aluminium bottles, a between-subjects field experiment was performed at a wine fair with voluntary participants (N = 375) who tasted red wine randomly assigned to one of these three conditions: control, treatment 1 (aluminium bottle) and treatment 2 (aluminium bottle + sustainability prompt). Notably, an aluminium bottle and a prompt do not impact consumer preferences. Additionally, Italian regular wine drinkers perceived aluminium packaging as less environment-friendly than traditional glass bottles. Furthermore, wine neophobia was significantly correlated with diminished hedonic liking and a decreased purchasing probability, whereas an increased frequency of wine consumption was inversely related to willingness-to-pay (WTP) and purchasing probability. Age demonstrated a significant negative effect on WTP, suggesting that younger consumers, who exhibit lower wine consumption and neophobia, may benefit from tailored marketing strategies designed for enhancing the acceptance of sustainable packaging solutions
TRAINING TO CURE: MEDICAL PEDAGOGY AT THE HEART OF HEALTH EDUCATION
No full textIn the current context of increasing complexity of Health Systems,
Medical Pedagogy emerges as a fundamental discipline to promote
an integrated, humanistic and competent training of health
professionals. The article proposes a critical reflection on the
importance of training to cure, that is, of investing in the quality of
training as the first act of care for the patient. Innovative educational
approaches, interprofessional pedagogical models and strategies to
enhance the therapeutic alliance through the enhancement of the
educational dimension of care are analyzed. The goal is to outline a
paradigm in which pedagogy is at the service of health, contributing
to the construction of a more aware, empathetic and sustainable
health system.essential to ensure an inclusive educational
environment
Outdoor Education: A New Paradigm for Urban Learning
No full textOutdoor Education represents an innovative pedagogical approach capable of addressing the educational challenges of contemporary urban contexts, characterized by high population density and fast-paced lifestyles. This way of learning is not limited to the classroom but combines the body, movement, direct experiences, and interaction with the environment, transforming cities into spaces where active and meaningful learning can take place. Outdoor activities promote the development of cognitive, socio-emotional, and transversal skills. The approach values individual differences, turning them into resources for collective learning, and fosters inclusive and conscious participation. In continuously transforming cities, Outdoor Education is not merely an alternative learning method but a new educational paradigm that connects school, territory, and daily life, offering lasting, inclusive, and meaningful learning experiences. This perspective supports lifelong learning, preparing students to face real-world complexities and to become active and responsible citizens
