African Swine Fever (ASF), a severe swine disease with potential zoonotic implications, historically limited to Sardinia in Italy since 1978, made its mainland debut in January 2022, raising concerns. The genotype found in northwest Italy (genotype II) differs from the Sardinian strain (genotype I). By January 2024, the epidemic had escalated, with 1435 wild boar cases and 21 domestic pig outbreaks reported [6]. The Epidemiology department of the "Istituto Zooprofilattico Sperimentale delle Venezie" (IZSVe) responded with innovative tools. These included a comprehensive data warehouse, integrating farm, processing centre, and slaughterhouse data with Laboratory Information Management Systems and geospatial information. Additionally, an "African Swine Fever/Manager" (ASF-Manager) tracked outbreak specifics, while "IZSVe GIS African Swine Fever" (IZSVeGIS-ASF) provided real-time monitoring and support for control measures. IZSVeGIS-ASF facilitates spatial analysis and filtering of data, offering insights into animal demographics and premises characteristics. Currently exclusive to IZSVe's Epidemiology department, efforts are underway to expand access to local and regional veterinary services, fostering collaborative ASF management. Ongoing enhancements aim to optimize functionality and broaden utilization during ASF outbreaks.

Transformative shifts in the knowledge economy of the XXI century, Industry 4.0 and Web 4.0 development and elaboration of networked society, emergency digitization of all social communicative spheres due to pandemic measures have imposed pressing revisions onto interdisciplinary and cross-sectorial job market demands of university level education, curriculum design and learning outcomes. As a product of modern civilization, digital reality has become an independent format of being. Accordingly, electronic media act not only as a means of transmitting information but also reveal their own world-creating, meaning-making, and, as a consequence, communicative potential. The global digital realm stands as an integral environment, demanding new cognition and perception ways via complex philosophic, cultural, social, and linguistic approaches, providing unlimited opportunities for human intellect, communicative development, and research.

The consequent functional tasks to meet this challenge in the educational sphere worldwide are estimated as 1) to adapt the existent educational scenarios to digital, remote and hybrid formats; 2) to upgrade e-competence and digital literacy of all stakeholders of the educational process and industry; 3) to activate complex interdisciplinary skillsets, otherwise latent or underutilized in the professional interaction; 4) to introduce functional technical solutions for facilitation of formal and informal educational workflow and communication.

The context of the erupted military intervention in Ukraine and the ensuing information warfare in various digital ambients (social media, news coverage, digital communications), the specific value is allocated to the enhanced role of digital humanism as a tool of the internationally broadcast strife for freedom and sovereignty.

In the contemporary landscape, the fields of cybernetics, artificial intelligence, and digital technology significantly impact society, reshaping production processes, decision-making frameworks, and human behaviors. Training engineers with transversal skills becomes imperative to navigate workflow complexities and communicate across these disciplines. We propose a new learning approach structured around expert prerequisites, integrating AI principles dedicated to Embedded Systems engineering track. Our module focuses on creating an autonomous driving vehicle using an autonomous robot kit, fostering interdisciplinary learning. Real-time demonstrations assess learning outcomes, emphasizing problem-solving skills. Inspired from recent evaluation concept of interdisciplinary assessment. Our evaluation criteria emphasize functionality, integrated idea defense, and written reports. The defense organization scheme fosters positive perceptions of interdisciplinary links.

This study investigates the application of the Xception architecture for accurate classification of skin lesions, focusing on the early detection of melanoma and other malignant skin conditions. Utilizing deep learning techniques, the research aims to enhance the precision and efficiency of skin lesions diagnosis. The study utilizes the TensorFlow framework and the HAM10000 dataset, comprising a vast collection of benign and malignant skin lesion images, for training and evaluating the Xception model. Preprocessing steps, including data splitting, augmentation, and image resizing, are applied to the dataset. The Xception architecture, a deep convolutional neural network, serves as the foundational model, supplemented with customized classification layers for specialized features and predictions. The model’s performance is evaluated using diverse metrics. The experimental outcomes reveal the Xception architecture’s potential in accurately classifying skin lesions. Moreover, the study underscores the significance of extensive and diverse datasets, as well as rigorous clinical validation, in the development of deep learning models for skin cancer detection. The findings contribute to the advancement of early melanoma detection, thereby improving patient outcomes and alleviating the burden of the disease.

This study investigated the influence of needs satisfaction and support on the well-being of physicians deployed in underserved communities. Basic Psychological Needs Theory is used as the theoretical framework, positing that fulfilling the three basic psychological needs of autonomy, competence, and relatedness can foster well-being and optimal functioning. The results revealed that meeting basic psychological needs alongside workplace conditions and individual characteristics can play distinct roles in promoting emotional, psychological, and social well-being as well as reducing the likelihood of anxiety and depression. This study suggests that promoting the well-being of human resources for health, particularly among physicians deployed in underserved communities, is crucial for achieving the Sustainable Development Goal for good health and well-being. By recognizing and addressing the diverse factors that contribute to the well-being of these physicians, healthcare organizations and policymakers can create environments that support their optimal functioning and, consequently, contribute to the overall improvement of health outcomes in underserved communities.

This paper explores the innovative integration of Generative AI (GenAI) in active learning environments to augment metacognitive knowledge and technological skill development among students. While active learning has been pivotal in promoting student engagement and learning, the incorporation of GenAI presents a novel approach to further enhance these outcomes. The study investigates how GenAI tools can be utilized within a reflective practice model to bolster metacognitive regulation and technological proficiency. By discussing the synergistic relationship between GenAI, active learning, and metacognitive strategies, this paper provides insights into the evolving landscape of educational technology and its impact on student learning processes. The paper offers a theoretical framework based on established concepts in metacognition, active learning, reflective practice, and technological skills, contextualized within the realm of GenAI. This paper contributes to the understanding of how GenAI can be harnessed as an educational tool, facilitating deeper and more effective learning experiences.

This report shows that with the most recent advancements in Artificial Intelligence (AI) and Natural Language Processing (NLP) using generative-pretrained transformers, we can develop robust AI applications to assist customer service departments with question answer systems. This paper addresses the question answering task using an OpenAI Application Programming Interface (API). This report examines how to create an AI question answering application from documents that generated correct answers to questions about those documents. We used two different approaches to create the question answering system. One was to use just the OpenAI API. The other was to use the LangChain framework and libraries. Both applications did answer questions correctly. LangChain used less code with a higher learning curve. The OpenAI API used more code and provided more detailed answers.

The interesting and compelling themes of the IMCI 2024 Conference can be found in the Action-Research we have been practicing as human ecologists within many Man/Society/Environment (M/S/E), complex and disordered eco-systems in which Nature, Science, Philosophy, Arts, Economies and Technologies interact with People, Societies, Cultures and Public Institutions in relation to the living environments of their influence.

All this has led us to consider the disordered complex systems - usually the domain of different/separate disciplines- as components of a “common home" in which they interact to build knowledge and stimulate wider scientific and human community dynamics, towards a new epistemology. This text aims to contribute to these arguments by developing into four parts:

1. The complex disordered systems, from science to experience and vice versa
2. Human Ecology, an approach to complex disordered systems in contemporary realities
3. Toward a common epistemology
4. Action-Research in Ternary Ecosystems in their becoming

The aim of this research was to find out the existing gaps between the current educational model of a specific degree course in Primary Education in Chile and the new pedagogical and disciplinary standards established by the Ministry of Education. To address this objective, a university located in the city of Santiago of Chile with a degree in Primary Education with a major in mathematics was considered. The data were collected from the pedagogical and disciplinary standards for the degree course in Primary Education, from the graduate profile of this degree course and from the syllabuses of the subjects of this degree course that are linked to the area of mathematics. The results show that the curricular design is aligned with the guiding standards for graduates in Primary Education. However, there was not the same congruence between what is indicated in the graduate profile and in the subject programmes with the disciplinary standards. Among the conclusions, it is found that the training of the Primary Education teacher is not deepened precisely in the area of mathematics.

Two variables (planning and organisation of e-tutorials, and knowledge of the subject matter, before and during covid-19) are preliminarily considered to assess e-tutoring in an engineering department of the University of South Africa. A Monte Carlo simulation has been performed on the two variables respectively, by making comparison of e-tutoring performance before and during covid-19. The results illustrated a probabilistic performance based on trials as opposed to a deterministic approach. Academic departments may make informed decisions for e-tutor programme based on a range of possibilities related to the variables under investigation.