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Navigating the Trust Landscape: Fraud Analysis of Ethereum Blockchain Networks Using A.I
No full textIn the contemporary era marked by the proliferation of digital transactions, ensuring their integrity and authenticity is paramount. This research embarks on an analytical journey into the Ethereum blockchain network, employing machine learning algorithms to scrutinize dataset transactions for fraud detection. The study provides an overview of blockchain networks, elucidating various types of fraud and exploring diverse anomaly detection algorithms. A detailed investigation into transaction-related fields is conducted using a correlation matrix, aiming to construct a robust model that can accurately identify fraudulent transactions within the Ethereum network. Two distinct machine learning algorithms, the Isolation Forest model and the Support Vector Machine (SVM) algorithm, are employed on the Ethereum Fraud Detection dataset sourced from Kaggle. Preliminary validation results are promising, with the Isolation Forest model achieving a 75% accuracy rate in fraud detection and the SVM algorithm demonstrating an exceptional 99.95% accuracy. This research contributes significantly to the field of fraud analysis in blockchain networks. It underscores blockchain technology's potential to bolster social trust by enhancing digital transactions’ security, transparency, and integrity. The findings of this research pave the way for developing and implementing innovative, blockchain-based solutions for fraud prevention and detection, ultimately contributing to enhancing social trust and fortifying various sectors against fraudulent activities
Sustainable Innovation and Management in Hospitality and Tourism [editorial]
No full textThe Special Issue on “Sustainable Innovation and Management in Hospitality and Tourism” aims to explore innovative strategies and practices that promote long-term sustainability within the hospitality and tourism sectors. The focus is on integrating environmental, socio-economic, and governance considerations into tourism and hospitality practices. The scope includes research on sustainable practices, policies, technological innovations, and metrics that can be applied across global tourism and hospitality contexts. The purpose is to foster a multidisciplinary dialogue that enhances our understanding of how the industry can evolve sustainably while supporting local communities, reducing environmental impact, and ensuring economic viability.
This Special Issue will enrich the existing literature by bridging theoretical frameworks and practical applications, offering fresh insights into sustainability assessment tools, policy impacts, and case studies from diverse geographical regions. It addresses key gaps in current scholarship by emphasizing measurable sustainability outcomes and integrated management approaches.
Aligned with the Special Issue goals, the Special Issue supports efforts to define and quantify sustainability through empirical studies, methodological innovations, and policy analysis. It further explores how sustainability can be embedded into decision-making processes within hospitality and tourism. By presenting innovative models, examining challenges and proposing actionable solutions, this issue will provide a critical resource for researchers, practitioners, and policymakers aiming to advance sustainable development in tourism-related fields. Ultimately, it will contribute to a more sustainable, equitable, and resilient hospitality and tourism industry
Green Bonds and Green Banking Loans: A Systematic Literature Review
No full textThe main purpose of this research is to examine the significance of green bonds and green banking loans as financing tools for ecologically sustainable projects in the face of increasing worldwide environmental issues. This research seeks to uncover the determinants of both instruments’ issuance and the obstacles to their acceptance. A thorough systematic literature review will be conducted to assess the efficacy of these tools in improving company financial performance and cost of debt, advancing environmental sustainability, and influencing investor behavior. This methodology guarantees a comprehensive and impartial examination of peer-reviewed publications from reputable sources such as Web of Science and Scopus. Although issues such as greenwashing, market liquidity, and regulatory discrepancies still exist, both tools are growing steadily in the sustainable financing spectrum. The results also suggest that both instruments are influenced by several factors, often overlapping due to their common focus on financing sustainable projects. The credit rating, financial health, and overall environmental performance of the issuing entity significantly influence the attractiveness and pricing of green bonds, as do the market conditions, regulatory frameworks, and certification. The environmental profile and creditworthiness of the borrower are key determinants for green banking loans. The review enhances the current body of knowledge by presenting a theoretical structure for comprehending the dynamics of green debt markets and proposing practical recommendations for policymakers and financial institutions. Furthermore, it emphasizes the deficiencies in existing research, including the need for further longitudinal investigations into green bank loans and a more thorough examination of the notion of ‘greenium’. We searched Web of Science and Scopus up to 26 April 2024. Eligibility criteria included peer-reviewed English-language studies on green bonds or green banking loans. After screening, 128 studies were found to have met the inclusion criteria
Como cumprir as normas de apresentação escrita das dissertações e teses UPT
No full textConteúdo programático relativo à sessão de formação sobre a aplicação das normas de apresentação escrita das dissertações e teses UPT promovida pela Biblioteca Geral UPT, no âmbito do Serviço de Formação e Literacia de Informação
Justice as World-Making: Creative Citizenship in H. Arendt
No full textThis essay proposes a novel interpretation of Hannah Arendt’s political theory as a crucial contribution to a post-metaphysical, creative conception of justice and citizenship. It argues that Arendt’s phenomenology of plurality, amor mundi, and critical thinking can be read under the prism of world-making. Against both ideal abstraction and empirical cynicism, the essay reconstructs the modern ideal of deliberative participatory democracy as a dynamic equilibrium between ontological shared power of beginning (i.e., freedom), interhuman trust, and communicative openness. It further situates this Arendtian model within the republican and cosmopolitan traditions, drawing on Kant’s Perpetual Peaceand contemporary political theories that defend fostering democratic innovation and democratic cosmopolitanism under conditions of global interdependence, authoritarian populism, digital fragmentation, and ecological crisis. The essay concludes that the “cosmopolitan constitution” envisioned by Kant and renewed by Arendt remains humanity’s most demanding and hopeful vocation: the continuous creation of a habitable world for freedo
Religious Tourism Events and Insights for AI on International Volunteering: The Case Study of Braga's Holy Week (Portugal)
No full textThe tourism sector makes a significant contribution to the development of the territory. Due to the strong set of religious structures and traditions, the north of Portugal is a region where religious tourism has a significant impact, serving as an economic engine for the region and generating a dynamic in the local economies. Holy Week in the city of Braga is one of the most outstanding examples of this, constituting a unique tourist attraction that enhances the municipality's promotion. A qualitative research study was conducted through three interviews with various institutional agents. The analysis of the collected information enabled us to gain detailed insights, thereby enhancing our understanding of Holy Week event organization and its tourist profile. From an interdisciplinary perspective, this chapter presents some insights into religious tourism, religious events but also envisages the relationship that artificial intelligence could play in international volunteering
Climate Change and Tourism: A Global Challenge with Regional Impacts and Responses
No full textClimate change is a pressing global challenge that significantly impacts the tourism sector. At the same time, it is influenced by the sector’s greenhouse gas emissions. This chapter examines the bidirectional relationship between tourism and climate change through a regional lens, analysing vulnerabilities, adaptation strategies, and mitigation efforts across Africa, the Americas, Asia-Pacific, Europe, and the Middle East. Findings highlight that tourism-dependent regions, mainly coastal and nature-based destinations, face heightened risks from rising temperatures, extreme weather events, and changing precipitation patterns. Concurrently, the tourism industry—primarily through air travel, accommodation, and activities—contributes substantially to global carbon emissions. Regional disparities in climate change impacts and in policy responses are evident, with some destinations implementing proactive adaptation measures while others remain highly vulnerable. This chapter underscores the necessity for collaborative governance, industry-wide carbon reduction commitments, and innovative destination management strategies to enhance tourism resilience. Future research should explore region-specific best practices and policy frameworks to ensure sustainable tourism development amid a changing climate
Education for Human Rights: A research project in Portugal [abstract]
No full textDespite the fact that on December 10, 2023 were celebrated 75 years since the Universal Declaration of Human Rights, we continue to witness a daily trampling of the most elementary rights of citizens in today's world. [...
Cuidados Paliativos Pediátricos: Perspetivas multidisciplinares
No full textOs Cuidados Paliativos Pediátricos (CPP) constituem uma área de intervenção técnica especializada no acompanhamento de crianças e adolescentes diagnosticados com doenças crónicas complexas (DCC), limitantes e que ameaçam a vida ou com prognóstico limitado, e das suas famílias. A intervenção nesta fase do ciclo de vida possui características únicas relacionadas com o desenvolvimento e a maturidade biológica e emocional da criança e/ou do adolescente e as trajetórias de doença e tratamento diferenciadas, bem como considerações éticas e legais específicas
Enhanced Histopathologic Image Analysis for Mouth Cancer Classification Using Morphological Reconstruction and UNet
No full textMouth cancer represents a significant global public health challenge due to its high incidence rate and potentially fatal outcomes if not diagnosed early. Among the various types, oral cancer is notably prevalent and poses considerable diagnostic complexity due to its intricate histopathological architecture. According to the World Health Organization and recent epidemiological studies, oral cancer accounts for approximately 377,000 new cases and 177,000 deaths annually worldwide. Traditional diagnostic methodologies such as manual clinical inspection and biopsy analysis are often time-intensive, inherently subjective, and susceptible to inter-observer variability among pathologists. To address these limitations, this study proposes novel framework, termed Depthwise Separable Convolution U-Net (DWSU-Net), aimed at enhancing the accuracy and efficiency of mouth cancer detection. Unlike traditional U-Net, which employs computationally expensive standard convolutional layers, DWSU-Net integrates depthwise separable convolutional blocks into both encoder and decoder stages, reducing parameter count and training complexity while preserving representational power. This makes the model more lightweight, scalable, and suitable for real-time or resource-constrained clinical environments. The research utilizes histopathologic images of oral tissues obtained from the publicly available oral cancer detection dataset on Kaggle, which were captured using a Leica ICC50 HD microscope. The proposed approach initiates with a comprehensive data preprocessing pipeline involving multiple filtering techniques. Raw histopathological images are transformed using Sobel filtering, Otsu thresholding, Canny edge detection, and morphological reconstruction via erosion, thereby improving feature saliency and contrast in malignant regions. The preprocessed dataset is partitioned into training, validation, and testing subsets in an 80:10:10 ratio and evaluated using fivefold cross-validation to ensure the robustness and generalizability of the model. A comparative analysis was conducted using conventional CNN architectures to identify the most effective combination of model and filtering technique. Empirical results indicated that MobileNet and U-Net, when applied to images filtered through morphological reconstruction by erosion, yielded superior classification performance. Motivated by these findings, the proposed DWSU-Net architecture was developed by integrating the strengths of MobileNet and U-Net. The novelty of the DWSU-Net model lies in morphological reconstruction-based preprocessing, which enhances interpretability by making malignant regions more distinct for both the algorithm and pathologists, thereby bridging the gap between AI predictions and clinical understanding. By combining efficiency, robustness, and interpretability, DWSU-Net goes beyond accuracy gains, offering a clinically relevant decision-support framework. Experimental evaluations demonstrate that the proposed model achieves an outstanding classification accuracy of 99.74% in distinguishing between healthy and malignant oral tissue images, underscoring its potential for clinical deployment in automated cancer diagnostics