Parthenope University of Naples
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Environmental impacts study of high temperature electrolyzers.
No full textA life cycle assessment of Solid Oxide Electrolysis Cells (SOEC) and Proton Conducting Ceramic Electrolyzers (PCCEL) is performed to identify and compare the environmental hotspots associated with their production and use. System boundaries include raw material extraction, manufacturing, and operation of SOEC and PCCEL units. Information available in the scientific literature is used to develop the life cycle inventories for the electrolyzers examined. These units are implemented in the SimaPro software using the Ecoinvent database. The Environmental Footprint (EF) 3.1 method is adopted for the impact assessment.
The results highlight that the operating phase for all electrolyzers analyzed in this study has a greater impact than the manufacturing phase, primarily due to the high electricity consumption required to power these electrolyzers. Regarding the manufacturing phase, the environmental impacts depend on how the electrolyzers are produced, as they can differ. In this study, two SOECs and one PCCEL are analyzed: cobalt oxide, used for manufacturing the interconnects of the first SOEC, has the highest environmental impact across all assessed impact categories, whereas in the second SOEC and PCCEL, stainless steel, also used for the interconnects, impact more than the other layers. Energy consumption associated with the production of cathodes in these three electrolyzers also significantly contributes to the overall environmental impact
Unexpected Giant Right Coronary Artery Aneurysm Diagnosed by Computed Tomography Angiography in the Emergency Department
No full textGiant coronary artery aneurysms (GCAA) are usually defined as diameter >8mm or >400% of the adjacent normal segment; they are very rare (reported prevalence ≈0.02%). Though coronary angiography is the diagnostic gold standard, computed to- mography angiography (CTA) offers a non-invasive, highly sensitive, and specific alternative. CTA enables detailed visualization of aneurysm morphology and detection of complications. We present the case of a 72-year-old man admitted to the Emergency Department with chest pain, where CTA played a crucial role in diagnosing a GCAA and assessing its potential life-threatening complications, highlighting its value in emergency cardiovascular imaging
LA REPRESENTACIÓN DEL GÉNERO EN LA ERA DE LA INTELIGENCIA ARTIFICIAL: Hacia una traducción más inclusiva del Español al Italiano.
No full textIn the digital age, AI-generated machine translation has revolutionized the way we interact globally. In this context, gender representation has become a crucial issue at the intersection of language, culture, and technology. However, despite advances, many challenges remain, particularly regarding gender misrepresentation. This study explores how ChatGPT 3.5, when translating textual segments from Spanish to Italian —two typologically similar Romance languages— often perpetuates and, in some cases, exacerbates gender biases. Large Language Models (LLMs), such as neural network-based machine translation systems, typically rely on vast datasets to learn linguistic patterns. However, these datasets can reflect inherent societal gender biases, leading to biased translations. This phenomenon not only has linguistic implications but also cultural and social ones, as it perpetuates gender stereotypes that can influence the perception and understanding of gender roles across different cultures. Moreover, these errors can be particularly problematic in contexts where accuracy and neutrality are essential. Therefore, addressing these challenges is crucial to promote more inclusive and accurate gender
representation. This requires a combination of technical and ethical approaches: on the one hand, AI developers must work on gender-sensitive algorithms and carefully select training data to reduce biases; on the other, it is important to foster critical awareness of gender representation in society and promote diversity and inclusion in the design and use of AI-based systems
Corporate Social Responsibility or Strategic Opportunism? Evidence From High and New Technology Firms
No full textCorporate Social Responsibility (CSR) presents a dual nature in practice. Beyond its explicit ethical imperatives, it can be strategically instrumentalized to manage external pressures, shape public impression, and even divert attention from corporate misconduct. Acknowledging this complexity, this study investigates the conditions under which CSR is leveraged as a strategic tool and how this distinction relates to earnings management (EM). Drawing on agency theory and instrumental stakeholder theory, this study examines 2973 Chinese High and New Technology Firms (HNTFs) from 2017 to 2021 and clarifies the boundary conditions under which a positive CSR–EM association is more plausible, namely, when CSR is predominantly symbolic/instrumental rather than substantive/genuine. This study also tests whether media attention moderates this linkage. It finds a positive association between CSR and EM concentrated in the social and governance pillars, consistent with the use of CSR as reputational insurance and impression management; the environmental pillar shows no meaningful association. Greater media attention strengthens the CSR–EM association, suggesting firms increase visible CSR to meet external expectations while simultaneously managing reported performance. Importantly, this evidence does not dispute substantive/genuine CSR; rather, it highlights conditions under which CSR may be instrumentalized, underscoring the need to differentiate substantive from symbolic engagement
Dual-Polarimetric SAR Measurements to Observe Liquefaction Surface Manifestations
No full textIn this study, a methodology is proposed to use dual-polarimetric synthetic aperture radar (SAR) to identify the spatial distribution of soil liquefaction. The latter is a phenomenon that occurs in conjunction with seismic events of a magnitude generally higher than 5.5-6.0 and which affects loose sandy soils located below the water table level. The methodology consists of two steps: first the spatial distributions of soil liquefaction is estimated using a constant false alarm rate method applied to the SPAN metric, namely the total power associated with the measured polarimetric channels, which is ingested into a bitemporal approach to sort out dark areas not genuine. Second, the obtained masks are read in terms of the physical scattering mechanisms using a child parameter stemming from the eigendecomposition of the covariance matrix-namely the degree of polarization. The latter is evaluated using the coseismic scenes and contrasted with the preseismic one to have rough information on the time-variability of the scattering mechanisms occurred in the area affected by soil liquefaction. Finally, the obtained maps are qualitatively contrasted against state-of-The-Art optical and interferometric SAR methodologies. Experimental results, obtained processing a time-series of ascending and descending Sentinel-1 SAR scenes acquired during the 2023 Türkiye-Syria earthquake, confirm the soundness of the proposed approach
Confiscated assets and PCTO: legality against school dropout
No full textThe use of assets confiscated from organized crime represents an educational resource of
great value, capable of transforming symbolic places of illegality into spaces of legality,
training and growth for the new generations. By integrating confiscated assets into the
Pathways for Transversal Skills and Orientation (PCTO), students are offered a concrete
opportunity for learning, development of transversal skills and career guidance. These
paths not only promote the recovery of skills and the strengthening of the link with the
territory, but are also a powerful tool in the fight against school dropout, offering
experiences that bring students closer to the world of work and motivate them to continue
their educational path. The article explores how the reuse of these assets in PCTOs can
stimulate values of active citizenship and build a more just and supportive future
Assessing the Maturity of Generative AI Systems: A Framework for Education and Public Engagement
No full textThe integration of generative AI tools in educational settings, exemplified by chatbots, presents novel opportunities for personalized learning while simultaneously posing challenges related to trust, ethics, and technical preparedness. This study introduces ALES (Academic Learning Engagement System), a university chatbot, alongside a comprehensive framework for its design, implementation, and evaluation. The framework incorporates international standards, including ISO/IEC 25010, TRL, CMMI, and GQM, to ensure quality, scalability, and alignment with institutional requirements. ALES integrates a fine-tuned transformer model, retrieval-augmented generation, and a modular infrastructure. Its evaluation encompasses six critical dimensions: accuracy, usability, performance, reliability, ethics, and educational impact. A five-level maturity model guides the development process from prototype to full deployment. Empirical findings indicate 90% accuracy, high user satisfaction (SUS > 80), and positive learning outcomes. The ALES case study underscores the value of a structured, iterative approach to the responsible implementation of AI in education and offers a transferable model for broader adoption
