Parthenope University of Naples
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Towards Numerical Method-Informed Neural Networks for PDE Learning
No full textSolving stiff partial differential equations with neural networks remains challenging due to the presence of multiple time scales and numerical instabilities that arise during training. This paper addresses these limitations by embedding the mathematical structure of implicit–explicit time integration schemes directly into neural network architectures. The proposed approach preserves the operator splitting decomposition that separates stiff linear terms from non-stiff nonlinear terms, inheriting the stability properties established for these numerical methods. We evaluate the methodology on Allen–Cahn equation dynamics, where interface evolution exhibits the multi-scale behavior characteristic of stiff systems. The structure-preserving architecture achieves improvements in solution accuracy and long-term stability compared to conventional physics-informed approaches, while maintaining proper energy dissipation throughout the evolution
Massimiliano Demata, Discourses of Borders and the Nation in the USA: A Discourse-Historical Analysis (Routledge, 2023)
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SAM-CyFra: A System for the Automated Management of Cybersecurity Frameworks
No full textGiven the expanding threat landscape, protecting critical infrastructures and sensitive information has become a top priority. Organizations are increasingly emphasizing security risk assessments to safeguard their assets and maintain compliance with evolving standards and regulations. As a result, various cybersecurity frameworks have been developed to assist organizations assess and strengthen their security practices, promoting a proactive and strategic approach to risk management. However, cybersecurity frameworks present significant challenges in terms of complexity, scalability, and adaptability. On the one hand, they generally rely on manual assessment processes, with all limitations of manual evaluations. On the other hand, they are characterized by a heterogeneous nature that works at different levels of granularity, thus resulting in a complex landscape for companies. To address these challenges, this work proposes SAM-CyFra, a system designed to automate and streamline the management of cybersecurity frameworks. SAM-CyFra organizes security into three layers, providing a simplified and modular approach that enhances adaptability to each organization’s specific needs. Some preliminary results are presented with a focus on U-space environments
Flow Matching Posterior Estimation for Simulation-Based Atmospheric Retrieval of Exoplanets
No full textThe characterization of exoplanetary atmospheres allows a deeper understanding of planetary formation, evolution, and habitability through atmospheric retrieval, which consists in inferring various properties of exoplanetary atmospheres given their spectroscopic observations. Traditional atmospheric retrieval methods based on Bayesian inference, such as Nested Sampling, require significant computational resources to compute the full posterior distribution of atmospheric parameters, limiting their scalability for future large-scale surveys and high-resolution characterizations. Additionally, the rise of modern density estimation techniques poses a fundamental need for comprehensive evaluation frameworks to objectively compare the posterior distributions of heterogeneous probabilistic estimators. Within the scope of the 2023 edition of the Ariel Data Challenge, this work proposes a novel, scalable atmospheric retrieval framework based on Flow Matching Posterior Estimation (FMPE) and Continuous Normalizing Flows (CNFs), leveraging transmission spectra, instrumental uncertainties across wavelength channels, and auxiliary information about planetary systems, to retrieve the posterior distribution of atmospheric parameters in a significantly reduced computational time compared to conventional techniques. Through the fair definition of an extensive posterior evaluation framework, our approach demonstrates superior performance in target prediction accuracy, uncertainty quantification, calibration, and posterior coverage—consistently outperforming existing neural- and sampling-based retrieval methods. In addition, complementary ablation studies emphasize the value of incorporating auxiliary planetary system data, enhancing the reliability, explainability, and interpretability of atmospheric inferences. Together, these contributions establish the proposed approach as a robust, scalable, and adaptable framework for the analysis of exoplanetary atmospheres
VIS-to-MIR reflectance and Raman spectroscopy of the CM2 NWA 12184 carbonaceous chondrite
No full textThe spectral analysis of CM meteorites can help to constrain the mineralogical composition of their parent body, the C-type asteroids. The CM2 NWA 12184 was spectrally examined employing seven complementary techniques at different spatial resolutions, including VIS-to-MIR reflectance and Raman spectroscopy. Furthermore, the effects of space weathering on asteroids can be investigated by performing laboratory simulations on meteorites samples; thus, the meteorite was processed with He+ ions at 200 keV (maximum fluence of 1.0 × 1017 ions cm−2) to simulate the solar wind irradiation on C-type asteroids. We discriminated the mineralogical composition of the NWA 12184 at the millimeter scale and at the micrometer scale, investigating both matrix and chondrules. The ion experiment produced spectral darkening, reddening, shifting of the hydration band, and weakening of the absorption band ascribed to olivine in the VIS-NIR range, as well as the reduction in the olivine's peak in MIR range, clue of the sample's amorphization. The study identified the native mineralogy of the meteorite, the products of terrestrial weathering, and the aqueous and thermal alteration experienced by the parent body of the sample
Interlocked and female directors in financial distress companies
No full textThis study aims to bridge gap by investigating whether the presence of interlocked and female directors in financially distressed firms influences the choice of legal procedure — namely, going-concern procedure versus liquidation
An accelerated implementation of Extended Cellular Potts Model for tumor angiogenesis simulations
No full textModern distributed systems and neural computation face increasing demands in processing complex simulations, particularly in computational biology. While distributed computing offers powerful solutions for large-scale problems, certain computational challenges can be effectively addressed through GPU acceleration alone, providing a foundation for future distributed implementations. In this work, we present a GPU-parallel approach for simulating angiogenesis using the Cellular Potts Model (CPM). Here we deal with how a traditionally sequential biological simulation can be transformed into a parallel implementation, establishing a methodology that could be extended to distributed systems. By implementing the CPM on GPU using CUDA, and incorporating both chemotaxis and electric field effects, we extend the basic angiogenesis model by introducing a tumor-related chemical source, thus making a more detailed and biologically relevant simulation environment, we develop a framework that achieves significant performance improvements while maintaining biological accuracy. Experiments conducted on LEONARDO supercomputer, show up to 39x speedup compared to CPU implementations, particularly in handling large-scale matrices and complex energy calculations
Exploring Sustainable Diet Drivers: An Extended TPB Approach to Alternative Protein Acceptance in Southern Italy
No full textBackground/Objectives: This study investigates how consumers decide to adopt alternative proteins—specifically insect-based, cultured meat, and plant-based options—as part of a transition towards environmentally sustainable diets. Building on an extended Theory of Planned Behaviour (TPB), the analysis adds personal moral norms and environmental concerns to better capture the ethical and normative drivers of food choice. Methods: Survey
data from 948 residents of the Campania region (southern Italy) were analysed using partial least squares structural equation modelling (PLS-SEM) to assess the relationship among classical TPB constructs, personal moral norms, environmental concerns, and behavioural intention towards alternative protein consumption. Results: Personal moral norms emerge as the strongest predictor of behavioural intention, directly and indirectly influencing attitudes and environmental concerns. Subjective norms also affect intention, primarily by reinforcing moral norms and perceived behavioural control, although their direct impact is not significant. Classical TPB constructs show limited direct effects. Conclusions: The findings suggest that consumers’ sustainable food intentions are more strongly shaped by moral identity and the surrounding social context than by attitudes alone. The evidence supports the development of culturally sensitive strategies designed to strengthen moral and normative motivations and foster the adoption of alternative proteins
