Archivio della ricerca della Scuola Superiore Sant'Anna
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Reclaiming strict protection via the European Green Deal
No full textStrict protection is a fundamental component of any strategy
for biodiversity protection and ecosystem restoration. Most
Western countries, however, currently fail to acknowledge its
relevance in their conservation programs. The European Green
Deal (EGD)—the climate neutrality strategy launched by the
European Union (EU) in 2019—is a marked exception. By identifying
strict protection as one of the key solutions to ensure ecosystem
health, the EGD reasserts the importance of strict
protection both at the regional and global level. However, its
approach is far from perfect. To harness the full potential of strict
protection, the EU must clarify the existing regulatory framework
and strengthen its commitment to ecological sustainabilit
Transizione digitale e diritto penale. Dall’evoluzione delle categorie sostanziali al “nuovo volto” del law enforcement
No full textL’impatto della transizione digitale sul diritto penale può essere apprezzato sul duplice versante del diritto sostan-
ziale e del law enforcement. Pur a fronte di una tendenziale anelasticità del diritto penale agli effetti trasformativi
di passaggi disruptive, l’evoluzione delle categorie sostanziali – dal soggetto attivo, alla condotta, dalla causalità
alla colpevolezza – risulta inevitabile. La pervasività degli effetti della transizione digitale, infatti, si riverbera sui
modelli di incriminazione e sui presupposti di imputazione di una responsabilità storicamente e strutturalmente
legata alla prospettiva della persona fisica, dello spazio “analogico” e della fondazione antropomorfica delle catego-
rie sostanziali. Come paradigmaticamente desumibile dai profili penali della cybersecurity, la trasformazione delle
categorie sostanziali e dei presupposti della responsabilità si collega anche alla sperimentazione di nuovi percorsi
di law enforcement, caratterizzati dall’enfasi sulle funzioni preventive e collaborative tra i diversi attori del mondo
digitale
Assessing costs and benefits of a Nature-based Solution through a triple bottom line and participatory approach
No full textALPACA
No full textALPACA, or ALPHACA, is a camera-only software that estimates user satisfaction (UX) from users' facial emotional dynamics.
It extracts a valence–arousal time series from RGB frames using a Facial Emotion Recognition module and computes features over time windows.
It supports identity-free (default, privacy-by-design) and context-aware (optional, with metadata to improve robustness) modes.
Designed to also run on-device without saving videos, storing only anonymized descriptors if required.
The software was developed with the contribution of Prof. Cosimo Antonio Prete of the University of Pisa
Beyond optimality: Genetic Algorithms and Fuzzy Inference for Coil-Order allocation in the steel industry
No full textThe paper addresses the Coil-Order Allocation problem in steel industry via Genetic Algorithms through two approaches: a basic solution with a standard objective function and an advanced method incorporating a Fuzzy Inference System to mimic human decision-making. Both solutions were tested on real-world data from a tinplate production plant, achieving significant improvements in orders fulfillment and material utilization compared to manual allocation. The basic genetic approach outperforms the baseline in efficiency, while the fuzzy-genetic method demonstrate flexibility for complex, customizable optimization. The results show the potential of combining heuristic techniques and fuzzy logic to enhance industrial operations
Intracoronary cytoprotective gene therapy in a dog with dilated cardiomyopathy: long term follow up
No full textOutcome centred process mapping in healthcare using random forest and process mining
No full text: System process mapping is essential for understanding complex systems and implementing effective management practices. In healthcare, mapping patient flow aims to reduce costs, improve the quality of care, and enhance efficiency. Process mining (PM) in healthcare is challenging due to the need for specialised knowledge and the inherent variability and complexity of healthcare processes. Comparing observed differences in patient flow pathways provides only a partial view; they must be combined with process outcomes and attributes for a comprehensive understanding. This paper proposes a combined stepwise approach using random forest (RF) and PM discovery to achieve outcome-centred process mapping from process-unaware systems. To this aim, we analysed the MIMIC-IV v2.2 dataset, containing healthcare data from patients at the Beth Israel Deaconess Medical Center (BIDMC) between the years 2008-2019. The MIMIC-IV dataset includes different types of sources within the hospital such as the emergency department (ED), patient measurements, procedures, transfer between departments, and intensive care units (ICUs). The results indicate that older patients with high ED priority and multimorbidity are particularly complex and challenging to treat, necessitating the implementation of tailored management strategies, in agreement with common clinical practice. A potential application of this approach is the real-time prediction of patients' length of stay, which could optimise clinicians' work, save healthcare resources, and improve the quality of patient care. Our approach can be applied to improve system process management by combining control-flow and data perspectives