Archivio della ricerca della Scuola Superiore Sant'Anna
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Joint and several liability between Europol and a Member State for damages from unlawful disclosure of personal data (comment on European Court of Justice, 5 March 2024, C‐755/21 P)
No full textA Comparative Study of Compressed, Learned, and Traditional Indexing Methods for Integer Data
Get PDFThe rapid evolution of learned data structures has revolutionized database indexing, particularly for sorted integer datasets. While learned indexes excel in static scenarios due to their low memory footprint, reduced storage requirements, and fast lookup times, benchmarks like SOSD and TLI have largely overlooked compressed indexes and SIMD-based implementations of traditional indexes. This paper addresses this gap by introducing a comprehensive benchmarking framework that (i) evaluates traditional, learned, and compressed indexes across 12 datasets (real and synthetic) of varying types and sizes; (ii) integrates state-of-the-art SIMD-enhanced B-Tree variants; and (iii) measures critical performance metrics such as memory usage, construction time, and lookup efficiency. Our findings reveal that while learned indexes minimize memory usage, a feature useful when internal memory constraints are mandatory, SIMD-enhanced B-Trees consistently achieve superior lookup times with comparable extra space. On the other hand, compressed indexes like LA-vector and EliasFano provide very effective compression of the indexed data with slower access speeds (2x–3x). Another contribution of this paper is a publicly available benchmarking framework (composed of code and datasets) that makes our experiments reproducible and extensible to other indexes and datasets
Virtue Monism and Medical Practice: Practical Wisdom as Cross-Situational Ethical Expertise
No full textThis article defends the centrality of practical wisdom in medical practice by building on a monistic view of moral virtue, termed the “Aretai model”, according to which possession of practical wisdom is necessary and sufficient for virtuousness, grounding both moral growth and effective moral behavior. From this perspective, we argue that practical wisdom should be conceived as a cross-situational ethical expertise consisting of four skills:moral perception, moral deliberation, emotion regulation, and moral motivation. Conceiving of practical wisdom as both overall virtuousness and ethical expertise makes it possible to deal adequately with the uniqueness of concrete ethically relevant situations. We contend that this becomes particularly evident in the context of medical practice, both in terms of decision-making and action-taking, especially in the most challenging or contentious clinical cases. We conclude the article by suggest- ing the potential implications of the Aretai model for continuing education in medical and healthcare professions
Book Review: The Normative Foundations of EU Criminal Justice. Powers, Limits and Justifications
No full textEarly detection of cardiac amyloidosis in patients with multiple myeloma by echocardiography: Is it suitable?
No full textL’accoglienza dei richiedenti asilo nella direttiva 2024/1346. Profili di continuità, qualche luce e persistenti ombre
Get PDFQuantitative ultrasound classification of healthy and chemically degraded ex-vivo cartilage
Get PDFIn this study, we explore the potential of ten quantitative (radiofrequency-based) ultrasound parameters to assess the progressive loss of collagen and proteoglycans, mimicking an osteoarthritis condition in ex-vivo bovine cartilage samples. Most analyzed metrics showed significant changes as the degradation progressed, especially with collagenase treatment. We propose for the first time a combination of these ultrasound parameters through machine learning models aimed at automatically identifying healthy and degraded cartilage samples. The random forest model showed good performance in distinguishing healthy cartilage from trypsin-treated samples, with an accuracy of 60%. The support vector machine demonstrated excellent accuracy (96%) in differentiating healthy cartilage from collagenase-degraded samples. Histological and mechanical analyses further confirmed these findings, with collagenase having a more pronounced impact on both mechanical and histological properties, compared to trypsin. These metrics were obtained using an ultrasound probe having a transmission frequency of 15 MHz, typically used for the diagnosis of musculoskeletal diseases, enabling a fully non-invasive procedure without requiring arthroscopic probes. As a perspective, the proposed quantitative ultrasound assessment has the potential to become a new standard for monitoring cartilage health, enabling the early detection of cartilage pathologies and timely interventions
Automated Neural Architecture Search for Cardiac Amyloidosis Classification from [18F]-Florbetaben PET Images
No full textMedical image classification using convolutional neural networks (CNNs) is promising but often requires extensive manual tuning for optimal model definition. Neural architecture search (NAS) automates this process, reducing human intervention significantly. This study applies NAS to [18F]-Florbetaben PET cardiac images for classifying cardiac amyloidosis (CA) sub-types (amyloid light chain (AL) and transthyretin amyloid (ATTR)) and controls. Following data preprocessing and augmentation, an evolutionary cell-based NAS approach with a fixed network macro-structure is employed, automatically deriving cells’ micro-structure. The algorithm is executed five times, evaluating 100 mutating architectures per run on an augmented dataset of 4048 images (originally 597), totaling 5000 architectures evaluated. The best network (NAS-Net) achieves 76.95% overall accuracy. K-fold analysis yields mean ± SD percentages of sensitivity, specificity, and accuracy on the test dataset: AL subjects (98.7 ± 2.9, 99.3 ± 1.1, 99.7 ± 0.7), ATTR-CA subjects (93.3 ± 7.8, 78.0 ± 2.9, 70.9 ± 3.7), and controls (35.8 ± 14.6, 77.1 ± 2.0, 96.7 ± 4.4). NAS-derived network performance rivals manually determined networks in the literature while using fewer parameters, validating its automatic approach’s efficacy
Transfer entropy analysis reveals interaction dynamics between termite castes
No full textTermites exhibit complex social structures characterized by distinct castes, each playing specialized roles within the colony. This study explores the interaction dynamics between the worker and soldier castes of Reticulitermes lucifugus using a transfer entropy framework. Inter-individual interactions were investigated across three caste pairings (worker with worker, soldier with soldier, and worker with soldier), enabling direct comparison of interaction dynamics. A computer vision pipeline tracked movements, and two variables, occupied area and speed, were analyzed as proxies for interaction. Transfer entropy quantified the amount, direction, and timing of information transfer. Sampling resolution and time lags were systematically varied to map temporal scales of influence. The working assumption was that higher transfer entropy values reflect a higher level of interaction between individuals. First, in the temporal-resolution analysis of speed, worker–worker pairs showed the highest total transfer entropy, and mixed pairs exhibited directional asymmetry, with higher information flow from soldiers to workers than vice versa. Second, in the time-lag analysis, total transfer entropy for occupied area was higher in worker–worker pairs (1.04 bits), compared with soldier–soldier (0.67 bits) and mixed (0.68 bits) pairs. The same pattern held for speed, with worker–worker pairs reaching 0.25 bits, whereas soldier–soldier and mixed pairs reached 0.20 bits. Overall, results indicate caste-specific interaction dynamics, with worker-worker pairs exhibiting a higher level of interaction. These insights advance understanding of termite social organization and suggest applications in pest management, with broader implications for swarm intelligence and bio-inspired engineering