“Dicam dumtaxat quod est historicon”: Varro and/on the past

Varro’s approach to his subjects is usually systematic and synchronic, but there are frequent diachronic digressions and observations on time and the past, often divided into three stages (remote past, near past, and present). I discuss Rust. 2.1, with a progressive concept of three successive stages in human history from Dicaearchus, and a fragment from Censorinus, where Varro distinguishes tria discrimina temporum. A significant affinity emerges between etymological research and the study of origins: both involve the study of antiquitas or the origo, and both use the genealogical-reconstructive method. The same image of gradus descendere indicates the sequence of logical and chronological steps in describing human history (Rust. 2.1.3–5) and etymological research (Ling. 5.7–9). Varro is fully aware of the difficulties in reconstructing the ancient past and the origins of language, because uncertainty is a characteristic of the origo of human history and of words

Information fusion in content based image retrieval: A comprehensive overview

An ever increasing part of communication between persons involve the use of pictures, due to the cheap availability of powerful cameras on smartphones, and the cheap availability of storage space. The rising popularity of social networking applications such as Facebook, Twitter, Instagram, and of instant messaging applications, such as WhatsApp, WeChat, is the clear evidence of this phenomenon, due to the opportunity of sharing in real-time a pictorial representation of the context each individual is living in. The media rapidly exploited this phenomenon, using the same channel, either to publish their reports, or to gather additional information on an event through the community of users. While the real-time use of images is managed through metadata associated with the image (i.e., the timestamp, the geolocation, tags, etc.), their retrieval from an archive might be far from trivial, as an image bears a rich semantic content that goes beyond the description provided by its metadata. It turns out that after more than 20 years of research on Content-Based Image Retrieval (CBIR), the giant increase in the number and variety of images available in digital format is challenging the research community. It is quite easy to see that any approach aiming at facing such challenges must rely on different image representations that need to be conveniently fused in order to adapt to the subjectivity of image semantics. This paper offers a journey through the main information fusion ingredients that a recipe for the design of a CBIR system should include to meet the demanding needs of users

Vettori, Piero

Biografia del filologo classico Piero Vettori (1499-1585), figura centrale della filologia classica italiana ed europea del Cinquencento. Erede della grande tradizione umanistica quattrocentesca (in particolare di Poliziano), svolse il suo insegnamento di greco e latino e la sua attività di ricerca a Firenze, in contatto con tutti i più grandi classicisti europeiBiography of the classical philologist Piero Vettori (1499-1585), central figure of the Italian and European classical philology of the sixteenth century. Heir of the great fifteenth-century humanistic tradition (in particular of Politian), he carried out his teaching of Greek and Latin and his research activity in Florence, in contact with all the greatest European classicist

Adversarial Attacks Against Uncertainty Quantification

Machine-learning models can be fooled by adversarial examples, i.e., carefully-crafted input perturbations that force models to output wrong predictions. While uncertainty quantification has been recently proposed to detect adversarial inputs, under the assumption that such attacks exhibit a higher prediction uncertainty than pristine data, it has been shown that adaptive attacks specifically aimed at reducing also the uncertainty estimate can easily bypass this defense mechanism. In this work, we focus on a different adversarial scenario in which the attacker is still interested in manipulating the uncertainty estimate, but regardless of the correctness of the prediction; in particular, the goal is to undermine the use of machine-learning models when their outputs are consumed by a downstream module or by a human operator. Following such direction, we: \textit{(i)} design a threat model for attacks targeting uncertainty quantification; \textit{(ii)} devise different attack strategies on conceptually different UQ techniques spanning for both classification and semantic segmentation problems; \textit{(iii)} conduct a first complete and extensive analysis to compare the differences between some of the most employed UQ approaches under attack. Our extensive experimental analysis shows that our attacks are more effective in manipulating uncertainty quantification measures than attacks aimed to also induce misclassifications

Explaining Machine Learning DGA Detectors from DNS Traffic Data

One of the most common causes of lack of continuity of online systems stems from a widely popular Cyber Attack known as Distributed Denial of Service (DDoS), in which a network of infected devices (botnet) gets exploited to flood the computational capacity of services through the commands of an attacker. This attack is made by leveraging the Domain Name System (DNS) technology through Domain Generation Algorithms (DGAs), a stealthy connection strategy that yet leaves suspicious data patterns. To detect such threats, advances in their analysis have been made. For the majority, they found Machine Learning (ML) as a solution, which can be highly effective in analyzing and classifying massive amounts of data. Although strongly performing, ML models have a certain degree of obscurity in their decision-making process. To cope with this problem, a branch of ML known as Explainable ML tries to break down the black-box nature of classifiers and make them interpretable and human-readable. This work addresses the problem of Explainable ML in the context of botnet and DGA detection, which at the best of our knowledge, is the first to concretely break down the decisions of ML classifiers when devised for botnet/DGA detection, therefore providing global and local explanations

User-driven Nearest Neighbour Exploration of Image Archives

Learning what a specific user is exactly looking for, during a session of image search and retrieval, is a problem that has been mainly approached with â??classificationâ?? or â??explorationâ?? techniques. Classification techniques follow the assumption that the images in the archive are statically subdivided into classes. Exploration approaches, on the other hand, are more focused on following the varying needs of the user. It turns out that image retrieval techniques based on classification approaches, though often showing good performances, are not prone to adapt to different usersâ?? goals. In this paper we propose a relevance feedback mechanism that drives the search into promising regions of the feature space according to the Nearest Neighbor paradigm. In particular, each image labelled as being relevant by the user, is used as a â??seedâ?? for an exploration of the space based on the Nearest Neighbors paradigm. Reported results show that this technique allows attaining higher recall and average precision performances than other state-of-the-art relevance feedback approaches

Indice delle opere recensite 1873-2002

Spoglio delle annate 21-40, 86-88, 103-114, coordinamento generale, definizione dei criteri di ordinamento, controllo delle correzioni e redazione dell’Avvertenza, pp. 4 sg. e dell’errata-corrige, p. 512. Delle opere recensite è stato effettuato sistematicamente il controllo della correttezza bibliografica, procedendo tacitamente a correggere i riferimenti scorretti presenti a stampa, e si è proceduto all'uniformazione delle modalità di citazione, cambiate nel corso della plurisecolare vita della rivista

Indice degli autori 1873-2002

Spoglio delle annate 21-40, 86-88, 103-114 e coordinamento finale. Revisione sistematica con correzione tacita degli errori presenti a stampa

What unrelated hematopoietic stem cell transplantation in thalassemia taught us about transplant immunogenetics

Although the past few decades have shown an improvement in the survival and complication-free survival rates in patients with beta-thalassemia major and gene therapy is already at an advanced stage of experimentation, hematopoietic stem cell transplantation (HSCT) continues to be the only effective and realistic approach to the cure of this chronic nonmalignant disease. Historically, human leukocyte antigen (HLA)-matched siblings have been the preferred source of donor cells owing to superior outcomes compared with HSCT from other sources. Nowadays, the availability of an international network of voluntary stem cell donor registries and cord blood banks has significantly increased the odds of finding a suitable HLA matched donor. Stringent immunogenetic criteria for donor selection have made it possible to achieve overall survival (OS) and thalassemia-free survival (TFS) rates comparable to those of sibling transplants. However, acute and chronic graft-versus-host disease (GVHD) remains the most important complication in unrelated HSCT in thalassemia, leading to significant rates of morbidity and mortality for a chronic non-malignant disease. A careful immunogenetic assessment of donors and recipients makes it possible to individualize appropriate strategies for its prevention and management. This review provides an overview of recent insights about immunogenetic factors involved in GVHD, which seem to have a potential role in the outcome of transplantation for thalassemia

BAT2 and BAT3 polymorphisms as novel genetic risk factors for rejection after HLA-related SCT.

The genetic background of donor and recipient is an important factor determining the outcome of allogeneic hematopoietic SCT (allo-HSCT). We applied whole-genome analysis to investigate genetic variants - other than HLA class I and II - associated with negative outcome after HLA-identical sibling allo-HSCT in a cohort of 110 β-Thalassemic patients. We identified two single-nucleotide polymorphisms (SNPs) in BAT2 (A/G) and BAT3 (T/C) genes, SNP rs11538264 and SNP rs10484558, both located in the HLA class III region, in strong linkage disequilibrium between each other (R2 =0.92). When considered as single SNP, none of them reached a significant association with graft rejection (nominal P<0.00001 for BAT2 SNP rs11538264, and P<0.0001 for BAT3 SNP rs10484558), whereas the BAT2/BAT3 A/C haplotype was present at significantly higher frequency in patients who rejected as compared to those with functional graft (30.0% vs 2.6%, nominal P=1.15 × 10-8; and adjusted P=0.0071). The BAT2/BAT3 polymorphisms and specifically the A/C haplotype may represent a novel immunogenetic factor associated with graft rejection in patients undergoing allo-HSCT