Preface of the 31st Italian Symposium on Advanced Database Systems

This volume contains the proceedings of the 31st Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), held in Galzinagno Terme (Padua, Italy) from 2 to 5 July 2023.</p

Preface of the 31st Italian Symposium on Advanced Database Systems

This volume contains the proceedings of the 31st Italian Symposium on Advanced Database Systems (SEBD - Sistemi Evoluti per Basi di Dati), held in Galzinagno Terme (Padua, Italy) from 2 to 5 July 2023.</p

Intelligenza artificiale e sicurezza: opportunità, rischi e raccomandazioni

L'IA (o intelligenza artificiale) è una disciplina in forte espansione negli ultimi anni e lo sarà sempre più nel prossimo futuro: tuttavia è dal 1956 che l’IA studia l’emulazione dell’intelligenza da parte delle macchine, intese come software e in certi casi hardware. L’IA è nata dall’idea di costruire macchine che - ispirandosi ai processi legati all’intelligenza umana - siano in grado di risolvere problemi complessi, per i quali solitamente si ritiene che sia necessario un qualche tipo di ragionamento intelligente. La principale area di ricerca e applicazione attuale dell’IA è il machine learning (algoritmi che imparano e si adattano in base ai dati che ricevono), che negli ultimi anni ha trovato ampie applicazioni grazie alle reti neurali (modelli matematici composti da neuroni artificiali) che a loro volta hanno consentito la nascita del deep learning (reti neurali di maggiore complessità). Appartengono al mondo dell’IA anche i sistemi esperti, la visione artificiale, il riconoscimento vocale, l’elaborazione del linguaggio naturale, la robotica avanzata e alcune soluzioni di cybersecurity. Quando si parla di IA c'è chi ne è entusiasta pensando alle opportunità, altri sono preoccupati poiché temono tecnologie futuristiche di un mondo in cui i robot sostituiranno l'uomo, gli toglieranno il lavoro e decideranno al suo posto. In realtà l'IA è ampiamente utilizzata già oggi in molti campi, ad esempio nei cellulari, negli oggetti smart (IoT), nelle industry 4.0, per le smart city, nei sistemi di sicurezza informatica, nei sistemi di guida autonoma (drive o parking assistant), nei chat bot di vari siti web; questi sono solo alcuni esempi basati tutti su algoritmi tipici dell’intelligenza artificiale. Grazie all'IA le aziende possono avere svariati vantaggi nel fornire servizi avanzati, personalizzati, prevedere trend, anticipare le scelte degli utenti, ecc. Ma non è tutto oro quel che luccica: ci sono talvolta problemi tecnici, interrogativi etici, rischi di sicurezza, norme e legislazioni non del tutto chiare. Le organizzazioni che già adottano soluzioni basate sull’IA, o quelle che intendono farlo, potrebbero beneficiare di questa pubblicazione per approfondirne le opportunità, i rischi e le relative contromisure. La Community for Security del Clusit si augura che questa pubblicazione possa fornire ai lettori un utile quadro d’insieme di una realtà, come l’intelligenza artificiale, che ci accompagnerà sempre più nella vita personale, sociale e lavorativa.AI (or artificial intelligence) is a booming discipline in recent years and will be increasingly so in the near future.However, it is since 1956 that AI has been studying the emulation of intelligence by machines, understood as software and in some cases hardware. AI arose from the idea of building machines that-inspired by processes related to human intelligence-are able to solve complex problems, for which it is usually believed that some kind of intelligent reasoning is required. The main current area of AI research and application is machine learning (algorithms that learn and adapt based on the data they receive), which has found wide applications in recent years thanks to neural networks (mathematical models composed of artificial neurons), which in turn have enabled the emergence of deep learning (neural networks of greater complexity). Also belonging to the AI world are expert systems, computer vision, speech recognition, natural language processing, advanced robotics and some cybersecurity solutions. When it comes to AI there are those who are enthusiastic about it thinking of the opportunities, others are concerned as they fear futuristic technologies of a world where robots will replace humans, take away their jobs and make decisions for them. In reality, AI is already widely used in many fields, for example, in cell phones, smart objects (IoT), industries 4.0, for smart cities, cybersecurity systems, autonomous driving systems (drive or parking assistant), chat bots on various websites; these are just a few examples all based on typical artificial intelligence algorithms. Thanks to AI, companies can have a variety of advantages in providing advanced, personalized services, predicting trends, anticipating user choices, etc. But not all that glitters is gold: there are sometimes technical problems, ethical questions, security risks, and standards and legislation that are not entirely clear. Organizations already adopting AI-based solutions, or those planning to do so, could benefit from this publication to learn more about the opportunities, risks, and related countermeasures. Clusit's Community for Security hopes that this publication will provide readers with a useful overview of a reality, such as artificial intelligence, that will increasingly accompany us in our personal, social and working lives

Neutralizing antibodies to Omicron after the fourth SARS-CoV-2 mRNA vaccine dose in immunocompromised patients highlight the need of additional boosters

IntroductionImmunocompromised patients have been shown to have an impaired immune response to COVID-19 vaccines.MethodsHere we compared the B-cell, T-cell and neutralizing antibody response to WT and Omicron BA.2 SARS-CoV-2 virus after the fourth dose of mRNA COVID-19 vaccines in patients with hematological malignancies (HM, n=71), solid tumors (ST, n=39) and immune-rheumatological (IR, n=25) diseases. The humoral and T-cell responses to SARS-CoV-2 vaccination were analyzed by quantifying the anti-RBD antibodies, their neutralization activity and the IFN-γ released after spike specific stimulation.ResultsWe show that the T-cell response is similarly boosted by the fourth dose across the different subgroups, while the antibody response is improved only in patients not receiving B-cell targeted therapies, independent on the pathology. However, 9% of patients with anti-RBD antibodies did not have neutralizing antibodies to either virus variants, while an additional 5.7% did not have neutralizing antibodies to Omicron BA.2, making these patients particularly vulnerable to SARS-CoV-2 infection. The increment of neutralizing antibodies was very similar towards Omicron BA.2 and WT virus after the third or fourth dose of vaccine, suggesting that there is no preferential skewing towards either virus variant with the booster dose. The only limited step is the amount of antibodies that are elicited after vaccination, thus increasing the probability of developing neutralizing antibodies to both variants of virus.DiscussionThese data support the recommendation of additional booster doses in frail patients to enhance the development of a B-cell response directed against Omicron and/or to enhance the T-cell response in patients treated with anti-CD20

A Short Account of Techniques for Assisting Users in Mastering Big Data

One of the most challenging problems faced by the database community is to assist inexperienced or casual users, who need the support of a sophisticated system that guides them in making sense of the data. This problem becomes especially relevant in the case of Big Data, where the amount of data may quickly overwhelm users and discourage them from leveraging the richness of the data patrimony. In the last years, often in collaboration with other members of the Italian database community, we have developed several different techniques whose aim is both to reduce the size of the problem and to focus on the information that is most relevant to the user. To this end, most of these techniques fruitfully extract and exploit data semantics, for example by succinctly characterizing data via intensional properties such as integrity constraints or by tailoring the answer to the user context or preferences. Other techniques support the users in information exploration, for instance by extracting data not readily accessible (such as the Hidden Web) or by presenting them with appropriate summaries and suggesting possible exploration paths

Effects of Malnutrition on Left Ventricular Mass in a North-Malagasy Children Population.

BACKGROUND:Malnutrition among children population of less developed countries is a major health problem. Inadequate food intake and infectious diseases are combined to increase further the prevalence. Malnourishment brings to muscle cells loss with development of cardiac complications, like arrhythmias, cardiomyopathy and sudden death. In developed countries, malnutrition has generally a different etiology, like chronic diseases. The aim of our study was to investigate the correlation between malnutrition and left ventricular mass in an African children population. METHODS:313 children were studied, in the region of Antsiranana, Madagascar, with age ranging from 4 to 16 years old (mean 7,8 ± 3 years). A clinical and echocardiographic evaluation was performed with annotation of anthropometric and left ventricle parameters. Malnutrition was defined as a body mass index (BMI) value age- and sex-specific of 16, 17 and 18,5 at the age of 18, or under the 15th percentile. Left ventricle mass was indexed by height2.7 (LVMI). RESULTS:We identified a very high prevalence of children malnutrition: 124 children, according to BMI values, and 100 children under the 15th percentile. LVMI values have shown to be increased in proportion to BMI percentiles ranging from 29,8 ± 10,8 g/m2.7 in the malnutrition group to 45 ± 15,1 g/m2.7 in >95th percentile group. LVMI values in children < 15th BMI percentile were significantly lower compared to normal nutritional status (29,8 ± 10,8 g/m2,7 vs. 32,9 ± 12,1 g/m2,7, p = 0.02). Also with BMI values evaluation, malnourished children showed statistically lower values of LVMI (29,3 ± 10,1 g/m2,7 vs. 33,6 ± 12,5 g/m2,7, p = 0.001). CONCLUSION:In African children population, the malnourishment status is correlated with cardiac muscle mass decrease, which appears to be reduced in proportion to the decrease in body size