Publications by authors named "G Destefanis"

The expansion of smart contracts on the Ethereum blockchain has created a diverse ecosystem of decentralized applications. This growth, however, poses challenges in classifying and securing these contracts. Existing research often separately addresses either classification or vulnerability detection, without a comprehensive analysis of how contract types are related to security risks.

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The developments in conversational AI raised urgent questions about the future direction of many aspects of society, including computing education. The first reactions to the fast-paced evolution of conversational agents were varied: Some announced "the end of programming," while others considered this "premature obituary of programming." Some adopted a defensive approach to detecting the use of conversational AI and avoiding an increase in plagiarism, while others questioned, "So what if ChatGPT wrote it?" Nevertheless, questions arise about whether computing education in its current form will still be relevant and fit for purpose in the era of conversational AI.

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Smart contracts (SC) are software programs that reside and run over a blockchain. The code can be written in different languages with the common purpose of implementing various kinds of transactions onto the hosting blockchain. They are ruled by the blockchain infrastructure with the intent to automatically implement the typical conditions of traditional contracts.

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The novel coronavirus that causes the Coronavirus Disease 2019 (COVID-19) has spread all over the world at an unprecedented rate. With growing recognition of the distributed nature of health services, the technology of blockchain has recently reached the impetus of the healthcare domain. This article provides: 1) a panoramic overview of existing solutions and scenarios incorporating blockchain to combat COVID-19 in the healthcare domain along with their benefits and challenges; as well as 2) a framework that will facilitate new research activities on this subject.

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Samples of longissimus thoracis muscle of young bulls belonging to Piemontese (n=10), Limousin (n=11) and Friesian (n=10) breeds were analysed in order to study the chemical composition, fatty acids and cholesterol content of beef purchased at retail. The breeds and their differences in intramuscular fat content strongly influenced the fatty acids profile. The Piemontese animals displayed the lowest intramuscular fat and SFA content, while Friesian animals showed the highest intramuscular fat, SFA and MUFA content.

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