Blockchain and Cryptocurrencies: a Classification and Comparison of Architecture Drivers

Blockchain is a decentralized transaction and data management solution, the technological leap behind the success of Bitcoin and other cryptocurrencies. As the variety of existing blockchains and distributed ledgers continues to increase, adopters should focus on selecting the solution that best fits their needs and the requirements of their decentralized applications, rather than developing yet another blockchain from scratch. In this paper we present a conceptual framework to aid software architects, developers, and decision makers to adopt the right blockchain technology. The framework exposes the interrelation between technological decisions and architectural features, capturing the knowledge from existing academic literature, industrial products, technical forums/blogs, and experts' feedback. We empirically show the applicability of our framework by dissecting the platforms behind Bitcoin and other top 10 cryptocurrencies, aided by a focus group with researchers and industry practitioners. Then, we leverage the framework together with key notions of the Architectural Tradeoff Analysis Method (ATAM) to analyze four real-world blockchain case studies from industry and academia. Results shown that applying our framework leads to a deeper understanding of the architectural tradeoffs, allowing to assess technologies more objectively and select the one that best fit developers needs, ultimately cutting costs, reducing time-to-market and accelerating return on investment.Comment: Accepted for publication at journal Concurrency and Computation: Practice and Experience. Special Issue on distributed large scale applications and environment

DevOps and Quality Management in Serverless Computing: The RADON Approach

The onset of microservices and serverless computer solutions has forced an ever-increasing demand for tools and techniques to establish and maintain the quality of infrastructure code, the blueprint that drives the operationalization of large-scale software systems. In the EU H2020 project RADON, we propose a machine-learning approach to elaborate and evolve Infrastructure-as-Code as part of a full-fledged industrial-strength DevOps pipeline. This paper illustrates RADON and shows our research roadmap

Real time contrast enhanced ultrasonography in detection of liver metastases from gastrointestinal cancer

Background: Contrast enhanced ultrasound (CEUS) is an imaging technique which appeared on the market around the year 2000 and proposed for the detection of liver metastases in gastrointestinal cancer patients, a setting in which accurate staging plays a significant role in the choice of treatment. Methods: A total of 109 patients with colorectal (n = 92)or gastric cancer prospectively underwent computed tomography (CT) scan and conventional US evaluation followed by real time CEUS. A diagnosis of metastases was made by CT or, for lesions not visibile at CT, the diagnosis was achieved by histopathology or by a malignant behavior during follow-up. Results: Of 109 patients, 65 were found to have metastases at presentation. CEUS improved sensitivity in metastatic livers from 76.9% of patients (US) to 95.4% (p < 0.01), while CT scan reached 90.8% (p = n.s. vs CEUS, p < 0.01 vs US). CEUS and CT were more sensitive than US also for detection of single lesions (87 with US, 122 with CEUS, 113 with CT). In 15 patients (13.8%), CEUS revealed more metastases than CT, while CT revealed more metastases than CEUS in 9 patients (8.2%) (p = n.s.). Conclusion: CEUS is more sensitive than conventional US in the detection of liver metastases and could be usefully employed in the staging of patients with gastrointestinal cancer. Findings at CEUS and CT appear to be complementary in achieving maximum sensitivity. © 2007 Piscaglia et al; licensee BioMed Central Ltd

Cervical cancer screening in women vaccinated against human papillomavirus infection: Recommendations from a consensus conference

In Italy, the cohorts of women who were offered Human papillomavirus (HPV) vaccination in 2007/08 will reach the age (25&nbsp;years) for cervical cancer (CC) screening from 2017. The simultaneous shift from cytology-based screening to HPV test-based screening gives the opportunity for unprecedented reorganisation of CC prevention. The ONS (National Screening Monitoring Centre) Directive and the GISCi (Italian Group for Cervical Screening) identified the consensus conference as the most suitable method for addressing this topic. A summary of consensus recommendations is reported here. The main objective was to define the best screening methods in girls vaccinated against HPV and the knowledge required for defining evidence-based screening strategies. A Jury made recommendations about questions and proposals formulated by a panel of experts representative of Italian scientific societies involved in CC prevention and based on systematic reviews of literature and evidence. The Jury considered changing the screening protocols for girls vaccinated in their twelfth year as appropriate. Tailored screening protocols based on vaccination status could be replaced by \u201cone size fits all\u201d protocols only when a herd immunity effect has been reached. Vaccinated women should start screening at age 30, instead of 25, with HPV test. Furthermore, there is a strong rationale for applying longer intervals for re-screening HPV negative women than the currently recommended 5&nbsp;years, but research is needed to determine the optimal screening time points. For non-vaccinated women and for women vaccinated in their fifteenth year or later, the current protocol should be kept

SARS-CoV-2 Breakthrough Infections: Incidence and Risk Factors in a Large European Multicentric Cohort of Health Workers

The research aimed to investigate the incidence of SARS-CoV-2 breakthrough infections and their determinants in a large European cohort of more than 60,000 health workers

The Genesy Model for a Blockchain-based Fair Ecosystem of Genomic Data

Recent advances in technology have drastically downsized costs and implementation times for genomic services. The wide availability of low-cost genomic technologies and the easy access to genomic data can significantly improve the productivity and efficiency of healthcare, all to the benefit of social well-being in general. For example, by creating the conditions for researchers to identify the causes of multiple diseases and by contributing to the development of new drugs, we can improve the quality of life and give people, as users of genomic services, the means to positively impact their health. This article describes how blockchain technology can lay the foundations of an ecosystem that encourages users to acquire and share their genomic data in full awareness and without fear of being circumvented, so as to participate in the benefits and advances in genomic research. The starting point is Genesy, an innovative blockchain platform that transcribes genomic data, thus facilitating and at the same time safeguarding the users of genomic services in their relationships with parties interested in accessing and using data they own, such as research centers, pharmaceutical companies, hospitals, geneticists. This result is obtained by exploiting the capabilities of blockchain technology to notarize data and prevent their unauthorized use, and at the same time to make them objects of possible transactions between different parties. Looking ahead, the Genesy model can be generalized to promote an ecosystem, and a fair market, of all types of biomedical data