1,720,962 research outputs found
Quick Direct-method Controlled (QDC): a simulator of metabolic experiments
No full textQuick Direct-method Controlled (QDC) is a stochastic simulator based on the direct method version of Gillespie’s Stochastic Simulation Algorithm (SSA). It has been specifically designed to simulate experiments performed on metabolic networks, when external operators can act on the system, modifying its spontaneous behaviour. Users of QDC can simulate different experimental controls: i.e., add or remove chemical species at a given time; change the rate of a reaction at a given moment; and describe reactions with complex stoichiometry that take place once the stoichiometric condition is verified (here called immediate reactions). Moreover, even though QDC is not designed to manage compartments, it can simulate up-take and excretion reactions. QDC represents a useful tool for the specific field of interest thanks to its computational performances and simple input language
Enhancing Supply Chain Transparency through Blockchain Product Passports
No full textThe European Union is tackling the challenge of reducing its environmental impact and carbon footprint: the Green Deal, promoted in 2022, is one of the most important regulations proposed by the European Union in terms of sustainability. The goal of this regulation is to make the production of almost all of the products manufactured in Europe more friendly to the environment and energy efficient. This regulation also introduces the Digital Product Passport, a tool designed to collect and share product data across all the phases of its lifecycle. The digital product passport aims to enable secure and transparent communication of essential product information among all economic stakeholders. This initiative is designed to enhance the sustainability and circularity of products. It also serves as a tool for regulatory authorities to ensure manufacturers meet legal requirements and assists consumers in making well-informed purchasing choices. Considering the utility of such information, it is crucial to make them the more trustworthy as possible. Leveraging blockchain’s inherent characteristics, like transparency and data immutability, ensures that the passport remains consistently verifiable and reliable. In this paper, we addressed the challenge of implementing a blockchain-based digital product passport, providing a detailed description of the required features and possible use cases and proposing some practical ideas for the implementation
A Blockchain-Based Privacy-Preserving Auditable Data Structure Framework
No full textEvery digital process needs to consume some data in order to work properly. It is very common for applications to rely on external data sources, such as APIs. When data is not self-generated, the reliability of both the external data source and its produced data cannot be taken for granted. Therefore, ensuring the trustworthiness and verifiability of the received data is paramount. While authenticated data structures are commonly used to establish trust by authenticating the data source and generating proofs of data authenticity or integrity, they fall short in use cases like data notarization that require also verification of data history and its consistency. This problem seems to be unaddressed by current literature, which proposes some approaches aimed at executing audits by internal actors with prior knowledge about the data structures. In this paper, we analyze the terminology and the current state of the art of the auditable data structures, then we propose a general framework that makes use of a public blockchain as trusted anchor for notarizing data, thereby supporting privacy-preserving audits from both internal and external entities without prior data knowledge. A detailed description of the framework implementation, alongside with experimental results, is provided, showing the effectiveness of our framework in terms of proof generation and evaluation
Trustworthy AI for infrastructure monitoring: a blockchain-based approach
No full textIn the field of Artificial Intelligence (AI), there is an increasing focus on enhancing trustworthiness especially in critical sectors such as in the management of civil infrastructure. This paper proposes the adoption of a framework based on Hybrid Distributed Ledger Technology (Hybrid-DLT) as a technological solution for improving trustworthiness. We detail three specific applications in the sector of critical infrastructure maintenance: Explainable AI (XAI) for risk classification, structural defects recognition, and real-time monitoring through IoT. The proposed approach employs tamper-resistant ledgers for tracking key processes such as dataset collection, model training, and inference generation, thereby ensuring non-repudiability for recorded actions and enabling auditability. We demonstrate how this strengthens the explainability mechanisms of AI models and enables the production of verifiable data lineage and certified inferences. Our framework can be applied to existing AI solutions, enhancing their trustworthiness
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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