102,093 research outputs found
Recensione a Squillace G., Filippo II di Macedonia, Salerno Editrice, Roma 2022, pp. 360, ISBN 9788869736780
No full textLa biografia su Filippo II di G.
Squillace è il risultato di una ricerca che
l’autore ha iniziato in ambito dottorale e
che ha conosciuto un primo sviluppo con
la pubblicazione di un libro dedicato al
Macedone nel 2009. Nonostante si tratti di
una seconda analisi della vita di Filippo, il
lavoro presenta elementi di novità, includendo non soltanto la storia evenemenziale,
ma anche uno studio, condotto spesso in
ottica comparatistica, delle fonti e delle
letture che su questo personaggio nacquero
a partire dal Settecento
DNA Methylation in Nasal Epithelium: Strengths and Limitations of an Emergent Biomarker for Childhood Asthma.
No full textAsthma is one of the most widespread chronic respiratory conditions. This disease primarily develops in childhood and is influenced by different factors, mainly genetics and environmental factors. DNA methylation is an epigenetic mechanism which may represent a bridge between these two factors, providing a tool to comprehend the interaction between genetics and environment. Most epidemiological studies in this field have been conducted using blood samples, although DNA methylation marks in blood may not be reliable for drawing exhaustive conclusions about DNA methylation in the airways. Because of the role of nasal epithelium in asthma and the tissue specificity of DNA methylation, studying the relationship between DNA methylation and childhood asthma might reveal crucial information about this widespread respiratory disease. The purpose of this review is to describe current findings in this field of research. We will present a viewpoint of selected studies, consider strengths and limitations, and propose future research in this area
Defining the big social data paradigm through a systematic literature review approach
No full textPurpose: This study aims to investigate the Big Social Data (BSD) paradigm, which still lacks a clear and shared definition, and causes a lack of clarity and understanding about its beneficial opportunities for practitioners. In the knowledge management (KM) domain, a clear characterization of the BSD paradigm can lead to more effective and efficient KM strategies, processes and systems that leverage a huge amount of structured and unstructured data sources. Design/methodology/approach: The study adopts a systematic literature review (SLR) methodology based on a mixed analysis approach (unsupervised machine learning and human-based) applied to 199 research articles on BSD topics extracted from Scopus and Web of Science. In particular, machine learning processing has been implemented by using topic extraction and hierarchical clustering techniques. Findings: The paper provides a threefold contribution: a conceptualization and a consensual definition of the BSD paradigm through the identification of four key conceptual pillars (i.e. sources, properties, technology and value exploitation); a characterization of the taxonomy of BSD data type that extends previous works on this topic; a research agenda for future research studies on BSD and its applications along with a KM perspective. Research limitations/implications: The main limits of the research rely on the list of articles considered for the literature review that could be enlarged by considering further sources (in addition to Scopus and Web of Science) and/or further languages (in addition to English) and/or further years (the review considers papers published until 2018). Research implications concern the development of a research agenda organized along with five thematic issues, which can feed future research to deepen the paradigm of BSD and explore linkages with the KM field. Practical implications: Practical implications concern the usage of the proposed definition of BSD to purposefully design applications and services based on BSD in knowledge-intensive domains to generate value for citizens, individuals, companies and territories. Originality/value: The original contribution concerns the definition of the big data social paradigm built through an SLR the combines machine learning processing and human-based processing. Moreover, the research agenda deriving from the study contributes to investigate the BSD paradigm in the wider domain of KM
Digital Transformation: A Definition of Component (Canvas) and Process (Roadmap) View
No full textDigital transformation has gathered a significant interest within the research and industrial
communities, and has become an umbrella concept to address the multiple technology, strategic, human
resource and operations management dimensions involved into a digital-enabled organizational
renewal. Despite such increasing interest, a shared understanding of what is involved in digital
transformation and how a digital transformation initiative can be undertaken is still missing in the extant
literature. This article aims to contribute by identifying the multifaceted conceptual and applicative
dimensions of digital transformation, and to integrate the same into a single unifying framework. Based
on a design science approach and the review of large although fragmented literature, the article presents
a component-view or Digital Transformation Canvas and a process–view or Digital Transformation
Roadmap. The contribution is thus both in the academic and in the practitioner field
Integrating Large Language Models and Optimization in Semi- Structured Decision Making: Methodology and a Case Study
No full textSemi-structured decisions, which fall between highly structured and unstructured decision types, rely on human intuition and experience for the final choice, while using data and analytical models to generate tentative solutions. These processes are traditionally iterative and time-consuming, requiring cycles of data gathering, analysis, and option evaluation. In this study, we propose a novel framework that integrates Large Language Models (LLMs) with optimization techniques to streamline such decision-making processes. In our approach, LLMs leverage their capabilities in data interpretation, common-sense reasoning, and mathematical modeling to assist decision makers by reducing cognitive load. They achieve this by automating aspects of information processing and option evaluation, while preserving human oversight as a crucial component of the final decision-making process. Another significant strength of our framework lies in its potential to drive the evolution of a new generation of decision support systems (DSSs). Unlike traditional systems that rely on rigid and inflexible interfaces, our approach enables users to express their preferences in a more natural, intuitive, and adaptable manner, substantially enhancing both usability and accessibility. A case study on last-mile delivery system design in a smart city demonstrates the practical application of this framework. The results suggest that our approach has the potential to simplify the decision-making process and improve efficiency by reducing cognitive load, enhancing user experience, and facilitating more intuitive interactions
Assessing learners’ satisfaction in collaborative online courses through a big data approach
No full textMonitoring learners' satisfaction (LS) is a vital action for collecting precious information and design valuable online collaborative learning (CL) experiences. Today's CL platforms allow students for performing many online activities, thus generating a huge mass of data that can be processed to provide insights about the level of satisfaction on contents, services, community interactions, and effort. Big Data is a suitable paradigm for real-time processing of large data sets concerning the LS, in the final aim to provide valuable information that may improve the CL experience. Besides, the adoption of Big Data offers the opportunity to implement a non-intrusive and in-process evaluation strategy of online courses that complements the traditional and time-consuming ways to collect feedback (e.g. questionnaires or surveys). Although the application of Big Data in the CL domain is a recent explored research area with limited applications, it may have an important role in the future of online education. By adopting the design science research methodology, this article describes a novel method and approach to analyse individual students' contributions in online learning activities and assess the level of their satisfaction towards the course. A software artefact is also presented, which leverages Learning Analytics in a Big Data context, with the goal to provide in real-time valuable insights that people and systems can use to intervene properly in the program. The contribution of this paper can be of value for both researchers and practitioners: the former can be interested in the approach and method used for LS assessment; the latter can find of interest the system implemented and how it has been tested in a real online course
Strategic business value from big data analytics: An empirical analysis of the mediating effects of value creation mechanisms
No full textBig data are a prominent source of value capable of generating competitive advantage and superior business performance. This paper represents the first empirical investigation of the theoretical model proposed by Grover et al. (2018), considering the mediating effects of four value creation mechanisms on the relationship between big data analytics capabilities (BDAC) and four value targets. The four value creation mechanisms investigated (the source of the value being pursued) are transparency, access, discovery, and proactive adaptation, while the four value targets (the impacts of the value creation process) are organization performance, business process improvement, customer experience and market enhancement, and product and service innovation. The proposed empirical validation of Grover et al.'s (2018) model adopts an econometric analysis applied to data gathered through a survey involving 256 BDA experts. The results reveal that transparency mediates the relationship for all the value targets, while access and proactive adaptation mediate only in case of some value targets, and discovery does not have any mediating effect. Theoretical and practical implications are discussed at the end of the paper
Indagare il lessico federale nella Grecia antica. La Confederazione beotica: un caso di studio
No full textThe paper aims to investigate the Greek federal lexicon, by considering the Boeotian confederacy as a case study. Starting from the assumption that the London papyrus’ discovery of the Oxyrhynchia Hellenika, which contains a long description of the Boeotian constitution, marks a pivotal moment for the history of Greek federalism, the analysis will extend to the impact that the federal lexicon used by the Oxyrinchus historian had on later authors. It will be shown that, before the testimony of the Oxyrhynchia Hellenika, the only way to refer to the Boeotian confederacy of the classic age was by using the ethnikon. The employment of the federal lexicon (e.g. koinon, sympoliteia, ethnos, synteleia) by 5th century BC authors whatsoever implies the presence of a federal state in Boeotia, as those same terms knew numerous other contexts in the Greek language. Thanks to the Anonymous these terms are also repurposed to refer to the Boeotian confederacy of the classical period and this tendency was shared by some later authors to also define the further stages of the koinon
The contractual relationships in the Italian durum wheat chain: Empirical survey evidence
No full textThe paper investigates the vertical relations along the Italian durum wheat chain and the factors affecting farmers’ behavior in adopting contractual agreements. Sale/crop-growing contracts in the durum wheat sector are analyzed through a direct survey to a sample of 261 durum wheat farmers. The questionnaire collected data on downstream relations and contract terms between farmers and processing and/or marketing firms along the durum wheat chain. A logit model is used to identify factors affecting the likelihood of contract farming between farms and processors. One of the main issues emerging is the low frequency of written contractual forms between durum wheat farmers and downstream operators. In most cases the farmers do not want constraints and reveal a lack of trust in contracts. They prefer to sell their product to a local downstream operator with whom they have a long-standing and solid relationship of trust. Moreo-ver, results of a logistic model show that certain farm features, such as turnover and degree of specializa-tion in durum wheat production, play an important role in driving the decision to adopt written contracts
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