La galassia Musisque Deoque: storia e prospettive

The resources in support of Latin scholars created under the scientific direction of Paolo Mastandrea are numerous; the undertaking of Musisque Deoque, which aims at equipping the entire corpus of ancient Latin poetry with “significant variants”, is the most emblematic effort, open to further developments. Looking at the general history of these projects, we try to trace the future path of the “Musisque Deoque galaxy” within Open Science.

Predicting Stages in Omnichannel Path to Purchase: A Deep Learning Model

The proliferation of omnichannel practices and emerging technologies opens up new opportunities for companies to collect voluminous data across multiple channels. This study examines whether leveraging omnichannel data can lead to, statistically and economically, significantly better predictions on consumers’ online path-to-purchase journeys, given the intrinsic fluidity in and heterogeneity brought forth by digital transformation of traditional marketing. Using an omnichannel data set that captures consumers’ online behavior in terms of their website browsing trajectories and their offline behavior in terms of physical location trajectories, we predict consumers’ future path-to-purchase journeys based on their historical omnichannel behaviors. Using a state-of-the-art deep-learning algorithm, we find that using omnichannel data can significantly improve our model’s predictive power. This enhanced predictive power benefits various heterogeneous online firms, regardless of their size, offline presence, mobile app availability, or whether they are selling single- or multi-category products. Using an illustrative example of targeted marketing, we further quantify the economic value of the improved predictive power and the value of data.

Machine Learning Cybersecurity Adoption in Small and Medium Enterprises in Developed Countries

In many developed countries, the usage of artificial intelligence (AI) and machine learning (ML) has become important in paving the future path in how data is managed and secured in the small and medium enterprises (SMEs) sector. SMEs in these developed countries have created their own cyber regimes around AI and ML. This knowledge is tested daily in how these countries’ SMEs run their businesses and identify threats and attacks, based on the support structure of the individual country. Based on recent changes to the UK General Data Protection Regulation (GDPR), Brexit, and ISO standards requirements, machine learning cybersecurity (MLCS) adoption in the UK SME market has become prevalent and a good example to lean on, amongst other developed nations. Whilst MLCS has been successfully applied in many applications, including network intrusion detection systems (NIDs) worldwide, there is still a gap in the rate of adoption of MLCS techniques for UK SMEs. Other developed countries such as Spain and Australia also fall into this category, and similarities and differences to MLCS adoptions are discussed. Applications of how MLCS is applied within these SME industries are also explored. The paper investigates, using quantitative and qualitative methods, the challenges to adopting MLCS in the SME ecosystem, and how operations are managed to promote business growth. Much like security guards and policing in the real world, the virtual world is now calling on MLCS techniques to be embedded like secret service covert operations to protect data being distributed by the millions into cyberspace. This paper will use existing global research from multiple disciplines to identify gaps and opportunities for UK SME small business cyber security. This paper will also highlight barriers and reasons for low adoption rates of MLCS in SMEs and compare success stories of larger companies implementing MLCS. The methodology uses structured quantitative and qualitative survey questionnaires, distributed across an extensive participation pool directed to the SMEs’ management and technical and non-technical professionals using stratify methods. Based on the analysis and findings, this study reveals that from the primary data obtained, SMEs have the appropriate cybersecurity packages in place but are not fully aware of their potential. Secondary data collection was run in parallel to better understand how these barriers and challenges emerged, and why the rate of adoption of MLCS was very low. The paper draws the conclusion that help through government policies and processes coupled together with collaboration could minimize cyber threats in combatting hackers and malicious actors in trying to stay ahead of the game. These aspirations can be reached by ensuring that those involved have been well trained and understand the importance of communication when applying appropriate safety processes and procedures. This paper also highlights important funding gaps that could help raise cyber security awareness in the form of grants, subsidies, and financial assistance through various public sector policies and training. Lastly, SMEs’ lack of understanding of risks and impacts of cybercrime could lead to conflicting messages between cross-company IT and cybersecurity rules. Trying to find the right balance between this risk and impact, versus productivity impact and costs, could lead to UK SMES getting over these hurdles in this cyberspace in the quest for promoting the usage of MLCS. UK and Wales governments can use the research conducted in this paper to inform and adapt their policies to help UK SMEs become more secure from cyber-attacks and compare them to other developed countries also on the same future path.

Valuation of carbon services produced by wild animals finances conservation

Filling the global biodiversity financing gap will require significant investments from financial markets, which demand credible valuations of ecosystem services and natural capital. However, current valuation approaches discourage investment in conservation because their results cannot be verified using market-determined prices. Here, we bridge the gap between finance and conservation by valuing only wild animals carbon services for which market prices exist. By projecting the future path of carbon service production using a spatially-explicit demographic model, we place a credible value on the carbon-capture services produced by African forest elephants. If elephants were protected, their services would be worth $35.9 billion (24.3-41.2) and store 377 MtC (318-388) across tropical Africa. Our methodology can also place lower bounds on the social cost of nature degradation. Poaching would result in $10-14 billion of lost carbon services. Our methodology enables the integration of animal services into global financial markets with major implications for conservation, local socio-economies, and conservation.

Applications of Operations Research in Human Resource Management

Operational HR encompasses the highly visible, day-to-day tactical operations required to keep a workforce running. This made us look for strategic approaches essential for most organisations. Be it defining the future path, determining the future plan, mission, vision, planning, objectives and goals of a particular organization. In a nutshell, we wanted to bring out the intricate relationship between HR and operational research especially considering the current dynamics of the external world. The unprecedented changes in HRM made us dig deeper on the importance of the role and applications of operations research to cope with these changes. Finally, we believed our research was complete when we presented real-world examples, and it was demonstrated to us that Operations Research approaches may assist firms in making good HR policy decisions at a low cost

The Ascent of Bitcoin: Bibliometric Analysis of Bitcoin Research

Bitcoin, as the first decentralized cryptocurrency, pioneers the cryptocurrency markets, both in terms of market capitalization and scientific interest. In this paper, we performed a comprehensive bibliometric study of the Bitcoin-related literature. Using the Scopus database, we created a sample that comprises 4495 documents written in the 2011–2020 period. Furthermore, we provided insights about dimensions such as the change in the number of publications over the course of years, the main research areas, types of published documents, most important platforms and sources of Bitcoin publications, highly cited studies, productive authors, author’s countries, and finally main funders of Bitcoin-related research. Lastly, our bibliometric study manifests the current state and future path of Bitcoin literature from distinct perspectives.

Good Regulation Reflects Words in Action

Given the impossibility of binary “yes” and “no” classical general legal rules to anticipate and address the future path of law, this paper imitates the adaptive human nature and frames future legal actions on it. Given this human trait, this paper presents some predispositions for substance and actions that are based on the systemic/cybernetic approach. The latter prioritises values, goals and their weights, with controllable thresholds that, based on feedback loops between events, facts, and intentions, activate different preestablished (legal) scenarios. The paper develops new responses to changed conditions (responsiveness, adaptability, agility and robustness); the first are needed in the law due to inevitability of dynamic changes to present some adaptive regulatory techniques, which could be implemented in practical systems. The paper concludes that such techniques can be used in the law used as sunset clauses, legal experiments, emergent strategies, negative scenarios, adaptable norms, Henry VII clauses, public opinion within collective intelligence and legal experiments. They all can address changed conditions in the environment.

The Ascent of Bitcoin: Bibliometric Analysis of Bitcoin Research

Blockchain is a path-breaking paradigm, and cryptocurrencies are one of the main application areas of Blockchain technology. Bitcoin leads the cryptocurrency markets, both in terms of market capitalization and in scientific interest. In this paper, we performed a comprehensive bibliometric study of the Bitcoin-related literature. Using the Scopus database, we created a sample that comprises 4495 documents written in the 2011–2020 period. Furthermore, we provided insights about dimensions such as the change in the number of publications over the course of years, the main research areas, types of published documents, most important platforms and sources of Bitcoin publications, highly cited studies, productive authors, author’s countries, and finally main funders of Bitcoin-related research. Lastly, our bibliometric study manifests the current state and future path of Bitcoin literature from distinct perspectives.