Context: The third generation of cryptocurrencies gathers cryptocurrencies that are as diverse as the market is big (e.g., Dogecoin or Litecoin). While Dogecoin is seen as a memecoin, the other gathers a very different category of investors. To our knowledge, no study has independently assessed the crypto community’s economical impact on these cryptocurrencies. Furthermore, various methodological possibilities exist to forecast cryptocurrency price—mainly coming from online communities.

Method: Our study has retrospectively studied (from 01/01/2015 to 03/11/2021)—using open access data—the association strength (using normalized mutual information) and the linear correlation (using Pearson’s correlation) between Twitter activity and cryptocurrency economical attributes. In addition, we have computed different models (ADF, ARIMA, and Interpretable MultiVvariable Long Short-Term Memory recurrent neural network) that forecast past price values and assessed their precision.

Findings and conclusions: While the average Dogecoin transaction value is impacted by tweets, tweets are impacted by Litecoin transactions number and average Litecoin transaction value. Tweet number is impacted by Dogecoin whale behavior, but no significant relationship was found between Litecoin whales and tweets. The forecasting error resulting from our ARIMA (0,0,0) models was 0.08% (with Litecoin) and 0.22% (with Dogecoin). Therefore, those are just the beginning of scientific findings that may lead to building a trading robot based on these results. However, in itself, this study is only for academic discussion, and conclusions need to be drawn by further research. The authors cannot be liable if any financial investment is made based on its conclusions.

The cost of treatment for rare diseases is notoriously high imposing threats to the global healthcare system. Existing market-based tools for orphan drugs are not designed to reduce drug prices and could be hampered by adverse selection. We propose an alternative insurance mechanism, Massive Group Insurance (MGI), which aims at reducing the prices of orphan drugs through offering separate Intellectual Property Right (IPR) Fees to the drug company from an MGI Agency, which will collect insurance premiums from each country on each orphan drug that the country wants all its citizens to enjoy access to. The premiums will be calculated so as to ensure that the drug company will collect a profit no smaller than what it enjoys under the traditional model. The plan uses the group insurance concept and will generate a significant increase in drug use. Blockchain technology is used to facilitate authentication and effective IPR payments and ensure data security and low administrative cost. This model can potentially be extended to other categories of expensive drugs and vaccines.

Programs on public blockchains often handle valuable assets, making them attractive targets for attack. At the same time, it is challenging to design correct blockchain applications. Checking code for potential vulnerabilities is a viable option to increase trust. Therefore, numerous methods and tools have been proposed with the intention to support developers and analysts in detecting code vulnerabilities. Moreover, publications keep emerging with different focus, scope, and quality, making it difficult to keep up with the field and to identify relevant trends. Thus, regular reviews are essential to keep pace with the varied developments in a structured manner. Regarding blockchain programs, Ethereum is the platform most widely used and best documented. Moreover, applications based on Ethereum are entrusted with billions of USD. Like on similar blockchains, they are subject to numerous attacks and losses due to vulnerabilities that exist at all levels of the ecosystem. Countermeasures are in great demand. In this work, we perform a systematic literature review (SLR) to assess the state of the art regarding automated vulnerability analysis of smart contracts on Ethereum with a focus on classifications of vulnerabilities, detection methods, security analysis tools, and benchmarks for the assessment of tools. Our initial search of the major on-line libraries yields more than 1,300 publications. For the review, we apply a clear strategy and protocol to assure consequent, comprehensive, and reproducible documentation and results. After collecting the initial results, cleaning up references, removing duplicates and applying the inclusion and exclusion criteria, we retain 303 publications that include 214 primary studies, 70 surveys and 19 SLRs. For quality appraisal, we assess their intrinsic quality (derived from the reputation of the publication venue) as well as their contextual quality (determined by rating predefined criteria). For about 200 publications with at least a medium score, we extract the vulnerabilities, methods, and tools addressed, among other data. In a second step, we synthesize and structure the data into a classification of both the smart contract weaknesses and the analysis methods. Furthermore, we give an overview of tools and benchmarks used to evaluate tools. Finally, we provide a detailed discussion.

In today’s scenario, it is essential for the healthcare sector to focus on balancing patient care records with information relevant to completeness, accessibility, and privacy concerns. Advancements in information technology and health infrastructure exponentially bolster transformative changes in the healthcare industry. Incorporation of blockchain along with distributed ledger technology (DLT) owes the potentiality to cater to the interoperability restraints in health IT systems and enables medical researchers, healthcare entities, and healthcare providers to share electronic health data in a secured and well-mannered system. In addition to these, such technologies also propose and offer latest models for health statistics exchange by making the records more secure and efficient. However, successful implementation of blockchain technology and DLT necessitates efficient infrastructure, connectivity, and other factors. Hence, there poses to be several challenges restraining the mainstream usage of blockchain technology in the healthcare sector. The article illustrates different generations of blockchain, issues in healthcare data, and network structures as well as the solutions offered by the sector to cater to such problems. In addition to these, the article also emphasizes on the different application areas of blockchain and DLT in healthcare infrastructure. This article further discusses latest trends and factors driving the need for the incorporation of blockchain and distributed ledger technology in the healthcare sector and the future scenario for the same.

In this paper, we present a methodology for quantifying the decentralization degree of a blockchain network. To accomplish this, we use two well-known graph models of Erdös-Rény and Barabási–Albert in order to study the blockchain network topology. We then quantify the decentralization degree using the clustering coefficient of our network models. We validate our approach through extensive simulations and analyze the decentralization degree with respect to network parameters such as the number of connections per node and the peer selection algorithm. Our results expose the trade-off between the average shortest path and the decentralization degree. Furthermore, we observe the impact of the average shortest path on the network speed and traffic overhead. Finally, we demonstrate that the presence of hub-like nodes such as relay gateways negatively impacts the decentralization degree of blockchain networks.

Credential Exchange Infrastructures based on open standards are emerging with work ongoing across many different jurisdictions, in several global standards bodies and industry associations, as well as at a national level. This article addresses the technology advances on this topic, particularly around identification mechanisms, through the Self-sovereign identity model. It also tackles necessary institutional processes and policy concerns relating to their implementation. Rooted in a sociohistorical culture and practice of inquiry, the goal of the article is to bring emerging digital identity systems within the grasp of a wider public as well as to contribute to mutual understanding across stakeholder groups (technical community, governments, international cooperation entities, civil society and academia) about what is at stake. This is expected to enhance their capacity to better navigate across the pitfalls of this transition period from paper to digital systems and the full adoption of the latter, with each of these stakeholders playing a part in enabling trust around digital identity infrastructure and transactions, both within related ecosystems and in the broader society. This article makes contributions around three axes. First axis is conceptual and analytical. The article outlines three conceptualized phases in the evolution of identity practices in history with the hypothesis that the availability of new record-creation methods invites changes in, and expansion of, the existing identification processes. This helps make a stronger case for why the Internet needs an identity capability. In addition, the article defines or elaborates on key concepts including identity, credential and trust. The second axis of the article is a case study on self-sovereign identity as instantiated by the Sovrin network. The case study presents the technology and its design with a view to enabling a non-technical public to understand what it is and how it works, while highlighting the fact that the technology still needs institutional processes to make it work as intended. The final axis of this article provides guidelines to policy actors potentially facing the need to enable large scale implementations of these emerging technologies, as they mature. Policy-makers approaching this material may want to read this section first and then return to the rest of the paper.

The Paris Agreement’s decentralized and bottom-up approach to climate action poses an enormous accounting challenge by substantially increasing the number of heterogeneous national, sub-national, and non-state actors. Current legacy climate accounting systems and mechanisms are insufficient to avoid information asymmetry and double-counting due to actor heterogeneity and fragmentation. This paper presents a nested climate accounting architecture that integrates several innovative digital technologies, such as Distributed Ledger Technology, Internet of Things, Machine Learning, and concepts such as nested accounting and decentralized identifiers to improve interoperability across accounting systems. Such an architecture can enhance capacity building and technology transfer to the Global South by creating innovation groups, increasing scalability of accounting solutions that can lead to leapfrogging into innovative systems designs, and improving inclusiveness.