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Liquidity is critical for a healthy and thriving blockchain ecosystem, enabling value exchange between participants. However, achieving unified liquidity across heterogeneous blockchain platforms remains challenging due to disparities in architecture, virtual machines, and asset management logic. These disparities force assets to be wrapped into other formats to ensure compatibility with underlying systems, thus fragmenting liquidity into multiple pools. This paper proposes LiquiSpell, a novel protocol that aims to unify liquidity across multiple parachains within the Polkadot ecosystem. By leveraging the cross-chain message passing (XCMP), LiquiSpell introduces the concept of a universal transaction that can be constructed to be compatible with any parachain, regardless of its underlying architecture or asset management pallet. This approach overcomes the obstacles posed by the diverse nature of parachains, enabling seamless asset sharing and enhancing cross-chain interoperability. The proposed solution mitigates liquidity fragmentation within the Polkadot ecosystem. It presents a framework that can be extended to other multichain environments outside Polkadot. Ultimately, LiquiSpell aims to foster a thriving ecosystem by facilitating the introduction of new assets and increasing overall liquidity, thereby driving innovation and adoption within the decentralized finance (DeFi) landscape. [ABSTRACT FROM AUTHOR]

This work presents a private consortium blockchain-based automotive data monetization architecture implementation using the Substrate blockchain framework. Architecture is decentralized where crowd-sourced data from vehicles are collectively auctioned ensuring data privacy and security. Smart Contracts and OffChain worker interactions built along with the blockchain make it interoperable with external systems to send or receive data. The work is deployed in a Kubernetes cloud platform and evaluated on different parameters like throughput, hybrid consensus algorithms AuRa and BABE, along with GRANDPA performance in terms of forks and scalability for increasing node participants. The hybrid consensus algorithms are studied in depth to understand the difference and performance in the separation of block creation by AuRa and BABE followed by chain finalization through the GRANDPA protocol. [ABSTRACT FROM AUTHOR]

The growing complexity of construction supply chains and the significant impact of the construction industry on the environment demand an understanding of how to reuse and repurpose materials. In response to this critical challenge, research gaps that are significant in promoting material circularity are described. Despite its potential, the use of blockchain technology in construction faces challenges in verifiability, scalability, privacy, and interoperability. We propose a novel multilayer blockchain framework to enhance provenance tracking and data retrieval to enable a reliable audit trail. The framework utilises a privacy-centric solution that combines decentralised and centralised storage, security, and privacy. Furthermore, the framework implements access control to strengthen security and privacy, fostering transparency and information sharing among the stakeholders. These contributions collectively lead to trusted material circularity in a built environment. The implementation framework aims to create a prototype for blockchain applications in construction supply chains. [ABSTRACT FROM AUTHOR]

Thanks to the opportunities provided by developing technology, there had an increase in the transactions carried out using the internet. This development also led to an increase in data. This situation created the need for new technology for businesses to store, share, control, and manage data securely. One of the current technologies that can be used in this context is the blockchain structure. The blockchain structure is a technology that can be used in many areas, and the most popular usage area today is cryptocurrencies. In this study, it is aimed to estimate Polkadot cryptocurrency, which is one of the essential sub-cryptocurrencies. In the study, the data between 20.08.2020 and 27.02.2023 are used. According to these data, it aimed to estimate the daily average Polkadot value as the output value. Clusters for input values are created in two different ways. In the first input values; number of Polkadot YouTube search, number of Polkadot Google search, and Polkadot volume are used. Unlike the first input values, Ethereum, the leader of the alt cryptocurrencies, is added in the second input value. In this study, which consists of two different input structures, to estimate the daily average values of the Polkadot currency, an estimation study is carried out using multi-layered sensors in artificial neural networks and a long-shortterm memory structure, which is one of the deep learning methods. When the results are examined, it is determined that the values of 4 input sets in the obtained artificial neural networks gave better results with a correlation coefficient of 0.93. [ABSTRACT FROM AUTHOR]

The growing complexity of construction supply chains and the significant impact of the construction industry on the environment demand an understanding of how to reuse and repurpose materials. In response to this critical challenge, research gaps that are significant in promoting material circularity are described. Despite its potential, the use of blockchain technology in construction faces challenges in verifiability, scalability, privacy, and interoperability. We propose a novel multilayer blockchain framework to enhance provenance tracking and data retrieval to enable a reliable audit trail. The framework utilises a privacy-centric solution that combines decentralised and centralised storage, security, and privacy. Furthermore, the framework implements access control to strengthen security and privacy, fostering transparency and information sharing among the stakeholders. These contributions collectively lead to trusted material circularity in a built environment. The implementation framework aims to create a prototype for blockchain applications in construction supply chains.

This work presents a private consortium blockchain-based automotive data monetization architecture implementation using the Substrate blockchain framework. Architecture is decentralized where crowd-sourced data from vehicles are collectively auctioned ensuring data privacy and security. Smart Contracts and OffChain worker interactions built along with the blockchain make it interoperable with external systems to send or receive data. The work is deployed in a Kubernetes cloud platform and evaluated on different parameters like throughput, hybrid consensus algorithms AuRa and BABE, along with GRANDPA performance in terms of forks and scalability for increasing node participants. The hybrid consensus algorithms are studied in depth to understand the difference and performance in the separation of block creation by AuRa and BABE followed by chain finalization through the GRANDPA protocol.

Peer-to-Peer (P2P) electricity trading is an emerging means for allowing communities to share local energy production and demand response through direct trading. It is projected to play an important role in the future energy market by increasing the incentive to own and operate distributed energy resources (DERs) and participate in demand response (DR). A common approach to implementing P2P trading is with blockchain, however, existing solutions feature limitations. Typically, concerns involve either scalability and high transaction costs or projects implementing a permissioned blockchain that does not provide the trust and decentralization desired. In addition, the majority of market designs are simplified and do not capture the distinct complexity of electricity markets. They do not consider the inter-temporal constraints of appliances and DERs that need to run for multiple periods. Complex market designs that address these issues have not been implemented in blockchain based systems due to the computational limitations of such systems. To improve these two aspects, this paper proposes a market formulation that supports products running multiple periods with flexible scheduling, modeled as a mixed integer linear programming problem that optimizes social welfare. The trading platform is then implemented as a side chain of Polkadot, a network of blockchains designed to be secure, scalable, and economically feasible to foster an ecosystem of application-specific sidechains. This design is demonstrated to improve social welfare and achieve scalability by benchmarking the number of transactions that can be included per second, based upon typical assumptions of the market size. The result is a decentralized and performant system that allows for complex market designs to be implemented in a blockchain environment. This approach simplifies the process for participants, allowing them to bid DER or DR devices, directly and easily, even when this requires constraints across periods. • MILP optimization considering multi-period energy products and flexible scheduling. • Parachain of Polkadot blockchain for peer-to-peer energy trading. • Trust of a public blockchain but still has control over cost and throughput. • Demonstration of how off-chain market computation can be validated on blockchain. [ABSTRACT FROM AUTHOR]