Over the last decade, blockchain technology has emerged to provide solutions to thecomplexity and privacy challenges of using distributed databases. It reduces cost for customers byeliminating intermediaries and builds trust in peer-to-peer communications. Over this time, theconcept of blockchain has shifted greatly due to its potential in business growth for enterprisesand the rapidly evolving applications in a collaborative smart-city ecosystem, healthcare, andgovernance. Many platforms, with different architectures and consensus protocols, have beenintroduced. Consequently, it becomes challenging for an application developer to choose the rightplatform. Furthermore, blockchain has misaligned with the goals for an efficient green collaborativedigital ecosystem. Therefore, it becomes critical to address this gap and to build new frameworks toalign blockchain with those goals. In this paper, we discuss the evolution of blockchain architectureand consensus protocols, bringing a retrospective analysis and discussing the rationale of theevolution of the various architectures and protocols, as well as capturing the assumptions conduciveto their development and contributions to building collaborative applications. We introduce aclassification of those architectures helping developers to choose a suitable platform for applicationsand providing insights for future research directions in the field to build new frameworks.

Diabetes is the leading cause of severe health complications and one of the top 10 causes of death worldwide. To date, diabetes has no cure, and therefore, it is necessary to take precautionary measures to avoid its occurrence. The main aim of this systematic review is to identify the majority of the risk factors for the incidence/prevalence of type 2 diabetes mellitus on one hand, and to give a critical analysis of the cohort/cross-sectional studies which examine the impact of the association of risk factors on diabetes. Consequently, we provide insights on risk factors whose interactions are major players in developing diabetes. We conclude with recommendations to allied health professionals, individuals and government institutions to support better diagnosis and prognosis of the disease.

Over the last decade the blockchain technology has emerged to provide solutions to the complexity and privacy challenges of using distributed databases. Its adoption is motivated by cost reduction for customers. Over this time, the concept of blockchain has shifted greatly due to its potential in business growth for enterprises and the rapidly evolving applications in a collaborative smart cities ecosystem, healthcare, and governance. Many platforms, with different architectures and consensus protocols, have been introduced. Consequently, it becomes challenging for an application developer to chose the right platform. Furthermore, blockchain has misaligned with the goals for efficient green collaborative digital ecosystem. Therefore, it becomes critical to address this gap and to build new frameworks to align blockchain with those goals. In this paper, we discuss the evolution of blockchain architecture and consensus protocols, bringing a retrospective analysis and discussing the rationale of the evolution of the various architectures and protocols, as well as capturing the assumptions conducting to their development and contributions to building collaborative applications. We introduce a classification of those architectures, helping developers to chose a suitable platform for applications and providing insights for future research directions in the field in building new frameworks. blockchain architecture and consensus protocol, it becomes more and more difficult to foresee the uses and applications of blockchain, therefore compounding the difficulty in achieving the goals. In 2017, the bitcoin mining used around 30.14 TerraWatt hours (TWh) of energy, which is equivalent to energy usage of the entire Ireland in a year [3]. According to a research, the annual carbon dioxide emissions by the bitcoin network are as high as 22.9 million metric tons, almost equivalent to the amount produced by the countries like Sri Lanka and Jordan [4].Further challenges have been placed on distributed applications by the expanding industrial market growth to serve a wide number of customers. Growing business requires trust and transparency between the customers and business providers. Customers require to eliminate intermediaries to reduce transactions cost. The issues of data communication overhead with increasing number of network participants further hinders the real-time services of the developed applications. Addressing these problems of energy consumption and scalability often trades off with security, and privacy. As such, the goals of this paper are four-fold: 1) we aim to provide a temporal evolution of blockchain applications development platforms architectures and consensus protocols with a retrospective analysis to their introduction. We classify the platforms and the consensus protocols under unifying architectures, and discuss various existing and upcoming blockchain applications, 2) help developers to choose the right platform architecture for applications, 3) we evaluate the current research on the topic, blockchai...

Healthcare data management has been gaining a lot of attention in recent years because of its high potential to provide more accurate and cost-efficient patient care. The traditional client-server and cloud-based healthcare data management systems suffer from the issues of single point of failure, data privacy, centralized data stewardship, and system vulnerability. The replication mechanism, and privacy and security features of blockchain have a promising future in the healthcare domain as they can solve some of the inherent issues of the health management system. However, most of the recent research works on blockchain in the healthcare domain have primarily focused on the permission-less Bitcoin network that suffers from drawbacks such as high energy consumption, limited scalability, and low transaction throughput. Consequently, there is a need for a scalable, fault-tolerant, secure, traceable and private blockchain to suit the requirements of the healthcare domain. We propose a lightweight blockchain architecture for the healthcare data management that reduces the computational and communication overhead compared to the Bitcoin network by dividing the network participants into clusters and maintaining one copy of the ledger per cluster. Our architecture introduces the use of canal, that allows secure and confidential transactions within a group of network participants. Furthermore, we propose a solution to avoid forking which is prevalent in the Bitcoin network. We demonstrate the effectiveness of our proposed architecture in providing security and privacy compared to the Bitcoin network by analyzing different threats and attacks. We also discuss how our proposed architecture addresses the identified threats. Our experimental results demonstrate that our proposed architecture generates 11 times lower network traffic compared to the Bitcoin network as the number of blocks increases. Our ledger update is 1.13 times faster. Our architecture shows a speedup of 67% in ledger update and 10 times lower network traffic when the number of nodes increases.

When will the coronavirus end? Are the current precautionary measures effective? To answer these questions it is important to forecast regularly and accurately the spread of COVID-19 infections. Different time series forecasting models have been applied in the literature to tackle the pandemic situation. The current research efforts developed few of these models and validates its accuracy for selected countries. It becomes difficult to draw an objective comparison between the performance of these models at a global scale. This is because, the time series trend for the infection differs between the countries depending on the strategies adopted by the healthcare organizations to decrease the spread. Consequently, it is important to develop a tailored model for a country that allows healthcare organizations to better judge the effect of the undertaken precautionary measures, and provision more efficiently the needed resources to face this disease. This paper addresses this void. We develop and compare the performance of the time series models in the literature in terms of root mean squared error and mean absolute percentage error.