Data-Intensive Modelling and Simulation in Life Sciences and Socio-economical and Physical Sciences

First paragraph: This special issue of the journal Data Science and Engineering is a result of the work fostered by the ICT COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet), an EU-funded research network across 30+ European countries and overseas partners (http://chipset-cost.eu/).Output Type: Editoria

Citizens Vote to Act: smart contracts for the management of water resources in smart cities

Smart cities leverage Information and Communication Technologies (ICTs) to enhance the quality of urban services. However, it is nowadays clear that the success of a smart city largely depends on the level of engagement of its citizens. In this paper we explore to what extent disruptive blockchain technologies can be used to incentivise the democratic participation of citizen. The investigated approach extends the standard IoT cycle 1) sense data, 2) cloudify and elaborate them, and 3) push information to the users. Here, the user takes an active role by means of data-informed votes on policies, therefore influencing behaviours. We illustrate such an approach by means of a proof-of-concept decentralised application (dApp) supporting the negotiation of polices for the management of urban water resources. The dApp consists of a smart contract that manages the execution of other smart contracts (the policies) according to the data-driven choices of the community. This use case demonstrates how suitably blockchain technologies can support fair and safe access to data and user engagement in smart cities

Formal reasoning on qualitative models of coinfection of HIV and Tuberculosis and HAART therapy.

BACKGROUND: Several diseases, many of which nowadays pandemic, consist of multifactorial pathologies. Paradigmatic examples come from the immune response to pathogens, in which cases the effects of different infections combine together, yielding complex mutual feedback, often a positive one that boosts infection progression in a scenario that can easily become lethal. HIV is one such infection, which weakens the immune system favouring the insurgence of opportunistic infections, amongst which Tuberculosis (TB). The treatment with antiretroviral therapies has shown effective in reducing mortality. An in-depth understanding of complex systems, like the one consisting of HIV, TB and related therapies, is an open great challenge, on the boundaries of bioinformatics, computational and systems biology. RESULTS: We present a simplified formalisation of the highly dynamic system consisting of HIV, TB and related therapies, at the cellular level. The progression of the disease (AIDS) depends hence on interactions between viruses, cells, chemokines, the high mutation rate of viruses, the immune response of individuals and the interaction between drugs and infection dynamics. We first discuss a deterministic model of dual infection (HIV and TB) which is able to capture the long-term dynamics of CD4 T cells, viruses and Tumour Necrosis Factor (TNF). We contrast this model with a stochastic approach which captures intrinsic fluctuations of the biological processes. Furthermore, we also integrate automated reasoning techniques, i.e. probabilistic model checking, in our formal analysis. Beyond numerical simulations, model checking allows general properties (effectiveness of anti-HIV therapies) to be verified against the models by means of an automated procedure. Our work stresses the growing importance and flexibility of model checking techniques in bioinformatics. In this paper we i) describe HIV as a complex case of infectious diseases; ii) provide a number of different formal descriptions that suitably account for aspects of interests; iii) suggest that the integration of different models together with automated reasoning techniques can improve the understanding of infections and therapies through formal analysis methodologies. CONCLUSION: We argue that the described methodology suitably supports the study of viral infections in a formal, automated and expressive manner. We envisage a long-term contribution of this kind of approaches to clinical Bioinformatics and Translational Medicine.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Formal Synthetic Immunology

The human immune system fights pathogens using an articulated set of strategies whose function is to maintain in health the organism. A large effort to formally model such a complex system using a computational approach is currently underway, with the goal of developing a discipline for engineering "synthetic" immune responses. This requires the integration of a range of analysis techniques developed for formally reasoning about the behaviour of complex dynamical systems. Furthermore, a novel class of software tools has to be developed, capable of efficiently analysing these systems on widely accessible computing platforms, such as commodity multi-core architectures

Towards High-Performance Haplo- type Assembly for Future Sequencing

The problem of Haplotype Assembly is an essential step in human genome analysis. Being the well known MEC model for its solution NP-hard, it is currently addressed by using algorithms that grow exponentially with the length of DNA fragments obtained by the sequencing process. Technological improvements will reduce fragmentation, increase fragment length and make such computational costs worst. WHATSHAP is a recently proposed novel approach which moves complexity from fragment length to fragment sovrapposition, improving the perspective of computational costs, but Haplotype Assembly still remains a demanding computational problem. Directions towards high-performance computing Haplotype Assembly for future sequencing, based on parallel WHATSHAP, are discussed in this paper

A combined process algebraic, agent and fluid flow approach to emergent crowd behaviour

Emergent phenomena occur due to the pattern of non-linear and distributed local interactions between the elements of a system over time. Surprisingly, agent based crowd models in which the movement of each individual follows a limited set of simple rules often re-produce quite closely the emergent behaviour of crowds that can be observed in reality. An example of such phenomena is the spontaneous self-organisation of drinking parties in the squares of cities in Spain, also known as "El Botellon" [22]. We revisit this case study providing an elegant stochastic process algebraic model in Bio-PEPA amenable to several forms of analyses among which simulation and fluid flow analysis. We show that a fluid flow approximation, i.e. a deterministic reading of the average behaviour of the system, can provide an alternative and efficient way to study the same emergent behaviour as that explored in [22] where simulation was used instead. Besides empirical evidence also an analytical justification is provided for the good correspondence found between simulation results and the fluid flow approximation. Scalability features of the fluid flow approach may make it particularly useful when studying models of more complex city topologies with very large populations

A general framework for blockchain analytics

Modern cryptocurrencies exploit decentralised blockchains to record a public and unalterable history of transactions. Besides transactions, further information is stored for different, and often undisclosed, purposes, making the blockchains a rich and increasingly growing source of valuable information, in part of difficult interpretation. Many data analytics have been developed, mostly based on specifically designed and ad-hoc engineered approaches.We propose a general-purpose framework, seamlessly supporting data analytics on both Bitcoin and Ethereum — currently the two most prominent cryptocurrencies. Such a framework allows us to integrate relevant blockchain data with data from other sources, and to organise them in a database, either SQL or NoSQL. Our framework is released as an open-source Scala library. We illustrate the distinguishing features of our approach on a set of significant use cases, which allow us to empirically compare ours to other competing proposals, and evaluate the impact of the database choice on scalability

On the Educational Curriculum in Finance and Technology

Recent technological developments have enabled a wide array of new applications in financial markets, e.g. big data, cloud computing, artificial intelligence, blockchain, cryptocurrencies, peer-to-peer lending, crowdfunding, and robo-advising, inter alia. While traditionally comprising of computer programs and other technology used to support or enable banking and financial services, the new fintech sector is often seen as enabling transformation of the financial industry. A more moderate and critical view suggests that for the full transformative potential of fintech to be enabled, there is a need for an updated educational curriculum that balances knowledge and understanding of finance and technology. A curriculum that provides a skill portfolio in the two core components and complements them with applied knowledge can support the enabling forces which will render fintech as a true opportunity for the financial service industry and for society as a whole. We attempt a scholarship inquiry into the educational curriculum in finance and technology, aiming to inform this modern educational agenda. We review skills shortages, as identified by firms and experts, and examine the state-of-the art by some of the first educational programs in fintech