EDALoCo: Enhancing the accessibility of blockchains through a low-code approach to the development of event-driven applications for smart contract management

Blockchain is a cutting-edge technology based on a distributed, secure and immutable ledger that facilitates the registration of transactions and the traceability of tangible and intangible assets without requiring central governance. The agreements between the nodes participating in a blockchain network are defined through smart contracts. However, the compilation, deployment, interaction and monitoring of these smart contracts is a barrier compromising the accessibility of blockchains by non-expert developers. To address this challenge, in this paper, we propose a low-code approach, called EDALoCo, that facilitates the development of event-driven applications for smart contract management. These applications make blockchain more accessible for software developers who are non-experts in this technology as these can be modeled through graphical flows, which specify the communications between data producers, data processors and data consumers. Specifically, we have enhanced the open-source Node-RED low-code platform with blockchain technology, giving support for the creation of user-friendly and lightweight event-driven applications that can compile and deploy smart contracts in a particular blockchain. Additionally, this platform extension allows users to interact with and monitor the smart contracts already deployed in a blockchain network, hiding the implementation details from non-experts in blockchain. This approach was successfully applied to a case study of COVID-19 vaccines to monitor and obtain the temperatures to which these vaccines are continuously exposed, to process them and then to store them in a blockchain network with the aim of making them immutable and traceable to any user. As a conclusion, our approach enables the integration of blockchain with the low-code paradigm, simplifying the development of lightweight event-driven applications for smart contract management. The approach comprises a novel open-source solution that makes data security, immutability and traceability more accessible to software developers who are non-blockchain experts

CEPchain: A graphical model-driven solution for integrating complex event processing and blockchain

Blockchain provides an immutable distributed ledger for storing transactions. One of the challenges of blockchain is the particular processing of dynamic queries due to accumulating costs. Complex Event Processing (CEP) provides efficient and effective support for this in a way, however, that is difficult to integrate with blockchain. This paper addresses the research challenges of integrating blockchain with CEP. More specifically, we envision an effective development environment in which (i) event-driven smart contracts are modeled in a graphical way, which are, in turn, (ii) automatically transformed into complementary code that is deployed in both a CEP engine and a blockchain network, and then (iii) executed on off-chain CEP applications which, connected to different data sources and sinks, automatically invoke smart contracts when event pattern conditions are met. We follow a classic systems engineering approach for defining the concepts of our system, called CEPchain, which addresses the described requirements. CEPchain was evaluated using a real-world case study for vaccine delivery, which requires an unbroken cold chain. The results demonstrate that our approach can be applied without requiring experts on event processing and smart contract languages. Our contribution simplifies the design of integrated CEP and blockchain functionality by hiding implementation details and supporting efficient deployment.This work was supported by the Spanish Ministry of Science and Innovation under the ‘‘Estancias de movilidad en el extranjero José Castillejo para jóvenes doctores’’ program [grant number CAS19/00241], and the Spanish Ministry of Science and Innovation and the European Regional Development Funds under project FAME [grant number RTI2018-093608-B-C33]. The authors would like to thank Orlenys López-Pintado for his help with the Caterpillar tool and his insightful comments. Juan Boubeta-Puig would also like to thank the Institute for Information Business for their hospitality when visiting them at the Vienna University of Economics and Business, Austria, where part of this work was developed

Mode Driven Engineering for Complex Event Processing: A Survey

Complex Event Processing (CEP) is a powerful technology for analyzing and correlating large amounts of data coming from different application domains to automatically detect situations of interest (event patterns) in real time. However, extensive knowledge on CEP is required to be able to implement CEP applications. To alleviate this situation, in recent years, several works have proposed the use of Model-Driven Engineering (MDE) to facilitate the development of such CEP applications for domain experts. In this paper, we propose a systematic literature review of existing approaches, frameworks, systems and languages that integrate MDE with CEP, along with the application domains and maturity levels with which these proposals have been successfully adopted. Based on our findings, future research challenges in the CEP field are also discussed

CEPEDALoCo: An event-driven architecture for integrating complex event processing and blockchain through low-code

Internet of Things (IoT) is made up of millions of devices generating large amounts of heterogeneous data from multiple sources. These devices can be from multiple manufacturers which makes their use in terms of data acquisition, processing, analysis and actions on these data challenging. Additionally, all these data must be analyzed and correlated in real time for the early detection of situations of interest (complex events) and subsequent decision making. These complex events must be able to automatically trigger decisions and be stored in a secure, immutable and accessible way. In this context, Event-Driven Applications (EDAs) are a solution to meet these needs, however, developing such applications requires vast knowledge in certain technologies. To address these challenges, an EDA is proposed in this paper to integrate Complex Event Processing (CEP) and blockchain through the low-code paradigm. This proposal allows for the development of EDAs in a user-friendly way. These applications make it possible to integrate IoT devices from multiple manufacturers and with different data formats together with CEP technology for complex event detection and blockchain for secure, immutable and accessible event storage. To demonstrate the feasibility, the architecture was applied and evaluated in a case study related to measuring and acting on air quality using IoT devices that measure different pollutants and factors such as temperature, humidity and wind. The results show that the graphically designed EDAs facilitate the real-time analysis of the collected IoT data via a CEP engine, whose outcome is transparently and automatically registered in a blockchain network.This work was partly supported by grant PID2021-122215NB-C33 (AwESOMe) funded by MCIN/AEI/10.13039/501100011033/ and ERDF “A way to do Europe”, by grant P20_00865 (DECISION) funded by the Andalusian Plan for Research, Development and Innovation and ERDF , and by grant EST2023-011 funded by the Research Plan from the University of Cadiz 2022–2023, Spain . We would like to thank Javier Berrocal for recommending the purchase of Netatmo sensors. Jesús Rosa-Bilbao would also like to thank the Department of Computer Science, Electrical Engineering and Mathematical Sciences for their hospitality when visiting them at Western Norway University of Applied Sciences, Bergen, Norway, where part of this work was developed

Empatía, role-taking y concepto de ser humano como factores asociados a la conducta pro-social - altruista

The predictor value of empathy, the ability to see things from the others� viewpoint, and the concept of humankind on altruistic prosocial behaviour were studied. The sample were 224 10-12 yr. old boys and girls from three different cities (Salamanca, Málaga and San Sebastián). Results show that the factors studied have a high predictor value.Se trata de un estudio realizado con 224 sujetos, de ambos sexos entre 10 y 12 años de tres ciudades distintas (Salamanca, Málaga y Donostia). En él se estudia el poder predictor de la empatía, la capacidad de ponerse en el punto de vista de los demás y el concepto de hombre sobre la conducta prosocial altruista. Los resultados demuestran un alto poder predictor de estos factores

The cognitive and psychiatric subacute impairment in severe Covid-19.

Neurologic impairment persisting months after acute severe SARS-CoV-2 infection has been described because of several pathogenic mechanisms, including persistent systemic inflammation. The objective of this study is to analyze the selective involvement of the different cognitive domains and the existence of related biomarkers. Cross-sectional multicentric study of patients who survived severe infection with SARS-CoV-2 consecutively recruited between 90 and 120 days after hospital discharge. All patients underwent an exhaustive study of cognitive functions as well as plasma determination of pro-inflammatory, neurotrophic factors and light-chain neurofilaments. A principal component analysis extracted the main independent characteristics of the syndrome. 152 patients were recruited. The results of our study preferential involvement of episodic and working memory, executive functions, and attention and relatively less affectation of other cortical functions. In addition, anxiety and depression pictures are constant in our cohort. Several plasma chemokines concentrations were elevated compared with both, a non-SARS-Cov2 infected cohort of neurological outpatients or a control healthy general population. Severe Covid-19 patients can develop an amnesic and dysexecutive syndrome with neuropsychiatric manifestations. We do not know if the deficits detected can persist in the long term and if this can trigger or accelerate the onset of neurodegenerative diseases

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies

International audienceSignificance There is growing evidence that preexisting autoantibodies neutralizing type I interferons (IFNs) are strong determinants of life-threatening COVID-19 pneumonia. It is important to estimate their quantitative impact on COVID-19 mortality upon SARS-CoV-2 infection, by age and sex, as both the prevalence of these autoantibodies and the risk of COVID-19 death increase with age and are higher in men. Using an unvaccinated sample of 1,261 deceased patients and 34,159 individuals from the general population, we found that autoantibodies against type I IFNs strongly increased the SARS-CoV-2 infection fatality rate at all ages, in both men and women. Autoantibodies against type I IFNs are strong and common predictors of life-threatening COVID-19. Testing for these autoantibodies should be considered in the general population

The risk of COVID-19 death is much greater and age dependent with type I IFN autoantibodies

International audienceSignificance There is growing evidence that preexisting autoantibodies neutralizing type I interferons (IFNs) are strong determinants of life-threatening COVID-19 pneumonia. It is important to estimate their quantitative impact on COVID-19 mortality upon SARS-CoV-2 infection, by age and sex, as both the prevalence of these autoantibodies and the risk of COVID-19 death increase with age and are higher in men. Using an unvaccinated sample of 1,261 deceased patients and 34,159 individuals from the general population, we found that autoantibodies against type I IFNs strongly increased the SARS-CoV-2 infection fatality rate at all ages, in both men and women. Autoantibodies against type I IFNs are strong and common predictors of life-threatening COVID-19. Testing for these autoantibodies should be considered in the general population

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

BackgroundWe previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in similar to 80% of cases.MethodsWe report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded.ResultsNo gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5-528.7, P=1.1x10(-4)) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70[95%CI 1.3-8.2], P=2.1x10(-4)). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR=19.65[95%CI 2.1-2635.4], P=3.4x10(-3)), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR=4.40[9%CI 2.3-8.4], P=7.7x10(-8)). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years; P=1.68x10(-5)).ConclusionsRare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old