Towards an interoperability certification method for semantic federated experimental IoT testbeds

IoT deployments and then related experiments tend to be highly heterogeneous leading to fragmented and non-interoperable silo solutions. Yet there is a growing need to interconnect such experiments to create rich infrastructures that will underpin the next generation of cross sector IoT applications in particular as using massive number of data. While research have been carried out for IoT test beds and interoperability for some infrastructures less has been done on the data. In this paper, we present the first step of the FIESTA certification method for federated semantic IoT test bed, which provides stakeholders with the means of assessing the interoperability of a given IoT testbed and how it can be federated with other ones to create large facility for experimenter. Focus is given on data and semantic context of the test beds and how they can interoperate together for larger experiments with data

AJCD1105001

Abstract: Periodontitis is a bacterially-induced, localized chronic inflammatory disease destroying both the connective tissue and the supporting bone of the teeth. In the general population, severe forms of the disease demonstrate a prevalence of almost 5%, whereas initial epidemiological evidence suggests an association between periodontitis and coronary artery disease (CAD). Both the infectious nature of periodontitis and the yet etiologically unconfirmed infectious hypothesis of CAD, question their potential association. Ephemeral bacteremia, systemic inflammation and immune-pathological reactions constitute a triad of mechanisms supporting a cross-talk between periodontal and vascular damage. To which extent each of these periodontitis-mediated components contribute to vascular damage still remains uncertain. More than twenty years from the initial epidemiological association, the positive weight of evidence remains still alive but rather debated, because of both the presence of many uncontrolled confounding factors and the different assessment of periodontal disease. From the clinical point of view, advising periodontal prevention or treatment targeting on the prevention of CAD it is unjustified. By contrast, oral hygiene including periodontal health might contribute to the overall well-being and healthy lifestyle and hence as might at least partially contribute to cardiovascular prevention

Utility Metrics Specifications. OpenIoT Deliverable D422

This deliverable specifies the utility metrics that are considered and used in the scope of the OpenIoT project. These utility metrics are recorded as part of the implementation of the Utility Manager component of the OpenIoT platform, while they have also been used to drive the utility based optimization mechanisms of the project. In particular we provided the following contributions: We provide an analysis and summary of utility metrics for different data providers and environments, including physical sensors, sensor networks, and virtual sensors. These metrics can be used to measure utility for interconnected objects. We proposed utility functions that use metrics in order to compute valuation and cost functions. These functions can be used by utility-based optimization techniques. The utility based schemes proposed provide means and algorithms that can help selecting virtual sensors for efficient data collection. We describe utility metrics, tailored specifically for the OpenIoT use cases, indicating the relevant parameters (e.g. location, bandwidth, availability, privacy), and cost and valuation functions (if applicable)

Diminished social motivation in early psychosis is associated with polygenic liability for low vitamin D

Insufficiency of vitamin D levels often occur in individuals with schizophrenia and first-episode psychosis (FEP). However, it is unknown whether this represents a biological predisposition, or it is essentially driven by illness-related alterations in lifestyle habits. Lower vitamin D has also been associated with adverse neurodevelopmental outcomes and predominant negative psychotic symptoms. This study aimed to investigate the contribution of polygenic risk score for circulating 25-hydroxyvitamin D concentration (PRS-vitD) to symptom presentation among individuals with FEP enrolled in the Athens First-Episode Psychosis Research Study (AthensFEP n = 205) and the Psychosis Incident Cohort Outcome Study (PICOS n = 123). The severity of psychopathology was evaluated using the Positive and Negative Syndrome Scale at baseline and follow-up assessments (AthensFEP: 4-weeks follow-up, PICOS: 1-year follow-up). Premorbid intelligence and adjustment domains were also examined as proxy measures of neurodevelopmental deviations. An inverse association between PRS-vitD and severity of negative symptoms, in particular lack of social motivation, was detected in the AthensFEP at baseline (adjusted R2 = 0.04, p < 0.001) and follow-up (adjusted R2 = 0.03, p < 0.01). The above observation was independently validated in PICOS at follow-up (adjusted R2 = 0.06, p < 0.01). No evidence emerged for a relationship between PRS-vitD and premorbid measures of intelligence and adjustment, likely not supporting an impact of lower PRS-vitD on developmental trajectories related to psychotic illness. These findings suggest that polygenic vulnerability to reduced vitamin D impairs motivation and social interaction in individuals with FEP, thereby interventions that encourage outdoor activities and social engagement in this patient group might attenuate enduring negative symptoms

Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market

In this paper we examine the importance of mean reversion and spikes in the stochastic behaviour of the underlying asset when pricing options on power. We propose a model that is flexible in its formulation and captures the stylized features of power prices in a parsimonious way. The main feature of the model is that it incorporates two different speeds of mean reversion to capture the differences in price behaviour between normal and spiky periods. We derive semi-closed form solutions for European option prices using transform analysis and then examine the properties of the implied volatilities that the model generates. We find that the presence of jumps generates prominent volatility skews which depend on the sign of the mean jump size. We also show that mean reversion reduces the volatility smile as time to maturity increases. In addition, mean reversion induces volatility skews particularly for ITM options, even in the absence of jumps. Finally, jump size volatility and jump intensity mainly affect the kurtosis and thus the curvature of the smile with the former having a more important role in making the volatility smile more pronounced and thus increasing the kurtosis of the underlying price distribution

Cross-domain interoperability using federated interoperable semantic IoT/Cloud testbeds and applications: The FIESTA-IoT approach

This work is funded by the European Commission under the EU-H2020 Project Grant ”Federated Interoperable Semantic IoT/cloudTestbeds andApplications (FIESTA)” with the Grant Agreement No. CNECT-ICT-643943

Configurable Distributed Data Management for the Internet of the Things

One of the main challenges in modern Internet of Things (IoT) systems is the efficient collection, routing and management of data streams from heterogeneous sources, including sources with high ingestion rates. Despite the existence of various IoT data streaming frameworks, there is still no easy way for collecting and routing IoT streams in efficient and configurable ways that are easy to be implemented and deployed in realistic environments. In this paper, we introduce a programmable engine for Distributed Data Analytics (DDA), which eases the task of collecting IoT streams from different sources and accordingly, routing them to appropriate consumers. The engine provides also the means for preprocessing and analysis of data streams, which are two of the most important tasks in Big Data analytics applications. At the heart of the engine lies a Domain Specific Language (DSL) that enables the zero-programming definition of data routing and preprocessing tasks. This DSL is outlined in the paper, along with the middleware that supports its runtime execution. As part of the paper, we present the architecture of the engine, as well as the digital models that it uses for modelling data streams in the digital world. We also discuss the validation of the DDA in several data intensive IoT use cases in industrial environments, including use cases in pilot productions lines and in several real-life manufacturing environments. The latter manifest the configurability, programmability and flexibility of the DDA engine, as well as its ability to support practical applications

Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool

In this paper we propose a three-factor spike model that accounts for different speeds of mean reversion between normal and spiky shocks in the Scandinavian power market. In this model both short and long-run factors are unobservable and are hence estimated as latent variables using the Kalman filter. The proposed model has several advantages. First, it seems to capture in a parsimonious way the most important risks that practitioners face in the market, such as spike risk, short-term risk and long-term risk. Second, it explains the seasonal risk premium observed in the market and improves the fit between theoretical and observed forward prices, particularly for long-dated forward contracts. Finally, closed-form solutions for forward contracts, derived from the model, are consistent with the fact that the correlation between contracts of different maturities is imperfect. The resulting model is very promising, providing a very useful policy analysis and financial engineering tool to market participants for risk management and derivative pricing particularly for long-dated contracts.Electricity derivatives Kalman filter Affine jump diffusion models

Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market

In this paper we examine the importance of mean reversion and spikes in the stochastic behaviour of the underlying asset when pricing options on power. We propose a model that is flexible in its formulation and captures the stylized features of power prices in a parsimonious way. The main feature of the model is that it incorporates two different speeds of mean reversion to capture the differences in price behaviour between normal and spiky periods. We derive semi-closed form solutions for European option prices using transform analysis and then examine the properties of the implied volatilities that the model generates. We find that the presence of jumps generates prominent volatility skews which depend on the sign of the mean jump size. We also show that mean reversion reduces the volatility smile as time to maturity increases. In addition, mean reversion induces volatility skews particularly for ITM options, even in the absence of jumps. Finally, jump size volatility and jump intensity mainly affect the kurtosis and thus the curvature of the smile with the former having a more important role in making the volatility smile more pronounced and thus increasing the kurtosis of the underlying price distribution.Affine jump diffusion models Implied volatility Volatility skew Electricity derivatives Risk management