The Interoperability of Things: Interoperable solutions as an enabler for IoT and Web 3.0

This paper presents an overview of the interoperability concepts along with the challenges for the IoT domain and the upcoming Web 3.0. We identify four levels of interoperability and the relevant solutions for accomplishing vertical and horizontal compatibility between the various layers of a modern IoT ecosystem, referred to as: technological, syntactic, semantic, and organizational interoperability. The goal is to achieve cross-domain interaction and facilitate the proper usage and management of the provided IoT services and applications. An interoperability framework is also proposed where the involved system components can cooperate and offer the seamless operation from the device to the backend framework. This by-design end-to-end interoperation enables the interplay of several complex service composition settings and the management of the system via patterns. The overall proposal is adopted by the EU funded project SEMIoTICS as an enabler towards the IoT and Web 3.0, even when products from different vendors are utilized

Agent-based autonomous systems and abstraction engines: Theory meets practice

We report on experiences in the development of hybrid autonomous systems where high-level decisions are made by a rational agent. This rational agent interacts with other sub-systems via an abstraction engine. We describe three systems we have developed using the EASS BDI agent programming language and framework which supports this architecture. As a result of these experiences we recommend changes to the theoretical operational semantics that underpins the EASS framework and present a fourth implementation using the new semantics

We are ready for faunistic surveys of bdelloid rotifers through DNA barcoding: the example of <i>Sphagnum</i> bogs of the Swiss Jura Mountains

The identification of biological diversity through DNA barcoding and metabarcoding of the organisms living in the field has the potential to revolutionise the way biological surveys and monitoring are performed. Yet, we still do not know if the current representativeness of the reference database of DNA sequence data is sufficient to allow such approaches. Here, we show that, at least for bdelloid rotifers (Metazoa; Rotifera; Bdelloidea) in Europe, current knowledge is ripe to perform such surveys. We show the results of an exercise performed on bdelloid rotifers in Sphagnum bogs of the Swiss Jura Mountain. The results of DNA-based identifications were rather consistent with the morphology-based identifications, and the few cases of mismatch could be used as a cautionary tale to avoid potential misinterpretations of results. The mismatches were due to cases of the closest match not being genetically very close, and to the occurrence of cryptic species.La identificación de la diversidad biológica a través de DNA barcoding y metabarcoding de los organismos en el medio ambiente tiene el potencial de revolucionar la forma en que se realizan los inventarios biológicos y el monitoreo. Sin embargo, todavía no se sabe si las bases de datos genéticos de referencia a disposición hoy en día son lo suficientemente representativas como para permitir tales enfoques. Aquí, mostramos que, al menos para los rotíferos bdelloideos (Metazoa; Rotifera; Bdelloidea) de Europa, el nivel de conocimiento es suficiente para realizar tales estudios. Mostramos los resultados de un ejercicio realizado sobre rotíferos bdelloideos en turberas de Sphagnum del Jura suizo. Los resultados de las identificaciones basadas en el ADN fueron bastante consistentes con las identificaciones basadas en la morfología, y los pocos casos de desajuste podrían utilizarse como una advertencia para evitar posibles interpretaciones erróneas de los resultados. Estos desajustes se debieron a que las secuencias más cercanas seguían alejadas de los organismos realmente encontrados y a la presencia de especies crípticas

Routes to sustainability in public food procurement: An investigation of different models in primary school catering

Increasingly, policymakers are setting ambitious goals for sustainability in public procurement, integrated across different pillars. Such ambitions are apparent in public catering services, where procurement models have been shifting towards greater localisation of supply chains and purchasing of more organically grown food. To date however, few studies have examined empirically what the impacts of different procurement models are across these multiple pillars of sustainability. This research aimed to fill the gap, by measuring and comparing the environmental, economic and nutritional outcomes of different models of school meals procurement. Case studies were undertaken of ten primary school meals services in five European countries, capturing different procurement model types. Results showed carbon emissions ranged from 0.95 kgs CO2e per meal in the lowest case to 2.41 kgs CO2e in the highest case, with adoption of low carbon food waste disposal methods and reduction of the amount of ruminant meat in the menus being the most important actions for lowering emissions. In terms of economic impact, local economic multiplier ratios ranged from 1.59 to 2.46, and although the level of local food sourcing contributed to these ratios, the effect was eclipsed, in some cases, by investment in local catering staff. Meanwhile, implementation of a robust standards regime and improving canteen environment and supervision were the most important actions for nutritional quality and intake. The paper discusses the implications of the findings for integrated, sustainable models of food procurement

Modelling the seasonal dynamics of Aedes albopictus populations using a spatio-temporal stacked machine learning model

Various modelling techniques are available to understand the temporal and spatial variations of the phenology of species. Scientists often rely on correlative models, which establish a statistical relationship between a response variable (such as species abundance or presence-absence) and a set of predominantly abiotic covariates. The choice of the modeling approach, i.e., the algorithm, is itself a significant source of variability, as different algorithms applied to the same dataset can yield disparate outcomes. This inter-model variability has led to the adoption of ensemble modelling techniques, among which stacked generalisation, which has recently demonstrated its capacity to produce robust results. Stacked ensemble modelling incorporates predictions from multiple base learners or models as inputs for a meta-learner. The meta-learner, in turn, assimilates these predictions and generates a final prediction by combining the information from all the base learners. In our study, we utilized a recently published dataset documenting egg abundance observations of Aedes albopictus collected using ovitraps. and a set of environmental predictors to forecast the weekly median number of mosquito eggs using a stacked machine learning model. This approach enabled us to (i) unearth the seasonal egg-laying dynamics of Ae. albopictus for 12 years; (ii) generate spatio-temporal explicit forecasts of mosquito egg abundance in regions not covered by conventional monitoring initiatives. Our work establishes a robust methodological foundation for forecasting the spatio-temporal abundance of Ae. albopictus, offering a flexible framework that can be tailored to meet specific public health needs related to this specie

VectAbundance: a spatio-temporal database of Aedes mosquitoes observations

Modelling approaches play a crucial role in supporting local public health agencies by estimating and forecasting vector abundance and seasonality. However, the reliability of these models is contingent on the availability of standardized, high-quality data. Addressing this need, our study focuses on collecting and harmonizing egg count observations of the mosquito&nbsp;Aedes albopictus, obtained through ovitraps in monitoring and surveillance efforts across Albania, France, Italy, and Switzerland from 2010 to 2022. We processed the raw observations to obtain a continuous time series of ovitraps observations allowing for an extensive geographical and temporal coverage of Ae. albopictus population dynamics. The resulting post-processed observations are stored in the open-access database VectAbundance.This initiative addresses the critical need for accessible, high-quality data, enhancing the reliability of modelling efforts and bolstering public health preparednes