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The application of Social and Emotional Learning (SEL) methodologies within classrooms has been widely adopted and examined, highlighting its positive impact on the academic, emotional, and social sectors at both the individual and classroom levels. Through this wide applicability, a need is identified to focus more on the development of SEL approaches that support the integration of the various parts of a SEL methodology (e.g., planning, implementation, monitoring and assessment). Such approaches should not underestimate the value of the SEL assessment. It is necessary to engage both the developers and the practitioners of SEL methodologies and provide tools to assist teachers to better interpret the collected data and results and plan targeted SEL activities. Motivated by such needs, we detail the EduCardia SEL methodology, which focuses on the provision of a set of guidelines and tools to assess and improve the social and emotional competencies of students in primary and secondary educational levels, taking advantage of Information and Communication Technologies (ICT). The EduCardia SEL methodology considers the integration of the various parts of a SEL methodological approach and supports continuous assessment processes while offering user-friendly interfaces to interpret the produced results. Evaluation results are provided based on the application of the EduCardia SEL methodology in K12 schools in Greece for a short period of time, considering three different age groups. The targeted competencies are shown to be improved, while teachers provide insights on the applicability and efficiency of the proposed approach.

Significant efforts have been allocated over the last thirty years towards the conceptualization and assessment of the Emotional Intelligence (EI) construct. However, there is limited work on examining the EI construct in a group level. Collective Emotional Intelligence (CEI) is introduced as the ability of a group to promote awareness and regulation of members’ and group’s emotions, improving their capacity to collaborate effectively and avoid or easily resolve conflicts. High CEI levels in a group positively affect the group’s performance. In this article, we provide a definition of collective EI constructs, based on the extension of the open-access EmoSocio EI model. EmoSocio is selected as a basis since it regards an EI model, enriched with sociometric indexes at an individual and group level. A set of new constructs are included in the model for representing abilities for emotions’ management in a group level along with indicators for revealing the group dynamics. EmoSociograms is also presented as an open-source psychometric tool to dynamically manage and assess the social and emotional competences of individuals and groups. Evaluation results regarding the validity and the reliability of the extended EmoSocio model are made available, based on the assessment of CEI constructs in in-person and online groups, formed under an educational and working context, as well as an online discussion forum.

The development of solutions to manage or mitigate climate change impacts is very challenging, given the complexity and dynamicity of the socio-environmental and socio-ecological systems that have to be modeled and analyzed, and the need to include qualitative variables that are not easily quantifiable. The existence of qualitative, interoperable and well-interlinked data is considered a requirement rather than a desire in order to support this objective, since scientists from different disciplines will have no option but to collaborate and co-design solutions, overcoming barriers related to the semantic misalignment of the plethora of available data, the existence of multiple data silos that cannot be easily and jointly processed, and the lack of data quality in many of the produced datasets. In the current work, we present the SustainGraph, as a Knowledge Graph that is developed to track information related to the progress towards the achievement of targets defined in the United Nations Sustainable Development Goals (SDGs) at national and regional levels. The SustainGraph aims to act as a unified source of knowledge around information related to the SDGs, by taking advantage of the power provided by the development of graph databases and the exploitation of Machine Learning (ML) techniques for data population, knowledge production and analysis. The main concepts represented in the SustainGraph are detailed, while indicative usage scenarios are provided. A set of opportunities to take advantage of the SustainGraph and open research areas are identified and presented.

The competitive dynamics of mitochondrial haplotypes juxtaposed within the same cell are poorly studied. Here the authors show, in the context of a transmissible cancer, that one haplotype has recurrently entered cancer cells by horizontal transfer and appears to have a ‘selfish’ selective advantage.

Significant efforts have been allocated over the last thirty years towards the definition and measurement of the Emotional Intelligence (EI) construct. Several EI theories and models have been produced to support psychological assessment processes. However, barriers are identified for their wide adoption and exploitation by social scientists. The absence of a common structured format to represent concepts in EI models has resulted in lack of clarity and consistency, while hindering comparison, validation and extensive evaluation processes. Provision of open access to such models and measurement instruments has not been promoted so far, however, considered crucial for their wide adoption. Furthermore, the inclusion of indexes from the sociometry domain can facilitate participatory modeling by multidisciplinary scientists during the development of social and emotional training programs. To address these challenges, we propose EmoSocio, an open access Emotional Intelligence Model, built upon a detailed comparison and synthesis of the main constructs represented in widely accepted EI models and enriched with sociometric indexes at an individual and group level. Upon detailing the methodological approach followed for the development of the EmoSocio model, we present the EI and social constructs of the model, followed by an assessment of the EI part in terms of reliability and validity. EmoSocio is also represented in a semantically-enriched format in the form of an ontology. Our ambition is to provide an open access EI model that can be used by multidisciplinary scientists to evaluate psychological assessment processes and develop interventions, aiming to strengthen interpersonal and intrapersonal competencies.

Nowadays, various frameworks are emerging for supporting distributed tracing techniques over microservices-based distributed applications. The objective is to improve observability and management of operational problems of distributed applications, considering bottlenecks in terms of high latencies in the interaction among the deployed microservices. However, such frameworks provide information that is disjoint from the management information that is usually collected by cloud computing orchestration platforms. There is a need to improve observability by combining such information to easily produce insights related to performance issues and to realize root cause analyses to tackle them. In this paper, we provide a modern observability approach and pilot implementation for tackling data fusion aspects in edge and cloud computing orchestration platforms. We consider the integration of signals made available by various open-source monitoring and observability frameworks, including metrics, logs and distributed tracing mechanisms. The approach is validated in an experimental orchestration environment based on the deployment and stress testing of a proof-of-concept microservices-based application. Helpful results are produced regarding the identification of the main causes of latencies in the various application parts and the better understanding of the behavior of the application under different stressing conditions.

The design of solutions that are able to exploit the available data collected in smart cities environments can lead to insights that can guide the implementation of approaches that have the potential to significantly improve the quality of life within a city. Such solutions include tools for the production of advanced analytics considering data fusion challenges. The preparation of qualitative input data sets, collected in many cases through heterogeneous sources and represented in various formats, constitute a very important step toward a meaningful analysis. Such input data sets, combined with approaches that reduce the data processing burden and support the easy and flexible-in terms of configuration-replication of an analysis, can lead to the next generation analytics tools. In this paper, a novel approach toward the production and consumption of linked data analytics in urban environments is presented. The approach is based on the exploitation of linked data principles, enhancing the ability of managing and processing of data, in ways not available before. In addition to the description of the overall technical approach, the application of the proposed solution into a real-life scenario for examining the health impact of outdoor air pollution in urban areas within an international, national, and regional perspective is detailed. A set of interesting results are produced along with their interpretation toward the provision of suggestions for policy making purposes.

5G is considered to be the technology that will accommodate the development and management of innovative services with stringent and diverse requirements from end users, calling for new business models from the industry. In this context, the development and efficient management of Network Services (NS) serving specific vertical industries and spanning across multiple administrative domains and heterogeneous infrastructures is challenging. The main challenges regard the efficient provision of NSs considering the Quality of Service (QoS) requirements per vertical industry along with the optimal usage of the allocated resources. Towards addressing these challenges, this paper details an innovative approach that we have developed for managing and orchestrating such NSs, called SONATA, and compare it with OSM and Cloudify, which are two of the most known open-source Management and Orchestration (MANO) frameworks. In addition to examining the supported orchestration mechanisms per MANO framework, an evaluation of main operational and functional KPIs is provided based on experimentation using a real testbed. The final aim is the identification of their strong and weak points, and the assessment of their suitability for serving diverse vertical industry needs, including of course the Internet of Things (IoT) service ecosystem.

Canine transmissible venereal tumour (CTVT) is a clonally transmissible cancer that originated approximately 11,000 years ago and affects dogs worldwide. Despite the clonal origin of the CTVT nuclear genome, CTVT mitochondrial genomes (mtDNAs) have been acquired by periodic capture from transient hosts. We sequenced 449 complete mtDNAs from a global population of CTVTs, and show that mtDNA horizontal transfer has occurred at least five times, delineating five tumour clades whose distributions track two millennia of dog global migration. Negative selection has operated to prevent accumulation of deleterious mutations in captured mtDNA, and recombination has caused occasional mtDNA re-assortment. These findings implicate functional mtDNA as a driver of CTVT global metastatic spread, further highlighting the important role of mtDNA in cancer evolution.

Sociometric-oriented approaches have been applied the last years in numerous cases and domains, targeting at the improvement of social groups’ characteristics for achieving personal and team-based objectives. Considering the existing approaches and the published results, in the current study, a set of emotional intervention activities based on a sociometric-oriented approach were designed and implemented with the clear objective to augment social cohesion within members of a social group in primary school students. Petrides’ trait emotional model was used to identify the emotional profile of the experimental and control group members, while the set of implemented activities was based on Bisquerra’s emotional competencies model. Sociometrics were used to evaluate the initial, intermediate and final level of social cohesion of both groups. Based on the realized statistical analysis and the produced evaluation results, useful insights with regards to the social group indicators that mainly affect the social cohesion levels are extracted and presented. It should be noted that the detailed study was based on the exclusive usage of open-source Information and Communication Technologies (ICT) tools for supporting educational needs.

Considering that the largest part of end-use energy consumption worldwide is associated with the buildings sector, there is an inherent need for the conceptualization, specification, implementation, and instantiation of novel solutions in smart buildings, able to achieve significant reductions in energy consumption through the adoption of energy efficient techniques and the active engagement of the occupants. Towards the design of such solutions, the identification of the main energy consuming factors, trends, and patterns, along with the appropriate modeling and understanding of the occupants’ behavior and the potential for the adoption of environmentally-friendly lifestyle changes have to be realized. In the current article, an innovative energy-aware information technology (IT) ecosystem is presented, aiming to support the design and development of novel personalized energy management and awareness services that can lead to occupants’ behavioral change towards actions that can have a positive impact on energy efficiency. Novel information and communication technologies (ICT) are exploited towards this direction, related mainly to the evolution of the Internet of Things (IoT), data modeling, management and fusion, big data analytics, and personalized recommendation mechanisms. The combination of such technologies has resulted in an open and extensible architectural approach able to exploit in a homogeneous, efficient and scalable way the vast amount of energy, environmental, and behavioral data collected in energy efficiency campaigns and lead to the design of energy management and awareness services targeted to the occupants’ lifestyles. The overall layered architectural approach is detailed, including design and instantiation aspects based on the selection of set of available technologies and tools. Initial results from the usage of the proposed energy aware IT ecosystem in a pilot site at the University of Murcia are presented along with a set of identified open issues for future research.