and economic stakeholders - in order to enable the better development of the cities of the future. From this starting point, an in-depth literature review has been conducted within the H2020 U_CODE Urban Collective Design Environment Project. The project`s objective is to develop a co-design methodology and a participation platform for urban development, and to provide an overall procedural blueprint for all stakeholders including planners, citizens together, authorities and project initiators. Our research focuses on the level in the methods pyramid ( Fig. 1
The concept of spatial justice relates to the fair and equitable distribution in space of socially valued resources and opportunities. In other words, spatial justice is the spatial dimension of social justice, placing more emphasis on the geography of distribution. On this basis, this paper examines the innovation ecosystem of the Alexander Innovation Zone of Thessaloniki in Greece. What is attempted is to scrutinise, through the lens of spatial justice, this state's initiative to deal at the regional level with innovation. This paper investigates whether a focus on localities and decentralisation would be better able to deliver the demands of spatial justice. The hypothesis to be tested is that equity in socially valued resources and opportunities can be better achieved through place-based strategies. Based upon empirical material, within the framework of the RELOCAL project (H2020, www.relocal.eu), this contribution attempts to shed some light on the aforementioned research hypothesis.
In this article, we present a rationale for investigating the role and contributions of universities to growth and sustainable development within the framework of the Europe 2020 Strategy (EU2020). To this extent, the literature suggests that the contemporary universities’ mission in the knowledge society relies on their capacity to promote knowledge exchange. This allows expansion of the degree of intervention of universities in society and broadening of the institutional and policy frameworks within which they operate, opening to a wider range of possible contributions of social science and humanities to the EU2020 objectives, which are not limited to education and research policies.
We present the Short supply chain Knowledge and Innovation Network (SKIN) project (H2020-2016)1 as an example of a systemic approach to university-business-society dialogue, based on the role of universities as “knowledge hubs” (Yusuf, 2008) and aimed at promoting knowledge exchange and multi-actor cooperation. One of the main challenges of the project relies on the capacities of the involved actors to cooperate and, thus, on the mechanisms activated in order to ensure such collaboration. To this extent, the role of humanities and social sciences, in particular multidisciplinary and participatory research, is crucial for the success of the process of knowledge circulation within and for society.
Remote and automatic monitoring of two Apis Cerana bee colonies was conducted in Indonesia to demonstrate precision beekeeping approach in that region. Successful implementation of the precision beekeeping system includes development of the bee colony monitoring hardware and software for data collection, analysis and visualisation. This paper focuses on development and installation of such systems at the private apiary in Indonesia. For bee colony monitoring at the apiary a developed monitoring unit was used, which is based on ESP microchip, and for the data storage SAMS data warehouse was used. The monitoring results showed that the choice of the location of the temperature sensor is important, as the temperature at the hive sides changes synchronously with the outside temperature. Also, feedback from the beekeeper is collected to further improve the system and monitoring process. This research is conducted within the SAMS – Smart Apiculture Management Services project, which is funded by the European Union within the H2020-ICT-39-2016-2017 call and with close collaboration with the local private beekeeper. To find out more, visit the project website https://sams-project.eu/.
Currently, an integrated site-specific and patient-specific comprehensive predictive model of plaque progression in various CVD is not available. In this study, we considered medical records of 256 patients obtained within the EU H2020 SMARTool project which is carefully designed to collect the features from various domains relevant for disease which are used in everyday clinical practice. The database contains detailed information of patients with suspected CAD disease regarding the clinical status, risk factors, routine blood analyses, CAD morphology and progression and current therapy. Results showed that there was statistically significant difference of values of this parameter for the SMARTool patients with and without disease progression, measured at the follow-up, F(1,250)=33.39, p < 0.001, while the CAD Score in the follow-up is significantly different from the score measured at the initial time point, F(1,254)=76.244, p < 0.001. The significant interaction of statins is achieved with aspirin F(1,252)= 3.921, p=0.049, while interactions with other medicaments are insignificant for CAD Score. The results showed that there was no significant interaction of statins and dyslipidemia, F(1,251)=0.877, p = 0.350. Also, there was no significant interaction of statins and hypertension, F(1,245)=0.283, p=0.596. The CAD score in the baseline was significantly different among patients who were further prescribed with therapy than those who were not, and this trend remained unchanged after a given time period, i.e. those patients who were at risk had progression in addition to statins, but the combination of statins and aspirin was shown as effective in decreasing the CAD Score. The Random Forest classifier applied on 24 selected features is the most reliable among all tested ML algorithms for the prediction of CAD progress.
References 1. European Commission (2011) Roadmap to a Single European Transport Area – Towards a competitive and resource efficient transport system. White Paper. COM (2011) 144 final . European Commission. Brussels, Belgium. 2. Yatskiv, I., Savrasov M., Kabashkin, I., Nathanail, E., Adamos, G., Mitropoulos, L. (2017) Knowledge Sharing Strategy as a Key Element of the H2020 Programme: Enhancing Excellence and Innovation Capacity in Sustainable Transport Interchanges (Alliance) Project. Procedia Engineering . Vol. 187, pp. 458-464. doi.org/10.1016/j.proeng.2017
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