Shipping noise is one of the most common underwater sounds and a substantial component of ambient noise in the sea. Traveling vessels are sources of low-frequency acoustic waves which propagate efficiently through the water mass and thus affect underwater noise levels at large distances from the major shipping lanes. A prediction model for shipping noise in the Eastern Mediterranean Sea is currently being developed combining real-time ship data (AIS data) provided by the MarineTraffic ship tracking service, typical acoustic emission characteristics, environmental data and acoustic propagation codes. Taking into account prevailing temperature and sound-speed distributions, as well as the exact bathymetry in the area, range-dependent propagation calculations are carried out using a simple ray-theoretic approach combined with sound-speed smoothing to account for low-frequency effects, and the three dimensional distribution of sound intensity is estimated. Results for the distribution of noise level at various depths are presented on a geographical background (map) and periodically updated.

To locate an object in a cluttered visual scene we often rely on its features (e.g. shape, colour) to guide our search. The frontal eye fields (FEF) and the lateral intraparietal area (LIP) are considered to control spatial attention through the generation of saliency maps in which stimuli are represented according to their behavioural relevance. However, how neural populations in each area contribute to feature attention remains largely unknown.
We investigated the role of FEF and LIP in attention in two macaque monkeys engaged in a free-viewing visual search paradigm. Animals were instructed to find a target among stimuli that either shared the target’s colour/shape or had nothing in common with the target. To decode feature-attention related information from neural activity we applied a linear support vector machine (SVM) classifier and used standard cross-validation approaches to calculate classification accuracy.
Significant decoding accuracy of feature-attention parameters was obtained from population activity in both FEF and LIP. However, decoding accuracies were higher and reached significance earlier in the FEF compared to LIP, indicating that feature-based information about the behavioural relevance of the stimulus is processed first in the FEF. Furthermore, we found enhanced synchronisation between the two areas in the beta frequency range in the cue, delay and search period, whereas modest enhancements in gamma synchronisation were found during the search period. These results suggest frequency specific interactions between the two regions in different task epochs and provide further support for a role of both beta and gamma frequency synchronisation in long-range communication in the brain.

SEN4RUS project is a recently launched project funded by ERA.Net-RUS Plus. Its main objective is to account for the specific requirements of spatial and urban planning in Russia to develop urban planning indicators. SEN4RUS will effectively and efficiently exploit the information content provided by Sentinels mass data streams in support of city and regional planning. A Web-based Information System (WIS) will be developed to on-line evaluate these indicators and to provide them in a form that allows direct implementation into urban planning procedures.

The Mediterranean region is projected as one of the most fragile areas of the world, due to climatic and anthropogenic changes with decreasing trends in rainfall and snowfall and increasing warming trends. Many Mediterranean areas are currently experiencing high water stress induced by anthropogenic and climate drivers which have led to severe problems in the natural vegetation over the mountainous areas. The decreasing precipitation trends and the snow cover period shortening are expected to lead to land cover changes in mountainous areas. The objective of the present study is to examine the changes in natural vegetation of the National Park of Samaria in Crete, by analyzing Landsat time series for the period 1985 – 2015 using applied remote sensing techniques. MODIS Snow Cover and NDVI products for selected locations in the alpine zone have been analyzed in order to understand the drivers of vegetation changes and more specifically, the vegetation response to the snow cover period shortening. In addition, local ecological knowledge has been utilized in order to interpret findings prior the availability of MODIS data. The analysis of the Landsat data shows a stability on the land cover over the National Park. Coniferous forests are stable across the landscape, while the low/sparse vegetation in two areas of the alpine zone found to vary interannually, depending on snow melting. Low/sparse vegetation in lower altitudes shows a stability whereas a slight increase in the spatial extent of cultivation areas was evident.

The H2020-Space project URBANFLUXES (URBan ANthrpogenic heat FLUX from Earth observation Satellites) investigates the potential of Copernicus Sentinels to retrieve anthropogenic heat flux, as a key component of the Urban Energy Budget (UEB). URBANFLUXES advances the current knowledge of the impacts of UEB fluxes on urban heat island and consequently on energy consumption in cities. In URBANFLUXES, the anthropogenic heat flux (QF) is estimated as a residual of UEB. Therefore, the rest UEB components, namely, the net all-wave radiation, the net change in heat storage and the turbulent sensible and latent heat fluxes are independently estimated from Earth Observation (EO), whereas the advection term is included in the error of the anthropogenic heat flux estimation from the UEB closure. The Discrete Anisotropic Radiative Transfer (DART) model is employed to improve the estimation of the net all-wave radiation balance, whereas the Element Surface Temperature Method (ESTM), adjusted to satellite observations is used to improve the estimation the estimation of the net change in heat storage. Furthermore, the estimation of the turbulent sensible and latent heat fluxes is based on the Aerodynamic Resistance Method (ARM). Based on these outcomes, QF is estimated by regressing the sum of the turbulent heat fluxes versus the available energy. In-situ flux measurements are used to evaluate URBANFLUXES outcomes, whereas uncertainties are specified and analyzed. URBANFLUXES is expected to prepare the ground for further innovative exploitation of EO in scientific activities (climate variability studies at local and regional scales) and future and emerging applications (sustainable urban planning, mitigation technologies) to benefit climate change mitigation / adaptation.

The objective of the Thinknature Η2020 project is the development of a platform that supports the understanding and promotion of nature based solutions (NBS). The platform is a communication space for a variety of stakeholders to share experiences. In order to achieve more sustainable and resilient societies, nature based solutions are an important topic on the EU Research and Innovation policy agenda. Nature based solutions are living solution inspired and supported by nature that simultaneously provide environmental, social and economic benefits and help to build resilience. They are solution that bring more nature and natural features and processes into cities, landscapes and seascapes, through locally adapted, resource-efficient and systemic interventions.

Graphene is a single (2D) layer of carbon atoms forming a regular hexagonal pattern, extracted from graphite, with astonishing properties and impressive potential applications.

In Graphene Nanocomposites nanographene flakes are used as fillers in a matrix, where they enhance/modify the properties of the entire system.

Polymer/Graphene nanocomposites are studied through all-atom Molecular Dynamics simulations

The main goals of the current work are:
A. The Study of the Effect of a Polymer Matrix on Nanographene Properties.
B. The Study of the Effect of Nanographene flake on Polymer Properties.

Numerous supramolecular protein assemblies have been demonstrated to have either physiological or pathological activities. The observation of their physical and chemical properties constitutes the focus of many experimental and computational studies. A very common, but of particular interest peptide, is diphenylalanine (peptide, FF) which has many potential applications, both biological and technological, due to a large number of different nanostructures which it attains. The current work concerns a detailed study of the self-assembled structures of FF in two different solvents, an aqueous (H2O) and an organic (CH3OH) through atomistic Molecular Dynamics (MD) simulations and experiments.