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FREEWAT is an HORIZON 2020 project financed by the EU Commission under the call WATER INNOVATION: BOOSTING ITS VALUE FOR EUROPE. FREEWAT main result will be an open source and public domain GIS integrated modelling environment for the simulation of water quantity and quality in surface water and groundwater with an integrated water management and planning module. FREEWAT aims at promoting water resource management by simplifying the application of the Water Framework Directive and other EU water related Directives. Specific objectives of the FREEWAT project are: to coordinate previous EU and national funded research to integrate existing software modules for water management in a single environment into the GIS based FREEWAT; to support the FREEWAT application in an innovative participatory approach gathering technical staff and relevant stakeholders (in primis policy and decision makers) in designing scenarios for the proper application of water policies. The open source characteristics of the platform allow to consider this an initiative "ad includendum" (looking for inclusion of other entities), as further research institutions, private developers etc. may contribute to the platform development. Through creating a common environment among water research/professionals, policy makers and implementers, FREEWAT main impact will be on enhancing science-and participatory approach and evidence-based decision making in water resource management, hence producing relevant and appropriate outcomes for policy implementation. The Consortium is constituted by partners from various water sectors from 10 EU countries, plus Turkey and Ukraine. Synergies with the UNESCO HOPE initiative on free and open source software in water management greatly boost the value of the project. Large stakeholders involvement is thought to guarantee results dissemination and exploitation.

The tumour growth paradox refers to the observation that incomplete treatment of cancers can enhance their growth. As shown here and elsewhere, the existence of cancer stem cells (CSCs) can explain this effect. CSC are less sensitive to treatments, hence any stress applied to the tumour selects for CSC, thereby increasing the fitness of the tumour. In this paper, we use a mathematical model to understand the role of CSC in the progression of cancer. Our model is a rather general system of integro-differential equations for tumour growth and tumour spread. Such a model has never been analysed, and we prove results on local and global existence of solutions, their uniqueness and their boundedness. We show numerically that this model exhibits the tumour growth paradox for all parameters tested. This effect becomes more relevant for small renewal rate of the CSC.

SUMMARYWe present a rigorous mathematical treatment of a model describing rain water infiltration through the vadose zone in case of runoff of the excess water. The main feature of the mathematical problem emerging from the model lies on the boundary condition on the ground surface which is in the form of a unilateral constraint. Existence and uniqueness of a weak solution is proved under general assumptions. We present also the results of a numerical study comparing the proposed model with other models which approach in a different way the rain water infiltration problem.

Ambient Particulate Matter (PM) has been shown to be associated with cardiopulmonary diseases and lung cancer. Several groups of investigators have shown that the size of the airborne particles and their surface area determine the potential to elicit inflammatory injury and other mechanisms of adverse cellular effects. Because traffic is an important source of PM, it seems obvious that physicochemical characterization of vehicles exhaust emission has an important impact on both quantitative and qualitative aspects of ambient PM. In the present study the exhaust emissions of 8 vehicles of different categories were analyzed to attempt to differentiate them. For such purpose the particulate was collected on SPME fibers exposed to the exhaust emission for 150 s. The particulate was first characterized by micro-Raman spectroscopy and then subjected to Fast Gas Chromatography-Mass Spectrometry analyses for the chemical identification of the Polycyclic Aromatic Hydrocarbons (PAHs) compounds, the organic fraction of particulate matter in air pollution with a major role in the toxicity, notably via its effects on inflammation. Both the particle count and the PAHs compositional data were assembled to be interpreted by Principal Components Analysis. This multivariate analysis grouped the data according mainly to the naphthalene amount, as well as the volume concentration of the particles smaller than 0.5 μm, suggesting that the different exhaust emissions could be easily differentiated. With this new methodology, future research should aim at establishing a mechanism of formation during internal engine combustion processes in order to obtain a clearer picture of the inflammatory and carcinogenic mechanisms of PM in the lungs.