Wednesday, 10 April 2024 Two new projects at UP FAMNIt and UP IAM in March
EUROPEAN COMMISSION'S EU4Health PROGRAMMEEUROPEAN COMMISSION'S EU4Health PROGRAMME
Modular Mental Health Toolbox, partners, lead organization: European Alliance Against Depression (EAAD), UP IAM, UP lead: dr. Vita Poštuvan
The MentBox project aims to bridge the gap between existing good practice in the field of mental health and the capacity of EU Member States to implement it effectively. The project aims to identify and adapt promising mental health interventions, especially those focusing on depression, suicide and non-clinical mental disorders. Through the Modular Mental Health Toolbox (MH Toolbox), the project will provide detailed guidance for implementation, including evidence-based interventions from past and ongoing EU-funded projects. These interventions will be optimized in collaboration with ministries, health professionals, patients and minority groups and tailored to the different EU Member States. Patients and people with experience will also contribute to the development of the measures to ensure their relevance and acceptance. Following the project, the MHToolbox will be managed by the European Alliance for the Prevention of Depression (EAAD), which is coordinating the project with partners UP, Universidad Autonoma de Madrid, Servicio Andaluz de Salud, Fundación Pública Andaluza Investiga and the Global Alliance of Mental Illness Advocacy Networks AISBL.
ERC COMPLEMENTARY SCHEME (ARIS)
Beyond sparsity: graph classes and width parameters, lead partner UP FAMNIT, partner UP IAM, project leader: dr. Martin Milanič, partner leader: dr. Nina Chiarelli
Graph Sparsity Theory by Nešetřil and Ossona de Mendez is a very active and rapidly developing topic in combinatorics and graph theory, with applications in many areas such as algorithmic graph theory, complexity theory and property testing. A recent focus of structural and algorithmic graph theory is the extension of the theory of sparsity of graphs to dense graph classes. The proposed project aims to present new ways and methods to achieve this goal. This is done along the following two interrelated lines of research: first, by advancing the recently emerged and rapidly evolving theory of graph width and depth parameters through a general framework based on graph measures and an in-depth analysis of known and novel graph parameters; second, by developing a biparametric theory of hereditary graph classes in which one parameter is bounded by a function of another, with the aim of identifying nontrivial structural and algorithmic implications. Our approach complements the theory of graph classes with bounded flip-width recently developed by Toruńczyk and will lead to a better understanding of tractability bounds for the maximum independent set and several other practically relevant graph optimization problems.
