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              <text>Air pollution is a growing concern in urban environments as it can heavily impact public health, especially in relation to respiratory diseases. This has led to a need for real-time monitoring of pollution levels to quickly identify any significant deviations and inform authorities, allowing for necessary interventions. Here, we propose a dynamic monitoring system that uses Kalman filters and multivariate statistical methods to track pollution trends and seasonality. By analysing the residuals of the model with non- parametric methods, we can detect changes in pollution levels and predict future readings. This gives rise to the anticipation of dangerous pollutant levels, enabling us to forewarn authorities. The approach is demonstrated using data from Athens, focusing on key pollutants such as ozone (O3), nitrogen dioxide (NO2), nitrogen oxide (NO), carbon monoxide (CO) and sulphur dioxide (SO2).</text>
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              <text>Phlebotomine sandflies vector multiple disease-causing agents, such as Leishmania spp.  Leishmaniasis causes great disease burden especially in developing nations, remains a neglected tropical disease and is endemic in tropical regions and across the mediterranean basin. Although it is curable, treatment can be problematic and expensive. To improve vector and parasite surveillance, sandfly sensory ecology can be exploited to develop novel tools, such as the use of semiochemicals. This work is part of a multidisciplinary approach to combat sandfly vector borne diseases named CLIMOS. This study aims to test the semiochemicals with the highest potential in the lab under field conditions to assess whether they can influence sandfly catches. The absence of significant results indicate a lack of significant effect of the semiochemicals on sandfly catches compared to the control treatment; thus, the current formulation may not be beneficial for vector surveillance. However, differences in sandfly abundance between sampling sites suggest that environmental factors may play a crucial role in trap effectiveness. The study's limitations include time constraints and challenges related to mounting and identification protocols, highlighting the need for long-term studies and the application of molecular techniques. Future research should aim to identify reasons underlying the lack of significant effects of semiochemicals, and testing different doses to optimise their use further in enhanced traps.</text>
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                <text>The Development of a Sandfly Semiochemical Surveillance Trap: Field-testing in a Leishmania-Endemic Region (Murcia, Spain)</text>
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              <text>This project extends the framework of Leung and Turrini (AAMAS 2024) by introducing behavioural diversity into populations of reinforcement learning agents playing repeated Prisoner's Dilemma games with partner selection. Agents differ in their learning rate and exploration-exploitation balance, forming “curious” and “conservative” types. Simulations show that heterogeneity sustains long-term cooperation. These insights contribute to understanding how diversity influences collective learning dynamics in multi-agent systems.</text>
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