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Achieving ambitious targets for energy efficiency, increasing the share of renewable energy and accelerating the transition to a climate-neutral society faces a number of technical, environmental and social barriers. Challenges include the difficulty of siting energy facilities, balancing public benefits, bottlenecks in energy infrastructure, fluctuations in the energy market and …

This dissertation examines the ecological dynamics of phytoplankton communities in the northern Adriatic Sea, focusing on phenology, environmental drivers, and trophodynamics. The complexity of the region, characterized by the richness of phytoplankton communities, environmental variability and intensive human activities, is not seen as an obstacle but as an opportunity to …

This thesis investigates two distinct but related optimization problems: bilevel and minmax problems, in the context of evolutionary algorithms (EAs). Bilevel optimization involves hierarchical decision-making, where decisions at the upper level are subject to constraints defined by the solutions of an optimization problem at the lower level. These problems are …

As ecological, agricultural, and biological disciplines face mounting challenges like biodiversity loss, food chain disruption, and climate change, leveraging machine learning (ML) to process complex and heterogeneous data becomes increasingly vital. This dissertation explores the potential of ML in combination with explainability approaches for enhancing research in life sciences, specifically …

Automatic terminology extraction, also known as automatic term extraction (ATE), is a natural language processing (NLP) task that identifies specialized terminology from domain-specific corpora. ATE is often used for terminographic tasks (e.g., the creation of specialized dictionaries) and contributes to several complex downstream tasks (e.g., machine translation and information retrieval). …

The rapid evolution of sensor technologies, particularly within the Internet of Things (IoT) domain, has led to an era dominated by massive real-time data flows. This transition resulted in the need for novel data processing methodologies that facilitate the shift from traditional offline batch analytics to agile real-time predictions and …

News spreads in many patterns, structures, and dynamics that change throughout time. For a variety of reasons, certain news is only covered in a particular area. Language, economy, geography, politics, time zone, and culture are just a few of the many barriers that prevent news from reaching a larger audience. …

The analysis of drug residues in waste and environmental waters offers valuable insights into the epidemiological and environmental implications of drug use. This study employs a wastewater-based epidemiology (WBE) approach to estimate the use of licit and illicit drugs and new psychoactive substances (NPS) among both general and specific populations. …

Metal oxide and sulfide nanostructures are a versatile family of materials with wide-ranging applications, and their development remains ongoing. In nanoscience, attention is being directed towards their synthesis and further advancement, including the creating of new complex structures and morphologies. In this regard, ion-exchange reactions have emerged as a cutting-edge …

The increasing prevalence of mental health issues worldwide has amplified the significance of computational psychotherapy, which includes creating computational tools for the mental healthcare and tools to support existing mental health professionals. This work presents a computational psychotherapy system that predicts and forecasts mental health issues in users, and utilizes …