Knowledge of the pollution activity at the mining and smelting sites and assessment of contamination levels at different sites is not always sufficient for reliable conclusions regarding lead (Pb) provenance and contributions from sources. Pb isotopes have long been used as ‘fingerprints’ of the source of Pb recorded in environmental …
Environmental contamination by toxic metals—such as Pb²⁺, Cr³⁺, and Hg²⁺—and organometallic species like monomethylmercury (MeHg) presents one of the most persistent global challenges due to their bioaccumulation, long-term toxicity, and resistance to degradation. This thesis addresses this critical issue through a multidisciplinary approach combining nanotechnology, environmental chemistry, biosensor engineering, and …
Water scarcity is becoming a greater issue worldwide due to ever-increasing anthropogenic activity. A dedicated effort is required to recover and maintain the purity of our water resources and has created an environment for developing better technologies to tackle this issue. Low-pressure gaseous plasma, consisting of a complex mixture of …
The thesis investigates associations between the biomarkers of lead (Pb) exposure (and mercury (Hg), where applicable) and genetic variability in in vulnerable populations, including pregnant women and their newborns from Italy, Slovenia, and Croatia, as well as Slovenian men of reproductive age. The research utilizes data from the Public Health …
Magnetic resonance imaging (MRI) is a diagnostic method that is used for broad range of hospitalized patient, emergency patients, chemotherapy treated and as well the patients that may have infectious diseases. Because the examinations of different patients are usually performed with the same equipment in the same environment, the surfaces …
This thesis investigates machine learning methods for analyzing sequential textual data. Sequential textual data refers to text collected in a specific order where the sequence is significant. Examples include (1) sentences, where word usage and order must adhere to the rules of grammar, (2) news reporting on events happening at …
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 …
This thesis focuses on the development and optimisation of zirconium conversion coatings (ZrCCs) on cold-rolled steel (CRS), zinc (Zn), and aluminium alloy AA5754 substrates through a multidimensional approach. The utilization of statistical tools, specifically response surface methodology (RSM), enabled the assessment of the individual and mutual effects of various parameters …
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 …
RNA molecules dynamically interact with RNA-binding proteins (RBPs), which control various aspects of RNA fate, such as its processing, localisation, and stability. Intricate networks of protein-RNA interactions thereby regulate gene expression and have a profound effect on downstream cellular processes. Most RBPs recognise specific motifs on their bound RNAs, characterised …