Search Results (94)
Speciation of ruthenium-based candidate drugs for cancer treatment and copper as a potential biomarker for cancer diagnosis in human serum
According to the World Health Organization (WHO), cancer represents the second leading cause of mortality, with almost 10 million deaths in 2020. A broad spectra of cancer treatments are being developed, among them are metal-based drugs. Consistent with the available data, platinum (Pt)-based chemotherapeutics are still widely used to treat …
Protection of biomedical alloys by thin films of alumina and hafnia prepared by atomic layer deposition
One of the most commonly used metal materials for the manufacture of biomedical implants are stainless steel and titanium-based alloys. Due to the specific conditions and complex environment in the human body, different strategies have been employed to protect them and improve their functionality in vivo. In this thesis, a …
Synergistic action of organic inhibitors to mitigate corrosion of aluminium, copper and aluminium-copper alloy in chloride solution
The inhibitory action of organic compounds, 2-mercaptobenzimidazole (MBI), octylphosphonic acid (OPA) and their binary combinations was studied on aluminium, copper and aluminium alloy (AA) 2024 in chloride environments by ex-situ conventional electrochemical methods and surface-analytical techniques. In addition, the influence of pre-treatment of the metal surface and the choice of …
Combining neural and symbolic representations in natural language processing
The thesis addresses a novel representation learning framework, combining neural and symbolic text representations, and demonstrates its utility for tackling diverse natural language processing problems. The proposed approach, avoiding the deficiencies of purely symbolic and purely neural methods, can be applied for the generation of efficient text representations. Its usefulness …
The use of high-throughput sequencing for detection of viral sequences in complex samples from environment and industry
Metagenomics based on high throughput sequencing (HTS) has opened a new era of discovery and genomic characterization of viruses associated with a given host or environment. The search for novel viral sequences provides an excellent opportunity to improve early detection of pathogens, and to predict viral hosts and environmental reservoirs …
Authenticity and traceability of food and food flavourings using a stable isotope approach
Food fraud or economically motivated adulteration has been an issue throughout history. Even today, it remains a significant and growing problem, driven by globalisation, economic opportunity and the low probability and severity of punishment. Fraud is a concern for food producers, consumers, regulatory agencies and scientific organisations, and food fraud …
High-precision wide-bandwidth isolated current measurement in networked devices
With the increasing use of electricity powered devices and processes in our daily lives, the need for the precise measurement of electrical currents across more than 15 decades from below nA to tens or hundreds of kA has become inevitable both for billing and more optimal energy distribution purposes as …
Time-efficient method for monitoring electrochemical energy conversion systems
According to the EU’s Green Deal plan, one of the main objectives for the EU is to become a net-zero greenhouse emission society by 2050. Achieving this goal requires advancements across many areas ranging from energy production, conversion, distribution and energy storage where the key role is taken by the …
Targeted analysis of organic contaminants, exposure assessment, and vulnerability of populations to hazardous compounds
From the moment of conception until death, humans are exposed to chemicals at varying intensities and frequencies. While an individual’s level of resilience is commonly high enough to tolerate these kinds of stressors, specific exposures or genetic predispositions can lower it. Therefore, the assessment of chemical exposure, the development of …
Scalable neuro-symbolic machine learning
With the resurgence of neural network-based learning in the last decade, machine learning methods are becoming critical components of many real-life intelligent systems. However, while being able to learn effectively and at scale, such systems are often non-interpretable and unable to exploit existing symbolic background knowledge. The paradigm that offers …