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Recent studies have revealed bacterial genome-wide evolution to be complex and dynamic even in a constant environment, characterized by the emergence of new clades competing or temporarily coexisting as each clade undergoes evolutionary change. Previous studies on predator-prey dynamics tracking simple ecological and phenotypic metrics have shown predation to fundamentally alter prey evolution, fa

When navigating our world, we often feel that we see the whole scene around us. However, large parts of nearby space are often not visible because they are occluded by other objects. Behavioural evidence suggests that such occluded regions can be perceived as empty, which is known as the illusion of absence. Stage magicians use this illusion to make objects appear out of thin air. If an object eme

Europe’s Beating Cancer Plan is a substantial European Union (EU) investment into cancer prevention and treatment. Integration of genetic services towards personalised cancer prevention and care is a flagship of this plan. Genetic counselling is critical to this integration, facilitating informed patient decision making and improved clinical management. However, growing demands for genetic testing

Background: Cyclic Cushing's syndrome (cCS) features fluctuating cortisol secretion, often causing diagnostic errors or delays, and possibly poorer outcomes. We aimed to identify unpublished cCS cases to characterise clinical challenges and guide strategies for improving outcomes by characterising cycle patterns, peak frequency, and evaluating complications. Methods: This was a retrospective obser

This thesis presents a case study on the application of artificial intelligence (AI) in hydrology using two approaches. This topic was chosen since AI is an important tool, and water is a vital resource. The first case is on leakage detection with artificial data, while the second is on precipitation prediction with real data. For leakage detection, a random forest (RF) model and an artificial neuWater is the most vital resource, yet globally, 30% is lost through leaks. By implementing artificial intelligence (AI), this thesis has developed methods to locate leaks with high precision, as well as models to improve accuracy on satellite-based precipitation data. This thesis investigates two applications of AI on real-world problems; detecting water leaks and improving precipitation data. Th

The chapter argues that employees play a central yet historically overlooked role in organizational crisis communication. Traditional crisis communication has emphasized external stakeholders and managerial control, but this chapter highlights internal communication as a continuous, relational, and sensemaking process that shapes organizational legitimacy. Employees are portrayed as active sensema

The transition toward sustainable energy systems has motivated extensive research into scalable routes for solar fuel generation. Silicon-based photoelectrodes are particularly promising due to their favorable optoelectronic properties, abundance, and compatibility with established microfabrication techniques. Nano-microstructuring silicon can enhance photoelectrochemical performance by improving

This work investigates lightweight personalisation of micro-electro-mechanical systems (MEMS)-based wearables using a public padel database as a case study. We compare a centralised CNN model, single-user models and two fine-tuning schemes (full and last-layer) on wrist-worn IMU data from 23 players and 13 stroke classes. Personalised models with data augmentation achieve weighted F1-scores above

Chronic obstructive pulmonary disease (COPD) is a progressive condition characterized by airway remodeling, including emphysema and fibrosis. Proteoglycans and their glycosaminoglycan (GAG) chains are key components of the extracellular matrix and may be altered as the disease advances. This study analyzed lung tissue from COPD patients (GOLD stages II-III and IV), non-COPD smokers, and non-smoker

In this paper, we investigate a Multi-layer Aerial system for GenAI inference at the Edge (MAGE). Therein, ground user equipments (UEs) request image synthesis services from a remote base station (BS) that leverages the Latent Diffusion Model (LDM) for image generation. Multiple Unmanned Aerial Vehicles (UAVs) are deployed to serve the UEs for relaying their images and prompts to the BS. To reduce

We explore mission assignment and task offloading in Open Radio Access Network (Open RAN)-enabled intelligent transportation systems (ITS), where autonomous vehicles utilize mobile edge computing for efficient processing. Existing studies often overlook mission dependencies and offloading costs, leading to suboptimal decisions. To address this, we formulate a novel optimization problem that integr

With the current climate crisis, it is time to reframe our understanding of active mobility as a solution for short journeys only. When combined with public transport, almost any journey can be an active one. To compete with private automobile travel, public transport must combine the speed of motorised transport, the reliability of dedicated right-of-way services, and the flexibility of active tr

Maternal alloantibody-induced hemolytic disease of the fetus and newborn (HDFN) remains a significant concern worldwide. Alloimmune HDFN can be pathogenetically named by the specific alloantibodies involved. Moreover, four mechanistic pathway types are generally recognized in clinical practice: classical or extravascular hemolysis; immune-pressure-escaped, also known as antibody-mediated antigen-m

Context. Massive contact binaries (CBs) are crucial objects for understanding close binary evolution and stellar mergers. Study of these objects has been hampered by a scarcity of observed systems, particularly of B-type systems which are expected to dominate this class. Aims. We bridge this observational gap by mining a large sample of massive CB candidates from the OGLE-IV database, potentially