MICROGRAVITY-INDUCED ALTERATIONS IN THE BRAIN-TO-BONE AXIS: IMPLICATIONS FOR BONE LOSS AND COUNTERMEASURE DEVELOPMENT IN LONG-TERM SPACEFLIGHT.

Space exploration over the next 30 to 50 years is projected to initially return to the Moon, with the creation of a permanent lunar settlement, followed by the establishment of a human colony on Mars. To ensure the success of these missions beyond low Earth orbit, it is essential to thoroughly investigate the effects of space environments on human physiology, crew performance, and overall health. While anti-resorptive drugs, a proper diet, and vitamin and mineral supplementation are used to a...

Toward more context-sensitive clinical measures for assessing executive attention in autistic children

Executive functions (EFs) are higher-order cognitive skills that enable individuals to control impulses, manage and update information, ignore distractions, and shift attention as needed, supporting effective adaptation to new or complex situations. EF challenges are frequently reported in neurodivergent children, particularly in autistic children, although existing research yields mixed and contradictory findings. These inconsistencies arise not only from differences in participant samples a...

Interplay between peptidoglycan biosynthesis and remodeling and outer membrane homeostasis in Acinetobacter baumannii

Time-resolved spectroscopic investigation of N2/H2 nanosecond pulsed discharges and EUV-induced low-temperature plasmas

Extreme ultraviolet (EUV) lithography is central to advanced semiconductor manufacturing, yet the low-density plasmas triggered by EUV photons in scanner-relevant environments remain only partially characterised. Their transient, photon-driven nature complicates invasive diagnostics and makes equilibrium assumptions unreliable. This thesis addresses this gap by developing and applying optical emission spectroscopy (OES) to EUV-induced plasmas in (\mathrm{H_2}), (\mathrm{N_2}), and (\mathrm{H_...

Decision-making based on Structural Health Monitoring: a Reliability-based Framework

The average age of strategic infrastructure in the Western world is steadily increasing, raising concerns about inspection, maintenance, and replacement costs. An accurate assessment of structural conditions is crucial to optimize resource allocation. Nowadays, advances in technology and computational methods have made structural health monitoring (SHM) increasingly attractive to researchers, prompting the scientific community to explore innovative methods that also take advantage of artifici...

Not the Pearls but the Thread: Using fNIRS Hyperscanning to Investigate Real-Life Social Interactions

The psychological underpinnings of collective climate action

We are in the midst of a dangerous climate crisis, and collective mobilization is needed to push for urgent global transformations. Many people already perceive the risk that human actions are driving increasingly catastrophic climate impacts, but only a few are taking actions such as asking governments for climate policy, educating peers, and implementing community-based models of ecological transition. This dissertation examines the psychological drivers of collective climate action among y...

Comprehensive Study of Identified Hadron Spectra, π± , K± and p(p̄) in PbPb Collisions at √sNN= 5.36 TeV with the ALICE Detector at CERN

In ultra-relativistic heavy-ion collisions, the Large Hadron Collider (LHC) at CERN recreates, for a brief instant, the conditions that existed microseconds after the Big Bang. Under such extreme conditions, ordinary nuclear matter transitions into a de- confined state of strongly interacting quarks and gluons, the fundamental degrees of freedom of Quantum Chromodynamics (QCD), forming what is known as the Quark Gluon Plasma (QGP). One of the central goals of modern nuclear physics and ...

Towards Self-configuring Efficient Neural Architectures for Automatic Speech Recognition

Recent advancements in developing neural architectures has led to the curation of complex deep neural networks which exhibit promising performance on downstream speech applications, like automatic speech recognition. The superior performance of these models is linked to the immense training data and time, along with significant computational resource requirements. Effectively leveraging the capabilities of such models on varying and resource-constrained edge devices pose considerable challeng...