Computational chemistry broadly investigates chemical problems using computer aided simulations/models. The exploration of material properties through computational means requires traversing length scales, from atomic to ...

This thesis presents glitch serendipity as a formalized approach to artistic practice. The study focuses on the concepts of glitch, remix, and serendipity, employing interdisciplinary methods and principles such as disjunctive ...

With the growing popularity of museums, there is an increasing awareness of the importance of acoustics in creating a high-quality visitor experience. As a result, the research field of museum acoustics has gained attention, ...

This dissertation develops and explores prospects for investigating human performance and adaptive behavior in competitive, individual- and team-based settings. It is motivated by recent work on theoretical underpinnings ...

Biotherapeutics, since their inception, have played a key role in the worldwide treatment of complex health conditions (e.g., cancer, autoimmune disorders, and viral infections). To meet the ever-increasing demand for these ...

Peptides and peptide conjugates are used for many applications, including as therapeutics and biomedical materials. At present, established synthetic routes to peptides and their conjugates include solid-phase peptide ...

We use both molecular dynamics (MD) simulations and density functional theory (DFT) calculations to investigate various nanomechanical properties of nanoparticles under compression, exfoliation of perovskite heterogeneous ...

Park-and-Ride (P&R) systems have emerged as a popular traffic management solution in response to the need for sustainable transportation options to combat the climate crisis and improve traffic flow. The goal of this ...

Interferometric imaging involves reconstructing an image from the cross-correlations of the scattered waves reflected from the illuminated medium. Phaseless imaging on the other hand involves reconstructing an image from ...

Cardiovascular diseases (CVDs) are the leading cause of global mortality, emphasizing the urgent need for accurate, accessible, and interpretable risk assessment methodologies. This dissertation introduces a deep learning ...