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Awarded Projects (332)
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This proposed study aims to explore the effects of soluble surfactant contamination on heat transfer in a turbulent bubbly channel flow using our in-house high-fidelity front-tracking code.

Inspired by dual-system cognitive theories, the project proposes a hybrid framework where a lightweight, fast-acting model operates in real-time while a larger, high-capacity model predicts future representations and refines decision-making.

This research proposal outlines the development of a transformer-based methodology for generating long videos through diffusion modeling. Initially, we propose using a causal encoder to compress images and videos into a shared latent space, facilitating cross-modality training and generation.

Transport and handling of complex fluids consumes large amounts of energy worldwide, and improving their mixing and heat transfer crucial from process industry to medicine.

Hydrophobic gating occurs when the ionic current flowing through a nanopore is hindered by the reversible formation of a vapour bubble inside the pore.

Silicon is the most widely used semiconductor material in electronic industry, including photovoltaics. In spite of this dominance and many decades of research, important questions remain unsolved.

We propose to run first-of-a-kind simulations of the embedded phase of star formation, covering the crucial time when protoplanetary disks are formed.

This proposal aims to unveil still debated properties of cosmic ray transport in the Universe.

The aberrant expression of CD44 variants has been associated with malignancy of various cancer cells, including glioblastoma, for which effective treatments are unavailable. Moreover, CD44 is a promising therapeutic target for hyaluronic acid (HA)-based drug delivery carriers.

The resulting LLM will be able to generate reports, written in natural language, of the market trends forecasted by the Axyon AI platform, with insightful explanations of such predictions.