ARC Centre of Excellence in Convergent Bio-Nano Science and Technology. The CoE in Convergent Bio-Nano Science &Technology comprises a multi-disciplinary team focused on research aiming to understand and control the interface of materials with biological systems. The Centre will exploit knowledge of the bio-nano interface to design materials that transport and deliver vaccines, drugs and gene therapy agents, and to design new diagnostic agents and devices. Nanomedicines are on the cusp of revol ....ARC Centre of Excellence in Convergent Bio-Nano Science and Technology. The CoE in Convergent Bio-Nano Science &Technology comprises a multi-disciplinary team focused on research aiming to understand and control the interface of materials with biological systems. The Centre will exploit knowledge of the bio-nano interface to design materials that transport and deliver vaccines, drugs and gene therapy agents, and to design new diagnostic agents and devices. Nanomedicines are on the cusp of revolutionizing diagnosis and therapy in many diseases. The CoE will be the focus of bio-nano research activity in Australia, uniting universities, research agencies, institutes and companies. The expected outcomes are better diagnostic and therapeutic tools designed via an enhanced understanding of the bio-nano-interface.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101749
Funder
Australian Research Council
Funding Amount
$379,480.00
Summary
A computational network model of the mental lexicon. Understanding a word's meaning is a challenge when learning a language and a capacity that is seriously affected in various disorders such as Alzheimer's disease, however little is known about how meaning is organised in the mental lexicon and evolves from childhood into old age. This project aims to build a detailed computational model integrating information available through the senses and structure in the language environment to derive a l ....A computational network model of the mental lexicon. Understanding a word's meaning is a challenge when learning a language and a capacity that is seriously affected in various disorders such as Alzheimer's disease, however little is known about how meaning is organised in the mental lexicon and evolves from childhood into old age. This project aims to build a detailed computational model integrating information available through the senses and structure in the language environment to derive a lexicon that covers most words people know. By distinguishing qualitative different types of meaning relations, this project will allow the prediction of the kind of information and processes required to understand words and an understanding of how this lexicon grows in childhood and declines in old age.Read moreRead less