Tyler O'Neal, Staff Editor HEALTH

Surrey scientists show how the early death of nerve cells is crucial to form healthy brains

Computer scientists at the University of Surrey have created a ground-breaking model that could improve our understanding of developmental disorders such as autism.

Scientists have long tried to better understand how the cerebral cortex and its layers develop, with pathologies such as autism, schizophrenia, and epilepsy linked to this process.

In a paper published by the journal Cerebral Cortex, scientists from Surrey, Newcastle University, and Nottingham University detail how they developed and used a computational model to simulate cell division, cell migration, and apoptosis (cell death) in the hope of understanding how these processes affect the development of the brain.

With their computer model's help, the researchers reproduced a wide number of cerebral structures to study - from rats to macaques, to humans.

The team also observed that slight changes in how cells perform division and apoptosis lead to the development of cortical structures found in neurodevelopmental disorders such as autism, polymicrogyria, and subcortical band heterotopia.

Dr. Roman Bauer, Engineering and Physical Sciences Research Council Research Fellow and lead author of the study from the University of Surrey, said: "We are working towards a comprehensive computational model of the cerebral cortex and how it develops - taking into account how neurons behave and organize themselves in our brains. It is clear to us that computational models have a crucial role to play in helping us to comprehensively understand the complex biological processes that lead to developmental disorders."

Marcus Kaiser, Professor of Neuroinformatics at the University of Nottingham and senior author of the study, said: "A large proportion of nerve cells dies before birth, but it was unclear why these cells are just born to die at such an early stage. The team's results showed that cell death plays an essential role in developing the brain, as it influences the thickness of the cortex's layers, variety and layer cell density."

SwRI to develop AI for integrated corridor management traffic solutions for Tennessee DOT

Tyler O'Neal, Staff Editor HEALTH

Software will use machine learning to optimize performance of regional transportation corridors

Southwest Research Institute, in collaboration with Vanderbilt University, is developing machine learning algorithms to help the Tennessee Department of Transportation (TDOT) coordinate traffic management and incident response along portions of Interstate 24 in the rapidly growing Nashville region.

The project will use artificial intelligence to enhance an integrated corridor management (ICM) system, using software and systems to promote smart mobility and improve collaboration among various transportation agencies.

"SwRI's ICM solutions fuse data across freeways, surface streets and transit systems to help balance traffic flow and improve performance of the entire corridor," said Samantha Blaisdell, a program manager at SwRI.

SwRI's Intelligent Systems Division and Vanderbilt University will develop an Artificial Intelligence-based ICM Decision Support System (DSS) through a TDOT grant funded by the U.S. Department of Transportation.

Integrated corridor management is making its way out of the laboratory and hitting the road following two decades of research led by the Federal Highway Administration (FHWA). ICM systems manage freeways and arterial roadways with dynamic lane control, speed harmonization, traffic signal control, ramp metering, demand management and other strategies. Deployment, however, has been limited by reliance on conventional traffic simulation modeling, which can be cost prohibitive due to the time and resources required to develop and maintain traffic models.

The project will use artificial intelligence in the place of simulation models to learn from and mimic operator behavior and decision making. This will enable quicker accident response and mitigation, rerouting traffic around problem areas quickly and efficiently, and ensuring state and local agency collaboration.

"SwRI's TDOT research aims to overcome the roadblocks of ICM traffic modeling by using artificial intelligence algorithms to speed up the analysis of traffic," said Clay Weston, an SwRI project manager leading the project. "After training the system using traffic patterns, the algorithms will be able to recommend alternative routes in real-time, taking advantage of high-capacity urban roads and surface streets."

The SwRI-led decision tool will have several applications, such as traffic signal coordination on underutilized roads to ease congestion on highways. State transportation operations staff will use the decision tool to evaluate and recommend traffic management strategies for real-time diversion routing. Using a web interface, the DSS will integrate into the state's management center, the public agency owned ActiveITS™ and other regional intelligent transportation systems (ITS).

The project is part of a bigger TDOT initiative known as the I-24 Smart Corridor, a 28-mile stretch of Interstate 24 with corresponding arterial roadways in the municipalities of Nashville, La Verne, Smyrna, and Murfreesboro. In addition to improving coordination, the ICM DSS tool will help meet I-24 Smart Corridor project goals to increase travel time reliability and multimodal mobility while reducing congestion associated with incidents such as collisions.

"Integrated corridor management is gaining interest as the ITS community deploys smart mobility solutions to solve old congestion problems using new technology, especially when investments in physical infrastructure may not be feasible," said Blaisdell. "We are excited to be part of this evolution with the forward-looking ITS professionals at TDOT."

City, University of London Prof Ma seeks to unlock the potential of marine wave energy

Tyler O'Neal, Staff Editor HEALTH

The City, University of London academic will lead on the development of a new generation modelling suite, combining machine learning techniques, for the survivability of wave energy converters in marine environments

City, University of London Professor of Hydrodynamics, Professor Qingwei Ma, will be helping the UK achieve its net zero carbon emissions goal by developing cutting-edge new wave energy technologies.

Supported by a £1m research grant from the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI), Professor Ma will develop the WavE-Suite, a new generation modelling suite for the survivability of wave energy converters in marine environments. Wave energy at sea CREDIT Mocean Energy

Professor Ma's project will build on the UK's leading role in marine wave energy to overcome challenges to devices that capture the energy generated by waves and convert it into a renewable source of electricity.

He says that there is a long history of research into wave energy converters (WECs), "but there are still many challenges to be overcome before they can become fully effective, reliable and economically viable".

"One of the challenges is the lack of robust modelling tools to assess survivability of WECs under extreme marine environments that cause extreme loads and large responses. Such numerical modelling tools should have the capability of dealing with breaking waves and two-phase flow and accurately estimating the effect of viscosity in turbulent states. In the meantime, they must be fast enough so that engineers can simulate the cases within practical time-scales for design."

Assisted by Dr Shiqiang Yan, the project will develop a novel numerical modelling suite by combining different models and by proposing new numerical approaches and machine learning techniques, which will be more accurate and require less computational effort. The modelling suite will be able to automatically go up to very complex simulations only when necessary, and down to simple simulations, depending on the conditions under which the WECs work.

The WavE-Suite project creates a new collaboration with leading academics from Imperial College, University of Edinburgh, University of Bath, Cardiff University, Indian Institute of Technology (IIT) Madras, Shanghai Jiao Tong University, and leading WEC developers, including Mocean in Scotland, CorPower Ocean in Sweden, Guangzhou Institute of Energy Conversion (GIEC) in China and BiMEP in Spain.

Professor Ma was granted the CH Kim Award by the International Society of Offshore and Polar Engineers (ISOPE) in 2016. He is the first academic from a UK university, and the second from Europe, to have received the award. He also received the 2015 Vice-Chancellor's Award for Excellence in Learning and Teaching.