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Researchers Develop AI Tool to Help Astronomers Identify Galaxy Clusters Quickly

The study was presented at the Royal Astronomical Society’s National Astronomy meeting at Lancaster University

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The decision is also intended to make image forensics understandable for everyone. Pixabay

Researchers have developed an Artificial Intelligence (AI)-powered tool that has been trained to “look” at colour images and identify galaxy clusters quickly.

The “Deep-CEE” – Deep Learning for Galaxy Cluster Extraction and Evaluation – model is based on neural networks, which are designed to mimic the way a human brain learns to recognise objects by activating specific neurons when visualising distinctive patterns and colours.

Matthew Chan, a PhD student at Lancaster University in Britain trained the AI by repeatedly showing it examples of known, labelled objects in images until the algorithm is able to learn to associate objects on its own.

Then the researchers ran a pilot study to test the algorithm’s ability to identify and classify galaxy clusters in images that contain many other astronomical objects.

“Data mining techniques such as deep learning will help us to analyse the enormous outputs of modern telescopes” said John Stott from Lancaster University.

“We expect our method to find thousands of clusters never seen before by science,” Stott said.

Galaxy clusters represent the most extreme environments that galaxies can live in and studying them can help us better understand dark matter and dark energy.

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“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

New state-of-the-art telescopes have enabled astronomers to observe wider and deeper than ever before, such as studying the large-scale structure of the universe and mapping its vast undiscovered content.

By automating the discovery process, scientists can quickly scan sets of images, and return precise predictions with minimal human interaction.

This will be essential for analysing data in future. The upcoming Large Synoptic Survey telescope (LSST) sky survey (due to come online in 2021) will image the skies of the entire southern hemisphere, generating an estimated 15 TB of data every night.

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“We have successfully applied Deep-CEE to the Sloan Digital Sky Survey,” said Chan.

“Ultimately, we will run our model on revolutionary surveys such as the LSST that will probe wider and deeper into regions of the Universe never before explored,” Chan added.

The study was presented at the Royal Astronomical Society’s National Astronomy meeting at Lancaster University. (IANS)

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Researchers Identify 102 Genes Associated with Autism

It's critically important that families of children with and without autism participate in genetic studies because genetic discoveries are the primary means to understanding the molecular, cellular, and systems-level underpinnings of autism

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Autism
Researchers have discovered how a Genetic Alteration that increases the risk of developing Autism and Tourette's impairs brain communication. Pixabay

In the largest genetic sequencing study of autism spectrum disorder (ASD) to date, researchers have identified 102 genes associated with risk for autism.

The discovery shows significant progress towards teasing apart the genes associated with autism from those associated with intellectual disability and developmental delay, conditions which often overlap.

According to the World Health Organisation (WHO), one in 160 children has an autism spectrum disorder (ASD).

ASDs begin in childhood and tend to persist into adolescence and adulthood. In most cases the conditions are apparent during the first five years of life.

“This is a landmark study, both for its size and for the large international collaborative effort it required.

“With these identified genes we can begin to understand what brain changes underlie ASD and begin to consider novel treatment approaches,” said Joseph D Buxbaum, Director of the Seaver Autism Center for Research and Treatment at Icahn School of Medicine at Mount Sinai.

For the study published in the journal Cell, an international team of researchers from more than 50 sites collected and analyzed more than 35,000 participant samples, including nearly 12,000 with ASD, the largest autism sequencing cohort to date.

Autism
Families of children with autism face high physical, mental and emotional burdens, are sometimes ridiculed and even accused of child abuse, says a new study. Pixabay

Using an enhanced analytic framework to integrate both rare, inherited genetic mutations and those occurring spontaneously when the egg or sperm are formed, researchers identified the 102 genes associated with ASD risk.

Of those genes, 49 were also associated with other developmental delays.

The larger sample size of this study enabled the research team to increase the number of genes associated with ASD from 65 in 2015 to 102 today.

In addition to identifying subsets of the 102 ASD-associated genes, the researchers showed that ASD genes impact brain development or function and that both types of disruptions can result in autism.

“Through our genetic analyses, we discovered that it’s not just one major class of cells implicated in autism, but rather that many disruptions in brain development and in neuronal function can lead to autism,” said Buxbaum.

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It’s critically important that families of children with and without autism participate in genetic studies because genetic discoveries are the primary means to understanding the molecular, cellular, and systems-level underpinnings of autism.

“We now have specific, powerful tools that help us understand those underpinnings, and new drugs will be developed based on our newfound understanding of the molecular bases of autism,” the researchers noted. (IANS)