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Researchers Develop an Algorithm to Predict Storms, Cyclones

This research is an early attempt to show feasibility of AI-based interpretation of weather-related visual information

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Hurricane
In this image provided by NOAA, Tropical Storm Gordon approaches the United States. VOA

Using Artificial Intelligence (AI), researchers have developed an algorithm to detect cloud formations that lead to storms, hurricanes and cyclones.

The study, published in the journal IEEE Transactions on Geoscience and Remote Sensing, shows a model that can help forecasters recognise potential severe storms more quickly and accurately.

The researchers created a framework based on Machine Learning (ML) — a kind of AI — that detects rotational movements in clouds from satellite images that might have otherwise gone unnoticed.

“The very best forecasting incorporates as much data as possible, there’s so much to take in as the atmosphere is infinitely complex. By using the models and the data we have, we’re taking a snapshot of the most complete look of the atmosphere,” said Steve Wistar, Senior Forensic Meteorologist at AccuWeather in the US.

For the study, researchers analysed more than 50,000 US weather satellite images and identified and labelled the shape and motion of ‘comma-shaped’ clouds.

These cloud patterns are strongly associated with cyclone formations which can lead to severe weather events including hail, thunderstorms, high winds and blizzards, they said.

cyclone kenneth, torrential rain
An aerial shot shows widespread destruction caused by Cyclone Kenneth when it struck Ibo island north of Pemba city in Mozambique, May, 1, 2019 (Representational image). VOA

Then, using computer vision and ML techniques, the researchers taught computers to automatically recognize and detect ‘comma-shaped’ clouds in satellite images.

The computers could then assist experts by pointing out in real time where, in an ocean of data, could they focus their attention in order to detect the onset of severe weather.

“Because the ‘comma-shaped’ cloud is a visual indicator of severe weather events, our scheme can help meteorologists to forecast such events,” said study lead author Rachel Zheng from Penn State University in the US.

The researchers found that their method can effectively detect ‘comma-shaped’ clouds with 99 per cent accuracy, at an average of 40 seconds per prediction.

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It was also able to predict 64 per cent of severe weather events, outperforming other existing severe weather detection methods.

This research is an early attempt to show feasibility of AI-based interpretation of weather-related visual information. (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)