Sunday September 22, 2019

Researchers Find Cocaine in UK Shrimp

Scientists have found evidence that they are entering the human body, with microplastics in human stools for the first time in 2018

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modern slavery
A government raid empties a shrimp shed in Samut Sakhon, Thailand. Slavery has often been considered an acceptable business practice in the country's seafood export capital. (VOA)

Researchers in the UK have found cocaine, pharmaceuticals and pesticides in all samples of freshwater shrimp in a rural area of eastern England.

Scientists from King’s College London and the University of Suffolk tested the exposure of freshwater shrimp to different micropollutants at 15 different sites in the county of Suffolk.

Scientists were surprised to find illicit drugs in the samples in rural England, with ketamine also widespread. The full results of the study were published in the journal Environment International.

“Such regular occurrence of illicit drugs in wildlife was surprising,” Leon Barron from King’s College London said in a press release.

“We might expect to see these in urban areas such as London, but not in smaller and more rural catchments.”

Researchers also found traces of fenuron, a pesticide that has long been banned in the UK, added Barron, who said that the sources of the chemical are not clear.

Cocaine. Wikimedia commons

“Although concentrations were low, we were able to identify compounds that might be of concern to the environment and crucially, which might pose a risk to wildlife,” said Thomas Miller from King’s College London.

“The impact of ‘invisible’ chemical pollution (such as drugs) on wildlife health needs more focus in the UK as policy can often be informed by studies such as these,” said Nic Bury from the University of Suffolk.

High levels of benzoylecgonine, the main metabolite of cocaine, have previously been detected in wastewater in London.

Also Read- Three Tombs Discovered Under Egypt’s Great Pyramids

Microplastics are also a concern, with the tiny plastic particles being found inside fish, sea turtles and even flying insects, the researchers said.

Scientists have found evidence that they are entering the human body, with microplastics in human stools for the first time in 2018. (IANS)

Next Story

Researchers Develop New Algorithm to Identify Cyber-bullies on Twitter

“In a nutshell, the algorithms ‘learn’ how to tell the difference between bullies and typical users by weighing certain features as they are shown more examples,” said Blackburn

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FILE - A man reads tweets on his phone in front of a displayed Twitter logo. VOA

Researchers have developed machine learning algorithms which can identify bullies and aggressors on Twitter with 90 per cent accuracy.

For the study published in the journal Transactions on the Web, the research team analysed the behavioural patterns exhibited by abusive Twitter users and their differences from other users.

“We built crawlers — programs that collect data from Twitter via variety of mechanisms,” said study researcher Jeremy Blackburn from Binghamton University in the US.

“We gathered tweets of Twitter users, their profiles, as well as (social) network-related things, like who they follow and who follows them,” Blackburn said.

The researchers then performed natural language processing and sentiment analysis on the tweets themselves, as well as a variety of social network analyses on the connections between users.

twitter, white swan, suicide, awareness
Twitter is a social media app that encourages short tweets and brief conversations. Pixabay

They developed algorithms to automatically classify two specific types of offensive online behaviour, i.e. cyber-bullying and cyber-aggression.

The algorithms were able to identify abusive users — who engage in harassing behaviour like those who send death threats or make racist remarks — on Twitter with 90 per cent accuracy.

Also Read: Facebook Announces Some New Features to its Video Capabilities

“In a nutshell, the algorithms ‘learn’ how to tell the difference between bullies and typical users by weighing certain features as they are shown more examples,” said Blackburn.

“Our research indicates that machine learning can be used to automatically detect users that are cyber-bullies, and thus could help Twitter and other social media platforms remove problematic users,” Blackburn added. (IANS)