People remember an average of 5,000 faces: Study

Agencies
October 11, 2018

London, Oct 11: Scientists have for the first time put a figure on how many faces people actually remember -- a staggering 5,000 on average.

Researchers from the University of York in the UK tested participants on how many faces they could recall from their personal lives and the media, as well as the number of famous faces they recognised.

Humans have typically lived in small groups of around one hundred individuals, but the study suggests our facial recognition abilities equip us to deal with the thousands of faces we encounter in the modern world -- on our screens as well as in social interactions.

The results, published in the journal Proceedings of the Royal Society B, provide a baseline with which to compare the "facial vocabulary" size of humans with facial recognition software that is increasingly used to identify people at airports and in police investigations.

"Our study focused on the number of faces people actually know -- we haven't yet found a limit on how many faces the brain can handle," said Rob Jenkins from the University of York.

"The ability to distinguish different individuals is clearly important -- it allows you to keep track of people's behaviour over time, and to modify your own behaviour accordingly," Jenkins said.

For the study, participants spent an hour writing down as many faces from their personal lives as possible -- including people they went to school with, colleagues and family.

They then did the same for famous faces, such as actors, politicians, and other public figures.

The participants found it easy to come up with lots of faces at first, but harder to think of new ones by the end of the hour.

That change of pace allowed the researchers to estimate when they would run out of faces completely.

The participants were also shown thousands of photographs of famous people and asked which ones they recognised. The researchers required participants to recognise two different photos of each person to ensure consistency.

The results showed that the participants knew between 1,000 and 10,000 faces.

"The range could be explained by some people having a natural aptitude for remembering faces. There are differences in how much attention people pay to faces, and how efficiently they process the information," said Jenkins.

"Alternatively, it could reflect different social environments -- some participants may have grown up in more densely populated places with more social input," he said.

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News Network
July 24,2020

Melbourne, Jul 24: Home-made cloth face masks may need a minimum of two layers, and preferably three, to prevent the dispersal of viral droplets associated with Covid-19, according to a study.

Researchers, including those from the University of New South Wales in Australia, noted that viral droplets are generated by those infected with the novel coronavirus when they cough, sneeze, or speak.

As face masks have been proven to protect healthy people from inhaling infectious droplets as well as reducing the spread from those who are already infected, several types of material have been suggested for these, but based on little or no evidence of how well they work, the scientists said.

In the current study, published in the journal Thorax, the researchers compared the effectiveness of single and double-layer cloth face coverings with a surgical face mask (Bao Thach) at reducing droplet spread.

They said the single layer covering was made from a folded piece of cotton T shirt and hair ties, and the double layer covering was made using the sew method described by the US Centers for Disease Control and Prevention (CDC).

The scientists used a tailored LED lighting system and a high-speed camera to film the dispersal of airborne droplets produced by a healthy person with no respiratory infection, during speaking, coughing, and sneezing while wearing each type of mask.

Their analysis showed that the surgical face mask was the most effective at reducing airborne droplet dispersal, although even a single layer cloth face covering reduced the droplet spread from speaking.

But the study noted that a double layer covering was better than a single layer in reducing the droplet spread from coughing and sneezing.

According to the researchers, the effectiveness of cloth face masks is dependent on the number of layers of the covering, the type of material used, design, fit as well as the frequency of washing.

Based on their observations, they said a home made cloth mask with at least two layers is preferable to a single layer mask.

"Guidelines on home-made cloth masks should stipulate multiple layers," the scientists said, adding that there is a need for more research to inform safer cloth mask design.

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Agencies
July 24,2020

Pune, Jul 24: Agile and dexterous, 85-year-old Shantabai Pawar wields sticks with absolute ease as she displays 'lathi-kathi' on the streets of Pune.

A video of her, displaying her skills in the Indian martial art form for livelihood, has gone viral on social media.

Pawar told media persons that she learnt the art form when she was only eight and has been practising it since then. The ancient martial art s believed to be linked to Dombari community, a nomadic tribe in Maharashtra.

"I have been pursuing the art of lathi-kathi since I was eight. I have never left it. It is part of me and it is an honour to practice it. My father taught me this. He taught me to work hard," Pawar told media persons.

In the video, the sari-clad octogenarian takes a warrior-like stride and effortlessly rotates a stick several times in a second in her hand and around her head and then does it with two sticks together with a smile on her face. She also tosses a stick in the air and catches it with ease.

The assembled gathering is impressed and enthused.

"People come and say, 'Well done Daadi!' I practice it to earn money for my children and grandchildren," she said.

Pawar leaves her home in the morning in the conditions created by coronavirus and performs the art form on roads and streets.

"I go to various areas to perform the art form and people give money," she said.

The artiste also uses thali and stick to gather the attention of people as most of them are indoors due to conditions created by COVID-19.

Senior citizens have been advised against venturing out due to their greater susceptibility to coronavirus but Pawar said she is not afraid to step out.

"People do advise me to not go out due to fear of COVID-19 but I am not scared. Whenever I step out, I pray to my God and he has kept me safe so far," she said.

Aishwarya Kale, a dancer and the person who uploaded the video on social media, said that it is "only an artist who can understand what help another artist needs".

"I was in that area shopping for some items and it was then I saw her performing and thought that I should film her and upload her video on social media. But I never thought that the video would go viral and she would receive financial help not just from people in the country but overseas as well," Kale told media persons.

"She is now getting honour for her craft that she couldn't get in the last 85 years. I feel good that through my small video, her art form has become viral," she added. 

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Agencies
July 4,2020

Twitter has joined efforts to do away with racially loaded terms such as master, slave and blacklist from its coding language in the wake of the death of African-American George Floyd and ensuing Black Lives Matter protests.

The project started even before the current movement for racial justice escalated following the death of 46-year-old George Floyd in police custody in May.

The use of terms such as "master" and "slave" in programming language originated decades ago. While "master" is used to refer to the primary version of a code, "slave" refers to the replicas. Similarly, the term "Blacklist" is used to refer to items which are meant to be automatically denied.

The efforts to change these terms in favour of more inclusive language at Twitter were initiated by Regynald Augustin and Kevin Oliver and the microblogging platform is now backing their efforts.

"Inclusive language plays a critical role in fostering an environment where everyone belongs. At Twitter, the language we have been using in our code does not reflect our values as a company or represent the people we serve. We want to change that. #WordsMatter," Twitter's engineering team said in a post on Thursday.

As per the recommendations from the team, the term "whitelist" could be replaced by "allowlist" and "blacklist" by "denylist".

Similarly, "master/slave" could be replaced by "leader/follower", "primary/replica" or "primary/standby".

Twitter, however, is not the first to start a project to bring inclusivity in programming language.

According to a report in CNET, the team behind the Drupal online publishing software started using "primary/replica" in place of "master/slave" as early as in 2014.

The use of the terms "master/slave" was also dropped by developers of the Python programming language in 2018.

Now similar efforts are underway at Microsoft's Github and LinkedIn divisions as well, said the report.

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