Adults with autism good at recognising complex emotions in others: Study

Agencies
January 9, 2019

Washington, Jan 9: Adults with autism can easily recognise complex emotions such as regret and relief in others, a recent study suggests.

As part of the study, which appears in the journal Autism Research, a team of psychologists used eye-tracking technology to monitor participants as they read stories in which a character made a decision and as a result, experienced a positive or negative outcome.

Heather Ferguson, lead author of the study explained that the study highlights a previously overlooked strength in adults with autism spectrum disorder (ASD).

The researchers found that adults with ASD were quickly able to think about how things might have turned out differently (either better or worse than reality), then judge whether the story character would feel regret or relief (known as counterfactual emotions).

The adults with ASD were found to be just as good at recognising regret emotions in the character as adults without the condition, and even better at computing relief.

The eye-tracking method provided sensitive information on when readers had inferred the appropriate counterfactual emotion for the character. Appropriate emotions resulted in shorter reading times.

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Agencies
April 15,2020

Dear parents, if you want your children to have proper sleep, read this carefully. Joining a growing list of studies that tell parents to shun devices at bed-time, researchers say that children who use devices and decide what time they go to sleep, achieve less sleep and feel more sleepier the following day than their peers.

The study of children in this age-group (aged 11 to 13 years), published in the New Zealand Medical Journal, found most (72 per cent) of the 163 students interviewed by University of Otago researchers achieved recommended guidelines of an average 9 to 11 hours sleep nightly over one week.

"But that also means that almost one in four students did not achieve sleep within these guidelines, which highlights an area for improvement," said study researcher Kate Ford.

However, consistent with previous research in 15 to 17-year-old New Zealanders, the study results show less sleep on the nights where devices are used in the hour before bed.

According to the researchers, students who used devices before going to sleep were also more likely to report that they felt sleepy the following morning. Watching television before bed had no significant effect on sleep length.

There were also some interesting observations over the weekends where students went to bed later but woke later achieving similar sleep length to the school days, the researchers said.

A small group of students (six per cent) who reported less than seven hours of sleep, including a small number reporting not sleeping at all, according to the study,

Therefore, while the average across the week of 72 per cent of students reporting adequate sleep is reassuring, it is far from the goal of every child achieving sleep within the recommended guidelines," Ford said.

Dr Paul Kelly, head of the Sleep Health Service at Canterbury District Health Board, supervised the study and explained that the foundations for good health are based on proper nutrition, regular exercise and good sleep quality.

Sleep quality is often overlooked as a contributory factor to poor health.

"The study findings suggest the need for parental guidance around bedtimings and moderation of the use and availability of electronic devices before bed," Kelly said.

"Respect and protect your sleep, as good daytime functioning is reliant on adequate sleep," Kelly added.

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Agencies
July 25,2020

The COVID-19 pandemic and the subsequent lockdown saw many people turning chefs overnight, but those who could not turned to online delivery of food. And not just any food, as per a new report, Indians "craved the most for Biryani" during the lockdown.

The "StatEATistics report: The Quarantine Edition" from food delivery platform Swiggy found that Indians ordered biryani over "5.5 lakh times" from their favourite restaurants.

The new normal might have opened a pandora's box of behavioral changes, but some old habits die hard like the love for Biryani, which took the top spot for overall orders. It was followed by butter naan and masala dosa at 3,35,185 and 3,31,423, respectively.

Biryani has topped the list of most ordered dishes for the fourth year in a row, the food delivery platform noted.

Indians didn't forget to indulge their sweet tooth in the uncertain months of lockdown. Their favourite comfort food during the lockdown period was the moist and decadent Choco Lava cake, ordered around 1,29,000 times.

"The humble Gulab Jamun (84,558) and chic Butterscotch Mousse cake (27,317) followed suit," said the report derived from Swiggy's order analysis in the past few months across cities that it is present in.

Also, as birthday parties moved to video calls, and virtual cake cutting sessions, according to the food delivery platform, it delivered nearly "1,20,000 cakes" to complete these celebrations.

According to the report, on average, "65,000 meal orders" were placed by 8 pm each day to make sure food arrived in time for dinner.

"It was the busiest hour for Swiggy delivery partners and restaurants. On average, they (customers) chose to tip Rs.23.65, with one particularly generous customer tipping Rs. 2500!," it added.

For those who only relied on home-made food during the quarantine, Swiggy delivered a whooping 323 million kgs of onions and 56 million kgs of bananas through its grocery section and hence ensured that its consumers were all stocked up.

That said, it also took care of the 'quick-fix meal' tribe -- consumers who resort to the evergreen college hacks of living on instant noodles.

"Around 3,50,000 packets of this ideal easy to cook meal were ordered during the lockdown," it said.

In all, Swiggy delivered 40 million orders across food, groceries, medicines and other household items during India's lockdowns. It also delivered over 73,000 bottles of sanitizers and hand wash along with 47,000 face masks as the definition of essentials' changed during these uncertain times.

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News Network
February 26,2020

New York, Feb 26:  A new wearable sensor that works in conjunction with artificial intelligence (AI) technology could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs, says a study.

The researchers said the system could eventually help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life.

"This study shows that we can accurately predict the likelihood of hospitalisation for heart failure deterioration well before doctors and patients know that something is wrong," says the study's lead author Josef Stehlik from University of Utah in the US.

"Being able to readily detect changes in the heart sufficiently early will allow physicians to initiate prompt interventions that could prevent rehospitalisation and stave off worsening heart failure," Stehlik added.

According to the researchers, even if patients survive, they have poor functional capacity, poor exercise tolerance and low quality of life after hospitalisations.

"This patch, this new diagnostic tool, could potentially help us prevent hospitalizations and decline in patient status," Stehlik said.

For the findings, published in the journal Circulation: Heart Failure, the researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four veterans administration (VA) hospitals in Utah, Texas, California, and Florida.

After discharge, participants wore an adhesive sensor patch on their chests 24 hours a day for up to three months.

The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.

This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities.

Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient's heart failure was getting worse.

Overall, the system accurately predicted the impending need for hospitalization more than 80 per cent of the time.

On average, this prediction occurred 10.4 days before a readmission took place (median 6.5 days), the study said.

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