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Yahoo
2 days ago
- Science
- Yahoo
Scientists Witnessed the Birth of a Monster—8.3 Billion Years After It Happened
Here's what you'll learn when you read this story: Observations from NASA's James Webb Space Telescope and other telescopes have shown what appears to be a supermassive black hole forming right between two merging galaxies. There have been multiple hypotheses surrounding supermassive black hole formation, but these observations support the hypothesis that suggests these behemoths are the result of immense clouds of shocked and compressed gas collapsing in on themselves. Future observations with Webb may finally confirm how supermassive black holes come into being. Supermassive black holes lurk in almost every large galaxy, including our own, but their origins are more elusive. Did they appear after the demise of gargantuan stars in the early universe? Do they form from smaller black holes that merge? Is it possible they emerge from monstrous clouds of star-forming gas that collapse in on themselves? That last hypothesis might be onto something. The pair of galaxies merging into what is now known as the Infinity Galaxy (so named because of its uncanny resemblance to the infinity symbol) is 8.3 billion light-years away, meaning we are seeing events unfold as they did that many billions of years ago. Between them is what astronomers now believe to be a supermassive black hole (SMBH) in its infancy. Whatever the object is, it is accreting tons upon tons of material, and supermassive black holes are known for their voracious appetites. Observations of this galaxy and the thing spawning in the middle might be the first hard evidence of a supermassive black hole being born. Each of the galaxies that collided to form the Infinity Galaxy have their own glowing nuclei containing supermassive black holes, but the one supposedly forming in between is unrelated to either of them—its source is apparently something else. The mystery convinced astronomers Pieter van Dokkum of Yale University and Gabriel Brammer of the University of Copenhagen, who discovered the nascent black hole while analyzing images from the COSMOS-Web survey of NASA's James Webb Space Telescope, that what they were seeing was no ordinary star. Van Dokkum and Brammer backed their findings up by poring over data from observations made by the W.M. Keck Observatory, the Chandra X-Ray Observatory, and more data from the archives of the National Radio Astronomy Observatory's Very Large Array. It was already strange that this black hole was not hiding in the nucleus of a galaxy, never mind that it was at the beginning of its life. Shrouded by clouds of gas between the two galaxies was most likely a supermassive black hole that probably formed from gas that had been shocked and compressed during the galactic merger, then collapsed in on itself. Witnessing one being born is unprecedented. 'The gas spans the entire width of the system and was likely shocked and compressed at the collision site,' they and their colleagues said in a study soon to be published in the Astrophysical Journal Letters. 'We suggest that the SMBH formed within this gas in the immediate aftermath of the collision, when it was dense and highly turbulent.' There are two main hypotheses for how supermassive black holes form. The 'light seeds' theory claims that supermassive black holes are the product of black holes that form after massive stars go supernova, collapsing in on themselves in violent explosions. These black holes then merge into larger black holes. The problem is that it would not only take an extremely long time for a supermassive black hole to form this way, this theory also cannot explain the existence of supermassive black holes, already observed by Webb, which were around when the universe was still young. The 'heavy seeds' hypothesis suggests that immense clouds of gas that collapse usually form stars, but sometimes, the gases collapse directly into supermassive black holes. This is the theory that seems to align with the more recent observations. About a few hundred million years after the universe dawned, clouds of gas in the middle of what would become galaxies collapsed. Hiding in those gaseous clouds were the seeds of supermassive black holes, whose powerful outflows and magnetic storms caused surrounding gas to collapse into multitudes of new stars. This explains the high populations of stars around galactic nuclei. 'If our proposed scenario is confirmed, the Infinity galaxy provides an empirical demonstration that direct-collapse formation of SMBHs can happen in the right circumstances—something that has so far only been seen in simulations and through indirect observations,' Brammer and van Dokkum said. More observations with Webb and other telescopes could finally reveal what a supermassive black hole's baby pictures look like. You Might Also Like The Do's and Don'ts of Using Painter's Tape The Best Portable BBQ Grills for Cooking Anywhere Can a Smart Watch Prolong Your Life? Solve the daily Crossword
Hans India
3 days ago
- Science
- Hans India
AI model trained to respond to online political posts impressive
Researchers. who trained a large language model to respond to online political posts of people in the US and UK, found that the quality of discourse had improved. Powered by artificial intelligence (AI), a large language model (LLM) is trained on vast amounts of text data and therefore, can respond to human requests in the natural language. Polite, evidence-based counterarguments by the AI system -- trained prior to performing experiments -- were found to nearly double the chances of a high-quality online conversation and 'substantially increase (one's) openness to alternative viewpoints', according to findings published in the journal Science Advances. Being open to perspectives did not, however, translate into a change in one's political ideology, the researchers found. Large language models could provide 'light-touch suggestions', such as alerting a social media user to the disrespectful tone of their post, author Gregory Eady, an associate professor of political science and data science at the University of Copenhagen, said. 'To promote this concretely, it is easy to imagine large language models operating in the background to alert us to when we slip into bad practices in online discussions, or to use these AI systems as part of school curricula to teach young people best practices when discussing contentious topics,' Eady said. Hansika Kapoor, research author at the department of psychology, Monk Prayogshala in Mumbai, an independent not-for-profit academic research institute, said, '(The study) provides a proof-of-concept for using LLMs in this manner, with well-specified prompts, that can generate mutually exclusive stimuli in an experiment that compares two or more groups.' Nearly 3,000 participants -- who identified as Republicans or Democrats in the US and Conservative or Labour supporters in the UK -- were asked to write a text describing and justifying their stance on a political issue important to them, as they would for a social media post. This was countered by ChatGPT -- a 'fictitious social media user' for the participants -- which tailored its argument 'on the fly' according to the text's position and reasoning. The participants then responded as if replying to a social media comment. 'An evidence-based counterargument (relative to an emotion-based response) increases the probability of eliciting a high-quality response by six percentage points, indicating willingness to compromise by five percentage points, and being respectful by nine percentage points,' the authors wrote in the study. Eady said, 'Essentially, what you give in a political discussion is what you get: that if you show your willingness to compromise, others will do the same; that when you engage in reason-based arguments, others will do the same; etc.' AI-powered models have been critiqued and scrutinised for varied reasons, including an inherent bias -- political, and even racial at times -- and for being a 'black box', whereby internal processes used to arrive at a result cannot be traced. Kapoor, who is not involved with the study, said that whilst appearing promising, a complete reliance on AI systems for regulating online discourse may not be advisable yet. The study itself involved humans to rate responses as well, she said. Additionally, context, culture, and timing would need to be considered for such regulation, she added. Eady too is apprehensive about 'using LLMs to regulate online political discussions in more heavy-handed ways.' Further, the study authors acknowledged that because the US and UK are effectively two-party systems, addressing the 'partisan' nature of texts and responses was straightforward. Eady added, 'The ability for LLMs to moderate discussion might also vary substantially across cultures and languages, such as in India. Personally, therefore, I am in favour of providing tools and information that enable people to engage in better conversations, but nevertheless, for all its (LLMs') flaws, allowing nearly as open a political forum as possible,' the author added. Kapoor said, 'In the Indian context, this strategy may require some trial-and-error, particularly because of the numerous political affiliations in the nation. Therefore, there may be multiple variables and different issues (including food politics) that will need to be contextualised for study here.' Another study, recently published in the 'Humanities and Social Sciences Communications' journal, found that dark personality traits -- such as psychopathy and narcissism -- a fear of missing out (FoMO) and cognitive ability can shape online political engagement. Findings of researchers from Singapore's Nanyang Technological University suggest that 'those with both high psychopathy (manipulative, self-serving behaviour) and low cognitive ability are the most actively involved in online political engagement.' Data from the US and seven Asian countries, including China, Indonesia and Malaysia, were analysed. Describing the study as 'interesting', Kapoor pointed out that a lot more work needs to be done in India for understanding factors that drive online political participation, ranging from personality to attitudes, beliefs and aspects such as voting behaviour. Her team, which has developed a scale to measure one's political ideology in India (published in a preprint paper), found that dark personality traits were associated with a disregard for norms and hierarchies.
Time of India
3 days ago
- Science
- Time of India
Researchers train AI model to respond to online political posts, find quality of discourse improved
Researchers who trained a large language model to respond to online political posts of people in the US and UK, found that the quality of discourse improved. Powered by artificial intelligence (AI), a large language model (LLM) is trained on vast amounts of text data and therefore, can respond to human requests in the natural language. Polite, evidence-based counterarguments by the AI system -- trained prior to performing experiments -- were found to nearly double the chances of a high quality online conversation and "substantially increase (one's) openness to alternative viewpoints", according to findings published in the journal Science Advances. Being open to perspectives did not, however, translate into a change in one's political ideology, the researchers found. Large language models could provide "light-touch suggestions", such as alerting a social media user to the disrespectful tone of their post, author Gregory Eady, an associate professor of political science and data science at the University of Copenhagen, Denmark, told PTI. "To promote this concretely, it is easy to imagine large language models operating in the background to alert us to when we slip into bad practices in online discussions, or to use these AI systems as part of school curricula to teach young people best practices when discussing contentious topics," Eady said. Hansika Kapoor, research author at the department of psychology, Monk Prayogshala in Mumbai, an independent not-for-profit academic research institute, told PTI, "(The study) provides a proof-of-concept for using LLMs in this manner, with well-specified prompts, that can generate mutually exclusive stimuli in an experiment that compares two or more groups." Nearly 3,000 participants -- who identified as Republicans or Democrats in the US and Conservative or Labour supporters in the UK -- were asked to write a text describing and justifying their stance on a political issue important to them, as they would for a social media post. This was countered by ChatGPT -- a "fictitious social media user" for the participants -- which tailored its argument "on the fly" according to the text's position and reasoning. The participants then responded as if replying to a social media comment. "An evidence-based counterargument (relative to an emotion-based response) increases the probability of eliciting a high-quality response by six percentage points, indicating willingness to compromise by five percentage points, and being respectful by nine percentage points," the authors wrote in the study. Eady said, "Essentially, what you give in a political discussion is what you get: that if you show your willingness to compromise, others will do the same; that when you engage in reason-based arguments, others will do the same; etc." AI-powered models have been critiqued and scrutinised for varied reasons, including an inherent bias -- political, and even racial at times -- and for being a 'black box', whereby internal processes used to arrive at a result cannot be traced. Kapoor, who is not involved with the study, said that whilst appearing promising, a complete reliance on AI systems for regulating online discourse may not be advisable yet. The study itself involved humans to rate responses as well, she said. Additionally, context, culture, and timing would need to be considered for such regulation, she added. Eady too is apprehensive about "using LLMs to regulate online political discussions in more heavy-handed ways." Further, the study authors acknowledged that because the US and UK are effectively two-party systems, addressing the 'partisan' nature of texts and responses was straightforward. Eady added, "The ability for LLMs to moderate discussion might also vary substantially across cultures and languages, such as in India." "Personally, therefore, I am in favour of providing tools and information that enable people to engage in better conversations, but nevertheless, for all its (LLMs') flaws, allowing nearly as open a political forum as possible," the author added. Kapoor said, "In the Indian context, this strategy may require some trial-and-error, particularly because of the numerous political affiliations in the nation. Therefore, there may be multiple variables and different issues (including food politics) that will need to be contextualised for study here." Another study, recently published in the 'Humanities and Social Sciences Communications' journal, found that dark personality traits -- such as psychopathy and narcissism -- a fear of missing out (FoMO) and cognitive ability can shape online political engagement. Findings of researchers from Singapore's Nanyang Technological University suggest that "those with both high psychopathy (manipulative, self-serving behaviour) and low cognitive ability are the most actively involved in online political engagement." Data from the US and seven Asian countries, including China, Indonesia and Malaysia, were analysed. Describing the study "interesting", Kapoor pointed out that a lot more work needs to be done in India for understanding factors that drive online political participation, ranging from personality to attitudes, beliefs and aspects such as voting behaviour. Her team, which has developed a scale to measure one's political ideology in India (published in a pre-print paper), found that dark personality traits were associated with a disregard for norms and hierarchies.
Powys County Times
21-07-2025
- Health
- Powys County Times
New tool can identify children who are likely to become obese in adulthood
A tool which can measure a child's risk of becoming obese in later life has been created by scientists. It is hoped that the new resource will one day mean that those at highest risk will get targeted support to prevent them from becoming obese in the first place. The tool, which assesses a person's genetic risk of obesity, works twice as well as any other obesity risk predictor, academics said. As well as identifying children at risk of obesity, it can also predict how well obese adults will respond to targeted weight loss programmes. Academics used detail on genetic variations from more than five million people to create a tool called a polygenic risk score, which analyses people's genetics to work out their risk of developing obesity. The tool could explain 17.6% of variation in body mass index score (BMI) from people in the UK, they found. Researchers, led by academics at the universities of Copenhagen and Bristol, tested whether the risk score was associated with obesity using datasets of the physical and genetic characteristics of more than 500,000 people. This included checking the tool on people taking part in the 'Children of the 90s' study – a long-term study in Bristol tracking families as children age. They found that it could successfully predict weight gain during childhood – from the age of just two and a half – through to adolescence. 'Overall, these data show that polygenic scores have the potential to improve obesity prediction, particularly when implemented early in life,' the authors wrote in the journal, Nature Medicine. Lead author of the research, assistant professor Roelof Smit from the University of Copenhagen, said: 'What makes the score so powerful is the consistency of associations between the genetic score and body mass index before the age of five and through to adulthood – timing that starts well before other risk factors start to shape their weight later in childhood. 'Intervening at this point could theoretically make a huge impact.' He told the PA news agency that BMI is not a good predictor for a child's obesity risk in later life but the genetic predictor can offer insight into the risk from early years. #BetterHealth offers a range of free NHS apps to help people eat better and get active, including the NHS Weight Loss Plan app. Data shows it can help people lose 5.8kg on average over just 12 weeks. Find out more: — NHS London (@NHSEnglandLDN) July 25, 2023 'Essentially it's fixed at conception already very early in life, you're able to essentially quantify what someone's innate predisposition is for BMI,' he said. 'So, being able to say something about someone's innate biology for obesity risk.' Meanwhile, the research team also looked at people taking part in 'intensive lifestyle intervention' programmes. People with a higher risk score lost more weight, but were also more likely to regain it. Prof Smit added: 'There is a huge amount of variation in how people respond to these interventions. 'What we observed was the higher someone's score was, the more they tended to respond to the intervention – people who had a higher score tended to lose more weight in the first year. 'And we also saw that people who had the higher scores tended to gain more weight.' Dr Kaitlin Wade, associate professor in epidemiology at the University of Bristol and second author on the paper, said: 'Obesity is a major public health issue, with many factors contributing to its development, including genetics, environment, lifestyle and behaviour. 'These factors likely vary across a person's life, and we believe that some of these originate in childhood. 'We were delighted to contribute data from the Children of the 90s study to this exceptional and insightful research into the genetic architecture of obesity. 'We hope this work will contribute to detecting individuals at high risk of developing obesity at an earlier age, which could have a vast clinical and public health impact in the future.' In 2022, some 64% of adults in England were estimated to be overweight or living with obesity. Last week, MPs on the Health and Social Care Committee launched a review into how the Government is tackling the nation's obesity epidemic. It comes after ministers pledged to 'launch a moonshot to end the obesity epidemic' in the one-year plan to improve the health of the nation.
Yahoo
21-07-2025
- Health
- Yahoo
A genetic test could predict the odds of obesity, allowing for early interventions
A genetic test may one day predict a child's risk of obesity in adulthood, paving the way for early interventions. Certain genetic variants can affect how a person's body stores fat or make them more prone to overeating. Genetic variation can also predict how well a person will respond to different weight loss drugs. In a study published Monday in the journal Nature Medicine, more than 600 researchers from around the world worked together to compile genetic data from more than 5 million people — the largest and most diverse genetic dataset to date. They also used genetic data from 23andMe. From the dataset, the researchers were able to create what's known as a polygenic risk score, which takes into account which genetic variants a person has that have been linked to a higher BMI in adulthood. The score, the researchers said, could be used to predict a person's risk of obesity as an adult — before they even turn 5. 'Childhood is the best time to intervene,' said study co-author Ruth Loos, a professor at the University of Copenhagen's Novo Nordisk Foundation Center for Basic Metabolic Research. (Research conducted at the center is not influenced by drugmaker Novo Nordisk, though some of the study authors had ties to pharmaceutical companies that make weight loss drugs.) The findings come as obesity is rising around the world. Rates of obesity in adults have more than doubled globally since 1990, and adolescent rates have quadrupled, according to the World Health Organization. About 16% of adults worldwide have obesity and the situation is worse in the United States, where more than 40% of adults have obesity, Centers for Disease Control and Prevention statistics show. Twice as effective The new test is not the first that predicts a person's risk of obesity, but Loos and her team showed it was about twice as effective as the method doctors currently use to assess their patients. That polygenetic score can account for about 8.5% of a person's risk for having a high BMI as an adult. The new score increased that to about 17.6%, at least in people with European ancestry. 'That's a pretty powerful risk indicator for obesity, but it still leaves open a lot that is unknown,' said Dr. Roy Kim, a pediatric endocrinologist at Cleveland Clinic Children's who was not involved with the research. Based on this score, more than 80% of a person's risk for obesity can be explained by other factors, such as where they live, what kinds of foods they have access to, and how much they exercise. The test was not nearly as effective in predicting obesity risk in non-Europeans. It explained about 16% of the risk for having a high BMI in East Asian Americans, but just 2.2% in rural Ugandans. About 70% of people whose data was included in the study were of predominantly European ancestry. About 14% were Hispanic and typically had a mix of ancestries. About 8% were of predominantly East Asian descent and just under 5% were of predominantly African ancestry. These samples were predominantly from African American people, who largely had mixed ancestry. Just 1.5% were of predominantly South Asian ancestry. Loos said the new score is a big step forward, but that it's still a prototype. The next step is to collect more — and more diverse — data on people with African ancestry in particular to improve how well the score works for everyone, not just white people. She said the score could offer one indicator — what high blood pressure is to heart disease, for example — that could help predict a person's risk of developing obesity. 'Obesity is not only about genetics, so genetics alone can never accurately predict obesity,' Loos said. 'For the general obesity that we see all over the world, we need other factors such as lifestyle that need to be part of the predictions.' Genetics play a bigger role in severe obesity, meaning a BMI of more than 40, she added. Still, identifying a person's genetic risk early on in childhood and intervening early with lifestyle coaching could make a big difference, she said. Research has shown that about 55% of children with obesity go on to have obesity in adolescence, and that about 80% of those individuals will have obesity in adulthood. 'Behavioral things are really important,' Kim said. 'Their environment, their access to healthy food, exercise opportunities, even their knowledge about healthy foods all affect a person's obesity risk.' How important are genetics, really? Although studies in identical twins have found that genetics can account for as much as 80% of the reason a person has obesity, lifestyle factors still play a huge role, Kim said. 'Even with the same genetic makeup, people can have different body types,' he said. 'From a very young age in my practice, we educate patients about the importance of eating protein-rich foods, a lot of fruits and vegetables and not too many refined carbs.' Dr. Juliana Simonetti, co-director of the Comprehensive Weight Management Program at the University of Utah, has been using genetic testing in her adult patients for about five years. She said understanding a person's genes can help doctors better treat weight gain. 'Obesity is not homogeneous. We have different kinds and different presentations,' said Simonetti, who wasn't involved with the new study. Simonetti uses a person's genes to determine if a patient struggles with satiety, or feeling full. 'They eat but do not feel full,' Simonetti said, adding that this is a disorder caused by genetic mutations affecting certain pathways in the body. People who have these mutations 'tend to have higher weight,' she said. But such mutations do not tell the whole genetic story of obesity, Simonetti said. The genes that a person inherits from either parent, even if they are not mutations, also determine how a person's body stores weight or uses energy. Both can play a big role in obesity risk. Genetic testing is also starting to be able to determine how well certain weight loss drugs will work for a person, Simonetti said, but she added this is just the beginning. 'We are talking about three out of 80 mutations that we can treat,' she said. 'We are getting better, and the more data we have, I'm hopeful that we are going to do a better job in being more precise in understanding treatment responses.' This article was originally published on Solve the daily Crossword
