This is why her and David Harbour's marriage REALLY ended': Following Lily Allen's'revenge album' against her ex-husband, his furious friends hit back at the'false' singer'A common medication sent my sex life roaring back... it's definitely not a rare side effect': Surprising ways women revived their flagging libidos - including a Netflix show dubbed'female Viagra' King Charles is heckled by Andrew protester shouting'how long have you known' - as he and Fergie prepare to leave Royal Lodge for separate houses Buffalo Bills suffer serious blow to Super Bowl hopes as star man Ed Oliver is ruled out'indefinitely' The NBA Mafia betting scandal is the tip of the iceberg. Now match-fixing expert speaks on wider web of sports shame... and who it implicates: 'Dancing with the devil' Woke Dem Jasmine Crockett's secret stock empire exposed - as she plots Senate run Anguish of mother whose son, four, and daughter, six, vanished in Nova Scotia woods six months ago... as cops reject claims a stranger abducted them This is exactly how to lose up to a stone by Christmas. My expert diet helps you slim while you sleep, won't leave you hungry - and no, you don't need Mounjaro or Ozempic! Trump ally and fellow real estate tycoon warns Zohran Mamdani will destroy NYC's housing market: 'That's not affordability, that's insanity' Bionic Woman actress Lindsay Wagner, 76, makes a rare appearance at fan event... see her now I wish my selfish sister had never been born. When she died at 33 after a life of hedonism, she became a saint in our family... I'll never forgive her for it Urgent warning to Gmail users as 183 MILLION passwords are stolen in data breach - here's how to check if your account is affected What HAS happened to Bradley Cooper's face?

The great wildebeest migration, seen from space: satellites and AI are helping count Africa's wildlife The Great Wildebeest Migration is one of the most remarkable natural spectacles on Earth. Each year, immense herds of wildebeest, joined by zebras and gazelles, travel 800-1,000km between Tanzania and Kenya in search of fresh grazing after the rains . This vast, circular journey is the engine of the Serengeti-Mara ecosystem. The migration feeds predators such as lions and crocodiles, fertilises the land and sustains the grasslands. Countless other species, and human livelihoods tied to rangelands and tourism, depend on it.

She has been cast in maternal roles since her teens. Now, playing a mother for the first time since becoming one, she has chosen the part of a woman pushed past the edge of sanity. In "Die My Love," Lawrence, as Grace, vibrates with boredom and fury. The novel "Die, My Love," by the Argentinean writer Ariana Harwicz, is narrated by a wife and new mother who is living in rural France and seems to be losing her mind. Motherhood has inserted an immersion blender into her psyche: lust, repulsion, pleasure, and doom swirl into a single mess. She calls herself a "sodomising rodent" with "bullet-wounds for eyes," and thinks, "When I masturbate I desecrate crypts, and when I rock my baby I say amen, and when I smile I unplug an iron lung." One night, standing in the cold, staring at her family through a sliding door, she thinks, "I'll stop trying to draw blood from a stone. I'll contain my madness, I'll use the bathroom. I'll put my baby to sleep, jerk off my man and postpone my rebellion in favor of a better life." Martin Scorsese saw a brief review of the novel in the some years ago and decided to pick up a copy. He found it to be a "powerful mosaic of the mind," he told me recently. Scorsese is a member of a book club of sorts, with a few other filmmakers, who read with an eye toward adaptation. For "Die, My Love," he imagined casting Jennifer Lawrence in the lead. He'd been amazed by her performance in Darren Aronofsky's bewildering 2017 fantasia, "Mother!" In that surreal film--it's like an allegory set inside an oil painting--Lawrence plays a woman living with her poet husband in an old farmhouse, which is gradually, then apocalyptically, invaded by strangers. "She really is feeling everything that's happening, in what appears to be a dream of some kind," Scorsese said. He and Lawrence had discussed adaptations before. They considered "The Awakening," Kate Chopin's 1899 novel of female liberation, which ends with the protagonist, Edna Pontellier, walking into the sea. "Die, My Love" was like "The Awakening" if it began with Edna already underwater.

Ebeyer published posts about famous people who had realized that they were aphantasic: Glen Keane, one of the leading Disney animators on "The Little Mermaid" and "Beauty and the Beast"; John Green, the author of "The Fault in Our Stars," whose books had sold more than fifty million copies; J. Craig Venter, the biologist who led the first team to sequence the human genome; Blake Ross, who co-created the Mozilla-Firefox web browser when he was nineteen. Ebeyer also wanted the Aphantasia Network to be a place where aphantasics could find recent scientific research. For instance, estimating the strength of a person's imagery had been thoroughly subjective until Joel Pearson, a cognitive neuroscientist at the University of New South Wales, in Australia, devised tests to measure it more precisely. In a paper from 2022, Pearson reported that when people with imagery visualized a bright object their pupils contracted, as though they were seeing a bright object in real life, but the pupils of aphantasics imagining a bright object stayed the same. Another study of his had shown that, although aphantasics had the same fear response (sweating) as typical imagers to a frightening image shown on a screen, when exposed to a frightening story they barely responded at all.

In Brownsville, Texas, some families found a buzzy new school's methods--surveillance of kids, software in lieu of teachers--to be an education in and of itself. At Alpha School's campus in Brownsville, Texas, a student works on exercises in a learning app. One day last fall, Kristine Barrios' 9-year-old daughter got stuck on a lesson in IXL, the personalized learning software that served as her math teacher. She had to multiply three three-digit numbers without using a calculator. Then she had to do it again, her mom says, more than 20 times, without making mistakes. At Alpha School, the private microschool the girl and her younger brother attended in Brownsville, Texas, she had been working a grade level ahead of her age in math, Barrios says. She could do three-digit multiplication correctly most of the time. But whenever she made an error in IXL, the software would determine she needed more practice and assign her more questions. She told her mom that she had asked her "guide," the adult who supervised her classroom in lieu of a teacher, to make an exception and let her move on. She said the guide's reply was that she needed to get it done, that it was expected of her. The adult guides in Alpha's classrooms "don't do any teaching," says the current head of the Brownsville school.

Erotic imagery and curiosity often arise in intimate relationships, especially when there's safety, play, and mutual recognition. It doesn't mean you've done anything "wrong." On the contrary, it shows that your imagination is alive and searching for ways to bridge the gap between closeness and distance, fantasy and reality. You offer me something charged, even a bit embarrassing, and you're watching--will I crumble?

-- Human activity intensity prediction is crucial to many location - based services. Despite tremendous p rogress in modeling d ynamics of human activity, most existing methods overlook physical constraints of spatial interaction, leading to uninterpretable spatial correlations and over - smoothing phenomenon . To address these limitations, this work proposes a physics - informed deep learning framework, namely Gravity - informed Spatiotemporal Transformer (Gravityformer) by integrat ing the universal law of gravitation to refin e transformer attention. Specifically, it (1) estimates two spatially explicit mass parameters based on spatiotemporal embedding feature, (2) models the spatial interaction in end - to - end neural network using proposed adaptive gravity model to learn the physic al constrain t, and (3) utilizes the learned spatial interaction to guide and mitigate the over - smoothing phenomenon in transformer attention. Moreover, a parallel spatiotemporal graph convolution transformer is proposed for achieving a balance between coupled spatial and temporal learning. Systematic experiments on six real - world large - scale activity datasets demonstrate the quantitative and qualitative superiority of our model over state - of - the - art benchmarks. Additionally, the learned gravity attention matrix can be not only disentangled and interpreted based on geographical laws, but also improved the generalization in zero - shot cross - region inference . This work provides a novel insight into integrating physical laws with deep learning for spatiotemporal prediction . Index Terms -- Human activity intensity prediction; Gravity model; Spatial interaction; Physics - informed machine learning; Over - smoothing phenomenon; Spatiotemporal graph neural network . This work is supported by the National Natural Science Foundation of China ( Grant # 42430106, 42371468, 424B2013) . Y i Wang, Zhenghong Wang, Fan Zhang, Chengling Tang, Weiyu Zhang and Yu Liu are with Institute of Remote Sensing and Geographic Information System, School of Earth and Space Sciences, Peking University, Beijing 100871, China. Chaogui Kang is with National Engineering Research Center of Geographic Information System, China University of Geosciences (Wuhan) 430074, China. Sijie Ruan is with School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China . Di Zhu and Zhongfu Ma are with Department of Geography, Environment and Society, University of Minnesota, Twin Cities, Minneapolis, MN 55455, USA . Y u Zheng is with JD iCity, JD Technology, Beijing 100176, China . P hilip S. Yu is with Department of Computer Science, University of Illinois Chicago, Chicago 60607, USA .

Simulating society with large language models (LLMs), we argue, requires more than generating plausible behavior; it demands cognitively grounded reasoning that is structured, revisable, and traceable. LLM-based agents are increasingly used to emulate individual and group behavior, primarily through prompting and supervised fine-tuning. Yet current simulations remain grounded in a behaviorist "demographics in, behavior out" paradigm, focusing on surface-level plausibility. As a result, they often lack internal coherence, causal reasoning, and belief traceability, making them unreliable for modeling how people reason, deliberate, and respond to interventions. To address this, we present a conceptual modeling paradigm, Generative Minds (GenMinds), which draws from cognitive science to support structured belief representations in generative agents. To evaluate such agents, we introduce the RECAP (REconstructing CAusal Paths) framework, a benchmark designed to assess reasoning fidelity via causal traceability, demographic grounding, and intervention consistency. These contributions advance a broader shift: from surface-level mimicry to generative agents that simulate thought, not just language, for social simulations.

Travel chaos as unpaid air traffic controllers abandon towers... while Thanksgiving threat looms Beloved TikTok star's cause of death revealed after she moved to LA to seek fame aged 19 Inside Andrew's family summit: How Fergie wailed and'melted down' at title loss, Beatrice and Eugenie were'blindsided' and now daughters' assets face'ethics check' to avoid more scandal: BARBARA DAVIES I have no sympathy for Britney Spears. What if her latest stunt had killed a kid? It's time to admit the truth about this public menace: KENNEDY Cardiologist reveals the five'healthy' foods he would never eat Professional gambler made staggering claims about Chauncey Billups' poker games two YEARS before his arrest Amy Schumer, 44, has'lost at least 40lbs' thanks to Mounjaro as she flashes tiny waistline in selfie Statins taken by 40 million Americans recalled after it's discovered they aren't releasing medication effectively I got the body of my dreams at 51 by following 9 simple rules, says beauty guru ROSIE GREEN. They're easy, non-negotiable... and not what you expect. Outrage as New York mayoral shoo-in Zohan Mamdani plans to bring back Bill de Blasio's boondoggle program to sub social workers for cops Experts reveal if a break up can really cause a brain aneurysm...after Kim Kardashian's startling diagnosis NBA star Terry Rozier's secret past explodes into public after gambling bust - and it's far more sordid than anyone imagined I think I've discovered Meghan's secret plan for if - or when - William strips away the Sussexes' royal titles: SHARON HUNT Thousands of objects sent by a non-human intelligence may have been spying on the world's nuclear tests all the way back in the 1940s.

A new artificial intelligence-powered tool can help researchers determine how well an enzyme fits with a desired target, helping them find the best enzyme and substrate combination for applications from catalysis to medicine to manufacturing. Led by Huimin Zhao, a professor of chemical and biomolecular engineering at the University of Illinois Urbana-Champaign, the researchers developed EZSpecificity using new enzyme-substrate pair data and a new machine learning algorithm. They have made the tool freely available online and published their results in the journal Nature. "If we want a certain product using an enzyme, we want to use the best enzyme and substrate combination," said Zhao, who also is the director of the NSF Molecule Maker Lab Institute and of the NSF iBioFoundry at the University of Illinois "EZSpecificity is an AI model that can analyze an enzyme sequence and then predict which substrate best can fit into that enzyme. It is highly complementary to the CLEAN AI model that we developed to predict an enzyme's function from its sequence more than two years ago."