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Categories: Geoscience: Earthquakes, Mathematics: Modeling

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Researchers have created digital babies to better understand infants' health in their critical first 180 days of life. The team created 360 advanced computer models that simulate the unique metabolic processes of each baby.

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Researchers are adding a new wrinkle to a long-held belief about what causes earthquakes in the first place.

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Have you ever wished you could understand what your dog is trying to say to you? Researchers are exploring the possibilities of AI, developing tools that can identify whether a dog's bark conveys playfulness or aggression.

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Researchers have developed a model that enables computers to interpret and understand human emotions, utilizing principles of mathematical psychology. In the future, the model can help the computer to adapt its own behavior and guide an irritated or anxious user in different ways. The implications of such technology are profound, offering a glimpse into a future where computers are not merely tools, but empathetic partners in user interaction.

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Biological processes depend on puzzle pieces coming together and interacting. Under specific conditions, these interactions can create something new without external input. This is called self-organization, as seen in a school of fish or a flock of birds. Interestingly, the mammalian embryo develops similarly. Scientists now introduce a mathematical framework that analyzes self-organization from a single cell to a multicellular organism.

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A novel, human-inspired approach to training artificial intelligence (AI) systems to identify objects and navigate their surroundings could set the stage for the development of more advanced AI systems to explore extreme environments or distant worlds, according to new research.

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As more and more people drive electric cars, congestion and queues can occur when many people need to charge at the same time. A new study shows how AI-controlled charging stations, through smart algorithms, can offer electric vehicle users personalized prices, and thus minimize both price and waiting time for customers. But the researchers point to the importance of taking the ethical issues seriously, as there is a risk that the artificial intelligence exploits information from motorists.

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A team of researchers have developed a new machine-learning method that detects hate speech on social media platforms with 88 per cent accuracy, saving employees from hundreds of hours of emotionally damaging work.

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During an earthquake, soil can weaken through subsidence and liquefaction. These processes can cause buildings to collapse as the soil becomes unable to support their weight. Researchers have now developed a model that predicts soil-bearing strength and thickness to identify stable construction sites and reduce structural risks. Additionally, the model can also predict other soil conditions in real-time and function as an early-warning system to identify potential hazards.

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Researchers recently published findings that could lay the groundwork for applying quantum computing methods to protein structure prediction.

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Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials science and more.

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Researchers have developed an assistive machine learning model that greatly improves the ability of medical professionals to read the electroencephalography (EEG) charts of intensive care patients. Because EEG readings are the only method for knowing when unconscious patients are in danger of suffering a seizure or are having seizure-like events, the computational tool could help save thousands of lives each year.

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Researchers uncover the unique mechanisms that resulted in severe tsunamis in Iida Bay caused by the 2024 Noto Peninsula Earthquake. The recent tsunamis in Iida Bay were locally amplified due to various factors, including ocean floor topology, the shape of the coastline, the location of coastal facilities, and seismic mechanisms associated with earthquakes, report scientists.

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Researchers developed a computer vision framework for posture estimation and identity tracking which they can use in indoor environments as well as in the wild. They have thus taken an important step towards markerless tracking of animals in the wild using computer vision and machine learning.

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With generative artificial intelligence (GenAI) transforming the social interaction landscape in recent years, large language models (LLMs), which use deep-learning algorithms to train GenAI platforms to process language, have been put in the spotlight. A recent study found that LLMs perform more like the human brain when being trained in more similar ways as humans process language, which has brought important insights to brain studies and the development of AI models.

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In a new study, a team of researchers used research on fossilizing techniques to create a new method for sealing cracks and fractures in rocks and bedrock using a 'concretion-forming resin'. This innovative technique has applications in a wide range of industries, from tunnel construction to long-term underground storage of hazardous materials.

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Researchers have unveiled a novel method to prepare quantum operations on a given quantum computer, using a machine learning generative model to find the appropriate sequence of quantum gates to execute a quantum operation. The study marks a significant step forward in unleashing the full extent of quantum computing.

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Researchers have built a prototype fiber optic gyroscope for high resolution, real-time monitoring of ground rotations caused by earthquakes in the active volcanic area of Campi Flegrei in Naples, Italy. A better understanding of the seismic activity in this highly populated area could improve risk assessment and might lead to improved early warning systems.

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Groundbreaking research has provided new insight into the tectonic plate shifts that create some of the Earth's largest earthquakes and tsunamis.

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Large language model-based chatbots can't effectively recognize users' motivation when they are hesitant about making healthy behavior changes, but they can support those who are committed to take action, say researchers.