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Categories: Mathematics: General, Mathematics: Modeling

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Researchers have found that artificial intelligence models that are most accurate at predicting race and gender from X-ray images also show the biggest 'fairness gaps' -- that is, discrepancies in their ability to accurately diagnose images of people of different races or genders.

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Researchers have developed a deep-learning model, called PepFlow, that can predict all possible shapes of peptides -- chains of amino acids that are shorter than proteins, but perform similar biological functions. Peptides are known to be highly flexible, taking on a wide range of folding patterns, and are thus involved in many biological processes of interest to researchers in the development of therapeutics.

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Meet SQUID, a new computational tool. Compared with other genomic AI models, SQUID is more consistent, reduces background noise, and can yield better predictions regarding critical mutations. The new system aims to bring scientists closer to their findings' true medical implications.

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Behavioral analysis can provide a lot of information about the health status or motivations of a living being. A new technology makes it possible for a single deep learning model to detect animal motion across many species and environments. This 'foundational model', called SuperAnimal, can be used for animal conservation, biomedicine, and neuroscience research.

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Scientists have developed a new, more energy-efficient way for AI algorithms to process data. His model may become the basis for a new generation of AI that learns like we do. Notably, these findings may also lend support to neuroscience theories surrounding memory's role in learning.

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Looking under the microscope, a group of cells slowly moves forward in a line, like a train on the tracks. The cells navigate through complex environments. A new approach now shows how they do this and how they interact with each other.

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Scientists have proposed a new AI method in which systems of habitual and goal-directed behaviors learn to help each other. Through computer simulations that mimicked the exploration of a maze, the method quickly adapts to changing environments and also reproduced the behavior of humans and animals after they had been accustomed to a certain environment for a long time. The study not only paves the way for the development of systems that adapt quickly and reliably in the burgeoning field of AI, but also provides clues to how we make decisions in the fields of neuroscience and psychology.

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Researchers used theoretical calculations assessing electron orbital symmetry to synthesize new molecule designed to be both transparent and colorless while absorbing near-infrared light. This compound demonstrates the first systematic approach to producing such materials and have applications in advanced electronics. This compound also shows semiconducting properties.

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A technique can plan a trajectory for a robot using only language-based inputs. While it can't outperform vision-based approaches, it could be useful in settings that lack visual data to use for training.

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Data assimilation is an important mathematical discipline in earth sciences, particularly in numerical weather prediction (NWP). However, conventional data assimilation methods require significant computational resources. To address this, researchers developed a novel method to solve data assimilation on quantum computers, significantly reducing the computation time. The findings of the study have the potential to advance NWP systems and will inspire practical applications of quantum computers for advancing data assimilation.

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Boys are good at math, girls not so much? A study has analyzed the social mechanisms that contribute to the gender gap in math confidence. While peer comparisons seem to play a crucial role for boys, girls' subjective evaluations are more likely to be based on objective performance.

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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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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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Researchers have developed a platform for the interactive evaluation of AI-powered chatbots such as ChatGPT. A team of computer scientists, engineers, mathematicians and cognitive scientists developed an open-source evaluation platform called CheckMate, which allows human users to interact with and evaluate the performance of large language models (LLMs).

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A team used experiments and simulations to quantify and predict how knit fabric response can be programmed. By establishing a mathematical theory of knitted materials, the researchers hope that knitting -- and textiles in general -- can be incorporated into more engineering and manufacturing applications.

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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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An international research team has sparked interest in the scientific community with results in quantum physics. In their current study, the researchers reinterpret the Higgs mechanism, which gives elementary particles mass and triggers phase transitions, using the concept of 'magnetic quivers.'

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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.