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Categories: Mathematics: Modeling

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Deep within every piece of magnetic material, electrons dance to the invisible tune of quantum mechanics. Their spins, akin to tiny atomic tops, dictate the magnetic behavior of the material they inhabit. This microscopic ballet is the cornerstone of magnetic phenomena, and it's these spins that a team of researchers has learned to control with remarkable precision, potentially redefining the future of electronics and data storage.

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In the same way that chatbots sometimes 'hallucinate,' or make things up, machine learning models designed for scientific applications can sometimes present misleading or downright false results. Researchers now present a new statistical technique for safely using AI predictions to test scientific hypotheses.

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Scientists used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.

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First of its kind AI-model can help policy-makers efficiently identify and prioritize houses for retrofitting and other decarbonizing measures.

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New studies support the idea that the brain uses a process similar to a machine-learning approach known as 'self-supervised learning.' This type of machine learning allows computational models to learn about visual scenes based solely on the similarities and differences between them, with no labels or other information.

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As urbanization advances around the globe, the quality of the urban physical environment will become increasingly critical to human well-being and to sustainable development initiatives. However, measuring and tracking the quality of an urban environment, its evolution and its spatial disparities is difficult due to the amount of on-the-ground data needed to capture these patterns.

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Researchers report that a single, simplified model can predict population fluctuations in three unrelated realms: urban employment, human gut microbiomes and tropical forests. The model will help economists, ecologists, public health authorities and others predict and respond to variability in multiple domains.

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A new study reveals the pitfalls of deep generative models when they are tasked with solving engineering design problems. The researchers say if mechanical engineers want help from AI for novel ideas and designs, they'll have to refocus those models beyond 'statistical similarity.' 

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An international team of scientists has recently developed a novel type of nano engine made of DNA. It is driven by a clever mechanism and can perform pulsing movements. The researchers are now planning to fit it with a coupling and install it as a drive in complex nano machines.

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Proteins are important molecules that perform a variety of functions essential to life. To function properly, many proteins must fold into specific structures. However, the way proteins fold into specific structures is still largely unknown. Researchers have developed a novel physical theory that can accurately predict how proteins fold. Their model can predict things previous models cannot. Improved knowledge of protein folding could offer huge benefits to medical research, as well as to various industrial processes.

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Computational models of hearing and vision can build up their own idiosyncratic 'invariances' -- meaning they respond the same way to stimuli with very different features, according to scientists.

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The synovium is a membrane-like structure that lines the knee joint and helps to keep the joint happy and healthy, mainly by producing and maintaining synovial fluid. Inflammation of this tissue is implicated in the onset and progression of arthritic diseases such as rheumatoid and osteoarthritis. Therefore, treatments that target the synovium are promising in treating these diseases. However, we need better models in the laboratory that allow us to find and test new treatments. We have developed an organ-on-a-chip based model of the human synovium, and its associated vasculature, to address this need.

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Artificial intelligence, AI, which finds patterns in complex biological data could eventually contribute to the development of individually tailored healthcare. Researchers have developed an AI-based method applicable to various medical and biological issues. Their models can for instance accurately estimate people's chronological age and determine whether they have been smokers or not.

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Models built on machine learning in health care can be victims of their own success, according to researchers. Their study assessed the impact of implementing predictive models on the subsequent performance of those and other models.

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Scientists have developed new tools, based on AI language models, that can characterize subtle signatures in the speech of patients diagnosed with schizophrenia.

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A team of computer scientists has created a neural network that can explain how it reaches its predictions. The work reveals what accounts for the functionality of neural networks--the engines that drive artificial intelligence and machine learning--thereby illuminating a process that has largely been concealed from users.   

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Applying machine learning to find the properties of atomic pieces of geometry shows how AI has the power to accelerate discoveries in maths.

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Big data and artificial intelligence (AI) are being used to model hidden patterns in nature, not just for one bird species, but for entire ecological communities across continents. And the models follow each species’ full annual life cycle, from breeding to fall migration to non-breeding grounds, and back north again during spring migration.

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Robots helped achieve a major breakthrough in our understanding of how insect flight evolved. The study is a result of a six-year long collaboration between roboticists and biophysicists.

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A research team has provided irrefutable proof that certain spherical vortices exist in a stable state.