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Categories: Energy: Batteries, Mathematics: Modeling

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Scientists introduce a large language model-based AI system that revolutionizes chemistry by integrating 18 advanced tools for tasks like organic synthesis and drug discovery.

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Emergency departments nationwide are overcrowded and overtaxed, but a new study suggests artificial intelligence (AI) could one day help prioritize which patients need treatment most urgently.

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Researchers have harnessed the technology behind foundation models, which power tools like ChatGPT, to discover new cancer imaging biomarkers that could transform how patterns are identified from radiological images. Improved identification of such patterns can greatly impact the early detection and treatment of cancer.

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Researchers have debunked a 75-year-old theory about how humans determine where sounds are coming from, and it could unlock the secret to creating a next generation of more adaptable and efficient hearing devices ranging from hearing aids to smartphones.

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Charge-recharge cycling of lithium-superrich iron oxide, a cost-effective and high-capacity cathode for new-generation lithium-ion batteries, can be greatly improved by doping with readily available mineral elements.

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Researchers have developed an AI method that improves the identification of toxic chemicals -- based solely on knowledge of the molecular structure. The method can contribute to better control and understanding of the ever-growing number of chemicals used in society, and can also help reduce the amount of animal tests.

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A study describes a new computer algorithm which can be applied to Earth System Models to drastically reduce the time needed to prepare these in order to make accurate predictions of future climate change. During tests on models used in IPCC simulations, the algorithm was on average 10 times faster at spinning up the model than currently-used approaches, reducing the time taken to achieve equilibrium from many months to under a week.

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A new computer model uses a better artificial intelligence process to measure snow and water availability more accurately across vast distances in the West, information that could someday be used to better predict water availability for farmers and others. The researchers predict water availability from areas in the West where snow amounts aren't being physically measured.

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Researchers have demonstrated that ferromagnetism, an ordered state of atoms, can be induced by increasing particle motility and that repulsive forces between atoms are sufficient to maintain it. The discovery not only extends the concept of active matter to quantum systems but also contributes to the development of novel technologies that rely on the magnetic properties of particles, such as magnetic memory and quantum computing.

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Elucidating the relationship between the sequences of non-coding regulatory elements and their target genes is key to understanding gene regulation and its variation between plant species and ecotypes. Now, an international research team developed deep learning models that link gene sequence data with mRNA copy number for several plant species and predicted the regulatory effect of gene sequence variation.

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Two of the biggest challenges faced by new and potential electric vehicle (EV) drivers are range anxiety and speed of charging, but these shouldn't have to be challenges at all. Researchers discovered that a change in refueling mindset, rather than improving the size or performance of the battery, could be the answer to these concerns.

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Cleveland Clinic researchers developed an artficial intelligence (AI) model that can determine the best combination and timeline to use when prescribing drugs to treat a bacterial infection, based solely on how quickly the bacteria grow given certain perturbations. PNAS recently published their findings.

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Estuaries -- where freshwater rivers meet the salty sea -- are great locations for birdwatching and kayaking. In these areas, waters containing different salt concentrations mix and may be sources of sustainable, 'blue' osmotic energy. Researchers report creating a semipermeable membrane that harvests osmotic energy from salt gradients and converts it to electricity. The new design had an output power density more than two times higher than commercial membranes in lab demonstrations.

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A nontoxic separation process recovers critical minerals from electronic scrap waste.

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Researchers have developed a method to use an image generation AI model to create realistic images of single cells, which are then used as 'synthetic data' to train an AI model to better carry out single-cell segmentation.

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A sensing technology that can assess the quality of components in fields such as aerospace could transform UK industry.

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Atrial fibrillation is the most common cardiac arrhythmia worldwide with around 59 million people concerned in 2019. This irregular heartbeat is associated with increased risks of heart failure, dementia and stroke. It constitutes a significant burden to healthcare systems, making its early detection and treatment a major goal. Researchers have recently developed a deep-learning model capable of predicting the transition from a normal cardiac rhythm to atrial fibrillation. It gives early warnings on average 30 minutes before onset, with an accuracy of around 80%. These results pave the way for integration into wearable technologies, allowing early interventions and better patient outcomes.

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The study highlights the rapid progress and transformative potential of AI in weather prediction.

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Lithium salts make batteries powerful but expensive. An ultralow-concentration electrolyte based on the lithium salt LiDFOB may be a more economical and more sustainable alternative. Cells using these electrolytes and conventional electrodes have been demonstrated to have high performance. In addition, the electrolyte could facilitate both production and recycling of the batteries.

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As early adopters of electric vehicles (EVs) trade up for the latest models, the used EV market is beginning to mature in the United States. Yet many potential buyers, particularly low-income drivers, are skeptical of EV's conveniences and are put off by the price.