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Categories: Environmental: Wildfires, Mathematics: Modeling

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Researchers have developed a sprayable gel that creates a shield to protect buildings from wildfire damage. It lasts longer and is more effective than existing commercial options.

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An artificial intelligence algorithm can allow researchers to more efficiently use 3D printing to manufacture intricate structures. The development could allow for more seamless use of 3D printing for complex designs in everything from artificial organs to flexible electronics and wearable biosensors. As part of the study, the algorithm learned to identify, and then print, the best versions of kidney and prostate organ models, printing out 60 continually improving versions.

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Artificial intelligence (AI) has exploded in popularity as of late. But just like a human, it's hard to read an AI model's mind. Explainable AI (XAI) could help us do just that by providing justification for a model's decisions. And now, researchers are using XAI to scrutinize predictive AI models more closely, which could help make better antibiotics.

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A multidisciplinary team has developed an action plan to help patients with respiratory diseases mitigate the consequences of poor air quality from wildfires.

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Low- and moderate-severity forest wildfires can reduce the intensity of future fires, according to new research on 'reburns.'

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A new machine learning model can predict autism in young children from relatively limited information. The model can facilitate early detection of autism, which is important to provide the right support.

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A mathematical framework that builds on the economic theory of hidden-action models provides insight into how the unobservable nature of effort and risk shapes investigators' research strategies and the incentive structures within which they work, according to a new study.

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Researchers simulated social norms with a supercomputer. Their findings contribute to a deeper understanding of the evolution of social norms and their role in fostering cooperative behavior.

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Researchers discover that while artificial intelligence (AI) tools can make accurate diagnoses from textbook-like descriptions of genetic diseases, the tools are significantly less accurate when analyzing summaries written by patients about their own health. These findings demonstrate the need to improve these AI tools before they can be applied in health care settings to help make diagnoses and answer patient questions.

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Unprecedented wildfires in Canada and parts of Amazonia last year were at least three times more likely due to climate change and contributed to high levels of CO2 emissions from burning globally, according to the a new systematic review. The State of Wildfires report takes stock of extreme wildfires of the 2023-2024 fire season (March 2023-February 2024), explains their causes, and assesses whether events could have been predicted. It also evaluates how the risk of similar events will change in future under different climate change scenarios.

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New research explains the mathematics behind how initial predispositions and additional information affect decision making.

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Large Language Models (LLMs) are entirely controllable through human prompts and lack 'emergent abilities'; that is, the means to form their own insights or conclusions. Increasing model size does not lead LLMs to gain emergent reasoning abilities, meaning they will not develop hazardous abilities and therefore do not pose an existential threat. A new study sheds light on the (until now unexplained) capabilities and shortcomings of LLMs, including the need for carefully engineered prompts to exhibit good performance.

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Climate-driven wildfire events are rapidly transferring harmful particulate matter containing toxic chemicals over long distances, compromising air quality in the New Jersey and New York City areas, according to recent research.

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A new artificial intelligence model can predict how different proteins may bind to DNA.

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Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use machine learning in computational biology, understanding model behavior remains crucial for uncovering the underlying biological mechanisms in health and disease. Researchers now propose guidelines that outline pitfalls and opportunities for using interpretable machine learning methods to tackle computational biology problems.

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In 2023, roughly 60,000 firework shells exploded above Manhattan's East River as part of Macy's Fourth of July show. The resulting air pollutant levels were many times higher in the hours after the display than those seen when smoke from a Canadian wildfire had blanketed the area a month before, according to the results of a new study.

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To protect the Amazon and support the wellbeing of its people, its economy needs to shift from environmentally harmful production to a model built around the diversity of indigenous and rural communities, and standing forests.

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With GROVER, a new large language model trained on human DNA, researchers could now attempt to decode the complex information hidden in our genome. GROVER treats human DNA as a text, learning its rules and context to draw functional information about the DNA sequences.

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Thermometer, a new calibration technique tailored for large language models, can prevent LLMs from being overconfident or underconfident about their predictions. The technique aims to help users know when a model should be trusted.

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A new study places the origin of the Imazighen in the Epipaleolithic, more than twenty thousand years ago. The research concludes that the genetic origin of the current Arab population of north Africa is far more recent than previously believed, placing it in the seventh century AD. The team has designed an innovative demographic model that uses artificial intelligence to analyze the complete genomes of the two populations.