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Categories: Environmental: Wildfires, Mathematics: Modeling

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Ecology: Nature Environmental: Ecosystems Environmental: General Environmental: Wildfires Geoscience: Environmental Issues
Published

Forest carbon storage has declined across much of the Western U.S., likely due to drought and fire      (via sciencedaily.com)     Original source 

Forests have been embraced as a natural climate solution, due to their ability to soak up carbon dioxide from the atmosphere as they grow, locking it up in their trunks, branches, leaves, and roots. But a new study confirms widespread doubts about the potential for most forests in the Western US to help curb climate change. The paper analyzed trends in carbon storage across the American West from 2005 to 2019.

Mathematics: Modeling
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Researchers customize AI tools for digital pathology      (via sciencedaily.com)     Original source 

Scientists developed and tested new artificial intelligence (AI) tools tailored to digital pathology--a rapidly growing field that uses high-resolution digital images created from tissue samples to help diagnose disease and guide treatment.

Computer Science: General Mathematics: Modeling
Published

Researchers introduce generative AI for databases      (via sciencedaily.com)     Original source 

Researchers have developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes. Their method combines probabilistic AI models with the programming language SQL to provide faster and more accurate results than other methods.

Mathematics: Modeling
Published

Innovative, highly accurate AI model can estimate lung function just by using chest x-rays      (via sciencedaily.com)     Original source 

An artificial intelligence (AI) model that can estimate with high accuracy a person's lung function just by using a chest radiograph has been successfully developed.

Biology: Biochemistry Mathematics: Modeling
Published

Deep machine-learning speeds assessment of fruit fly heart aging and disease, a model for human disease      (via sciencedaily.com)     Original source 

Drosophila -- known as fruit flies -- are a valuable model for human heart pathophysiology, including cardiac aging and cardiomyopathy. However, a choke point in evaluating fruit fly hearts is the need for human intervention to measure the heart at moments of its largest expansion or its greatest contraction to calculate cardiac dynamics. Researchers now show a way to significantly cut the time needed for that analysis while utilizing more of the heart region, using deep learning and high-speed video microscopy.

Computer Science: General Mathematics: Modeling Physics: General Space: Astrophysics Space: Exploration Space: General Space: The Solar System
Published

Machine learning could aid efforts to answer long-standing astrophysical questions      (via sciencedaily.com)     Original source 

Physicists have developed a computer program incorporating machine learning that could help identify blobs of plasma in outer space known as plasmoids. In a novel twist, the program has been trained using simulated data.

Energy: Alternative Fuels Environmental: General Mathematics: Modeling
Published

Moving beyond the 80-year-old solar cell equation      (via sciencedaily.com)     Original source 

Physicists have made a significant breakthrough in solar cell technology by developing a new analytical model that improves the understanding and efficiency of thin-film photovoltaic (PV) devices.

Mathematics: Modeling
Published

AI model finds the cancer clues at lightning speed      (via sciencedaily.com)     Original source 

AI model finds the cancer clues at lightning speed. Researchers have developed an AI model that increases the potential for detecting cancer through sugar analyses. The AI model is faster and better at finding abnormalities than the current semi-manual method.

Mathematics: Modeling
Published

Can A.I. tell you if you have osteoporosis? Newly developed deep learning model shows promise      (via sciencedaily.com)     Original source 

Researchers have developed a novel deep learning algorithm that outperformed existing computer-based osteoporosis risk prediction methods, potentially leading to earlier diagnoses and better outcomes for patients with osteoporosis risk.

Mathematics: Modeling
Published

Study reveals why AI models that analyze medical images can be biased      (via sciencedaily.com)     Original source 

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.

Biology: Biochemistry Biology: Biotechnology Biology: Cell Biology Biology: General Biology: Genetics Biology: Molecular Mathematics: Modeling
Published

New deep-learning model outperforms Google AI system in predicting peptide structures      (via sciencedaily.com)     Original source 

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.

Chemistry: Biochemistry Environmental: Wildfires
Published

Wildfires increasingly threaten oil and gas drill sites, compounding potential health risks      (via sciencedaily.com)     Original source 

More than 100,000 oil and gas wells across the western U.S. are in areas burned by wildfires in recent decades, a new study has found, and some 3 million people live next to wells that in the future could be in the path of fires worsened by climate change.

Ecology: General Ecology: Invasive Species Ecology: Nature Ecology: Research Ecology: Trees Environmental: Ecosystems Environmental: General Environmental: Wildfires
Published

Fuel treatments reduce future wildfire severity      (via sciencedaily.com)     Original source 

There is a common belief that prescribed burning, thinning trees, and clearing underbrush reduce risks of the severity of future fires. But is that true? A new project analyzing 40 studies where wildfire burned into different vegetation treatments, spanning 11 western states. Researchers found overwhelming evidence that in seasonally dry mixed conifer forests in the western U.S., reducing surface and ladder fuels and tree density through thinning, coupled with prescribed burning or pile burning, could reduce future wildfire severity by more than 60% relative to untreated areas.

Chemistry: Biochemistry Computer Science: Artificial Intelligence (AI) Computer Science: Virtual Reality (VR) Mathematics: Modeling Offbeat: Computers and Math Offbeat: General
Published

Prying open the AI black box      (via sciencedaily.com)     Original source 

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.

Biology: General Biology: Zoology Mathematics: Modeling
Published

Unifying behavioral analysis through animal foundation models      (via sciencedaily.com)     Original source 

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.

Mathematics: General Mathematics: Modeling Offbeat: Computers and Math Offbeat: General
Published

Can AI learn like us?      (via sciencedaily.com)     Original source 

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.

Computer Science: General Mathematics: Modeling
Published

Simplicity versus adaptability: Understanding the balance between habitual and goal-directed behaviors      (via sciencedaily.com)     Original source 

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.

Chemistry: Biochemistry Chemistry: General Chemistry: Inorganic Chemistry Chemistry: Organic Chemistry Mathematics: Modeling Physics: Optics
Published

Custom-made molecules designed to be invisible while absorbing near-infrared light      (via sciencedaily.com)     Original source 

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.

Computer Science: Artificial Intelligence (AI) Computer Science: General Engineering: Robotics Research Mathematics: Modeling
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Researchers use large language models to help robots navigate      (via sciencedaily.com)     Original source 

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.