A research team from the Xinjiang Technical Institute of Physics and Chemistry of the Chinese Academy of Sciences has made strides in the theoretical design of nonlinear optical (NLO) materials by ...

Researchers at University of Toronto Engineering, led by Professor Yu Zou, are leveraging machine learning to improve additive manufacturing, also commonly known as 3D printing. In a new paper, ...

Read more about Industry 4.0 energy systems get security boost with AI and blockchain integration on Devdiscourse ...

Neuroblastoma is the most common solid tumor in infants and accounts for nearly 15% of all pediatric cancer-related deaths. Despite decades of progress in surgery, chemotherapy, and stem cell ...

(a) Conventional neuron models used in reservoir computing. Artificial neural networks (ANNs) comprise of neuron models that sum up weighted inputs, filter the value through an activation function, ...

Underpinnings and advantages of the scDiffEq model The new machine learning-based framework developed by the researchers models how cells change over time using neural stochastic differential ...

Scientists at the U.S. Department of Energy's (DOE) Brookhaven National Laboratory have developed a new machine learning framework that can accelerate the search for better catalysts—the materials ...

Urea is an extremely important chemical, especially for fertilizers. But, making urea is energy intensive and relies heavily ...

For decades, scientists have relied on structure to understand protein function. Tools like AlphaFold have revolutionized how researchers predict and design folded proteins, allowing for new ...

Researchers from GIM and Graphic Era have developed an innovative AI framework assisting retail businesses in adapting to ...