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Categories: Engineering: Biometric, Mathematics: Modeling
Published Researchers use AI to find new magnetic materials without critical elements
(via sciencedaily.com) A team of scientists developed a new machine learning model for discovering critical-element-free permanent magnet materials based on the predicted Curie temperature of new material combinations.
Published Surpassing the human eye: Machine learning image analysis rapidly determines chemical mixture composition
(via sciencedaily.com) Machine learning model provides quick method for determining the composition of solid chemical mixtures using only photographs of the sample.
Published AI models are powerful, but are they biologically plausible?
(via sciencedaily.com) Researchers hypothesize that a powerful type of AI model known as a transformer could be implemented in the brain through networks of neuron and astrocyte cells. The work could offer insights into how the brain works and help scientists understand why transformers are so effective at machine-learning tasks.
Published Researchers use mathematical modeling and dynamic biomarkers to characterize metastatic disease during adaptive therapy
(via sciencedaily.com) Researchers demonstrate how mathematical modeling combined with dynamic biomarkers can be used to characterize metastatic disease and identify appropriate therapeutic approaches to improve patient outcomes.
Published Distribution of genetic information during bacterial cell division
(via sciencedaily.com) A mathematical model provides new insights into the distribution of genetic information during bacterial cell division
Published Artificial intelligence designs advanced materials
(via sciencedaily.com) Scientists pioneer a new machine learning model for corrosion-resistant alloy design.
Published Tool finds bias in state-of-the-art generative AI model
(via sciencedaily.com) Researchers introduce a new tool to measure bias in text-to-image AI generation models, which they have used to quantify bias in the state-of-the-art model Stable Diffusion.
Published Turning ChatGPT into a 'chemistry assistant'
(via sciencedaily.com) Developing new materials requires significant time and labor, but some chemists are now hopeful that artificial intelligence (AI) could one day shoulder much of this burden. In a new study, a team prompted a popular AI model, ChatGPT, to perform one particularly time-consuming task: searching scientific literature. With that data, they built a second tool, a model to predict experimental results.
Published New model reduces bias and enhances trust in AI decision-making and knowledge organization
(via sciencedaily.com) Researchers have developed a new explainable artificial intelligence (AI) model to reduce bias and enhance trust and accuracy in machine learning-generated decision-making and knowledge organization.
Published Self-supervised AI learns physics to reconstruct microscopic images from holograms
(via sciencedaily.com) Researchers have unveiled an artificial intelligence-based model for computational imaging and microscopy without training with experimental objects or real data. The team introduced a self-supervised AI model nicknamed GedankenNet that learns from physics laws and thought experiments. Informed only by the laws of physics that universally govern the propagation of electromagnetic waves in space, the researchers taught their AI model to reconstruct microscopic images using only random artificial holograms -- synthesized solely from 'imagination' without relying on any real-world experiments, actual sample resemblances or real data.
Published How good is that AI-penned radiology report?
(via sciencedaily.com) New study identifies concerning gaps between how human radiologists score the accuracy of AI-generated radiology reports and how automated systems score them. Researchers designed two novel scoring systems that outperform current automated systems that evaluate the accuracy of AI narrative reports. Reliable scoring systems that accurately gauge the performance of AI models are critical for ensuring that AI continues to improve and that clinicians can trust them.
Published Deep learning for new protein design
(via sciencedaily.com) Deep learning methods have been used to augment existing energy-based physical models in 'do novo' or from-scratch computational protein design, resulting in a 10-fold increase in success rates verified in the lab for binding a designed protein with its target protein. The results will help scientists design better drugs against diseases like cancer and COVID-19.
Published New method simplifies the construction process for complex materials
(via sciencedaily.com) A new technique incorporates many different building blocks of cellular metamaterials into one unified graph-based representation. This can be used to make a user-friendly interface that can quickly and easily model metamaterials, edit the structures, and simulate their properties.
Published Scientists uncover a surprising connection between number theory and evolutionary genetics
(via sciencedaily.com) An interdisciplinary team of mathematicians, engineers, physicists, and medical scientists has uncovered an unexpected link between pure mathematics and genetics, that reveals key insights into the structure of neutral mutations and the evolution of organisms.
Published Researchers successfully train a machine learning model in outer space for the first time
(via sciencedaily.com) Original source Scientists have trained a machine learning model in outer space, on board a satellite. This achievement could revolutionize the capabilities of remote-sensing satellites by enabling real-time monitoring and decision making for a range of applications.
Published Engineering team uses diamond microparticles to create high security anti-counterfeit labels
(via sciencedaily.com) Original source Researchers have developed a pioneering technological solution that counterfeiters have no response to.
Published A simpler method for learning to control a robot
(via sciencedaily.com) A new machine-learning technique can efficiently learn to control a robot, leading to better performance with fewer data.
Published AI predicts the work rate of enzymes
(via sciencedaily.com) Enzymes play a key role in cellular metabolic processes. To enable the quantitative assessment of these processes, researchers need to know the so-called 'turnover number' (for short: kcat) of the enzymes. A team of bioinformaticians now describes a tool for predicting this parameter for various enzymes using AI methods.
Published The economic life of cells
(via sciencedaily.com) A team has combined economic theory with biology to understand how natural systems respond to change. The researchers noticed a similarity between consumers' shopping behavior and the behavior of metabolic systems, which convert food into energy in our bodies. The team focused on predicting how different metabolic systems might respond to environmental change by using an economic tool called the Slutsky equation. Their calculations indicated that very different metabolic systems actually share previously unknown universal properties, and can be understood using tools from other academic fields. Metabolic processes are used in drug development, bioengineering, food production and other industries, so being able to predict how such systems will respond to change can offer many benefits.
Published Researchers visualize activity of CRISPR genetic scissors
(via sciencedaily.com) Original source Scientists have developed a new method to measure the smallest twists and torques of molecules within milliseconds. The method makes it possible to track the gene recognition of CRISPR-Cas protein complexes, also known as 'genetic scissors', in real time and with the highest resolution. With the data obtained, the recognition process can be accurately characterized and modeled to improve the precision of the genetic scissors.