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Categories: Mathematics: Modeling, Physics: Acoustics and Ultrasound
Published AI models are powerful, but are they biologically plausible?


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


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 Brain recordings capture musicality of speech -- with help from Pink Floyd


For those with neurological or developmental disorders compromising speech, brain machine interfaces could help them communicate. But today's interfaces are slow and, from electrodes placed on the scalp, can detect letters only. The speech generated is robotic and affectless. Neuroscientists have now shown that they can reconstruct the song a person is hearing from brain recordings alone, holding out the possibility of reconstructing not only words but the musicality of speech, which also conveys meaning.
Published Distribution of genetic information during bacterial cell division


A mathematical model provides new insights into the distribution of genetic information during bacterial cell division
Published Artificial intelligence designs advanced materials


Scientists pioneer a new machine learning model for corrosion-resistant alloy design.
Published Tool finds bias in state-of-the-art generative AI model


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'


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


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


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?


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


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


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


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



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 A wearable ultrasound scanner could detect breast cancer earlier


In hopes of improving the survival rate for breast cancer patients, researchers designed a wearable ultrasound device that could allow women to detect tumors when they are still in early stages.
Published A simpler method for learning to control a robot


A new machine-learning technique can efficiently learn to control a robot, leading to better performance with fewer data.
Published A quick look inside a human being



Physicists have succeeded in making a new imaging technique ready for use on humans. Radioactive markers and radiation are not necessary for this.
Published AI predicts the work rate of enzymes


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 Controlling signal routing in quantum information processing



Routing signals and isolating them against noise and back-reflections are essential in many practical situations in classical communication as well as in quantum processing. In a theory-experimental collaboration, a team has achieved unidirectional transport of signals in pairs of 'one-way streets'. This research opens up new possibilities for more flexible signaling devices.
Published The economic life of cells


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.