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Categories: Engineering: Biometric, Mathematics: Statistics

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Researchers have developed a highly efficient method to investigate systems with long-range interactions that were previously puzzling to experts. These systems can be gases or even solid materials such as magnets whose atoms interact not only with their neighbors but also far beyond.

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Scientists have recently proposed a workflow that can dramatically accelerate the search for novel materials with improved properties. They demonstrated the power of the approach by identifying more than 50 strongly thermally insulating materials. These can help alleviate the ongoing energy crisis, by allowing for more efficient thermoelectric elements, i.e., devices able to convert otherwise wasted heat into useful electrical voltage.

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Why do some people take part in genetic studies while others do not? The answer may lie within our genetic makeup. According to a groundbreaking study, people who participate in genetic studies are genetically more likely to do so, leaving detectable 'footprints' in genetics data. This breakthrough equips researchers with the ability to identify and address participation bias, a significant challenge in genetic research.

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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.

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We humans can be a scary acquaintance for whales in the wild. This includes marine biologists tagging them with measuring devices to understand them better. These experiences can make whales behave erratically for a while. Such behaviour can affect research quality and highlights an animal ethics dilemma. Now, researchers have figured out how to solve the problems with math.

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Many factors influence where a landslide will occur, including the shape of the terrain, its slope and drainage areas, the material properties of soil and bedrock, and environmental conditions like climate, rainfall, hydrology and ground motion resulting from earthquakes. Geologists have developed a new technique that uses artificial intelligence to better predict where and why landslides may occur could bolster efforts to protect lives and property in some of the world's most disaster-prone areas. The new method improves the accuracy and interpretability of AI-based machine-learning techniques, requires far less computing power and is more broadly applicable than traditional predictive models.

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In the space of a few months generative AI models, such as ChatGPT, Google's Bard and Midjourney, have been adopted by more and more people in a variety of professional and personal ways. But growing research is underlining that they are encoding biases and negative stereotypes in their users, as well as mass generating and spreading seemingly accurate but nonsensical information. Worryingly, marginalized groups are disproportionately affected by the fabrication of this nonsensical information.

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How do asset markets work? Which stocks behave similarly? Economists, physicists, and mathematicians work intensively to draw a picture but need to learn what is happening outside their discipline. A new paper now builds a bridge.

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Miniaturization is progressing rapidly in just any field and the trend towards the creation of ever smaller units is also prevalent in the world of robot technology. In the future, minuscule robots used in medical and pharmaceutical applications might be able to transport medication to targeted sites in the body. Statistical physics can contribute to the foundations for the development of such technologies.

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Scientists have developed a software package to help answer key questions about genetic factors associated with shared characteristics among different species.

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It is possible to retrieve forensically relevant information from human DNA in household dust.

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Collaborative research across the country has shown that strengthening the relationship between the student and advisor can increase retention rates in engineering doctoral studies.

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A recent study that examined the relationship between artificial intelligence (AI) and law enforcement underscores both the need for law enforcement agencies to be involved in the development of public policies regarding AI -- such as regulations governing autonomous vehicles -- and the need for law enforcement officers to better understand the limitations and ethical challenges of AI technologies.

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Researchers have mapped the sparse life hidden away in salt domes, rocks and crystals at Salar de Pajonales at the boundary of the Chilean Atacama Desert and Altiplano. Then they trained a machine learning model to recognize the patterns and rules associated with their distributions so it could learn to predict and find those same distributions in data on which it was not trained. In this case, by combining statistical ecology with AI/ML, the scientists could locate and detect biosignatures up to 87.5 percent of the time and decrease the area needed for search by up to 97 percent.

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Researchers have created and preliminarily tested what they believe may be one of the first models for predicting who has the highest probability of being resistant to COVID-19 in spite of exposure to SARS-CoV-2, the virus that causes it.

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Researchers tested a large sample of the major AI technologies available today and found that not only did they reproduce human biases in facial age recognition, but they exaggerated those biases.

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By flagging disease-associated DNA biomarkers, medical professionals can make early diagnoses and provide personalized treatments, but the typical screening methods can be laborious, expensive or limited in scope. Now, a new biosensor could pave the way to accessible and expansive diagnostics.

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Synthetic populations are computer-generated models that mimic real-world populations in terms of characteristics such as age, gender, and occupation; they are useful when conducting social simulations. In a recent study, researchers developed a new approach to assign workplaces to individuals in a synthetic Japanese population with household information, based on ODI (Origin-Destination-Industry) data. Their efforts will enable more accurate, realistic simulations of the day-time distribution of workers in Japan, helping to improve decision-making and planning.

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A new paper presents a mathematical model for the motion of bacteria that includes cell division and death, the basic ingredients of the cell cycle.

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A new study shows machine-learning models trained using simple symptoms, demographic features are effective in predicting COVID-19 infections.