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Categories: Archaeology: General, Mathematics: Modeling

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An artificial intelligence algorithm can allow researchers to more efficiently use 3D printing to manufacture intricate structures. The development could allow for more seamless use of 3D printing for complex designs in everything from artificial organs to flexible electronics and wearable biosensors. As part of the study, the algorithm learned to identify, and then print, the best versions of kidney and prostate organ models, printing out 60 continually improving versions.

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New research has revealed how an underwater avalanche grew more than 100 times in size causing a massive trail of destruction as it traveled 2000km across the Atlantic Ocean seafloor off the North West coast of Africa. Researchers provide an unprecedented insight into the scale, force and impact of one of nature's mysterious phenomena, underwater avalanches.

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Archeologists say new findings might help resolve the debate about Clovis points and reshape how we think about what life was like roughly 13,000 years ago. After an extensive review of writings and artwork -- and an experiment with replica Clovis point spears -- a team of archaeologists says humans may have braced the butt of their weapons against the ground in a way that would impale a charging animal. The force would have driven the spear deeper into the predator's body, unleashing a more damaging blow than even the strongest prehistoric hunters would have been capable of by throwing or jabbing megafauna.

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Artificial intelligence (AI) has exploded in popularity as of late. But just like a human, it's hard to read an AI model's mind. Explainable AI (XAI) could help us do just that by providing justification for a model's decisions. And now, researchers are using XAI to scrutinize predictive AI models more closely, which could help make better antibiotics.

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A new machine learning model can predict autism in young children from relatively limited information. The model can facilitate early detection of autism, which is important to provide the right support.

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A mathematical framework that builds on the economic theory of hidden-action models provides insight into how the unobservable nature of effort and risk shapes investigators' research strategies and the incentive structures within which they work, according to a new study.

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Researchers simulated social norms with a supercomputer. Their findings contribute to a deeper understanding of the evolution of social norms and their role in fostering cooperative behavior.

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New research has revealed Stonehenge's monumental six-ton Altar Stone, long believed to originate from Wales, actually hails from Scotland.

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Researchers discover that while artificial intelligence (AI) tools can make accurate diagnoses from textbook-like descriptions of genetic diseases, the tools are significantly less accurate when analyzing summaries written by patients about their own health. These findings demonstrate the need to improve these AI tools before they can be applied in health care settings to help make diagnoses and answer patient questions.

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A new interpretation of the runic inscription on the Forsa Ring (Forsaringen in Swedish), provides fresh insights into the Viking Age monetary system and represents the oldest documented value record in Scandinavia. The inscription describes how the Vikings handled fines in a flexible and practical manner.

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Since its discovery by modern researchers a century ago, an ancient structure known as the 'Christian building' has become widely considered the cornerstone of early Christian architecture. Constructed around 232 C.E. in the ancient city of Dura-Europos, a Roman garrison town in what is now eastern Syria, the building is the only example of a 'house church,' or domus ecclesiae, a domestic space that was renovated for worship by Christians at a time when the open practice of their faith is thought to have made them subject to persecution.

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New research explains the mathematics behind how initial predispositions and additional information affect decision making.

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Large Language Models (LLMs) are entirely controllable through human prompts and lack 'emergent abilities'; that is, the means to form their own insights or conclusions. Increasing model size does not lead LLMs to gain emergent reasoning abilities, meaning they will not develop hazardous abilities and therefore do not pose an existential threat. A new study sheds light on the (until now unexplained) capabilities and shortcomings of LLMs, including the need for carefully engineered prompts to exhibit good performance.

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A new artificial intelligence model can predict how different proteins may bind to DNA.

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Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use machine learning in computational biology, understanding model behavior remains crucial for uncovering the underlying biological mechanisms in health and disease. Researchers now propose guidelines that outline pitfalls and opportunities for using interpretable machine learning methods to tackle computational biology problems.

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An archaeological strategy adapted for space used daily photos to reveal how astronauts actually use areas aboard the International Space Station -- and how this differs from intended uses.

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The first-ever archeological survey in space has provided new insights into how astronauts use and adapt their living space on the International Space Station, which could influence the design of new space stations after the ISS is decommissioned.

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To protect the Amazon and support the wellbeing of its people, its economy needs to shift from environmentally harmful production to a model built around the diversity of indigenous and rural communities, and standing forests.

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Markings on a stone pillar at a 12,000 year-old archaeological site in Turkey likely represent the world's oldest solar calendar, created as a memorial to a devastating comet strike, experts suggest.

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With GROVER, a new large language model trained on human DNA, researchers could now attempt to decode the complex information hidden in our genome. GROVER treats human DNA as a text, learning its rules and context to draw functional information about the DNA sequences.