Jupiter may be the king of planets in our Solar System, but in other star systems across the galaxy, even larger planets orbit billions of miles from their stars – in places where traditional formation theories struggle to explain them.
An exploration of the themes of Frankenstein in a hard science context and the possibility of biological SETI in deep space.
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An exploration of the idea of an all powerful matrioshka brain equipped with a Nicoll-Dyson beam controlling and ruling an entire galaxy.
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Greenland’s largest glacier, Jakobshavn Glacier, may be edging closer to a critical threshold as meltwater runoff from the Greenland Ice Sheet accelerates in ways not seen in over a century, according to new research published in Climate of the Past. The study reconstructs more than 100 years of freshwater discharge flowing from the ice sheet into Disko Bay in western Greenland, revealing a striking and sustained change that began in the early 2000s.
Researchers from Kiel University, Germany, and colleagues found that runoff did not increase gradually, but instead shifted into sharp acceleration. By 2007, the volume of freshwater entering the ocean had permanently exceeded the range of natural variability seen throughout the 20th century. Simply put, the system appears to have moved into a new state, one characterized by consistently higher meltwater output. This pattern suggests the ice sheet may be approaching what scientists call a “tipping point”—a threshold beyond which changes become self-reinforcing and potentially difficult to reverse.
Artificial intelligence (AI) systems are computational models that can learn to identify patterns in data, make accurate predictions or generate content (e.g., texts, images, videos or sound recordings). These models can reliably complete various tasks and are now also used to carry out research rooted in different fields.
Over the past few decades, some AI models have proved promising for the early diagnosis and study of specific diseases or neuropsychiatric conditions. For instance, by analyzing large amounts of brain scans collected using a noninvasive technique known as magnetic resonance imaging (MRI), AI could uncover patterns associated with tumors, strokes and neurodegenerative diseases, which could help to diagnose these conditions.
Researchers at Mass General Brigham, Harvard Medical School and other institutes recently developed Brain Imaging Adaptive Core (BrainIAC), a large AI system pre-trained on a vast pool of MRI data that could be adapted to tackle different tasks. This foundation model, presented in a paper published in Nature Neuroscience, was found to outperform many models that were trained to complete specific medical or neuroscience-related tasks.
The evolution of eukaryotes was accompanied by an increased need for intracellular communication and cellular specialization. Thus, a more complex collection of secreted and membrane proteins had to be synthesized, modified, and folded. The endoplasmic reticulum (ER) thereby became equipped with devoted enzymes and associated factors that both catalyze the production of secreted proteins and remove damaged proteins. A means to modify ER function to accommodate and destroy misfolded proteins also evolved. Not surprisingly, a growing number of human diseases are linked to various facets of ER function. Each of these topics will be discussed in this article, with an emphasis on recent reports in the literature that employed diverse models.