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Category: computing – Page 359

TMCs are responsible for all aspects of data generation from tissue collection and analysis to data integration and interpretation. We anticipate that TMCs will acquire and integrate imaging and omics data to benchmark, standardize and validate SnC maps at single-cell resolution for their assigned tissues. The TDA sites are responsible for development of innovative, new approaches and tools necessary to deeply phenotype SnCs in human tissues and model systems. Examples include multi-omics characterization of the 4D nucleome in SnCs, high-throughput quantification of telomere-associated foci, and in vivo detection of SnCs via positron emission tomography imaging. Once developed, these new technologies are expected to be applied broadly and collaboratively across multiple tissues by the TMCs. The CODCC will collect, store and curate all data and metadata generated by the TMCs and TDA sites. The CODCC is responsible for generating the computational models, and final atlas products as well as the tools to visualize and disseminate the data as a resource for the broad scientific community.

It is expected that SenNet will interface with other cell mapping programs such as Human Bimolecular Atlas Program (HuBMAP), Human Cell Atlas (HCA) and the Kidney Precision Medicine Project (KPMP). HuBMAP is an NIH Common Fund Initiative to develop the resources and framework to map the 30 trillion cells that make up the human body using protein identifiers of cell lineage. HCA is using single-cell and spatial transcriptomics to create cell reference maps defining the position, function and characteristics of all cells in the human body. The KPMP is an initiative of the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) aimed at using state-of-the-art and emerging technologies to characterize renal biopsies from participants with acute kidney injury or chronic kidney disease to enable personalized approaches to their treatment.

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Researchers have finally succeeded in building a long-sought nanoparticle structure, opening the door to new materials with special properties.

Alex Travesset does not have a sparkling research lab stocked with the most cutting-edge instruments for probing new nanomaterials and measuring their unique properties.

Instead of using traditional laboratory instruments, Alex Travesset, a professor of physics and astronomy at Iowa State University and an affiliate of the U.S. Department of Energy’s Ames National Laboratory, relies on computer models, equations, and figures to understand the behavior of new nanomaterials.

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I wanted to focus on the animal testing portion of the Show and Tell. Neuralink representatives showed us videos of a pig that has a cortex and spinal chip in its body. It also has pin points on joints in its leg that are sending data to the Neuralink scientist. When the scientist stimulates a joint it creates an uncontrolled movement. The pig moves its leg without wanting too, but because someone else wanted it too, the pig did not want to move. That’s the focus of this video.

#neuralink #neuroscience #videoessay #yuvalnoahharari #elonmusk #podcast #neurology

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As computer scientists tackle a greater range of problems, their work has grown increasingly interdisciplinary. This year, many of the most significant computer science results also involved other scientists and mathematicians. Perhaps the most practical involved the cryptographic questions underlying the security of the internet, which tend to be complicated mathematical problems. One such problem — the product of two elliptic curves and their relation to an abelian surface — ended up bringing down a promising new cryptography scheme that was thought to be strong enough to withstand an attack from a quantum computer. And a different set of mathematical relationships, in the form of one-way functions, will tell cryptographers if truly secure codes are even possible.

Computer science, and quantum computing in particular, also heavily overlaps with physics. In one of the biggest developments in theoretical computer science this year, researchers posted a proof of the NLTS conjecture, which (among other things) states that a ghostly connection between particles known as quantum entanglement is not as delicate as physicists once imagined. This has implications not just for our understanding of the physical world, but also for the myriad cryptographic possibilities that entanglement makes possible.

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