With careful development and thoughtful approaches, Kazi believes the changes AI will bring to healthcare will be some of the most exciting technological advances of our lifetime.
Learn more about building a modern data foundation to deliver the next generation of personalized healthcare with AI, ML, and generative AI.
Applying deep learning to large-scale genomic data of species or populations is providing new opportunities to understand the evolutionary forces that drive genetic diversity. This Review introduces common deep learning architectures and provides comprehensive guidelines to implement deep learning models for population genetic inference. The authors also discuss current opportunities and challenges for deep learning in population genetics.
A new nanoscience study led by a researcher at the Department of Energy’s Oak Ridge National Laboratory takes a big-picture look at how scientists study materials at the smallest scales.
The paper, published in Science Advances, reviews leading work in subsurface nanometrology, the science of internal measurement at the nanoscale level, and suggests quantum sensing could become the foundation for the field’s next era of discoveries. Potential applications could range from mapping intracellular structures for targeted drug delivery to characterizing quantum materials and nanostructures for the advancement of quantum computing.
“Our goal was to define the state of the art and to consider what’s been done and where we need to go,” said Ali Passian, an ORNL senior research scientist and senior author of the study.
A family of large-genome bacteriophages assembles a protective protein shell around its replicating DNA called the ‘phage nucleus’. Here, Enustun et al. use proteomics to identify a set of proteins associated with the phage nucleus that aid macromolecule transport through the nuclear shell.
Einstein’s theory of relativity say black holes are ‘bald’, but a new tweak to his research may give the mysterious objects their long-sought ‘hair.’
A study recently published in the journal Nanophotonics reveals that by rapidly modulating the refractive index – which is the ratio of the speed of electromagnetic radiation in a medium compared to its speed in a vacuum – it’s possible to produce photonic time crystals (PTCs) in the near-visible part of the spectrum.
The study’s authors suggest that the ability to sustain PTCs in the optical domain could have profound implications for the science of light, enabling truly disruptive applications in the future.
PTCs, materials in which the refractive index rises and falls rapidly in time, are the temporal equivalent of photonic crystals in which the refractive index oscillates periodically in space causing, for example, the iridescence of precious minerals and insect wings.
Just like a gecko that regrows a broken tail, our peripheral nervous system knows how to regenerate the branches of its cells after an injury. Unfortunately, the cells in our central nervous system—our brain and spinal cord—are far more limited when it comes to regeneration.
Accordingly, diseases that lead to the degeneration and death of brain neurons, such as Alzheimer’s, Parkinson’s and ALS, are irreversible and incurable. So, what is it about the peripheral nervous system, which connects our brain and spinal cord to the other organs, that gives it the power to regenerate itself so readily?
In a new study, researchers at the Weizmann Institute of Science have discovered that a protein, previously known to be expressed only during embryonic development, plays a key role in regenerating adult neurons in the peripheral nervous system.
(RQM) is the most recent among the interpretations of quantum mechanics which are most discussed today. It was introduced in 1996, with quantum gravity as a remote motivation (Rovelli 1996); interests in it has slowly but steadily grown only in the last decades. RQM is essentially a refinement of the textbook “Copenhagen” interpretation, where the role of the Copenhagen observer is not limited to the classical world, but can instead be assumed by any physical system. RQM rejects an ontic construal of the wave function (more in general, of the quantum state): the wave function or the quantum state play only an auxiliary role, akin to the Hamilton-Jacobi function of classical mechanics. This does not imply the rejection of an ontological commitment: RQM is based on an ontology given by physical systems described by physical variables, as in classical mechanics. The difference with classical mechanics is that (a) variables take value only at interactions and (b) the values they take are only relative to the (other) system affected by the interaction. Here “relative” is in the same sense in which velocity is a property of a system relative to another system in classical mechanics. The world is therefore described by RQM as an evolving network of sparse relative events, described by punctual relative values of physical variables.
The physical assumption at the basis of RQM is the following postulate: The probability distribution for (future) values of variables relative to S ′ S′[/sup depend on (past) values of variables relative to S′[/sup but not on (past) values of variables relative to another system S″.
We are about to leap into the age of quantum computing and possibly our technological capabilities will evolve rapidly as a result.
Does this mean we are on the threshold of developing a Type 2 civilization?
If so, we should soon be able to make first contact with other intelligent life forms and slowly conquer space.
Continue reading “Why We Can Never Find a Type-7 Civilization!” »
Going from 49kB of transient program area to 60kB took only a single NAND chip, in this interesting experiment in vintage bank-switching.
