SpaceX CEO Elon Musk wants employees to focus on the company’s Starship rocket, according to an email seen by CNBC.
Light-sheet images of DEEP-Clear processed zebrafish showing proliferative cells (pink) and the nervous system (green). Credit: TU Wien / Max Perutz Labs.
An important observation that helped to develop the new method was that the combination of different chemical treatments had a synergistic effect, allowing for fast depigmentation and tissue clearing. “Shortening chemical processing preserves the integrity of tissues and organisms, so that the molecules and internal structures of interest are more likely to be retained,” explains Marko Pende, the developer of the clearing method, from the lab of Hans-Ulrich Dodt at the TU Wien and the Center for Brain Research (CBR) of the Medical University of Vienna, and one of the first authors of the study. This way multiple organisms could be imaged from different clades ranging from mollusks to bony fish to amphibians. “These are just a few examples. We believe that the method is applicable to multiple organisms. It was just not tried yet”, explains Prof. Hans Ulrich Dodt, senior author of the study.
New tools that can give a more detailed look at how neurons work are leading the research of brain scientists in new directions.
Galaxy KK 246, a dwarf irregular galaxy residing within the Local Void, looks like glitter spilled across a black velvet sheet in this Hubble image. Credit: ESA/Hubble & NASA, E. Shaya, L. Rizzi, B. Tully, et al.
Recently, OpenAI collaborated with UberAI to propose a new approach — Synthetic Petri Dish — for accelerating the most expensive step of Neural Architecture Search (NAS). The researchers explored whether the computational efficiency of NAS can be improved by creating a new kind of surrogate, one that can benefit from miniaturised training and still generalise beyond the observed distribution of ground-truth evaluations.
Deep neural networks have been witnessing success and are able to mitigate various business challenges such as speech recognition, image recognition, machine translation, among others for a few years now.
According to the researchers, Neural Architecture Search (NAS) explores a large space of architectural motifs and is a compute-intensive process that often involves ground-truth evaluation of each motif by instantiating it within a large network, and training and evaluating the network with thousands or more data samples. By motif, the researchers meant the design of a repeating recurrent cell or activation function that is repeated often in a larger Neural Network blueprint.
Although planets, stars, and galaxies all spin along an axis of rotation, new research suggests that the universe itself might also revolve around an axis, or several, but on a cosmic scale challenging one of the fundamental assumptions of astrophysics, the cosmological principle, which holds that the same physical laws are homogeneous and uniform, isotropic, everywhere in the universe. This exotic new theory paints a picture of a spinning universe that creates structural anisotropies and asymmetries on cosmic scales of hundreds of millions of light years.
Enter one Lior Shamir, a computational astronomer at Kansas State University, who presented evidence that has yet to be peer reviewed at the recent virtual Zoom meeting of the American Astronomical Society that the early universe rotated like an enormous, complex galaxy, and continued this momentum through the galaxies we see today, hinting that the early universe had a more uniform structure that it has been steadily losing through time, resulting in an increasingly chaotic cosmos.
This is the inaugural episode of my new podcast “Cosmic Controversy” which is available at the moment on Podbean. Many thanks to my first guest astrobiologist Lara Maldanis who talks about her and colleagues’ recent work in identifying ancient earth microfossils and how we can hope to identify microfossils on Mars.
Cosmic Controversy delves into current aerospace, astronomy, and astrobiology as well as long-standing issues in aerospace and aviation history…
It sounds like something from a sci-fi movie, but the newly revealed Shadow-Effect Energy Generator (SEG) is a real prototype device. The fascinating concept could help us to transform the way renewable energy is generated indoors.
The SEG uses the contrast between darkness and light to produce electricity. It’s made up of a series of thin strips of gold film on a silicon wafer, placed on top of a flexible plastic base.
Whereas shadows are usually a problem for renewable solar energy production, here they’re actually harnessed to keep on generating power. The technology — which is cheaper to produce than a typical solar cell, according to its developers — produces small amounts of power and could be used in mobile gadgets, for example.
Virus DNA left on a hospital bed rail was found in nearly half of all sites sampled across a ward within 10 hours and persisted for at least five days, according to a new study by UCL and Great Ormond Street Hospital (GOSH).
The study, published as a letter in the Journal of Hospital Infection, aimed to safely simulate how SARS-CoV-2, the virus that causes Covid-19, may spread across surfaces in a hospital.
Instead of using the SARS-CoV-2 virus, researchers artificially replicated a section of DNA from a plant-infecting virus, which cannot infect humans, and added it to a milliliter of water at a similar concentration to SARS-CoV-2 copies found in infected patients’ respiratory samples.
No one can say whether androids will dream of electric sheep, but they will almost certainly need periods of rest that offer benefits similar to those that sleep provides to living brains, according to new research from Los Alamos National Laboratory.
“We study spiking neural networks, which are systems that learn much as living brains do,” said Los Alamos National Laboratory computer scientist Yijing Watkins. “We were fascinated by the prospect of training a neuromorphic processor in a manner analogous to how humans and other biological systems learn from their environment during childhood development.”
Watkins and her research team found that the network simulations became unstable after continuous periods of unsupervised learning. When they exposed the networks to states that are analogous to the waves that living brains experience during sleep, stability was restored. “It was as though we were giving the neural networks the equivalent of a good night’s rest,” said Watkins.
