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Circa 2018 o.o


Rockets with nuclear bombs for propulsion sounds like a Wile E. Coyote cartoon, but it has been seriously considered as an option for the space program. Chemical rockets combust a fuel with an oxidizer within themselves and exhaust the result out the back, causing the rocket to move in the opposite direction. What if instead, you used the higher energy density of nuclear fission by detonating nuclear bombs?

Detonating the bombs within a combustion chamber would destroy the vehicle so instead you’d do so from outside and behind. Each bomb would include a little propellant which would be thrown as plasma against the back of the vehicle, giving it a brief, but powerful push.

That’s just what a group of top physicists and engineers at General Atomic worked on between 1958 and 1965 under the name, Project Orion. They came close to doing nuclear testing a few times and did have success with smaller tests, exploding a series of chemical bombs which pushed a 270-pound craft up 185 feet as you’ll see below.

It can be difficult to distinguish between substance and hype in the field of artificial intelligence. In order to stay grounded, it is important to step back from time to time and ask a simple question: what has AI actually accomplished or enabled that makes a difference in the real world?

This summer, DeepMind delivered the strongest answer yet to that question in the decades-long history of AI research: AlphaFold, a software platform that will revolutionize our understanding of biology.

In 1,972 in his acceptance speech for the Nobel Prize in Chemistry, Christian Anfinsen made a historic prediction: it should in principle be possible to determine a protein’s three-dimensional shape based solely on the one-dimensional string of molecules that comprise it.

Proteins are structured like folded chains. These chains are composed of small units of 20 possible amino acids, each labeled by a letter of the alphabet. A protein chain can be represented as a string of these alphabetic letters, very much like a string of music notes in alphabetical notation.

Protein chains can also fold into wavy and curved patterns with ups, downs, turns, and loops. Likewise, music consists of sound waves of higher and lower pitches, with changing tempos and repeating motifs.

Protein-to-music algorithms can thus map the structural and physiochemical features of a string of amino acids onto the musical features of a string of notes.

Without a new legal framework, they could destabilize societal norms.


Autonomous weapon systems – commonly known as killer robots – may have killed human beings for the first time ever last year, according to a recent United Nations Security Council report on the Libyan civil war. History could well identify this as the starting point of the next major arms race, one that has the potential to be humanity’s final one.

Autonomous weapon systems are robots with lethal weapons that can operate independently, selecting and attacking targets without a human weighing in on those decisions. Militaries around the world are investing heavily in autonomous weapons research and development. The U.S. alone budgeted US$18 billion for autonomous weapons between 2016 and 2020.

Meanwhile, human rights and humanitarian organizations are racing to establish regulations and prohibitions on such weapons development. Without such checks, foreign policy experts warn that disruptive autonomous weapons technologies will dangerously destabilize current nuclear strategies, both because they could radically change perceptions of strategic dominance, increasing the risk of preemptive attacks, and because they could become combined with chemical, biological, radiological and nuclear weapons themselves.

Indeed, as Gizmodo’s report highlights, many experts believe that these researchers have not actually found evidence of dinosaur DNA. They told the news outlet, for example, that—even under the best circumstances—DNA couldn’t last more than three million years. Let alone more than 100 million. And that the chemicals may have been staining inorganic matter that only looks cellular in nature.

As of now, the most ancient DNA that scientists have been able to sequence was that of a million-year-old woolly mammoth. And the youngest dinosaurs are at least 65 million years old. But if future experiments do confirm this evidence as real, then that really changes things. At least in our fantasies, where reanimated dinosaurs and Ian Malcolms abound.

The post Fossil of Peacock-Like Dinosaur May Have Preserved DNA Remnants appeared first on Nerdist.

When Dr. Robert Murphy first started researching biochemistry and drug development in the late 1970s, creating a pharmaceutical compound that was effective and safe to market followed a strict experimental pipeline that was beginning to be enhanced by large-scale data collection and analysis on a computer.

Now head of the Murphy Lab for computational biology at Carnegie Mellon University (CMU), Murphy has watched over the years as data collection and artificial intelligence have revolutionized this process, making the drug creation pipeline faster, more efficient, and more effective.

Recently, that’s been thanks to the application of machine learning—computer systems that learn and adapt by using algorithms and statistical models to analyze patterns in datasets—to the drug development process. This has been notably key to reducing the presence of side effects, Murphy says.

Brains aren’t the easiest of organs to study, what with their delicate wiring and subtle whispering of neurotransmitter messages. Now, this research could be made a little easier, as we’ve learned we can swap some critical chemical systems with the host animal being none the wiser.

In a proof-of-concept study run by a team of US researchers, the microscopic worm Caenorhabditis elegans was genetically gifted pieces of a nervous system taken from a radically different creature – a curious freshwater organism known as Hydra.

The swap wasn’t unlike teaching a specific brain circuit a foreign language, and finding it performs its job just as well as before.

Developing drugs for a range of tauopathies — dr leticia toledo-sherman, senior director, drug discovery, tau consortium, rainwater charitable foundation.


Dr. Leticia Toledo-Sherman is Senior Director of Drug Discovery of the Tau Consortium (https://tauconsortium.org/) for The Rainwater Charitable Foundation (https://rainwatercharitablefoundation.org/medical-research) and also holds an appointment as Adjunct Assistant Professor of Neurology at UCLA.

Dr. Toledo-Sherman leads drug discovery activities for an international network of scientists working to develop therapies for Tauopathies, a group of neurodegenerative disorders characterized by the deposition of abnormal Tau protein in the brain.

Previously, Dr. Toledo-Sherman was Director of Medicinal Chemistry and Computer-Aided Drug Design at the CHDI Foundation, leading drug discovery programs for therapeutic development in Huntington’s Disease (HD). At CHDI, she also led a structural biology initiative critical to the understanding of the relationship between structure and biological function of huntingtin, the protein that when mutated causes HD.

Prior to joining CHDI, Dr. Toledo-Sherman was Executive Director of Chemistry at Lymphosign (now part of Pharmascience Inc), a privately held biotechnology company that applied rational design principles to the development of therapeutics for blood cancers. From 2000 to 2,004 she led a multi-site, multidisciplinary team using chemical proteomics and bioinformatics to discover therapeutic targets and to investigate the mechanism of action of drugs.

Autonomous weapon systems – commonly known as killer robots – may have killed human beings for the first time ever last year, according to a recent United Nations Security Council report on the Libyan civil war. History could well identify this as the starting point of the next major arms race, one that has the potential to be humanity’s final one.

Autonomous weapon systems are robots with lethal weapons that can operate independently, selecting and attacking targets without a human weighing in on those decisions. Militaries around the world are investing heavily in autonomous weapons research and development. The U.S. alone budgeted US$18 billion for autonomous weapons between 2016 and 2020.

Meanwhile, human rights and humanitarian organizations are racing to establish regulations and prohibitions on such weapons development. Without such checks, foreign policy experts warn that disruptive autonomous weapons technologies will dangerously destabilize current nuclear strategies, both because they could radically change perceptions of strategic dominance, increasing the risk of preemptive attacks, and because they could become combined with chemical, biological, radiological and nuclear weapons themselves.

A possible explanation for life from nonliving material.


Exactly how life first emerged from non-living matter is one of the most enduring mysteries of science. In a new study, Japanese scientists have created self-replicating protocells in the lab, which they say could represent the “missing link” between chemistry and biology.

Primitive Earth was covered with a sludgy mix of chemicals, containing organic molecules that formed the precursors for vital biological components like proteins and amino acids. There are several different hypotheses for how and where life sprang out of this soup, but one of the first ideas was known as chemical evolution, which is what the new study investigated.

“Chemical evolution was first proposed in the 1920s as the idea that life first originated with the formation of macromolecules from simple small molecules, and those macromolecules formed molecular assemblies that could proliferate,” says Muneyuki Matsuo, first author of the study. “However, the origin of molecular assemblies that proliferate from small molecules has remained a mystery for about a hundred years since the advent of the chemical evolution scenario. It has been the missing link between chemistry and biology in the origin of life.”