Boulder Future Salon

"A new multiscale coarse-grained model of the complete SARS-CoV-2 virion, its core genetic material and virion shell, has been developed for the first time using supercomputers."

"A coarse-grained model resolves only groups of atoms, versus all-atom simulations, where every single atomic interaction is resolved." "If you do that well, which is always a challenge, you maintain the physics in the model."

"The early results of the study show how the spike proteins on the surface of the virus move cooperatively." "They don't move independently like a bunch of random, uncorrelated motions. They work together."

"This cooperative motion of the spike proteins is informative of how the coronavirus explores and detects the ACE2 receptors of a potential host cell."

The researchers combined a number of statistical approaches to come to the correlation conclusion. They used principal component analysis, a dimensionality-reduction technique, on a subset of the coarse-grained particles to examine collective modes of motion of the virion. From that they computed a covariance matrix. This analysis included membrane, nucleocapsid, and envelope proteins, as well as the spike proteins, which were all part of the coarse-grained simulation. The analysis showed correlated modes of motion with the spike proteins.

"From somewhere beyond his perception, a voice asked: 'Do you speak Spanish?' He hesitated. He had expected the questions to come -- but he did not know how to answer this one."

"Eventually, he responded to the voice: 'No.' He had a good grasp of Spanish, but he wasn't fluent. The voice asked some more questions, and the young man answered, yes or no."

"And then he woke up."

"This 20-year-old biology student, identified only as 'AC,' was one of 36 participants in a proof-of-concept study investigating whether it is possible to have a real-time, two-way conversation between a researcher and an asleep dreamer. And along with five other participants, AC's experience reveals the answer appears to be yes."

"AC is in some ways a special case -- he has narcolepsy, a sleep disorder which causes people to fall asleep both often and spontaneously throughout their day."

"The Ramanujan Machine is a novel way to do mathematics by harnessing your computer power to make new discoveries. The Ramanujan Machine already discovered dozens of new conjectures."

"Our algorithms search for new mathematical formulas. The community can suggest proofs for the conjectures or even propose or develop new algorithms. Any new conjecture, proof, or algorithm suggested will be named after you."

"Want to contribute to the Ramanujan Machine? Have no time? Let your computer discover new conjectures whenever you're not using it. Have a conjecture named after you! Have time for math? Suggest a proof to any of the conjectures that were discovered by the Ramanujan Machine. Have a formula named after you! Have time to code? Propose or develop new algorithms to explore new mathematical structures. Have an algorithm named after you!"

Mapping the US Military.

"At Embark, we've taken a hard look at how we go about creating game content, and as part of that, we have come to embrace machine learning and procedural content across many of our workflows."

"Animation is a big bottleneck in all game development. Characters or creatures have to be designed and scripted manually, to achieve seemingly realistic interactions with the world."

"So over the past two years, we've continued down the path of physical animation based on reinforcement learning. In short, that means we train physically-based machines to walk by giving them rewards for doing the right things -- like virtual dog treats."

"As you'll see in the examples below, achieving good movement behaviors can lead to more immersive and interesting gameplay, where the world becomes truly alive -- where there aren't any pre-made animations, stuttering transitions between poses, or weird ragdolls."

"I've been America's top-rated ICCF Grandmaster for several years. As such, I'm an active and experienced chess engine user. So I know that utilizing the best chess engine for high-quality chess analysis is vital for success. But, how does one determine which engine to use?"

"In the pre-NNUE (Efficiently Updatable Neural Network) era, Stockfish was my engine of choice." "However, I was frustrated by its often unsatisfactory evaluation function. It assessed most of my game positions with the infamous 0.00 evaluation."

"After the development of Stockfish NNUE, its evaluation improved 100%. Clearly, the NNUE concept is the way to go." "However, while fewer positions are evaluated 0.00, too many still are. And many positions remain incorrectly evaluated, either given scores that are excessively high/low. Some are outright wrong."

"Enter Fat Fritz 2. Existing NNUE architecture has a network of 256 neurons." "When reading that Fat Fritz 2 supplies a NNUE that's twice the size of what I was using, I was intrigued."

A snake cutting open the abdomen of a toad, inserting its head, pulling out the toad's organs, and swallowing them, all while the toad is alive. It may take several hours before it dies. Three species of Asian kukri snakes feed this way. With video.

Humans probably responsible for global dimming... which we're doing less of. The amount of sunlight reaching the Earth’s surface declined steadily from the 1950s to the late 1980s, then turned around and the amount of sunlight brightened again.

The question was whether human pollution caused this or is it the result of natural variations in the climate system? "Cloud cover may have changed over the years, absorbing the sun’s rays more effectively during the dimming phase than during the brightening phase."

To answer the question, researchers filtered out the effects of cloud cover to see whether these long-​term fluctuations in solar radiation also occurred in cloud-​free conditions. Finding they did, the researchers ruled out clouds and decided aerosols entering the atmosphere due to air pollution are probably the major contributor to global dimming.

"If someone loses their sense of touch and 'proprioception' -- their sense of body position -- as an adult, they may learn compensatory skills using visual cues and conscious thought, or reasoning, to move their bodies. Someone who has never had a sense of touch or proprioception, however, can find faster, unconscious ways of processing visual cues to move and orient themselves."

Wait, what? It's possible for someone to lose their sense of touch and proprioception? That's news to me.

"The team worked with two individuals -- called Ian and Kim -- who have had unique sensory experiences: Ian developed a complete loss of tactile sense and proprioception (sense of body position), together called somatosensation, below his neck after an autoimmune response to an illness as a teenager. Kim was born without somatosensation, lacking the sensory nerve fibres needed to feel her body."

"For the study, Kim and Ian came into the lab at the University of Birmingham, along with age-matched control subjects, to participate in a number of experiments designed to assess both their mental image of their bodies as well as their unconscious sense of their bodies in space. These included reporting on the shape and size of their hands by moving a cursor on a screen to locate landmarks like fingertips and knuckles, and estimating their 'reach' distance (the length of their arm)."

"The study found a number of similarities and, intriguingly, differences in how Kim and Ian performed in the experiments. In the hand experiment, for example, Kim's estimation of her hand shape and size was close to the control group's, being wider and shorter than her actual hand, whereas Ian's was much more accurate."

"We think the differences between Ian's and Kim's responses relate to the visual control that both of them use to navigate their environment. For Ian, this is a very conscious process and he has learned to use visual cues to continually evaluate and monitor that environment. For Kim the process is much more unconscious."

Astronomers found signs of a Neptune-​sized planet in the habitable zone in the Al­pha Cen­tauri star sys­tem, 4.4 light years away from here. The "habitable zone" is the zone around a star that may of­fer suit­able con­di­tions for life -- not too hot, not too cold, the Goldilocks zone.

"One reason that the search for Earth-​like plan­ets has so far proved fruit­less is that it has been con­duc­ted in the near-​infrared range, even though Earth-​like plan­ets that might have wa­ter are bright­est in the mid-​infrared range. Yet it is pre­cisely in that range that meas­ure­ments with nor­mal tele­scopes are dif­fi­cult, be­cause that is where the Earth and its at­mo­sphere are also at their bright­est. This means the faint sig­nals from exo­plan­ets are lost in par­tic­u­larly strong back­ground noise."

"Re­search­ers have now been able to over­come this dif­fi­culty and take meas­ure­ments in the mid-​infrared range. They used the Very Large Tele­scope at the European South­ern Ob­ser­vat­ory in Chile to ex­am­ine Al­pha Cen­tauri stars A and B, log­ging nearly 100 hours over the course of a month."

"The re­search­ers not only pro­cessed a huge volume of data, they also em­ployed two soph­ist­ic­ated meas­ure­ment tech­niques: one was to use a new de­form­able sec­ond­ary tele­scope mir­ror, which made it pos­sible to cor­rect for dis­tor­tions in the light com­ing through the Earth's at­mo­sphere; and the other was to use a coro­na­graph to al­tern­ately block the light from each of the stars in turn at very short in­ter­vals."

"A neural network trained on high-resolution maps of protein-DNA interactions can uncover subtle DNA sequence patterns throughout the genome and provide a deeper understanding of how these sequences are organized to regulate genes."

"One of the big unsolved problems in biology is the genome's second code -- its regulatory code. DNA bases (commonly represented by letters A, C, G, and T) encode not only the instructions for how to build proteins, but also when and where to make these proteins in an organism. The regulatory code is read by proteins called transcription factors that bind to short stretches of DNA called motifs. However, how particular combinations and arrangements of motifs specify regulatory activity is an extremely complex problem that has been hard to pin down."

"A neural network -- named BPNet for Base Pair Network -- that can be interpreted to reveal regulatory code by predicting transcription factor binding from DNA sequences with unprecedented accuracy. The key was to perform transcription factor-DNA binding experiments and computational modeling at the highest possible resolution, down to the level of individual DNA bases. This increased resolution allowed them to develop new interpretation tools to extract the key elemental sequence patterns such as transcription factor binding motifs and the combinatorial rules by which motifs function together as a regulatory code."

"The neural network models enabled the researchers to discover a striking rule that governs binding of the well-studied transcription factor called Nanog. They found that Nanog binds cooperatively to DNA when multiples of its motif are present in a periodic fashion such that they appear on the same side of the spiraling DNA helix."

"There has been a long trail of experimental evidence that such motif periodicity sometimes exists in the regulatory code. However, the exact circumstances were elusive, and Nanog had not been a suspect. Discovering that Nanog has such a pattern, and seeing additional details of its interactions, was surprising because we did not specifically search for this pattern."

"BPNet's network architecture is similar to that of neural networks used for facial recognition in images." "BPNet learns from the raw DNA sequence and learns to detect sequence motifs and eventually the higher-order rules by which the elements predict the base-resolution binding data."

So, it took to here to find out it's a convolutional network. I would tell you more but the full paper is paywalled, so I just have to quote from the press release. They somehow combined a convolutional neural network with "interpretation tools".

"Once the model is trained to be highly accurate, the learned patterns are extracted with interpretation tools. The output signal is traced back to the input sequences to reveal sequence motifs. The final step is to use the model as an oracle and systematically query it with specific DNA sequence designs, similar to what one would do to test hypotheses experimentally, to reveal the rules by which sequence motifs function in a combinatorial manner."

That's all we get to know about the "interpretation tools". They say they used CRISPR to experimentally verify that the results from the interpretation tools are correct. Also the press release doesn't mention it, but this experiment was limited specifically to "base-resolution chromatin immunoprecipitation (ChIP)–nexus binding profiles of pluripotency transcription factors". Pluripotency transcription factors are transcription factors that play a role in reprogramming somatic cells back into an embryonic stem cell-like state. Nanog is one of these which is probably why they were looking at it. chromatin immunoprecipitation is a specific technique for mapping transcription factors and other "promoters" that bind to DNA binding sites.

Sepsis is a major killer and now there may be an intervention (or two) for it. The focus is two molecules called ADM and DPP3. ADM stands for adrenomedullin and DPP3 stands for dipeptidyl peptidase 3. The idea is to use rapid bedside biomarker assays and intervene to either increase ADM or block DPP3, depending on what the assay reports is going on in the person's body.

ADM affects endothelial barrier function, which is to say, the cells that line the interior of blood vessels (and also lymphatic vessels), and which regulate what can go in and out of the blood. DPP3, on the other hand, is a cytosolic enzyme, which is to say it's an enzyme that operates inside cells but outside the nucleus, in what's called the cytosol, and its job is hydrolysing short proteins between three and ten amino acids in length, which is to say, its job is to chop up certain proteins. One of those proteins is angiotensin II, which is essential to regulation of the the degree of constriction vs dilation of blood vessels, which is called "vascular tone", and essential for proper regulation of blood pressure. When DPP3 spirals upward out of control, angiotensin II also goes out of control, vascular tone goes out of control, and blood pressure falls.

You might be wondering how ADM and DPP3 are controlled by these medical interventions? In the case of ADM it's done with an ADM antibody called Adrecizumab. ADM-Adrecizumab complexes cannot cross the endothelial barrier, effectively trapping ADM in the circulation, where ADM stabilizes the endothelial barrier function and vessel tone which reduces septic shock.

In the case of DDP3, antibodies that help the immune system dispose of DPP3 have been identified, at least in lab animals, and neutralizing DPP3 reduces septic shock. All this has been tested in lab animals, and the hope is that it will translate into medical treatment for humans.

Seeing through clouds. "Over the last few years, several cloud removal techniques have been developed: Sentinel-2 Cloudless, Mapbox Cloudless Atlas and Google's Cloudless Satellite Map. These techniques are sifting through multiple years of images to create cloud-free scenes. This works fine if the goal is to improve the aesthetics of the satellite images, but the trade-off is recency. In applications like ours, where we rely on the most recent images to monitor changes on the land, these techniques cannot be used."

"Clouds can be broadly classified into two types: dense, and thin or cirrus clouds. Dense clouds do not allow the penetration of visible spectral radiation from the ground and tend to cast a shadow on the ground."

"Thin or cirrus clouds on the other hand are transparent or semi-transparent clouds. Most spectral bands can partially see through these clouds. This is key to accurate de-clouding with our model."

"Our main contribution is to create a training dataset based on (cloud, no-cloud) pairs for the same geography but from different days. The machine learning model then learns to re-construct the no-cloud sample from the cloud sample."

"The basic assumption is that between cloud and no-cloud scenes only cloud pixels will change. This simple approach worked very well for us."

Video from Mars. NASA put a bunch of cameras on the spacecraft so all of us could experience the landing as close to actually being there as possible. We can look at the parachute inflating, the descent with the heat shield, the separation of the rover and descent stage, the touchdown at the landing site, with the engines blowing dust around on the surface. We can look upward from the rover to the descent stage. They even put microphones on the rover so you can hear wind gusts from another planet.

The mystery of where fast radio bursts (FRBs) come from looks like it's solved. One of the greatest mysteries in astronomy. A fast radio burst was observed, and the source was tracked down to a magnetar. The magnetar goes by the unmemorable name "J1935+2154". It's in the Milky Way about 30,000 light years from here, located in the sky in the constellation Vulpecula.

Magnetars are dead massive stars after they've gone supernova and turned into neutron 'stars', which have insanely high magnetic fields -- billions of times stronger than the sun's.

As for FRBs, "They release a huge amount of energy in only several milliseconds. About a hundred such events have been detected in different regions of our universe. Moreover, repeated FRBs have been found from the same direction."

The Hard X-ray Modulation Telescope (HXMT), named "Insight", China's first X-ray astronomy satellite, determined that a double-spike structure of an X-ray burst was the high energy counterpart of "FRB 200428". "This discovery, together with results from other telescopes, proves that FRBs can come from magnetar bursts, thus resolving the longstanding puzzle concerning the origin of FRBs."

"On April 28, 2020 at 14:34 GMT, the Canadian CHIME experiment and the STARE2 experiment in the US independently detected a very bright FRB, which was named FRB 200428. It came from roughly the same direction as the Galactic magnetar SGR J1935+2154. Based on the FRB's dispersion measurement, the source of this FRB was located about 30,000 light-years away, which approximately agrees with the distance to SGR J1935+2154."

Photons can fuse. Photons -- particles of light, not protons. This is something I did not know was possible. But apparently theoretical physics predicted it and it has now been observed at the LHC. When photons fuse, they form leptons. Electrons are leptons, but they are not the only subatomic particle in the category. There are also muons and tau particles, and each of these have associated neutrinos (electron neutrino, muon neutrino, and tau neutrino).

"If two photons collide, the result could be an electron-positron pair or a muon-antimuon pair (a muon is about 200 times more massive than an electron)."

All you need to achieve this is energy sufficiently intense to exceed the Schwinger limit of 10^18 volts per meter.

In quantum electrodynamics (QED), the Schwinger limit is supposed to mark a point where an electromagnetic field becomes nonlinear. It's a very high energy level, capable of accelerating protons (protons, not photons -- the words look similar) at the LHC from rest to the LHC's maximum speed in 5 micrometers. How this break in linearity leads to particle creation is beyond me.