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Surprise your babies to boost their knowledge

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For a neuroscientists, studying an infants brain can be very compelling, as it is filled with vast knowledge of the fundamental aspects of life and also functioning on a subcortical level without any cortical inhibition. If you don’t know what cortical and subcortical means, the cortical represents the grey matter that lies on the surface of the brain and controls the consciousness, as for the subcortical it represents the white matter and also all the structures that lie beneath the cortex, like the cerebellum, brainstem and spinal cord.

Researchers at Johns Hopkins University have proved that by using this natural knowledge they have the ability to learn new things. Even more it seems that their brains react even better when an object is presented in a surprising form rather than simply showing them an object and explaining them what it is. For example by presenting to babies a ball passing through a wall, because they expect the ball to be stopped by the wall, they’re going to start to think about the balls mass and to develop some basic knowledge about physics. It seems that they will be more interested about an object that does something that they don’t predict rather than just a simple new toy. They’ve actually used this method in the study and gave the babies two options: To explore the object that did something surprising or to choose a new random object. By now I think you know what the babies chose.

“Babies can use their sophisticated prior knowledge of the world to guide what they should learn about in the future, when their expectations are violated, this might signal a special opportunity for them to learn.” Stahl Feigenson. Although they are not going to modify the recent guidelines in raising a child this study can determine parents to try and arouse the curiosity of their children rather than feeding them information.

Who doesn’t enjoy listening to a good story. Personally I love reading about the people who inspire me and what it took for them to achieve their success. As I am a bit of a self confessed tech geek I think there is no better way to discover these stories than by reading every day some articles or the newspaper . My bookcases are filled with good tech biographies, they remind me that anyone can be a success. So even if you come from an underprivileged part of society or you aren’t the smartest person in the room we all have a chance to reach the top. The same message shines in my beliefs. All it takes to succeed is a good idea, a little risk and a lot of hard work and any geek can become a success. VENI VIDI VICI .

Biology

The First 3D-Printed Vegan Salmon Is In Stores

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Revo Foods’ “THE FILET – Inspired By Salmon” salmon fillet may be the first 3D-printed food to hit store shelves. said that firm CEO Robin Simsa remarked, “With the milestone of industrial-scale 3D food printing, we are entering a creative food revolution, an era where food is being crafted exactly according to customer needs.”

Mycoprotein from filamentous fungi is used to make the salmon alternative and other meat substitutes. Vitamins and omega-3 fatty acids are in the product, like in animals. Is high in protein, at 9.5 grams per 100 grams, although less than conventional salmon.

Revo Foods and Mycorena developed 3D-printable mycoprotein. Years of research have led to laser-cooked cheesecakes and stacked lab-grown meats.

One reason for this push is because printed food alternatives may make food production more sustainable, which worries the fishing sector. Overfishing reduces fish populations in 34% of worldwide fish stocks.

Over 25% of worldwide greenhouse gas emissions come from food production, with 31% from livestock and fish farms and 18% from supply chain components including processing and shipping. According to Revo Foods’ website, vegan salmon fillet production consumes 77 to 86% less carbon dioxide and 95% less freshwater than conventional salmon harvesting and processing.

The salmon alternative’s sales potential is unknown. In order to succeed, Revo Foods believes that such goods must “recreate an authentic taste that appeals to the flexitarian market.”

The commercial distribution of 3D-printed food could change food production.

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Artificial Intelligence

Open-source Microsoft Novel protein-generating AI EvoDiff

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All diseases are based on proteins, natural molecules that perform vital cellular functions. Characterizing proteins can reveal disease mechanisms and ways to slow or reverse them, while creating proteins can lead to new drug classes.

The lab’s protein design process is computationally and human resource-intensive. It involves creating a protein structure that could perform a specific function in the body and then finding a protein sequence that could “fold” into that structure. To function, proteins must fold correctly into three-dimensional shapes.

Not everything has to be complicated.

Microsoft introduced EvoDiff, a general-purpose framework that generates “high-fidelity,” “diverse” proteins from protein sequences, this week. Unlike other protein-generating frameworks, EvoDiff doesn’t need target protein structure, eliminating the most laborious step.

Microsoft senior researcher Kevin Yang says EvoDiff, which is open source, could be used to create enzymes for new therapeutics, drug delivery, and industrial chemical reactions.

Yang, one of EvoDiff’s co-creators, told n an email interview that the platform will advance protein engineering beyond structure-function to sequence-first design. EvoDiff shows that ‘protein sequence is all you need’ to controllably design new proteins.

A 640-million-parameter model trained on data from all protein species and functional classes underpins EvoDiff. “Parameters” are the parts of an AI model learned from training data that define its skill at a problem, in this case protein generation. The model was trained using OpenFold sequence alignment data and UniRef50, a subset of UniProt, the UniProt consortium’s protein sequence and functional information database.

Modern image-generating models like Stable Diffusion and DALL-E 2 are diffusion models like EvoDiff. EvoDiff slowly subtracts noise from a protein made almost entirely of noise to move it closer to a protein sequence.

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Beyond image generation, diffusion models are being used to design novel proteins like EvoDiff, create music, and synthesize speech.

“If there’s one thing to take away [from EvoDiff], I think it’s this idea that we can — and should — do protein generation over sequence because of the generality, scale, and modularity we can achieve,” Microsoft senior researcher Ava Amini, another co-contributor, said via email. “Our diffusion framework lets us do that and control how we design these proteins to meet functional goals.”

EvoDiff can create new proteins and fill protein design “gaps,” as Amini noted. A protein amino acid sequence that meets criteria can be generated by the model from a part that binds to another protein.

EvoDiff can synthesize “disordered proteins” that don’t fold into a three-dimensional structure because it designs proteins in “sequence space” rather than structure. Disordered proteins enhance or decrease protein activity in biology and disease, like normal proteins.

EvoDiff research isn’t peer-reviewed yet. Microsoft data scientist Sarah Alamdari says the framework needs “a lot more scaling work” before it can be used commercially.

“This is just a 640-million-parameter model, and we may see improved generation quality if we scale up to billions,” Alamdari emailed. WeAI emonstrated some coarse-grained strategies, but to achieve even finer control, we would want to condition EvoDiff on text, chemical information, or other ways to specify the desired function.”

Next, the EvoDiff team will test the model’s lab-generated proteins for viability. Those who are will start work on the next framework.

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Biology

Chinese Dinosaur Might Have Been as Iridescent as a Hummingbird

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Earlier this month, I wrote an article on a toy line of scientifically accurate Velociraptor action figures with plumage inspired by modern birds. I mused how impressive it would be if prehistoric raptors had been covered by feather patterns not unlike those in the toy line. Little did I know that two weeks later, researchers would reveal that some theropods had iridescent feathers that outshine David Silva’s velocifigures.

The Caihong juji, Mandarin for “rainbow with a big crest” (or just Caihong for short), was a “paravian theropod,” a clade commonly known for its winged forelimbs (even though many weren’t capable of flight) and enlarged sickle foot claws. In 2014, a farmer in the Qinlong County in the Hebei Province of Northeastern China gave a nearly complete Caihong fossil, feathers included, to The Paleontological Museum of Liaoning. Finding a complete skeleton is rare in paleontology and proved very helpful to the researchers. However, you might wonder just how scientists were able to determine the iridescent nature of the Caihong’s plumage. Two words: fossilized melanosomes.

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Melanosomes are organelles that create, store, and transport melanin, which determines the pigments/colors of animal hair, fur, skin, scales, and feathers. Upon examining the Caihong’s head, crest, and tail feathers with an electron microscope, scientists discovered platelet-shaped structures similar in shape to the melanosomes that give hummingbirds their iridescent coloring. The rest of the body feathers had melanosome structures similar to those in the grey and black feathers of penguins, which would have made for an odd sight: a duck-sized dinosaur with body feathers as drab as a raven’s and head and neck feathers more colorful than a peacock’s.

The inferred feather coloration of the Caihong is not its only unusual feature, though. The dinosaur had longer arm and leg feathers than its relatives, and its tail feathers created a “tail surface area” that was larger than the famous proto-bird the Archaeopteryx.  Furthermore, the Caihong had bony crests, which while common among most dinosaurs, are almost unheard of among paravian theropods. But, more importantly, it had proportionally long forearms, which is a feature of flight-capable theropods, even though scientists believe the Caihong didn’t fly. While this dinosaur apparently has the earliest examples of proportionally long forearms in the theropod fossil records, it still falls in line with the belief that the evolution of flight-capable feathers outpaced the evolution of flight-capable skeletons. The melanosomes, however, are the more intriguing discovery, since they are the earliest examples of “organized platlet-shaped nanostructures…in dinosaurian feathers.”

While paleontologists are confident the Caihong’s platelet structures are melanosomes, the researchers understand that their discovery is based partially on inference and could potentially be incorrect. If the structures aren’t melanosomes, well, that invalidates this entire article. But that’s what paleontology is all about: examining the evidence, creating inferences supported by that evidence, and changing those inferences when new information becomes available. Still, the concept of dinosaurs with iridescent feathers is pretty cool. If you want to learn more about the Caihong juji, you can read the original article on Nature.

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