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Category: robotics/AI

Beijing’s Da Vinci Dynamics has launched its DC100, a high-performance electric streetbike with an impressive 250-mile (400 km) NEDC range, and some wacky “robotic” tricks, including the alleged ability to self-balance and follow you around.

We’ve got ourselves a bit of a kitchen sinker here; Da Vinci has thrown all sorts of features at this one. But even some of the basic specs are a tad elusive. For starters, while it makes a peak of 135 horsepower, putting it very much in the “fast electric” category, the company says it runs “a smart control system that seamlessly integrates multiple different motors.” Who the what now? Multiple motors? A separate press release then states it’s actually 137 horsepower, running through a hub motor.

Peak torque is listed at a ludicrous 850 Nm (627 lb-ft), but then hub motors often have wild torque specs; witness the outrageous Verge TS, with a hub motor that doesn’t even need a middle in it to break 1000 Nm (738 lb-ft). The DC100 will sprint from 0–100 km/h in somewhere between 3–4 seconds, so crazy torque or no crazy torque, a well-ridden gixxer will still see it off at the lights.

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An organic transistor that incorporates two bulk heterojunctions can exhibit active photoadaptation behaviour for light intensities that range over six orders of magnitude.

The development of artificial visual systems that mimic biological systems requires devices that can autonomously adapt their response to varying stimuli. However, emulating biological feedforward visual adaptation is challenging and requires complementary photoexcitation and inhibition, ideally in a single device. Here we show that an organic transistor that incorporates two bulk heterojunctions is capable of light intensity-dependent active photoadaptation. The approach couples the photovoltaic effect in bulk heterojunctions with electron trapping in the dielectric layer, allowing adaptive modulation of the carrier concentration of the transistor. Our device exhibits active photoadaptation behaviour for light intensities ranging over six orders of magnitude (1 to 106 cd m−2).

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Bioprinting in seconds.

Biofabrication technologies, including stereolithography and extrusion-based printing, are revolutionizing the creation of complex engineered tissues. The current paradigm in bioprinting relies on the additive layer-by-layer deposition and assembly of repetitive building blocks, typically cell-laden hydrogel fibers or voxels, single cells, or cellular aggregates. The scalability of these additive manufacturing technologies is limited by their printing velocity, as lengthy biofabrication processes impair cell functionality. Overcoming such limitations, the volumetric bioprinting of clinically relevant sized, anatomically shaped constructs, in a time frame ranging from seconds to tens of seconds is described. An optical-tomography-inspired printing approach, based on visible light projection, is developed to generate cell-laden tissue constructs with high viability (85%) from gelatin-based photoresponsive hydrogels. Free-form architectures, difficult to reproduce with conventional printing, are obtained, including anatomically correct trabecular bone models with embedded angiogenic sprouts and meniscal grafts. The latter undergoes maturation in vitro as the bioprinted chondroprogenitor cells synthesize neo-fibrocartilage matrix. Moreover, free-floating structures are generated, as demonstrated by printing functional hydrogel-based ball-and-cage fluidic valves. Volumetric bioprinting permits the creation of geometrically complex, centimeter-scale constructs at an unprecedented printing velocity, opening new avenues for upscaling the production of hydrogel-based constructs and for their application in tissue engineering, regenerative medicine, and soft robotics.

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DeepMind is using its AI prowess to accelerate scientific work.

AI research lab DeepMind has created the most comprehensive map of human proteins to date using artificial intelligence. The company, a subsidiary of Google-parent Alphabet, is releasing the data for free, with some scientists comparing the potential impact of the work to that of the Human Genome Project, an international effort to map every human gene.

Proteins are long, complex molecules that perform numerous tasks in the body, from building tissue to fighting disease. Their purpose is dictated by their structure, which folds like origami into complex and irregular shapes. Understanding how a protein folds helps explain its function, which in turn helps scientists with a range of tasks — from pursuing fundamental research on how the body works, to designing new medicines and treatments.

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Neuroscientists removed fear from rats by inactivating amygdala — brain region mediating fear.

#Neuroscience #Brain #YuriNeuro #Neurobiology #Amygdala.

Timecodes:
0:00-Introduction.
0:17-Amygdala role in fear regulation.
0:45-Difficulties in exploring prey-predator interaction.
1:02-Lego robot to simulate a predator. Robogator (LEGO Mindstorms robot)
1:53-Fear response before the amygdala inactivation.
2:33-Fear response aftert the amygdala inactivation.
3:59-Amygdala is one of the key regions of the fear regulation.
4:50 — Human-based experiments on the electrical stimulation of amygdala.
6:01-Future prospects. Optogenetics.
6:34-Share your ideas and emotions in the comments.

In this video I review a scientific neuroscience publication :“Amygdala regulates risk of predation in rats foraging in a dynamic fear environment” from University of Washington and Korea University, Seoul. The scientific paper addresses the mechanism of fear regulation in rats. Neuroscientists inactivated neurons of the brain region regulating fear — amygdala. In order to inactivate amygdala neurons neurobiologists applied GABAA receptor agonist muscimol. In this way neuroscientists made the rat fearless. Neurobiologists simulated fear enviroment by using lego robot — Robogator (LEGO Mindstorms robot) programmed to surge toward the animal as it emerges from the nesting area in search of food.

Neuroscientists also increased the activity of amygdala neurons by applying GABAA receptor antagonist bicuculline methiodide. In this way neuroscience researchers increased the fear response of the laboratory rodent.

Similar role of amygdala in fear regulation was demonstrated for humans. For instance, in 2007 neuro researchers from Universite de Provence from France in their paper :” Emotion induction after direct intracerebral stimulations of human amygdala ” electrically stimulated amygdala and could induce negative emotions that were either verbally self-reported by a participant or measured by physiological markers such as skin conductance.

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Large space structures, such as telescopes and spacecraft, should ideally be assembled directly in space, as they are difficult or impossible to launch from Earth as a single piece. In several cases, however, assembling these technologies manually in space is either highly expensive or unfeasible.

In recent years, roboticists have thus been trying to develop systems that could be used to automatically assemble structures in . To simplify this , space structures could have a modular design, which essentially means that they are comprised of different building blocks or modules that can be shifted to create different shapes or forms.

Researchers at the German Aerospace Center (DLR) and Technische Universität München (TUM) have recently developed an autonomous planner that could be used to assemble reconfigurable structures directly in space. This system, introduced in a paper presented at the 2021 IEEE Aerospace Conference, could allow aerospace engineers and astronauts to assemble large structures in space and adapt them for specific use cases, reconfiguring them when necessary.

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There are many reasons for drones to be quick. The professional drone racing circuit aside, speed bodes well when you are searching for survivors on a disaster site, or delivering cargo, or even inspecting critical infrastructure. But how do you get something done in the shortest possible time with limited battery life when you have to navigate through obstacles, changing speeds, and altitude? You use an algorithm.

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DeepMind and EMBL release the most complete database of predicted 3D structures of human proteins.

Partners use AlphaFold, the AI system recognized last year as a solution to the protein structure prediction problem, to release more than 350000 protein structure predictions including the entire human proteome to the scientific community.

DeepMind today announced its partnership with the European Molecular Biology Laboratory (EMBL), Europe’s flagship laboratory for the life sciences, to make the most complete and accurate database yet of predicted protein structure models for the human proteome. This will cover all ~20000 proteins expressed by the human genome, and the data will be freely and openly available to the scientific community. The database and artificial intelligence system provide structural biologists with powerful new tools for examining a protein’s three-dimensional structure, and offer a treasure trove of data that could unlock future advances and herald a new era for AI-enabled biology.

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