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The AWWA Sky Whale concept represents luxurious and greener aviation.

AWWA Sky Whale, a large, intriguing-looking flying machine, is meant to represent the pinnacle of luxury, performance, and sustainability.

At a recent exhibition on future transportation hosted at Kuwait’s Sheikh Abdullah Al Salem Cultural Center, the design of Oscar Vinals was on display.

The Sky Whale concept focuses on the “green” aircraft designs of the future for the ordinary airliner planes of the twenty-first century, which might profit from technological solutions that are more eco-friendly, most efficient, and offer maximum performance.

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Ray Kurzweil is an author, inventor, and futurist.

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Last night at 23:14 UTC, NASA’s DART spacecraft successfully struck asteroid Dimorphos, the 160-metre moonlet orbiting around the larger Didymos asteroid. About 38 seconds later, the time it took for the light to arrive at Earth, people all over the world saw the abrupt end of the live stream from the spacecraft, signalling that the impact had happened successfully – DART was no more.

Astronomers on a small slice of our planet’s surface, extending from southern and eastern Africa to the Indian Ocean and the Arabian Peninsula, could actually watch it live with their telescopes. Among those were a half dozen stations joined together for a dedicated observing campaign organised by ESA’s Planetary Defence Office and coordinated by the team of observers of the Agency’s Near-Earth Object Coordination Centre (NEOCC). As usual, when such a timely astronomical event happens, not all stations were successful in their observations: clouds, technical problems and other issues always affect real-life observations.

However, a few of ESA’s collaborating stations could immediately report a successful direct confirmation of DART’s impact. Among them was the team of the Les Makes observatory, on the French island of La Reunion in the Indian Ocean. The sequence of images they provided in real time was impressive: the asteroid immediately started brightening upon impact, and within a few seconds it was already noticeably brighter. Within less than a minute a cloud of ejected material became visible and could be followed while it drifted eastwards and slowly dissipated.

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In a new paper published today in the journal Nature Ecology and Evolution, scientists have estimated the conservation status of nearly 1,900 palm species using artificial intelligence, and found more than 1,000 may be at risk of extinction.

The international team of researchers from the Royal Botanic Gardens, Kew, the University of Zurich, and the University of Amsterdam, combined existing data from the International Union for Conservation of Nature (IUCN) Red List with novel machine learning techniques to paint a clearer picture of how palms may be threatened. Although popular and well represented on the Red List, the threat to some 70% of these plants has remained unclear until now.

The IUCN Red List of Threatened Species is widely considered to be a gold standard for evaluating the conservation status of animal, plant, and . But there are gaps in the Red List that need to be addressed, as not all species have been listed and many of the assessments are in need of an update. Conservation efforts are further complicated by inadequate funding, the sheer amount of time needed to manually assess a species, and public perception favoring certain over plants and fungi.

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Daegu Gyeongbuk Institute of Science & Technology (DGIST, President Yang Kook) Professor Hongsoo Choi’s team of the Department of Robotics and Mechatronics Engineering collaborated with Professor Sung-Won Kim’s team at Seoul St. Mary’s Hospital, Catholic University of Korea, and Professor Bradley J. Nelson’s team at ETH Zurich to develop a technology that produces more than 100 microrobots per minute that can be disintegrated in the body.

Microrobots aiming at minimal invasive targeted precision therapy can be manufactured in various ways. Among them, ultra-fine 3D called two-photon polymerization method, a method that triggers polymerization by intersecting two lasers in synthetic resin, is the most used. This technology can produce a structure with nanometer-level precision. However, a disadvantage exists in that producing one microrobot is time consuming because voxels, the pixels realized by 3D printing, must be cured successively. In addition, the magnetic nanoparticles contained in the robot can block the light path during the two-photon polymerization process. This process result may not be uniform when using magnetic nanoparticles with high concentration.

To overcome the limitations of the existing microrobot manufacturing method, DGIST Professor Hongsoo Choi’s research team developed a method to create microrobots at a high speed of 100 per minute by flowing a mixture of magnetic nanoparticles and gelatin methacrylate, which is biodegradable and can be cured by light, into the microfluidic chip. This is more than 10,000 times faster than using the existing two-photon polymerization method to manufacture microrobots.

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The joint research team of Professor Choi Hongsoo at Robotics Engineering, DGIST, a senior researcher Jinyoung Kim from DGIST-ETH Microrobotics Research Center, and the research team of Professor Sung Won Kim at Seoul St. Mary’s Hospital of the Catholic University, made a breakthrough for the improvement of the therapeutic efficacy and safety in stem cell-based treatments.

The team developed a magnetically powered human nuclear transfer (hNTSC)-based and a method of minimally invasive of therapeutic agents into the brain via the intranasal pathway. And they also accomplished transplanting the developed stem cell-based microrobot into brain tissue through the intranasal pathway that bypasses the . The proposed method is superior in efficacy and safety compared to the conventional surgical method and is expected to bring new possibilities of treating various intractable neurological diseases such as Alzheimer’s disease, Parkinson’s disease, and brain tumors, in the future.

The limitation of stem cell therapy is the difficulty in delivering an exact amount of stem to an accurate targeted location deep in the body where the treatment is with high risk. Another limitation is that both efficacy and safety of the treatment are low owing to a large amount of the therapeutic agent loss during delivery, while the cost of the treatment is high. In particular, when delivering stem cells into the brain through blood, the efficiency of cell delivery may decrease owing to the “blood-brain barrier,” which is a unique and specific component of the cerebrovascular network.

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One day they shall make nano bots out of graphine.

A team of researchers affiliated with several institutions in South Korea has created microrobots that are able to serve as bridge builders between rat nerve cell networks. In their paper published in the journal Science Advances, the group describes how their microrobots were constructed and how well they served as a bridge builder between neural networks.

Scientists have taken many approaches to study of the brain. One way is to try to grow a brain from nerve cells. Prior work has shown that it is possible to grow a network of neural cells on a Such a network is, of course, 2-D. In this new effort, the researchers have taken a step toward the creation of a 3D neural network by devising a way to connect 2-D neural networks using microrobots.

The work consisted of creating rectangular microrobots (300 micrometers long and 95 micrometers wide) out of a polymer coated with nickel and titanium. The movement of the microrobot was controlled by applying external magnetic fields. To make use of such robots, the researchers first grew two separate neural networks on a plate of glass just 300 micrometers apart. Next, they grew another neural network on the surface of the microrobot. Once all the networks were grown and in place, the researchers applied a magnetic field to the robot to push it into place between the other two neural networks. Another magnetic field was used to fine-tune the position of the microrobot relative to the two networks. And then the researchers simply waited and watched as events unfolded. They found that not only did nerve cells grow from either end of the microrobot toward the other neural networks, but the other networks began reaching out to the network on the microrobot.

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