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A drone is an autonomous unmanned aerial vehicle (UAV) that can be programmed for automatic routing and delivery. These come handy in delivery medicines which is easier to carry and can add value to the pharma supply chain. Drone helps to deliver to places with the high expense involved or poor infrastructure and thereby plays a significant role in last-mile delivery.

The pace with which they are now being used for delivery, even Amazon is experimenting with the delivery mechanism offered by drone as its logistics and transport market is forecast to grow 20% in coming times.

Originally a bunch of children’s toys, then comic books, cartoons and movies, robot action figures than morph into vehicles and back again have proved immensely popular over the years. After a successful Kickstarter last year, Robosen Robotics has launched the T9, a robot that transforms into a vehicle through voice commands or via an app.

There are many Transformer-like robot toys already available, but most require the user to manually change the thing from action figure to vehicle, animal, device or whatever, and back again. Like the bots from the cartoons and movies, the T9 is an actual transforming robot designed to stimulate a child’s interest in programming, robotics and artificial intelligence.

The T9 is claimed to be the first robot in the consumer space that can automatically move from vehicle to robot and back again, can walk on two legs when in robot form, race on its wheels when in vehicle form, involves coding and program development, and can be controlled by voice commands or through a mobile app. It can even bust some funky dance moves if you want it to.

What the reasons underlying these impairments are is yet unclear but scientists at the Center for Regenerative Therapies of TU Dresden (CRTD) wanted to investigate if increasing the number of stem cells in the brain would help in recovering cognitive functions, such as learning and memory, that are lost during ageing.”

https://tu-dresden.de/tu-dresden/newsportal/news/verjuengung…en-maeusen

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Ein jeder wird es irgendwann erleben: Je älter wir werden, desto schwieriger wird es für unser Gehirn, neue Dinge zu lernen und sich an sie zu erinnern. Die Gründe hinter diesen Beeinträchtigungen sind oft unklar. Nun haben Wissenschaftler des Zentrums für Regenerative Therapien der TU Dresden (CRTD) untersucht, ob eine Erhöhung der Anzahl von Hirnstammzellen helfen würde, kognitive Funktionen wie Lernen und Gedächtnis wiederzuerlangen, die im Laufe des Alterns verloren gehen.

Die Forschungsgruppe von Prof. Federico Calegari hat dazu eine im eigenen Labor entwickelte Methode verwendet: Im Gehirn alter Mäuse stimulierten die Wissenschaftler den dort vorhandenen kleinen Pool neuronaler Stammzellen so, dass sich die Menge dieser Stammzellen und damit auch die Anzahl der aus ihnen erzeugten Gehirnzellen erhöhte. Das Team beobachtete, dass diese zusätzlichen Neuronen überleben und sogar neue Kontakte zu benachbarten Zellen knüpfen können. In einem nächsten Schritt untersuchten die Wissenschaftler eine wichtige Aufgabe des Gehirns, die ähnlich wie bei der Maus auch beim Menschen im Laufe des Alterns verloren geht: die Navigationsfähigkeit.

Satellites have been flying around the earth for decades — scanning landscapes and capturing images of our fast-changing planet. Remote sensing has been around since even before the first flight of the Wright brothers. It was restricted to hot air balloon flights back then. Systematic aerial photography and satellite remote sensing reached an inflection point during the Cold War, when the need for surveillance led to modification of combat aircraft for the purpose of spying. The space race also gave a fillip to satellite launches. The first satellite photographs of the earth were taken on August 14, 1959 and satellite image processing techniques evolved in 1960s and 1970s.

Till late 1990s, the primary consumer of remote sensing data was either governments bodies or defence agencies. This was because of the strategically sensitive nature of technology, which gave birth to the fear that it can be used for spying. However, after the fall of the Soviet Union commercial satellite imagery market began to evolve and IKONOS became the first commercial, very-high resolution satellite to be launched in 1999. Another factor in play was the growing use of computer software for analysis of data and satellite data consumption benefited from this growth in the 1990s.

The 21st century saw rapid changes in the remote sensing industry. Data consumption continued to increase. This was accelerated by the fall in costs of satellite imagery. Moreover, open data sources emerged with Landsat data becoming publicly available in 2009. Copernicus Hub followed in 2014 when the European Space Agency launched Sentinel 1. Another inflection point occurred in the industry when Planet launched a constellation of 88 Dove satellites abroad the PSLV-C37 of ISRO. These are shoe-box sized satellites leveraging the power of off-the-shelf consumer electronics to reduce costs. Further innovation in satellite launching by a slew of startups led by SpaceX has reduced costs of launching satellites.

Proteins are often called the working molecules of the human body. A typical body has more than 20,000 different types of proteins, each of which is involved in many functions essential to human life.

Now, Purdue University researchers have designed a novel approach to use deep learning to better understand how proteins interact in the body – paving the way to producing accurate structure models of protein interactions involved in various diseases and to design better drugs that specifically target protein interactions. The work is released online in Bioinformatics.

“To understand molecular mechanisms of functions of protein complexes, biologists have been using experimental methods such as X-rays and microscopes, but they are time- and resource-intensive efforts,” said Daisuke Kihara, a professor of biological sciences and computer science in Purdue’s College of Science, who leads the research team. “Bioinformatics researchers in our lab and other institutions have been developing computational methods for modeling protein complexes. One big challenge is that a computational method usually generates thousands of models, and choosing the correct one or ranking the models can be difficult.”

For the moment, massive job losses from automation and artificial intelligence are a largely theoretical worry. But tax economists and lawyers are thinking through the economic circumstances in which robot taxes might make sense and the tricky legal decisions and definitions needed to implement them.


A debate is heating up over whether businesses should pay up when they replace human workers with machines.