Following the 2017 Royal Rumble, the WrestleMania 33 match card looks to be falling into place. Brock Lesnar vs. Goldberg has already been made official for the pay-per-view, and a few of the other top matches aren't difficult to predict. There seems to be some uncertainty, however, surrounding the future plans for WWE's biggest full-time performer. With WrestleMania 33 still nearly two months away, Cena's opponent remains unclear. As the current WWE Champion, Cena is in line to face Royal Rumble winner Randy Orton on April 2 in Orlando. That could change at Sunday's PPV when Cena puts his belt on the line against five other wrestlers in the Elimination Chamber.

Skin cancer is the most commonly diagnosed cancer in the United States. Over five million cases are diagnosed each year, costing the U.S. healthcare system over $8 billion. More than 100,000 of these cases involve melanoma, the deadliest form of skin cancer, which leads to over 9,000 deaths a year, and the numbers continue to grow. Internationally, melanoma also poses a major public health threat. In Australia, there are over 13,000 new instances of melanoma yearly, leading to more than 1,600 deaths.

The autoregression integrated moving average model or ARIMA model can seem intimidating to beginners. A good way to pull back the curtain in the method is to to use a trained model to make predictions manually. This demonstrates that ARIMA is a linear regression model at its core. Making manual predictions with a fit ARIMA models may also be a requirement in your project, meaning that you can save the coefficients from the fit model and use them as configuration in your own code to make predictions without the need for heavy Python libraries in a production environment. In this tutorial, you will discover how to make manual predictions with a trained ARIMA model in Python.

Facebook has extended its controversial'Safety Check' to let people offer help. The Safety Check tool has been available since 2014 and is activated whenever a crisis is present, allowing people to tell their friends and family that they are safe. But the new tool will allow the actually help out. The Community Help feature allows unaffected people to offer help – like blankets or accomodation – to people who are in the area of such a crisis. The giant human-like robot bears a striking resemblance to the military robots starring in the movie'Avatar' and is claimed as a world first by its creators from a South Korean robotic company Waseda University's saxophonist robot WAS-5, developed by professor Atsuo Takanishi and Kaptain Rock playing one string light saber guitar perform jam session A man looks at an exhibit entitled'Mimus' a giant industrial robot which has been reprogrammed to interact with humans during a photocall at the new Design Museum in South Kensington, London Electrification Guru Dr. Wolfgang Ziebart talks about the electric Jaguar I-PACE concept SUV before it was unveiled before the Los Angeles Auto Show in Los Angeles, California, U.S The Jaguar I-PACE Concept car is the start of a new era for Jaguar.

Last August, NASA opened the first round of the Space Robotics Challenge. A follow-on to the DARPA Robotics Challenge, the SRC is focused on what it's going to take to get humans back to the moon or on to Mars, embracing the idea that sending humanoid robots there first would make everything a heck of a lot easier. Just like the DRC, the SRC starts in simulation, with an initial round to select 20 finalists from 93 competing teams. NASA has just announced the results. In order to make it into one of the 20 finalist slots, teams had to perform some simple tasks in simulation (using Gazebo) as quickly as possible.

Good weather seldom lasts more than a few hours off the coast of Antarctica, and after a remarkable day of cloudless fine conditions, the next day dawns grey and cold. The research vessel, Akademik Treshnikov, moves back from its parking spot against the glacier and sails to a nearby location, where the submarine is again launched. Instead of exploring the underside of the glacier, this time the focus is on marine life on the ocean floor. As the unmanned sub reaches a depth of 900m, a giant sponge resembling an enormous gourd looms into view. The four-man team operating the robotic sub manoeuvre it into place, and then using a robotic arm, lift the beautiful creature from its perch, and places it in one of the sampling boxes.

Gab Scanu works alone, with a special operating licence for his UAV (unmanned aerial vehicle) from the Civil Aviation Safety Authority in Australia. The 20-year-old's drone photography shows a new perspective on well-known locations such as Sydney's Bondi beach, Mona Vale and other famous coastlines on the country's east coast. He has also travelled abroad and shot the LA coast at Malibu. The son of a cinematographer, Scanu has inherited a keen eye for photographic composition, capturing both the dramatic and the picturesque qualities of the Australian summer experience. He has developed a unique style and feel, using a combination of post production and drone technology to capture often never-before-seen landscape views.

In surpassing 30,000 attendees - up from 19,000 the year previous - AWS re:Invent 2016 continues to capture the imagination of the partner, customer and developer communities. Yet despite the bumper crowds, it was intelligence exhibited by machines that stole the show in Las Vegas. Artificial intelligence to be precise, heralded as the next great disrupter in cloud, and the weapon of choice for vendors fighting for increased market share. While nothing is certain in life but death and taxes - well, perhaps for some - when it comes to public cloud, the dominance of Amazon Web Services is both predictable and undeniable. Yet the battle for control of the skies has been raised a notch further with the tech giant enhancing its services across its broad portfolio, with its new cloud-native database offerings designed to lure large enterprise accounts.

Step into the latest exhibition at London's Science Museum, and you will be instantly welcomed by an animatronic baby. With his moving arms and blinking eyes, this incredibly realistic mechanical human is a bewildering - if not unsettling - sight. And that's one of the goals of the museum's new show looking at 500 years of humanoid robots: to chart their evolution and explore our reaction towards them throughout history. "Robots trouble us," curator Ben Russell tells Al Jazeera. "When you see a robot you're reading a lot into it as a human. If they are very life-like you don't really know what is the source of their being," he continues.

The autoregression integrated moving average model or ARIMA model can seem intimidating to beginners. A good way to pull back the curtain in the method is to to use a trained model to make predictions manually. This demonstrates that ARIMA is a linear regression model at its core. Making manual predictions with a fit ARIMA models may also be a requirement in your project, meaning that you can save the coefficients from the fit model and use them as configuration in your own code to make predictions without the need for heavy Python libraries in a production environment. In this tutorial, you will discover how to make manual predictions with a trained ARIMA model in Python.