Scientists have just discovered a new species of heavyweight shark - but we're 20 million years too late to have seen it.
Based on fossilised teeth - themselves 4.5cm long - that were found in the US, Peru and Japan, researchers have formally described the ancient, extinct shark, named Megalolamna paradoxodon.
Although smaller than members of the "mega-toothed" lineage of shark containing the fearsome "megalodon" that reached well over 10 metres, the species was still considered an impressive-looking shark.
It was estimated to be minimally equivalent to the size of a typical modern-day great white, roughly four metres, and lived during the early Miocene epoch about 20 million years ago in the same ancient oceans in which the mega-toothed sharks roamed.
Belonging to a shark group called Lamniformes, which includes the modern-day great white and mako sharks, the shark had grasping-type front teeth and cutting-type rear teeth likely used to seize and slice medium-sized fish.
The new species name, "paradoxodon", or paradoxical teeth, comes from the fact that the shark appears to emerge suddenly in the geologic record with a-yet-unresolved nearly 45-million-year gap from when Megalolamna possibly split from its closest relative, Otodus.
"It's quite remarkable that such a large lamniform shark with such a global distribution had evaded recognition until now, especially because there are numerous Miocene localities where fossil shark teeth are well sampled," said US paleobiologist Professor Kenshu Shimada, who led the team behind the discovery.
Robots: the nurses of the future
Yet another study has pointed to a future of robot nurses caring for us in hospital.
An international research team led by Italian scientist Dr Elena De Momi has trained a robot to imitate human actions, indicating that humans and robots can effectively co-ordinate their actions during high-stakes events such as surgeries.
Over time, this could lead to improvements in safety during surgeries because, unlike their human counterparts, robots do not tire and can complete an endless series of precise movements.
In the study, the team photographed a human being conducting numerous reaching motions, in a way similar to someone handing instruments to a surgeon.
These captured motions were input into the neural network of the robotic arm, before a human operator guided the arm in imitating the motions.
Finally, the team observed whether the motions the arm itself later made were "biologically inspired" and came as a result of its neural networks learning the movements.
The researchers say the goal is not to remove human expertise from the operating room, but to complement it with a robot's particular skills and benefits.
"As a roboticist, I am convinced that robotic workers and collaborators will definitely change the work market, but they won't steal job opportunities," De Momi said.
"They will just allow us to decrease workload and achieve better performances in several tasks, from medicine to industrial applications."
The science of standing out in a crowd
How attractive we appear depends on who's standing next to us - and how good-looking they are in comparison.
This won't be news to anyone who's image-conscious enough to worry about how they look in group photos posted on social media, but now psychologists have given scientific credence to it.
"Rightly or wrongly, the way people look has a profound impact on the way others perceive them," said UK psychologist Dr Nicholas Furl, lead author of the new study just published in Psychological Science.
"We live in a society obsessed with beauty and attractiveness, but how we measure and understand these concepts is still a grey area."
Furl said that, until now, it had been understood that a person's level of attractiveness was "generally steady".
"If you saw a picture of George Clooney today, you would rate him as good-looking as you would tomorrow."
But the study showed how attractive we are was far from static, proving that an averagely attractive face surrounded by undesirable faces becomes more appealing than it would on its own.
In a series of experiments, participants were asked to rate pictures of different faces for attractiveness one by one, before later assessing the same faces when placed alongside ones perceived to be undesirable.
When adding these "distractor faces", the attractiveness of the same faces increased.
Participants were then shown two attractive faces, alongside a "distractor" face and asked to judge between them, showing that the presence of the less attractive face made the viewers more critical between the attractive face, Furl said.
"The presence of a less attractive face does not just increase the attractiveness of a single person, but in a crowd could actually make us even more choosey."