Science News

Headlines

. New insight into how bubbles burst
. Mirror, mirror on the wall: fishy reflections
. Dreaming skills
. Phyics in free fall
. Smoothing digital images: then and now

Some of these are discussed in more detail below.

New insight into how bubbles burst

How many times have you seen soap bubbles form, and watched them breathlessly until they burst? What's new about that?  With the help of high speed video, scientists have discovered that there is far more to bursting bubbles than meets the eye.
Scientists studied bubbles formed on liquid surfaces and watched them at the moment they burst. Under the right conditions, a bursting bubble does not simply vanish, but creates a perfect ring of tiny "daughter bubbles".
This happens when the bubble has just ruptured (punctured) in the middle. The bubble is in the shape of a hemisphere (half a ball, since it is "sitting" on the liquid surface. So when it bursts, it forms a doughnut (vada) shape of trapped air. This in turn forms a ring of bubbles called daughter bubbles at the surface where the hemispherical bubble was in contact with the surface.
Each of these daughter bubbles in turn ruptures, forming rings of even smaller bubbles. The process continues until the daughter bubbles are sufficiently small. Finally the last set of bubbles rupture, sending jets of liquid-air mixture (called aerosols) into the atmosphere.
You may see sometimes see a ring of "daughter bubbles" while washing up.  While the fundamental process is itself interesting, this discovery could have many uses. 
For instance, bubbles often form when making glass sheets. Such defects weaken the glass and also spoil its smooth surface. The new understanding could help to reduce the formation of such drops. It could also have appications in health research.

Mirror, mirror on the wall: fishy reflections
Scientists use mirrors to try to study how animals think. Previous studies have shown that some animals recognise themselves in a mirror. This is called cognition. Examples are great apes, elephants, dolphins and magpie birds.
Not every animal knows its mirror self -- monkeys and fish, for example, don't seem to recognize themselves in the mirror.
Cichlids are freshwater fish, many of which are found in aquariums (such as angelfish). A male cichlid is very aggressive and may go after other fish who dare cross its path. A male cichlid will even attack when they see themselves in a mirror, thinking that the reflection it sees is some "other fish".
The new study did not observe a difference in the behaviours of these fish when shown after other fish compared with the behaviour when they were shown their own reflections. In both cases, they showed aggressive behaviour.  When the scientists looked at hormones in the fish, they was no difference there either. But when they looked in the fish's brain, they found a difference.
They used a technique called immediate early gene (IEG) expression. With this technique, the scientists could determine which areas of the brain were more active than others.
When a fish went after its own reflection, the scientists found that the fish brain was especially active in a particular region. This region is similar to a region called amygdala in human beings and other animals, which is associated with fear and other negative emotions.
When the male cichlids went after other fish, they didn't have the same activity in their amygdala regions -- showing that their brains reacted differently when they looked at other fish or at their own reflections.
A similar study with monkeys has also shown that they do not recognise themselves in a mirror but show different responses than if they are shown some other monkey. Such a study will throw more light on brain activity in animals.

Dreaming skills
Dreams can be familiar and strange, fantastical or boring. No one knows for certain why people dream, but some dreams might be connected to the mental processes that help us learn. In a recent study, scientists found a connection between nap-time dreams and better memory in people who were learning a new skill.
In the study, 99 college students between the ages of 18 and 30 each spent an hour on a computer, trying to get through a virtual maze. The maze was difficult, and the study participants had to start in a different place each time they tried -- making it even more difficult.  They were also told to find a particular picture of a tree and remember where it was.
After one attempt, the participants were given a five-hour break. Half the participants were told to take a one-and-a-half hour nap. The other half stayed awake. Those who slept had their brain pattern monitored so that they were asked about their dreams within a minute of sleep. After the break, all of them did the task again.
Four of the 50 people who slept said their dreams were connected to the maze. All four of these people had done poorly the first time. When these four people tried the computer maze again, they were able to find the tree faster than before their naps.
Others who had perhaps not found the task very difficult did not dream about it. They also did not show any improvement after the nap. None of the people who had kept awake showed any improvement either.
It appears that the dream itself doesn't help a person learn -- it's the other way around: the dream was caused by the brain processes associated with learning. That is, if a person finds a task difficult, he or she dreams about it.
So perhaps one way to learn something new is to practice, practice, practice -- and then sleep on it. (Warning: This research still doesn't provide an excuse for falling asleep during class.)

Phyics in free fall
The famous physicist Albert Einstein wrote about a thought experiment: an experiment which he did not actually perform, but simply thought about. Einstein imagined a person inside a falling elevator. Such a person would feel weightless, Einstein said. This is because the elevator is falling due to gravity and a person's weight is also due to the same force. So gravity's tug on the person is canceled by the downward acceleration. This insight led Einstein to develop the theory of general relativity that predicts how gravity affects the movement of people, things as well as stars and galaxies.
But just how general relativity applies to objects on very small scales, for example at the level of atoms, remains a mystery. At these small scales, atomic forces are governed by a property called quantum mechanics. How these are modified by general relativity is not known.
In a new experiment, scientists tried to find out. They made a small blob of about 10,000 ultracold rubidium atoms that fused to form an obect called a Bose-Einstein condensate (BEC). Such an object has been studied for its quantum properties. They then dropped this blob down a 146-meter-tall shaft. Freely falling objects are essentially weightless, according to Einstein. Hence they could study the properties of this object in near-zero gravity.
One of the biggest challenges for the researchers was miniaturising the jungle of complex equipment usually needed to create and maintain a condensate. Since it needs to be at low temperature, a huge laboratory is needed. For this experiment, everything was fitted into a capsule 60-by-60 centimeter by 2-meter.  
A camera caught the BEC expanding before the capsule crashed into an 8-meter-deep pit of plastic balls. The atoms' behaviour in near-weightlessness largely agreed with theoretical predictions.
Scientists think that such experiments may lead to a deeper understanding of difficult topics such as how gravity behaves at very small atomic scales.

Smoothing digital images: then and now
More than 50 years ago, Russell Kirsch took a picture of his infant son and scanned it into a computer. It was the first digital image: a grainy, black-and-white baby picture that literally changed the way we view the world. With it, the smoothness of images captured on film was shattered literally to bits.
Consider a black-and-white picture. The entire image is in shades of grey. In a digital image, all the information (all the grey shades) are not reproduced. Instead, the picture is divided into small squares, called pixels. Each pixel is given a uniform shade of grey, which is encoded in binary format (0s and 1s). The grey shade is closest to the dominant shade in that pixel. It is possible that there were many shades of grey in that pixel, but that pixel size is very small and so the approximation works.
While some information loss is there, the picture, when reconstructed, is still recognisable. The main advantage is that only a small amount of information needs to be stored (the pixel information) to recover the entire picture.
As computers became more powerful, a picture could be divided into more and smaller pixels, so that the picture clarity was greatly improved. The first image (see figure) was just 176 by 176 pixels, roughly one-thousandth of the information in pictures captured with today's digital cameras.
The work of Kirsch and colleagues laid the foundations for satellite imagery, CT scans, virtual reality and Facebook. However, the choice of square pixels remained a limitation: when viewing the image under high magnification, the pixels show up clearly.
Recently, Kirsch has written a program that turns the chunky squares of a digital image into a smoother picture. He did this by allowing the pixels to be no longer square, but variably shaped. The shape is determined by the places where maximum colour/shade differences occur. That is, edges or boundaries in the picture are carefully handled.
The picture shows the effect of this treatment. Before transforming the square-pixel image, a close-up of one ear appears as a blocky stack. The variably shaped pixel treatment turns it back into an ear.
The program may find a home in the medical community, he says, where it's standard to feed images such as X-rays into a computer.

--Compiled from many sources