Highlighting science news you may have missed, and tellin you why it matters in about a minute.
What it is: Researchers found out that mice, once infected with a particular parasite, permanently lose their fear of cats irrespective of whether the infection persists over time.
The parasite, called Toxoplasma gondii, is known to infect most types of mammals and birds, including up to one-third of people around the world. It’s peculiar effect on cats was already known: while normal mice flee cat urine odour, those infected with the parasite are mildly attracted to it.
But what surprised researchers was that this behavioural change persists even after the infection has cleared. This observation suggests that the microbe may have caused a permanent structural change in the brain of the host; an idea that may have big implications for infectious diseases medicine.
Why it matters: Several studies have linked the Toxoplasma gondii parasite to schizophrenia in humans. Most medications targeting schizophrenia work by inhibiting the microbe’s replication. However, if the behavioural changes are hardwired in the brain during time of infection then this strategy may be inadequate. A better way may be to test the patients blood for not just pathogens but also antibodies, which would determine all the infections he or she has ever been exposed to, rather than just the ones that currently exist.
What it is: Scientists have found what it is that lets static charges clump on some surfaces instead of just fading away.
Static electricity is easy to encounter. If you rubbed a rubber balloon against your hair and pulled it away, you’d strands of hair clinging to the balloon’s surface. This is because electric charges at the tip of your hair are attracted to charges on the surface of the balloon. These charges constitute static electricity – due to charges that clump in one place.
But why clump? No one knew exactly for a long time until only last week. Scientists from Northwestern University, Illinois, USA, used a microscope to look at electric fields on the surface of polymers. They found that the charges were clumping because they were able to gather around radicals – molecules with extra electrons – close to the surface.
Such clumps are a bane. For example, static electricity jumping between transistors inside a computer motherboard could damage the motherboard. More explosively, charges around plastic fuel filters inside vehicles could accidentally ignite the fuel. Manufacturers already use expensive coatings to keep such problems from rising, but now that we know why charges clump, the solution could be a lot simpler.
Why it matters: The Northwestern University scientists found that simply coating surfaces with an antioxidant that could absorb the radicals could solve the problem. Their discovery could save billions of dollars.
What it is: Scientists have found out that animals with faster metabolism perceive time to be much slower than human beings.
A measure of how differently different species can observe movement was studied using a measure called ‘critical flicker fusion frequency’. This is the lowest frequency at which an animal can tell a light is flickering rather than remaining constant. For humans this is 60 Hertz, ie. we can observe a light flickering upto 60 times/second; beyond that the light seems to be burning continuously.
By comparing the CFF for different species, scientists observed that smaller animals like insects and squirrels usually with shorter lifespans and consequently higher metabolism rates have very high CFFs. This can be interpreted as them being able to perceive time in slow motion, compared to how we humans do.
Why it matters: Besides this being able to explain everyday phenomena like why it is so difficult to swat a fly (CFF: 250 Hertz), this study highlights that tiny brains may not have the deepest thoughts but they definitely have amazing reflexes! This also explains that our CFF puts a limit on how much visual information we are able to process; for example there may be only so much speed with which we can travel that our visual systems can handle without everything becoming a blur.
What it is: The social network firm is all set to employ a new approach to artificial intelligence that will push the frontier of machine learning.
Machine learning, or the process by which computers identify and process data, has long been a tedious process. When developers create software, they often have to feed in markers into their data, so that the computers reading the data can recognize when and what to process.
As can be expected, this is a slow and not a very effective process.
Deep learning on the other hand, which is the new technology that Facebook has started research on, uses simulated networks of brain cells to process data.’
In other words, if deep learning proves to be successful, it could radically change the way machine learning is carried out—Facebook’s team believes that it will allow computers to recognize emotions and events described in text even if they aren’t explicitly references through markers.
Why it matters: Facebook joins the list of a large number of companies investing in deep learning. With advancements in machine learning, technologies such as spam detection and facial recognition are certain to get a boost in the years to come.
Compiled by Nandita Jayaraj, Vasudevan Mukunth & Anuj Srivas