You would be surprised to know how much difference a simple idea can make when it comes to the efficiency of an algorithm.

By Gvendolin Fonyó

From computer networks to biological data analysis the graphs named after the Dutch mathematician N. G. de Bruijn are used in a wide variety of scientific fields. But as widespread as they are, up until now there was no space and time-efficient way of building such De Bruijn graphs. Just last year a group of scientists set out to come up with a method to accomplish the task with an efficiency never before seen. Their answer to the question is simple: buffering. Also known as batch-adding data, when updating a graph.

Suppose that you are working on a project that briefly touches on genomes. Writing a small paragraph shouldn’t take too long, right? But then you discover that simply zooming into a graph, to find the information you are looking for isn’t possible. Instead, you have to scroll through tens or potentially hundreds of graphs, because anytime new data became available a new graph had to be created.

The issue

One of the main problems that bioinformatics experts are facing in recent years is the rapidly growing amount of data that is being collected. Assembling such volumes of nucleotide sequences has been posing significant algorithmic challenges.  You can magine nucleotides as pieces of Lego in a game of building DNA and RNA.  At the same time, the demand for dynamic solutions is also rising. Adding, changing, and deleting aspects of a visual representation of their findings is highly sought after. The biggest challenge on the other hand is combining this mutability feature with space and time efficiency since mutability and compressibility are contradictory by nature.

The science behind it

The way this works is by representing bits of information with circles or rectangles, also known as vertices (singular: vertex), and connections between them with lines (or arrows in the case of a directed graph), also known as edges. Similar to how your house is connected to that building down the road by the street that you live on (two vertices connected to each other by an edge), but to reach the nearest grocery store a few, or a lot, more turns are needed (going from 1 to 6 on the graph below).

A De Bruijn graph works similarly, representing overlaps between sequences in a genome. In biology, a genome is all the genetic information of an organism. While this type of graph gets its name from Nicolaas Govert de Bruijn it was actually discovered by both the British mathematician Irving John Good and De Bruijn independently.

Line of attack

The researchers’ approach for implementing mutability is by creating a space-efficient De Bruijn graph with two supporting structures. As requests for adding or deleting information come in, only the corresponding support element is updated. This is where you can see the magic of buffering the data happen. Buffering data means that the information waiting to be added to the graph is first collected in a virtual pool and only once that is filled up can the static or main data structure be updated. Hereby eliminating lots of unnecessary computations and saving computer power. Testing happens by criteria like memory and time needed to complete the requests.

Testing and conclusion

After rigorous testing, the group found that their method, named BufBOSS, is up to five times faster than its closest competitor, Bifrost. When it comes to the time required for adding new sequences, BufBOSS is a strong second in the competition, outcompeted by Bifrost, by only a factor of two, but beating all other contestants by a factor of ten or more.

Their conclusion was that BufBOSS offers attractive trade-offs when it comes to memory, time, and data, compared to its competitors. They, on the other hand, emphasized that some of the other available methods could be greatly improved by further developing them. This means that you do not necessarily have to develop a whole new method if keeping the existing one(s) up to date is a realistic option.

Alanko , J , Alipanahi , B , Settle , J , Boucher , C & Gagie , T 2021 , ‘ Buffering updates enables efficient dynamic de Bruijn graphs ‘ , Computational and Structural Biotechnology Journal , vol. 19 , pp. 4067-4078 . https://doi.org/10.1016/j.csbj.2021.06.047

By Eva Kastrinos

Throughout years of hearing about climate change and feeling worried, scared and sometimes just plain useless one group of scientists went out looking for solutions. They have created l2O3- Ta2O5-Al2O (aluminum oxide-tantalum pentoxide- aluminum oxide) a fittingly long and complex name, so for our ease, Solarpaint.

Where did this all come from?

They honed in on a type of green energy, solar energy produced by solar panels.

Although this is a great form of energy, solar panels have an efficiency of 15-20%. This means only 15-20% of the sunlight panels absorb is turned into power. So, these scientists focused on finding a cheap and simple way to improve solar panels, a way that governments could not ignore. With this they created Solarpaint, which increases solar panel efficiency by 14%, almost doubling their current efficiency.

So, what is it?

Solarpaint is a coating, a paint, that will be applied on top of solar panels to stop the reflection of light off of them. This may sound strange but a lot of solar panels efficiency is lost because of their reflective surface. Instead of absorbing all the sunlight that reaches them, they reflect over 35% of it back, like a mirror. So the scientists set out on solving this issue, so more of the light that reaches them could be used for power.

But how did they create it?

To find Solarpaint the researchers went through a bunch of compounds and settled on two, Ta2O3 and Al2O, which have great properties.

Ta2O3 has a high dielectric strength. Now this may seem too jargon-y but it’s simple to understand with a little story. Last week I noticed one of the hinges on a window at home had popped off. Although houses in Finland have good insulation, the loose hinge was letting a breeze through the house. So, the insulation wasn’t really useful because the house was still cold. We could say my house has a low protective-strength. If my house had a high protective-strength, it would have sustained the wind and the insulation would have remained useful and intact. So, in terms of dielectric strength, saying Ta2O3 has a high dielectric strength means it will remain a great insulator and stop electricity (wind) from flowing even when put in places with high electric fields (very windy places). This means that it doesn’t heat up very much, because it isn’t conducting electricity (like when you touch a lightbulb that’s off it’s cold, because it’s not conducting electricity).

Now you may be asking yourself why this matters. All solar panels degrade over time and one of the main causes of this is the temperatures they reach; they’re like people, if you’re under the sun a long time you’ll burn. So, using Ta2O3 ensures that the solar panel doesn’t heat up even more, so it does not speed up degradation. It acts like a suncream, protecting the solar panel from heating up.

Finally, the two compounds were chosen because they have no smell, colour, are not toxic, and as explained, they resist high temperatures. After coating a solar cell (a small part of a solar panel) with Solarpaint, they took its temperature and then did the same with an uncoated cell. The results showed that the coated cell had a lower temperature- their ideas had worked! The solar panels worked more efficiently and produced more power because of their Solarpaint.

This discovery could change the world of solar energy, and help progress the use of green energy immensely. By increasing solar panel efficiency cheaply and easily, they present governments with yet another great reason to invest in solar energy.

Rajvikram, M., & Leoponraj, S. (2018). A method to attain power optimality and efficiency in solar panel. Beni-Suef University Journal of Basic and Applied Sciences, 7(4), 705–708. https://doi.org/10.1016/j.bjbas.2018.08.004

 

 

 

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