Today I bring you new plushies… biological ones resembling virus, microbes and cells.
Giant microbes is an online shop for those who love biology.
Some of them are quite unpractical, but for sure all of them are the perfect gift to learn about biology.
Also, if somebody has just recovered from that particular illness, they are perfect.
They can be a good way of making a boring class into something funny and help people learn.
Original title: The rest of the robots.
Title of this edition: The rest of the robots.
Author: Isaac Asimov.
Gender: Science fiction.
Saga: Asimov Robots.
Editorial: panther
Edition year: 1, 1969.
Prizes: …
Synopsis [Warning: Spoiler]: As the own Asimov states, the book is made with stories that didn’t fit anywhere. They are robot stories, sometimes involving Susan Calvin, all happening before the Foundation, but not following the same plot.
Robot AL-76 Goes Astray: A robot designed to work on the moon gets lost on earth and as a result of its program, builds a machine to harvest resources. His design is much more efficient and the humans around him are scared because robots are prohibited on earth. In the end his machine is destroyed and there is no way of reproducing it.
Victory Unintentional: There is an alien civilization living on Jupiter. Due to the high pressures on the planet, they never get out of the surface and no human has ever been there. An expedition of robots is sent for the first contact. Jupiter’s population, initially hostile, comes to peaceful terms with earth because they mistook the robots, and their capabilities, with average human beings.
First Law: Very short story of a robot escaping and letting one man to die. It seems the robot had a child and was protecting it.
Let’s Get Together: Americans versus Russians. The Russians let know the Americans they have a group of humanoid robots that will meet inside united states and when that happens… explode.
Satisfaction Guaranteed: The new robot version has to be tested with humans… the chosen one is the wife of one of the engineers… At the beginning she was not sure about it, but after a while she falls in love with the robot. In fact, she is so much in love with him that the robot has to abandon her in order to protect her.
Risk: A spaceship that uses teleportation has to be tested…. with a robot. Unfortunately it doesn’t work, and a human has to be sent in order to study why. The reason… the commands given to the robot induce him to overturn the controls and destroy them.
Lenny: Dr Susan Calvin finds a robot with some oddities in the neural networks that allows him to learn as a human. She trains him to speak. He is also able to develop feelings.
Galley Slave: A robot is developed to perform article reviews. While it represents an advantage for the community, one evil professor tries to accuse him of deliberately changing his manuscript. However, it’s own lack of knowledge about robots betrays him and he is finally accused in court.
Personal Review: This is a very nice collection of stories with the pure Asimov essence. Because they are very brief, sometimes is difficult to judge if they are good or bad (in general good). The one I liked the most is “Victory Unintentional”, because it goes beyond the usual stories of robots including aliens. More interesting, it gowns around the question about humans/robots. Asimov imagined Jupiter as the scenario for his novel, but imagine something much more further away. In the other side of the galaxy for instance. Imagine that we send a spacecraft in a 1000 years voyage with robots in it. They will be our expeditioners, our ambassadors… and most likely, by the time they arrive, they will be like ourselves. Interesting.
The second story that i liked most is Satisfaction Warranted, because it describes perfectly how our society will be like with robots. Personal assistants, friends, people who care about us and help us having a better life. They are not a menace or a big technical leap but new friends and companions.
The other stories are good to build a background around the robots universe, but for me they are not as good as the ones I like. For instance, Risk is a good story, but they use a human to inspect the spaceship because a robot is too valuable to loose it. Why not a radio controlled robot? Some kind of drone, not as complex as a real robot but good enough to go into the spaceship? The problem here is that this is a story about all or nothing.
Original title: c
Title of this edition: The selfish gene.
Author: Richard Dawkins.
Gender: Divulgation.
Saga: —
Editorial: Oxford University Press.
Edition year: 1, 1989.
Prizes: …
Synopsis [Warning: Spoiler]: The gen is the basic entity in terms of evolution. When you think of evolution you need to think of the gen as a self-replicating structure that competes with other gens for the materials to replicate. The best ones will replicate, the worst… well, there is no second price. In this challenge the gens choose to cooperate, to be selfish and to build elaborate survival machines known as cells, tissues and bodies.
Personal Review: My field is physics, but I have some background in complex systems, and viewing this book from that perspective, this is a must read.
What is important here is that this book will go a little bit further than the “survival of the best fittest”. Allowing people with a good scientific level to reason into further details and general public to have access to a more updated view inside the field.
I think what the book does very well is turning the table and putting the gene and not the individual as the key element in the evolution game. This allows to go further into the implications of evolution and the book discusses a few examples quite interesting.
For those not willing to read it, this video tells more or less the key elements of the book.
Something that the book also introduces is the meme idea. Meme’s have been around since humans begun to create abstractions from the reality, but it is not until very recently that the idea of meme has hit the big public. As in the gene pool, there is a meme pool where meme’s compete for time in human brains, the more interesting (or funny), the more attraction and the best chances to survive longer time and pass from one mind to another (self-replicate). Chances to mutate or evolve may be different from meme to meme. For instance a Mozart’s composition is a meme that will not evolve quite fast, but still remain in many brains, while the internet memes change and mix together quite fast.
A quite interesting observation is that some memes cooperate together (as genes do). For instance, religion is a meme and celibacy is another meme. There is no reason for them to cooperate, but the fact is that if they do, there is more chances for them to survive. The idea here is that if monks practice celibacy, they will expend more time into the religion, making it possible for the religion to self-replicate.
Bear in mind that this is an essay and that some terms are quite vague, so it is easy to generalize them from one context to another. That doesn’t mean applying the ideas to a field will help making advances in the field. For instance, car shapes can be think as a meme that self-replicates and evolves. Since every new generation goes back to the designing table and starts from ideas that worked in the previous version… there is parallelism with evolution. But this doesn’t mean you will know how to design the new car. You know what you should not put on the car and that some features can be kept, but you will have no idea about how to proceed.
In resume, I encourage you to read it, because I learn quite a lot from it and I’m now willing to read its continuation, the extended phenotype.
It has been while since I saw 3D effect in GIFs, like the ones below made from stereoscopic images.
I think it is a nice trick and I have been wishing to reproduce it for a while.
It seems now it is as easy as downloading an APP called Google Camera
With this application you will take a picture and then pan the camera a little bit. This creates a special kind of picture that allow you to create the 3D effect.
To complete the effect and generate a GIF, you only need to load the picture into an online software called Depthy.
Nice and easy. Do you remember my Post about 3D with Catch? Here it is the same army but with this effect.
Paperscape is a tool to visualize papers in Arxiv (Arxiv is a free open archive for scientific papers and preprints), but not the information inside the papers, the relation between papers. Each paper is represented by a circle, and the size of the circle represent how many citations it has. To group together the papers they use an algorithm based on the common citations between papers.
So basically, is a tool to see what is going on in physics and what are the important things in your area.
Ok, let’s give it a try.
I’m going to look for Neural Network,s my old topic (hope to go back soon).
Nice, they lay close to quantitative biology.
And now my new topic, magnetic domain walls.
Not bad! Pretty close actually! And computer science is in between!
Hope you like it.
Pixel Painter is a documentary about how the most silly thing, Microsoft paint, can become the way of an old man of beating his age and makes amazing art. Hal Lasko is about 97-year-old, he was a former graphic artist who started creating in Microsoft Paint when he lost his eyesight. Just watch it.
Today I bring you a quite nice web application to explore science and relation between different sciences.
This web has an amazing and interesting tools inside.
The first of it are the sciences maps (go to the web to see more). This maps show you how different articles from different sciences cite each others.
I think some of my complex networks colleages will find interesting to have the data to perform some analisis. For example, if this network has power law in his degree distribution, it means that it is resistant to deleting some nodes randomly. In real life, that means that science will continue even if for a certain time there is no new improvements in some areas (deleting some of the nodes).
I wish to have a look to the info and plot the degree distribution, but unfortunately, to get the raw data one has to pay to Thomson Reuters.
Other tool inside this web is the citation paterns.
This allows you to see where the citations came from to an specific topic and (with colors) which was the journal that publish it.
Those are just two examples of the things inside the web. There is a lot of more kind of plots and info. Take a break and check them out. Without any kind of doubt, playing around a little bit with this web is interesting to understand the relations of your interests with other areas. And if you are looking for some especific information, this will be a good way of knowing where to find that information.
And as a final…
EigenFACTOR is close related to this other web:
This webpage is basically a big JAVA application to plot your networks and make them look as cool as eigenFACTOR ones.
As an example, I’m going to show you how to plot the network of Protein-protein interaction in budding yeast. I know, I know, there more much more interesting, but this one is free, so don’t blame at me. (Thanks to Max Stirner for helping me a little bit with this part).
Step 1. Get the data of the network. It must be in Pajek format. So you can just type “pajek network download” in google and you will get lots of examples. In my case, I found this one:
http://vlado.fmf.uni-lj.si/pub/networks/data/bio/Yeast/Yeast.htm
You can choose another one if you wish. Here you can find links to the most popular data sets for networks. Most of them in Pajek format or with instructions to turn them into pajek.
Step 2. Once downloaded the data, go back to Mapequation, to section “Mapgenerator“.
Step 3. In the lower part of the page you have a short tutorial of how to use it. For now, just click on Load network>Open File. This one I’m using is undirected. Look for the files you downloaded. In my case YeastS.net.
Step 4. Wait until it is loaded, and then click on calculate clusters. As you can see, the result is a little bit… Well, not impresive… but go to next step!
Step 5. To change the number of nodes displayed, go to Placement tools and play with the parameters. (In my case, my poor netbook can only show 35 nodes, above that it starts to suffer). And voilá:
Using this kind of tools researchers can look for missing relations (for example a part of the network has a low degree distribution, below the average, suggesting undiscovered relations that must be discovered and added to the graph to make it complete).
Hope you enjoy this resources and if you wish to look for more knowledge, don’t forget to visit the Barabási Lab.
I can’t remember the last week I stayed sober for more than a week… I can’t remeber the last time I though I was not dead. Because that’s how i feel. I feel that I die long time ago and this living is not living, is a dream that never ends, like a third person game where I control myself. Playing in exploration mode without any quest. No evil lord, no princess to rescue, just an open world to explore.
Why I drink? Because there is one point after getting drunk where I feel like there is no dreaming and can get real control again. But it’s just an ilusion, and continue my jumping from a computer to another one. From one piece of data to a new collection of bits. Just one more line of code, that’s what I am.
After a while, you realize that all the people are the same, just efficient control systems. From blood acideness to protein levels, from hunger to driving a car, from relationships to manage a bank balance, we are just eficient control systems.
And… and when you think that you are not more than a control machine, you start to be free. Because you can now ask yourself things like, why you see that girls in the street whyle coming home hitting a bus stop and decide to do what you did instead of anything more? What makes you behave in that maner and no take another action? If there is allways a reason for your actions what is that reason when you don’t know it? Can I decide to break my own rules? What happens If I decide to go against myself?
Actually, control theory has classes for controlers, and you can find yourself ass a kind of controller with feedback (you get your response, you know what your response want to be, and you try to improve it until you get the response you want to have). So… you take actions in response to things (like going to the kitchen in response to hunger, or going work in response to the necesity of buying things… probably because of hunger again). And even when ypu think there is no reason for it, there it is. The most hidden of all… you do things because you think they are good. Your objetive is getting food, getting funny things to not get bored, sleep, and sex. And in a more complex level, your control will take you to control difficult social situations where you are involved and where you expect to find new friends or improve relationships with old ones.
So… caming back to me. That’s the reason I drink. because I’m a controller that has no objetive. My error function is lost and have no good response to meet. How i loose it, and why I’m not going to have it anymore, is more complicated. But that’s the reason.
Or maybe I just need to be completelly broken before caming back again…
…
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Almost forgot. Today I officially achive one of my dreams. I wanted to be in physics books before finishing my degree… because any especial contribution. Well, now I’m not yet a Ph.D. but part of my work is yet used to teach another students. So maybe the reason I get drunk is because the only way of finding new places is getting lost and reach places no one knows.
the Brick In the Sky 