In 1952 A. Turin published a paper ‘The Chemical Basis of Morphogenesis’ which was a milestone for the development of mathematical biology and for many other disciplines. He proposed an original solution to the problem of morphogenesis, by adapting a system of coupled differential equations to describe both chemical reaction and diffusion of morphogenetic substances in an initially homogeneous configuration. He was clearly determined to provide an argument for the generation of ‘order-from-disorder’: explaining how a chemical soup of molecules could possibly give rise to a biological pattern, given the transcription of genes into diffusible molecules. One of the examples he suggested was the formation of the radiolarian skeleton.

Radiolarian skeleton: the preferred case study of A.Turing

Imagine future networks as “soups” of (communication and processing) resources. Actually already today we are living in an increasingly interconnected world and it is reasonable to imaging tomorrow networks characterized by such abundance of pervasively distributed resources around us. Understanding and simplifying the complexity of these “soups of resources” are crucial issues for managing socio-technical systems and the dynamical processes running on top of them.

Interestingly, this paper elaborates about that. It is shown how emergence of collective behavior in complex systems and networks is allowing us to adopt a route analysis which essentially similar to the statistical physics. Example are the reaction-diffusion processes, the same studied by A. Turing. Very similar spreading models can adopted for the description of the diffusion of both real pathogens and pieces of information in complex networks. The analysis of the adaptive behavior of the individuals to these dynamical processes is still an open challenge: for instance, little work has been done to coupled reaction diffusion processes with (autonomic) behavioral adaptation of individuals, and the related emergent properties, as triggered by the perception of pathogens’ (e.g. pieces of information, knowledge) spreading.

These researches are moving towards understanding how the emergent properties in complex networks impact their controllability and vice versa how we can direct emergence: I see them as hot topics for managing future socio-technical systems and applications.

It is now a few years that researchers have found ways to print electronic components, like transistors, antennas and so on. There have been a few applications, like RFID tags, but the market has still to take off.

It is therefore interesting to note that a number of companies, each one specialized in a certain area, have decided to join effort to create a mass market application for printed electronics.

Battery printed on a thin layer of polymer

They are targeting the creation of stickers, at a cost of 30c of a $ each that can be applied to bottles, packages and pallets to continuously record the temperature. The sticker embeds a microprocessor, a storage part, a sensor, radio communication part and the battery.

Thin Film Electronics, a Norwegian company, has a good background in printing memory and they are cooperating with PARC, California, to embed transistors and with PST Sensors, University of Cape Town, and Imprint Energy, California, for the battery part.

They are expecting to have the first prototype available later this year. The challenge is to create an industry standard allowing the packaging of all components. As in any new product it is key to find a viable application that can be used as a spring board for others.

The idea of using it as a sensor to record temperature makes sense since on the one hand there are sensors costing a few pennies but offering only instantaneous measurements and a not very precise one (like stickers with a chemical that changes color) and on the other sensors with very good performances costing 20$. An offer priced at 30c may create a new market.

Ever felt green with envy for those top brass moving around in nice car and reading a newspaper since the chaffeur is taking the burden of driving around?

Well, technology is promising to deliver us a personal chaffeur embedded in the car! Take a look at this video:

And also read the articles on driverless cars and on autonomous systems.

Clearly technology has made amazing progress. Today you can feel if the plane you are on is under the control of the auto-pilot or if a human pilot is flying it. And you can tell because the flight is so much smoother when the computers are in control…

Add to this the fact that in most flying accidents pilot’s mistakes are involved. Clearly, this does not prove anything. It does not provide any figure on the instances where no accident occurred because the pilot skill saved the day, and I suspect there may be many of these instances.

If everything is going according to plan I have no doubt that computers fare much better than us human being. We tend to become distracted, to lose focus and to act unpredictably. Not so with a well designed computer.  But is something goes not according to plans then the computer, that needs to have a plan to follow, is lost. And this is where we are still superior machine. Our brain embeds so many different plans and can select one out of many other in a blink of an eye, to cover with unexpected situations. Of course this is one way to see what is happening inside our skull. A different vision is to imagine that our brain is cable to create a new plan to fit the new circumstances…

These two visions have a correspondent in the Artificial Intelligence domain: for many years scientists have tried to find out ways to “invent” new plans within a computer with results that have been interesting but remained short of meeting the goal. More recently, the abundance of resources, data, processing… and the use of statistical approaches mining big data have provided a new way to extract (create?) information and take decision. In a way, it is much more like what is going on in our brain, according to most recent study. Rather than an automatic machine our brain is an autonomous system able to finely tune its responses by mining a multitude of data. The behavior is an emerging property of the way we accumulate and interact with data.

This is why I feel that the furthering of study on autonomous systems is key to  more “intelligent” future.

According to some estimates of the San Francisco Municipalities 30% of the cars in downtown San Francisco are not going anywhere, they are just rolling looking for a parking space! That’s quite a lot, and although I do not have specific figures for Italy I have the feeling that the situation is similar in major metropolitan areas. Think about the time wasted, fuel consumed and CO2 emissions! And digest this estimate coming from Lo Angeles: factoring in just 3 minutes spent looking for a parking lot in LA on the average means 350,000 extra miles driven in LA per year!

Red streets have no more parking slots available, try the blue ones!

No wonder that so many projects on Smart Cities include one sort or another to easy the chasing of parking.

This is what is being done in San Francisco with the SFPark program.

The city has installed over 8000 sensors in parking slots, embedding them in the asphalt, that detect the presence of a car by measuring the change in the magnetic field (created by the car steel parts), sensors in garages and public parking spaces. Additionally smart park meters are also providing information on availability (assuming people are paying for the slot).

All this information is made available to apps running on smart phones so that one can be informed on where to go and likely find a parking slot. I would also elect to get this information on the car navigator.

The benefits of easing the parking search are many, beyond time and fuel consumption. According to Jay Primus, the SFPark manager:

“Circling drivers are distracted drivers. They’re much more likely to hit pedestrians, bicyclists, and other cars, and as they search for parking spots, making frequent turns and making frequent stops, they can cause unpredictable delays to the transit system.”

It is clear that leveraging on data (creating them, collecting and making them accessible) can greatly improve our quality of life and we should consider the negative aspects (like privacy) to solve them and not let us stop in using data.

Sony has announced a new sensor specifically designed for cell phone cameras that promises a significant advance in quality.

Cell phone cameras suffer from the tiny size of the sensor (a bigger sensor size would require a bigger lens and hence a bigger form factor). The limited space available to pixels lead to very small pixel and the rush towards more and more resolution shrunk the pixels even more.

The solution proposed by Sony is to move the electronics for manipulating each pixel to the back of the sensor, as shown in the figure, whilst today the electronics uses part of the sensor surface.

This is made possible by the new 3D chips and results in bigger pixels, hence in reduced noise, one of the problem affecting the cell phone photos.

It does not solve the problem of the lens quality (and the fact that given the small distance basically we lose depth in the image, but it is a good improvement in quality.

Today there are more cell phone cameras than digital cameras (Nokia has claimed to be the largest digital camera manufacturer) and this is going to remain so..for a while.

By the end of the decade I see the possibility for the embedding of cameras in dresses and at that point we might see Abercrombie becoming one of the largest camera manufacturer!

Take a look at what Samsung has presented at CES, their “smart window”:

Although it is not clear in the video from CES, the smart window is supposed to look like a normal window, to replace a real window you have in your home. When it is “switched off” it is a plain window. Actually, you can use its capability to provide electronic blinders to stop the life from entering your room.

But then you can use it as a screen. And this is what it is shown in the video.

What I can imagine, however, is a third use…a window that provides me with information on what I am seeing through the window. I have been in many hotels offering a dramatic view of a city landscape. It would have been nice to have a window that would let me play on that landscape touching a monument in the distance and seeing it becoming bigger, as if it was closer, associating information on that, about who did it, what happened at that spot, how can I get there and so on.

And of course, being able to “paste” those information on my travel book to add my personal comments.

We do not know the price for these smart windows but it is an easy bet that their price will be high… and it will come down rapidly. My bet is that in the next decade such a smart window (its grandchildren of course…) will become part of the option list offered by any constructor as you select a window, in the same way that today you are given the choice of different insulation window panes.

Now, that will be a quite different interface!

I wish resuming from the nice piece of comment of Roberto to the post Network Science.

 Actually, in most cases, there is no network! The spontaneous, autonomous interactions taking place are forming a fleeting network without it having to exist in a physical sense. It is just in our perception. This is crucial when we come to think about future telecommunications networks. The CAPEX for such networks may be 0,  since it is hidden in the nodes. It is the collection of autonomously interacting nodes that creates the network. This latter is an emergent property of the set.

 That’s true, I see it : in most cases the network is just a creation of our mind in order to understand and explain certain complex phenomena (I mean  not only when studing a cell but also when looking at a telecommunications network)

The intricate network of microtubule (yellow) and actin filament (purple) fibers that builds a cell's structure. Credit: Torsten Wittmann, UCSF.

 In 1948 Claude Shannon published his paper “ A Mathematical Theory of Communication”. He argued that “the fundamental problem of communication is that of reproducing at one point either exactly or approximately a message selected at another point.”

 In this paper about Order and Chaos of networks, they borrow from Shannon arguing that every process is a communication channel. Again this is an abstraction to model a process or a system. Any node of a network is like a web of channels communicating its past to its future through its present.

 Actually, the state of a system or a node in a given moment of time can be characterized by values of state variables (at that moment). The minimum number of independent state variables which are necessary to characterize a state is called the number of degrees of freedom and it can be represented in an n-dimensional space (phase space). In a node’s phase space, a process is a series of gradual changes (a trajectory).

So, we may conclude that:

Any node is like a channel and the nodes of a network interact with each other again through other channels.

 In this sense a “network” is an abstraction of our mind: it is a web of communication channels, but it might not exist physically, being potentially embedded, hidden, into the inter-, intra- nodes processes.

 Time to change our perception of the network ?

Science fiction has imagined a time when our brains will be “on the web” wirelessly connected and has shown the various twists that may result. I remember a book from Hofstadter, Mind’s I, dealing with this subject. But that was just science fiction, nothing to be concerned about.

However, I just read a news from Technology Review reporting on a device created by Kendall Research, a tiny, 3 grams, device that can be implanted in the brain and that generates a last beam to stimulate, selectively, cells. It receives signals wirelessly as well as the power it needs to work. This latter is provided by super capacitors that are embedded in the lower part o the cage where the animal is placed.

Biotech is providing tools to insert in a cell proteins that can be triggered by a beam of light at a given frequency (as it is the case in the eye retina where rhodopsin intercepts photons and sends a signal). This is what is being done by researchers. Specific brain cells are conditioned to respond to light and through this device they can be triggered.

There is expectation to be able to use this device to learn more, first, about the inner working of the brain, and then to be able to provide very specific signal to the brain to counterbalance trauma or disease effects on the brain. This latter may take several more years but it is a very exciting perspective. Using a beam of light can provide for very precise control of the brain, contrary to using electrical probes, since the electrical signal spreads to billions of brain cells at a time.

In this paper “The network takeover”, Albert-László Barabási elaborates how data-based mathematical models applied to complex systems are creating a new rapidly developing discipline: Network Science.

We will never understand the workings of a cell if we ignore the networks through which its proteins and metabolites interact.

Understanding a cell through the networks of its proteins and metabolites

I would add, we will never understand the workings of an ecosystem if we ignore the networks through which its components interact. And despite the many differences in the nature of the nodes and the interactions the networks behind most complex systems are governed by a set of fundamental laws. Universality is one of them.

Welcome to Network Science: the aims is to understand the characteristics of networks that hold together the components in various complex systems.

Today, the huge amounts of data collected through sensors and smart devices are creating a new way to understand the inner behavior of many complex systems, and the networks behind them. I’m not just talking about communications: consider for example the proteomic tools allowing to collect data on human proteins networking.

No understanding of a cell, of social media or of the Internet can ignore the network fundamental laws. Data-based mathematical analysis will pave the way to this understanding.

Imagine what we may exploit from understanding these networks.

Raspberry promised a 25$ computer back in 2011 and now it delivers!

As you can see it is a tiny board, the size of a credit card and you need to connect it to a screen (it has a DMI socket to connect to your HD TV) and to a keyboard.

What is amazing is the price. You get a device that can be used to process video and to do whatever your PC can do. Of course there are limitation, like its 256MB storage (there is a 512 MB version selling at 35$) and you are not going to use it for gaming. Still, it is a fu fledged PC with Linux and along with it thousands of free applications you can find on the web.

You also get access to tutorials for leveraging on its capabilities. One possible application will be in class room, to teach programming to pupils at an affordable price also in many developing countries.  Just remember that 5 years ago the 100$ LapTop computer seemed an utopia. Generation Z is probably the first truly digital native generation and there is no turning back.