Aromatherapy involved inhaling pleasant smells and is a non-medicinal form of treatment for various psychological disorders. A nice smell triggers hormones of happiness (serotonin, dopamine, oxytocin, and endorphin) and helps overcome depression by stimulating the brain. A smell disorder is a malfunction that might even indicate neurological and psychological illnesses. One of the most crucial parts of the brain that is impacted by Parkinson’s or Alzheimer’s is the region that specializes in sense of smell. We mostly fail to notice what a blessing it is to be able to smell until we lose it. Otherwise, we are exposed to thousands of different smells every day.

Even minor issues with the nose can cause major inconveniences. Nasal congestion lessens the quality of everyday life: it is hard to sleep with a congested nose; even if you manage to fall sleep, the quality of sleep drops significantly.

The magnificent functions of the nose are as follows:

1. Sense of smell enables us to identify beneficial and harmful things and keep away from harmful ones. The nose helps spread the feeling of peace and happiness produced by nice smells that influence the spirit through the brain (olfaction).
2. The nose helps protect the respiratory passage from diseases by moistening and heating the inhaled air as it is carried to the lungs and cleaning foreign objects from the lungs with the mucus it secretes (inspiration and regulation).
3. It regulates the resonance of sound vibrations formed in the vocal cords, thereby virtually acting as loudspeakers (phonation).

These functions are miraculous, and yet we never contemplate them or their perfect engineering.

The nose: our body’s air-conditioning device

Before inhaled air reaches our lungs, it passes a turbulent current through the nose, which is by all means a perfect air-conditioning device and air filter.

Air that enters the nasal cavities through the nostrils flows through inner nasal canals to the nasopharynx (upper-frontal pharynx). It then flows down the pharynx to the larynx and finally to the lungs. Inside the nostrils are hairs that trap and filter dust, sand, pollen, and little bugs. Cleaned of these particles, air then passes through canals (meatus), which are anatomical engineering wonders in each nostril, and over turbinal structures (conchae) (Figure 1).

The exterior of these scroll-shaped canals in the nasal cavity are lined with a moist layer that secretes the fluid called mucus. Thanks to the magnificent architecture of the air conditioning chimney made up of these canals and folds, particles of dust are retained by this mucosa membrane. On this membrane there are also thin hairs (cilia) which constantly wave to and fro. This movement carries particles of dust not toward the lungs but toward the nostrils, which are then expelled when the person sneezes or blows the nose. If it were not for this precisely built structure, the inhaled air would directly go to the lungs without undergoing cleaning.

The inner working of the nose also heat or cool air, as necessary. The mucosa that lines the inside of the nose is rich in capillaries and mucus secretion. As inhaled air travels through the nose, it both warms up by absorbing heat from the blood in the mucosa veins and gains moisture by absorbing it from the mucosa. For example, when a person inhales through air from a room where the temperature is 20-22°C (68-71°F), the air heats up to 32-35°C (89-95°F) and becomes 95-98% moist by the time it reaches the larynx. If the same person breathes in through the mouth in the same room, the inhaled air can warm only up to 28–30°C (82-86°F) and reach a moisture point of 80-85%.

Without the nose, air would not be heated, moistened, and purified. The dusty, dirty, or cold air we inhale would directly go to the lungs, which would cause frequent illnesses in them and the upper respiratory tract.

How do we smell?

The nose is created with the ability to distinguish about ten thousand different smells. Its magnificent architecture is a perfect means of transport that facilitates the sense of smell in our brain, which is the real center of smell in our body. As this sense of smell function in our body, we take pleasure out of it in our soul.

The “smell molecules” communicated through the air first reach the receptors in the “olfactory epithelium” in the upper region of the nose that is equipped with a multitude of nerve cells. The stimulus that is converted into an electrical signal in this epithelium is conveyed to the smell center in the brain through olfactory nerves (Figure 2). All this process the smell molecules go through in the nose and the brain interact and impact with our soul in such a subtle way that we take delight and even be healed.

The sense of smell in certain animals (especially in dogs, moths, and some fish species) is hundreds of times more sensitive than in humans. For these animals, it is crucial for finding food and their survival.

The inability to perceive smells, or “smell blindness” (also called “anomia” in medicine), can be temporary or permanent depending on the underlying factor. Anomia is usually temporary in cases of the flu, cold, bad sinus congestion, or allergies. A decrease in olfactory sensitivity (hyposmia) can also be caused by nasal congestion, enlarged adenoids, nasal polyps, nasal deviations, or concha bullosa, which prevent air currents from reaching the olfactory region. The sense of smell usually recovers when these anatomical abnormalities are corrected; only in cases when duration of sinusitis is prolonged, namely when it becomes chronic, does loss of smell become permanent.

The impact of the nose on our voice quality

We can feel the effect of our nose on our voice quality, such as when the voice changes due to congestion or closing the nostrils with our fingers. Experienced physicians can immediately diagnose nasal congestion from the way a patient talks. Life is indeed an ordeal for people who cannot breathe easily through their noses.

Air cleared of germs

Nasal mucus is a slightly acidic secretion that carries an antibody called “immune globulin A” (IgA). Its slight acidity as well as the antibody in it allows the mucus to eliminate various germs, and the respiratory tracts are thus protected against perilous sources of illness.

The tiny sweeping hairs that line the interior of the nose can break down or stop working altogether because of certain germs, particularly viruses that cause the flu, filthy and dry air, sulfur dioxide, carbon monoxide, and cigarette smoke. Because nasal cleaning is disrupted, disease-inducing microorganisms can easily cause upper respiratory tract inflammation and other serious infections.

 The nose’s role in taste

Smell is crucial for a better perception of taste. Indeed, when there is a problem with the function of smell, a person’s sense of taste suffers, too. Nice smells have a favorable impact on the sense of smell. If we could not detect the bad smell of a rotten, harmful food item, we would not be able to stop ourselves from eating it and harming our body.

The importance of smell is highlighted in religious traditions. It is reported that the Prophet Muhammad, peace be upon him, mentioned putting on pleasant perfumes among other things that were the traditions of the messengers of God. Clippings from mush, camphor, amber or aloeswood were also burnt in the Prophet’s home for their pleasant scents.

Humans rarely consider their sense of smell. In fact, we tend to take it for granted. But through the nose’s perfect design, we are to smell and taste so much of the world around us, which is surely an everyday miracle.

Figure 1: The magnificent design of the anatomy of the nose

Figure 2: The awe-inspiring structure of the olfactory region

Have you ever seen a rainbow? Until recently, I had looked at many rainbows, but had never truly seen a rainbow.

In his writings on faith and logic, religious scholar Bediuzzaman Said Nursi maintained that looking and seeing are two different things. In his book, The Words, he says: “The eye is a window through which the spirit looks at this world. If you use it on behalf of your carnal soul, without selling it to God Almighty, by gazing at transient, impermanent beauties and spectacles, it panders to lust and other carnal desires.”

Using Nursi’s reasoning, you might look at a magician who is right in front of you, for example, but never see how a trick is accomplished. The same thing happens when you look at a mathematical equation but don’t see what the x value is – unless you are good at mathematics.

After watching MIT physics professor Walter Lewin’s lecture “The Hidden Beauty of Rainbows,”[1] I am finally able to see the rainbow, instead of just looking at it. To share my fascination about this topic, and reinforce my own knowledge, here are some notes I took during Lewin’s lecture. Walter Lewin is the author of For the Love of Physics. This book is really a perfect book if you love Physics.

Figure 1.0

There are four fundamental facets we need to cover to understand a rainbow (Figure 1.0). The first is the “radius” of a rainbow. Since every rainbow has a radius, this means a rainbow is a circle. And every circle has a center point. A rainbow’s center point is below the horizon. Here, we can ask these follow-up questions:

1.1 How we can find the radius of a rainbow in degrees?

1.2 Do all rainbows have the same radius?

The second question is about the colors of a rainbow, specifically red. If you see a rainbow, there is always a red color. But:

2.1 Is the color red always on the inside or outside of the rainbow?

2.2 Does the position of the red color depend on the time of the day and year?

It’s obvious that light determines a rainbow. If there is a rainbow somewhere, there is an enormous difference in the brightness of the sky above and below a rainbow. We can now ask:

3.1 Where is it bright?

3.2 Where is it dark?

There are some additional questions we need to discuss regarding the second bow in Figure 2, specifically:

4 Have you ever noticed the second bow? If yes, then;

5 Where do you look for the second bow?

6.1 What is the color sequence of the second bow?

6.2 Is it the same as the primary bow, is it brighter, or is it reversed?

Figure 2.0

In order to understand rainbows better, we need to review some basic physics. Let’s start with reflection and refraction.

Mediums, reflection, and refraction

Definition: A medium[2] is the substance that carries a wave from one location to another.

When light goes from one medium to another, like from air to water, one of two things happens:

● Some of that light bounces back, which we call reflection. The light will reflect at the same angle at which it hit the surface.

● Part of the light doesn’t reflect, instead continuing into water at an angle. We call this refraction.

Each medium has an index of refraction, which tells us what the speed of light in that medium is. The index of refraction of air is 1.0003, and the index of refraction of a vacuum is 1.

That means the speed of light in air and in a vacuum is almost the same. That speed is 300,000 kilometers per second, and that’s why the index of refraction for air and a vacuum is 1. But in water, the index of refraction is approximately 1.33. The difference between 1 and 1.33 means that in water the speed of light is 33 percent slower than it is in air.

Snell’s law and an angle of incidence

There is also a connection between angle of reflection, angle of refraction, and the index of refraction. We call it Snell’s law.

Snell’s law illustrated:

Figure 3.0

To understand this formula, you need to know the definition of the sine of an angle.

Definition:The sine[3] is a trigonometric function of an angle. It is found by taking the length of the side opposite the angle and dividing by the length of the longest side of the triangle.

If α is 0°, then sin (α) = 0.

If α is 30°, then sin (α) = 0.5.

If α is 90°, then the sin (α) = 1.

Let’s do an example where we can apply Snell’s law (Figure 4.0).

Light comes from air to water at an angle of 60°. (This is possible, because the angle at which water comes in, the angle β, will be 40.6°.)

Definition: The angle of incidence[4] is the angle between the incoming light and the vertical on the surface.

Figure 4.0

Like professor Lewin said, “very simple, very straightforward.”

Figure 5.0 | Figure 5.0. Example of refraction and reflection. See also [5].[5]

Figure 6.0

Figure 6.0 displays a true wonder of water. Sunlight is coming from the left side, landing everywhere on half the surface of that raindrop. We can choose one very narrow beam of all that sunlight with a 60° angle of incidence. We call the angle of incidence “i” and the angle for the refraction “r.”

Of course, that narrow beam is the only a small fraction of the total.

At point A, two things happen (in accordance with Snell’s law);

● A little bit of light reflects.

● The remaining light refracts.

The light reaches point B inside the water drop. At point B, two things happen:

● Some of the light goes back into the air (signaling refraction).

● Some of the light gets reflected. (Therefore, at point B, the angles are the same, “r.”)

Then the reflected light goes on its way to point C. Here, a little bit of the light is reflected and goes back into the water. Most of it comes out of the water, which results in refraction.

At this point, if we use Snell’s law at point A, the reflection law at point B, and then Snell’s law at point C again, we will see that our angle for the refraction at point C will be, surprisingly, “i.”

Now, if we check the line that comes out from the water at point C, we will have a changing angle. We can call it φ (Phi). And for the angle φ, we have an algebraic formula, as follows:

φ= 4r — 2i

If you check the figure, you will see that we have 4 r and 2 i.

By the way, if we take the narrow beam which passes through the center of the raindrop, we can easily see that the angle of incidence is zero. In accordance to Snell’s law, this narrow beam goes straight through. Then it reflects back and finally it comes out of the water. This is true because:

if i = 0, then r = 0 and therefore φ = 0.

Let’s do something interesting and change the value of “i.” If the light hits the water drop higher up, the angle “i” increases. At some point, the angle φ also increases and reaches a maximum value.

Figure 7.0

If you recall, the index of refraction for water is 1.336. If we take any value of “i” on the table and apply Snell’s law, we can easily calculate values of r. And then, if we use the formula φ=4r — 2i, we can come up with the values of φ. This is illustrated in Figure 7.0.

If this doesn’t seem all that special, there is something else that you wouldn’t expect: φ reaches a maximum value, and when you go to higher values of i, then φ goes down again. This plays a key role in the formation of a rainbow.

The index of refraction depends on the color of the light.

Figure 8.0

As seen in the table, when the angle of incidence for red light is very close to 60°, the value of φ is at its maximum, which is 42.3°. In other words, the value of φ can be smaller than 42.3°, but it cannot be larger. For blue light, the angle of incidence is slightly lower, and the φ maximum is at 40.7°.

Water drop and a cone

A key question arises: Let us say we have one water drop, and the sunlight falling onto that water drop is coming from the left. What is that one water drop going to do with the white light from the sun that covers half of the rainbow?

Let us check first for red light and then for blue light.

Light beams will come out of this drop, and that cone will be filled with red light. But the angle for the light beams cannot be larger than 42°, meaning they can be smaller. Then we will see a cone of lights.

But why is it a cone? Because, if we go back to what was previously discussed, we will remember that one light beam comes in with an angle i, and then comes out with an angle i.

Figure 9.0

Figure 9.0 shows a representation of a water drop. The light that comes in at the angle of incidence is 60°. It refracts and reflects inside the droplet, then goes to point C and comes out of droplet at an angle of 42°. And, surprisingly, if the angle of incidence is 60°, when the light beam comes out, it has to be red light. On the other hand, there is not only one light beam coming in with an angle 60°. The entire surface of this water drop is illuminated by the sun, so there are an enormous number of beams for which the angle of incidence is 60°.

If we go back to Figure 9.0, we see the black line on this water drop. Any light beam that comes in anywhere on that black line will have an angle of incidence of 60°.

Figure 6.1

Now we will do the same for blue light. This time, we will have another cone which is completely filled with blue light, but when the blue light beams come out, the angle will be at a maximum of 40.7°.

Interesting fact: All the colors except for red and blue that are in the sunlight will be in between the red and blue.

Figure 6.2

A journey: refraction, reflection, and refraction

We know that when the light comes in, it goes through a journey. A light beam refracts, then reflects, and then refracts. That’s all. But, how about the light on the right side of the cone? Is there any light? When the sun shines in, does this water drop bring light there?

If the angle φ is larger than 42°, then, yes, it is possible. But we have already proven that the angle φ cannot be larger than 42°. So, it is impossible: There is no light outside the cone.

Another question… What will be the color of the light inside the blue cone? We should remember that the red light is everywhere in this cone, because as long as the angle φ is smaller than 42°, red light can be anywhere. The blue light is also almost everywhere because the blue light is allowed to be smaller than 40°. This means all the colors that we didn’t mention are coming out inside the blue cone and there will be just white light.

Figure 6.3

To summarize, if we have a water drop, and a bright light shining onto this water drop, we will see red, blue, green, white, and other colors inside the cone or circle. In other words, all the colors of a rainbow. And of course, there will be no light outside the cone. There are some experiments on YouTube that you can watch if you want.

Figure 6.4

You may think that at the location where blue comes out, if all the other colors can come out — which they can because the angle is smaller than 40° — the light should be also white, not blue. It is a nice approach, but wrong.

It is wrong, because of the light intensity. If you check the graph for the intensity of the light, you will see that different colors have peak points where φ reaches the maximum value. If all the colors are present and equal intensity, we see white light. That’s why the inside of the cone is white. However, when the color red spikes up, it dominates its location. We don’t even notice the other colors.

Figure 6.5

Looking at the sky

Let’s say you are standing at point A and the sunlight is coming from the left. Since the light comes from infinitely far away, all these lines are parallel to each other. Let’s say you look at the sky in direction B and pick a raindrop at any point. Any point you pick will cast the cone in the direction of the sun with the angle 60°.

When you look at the sky in the direction B, will you see light? You will not, because you are outside the 42°.

Figure 10.0

What if you look in a different direction? We will look at point C (it doesn’t matter where), and take a rain drop on line C. Light beams will do the same thing. Again, they will produce a 42° red cone. However, you will see white light. Yes, you read that right, white light, because you are looking straight in the middle of the cone of white light.

Let’s say we choose another angle and look at point D. If we choose a raindrop anywhere on line D, it will make no difference. It will cast into the sky the famous 42° angle because that’s the angle that was chosen there. If we look in that direction of the sky, what will we see? Yes, only red. No other color!

Figure 10.1

And now, we know where we will see red light, blue light, or white light. And we also know which direction has no light.

A rainbow is a bow in the sky

Let’s suppose the sun is on your left and you are standing at point A (Figure 11.0). Since there is light, you will have a shadow on the ground. As long as you look 42° away from any direction, you will only see red. That is because a cone is a spherical object. And that explains why the rainbow is a bowl in the sky. As long as it is 42° away from a line in any direction, you will always see red light. And if you decrease the angle, you will see the other colors in the sky.

And so now, we can make a picture of a rainbow.

When we look at the horizon, sometimes we see a rainbow. And we will have a center point somewhere below the horizon. The radius with 42° has red light. The blue light is closer to the 40° radius. This tells us that the red bowl is always on the outside and the blue light is always on the inside. That’s what we always see.

Figure 11.0

Double Reflection in the Rainbow

We can also include two reflections in the rainbow. If we do, we get refraction, reflection, another reflection, and then another refraction. So, the light beams reflect twice. And if we do this hocus-pocus again and again, we can come to a conclusion: There is no maximum value for the various colors, but there is a minimum value. In other words, various colors cannot be lower than a certain value, but they can be higher.

And if we do some calculation for the angles, we will see something very similar. We will find out that the second bow is pointing at the sky, and the angle is 10° above the first one (which is 52°). And, surprisingly, the colors of the second bowl reverse. In other words, red is the one on the inside, and blue is on the outside this time.

Figure 11.1

Interesting fact: There is no light between the two bowls. This is because of the φ maximum and minimum. We call that dark part Alexander’s dark band.[6]Additionally, since the second bowl is formed by φ minimum, sunlight can come out at angle φ or larger and there will be sunlight above a rainbow.

Figure 11.2

Some examples…

Image 1: René Descartes’ sketch of how primary and secondary rainbows are formed (probable engraver: Frans van Schooten the younger).

Image 2: This diagram was drawn by the famous physicist Newton who was one of the first to understand the rainbow, from his book Optics.

Image 3: Double rainbow. The primary red bow is on the outside, and blue is on the inside. Alexander’s dark band can be seen in between the two bows. It shows up really dark. For the secondary bow, red is on the inside, and blue is on the outside.

Image 4: Walter Lewis’ backyard and his rainbow. When you water your garden when the sun is high in the sky, you can get a rainbow all the way around you. 42° away from the line is always red. If you turn around and look back, it is red.

Image 5 | A white rainbow. It is very unique and rare. It is also called a fog bow, because fog has small water droplets that create this effect.

Image 8 | Red rainbow. Let us imagine that there is a rainbow at sunset. What would you expect to see? We would only see red light because there is only red light. What would happen to the white light inside the bow? It would be red too.

Are cities the same as water? It’s possible to look at chemistry for new understandings of social dynamics.

The universe is a field where existence is transformed from state to state. The transformation of matter from one state to another is generally called a “phase transition” and each phase has its own characteristics. A phase transition is possible via the alteration of some parameters and variables. For instance, heat is one of the parameters required for the transition of ice (solid) into water (liquid) and later into vapor (gas); the increased heat causes ice to change states. The characteristic feature of each phase (ice, water, and vapor) is unique. For example, ice has a certain volume; however water and vapor take the shapes of their containers. In contrast to ice, water and vapor have flowing properties.

In a similar way, if the temperature of a ferromagnetic material displaying magnetic properties is elevated, at a certain temperature, it is observed to lose its magnetism; this is called the “Curie point.” In some materials, such as some solutions, the transition into different phases can be achieved by adding solvents.

Seasons can also be considered different phases. Each season has its own specific traits and features. Seasons are generated by the alteration of the angle between the axis of earth and its orbital plane.

As these examples show, the universe resembles an erase board where continuous transitions are taking place, new sentences are being written, and existing writings are dismissed to form new sentences with new meanings.

In a recently completed academic study, a new definition of a phase transition encountered in social life has been made and this phase transition is called “freezing by heating” [1]. It is well known in daily life that the less individuals are informed about their temper and the direction they are headed, the weaker the efficiency of cooperation among individuals. If people in a unit or group behave irregularly, a dead end or bottleneck could occur. Solving dead-end problems and bottleneck situations, or preventing them before they happen, is among the topics scientists study today. In Figure 1, cases showing the traffic stream of people moving in opposite directions obtained in this study are displayed.

It is stated that there is less “noise” in situations in which there is a reduced amount of irregular behavior taking place. The term “noise” is used to define concepts that can be disruptive human relations. The higher the noise, the more the degradation of human relationships, and as a result, a disruption or even an arrest (freezing) may happen regarding social events. The elevated temperature of a melting solid material provides it with the properties of a fluid, whereas in social events, an increase in temperature ends up with a jam and freeze in social life. In Figure 1a, a pedestrian traffic flow in which there is less noise present – in other words, a situation that characterizes ideal relations among people – is displayed. Here, it is observed that people with yellow marks have a stable flow towards the left and those with red marks move towards the right side. They do so via lanes of people going towards both directions. A stable flow indicates that the system is not frozen (not in an arrest), or free of a bottleneck. In such a flow, relations work in such a way that fluidity results.

Figure 1

An intermediate noise level causes an increase of irregular behaviors (in other terms, unpredictable human behavior) and shows the presence of serious problems that are experienced regarding the relationships among people. The corresponding situation for this case is shown on Figure 1b. Here, the pedestrian traffic is now jammed and the flow is almost halted. It is impossible for lanes to form since irregular behaviors are above a certain critical level. For a system to be rescued out of this state, oscillations of sufficient magnitude are necessary.

If the situation in Figure 1c occurs, forming a vertical interface (please note the vertical interface that separates people going left and right), this case is called a “frozen state” and much bigger oscillations are required to get out of this state. Figures 1a, 1b, and 1c exhibit before our eyes how elevated noise affects pedestrian traffic: an increase of the noise in the system (for instance, an increase in the number of people who do not stop at red lights and do not continue on green) changes it from a fluid phase to a frozen one, resulting in gridlock. It is possible to compare the increased noise of the pedestrian traffic to an increase in temperature; the elevation of temperature also causes an abundance of irregular movements inside matter. Just like that, the rise of heat in a society due to a particular issue (like turmoil or other problems) may generate an increase in chaotic behaviors. Let’s try to explain this with certain events happening right now.

Let’s think about motor vehicle traffic in any city. If every individual driver observes the rules of the road, this means a low temperature – less noise, and little traffic. Fluidity is present here. On the contrary, if there is not any consensus in terms of traffic rules among the citizens – in other terms, if majority of the people are failing to abide the rules – there will be “heat”; the noise will be high, and there will be a traffic jam. If drivers cannot assess the rules at a four way intersections, or if people with no knowledge of red, yellow, or green lights are driving, a city will have a major problem with traffic.

When a freezing event takes place, waiting becomes inevitable. Unfortunately, most people don’t like waiting. Thus, such “freezing” events should be avoided, so as to keep citizens happy. For example, public announcements of road closures due to scheduled road works limit the reactions against traffic problems on certain routes. However, if traffic is announced and no reason is given, people might still be very unhappy.

For a second example, let’s consider a judiciary system. Just like the example of motor vehicle traffic, the presence of irregular moves independent from rules can lock a legal system. If laws are insufficient, or existing laws are not universally implemented nationwide, or the laws are executed and interpreted differently according to individuals, it is inevitable for a bottleneck or a freeze in the legal system. Actors within the system may anticipate a “freeze” about to happen. People in a state of anticipation need to be convinced and satisfied pertaining to legal practices. Otherwise, they may not enforce the laws properly, and legal chaos may ensue.

Freezing by heating may also apply for certain economic processes. Some economic uncertainties or some actions of unknown cause can be considered as noise by elements of the economy, thus enforcing a behavioral change that is able to affect the entire economy. Therefore, any applied change is followed carefully by the actors of the market and these actors must be satisfied about the changes taking place. Higher noise levels and dissatisfaction of members who are waiting affects the liquidity of the market and can lead to the withdrawal of funds. Withdrawal of money negatively impacts the parties who are in need of cash in various ways and the economic system gains momentum towards a “frozen state.” Negative factors are not the only reason for a bottle neck. Conservation of balance and the fluidity of the economic system are considered as the essence of this issue.

The principles briefly given above can also be applied to socio-psychological events. It is impossible not to encounter a bottleneck for a society consisting of members who are aggressive, stressed, or have less knowledge of their destinations. If a decision can be made with a peaceful state of mind and there is no doubt present regarding current practices, patience becomes the most important parameter. Hence, until a state of balance is established, it is advised to wait with understanding and patience. Patience is a healing aid that plays a role in reducing the temperature in all bottleneck situations.

Fasting prayer is very important for people in terms of gaining this habit. Even for a person who observes fasting one day or two in a week, it becomes more possible to deal positively with any bottleneck situations encountered that week. Another way to lessen the impact of a bottleneck is living to be aware of the fact that each event may serve a purpose. As Nursi stated, each negative or positive event that has been experienced has a purpose. Every event will be over once its purpose is reached. For a sincere believer who is aware of this, realizing that patience also means to appreciate time; thus, it is possible for him to disperse the negative elements that this waiting will bring.

It is possible to expand the “freezing by heating” phase transition to various different mediums across many other disciplines. However, the only necessary element in all of them to prevent such freezes, or to break present freezes, is the reduction of noise (temperature). It’s possible to find guidance by acknowledging that this world is a place of wisdom and service, and rewards do not always come in this life.

References

1. Dirk Helbing, Illes J. Farkas, Tamas Vicsek, “Freezing by Heating in a Driven Mesoscopic System,” Physical Review Letters 84, 1240-1243 (2000).
2. H.Eugene Stanley, “Non-equilibrium Physics: Freezing by Heating,” Nature 404, 718-719 (2000).

Like all omnivorous foods, peppers – both hot and sweet – have been created in unique, wise ways to make them appealing to eat and to help reproduce.

Plants and their fruits are sustenance for herbivores, including humans. They are often brightly colored – be it red, orange, yellow, purple, or green, inviting us to a delicious food. But not all plants are meant to be eaten. Indeed, some plants are designed to be unappetizing, either through look or smell; some even have thorns, or sticky, hairy surfaces to deter us from eating them. Another remarkable way that plants are protected against herbivores is the presence of unique chemicals that induce vomiting and pain, or may be toxic.

Many edible plants need to be eaten – it’s how they spread their seeds. Thus, they produce juicy, tasty skin and sweet-smelling aromas. Why, then, are hot peppers different? Though they are nicely colored and juicy, and sweet smelling, they are also hot, and not terribly pleasant for animals to eat.

A recent study at New Mexico State University’s Chile Pepper Institute determined the hottest chili to be the Trinidad Moruga Scorpion Chili. It was chosen from among 125 varieties. Researchers dried and ground it to powder, to isolate its active compound. This way, they were able to determine that the Trinidad Moruga Scorpion reaches about 1.2 million units on the Scoville heat scale. It is so potent that it could induce sweating and tears, and of course puts the mouth on fire.

Figure 1. Molecular mechanism of TRPV receptor activated by capsaicin. TRPVs are located on the surface of nerve cells where they normally respond to changes in temperature by releasing calcium ions. Those ions signal to intracellular machinery to fire nerve action to inform the brain about increased levels of heat. Capsaicin in hot peppers mimics this system, and thus fools brain to think mouth is hot.

What make hot peppers hot?

Animals are equipped with receptors, like TRPV1 in the mouth’s nerve endings, which sense heat. Hot peppers produce a chemical called capsaicin. Capsaicin binds to and activates TRPV1 receptors; thus we feel a heat similar to a burning sensation. In reality, capsaicin does not actually increase the temperature in the mouth, but instead mimics the same process (Figure 1). Since capsaicin mainly dissolves in oil instead of water, drinking water does not help much to get rid of the burning sensation. Cold water provides only temporary aid. However, the drinking of ayran (a Turkish yogurt drink) relieves hotness by removing capsaicin due to the presence of oil in ayran. Interestingly, although mammals have receptors for capsaicin, scientists have recently discovered that birds don’t.

Capsaicin deters mammalian consumption

It is an interesting phenomenon that peppers are hot but need to be eaten to propagate their seeds in different environments, which is done through the droppings of animals. If this is the case, why are hot peppers made unpleasant with capsaicin? To figure out the wisdom behind this contradiction, Joshua Tewksbury performed a study with a group of mice and birds, and found that birds do not distinguish between sweet and hot peppers in their diet. In this study, both mice and birds ate the same amount when fed with food mixed with sweet peppers. However, mice refused to eat foods mixed with hot peppers, while birds happily ate such food. Moreover, analysis of the droppings of birds and mice showed that the seeds passed through the bird’s digestion systems were intact and fully fertile and could germinate, while seeds eaten by mice were either crushed or semi digested so that they were not fertile. Thus, the role of capsaicin in hot peppers is to deter mammals that destroy their seeds while not disturbing birds. This is a great example of ingenious interdependence.

Capsaicin as antifungal agent of peppers

Figure 2. Capsaicin is not only protective against mammals but also fungus contaminations. A) Insects make peppers prone to fungus contamination by causing harm. B) Healthy pepper C) A pepper with fungal contamination. Modified Image from Tewksbury lab.

The infinite wisdom of capsaicin protects peppers against fungus as well. Another study by Tewksbury showed that hot peppers are relatively protected against fungal infections. Tewksbury demonstrated that increased doses of capsaicin inhibit the growth of fungus. This finding is in parallel with lower fungus growth in hot peppers compared to sweet peppers.

But what about insects? How could peppers be protected from insects?

Adaptations against insects

Interestingly, the skins of hot and sweet peppers have different levels of thickness. It has been suggested that this gives an advantage to sweet peppers. Furthermore, this protective layer is made of lignin, which is made of the same material as capsaicin and helps to protect from other threats. This allows peppers to adapt to many different environments. For instance, in the presence of fungal contamination, a pepper might be able to produce more capsaicin and decrease lignin production, or vice versa.

Why do we like to eat hot peppers then?

Humans differ from mammals in their love of hot peppers. There are different explanations why we like to eat hot peppers, despite them being painful. Some experts assert that hot peppers are good for our health by lowering blood pressure, having antimicrobial effects, and increasing salivation thus making a boring diet fun. On the other hand, some experts approach it from the perspective of human emotions and argue that we are actually after the pain produced by hot peppers. In addition, there are some studies suggesting that capsaicin could also suppress other pains.

Hot pepper or capsaicin as pain suppressor

Capsaicin in hot peppers could be used as a pain suppressor, as some studies suggested. A study using mice lacking TRPV1 heat receptors showed that the increased long term activation of TRPV1 by capsaicin could relieve pain following the accumulation of high doses of Ca2+ in the cells. This is accomplished by the suppression of both cellular activities and the transmission of pain through nerves.

Hot peppers are hot and we love them. It seems like we will continue consuming them. As every other art of creation, hot or sweet peppers are likely to have many more levels of wisdom awaiting us to discover.

References

• Tewksbury Lab. Retrieved from: http://faculty.washington.edu/tewksjj/res_pai.html on 18.2.2012.
• Yalgın. Ç. 2012. Acı biberler niye acı? (Why Are Peppers Hot?) Açık Bilim. Retrieved from: http://www.acikbilim.com on 18.2.2012.
• Zivkovic, B. 2006. Hot peppers – Why are they hot? A Blog Around The Clock.

A planet that revolves around another star outside our solar system is called an Exoplanet or Extra solar planet. Ongoing studies involving this field are carried out via simultaneous ground and space based missions and observations. Scientists are searching a small portion of the Milky Way galaxy, approximately 3000 light years away, by using ground and space telescopes, along with various other astronomic methods (1). Despite all this technology, the observation area is too big when compared to the size of the object of interest.

It has been calculated that the Milky Way, a disc shaped galaxy, consists of 200 billion stars spread over a diameter of nearly 100,000 light years and a thickness of 1000 light years. When we consider the amount of stars in a single galaxy, and the fact that there are between a hundred billion and one trillion galaxies in the universe, the number of possible exoplanets is likely much larger than those we currently know of.

Classification of exoplanets

Exoplanets are classified according to their physical, chemical, and other characteristics, along with their diameter and mass: Jupiter like; greater than Jupiter; Earth like; greater than Earth

Classifications according to surface and atmospheric temperatures are as follows: Hotter than Jupiter; colder than Neptune; colder than Jupiter; small blue dots or twin Earths.

The presences of free-floating planets which have lost their parent stars because of different formation processes or other factors have also been discovered.

One of the common features of the exoplanets currently discovered is their short distance to the star they revolve around, which is usually less than half the distance between the Earth and the Sun. The known exoplanets are also defined by their faster revolutions in much shorter periods. Therefore, larger planets that are closer to their stars can be observed easily. When these planets are passing in front of their stars, a decrease in the brightness of the star is detected via spectrometers (Figure 1).

Figure 1. Passing of a planet in front of a star and a spectrum of this event.

Radial velocity, one of the methods used to discover exoplanets, relies on the observations of a star’s kinetic fluctuations. The proximity and size of a revolving planet leads to slight changes in location and velocity of a host star. As a result of this, the star gets closer to earth and then becomes more distant, which is observed as the Doppler shift of spectral line color waves. 75 % of all known planets have been discovered using this method (Figure 2).

Figure 2. Doppler shift – radial velocity

Earth-like planets or habitable places

In an official NASA report in December 2011, the discovery of an Earth-like planet was announced for the first time. This planet, named Kepler 22b, is 600 light years away and remains the most similar one to Earth among the known heavenly bodies. The distance of Kepler 22b to its star shows a high possibility for the presence of a habitable zone.

So what does this mean?

Earth is such a special home for us humans that everything here has been assigned to serve us with delicate calculations. Factors such as the Earth’s mass, gravity, distance to the Sun, rotational and revolution velocity, chemistry, thickness of the atmosphere, magnetic shield, hydrosphere/land ratio, ecological balances, and average temperature are all perfect for biological life.

Earth revolves in such a region and position that a majority of the planetary water is in a liquid state and is not ice or vapor.Thedistance of the habitable zone to our Sun is between 135,000,000 – 225,000,000 km. Earth revolves at a 150,000,000 km distance to the Sun. The value of a habitable zone for each planet depends on the diameter, mass, heat and radiation strength of the host star. In other words, aside from the similarity of an exoplanet to Earth, a classification of its host star with in terms of size and age is also important.

Kepler 22b owns the title as the first planet to match the criteria above with its following features:

• Has a radius 2.4 times bigger than Earth
• Revolution time is 290 days (365 for Earth)
• 15% closer to its star compared to the Earth-Sun distance
• The size and surface temperature of Kepler 22b’s host star is very similar to that of the Sun’s
• The surface temperature of the planet is 22 C
• The size of the habitable zone for Kepler 22bis 133,500,000 – 240,000,000 km (Figure 3).

Figure 3. Comparison of the solar systems of Kepler 22b and Earth.

Aside from these similarities, it is noteworthy to report the problems that scientists encountered regarding Kepler 22b:

• The unknown presence of water on the surface
• No information on the gaseous contents of the atmosphere.
• The gravitational force is 2.5 times greater than on Earth.
• Rocks constitute the surface instead of soil.

The hardest part is that Kepler 22bremains 600 light years away from us. This means it would take us 11 billions years to get there with today’s fastest spacecrafts. Who knows when we will be able to decrease this time with the advent of superior technology.

What do religious scholar say about life in outer space?

Among His manifest signs is the creation of the heavens and the earth, and that He has dispersed in both of them living creatures. And He has full power to gather them together when He wills. (Ash-Shura 42:29)

While interpreting the Qur’anic verse above, Fethullah Gülen notes the following:

“Since the earliest times, this verse has been taken as a proof for the view that there are living creatures, whether resembling human beings or not, in the places other than the earth. This view may be true. The second part of the verse, ‘He has full power to gather them together when He wills,’ has been understood that these creatures and human beings will possibly come together either in this world or in that of the other creatures. … there may be earth-like globes in the heaven where creatures resembling earthly ones live.” (Gülen 2012, 272-273)

“Perhaps people will not be able to reach those places individually or as a whole generation, but this can be achieved by mankind as a species. In other words, when the Divine Will manifests itself in that direction, humans here can encounter those other life forms.” (Gülen 2007, 232)

This commentary reflects what Bediuzzaman Said Nursi had said decades ago:

“The earth, although much smaller than other heavenly bodies, is so densely inhabited by living creatures that even its grossest and most rotten parts are full of living things, such as micro-organisms. This shows that those infinite firmaments, with their numerous stars and constellations, are inhabited by conscious, living beings …” (Nursi 2010, 530-531) 29th Word, First Aim, First Fundamental)

Nebiyev is a professor of physics in Azerbaijan.

References

• http://kepler.nasa.gov/
• http://planetquest.jpl.nasa.gov/
• http://en.wikipedia.org/wiki/Habitable_zone
• Gülen, M. Fethullah. 2007. Kendi iklimimiz, Istanbul, Nil Yayinlari.
• Gülen. M. Fethullah. 2012. Reflections on the Qur’an: Commentaries on Selected Verses, NJ: Tughra Books.
• Nursi, Bediuzzaman Said. 2010. The Words, (29th Word) NJ: The Light, Inc.
• Chris Kitchin Exoplanets: Finding, Exploring, and Understanding Alien Worlds- (www.springer.com/series/6960)-2012
• Mercy, G., P. Butler et al. 2005. “Observed Properties of Exoplanets: Masses, Orbits, and Metallicitie”.. Progress of Theoretical Physics Supplement, Vol. 158, No. 24-42.

All health issues are best understood and treated with a combination of biological, psychological, and social factors rather than with purely biological means. This context entails thoughts, emotions, behaviors, social factors, and environment, all of which play significant roles in human functioning and overall health. Therefore, it is important to gather input from all aspects of an individuals’ life to get better insight into depression.

Many people use the word “depression” to explain the feeling of sorrow, but depression is much more than just sadness. Sadness is a normal reaction to life’s struggles, setbacks, and disappointments. However, depressed people don’t feel sad—they may feel lifeless, empty, apathetic, and hopeless. Depression starts with just a feeling and then manifests in physical behaviors. The feeling of helplessness, hopelessness, and worthlessness are intense and unrelenting. An unwanted complication of depression is suicide, which in fact has a higher rate than homicides in the US (1).

Hopelessness is the main indicator leading to suicide, a trapped pattern of thinking where individuals believe things will never get better. The deep despair and hopelessness that accompanies depression can make suicide seem like the only way to escape from the overwhelming circumstances. Therefore, suicidal thoughts must be considered as a cry for help and dealt with accordingly.

Psychosocial context appears to be the commonly associated culprit that may predispose people to depression instead of genetic predisposition and other secondary etiologic factors. Depression in the psychosocial context is related to a person’s perception of daily events. A specific event in a person’s life can trigger the beginning of a vicious cycle. Examples could include: changes in occupation, loss of a loved one, etc.

Modesty

In addition to hopelessness, avarice can lead to depression because it contributes to dissatisfaction, disappointment, and loss of sincerity. Sometimes, the lack of material goods can make a person happier than having them. Jealously chasing material things that others have can lead a person into depression. For example, the ancient philosopher Plato was wise but not wealthy; despite his lack of money he was content with his life. One day, as he was passing by a spring, he noticed a boy drinking water with his hands. The average person, having witnessed this, would give the child a cup, but Plato asked himself if the cup is even needed. If you focus on what you do not have, you will always be disappointed. Actually focusing on what you need in the present time can decrease the damage one incurs from his or her problems. The child was thirsty and he only needed water, so the cup was unnecessary.

If a person is only concerned with his or her own situation and not noticing the condition of those around them, it can turn trivial problems into mountains. By comparing one’s own problems with greater problems of others, the person can get a more accurate perspective. Though a person’s burden may appear unbearable, God has created each person with the ability to handle these burdens. It is recommended to keep hope by exercising patience and concerning yourself with the present condition rather than bringing problems up from the past or worrying about the future. The patience given to human beings is sufficient to all types of difficulties, unless used inappropriately to obsess about what already happened in the past or to worry about distant future.

Never lose hope

As shown in Table Figure 1, The American Psychiatric Association (APA) has established the universal criteria for health professionals to diagnose depression. According to The Diagnostic and Statistical Manual of Mental Disorders IV (DSM IV) criteria, physicians diagnose an individual as having depression, which is further classified as minor or major in terms of the severity of the symptoms (2).

Hopelessness deserves special concern because it often triggers the other symptoms which may eventually lead to inertia.

Belief and prayer have found to be extremely helpful in combatting hopelessness by keeping hopes high. This can help to prevent serious depression or even suicide, for even in the most difficult times, belief can allow a person to stand firm with the conviction that even a single leaf would not drop without God’s knowledge. The Qur’an states: “Say (God gives you hope): ‘O My servants who have been wasteful (of their God-given opportunities and faculties) against (the good of) their own souls! Do not despair of God’s Mercy. Surely God forgives all sins. He is indeed the All-Forgiving, the All-Compassionate’” (The Qur’an 39.53).

The Bible echoes a similar tone when it says, “For as high as the heavens are above the earth, so great is his steadfast love toward those who fear him; as far as the east is from the west, so far does he remove our transgressions from us (Psalm 103, 8-12).

What does the literature say about belief?

A survey revealed the fact that 82% of Americans believe that prayer can cure serious illness, 73% believe that praying for others can cure illness, and 64% want their physicians to pray with them. Health professionals – especially doctors and nurses – should be aware of the spiritual needs of their patients, should be familiar with literature on the effectiveness of prayer, and should integrate it into their comprehensive care plans (3).

From the biological perspective, as shown in Figure 2, symptoms and signs of depression shown in Figure 1 occur as a result of the change in the level of neurotransmitters – namely serotonin, norepinephrine, and dopamine. Today, pharmacological interventions to heal depression are mainly provided by drugs. These regulate the levels of the neurotransmitters. There aren’t many scientific studies focusing on depressing and religion, however McCullough’s review of literature clearly states that “People with high levels of general religious involvement, organizational religious involvement, religious salience, and intrinsic religious motivation are at reduced risk for depressive symptoms and depressive disorders” (4).

In conclusion, depression may arise from the lack of staying active. In order to keep away from the negative thoughts which serve as a starting point for depression’s vicious circle, praying and seeking help from the All-Knowing, All-Wise serves as a shelter from the negative feelings of temporary worldly troubles. Praying may provide a protection against negative thoughts that may arise from an external or internal source, eventually leading to a distortion of healthy thinking.

Subjective healing and improvement in health after praying, psychological therapy, and family and social support may stimulate some neurotransmitters, though this needs to be further clarified by comprehensive studies (5). However, even simple words may have an impact on the mood of any individual. Hearing a compliment may cause a smile, or receiving a phone call giving a bad news might cause sadness. How could sincerely pouring one’s heart out to the All-Knowing not reverberate from His eternal source into the body, even if the circumstances appear overwhelming?

Mucteba Muezzinoglu is a freelance currently living in Illinois, US.

Nate Emru is a Mental Health Counselor in Indianapolis, Indiana, US.

References

1. Further information is available at http://www.sprc.org/basics/about-suicide. Reached in April 25.
2. The Diagnostic and Statistical Manual of Mental Disorders (DSM). American Psychiatric Association provides a common language and standard criteria for the classification of mental disorders.
3. Ameling A. 2000. “Prayer: an ancient healing practice becomes new again.” Holist Nurs Pract. Apr;14(3):40-8.
4. McCullough ME, Larson DB. 1999. “Religion and depression: a review of the literature.” Twin Res. Jun;2(2):126-36.
5. National Institute of Mental Health. What medications are used to treat depression? Reached from the website. http://www.nimh.nih.gov/health/publications/mental-health-medications/complete-index.shtml#pub5

Southern Pine Beetles (Dendroctonus frontalis, figure 1) are one of the most harmful pests in the world, causing hundreds of million dollars worth of damage to pine trees in the Southern United States. These beetles initiate their attack on a pine tree by having a small group of female beetles dig into the inner park (Figure 2) and phloem of the pine tree. Once this work is done these females will secrete a chemical that will draw other male and female beetles to the affected pine tree. This initial attack is followed by a massive attack by a larger number of beetles, enabling them to easily overcome the defenses of the pine trees due to the sheer number of beetles. Shortly after taking over the tree, mating begins between the male and female beetles. As part of the mating process the females fill the excavated galleries within the trees with eggs. After the eggs have been laid the adult beetles will then leave the tree and continue to attack other trees. Attacking trees and causing their death is of course a sad story and may not sound very interesting since most pests have similar attack strategies; however, one detail that we did not mention yet makes this process more intriguing. What do the larvae eat to complete their development within a gallery that is inside a dead tree? The answer is: Fungi.

Pine beetles establish a symbiotic life structure with a beneficial fungus (Entomocorticium sp. A), which is the main food source for their larvae. Adult pine beetles have a body compartment (mycangium), in which they can carry this fungus. When adult beetles dig galleries in tree barks, they inoculate these galleries with the fungi. This fungus will grow in these galleries that helps the beetles’ larvae complete their development by providing them with a source of nutrition. Fungi also benefit from this process by being transferred from one tree to another with the help of the beetles. This symbiotic life structure is threatened by the existence of an antagonistic fungus, (Ophiostoma minus, also known as blue stain fungus) and parasitic mites both of which the southern pine beetles also bring along. The blue stain fungus has no nutritional importance for larvae, this fungus can grow in the same galleries as the beneficial fungus and they can even outcompete them. In addition, the parasitic mites feed on the blue fungi and can prove harmful beetles as the amount of blue fungi increases. Therefore, beetles’ larvae cannot survive for long and thus the reproduction of the southern pine beetles can be disrupted without some form of defense.

A recent study by Scott et al. has shed some light on this complicated life structure [3]. These tiny beetles, which are only a few millimeters long, have a smart defense mechanism to prevent their larvae (Figure 3, pink arrow). As far as the history tells us, humankind started using pesticides about 5000 years ago, but these tiny beetles have been using them for preventing the growth of the blue-stain fungi long before humans started using pesticides. These studies showed that the symbiotic coexistence of southern pine beetles and the beneficial fungi (Figure 3, yellow circle) is maintained by a (actinomycetous) bacterium (Figure 3, inside the red square). This bacterium produces a previously unknown antibiotic compound (named mycangimycin), which selectively inhibits the growth of blue-stain fungus hence providing a significant advantage for the maintenance of the beneficial fungi (that is, the main food source of the larvae). How can this bacterium even be present in the freshly carved galleries in pine trees in the first place? The surprising answer to this question is that they are transferred to these galleries by the very same pine beetles. As mentioned earlier, adult pine beetles carry beneficial fungi in their body compartment (mycangium) and inoculate the galleries they carved with this fungus to provide food for their larvae. In addition to this beneficial fungi these beetles carry they also carry bacteria that can produce antibiotic compound to inhibit the growth of blue-stain fungi and consequently diminish the number of parasitic mites. This bacterium can grow inside these galleries and even in a body compartment of adult southern pine beetles. Interestingly, this antibiotic kills blue-stain fungi but does not significantly affect the growth of the fungi, which is the food source for larvae. Thus, the beneficial fungi can multiply in number and offer enough food for the development of beetle larvae. Some of these larvae manage to grow to adults and then leave to attack other pine trees carrying the same fungi and bacteria with them (Figure 4).

The interactions within the rest of the life kingdoms is not any less complicated than the symbiosis between pine beetles, fungi, and the bacteria. The interactions between animals, plants and microbes are very complex and also fragile. Removing or replacing any member of an ecosystem can often result in a serious failure in the ecosystem as was observed many times especially within the last century.

References

1. http://www.nsf.gov/news/news_summ.jsp?org=NSF&cntn_id=112319&preview=false.
2. http://entnem.ufl.edu/creatures/trees/southern_pine_beetle.htm.
3. Scott, J.J., et al., “Bacterial protection of beetle-fungus mutualism.” Science, 2008. 322 (5898): p. 63.

“The human brain, then, is the most complicated organization of matter that we know.”
Isaac Asimov

If someone asks what you recall when you look at the following pictures, I can hear you say ‘President Obama’ and ‘Statue of Liberty’. You just see a fragment of the pictures and remember them.

So, how does it happen? This is just a simple task for the brain. It stores an image and retrieves it whenever a part of it is seen. Amazing features of the brain, especially its power to learn and make decisions, inspires computer scientists in the field of artificial intelligence.

In computer science, an artificial neuron is a simple computational model of a neuron in the brain that excludes biological properties. Artificial neural networks (ANNs) are composed of artificial neurons, and they are utilized to solve specific problems, especially those that require learning and decision-making. ANNs may not be the best solutions in various machine learning problems; however, they are accepted as strong alternatives. Although ANNs don’t claim to be so, currently they are not even close to producing a simple model of the brain. Let’s take a short journey into the world of ANNs to experience the extreme difficulty of modeling the brain.

Some Applications of ANNs

Figure 1: Overview of ALVINN structure. Images obtained from the camera installed on the vehicle are provided to the ANN, and ANN decides the steering angle.

(adapted from: http://virtuallab.kar.fei.stuba.sk/robowiki/images/e/e8/Lecture_ALVINN.pdf).

ANNs have various applications in very large spectrum of problems that require learning, such as the Autonomous Land Vehicle in a Neural Network (ALVINN). The structure of ALVINN is shown in Figure 1. The ALVINN project by Carnegie Mellon University started in 1986 and aims to make a vehicle without a driver (Mitchell, 1997). In this project, ANN learns the steering habits of a driver. A camera is mounted on the vehicle to capture the images of the road. With respect to the continuous images provided, ALVINN determines the steering level with 45 different angle positions from sharp left to sharp right. Steering is updated 15 times per second so that it allows real-time control while driving at 55 mph. The system is trained by the data obtained from a human driver in a simulator and a real vehicle. ALVINN was able to speed up to 70 mph and successfully drive at 55 mph for 90 miles.

Figure 2: Handwritten zip codes (LeCun, et al., 1989)

Another example is handwritten zip code recognition (LeCun, et al., 1989). Zip codes from US Mail written by various people with large variety of styles and sizes were used in the experiments. Figure 2 presents some examples of zip codes in the experiment database. After the ANN was trained with more than 7,000 digits in the zip codes, it was 99% successful in recognizing around 2,000 digits in new zip codes.

Learning and Decision-making in ANNs

In order to understand the challenges better, we will first examine learning and decision-making in neurons and ANNs on simple examples.

Figure 3: (a) A typical neuron (adopted from http://commons.wikimedia.org/wiki/File:Neuron_-_annotated.svg), (b) artificial neuron in computer

Figure 3(a) illustrates a typical neuron which is the constituent of brain’s complicated network structure. Each neuron receives information as signals via dendrites, then evaluates it and generates a signal that is transmitted through its axon. A neuron has many connections between its dendrites and the axons of various other neurons. Figure (b) demonstrates an artificial neuron in computer science. It is considered a function: dendrites as the inputs of the function and generated signal via the axon as the output of the function.

Let’s see an example of an artificial neuron that understands if a given produce is a red apple or not. Think about how you understand whether a produce is a red apple or not. You see the shape and the color. However, it might be an artificial one for decoration. Then you can taste it and you get the sweetness of the apple. Similarly, our neuron receives three pieces of information as the input; ‘has circular shape?’, ‘is sweet?’, and ‘has red color?’. If the output is ‘yes’, that means the neuron recognizes the produce as a red apple. Otherwise, it will be ‘no’, which means the produce is not a red apple (Figure 4). Here, the neuron’s function is defined in such a way that it only generates ‘yes’ when all the inputs are ‘yes’.

Figure 4: Example inputs and outputs for the artificial neuron.

In an artificial neuron, some of the information can be more important than the others. For instance, to have red color may be more valuable in determining the price of produce. Assume that round shape and sweetness has equal value of $1; however, having red color is $2 – twice as valuable as the other features (Figure 5).

Figure 5: Artificial neuron with different input weights. Arrow thickness indicates the importance.

So, what is the big fuss about artificial neurons if they are only functions? In fact, the main feature of artificial neurons is learning. Considering the last example above, the neuron initially does not know the importance of the dendrites, i.e. the weights of inputs are all the same. If not trained, the neuron will generate the following answers which are sometimes wrong as indicated in Table 1.

Table 1: Artificial neuron before training; highlighted answers are wrong.

In real life, a teacher trains students. For instance, the teacher asks a question and if the received answer is not correct, she provides the right answer. Students learn the right answer and use this correct information in their lives. It is similar in artificial neurons as depicted in Figure 6. When the response of the neuron is incorrect, it adjusts the importance of the dendrites with respect to the correct answer hence it answers the same question correctly next time. During the training session, the neurons will be continuously asked the values of all the produce until it learns them all.

Figure 6: The learning process of the artificial neuron.

What if the problem gets complicated? Then one artificial neuron will not be sufficient, and we will need a network of neurons; ANNs. A more complex problem, ‘learning the digits’ is indicated in Figure 7.

Figure 7: (a) Digit learning problem, (b) ANN structure that learns digits. Due to the difficulty, only the connections between the input layer and first / last neurons in the middle layer are shown.

ANN has 3 x 5 = 15 input units like receptors of an eye retina. Each input unit corresponds to one square in the digits; either filled or blank. Each input unit is connected to the dendrites of all neurons in the middle layer. The output of each cell in the middle is connected to the dendrites of all neurons in the output layer. There are 10 output neurons corresponding to the digits from 0 to 9. After the ANN is trained, it provides a correct answer to the given digit as input. When digit ‘3’ is provided to the network, the neuron labeled with number ‘3’ in Figure 7(b) is triggered and outputs ‘yes’ whereas the rest of the neurons output ‘no’.

Figure 8: Faulty digit ‘3’ with a missing black square on the top right side.

Initially, all neurons in the network have equally weighted dendrites. After a reasonable amount of training, neurons adjust their weights, and ANN is able to identify digits. Here, we have some major challenges: what does ‘reasonable amount of training’ mean? When the ANN is undertrained, it will not always answer correctly to the digits given in Figure (a). In the other case, when the ANN is overtrained, it will memorize the digits provided during the training and will not recognize the faulty ones such as the one in Figure 8.

Challenges of ANNs

Beyond the mentioned the overtraining / undertraining problems, ANNs have a bigger challenge – how to determine the structure of ANN that fits the problem? In the digit learning example, we’re lucky because the structure is provided in Figure 7(b). However, the outcome of the solution may drastically depend on the number of neurons and the connections among them which is indeed a hard problem for ANNs.

The huge capability of the brain in learning and decision making comes from the huge number of neurons – around 100 billion – and the enormous amount of connections among them – from 100 to 500 trillion. The challenge to design such a huge network requires huge computation power. With the increasing number of neurons, ANN dramatically slows down especially during the learning process. Here, our example is a simple learning task of 3×5 pixel digits compared to the brain’s acquisition capacity of hundreds of images in our daily life. 

When the number of neurons gets larger, the reliability of network also reduces. Small adjustments in weights may change the entire behavior of the network hence it is easy to lose control of ANN. In contrast, the brain has a robust system, and its fault tolerance is admirable. Although neurons die every day, this doesn’t affect its performance significantly. The training method and how to update the weights are other hard problems leading to many different approaches in the neural computation field.

We have presented some simple tasks that can be solved using a few neurons and their challenges. On the other hand, consider the thousands of problems, various and incredible amount of information we have learned, and the thousands of decisions we make. The brain is truly amazing from the computer science perspective.

Bibliography

• Hertz, J. A., Krogh, A. S., & Palmer, R. G. (1991). Introduction To The Theory Of Neural Computation. Reading, MA: Addison-Wesley.
• Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational properties. Proceedings of the National Academy of Sciences of the USA , 79, 2554-2588.
• LeCun, Y., Boser, B., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W., et al. (1989). Backpropagation applied to handwritten zip code recognition. 1 (4), 541-551.
• Mitchell, T. M. (1997). Machine Learning. McGraw-Hill.

Every human being asks the question “why,” though at different levels, to explain the unexplained. It follows a pattern of questions, like “Why did the financial crisis in the U.S. happen in August 2008?” “Why did the space shuttle Challenger explode?” “Why did the terrorists commit the September 11 attacks?” In statistical terms, such unexpected events are named “outliers,” however, they are part of the system and among the components constituting the overall system’s complex behavior. Thus, they need to be part of the explanation in order for the explanation to be complete. We are naturally tempted to come up with universal explanations of the complexity behind these major events so that we can be ready when a similar thing happens again. Though simple mathematical equations or relationships relate to us better and provide a universal explanation, they are typically practical only when the outliers are excluded from the system behavior. Statistics help us greatly in quantifying and characterizing the outliers, especially in the form of probabilistic expressions, such as “there is a 30% chance of a hurricane next week.”

Understanding the complexity around us involves the development of a model that is simple enough for us to comprehend but yet universal enough to capture most of the dynamics of the complexity. The simpler and the more universal the model, the more powerful it is. The universality of a model, however, is hindered by the potential inability to capture something unexpected. The tradeoff between simplicity and universality exists in all modeling efforts; and the models finding the delicate balance in this tradeoff are the most effective ones. A simple mathematical relationship known as “the power law” has been used extensively to characterize and model various natural and social phenomena.

What is the Power Law?

The “power law” does not refer to a misconception that “whoever has power will rule,” but rather it refers to a particular way of characterizing dependency between two quantities. When the number or frequency of an object or event varies as a power of some attribute of that object (e.g., its size), the number or frequency is said to follow a power law. In more general terms, there exists a power law relationship between x and y if y is growing or reducing polynomially when x is growing linearly (y _͌ x^–α). Mathematically speaking, this means that the relationship between y and x is mainly characterized by the exponent -a. An exponent is simply shorthand for multiplying that number of identical factors. So, 4³ is the same as 4x4x4; that is three identical factors of 4. As shown in Figure 1, a quantity with an exponent has three components: the base, the exponent, and the coefficient. So, for 4³, the base is 4, the exponent is 3, and the coefficient is an implicit 1.

Figure 1: Description of an exponent in a power law relationship.

Figure 2: Sample power law relationships between x and y, where y = x^–α.

The power law relationships are traditionally expressed with a negative exponent, which simply means the inverse of the quantity. That is, y _͌ x^–α is equivalent to y _͌ 1/x^α. For example, when a is 2, y will reduce from 1/4 (i.e. 0.25) to 1/9 (i.e. ~0.11) if x grows from 2 to 3. Likewise, when a is 0.5, y will reduce from 1/2 (i.e. 0.5) to 1/3 (i.e. 0.33) if x grows from 4 to 9. For those who enjoy graphs, Figure 2 illustrates these mathematical relationships in linear and logarithmic scales.

Power law on different scales: Atoms to planets

To start with, gravitation, acoustics, electrostatics, and light and electromagnetic radiation, all exhibit a form of power law in that physical quantity or strength that is inversely proportional to the square of the distance, which corresponds to a power exponent of 2. [1] Gravitational force between two particles, the electrostatic force of attraction between two electrically charged particles, the intensity of sound signals coming from a source, and finally the intensity of light or electromagnetic field coming from a source all follow a power law with respect to the distance.

What makes the power law relationships more interesting is their independence from scale or size of the measures being related to each other. This is why we sometimes call power law relationships as “scale-free” relationships or “scale-invariance.” For example, the gravitational force between two spherical particles decays with a power exponent of 2 regardless of the sizes of the particles though the actual force is certainly dependent on the particle sizes. So, the particles can be at nano scales (e.g. a group of atoms) or macro scales (e.g. a planet), but the relationship stays the same!

Power law in frequency: Wealth, terror, and earthquakes

A common usage of power law relationships has been to model and understand frequency of a varying measure. A power law typically very well represents the distribution of wealth in a society. [2] According to a recent study, the distribution of wealth in China during the years 2003–2005 follows a power law with an exponent ranging from 1.758 to 2.285. If we consider an average exponent of 2 for Chinese wealth distribution, this means that if there are 1 million Chinese people who owned $1000 there were 1000 that owned $1M. Thus, the power law essentially expresses how skewed the distribution of a frequency is (see Figure 2). The larger the power exponent, the more skewed the distribution. In this case, a larger power exponent means a more imbalanced wealth distribution while a power exponent of 1 refers to an evenly distributed wealth.

Many other social patterns exhibit power law. A recent study showed that it exists even in terror events! The number of casualties per insurgent event and the number of insurgent events per day follow a power law. [3] Historical data for the last two centuries show further that the number of casualties per war or a terror attack follows a power law distribution. What is even more interesting is that the number of casualties and the number of attacks within an insurgent conflict both follow power law. That is, when only a particular conflict between two countries or ethnic groups is considered, the number of casualties per insurgent event and the number of insurgent events per day follow the power law. This suggests a “self-similar” pattern. Likewise, traffic measurements for many systems show power law distributions of size. For instance, if one observes the data traffic on an Internet connection and counts the number of bytes being transmitted per hour over that connection, a power law distribution of the count of bytes will emerge. Further, if this counting is done per minute instead of per hour, a similar distribution will still emerge – again showing a self-similar pattern. [4]

The power law has been observed in several natural phenomena as well. The frequency of earthquake magnitudes follows a power law. [5] This refers to the intuitive notion that the number of earthquakes with small magnitudes (which humans do not even feel) is much larger than the number of earthquakes with large magnitudes, (which can kill many humans). Small earthquakes are the norm while large ones the outliers. However, without the outliers, there is no power law distribution! Thus, the power law distribution of a quantity comes with an interesting observation: If a quantity is indeed following a power law distribution, then the likelihood of an outlier event increases as the time goes by without an outlier event. This is why geoscientists would make comments like “The region X is due for a major earthquake!” indicating that the region X has not been receiving a major earthquake (i.e. an outlier) for several years. The issue, though, is determining the threshold for an outlier is typically ambiguous and may require many years of measurements and data, which may be impractical.

Power law in growth: Rich get richer

Growth of systems also exhibit power law in various ways. Social growth follows power law due to the well-known “rich get richer” rule, which refers to the intuition that “important” people in the society attract more of the attention of newcomers. This dynamic situation is observed, for example, in the growth of the Internet. Several studies [6] showed that the connections between Internet Service Providers (ISPs) (e.g., AOL, Yahoo!, AT&T, Sprint) follow a power law distribution in that the number of connections per ISP (which shows how well an ISP is connected to the rest of the world) is represented by power law. In other words, there are few ISPs with many connections to other ISPs while most ISPs have a few connections to the others. This is believed to be due to the “rich get richer” rule since an existing ISP with many connections is more likely to gain the business of a new ISP who is joining to the Internet. So, it is somewhat an economic pattern too.

If economics (or the money) is taken out of the picture, social growth still exhibits power law. Online social networks such as Facebook, LinkedIn, and Flickr are clearly following a power law distribution. It is found that the power exponents are in the range of 2.5 to 3.7, indicating a highly imbalanced social growth pattern where few people are at the “center” of the social network with hundreds or thousands of friends, and many people have only one or two friends. [7] Again, the typical explanation for this growth pattern has been the “rich get richer” rule, but “richness” refers to the number of existing friends in this context rather than money.

Physical growth shows power law too in many ways. For instance, roughness of a growing surface as time goes by follows a power law distribution with an exponent ranging between 0 and 1 where an exponent of 0 refers to a smooth growth and 1 refers to a stiff growth. The surface roughness is measured by the variance of heights of surface locations. [8]

Does it really exist? Why does it exist?

Verifying existence of a power law distribution is not easy and requires enough number of samples to show the “tail” of the distribution. The tail of the distribution refers to the samples with large (or rare) values. For example, for the power law distributions in Figure 2, the portion of the distribution when x is greater than 10 (i.e. x>10) roughly corresponds to the “tail.” The tail corresponds to the rare samples. Though statistical theory calls those rare samples “outliers,” the distribution will not be a power law distribution without them. They are strictly parts of pieces that constitute a power law relationship, and observing them typically requires long periods or large numbers of measurements. Due to this difficulty, the existence of the power law is questioned for many real systems. Most of the time, claims of the existence of the power law typically come with an error factor indicating the confidence of the claim. The bottom-line is to observe trends in the samples and thus establish sufficient confidence (e.g., more than 95%) that the power law distribution does exist in the samples.

For those systems with clear exhibition of power law, the root causes of it have been of high interest. The “rich get richer” rule is intuitively one of the root causes, and it is intuitively a natural dynamic to get attracted by a rich member rather than a poor one. Growth certainly naturally follows the “rich get richer” rule, but we have system components slowing their growth, flattening, and then deteriorating. So, not everything is growing, and actually, we have as many things deteriorating as growing. For instance, participants join or leave the Internet or the social networks, and likewise, people join (i.e. birth) or leave (i.e. death) society. How does the power law stay in such systems then?

Due to the “rich get richer” intuition, the power law is considered to be the signature of “self-organization.” The fact that so many natural or synthetic systems are exhibiting this signature deserves the question: “Is it really self-organization?” Maintaining a global power law distribution for a system requires either (i) every member joining or leaving the system according to the “rich get richer” rule and having global knowledge of the whole system or (ii) somebody who knows everything about the system and gives explicit direct orders to each member when they are joining or leaving. Which one is more likely?

Murat Yuksel is an Assistant Professor at the CSE Department of The University of Nevada – Reno (UNR), Reno, NV.

References

[1] Wikipedia, “Inverse-square law,” http://en.wikipedia.org/wiki/Inverse-square_law

[2] M. A. Santos, R. Coelho, G. Hegyi, Z. Néda, and J. Ramasco. 2007. “Wealth distribution in modern and medieval societies,” The European Physical Journal, Volume 143, Number 1, pages 81-85.

[3] J. C. Bohorquez, S. Gourley, A. R. Dixon, M. Spagat, and N. F. Johnson. 2009. “Common ecology quantifies human insurgency,” Nature, Volume 462, December, pages 911-914.

[4] T. Karagiannis, M. Molle, and M. Faloutsos. 2004. “Long-Range Dependence: Ten Years of Internet Traffic Modeling,” IEEE Internet Computing, September/October, pages 57-64.

[5] T. Lay and T. Wallace. 1995. Modern Global Seismology, Academic Press, San Diego, CA.

[6] M. Faloutsos, P. Faloutsos, and C. Faloutsos. 1999. “On power-law relationships of the Internet topology,” ACM Computer Communication Review, Volume 29, Issue 4.

[7] R. Kumar, J. Novak, and A. Tomkins. 2006. “Structure and evolution of online social networks,” Proceedings of ACM SIGKDD, pages 611-617.

[8] A. L. Barabasi and H. E. Stanley. 1995. Fractal Concepts in Surface Growth, Cambridge University Press, Cambridge, England.

The existence of antimatter was suggested in 1928 by Paul Dirac and was confirmed experimentally in 1932 by Carl D. Anderson. They state that every elementary particle (matter) has its own anti-particle (antimatter): electrons have anti-electrons (positrons) and protons have anti-protons and so on. Antimatters have the same mass as matter, but they carry an opposite electrical charge [1]. For that reason, if matter and antimatter collide they cancel each other out, resulting in annihilation. This collision produces a tremendous amount of energy. For instance, a collision of 1 kg of matter and antimatter releases the energy equivalent to the explosion of 43 megatons of TNT [2].

However, producing antimatter is not an easy process and requires very energetic collisions in giant accelerators such as CERN, located near Switzerland, and Fermilab, located near Chicago, US. The annual amount produced in these laboratories is 1^-10 nanograms. The typical process is to accelerate protons to almost the speed of light, and then send them into a metal target, which is usually tungsten. Because of the collision, the protons are slowed or stopped by the nuclei of the tungsten atoms. The protons’ kinetic energy is converted into matter that contains subatomic particles, and some of these particles are antiprotons [3].

To avoid annihilation, antimatter must be separated from other subatomic particles. One way to do that is to use the Penning trap in which charged particles of antimatter are confined radially by homogenous magnetic fields and axially by quadropole electric fields. Penn State and NASA scientists have already built such a device capable of holding 10 million antiprotons for a week. Now they are developing a Penning trap with a capacity 100 times greater [3].

Figure 1: Schematic of Penning Trap: Electric fields are blue, Magnetic fields are red, a: end cap, b: ring electrode, c; magnets (www.en.wikipedia.org)

Many of us remember the antimatter engine from the Star Trek series. Interplanetary travel has been humankind’s dream for centuries. Now, scientists are designing a spacecraft propulsion system that will work by expelling the products from the annihilation of protons and antiprotons. Such a propulsion system requires antimatter the size of an aspirin (10 grams) for hundreds of light years of travel. However, this amount of antimatter is not available yet, and with current technologies, it would cost around 100 trillion dollars to produce 1 milligram of antimatter.

One of the discoveries made by scientist at Penn State was that a space propulsion system would need only a small fraction of the antimatter consumed by a beamed core engine. It would work with an antiproton induced micro-fission (ACMF). In this process, Deuterium-Tritium (D-T) pellet and Uranium-238 (U-238) are compressed with a proton beam [1 in Figure 2]. After two nanoseconds, the pellet is subject to antiproton beams [2 in Figure 2]. Uranium U-238 absorbs the antiprotons and the result is a hyper neutronic fission that transfers the heat energy from the uranium core to D-T pellet and ignites it [3 in Figure 2]. Propellant inside the pellet is expanded to produce a pulsed thrust [4 in Figure 2].

Figure 2: Illustration of ACMF reaction chain, in four steps (www.ffden-2.phys.uaf.edu)

Another concept is called Antimatter-initiated micro-fusion (AIM), which was also designed by Penn State scientists. In this mechanism, electromagnetic fields continuously compress a small concentration of antiproton plasma [1 in Figure 3] Than the Deuterium-Tritium droplet injected into the plasma [2 in Figure 3]. Also a small amount of U-238 is allowed to annihilate with the antiprotons, which fully ionizes and heats the plasma. The resulting product is expelled out of a magnetic nozzle to produce thrust [3 in Figure 3]. Finally potential well is relaxed to its original state [4 in Figure 3]

Figure 3: Illustration of AIM reaction chain, in four steps (www.ffden-2.phys.uaf.edu)

Scientists also believe that antimatter has the potential to be applied in medical sciences and one of them is fighting cancer. Currently, scientists at CERN are investigating the antiproton beam therapy as an alternative treatment. Experiments have compared the damage of proton and antiproton beams on hamster cells. The results show that the damage inflicted by antiprotons to cells at the end of the beam path was four times greater than that of proton beams. This means that one antiproton is enough to achieve the same damage as four protons, and moreover, antiprotons have unsurpassed ability to preserve healthy tissue [4].

Image of antimatter cell interaction experiment (www.rsc.com)

It seems that producing large quantities of antimatter is difficult and expensive today, but as long as we are on the right track with the right developments, one day, it could become a reality. If a significant amount of antimatter can be produced and controlled, this could help us obtain more information about nature, and it might become one of the world’s primary energy sources. It can also bring innovative solutions with medical benefits such as cancer therapy. Last but not least, antimatter also offers implications of existence beyond what we can see, thus an infinitely vast area of research to conduct via not only with our minds but also with our hearts.

Mehmet Fatih Yýlmaz is Assistant Professor at the engineering faculty of Mevlana University, Konya, Turkey.

Note: Author would like to thank Margaret Johnson for her useful comments on this article.

References

1. Dirac, Paul. 1928. “The Quantum Theory of the Electron,” from Proceedings of the Royal Society of London: Series A 117 (778): 610–624.

2. www.wikipedia.com

3. www.engr.psu.edu/antimatter

4. www.press.web.cern.ch