| DNA & Information & Chemical Reaction |

Chemical Reaction & Information

Description of Chemical Reactions;

||Reactions are the verbs of chemistry. The activity that chemists study. Many reactions move to their conclusion and then stop, meaning that the reactants have been completely transformed into products, with no means of returning to their original state. In some cases, the reaction truly is irreversible, as for instance when combustion changes both the physical and chemical properties of a substance. There are plenty of other circumstances, however, in which a reverse reaction is not only possible but an ongoing process, as the products of the first reaction become the reactants in a second one. This dynamic state, in which the concentration of reactants and products remains constant, is referred to as equilibrium. It is possible to predict the behavior of substances in equilibrium through the use of certain laws, which are applied in industries seeking to lower the costs of producing specific chemicals. Equilibrium is also useful in understanding processes that preserve or potentially threaten human health.

A chemical reaction is a process whereby the chemical properties of a substance are altered by a rearrangement of the atoms in the substance. The changes produced by a chemical reaction are fundamentally different from physical changes, such as boiling or melting liquid water, changes that alter the physical properties of water without affecting its molecular structure.

Though chemical reactions are most effectively analyzed in terms of molecular properties and behaviors, there are numerous indicators that suggest to us when a chemical reaction has occurred. It is unlikely that all of these will result from any one reaction, and in fact chances are that a particular reaction will manifest only one or two of these effects. Nonetheless, these offer us hints that a reaction has taken place.

Signs that a substance has undergone a chemical reaction:

Water is produced, A solid forms, Gases are produced, Bubbles are formed, There is a change in color, The temperature changes, the taste of a consumable substance changes, The smell changes.

Many of these effects can be produced simply by changing the temperature of a substance, but again, the mere act of applying heat from outside (or removing heat from the substance itself) does not constitute a chemical change. Water can be produced by melting ice, but the water was already there it only changed form. By contrast, when an acid and a base react to form water and a salt, that is a true chemical reaction.

Similarly, the freezing of water forms a solid, but no new chemical substance has been formed. In a chemical reaction by contrast, two liquids can react to form a solid. When water boils through the application of heat, bubbles form, and a gas or vapor is produced; yet in chemical changes, these effects are not the direct result of applying heat.

In this context, a change in temperature, noted as another sign that a reaction has taken place, is a change of temperature from within the substance itself. Chemical reactions can be classified as heat producing (exothermic) or heat absorbing (endothermic). In either case, the transfer of heat is not accomplished simply by creating a temperature differential, as would occur if heat were transferred merely through physical means.

At one time, chemists could only study reactions from the outside, as it were, purely in terms of effects noticeable through the senses. Between the early nineteenth and the early twentieth century, however, the entire character of chemistry changed, as did the terms in which chemists discussed reactions. Today, those reactions are analyzed primarily in terms of subatomic, atomic, and molecular properties and activities.

Despite all this progress, however, chemists still do not know exactly what happens in a chemical reaction but they do have a good approximation. This is the collision model, which explains chemical reactions in terms of collisions between molecules. If the collision is strong enough, it can break the chemical bonds in the reactants, resulting in a re formation of atoms within different molecules. The more the molecules collide, the more bonds are being broken, and the faster the reaction.

Considering all other kinetic parameters constant, an increase in the numbers of collisions can be produced in two ways: either the concentrations of the reactants are increased, or the temperature is increased. By raising the temperature, the speeds of the molecules themselves increase, and the collisions possess more energy. A certain energy threshold, the activation energy must be crossed in order for a reaction to occur. A temperature increase raises the likelihood that a given collision will cross the activation energy threshold, producing the energy to break the molecular bonds and promote the chemical reaction.

Raising the temperature and the concentrations of reactants can increase the energy and hasten the reactions, but in some cases it is not possible to do either. Fortunately, the rate of reaction can be increased in a third way, through the introduction of a catalyst, a substance that speeds up the reaction without participating in it either as a reactant or product.

A chemical equation, like a mathematical equation, symbolizes an interaction between entities that produces a particular result. In the case of a chemical equation, the entities are not numbers but reactants, and they interact with each other not through addition or multiplication, but by chemical reaction. Yet just as a product is the result of multiplication in mathematics, a product in a chemical equation is the substance or substances that result from the reaction.

Instead of an equals sign, between the reactants and the product, arrows are used. When the arrow points to the right, this indicates a forward reaction; conversely, an arrow pointing to the left symbolizes a reverse reaction. In a reverse reaction, the products of a forward reaction have become the reactants, and the reactants of the forward reaction are now the products.

Chemical equilibrium, which occurs when the ratio between the reactants and products is constant and in which the forward and reverse reactions take place at the same rate.

Chemical equations usually include notation indicating the state or phase of matter for the reactants and products: (s) for a solid; (l) for a liquid; (g) for a gas. A fourth symbol, (aq), indicates a substance dissolved in water that is, an aqueous solution.

Not all situations of equilibrium are alike: depending on certain factors, the position of equilibrium may favor one side of the equation or the other. If a company is producing chemicals for sale, for example, its production managers will attempt to influence reactions in such a way as to favor the forward reaction. In such a situation, it is said that the equilibrium position has been shifted to the right. In terms of physical equilibrium, mentioned above, this would be analogous to what would happen if you were holding your arms out on either side of your body, with a heavy lead weight in your left hand and a much smaller weight in the right hand.

Your center of gravity, or equilibrium position, would shift to the left to account for the greater force exerted by the heavier weight.

Suppose we add more of a particular substance to increase the rate of the forward reaction. In an equation for this reaction, the equilibrium symbol is altered, with a longer arrow pointing to the right to indicate that the forward reaction is favored. Again, the equilibrium position has shifted to the right just as one makes physical adjustments to account for an imbalanced weight. The system responds by working to consume more of the reactant, thus adjusting to the stress that was placed on it by the addition of more of that substance. By the same token, if we were to remove a particular reactant or product, the system would shift in the direction of the detached component.

If the volume of gases in a closed container is decreased, the pressure increases. An equilibrium system will therefore shift in the direction that reduces the pressure; but if the volume is increased, thus reducing the pressure, the system will respond by shifting to increase pressure.

However, that not all increases in pressure lead to a shift in the equilibrium. If the pressure were increased by the addition of a noble gas, the gas itself since these elements are noted for their lack of reactivity would not be part of the reaction. Thus the species added would not be part of the equilibrium constant expression, and there would be no change in the equilibrium.

 In an exothermic, or heat-producing reaction, the heat is treated as a product. Thus, when nitrogen and hydrogen react, they produce not only ammonia, but a certain quantity of heat. If this system is at equilibrium, Le Chatelier's principle shows that the addition of heat will induce a shift in equilibrium to the left in the direction that consumes heat or energy.

The reverse is true in an endothermic, or heat-absorbing reaction. Chemical reactions involve the making and breaking of bonds. It is essential that we know what bonds are before we can understand any chemical reaction. To understand bonds, we will first describe several of their properties. The bond strength tells us how hard it is to break a bond. Bond lengths give us valuable structural information about the positions of the atomic nuclei. Bond dipoles inform us about the electron distribution around the two bonded atoms. From bond dipoles we may derive electronegativity data useful for predicting the bond dipoles of bonds that may have never been made before.

From these properties of bonds we will see that there are two fundamental types of bonds covalent and ionic. Covalent bonding represents a situation of about equal sharing of the electrons between nuclei in the bond. Covalent bonds are formed between atoms of approximately equal electronegativity. Because each atom has near equal pull for the electrons in the bond, the electrons are not completely transferred from one atom to another. When the difference in electronegativity between the two atoms in a bond is large, the more electronegative atoms that can strip an electron off, of the less electronegative one, to form a negatively charged anion and a positively charged cation. The two ions are held together in an ionic bond because the oppositely charged ions attract each other, when in the solid state, can be described as ionic lattices whose shapes are dictated by the need to place oppositely charged ions close to each other and similarly charged ions as far apart as possible. Though there is some structural diversity in ionic compounds, covalent compounds present us with a world of structural possibilities.

Conclusively, the number of possibilities of new chemical reactions for the industry is greatly enhanced by the capacity of modern computers.

||

How little change in small scale makes big different in large scale?!

It is Dynamic System. The system that always its elements are moving and there is no rule & role how to move!

It is always Chaotic.

Because of this we get, How DNA strings shape live organs and How simple bits of information generate complex system.

But we can predict what happen in the end of chemical reactions. For example if we mix A and B we can predict to have AB. However we can guess correctly results of reactions But we cannot mark each element. We can guess about congeries of materials. Even if we suppose that can mark some molecules we cannot mark electrons and of course we cannot predict about spins of electrons.

Chemical Reactions are depend on electrons when you observe them in small scale (on classical physics).

String of Information becomes observable at first step of classical viewpoint on spin & wave.

At second step its spinal state that shapes our universe; life & another structures.

But at the first step it is information, that can be stored on spinal state, atoms, molecules, wave state, quarks, sea, mountain, cells, trees, … & nothing!

When you chemically mix A & B it changes their structures so their information generate new structure with new properties and features it is How DNA can build completely new structure: with new internal & external features.

To be continue…

| Neural Net. - Computer Net. - Information |

Natural Network

Brief Introduction of Neural Networks & Control Center(Brain);

|| The brain is the control centre of human’s body and it sits in the skull at the top of spinal cord.

Brain is the most powerful & cleverest system in body. It acts quickly and accurately, it is too complex that scientists believe many actions of brain is unknown yet.

It collects all of the signals inside the body or from outside of body constantly and then sent a suitable order. Hearing, tasting, smelling, touching, seeing & moving are senses which get information for brain. These information are making neural signals. Neural signals cross nerve cells all over the body when get order from brain.

Brain has three important parts:

1- The cerebrum; which has two parts, the left and right cerebral hemispheres.

This area of the brain is involved in several functions of the body, like perception, thought, judgment, imagination, and decision. It includes about 10 billion neurons, with about 50 trillion synapses! It has four areas which called Lobes. Each lobe does its special task. For example neural signals of eyes, sent to Occipital Lobes or opinion and personality processing center is Frontal lobe.

2 - The cerebellum;

The cerebellum is under the cerebrum that does some important Task like learning & body’s balance. It gets the signals from muscles, Joints & skin by helping brain & spinal cord and after data processing sends an order.

3- The brain stem that controls a lot of the 'automatic' actions of the body such as breathing and heart beat, and links the brain to the spinal cord and the rest of the body.

The brain and spinal cord together make up the central nervous system (CNS).

The spinal cord has three major functions: as a conduit for motor information, which travels down the spinal cord, as a conduit for sensory information in the reverse direction, and as a center for coordinating certain reflexes.

Neuron cells

Brain and spinal cord are made a big group of neuron cells that estimated only a brain has 100 billion neurons.

A neuron is an electrochemical cell that Irritated easily. It transmits information by electrical and chemical signals. Neurons connect to each other to form neural networks, called Peripheral Nervous System (PNS).

All neurons are electrically excitable. Ions motion such as sodium, potassium, chloride, and calcium produce voltage gradients across neuron's membranes. Voltage gradients changing generate electrical Signals-called an action potential that cross all over the neuron. When action potential arrive the end of cell's axon, synaptic connections with other cells are acted. In synapses chemical molecules release and cause action potential at the next neuron.

There are 3 types of neurons:

1- Motor neurons, receive signals from the Central Nervous System to muscles, glands & elsewhere in the body.

2- Sensory neurons, respond to touch, sound, light and other sensory organs that then send signals to CNS. This neuron has long dendrites & short axon.

3- Relay Neuron, located within the brain and spinal cord, relay neurons transmit the electrical impulses generated by the stimuli to other nerves.

||

Description of Neural Network by Miriam Strauss;

||Artificial neural networks are systems implemented on computer programs as specialized hardware or sophisticated software that loosely model the learning and remembering functions of the human brain. They are an attempt to simulate the multiple layers of processing elements in the brain, called neurons. These elements are implemented in such a way so that the layers can learn from prior experience and remember their outputs. In this way, the system can learn to recognize certain patterns and situations and apply these to certain priorities and output appropriate results. These types of neural networks can be used in many important situations such as priority in an emergency room, for financial assistance, and any type of pattern recognition such as handwritten or text to speech recognition.

The most basic elements of a neural network, the artificial neurons, are modeled after the neurons of the brain. The real neuron is composed of four parts: the dendrites, soma, axon, and the synapse. The dendrites receive input from other neuron's synapses, the soma processes the information received, the axon carries the action potential which fires the neuron when a threshold is breached, and the synapse is where the neuron sends its output, which are in the form of neurotransmitters, to the dendrites of other neurons. Each neuron in the human brain can connect with up to 200,000 other neurons. The power and processing of the human brain comes from a multitude of these basic components and the many thousands of connections between them.

The artificial neurons simulate the four basic functions of the real neuron. The artificial neuron is much simpler than the neuron of the brain. It takes inputs just as the real neuron but also multiplies these inputs by a weight value. Then they are sent to a processing unit which does what it needs to do to the value and then sends this value to the output path. In the simplest case, the products of these values are simply summed up and then put through a transfer process and output. This is the basic building block of all artificial neural networks, although there are many different implementations of this simple block and fundamental differences which allow for different artificial networks to be built.

The neurons are constructed in many different layers. There is an input layer which receives the inputs from the world or user, then there are hidden layers, sometimes many, that are only connected to other layers and not the real world; and finally there is the output layer which sends the results to the world or user. Neurons that are grouped into layers can be connected to other neurons on their layers and to neurons of other layers. When the input layers receives input, it produces an output, which then is the input of the neurons it is connected to, and then they in their turn produce an output to other neurons. This continues until a certain condition is met and then the results are output.

The brain basically learns from prior experience. Artificial neural networks change their connection weights, usually by training, which causes the network to learn the problem to a solution. So when a system learns a new solution, it changes the connection weights to the inputs of some or all of the artificial neurons of the system. Network systems learn this by being put through training, which usually consists of being given inputs and then feedback on how they do on the outputs. The network uses this feedback information to adjust the weights to its neurons to better solve the problem. There are a few good training methods, but the best seems to be by back propagation. In back propagation, feedback is given and then fed back through the layers so that each of the neurons involved may change their weights. This improves performance and proves to be the best form of learning. Neural networks may also be used on-line or off-line. Off-line is a form where the neurons are taught information in a domain and then when in use, they no longer change their weights. This is the most common type of neural network. In the on-line form, the neural networks are taught originally and then continue to learn while in use. This design is much more complicated in design than the off-line form.

Neural networks are performing successfully where other methods do not recognize nor match complicated, vague, or incomplete patterns. Neural networks have been applied in solving a wide variety of problems. One of the most used methods for neural networks is to tell of what will most likely happen. One use is in emergency rooms where it can become so hectic and priorities are sometimes hard to find for humans that the neural network can place priorities and enable a more successful operation in the emergency room. Neural networks are also used in financial institutions where recommendations for financial plans can be acquired. One very important use that the government uses neural networks for is the device called Snoop. Snoop is installed as a bomb detector in some U.S. airports. It uses a neural network that can determine the presence of certain compounds from the chemical configurations of their components. This is a type of recognition system that only a neural network can perform.

Neural networks are important because they can be used in a variety of situations in which other means are not possible. They can be used for prediction analysis and recognition. Not only can they outperform other means, they also can be taught to perform on different input or even taught while performing the tasks they have already learned. In the future, they will be able to teach themselves and to learn infinitely many things. This will allow for a more generalized neural network to be created without all the trial and error processes and it will be able to be applied to any situation and can learn any other situations. This is the main idea behind building computer systems that can learn and have Artificial Intelligence.

Recently, as an example, a new research have determined the complete wiring diagram for the part of the nervous system controlling mating in the male roundworm Caenorhabditis elegance, an animal model intensively studied by scientists worldwide.

The study represents a major contribution to the new field of connectomics, the effort to map the myriad neural connections in a brain, brain region or nervous system to find the specific nerve connections responsible for particular behaviors. A long-term goal of connectomics is to map the human connectome all the nerve connections within the human brain.

The Einstein scientists solved the structure of the male worm's neural mating circuits by developing software that they used to analyze serial electron micrographs that other scientists had taken of the region. They found that male mating requires 144 neurons, nearly half the worm's total number and their paper describes the connections between those 144 neurons and 64 muscles involving some 8,000 synapses. A synapse is the junction at which one neuron (nerve cell) passes an electrical or chemical signal to another neuron.

As we can see that the structure of a network has spatial characteristics that help explain how it exerts neural control over the multi step decision making process involved in mating.

Neural networks take a different approach to problem solving than that of conventional computers. Conventional computers use an algorithmic approach i.e. the computer follows a set of instructions in order to solve a problem. Unless the specific steps that the computer needs to follow are known the computer cannot solve the problem. That restricts the problem solving capability of conventional computers to problems that we already understand and know how to solve. But computers would be so much more useful if they could do things that we don't exactly know how to do.

Neural networks process information in a similar way the human brain does. The network is composed of a large number of highly interconnected processing elements (neurons) working in parallel to solve a specific problem. Neural networks learn by example. They cannot be programmed to perform a specific task. The examples must be selected carefully otherwise useful time is wasted or even worse the network might be functioning incorrectly. The disadvantage is that because the network finds out how to solve the problem by itself, its operation can be unpredictable.

On the other hand, conventional computers use a cognitive approach to problem solving; the way the problem is solved must be known and stated in small unambiguous instructions. These instructions are then converted to a high level language program and then into machine code that the computer can understand. These machines are totally predictable; if anything goes wrong, it is due to a software or hardware fault.

Neural networks and conventional algorithmic computers are not in competition but complement each other. There are tasks are more suited to an algorithmic approach like arithmetic operations and tasks that are more suited to neural networks. Even more, a large number of tasks, require systems that use a combination of the two approaches (normally a conventional computer is used to supervise the neural network) in order to perform at maximum efficiency.

||

Both Neural Net. & Computer Net. are about how components (clients) communicate together.
A Client as user in computer network cannot order server to do something more than its permissions, as such a cell cannot order a cell in brain. cause brain is Administrator and each parts of it are as user with Administrator Privilege. And there is policy! like group policy and local policy & etc. in computer net to set permissions and state, to define important system with some special features and properties.
Like Heart as a pumping system of Oxygen and energy. but cells of skin is not important like heart cause always they are changing. but if there s virus in surface system (like skin) it can effect on all internal network.
like skin concern.
In  Part1 of We are Quantum Computer, you can find some more informatique viewpoint on network in society.

Now check these Scientific explanation & compare with these two essays;

We are Quantum Computer -Part1

We are Quantum Computer -Part2

| Measure – Relativity - Illusion |

What we See & What we Observe!

Description of illusion;

||That the ancients sensed the existence or possibility of optical illusions is evidenced by the fact that they tried to draw and to paint although their inability to observe carefully is indicated by the absence of true shading. The architecture of ancient Greece reveals knowledge of certain optical illusions in the efforts to overcome them. However, the study of optical illusions did not engage the attention of scientists until a comparatively recent period.

Undoubtedly, thoughtful observers of ages ago would have noticed optical illusions, especially those found in architecture and nature. When it is considered that geometrical figures are very commonly of an illusory character it appears improbable that optical illusions could have escaped the keenness of Euclid. The apparent enlargement of the moon near the horizon and the apparent flattened vault of the sky were noticed at least a thousand years ago and literature yields several hundred memoirs on these subjects.

The purpose of visual processing is to take in information about the world around us and make sense of it. Vision involves

the sensing and the interpretation of light. The visual sense organs are the eyes, which convert incoming light energy into electrical signals.

However, this transformation is not  vision in its entirety. Vision also involves the interpretation of the visual stimuli and the processes of perception and ultimately cognition.

The visual system has evolved to acquire veridical information from natural scenes. It succeeds very well for most tasks. However, the information in visible light sources is often ambiguous; and to correctly interpret the properties of many scenes, the visual system must make additional assumptions about the scene and the sources of light. A side effect of these assumptions is that our visual perception cannot always be trusted. Visually perceived imagery can be deceptive or misleading. As a result, there are situations where seeing is not believing, i.e., what is perceived is not necessarily real. These misperceptions are often referred to as illusions.

Physical illusions are those due to the disturbance of light between objects and the eyes, or due to the disturbance of sensory signals of the eyes (also known as physiological illusions). Cognitive illusions are due to misapplied knowledge employed by the brain to interpret or read sensory signals. For cognitive illusions, it is useful to distinguish specific knowledge of objects from general knowledge embodied as rules.

An important characteristic of all illusions is that there must be some means for demonstrating that the perceptual system is somehow making a mistake.

Usually this implies that some aspect of the scene can be measured in a way that is distinct from visual perception (e.g., can be measured by a photometer, a spectrometer, a ruler, etc.). It is important to recognize that these mistakes may actually be useful features of the visual system in other contexts because the same mechanisms underlying an illusion may give rise to a veridical percept for other situations. An illusion is only an illusion if the mistakes are detectable by other means.

The visual system processes information at many levels of sophistication. At the retina, there is low-level vision, including light adaptation and the center-surround receptive fields of ganglion cells. At the other extreme, there is high-level vision, which includes cognitive processes that incorporate knowledge about objects, materials and scenes. In between there is mid-level vision. Mid-level vision is simply an ill-defined region between low and high. The representations and the processing in the middle stages are commonly thought to involve surfaces, contours, grouping and so on. Lightness perception seems to involve all three levels of processing.

The low-level approach to lightness is associated with adaptation and local interactions at a physiological level, as the crucial mechanisms. This approach has long enjoyed popularity because it offers an attractive connection between physiology and psychophysics. The high-level approach is historically associated with the product of unconscious inference. What we perceive is our visual system's best guess as to what is in the world. The guess is based on the raw image data plus our prior experience.

The eye is a fantastic organ being very complex in construction, even though we only need to know about a few of its structures. Light enters the eye through the cornea; a tough transparent tissue covering the front of the eye. It then passes through the pupil—the black hole in the middle of the colored part of the eye (the iris). The lens then focuses the light on the retina, which contains the photoreceptors—light-sensitive cells called rods and cones.

The electro-magnetic energy that we know as light energy is converted by the rods and cones into electro-chemical nerve impulses. This allows the visual information to travel along the fibers of the optic nerve onto the brain.

The next task for the rods and cones is to send the nerve impulses along the optic nerve to the primary visual cortex in the occipital lobes, at the very back of the brain where specialized receptor cells respond as the process of visual perception continues.

We can’t possibly pay attention to all the millions of stimuli that enter the eye at the same time, so we pick out the ones that are important to us and pay attention to those. At this stage of the process, the image is broken up by specialized cells called feature detectors. Feature detectors are cells that individually

respond to lines of a certain length, lines at a certain angle or lines moving in a certain direction.

When visual information reaches the brain (visual cortex), it is reorganized so that we can make sense of it. We do this by using certain visual perceptual principles: perceptual constancies, Gestalt principles, depth and distance cues.

Once the image is reassembled using these principles, it travels along two pathways simultaneously: to the temporal lobe, to identify the object and to the parietal lobe, to judge where the object is in space in relation to our visual field and our selves.

The process whereby the visual stimulus object is given meaning. The temporal lobes identify what the object is by comparing incoming information with information already stored in memory.

The more familiar we are with the observed object, the more likely it is that we will maintain perceptual constancy of it.

Size constancy: This term refers to the fact that we maintain a constant perception of an object’s size even though the size of the image on the retina alters as the object moves nearer to

or further from us.

Shape constancy: An object is perceived to maintain its known shape despite the changing perspective from which it is observed. This is a learnt skill. A toddler may have difficulty perceiving a

familiar toy if it is viewed from an unusual angle.

Depth and distance cues are vital to us. This is because we exist in a three-dimensional world but have only two-dimensional images on our two retinas from which to judge depth and distance.

Optical illusions are legion. They greet the careful observer on every hand. They play a prominent part in our appreciation of the physical world. Sometimes they must be avoided, but often they may be put to work in various arts. Their widespread existence and their forcefulness make visual perception the final judge in decoration, painting, architecture, landscaping, lighting and in other activities. The ultimate limitation of measurements with physical instruments leaves this responsibility to the intellect. The mental being is impressed with things as perceived, not with things as they are. It is believed that this intellectual or judiciary phase which plays such a part in visual perception will be best brought out by examples of various types of static optical illusions coupled with certain facts pertaining to the eye and to the visual process as a whole.

In vision, judgments are quickly made and the process apparently is largely outside of consciousness. Higher and more complex visual judgments pass into still higher and more complex intellectual judgments. All these may appear to be primary, immediate, innate, or instinctive and therefore, certain, but the fruits of studies of the psychology of vision have shown that these visual judgments may be analyzed into simpler elements. Therefore, they are liable to error.

Do you have a fascination with Einstein's theory of relativity? What I mean is, do you find yourself fascinated by the weird predictions of this theory and would you like to get to the bottom of it once and for all? While relativity Is not a light read, pieces of it can be easily understood. This is particularly the case with Special Relativity.

We attempt to explain in an intuitive way, why the time of a rapidly traveling object seems (from your point of view) to slow down. That is, why an object seems to age more slowly when it travels at very high speeds.

Our brains are wired for survival purposes for a 3 dimensional and very slow moving environment. Compared to the speed of light, the everyday objects that our brains perceive and reason about are barely moving at all. Our common sense about how the world works is specialized for dealing with an almost non-moving or static environment (again, that's compared to the speed of light).

What this means, is that what our common sense tells us about our sluggish everyday world is mostly correct but otherwise its judgements cannot be trusted when dealing with extremely fast things.

So when experiments and mathematics tell us things that are contrary to our crude perceptions about how things should work, we find it to be totally bizarre.

Our everyday common sense tells us that if while standing on a moving barge we hit a golf ball off the front, the speed of the barge adds to the speed of the golf ball. If we were to shine a flashlight in the same direction as we had hit the ball we would find that the speed of the barge does not add to the speed of the light beam. Its speed would be the same as if the barge were not moving at all.

In 1905, Einstein explained that this was simply the way that light behaved and that it only seemed strange because our common sense notions of how relative speeds were supposed to add up were only true for very slow moving objects (as compared to the speed of light).

Alternatively, if we know about the physics of water, air and light, we can explain the effect in terms of air blowing across a water surface and producing ripples, which produce a rippling effect. However, since we cannot predict precisely how gusts of air will cause a certain pattern of ripples to be in, say, one hour's time, the "classical" explanation may not be any more accurate than the abstract quantum mechanical description, and if we do not know about the precise behavior of air and water (or do not know whether these are the real cause of what we see), the QM description may be seen as more efficient. Where the interpretative approach scores is in its ability to deal robustly with a wider range of dynamic situations it allows us to immediately imagine the sort of image that should result if we throw a stone at the reflected image: using a quantum description, the calculations might be theoretically possible, but might be unmanageably complex, and it might be difficult to be certain whether or not the calculations had been done correctly and how far they could be trusted, or how their results could be visualized.

 ||

But There is no illusion actually, unless for weak mind…

If you concentrate on illusionary images you can understand what are they?!

There is just visual effect always base on different colors that mixed together to interact and make illusion image on our brain. All of us have experience of illusionary Because always there is new structure presented by artists. But concentrate on an image and look at it several times and zoom on different part of it after few days it becomes like normal image or with less effect on your mind.

And illusionary happens because of holographic structure of our brain. Brain, automatically, tries to combine colors or texts and fix some sketchy parts. So make new image on brain thats because we cannot understand it exactly. 

Also illusionary effect on scientific observations & results. Base on viewpoint of Relativity to observe an object it s important how you observe it!

Which coordinates, which angle, what is your speed, what isyour acceleration, & etc.

Different frame effect on your measurement. So I know what that you cannot even see!

 It s type of illusion for you in my frame. We can define some solutions for it; Be patient!

First try to measure from different frames carefully then collect the results & then talk about it.

(First Think, Then Talk)

Some results of Relativity are not scientific. They are just illusion. Like change in length on high speed & …