The manager as a teacher: selected aspects of stimulation of scientsfsc thinking
Selected aspects of stimulation of scientific thinking. Meta-skills. Methods of critical and creative thinking. Analysis of the decision-making methods without use of numerical values of probability (exemplificative of the investment projects).
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Dynamic processes. Dynamic process is the process of changing functional state/mode/condition of the system. The system is in dynamic process when the change in the number of its actuated SFU occurs. The number of continually actuated SFU would determine stationary state/mode/condition of the system. Hence, dynamic process is the process of the system's transition from one stationary level to another. If the speed of change in external influences exceeds the speed of fixing the preset result of action of the system, transition processes (multi-micro-cycles) occur during which variation of number of functioning SFU also takes place. Therefore, these transition processes are also dynamic. Consequently, there are two types of dynamic processes: when the system is shifting from one stationary condition (level) to another and when it is in transient multi-micro-cycle. The former is target-oriented, whereas the latter is caused by imperfection of systems and is parasitic, as its actions take away additional energy which was intended for target actions. When the system is in stationary condition some definite number of SFU (from zero to all) is actuated. The minimum step of change of level of functional condition is the value determined by the level of operation of one SFU (one quantum of action). Hence, basically transition from one level of functional condition to another is always discrete (quantized) rather than smooth, and this discrecity is determined by the SFU “caliber”. Then umber of stationary conditions is equal to the number of SFU of the system. Systems with considerable quantity of “small” SFU would pass through dynamic processes more smoothly and without strenuous jerks, than systems with small amount of “large” SFU. Hence, dynamic process is characterized by an amplitude of increment of the system's functions from minimum to maximum (the system's minimax; depends on its absolute number of SFU), discrecity or pace of increment of functions (depends on the “caliber” or quantum of individual SFU) and parameters of the function's cyclic recurrence (speed of increase of actions of system, the period of phases of a cycle, etc.). It can be targeted or parasitic. It should be noted that stationary condition is also a process, but it's the steady-state (stationary) process. In such cases the condition of systems does not vary from cycle to cycle. But during each cycle a number of various dynamic processes take place in the system as the system itself consists of subsystems, each of which in turn consists of cycles and processes. The steady-state process keeps system in one and the same functional condition and at one and the same stationary level. In accordance with the above definition, if a system does not change its functional condition, it is in stationary condition. Consequently, the steady-state process and stationary condition mean one the same thing, because irrespective of whether the systems are in stationary condition or in dynamic process, some kind of stationary or dynamic processes may take place in their subsystems. For example, even just a mere reception by the “Õ” receptor is a dynamic process. Hence, there are no absolutely inert (inactive) objects and any object of our World somewise operates in one way or another. It is assumed that the object may be completely “inactive” at zero degrees of Kelvin scale (absolute zero). Attempts to obtain absolutely inactive systems were undertaken by freezing of bodies up to percentage of Kelvin degrees. It's unlikely though, that any attempts to freeze a body to absolute zero would be a success, because the body would still move in space, cross some kind of magnetic, gravitational or electric fields and interact with them. For this reason at present it is probably impossible in principle to get absolutely inert and inactive body. The integral organism represents mosaic of systems which are either in different stationary conditions, or in dynamic processes. One could possibly make an objection that there are no systems in stationary condition in the organism at all, as far as some kind of dynamic processes continually occur in some of its systems. During systole the pressure in the aorta increases and during diastole it goes down, the heart functions continuously and blood continuously flows through the vessels, etc. That is all very true, but evaluation of the system's functions is not made based on its current condition, but the cycles of its activity. Since all processes in any systems are cyclic, including in the organism, the criterion of stationarity is the invariance of integral condition of the system from one cycle to another. Aorta reacts to external influence (stroke/systolic discharge of the left ventricle) in such a way that in process of increase of pressure its walls' tension increases, while it falls in process of pressure reduction. However, take, for example, the longer time period than the one of the cardiocycle, the integrated condition of the aorta would not vary from one cardiocycle to another and remain stationary.
Evaluation of functional state of systems. Evaluation may be qualitative and quantitative. The presence (absence) of any waves on the curve presents quality evaluation, whereas their amplitude or frequency is their quantitative evaluation. For the evaluation of functional condition of any systems comparison of the results of measurements of function parameters to those that should be with the given system is needed. In order to be able to judge about the presence (absence) of pathology, it is not enough to measure just any parameter. For example, we have measured someone's blood pressure and received the value of 190/100 mm Hg. Is it a high pressure or it is not? And what it should be like? To answer these questions it is necessary to compare the obtained result to a standard scale, i.e. to the due value. If the value obtained differs from the appropriate one, it speaks of the presence of pathology, if it does not, then it means there is no pathology. If blood pressure value of an order of 190/100 mm Hg is observed in quiescent state it would speak of pathology, while at the peak maximum load this value would be a norm. Hence, due values depend on the condition in which the given system is. There exist standard scales for the estimation of due values. There exist maximum and minimum due values, due values of quiescence state and peak load values, as well as due curves of functions. Minimum and maximum due values should not always correspond to those of quiescence state or peak load. For example, total peripheral vascular resistance should be maximum in quiescence state and minimum when loaded. Modern medicine makes extensive use of these kinds of due values, but is almost unfamiliar with the concept of due curves. Due value is what may be observed in most normal and healthy individuals with account taken of affiliation of a subject to certain standard group of alike subjects. If all have such-and-such value and normally exist in the given conditions, then in order for such subject to be also able to exist normally in the same conditions, he/she should be characterized by the same value. For this purpose statistical standard scales are applied which are derived by extensive detailed statistical research in specific groups of subjects. These are so-called statistical mathematical models. They show what parameters should be present in the given group of subjects. However, the use of standard tables is a primitive way of evaluation of systems' functions. First, they provide due values characterizing only a group of healthy individuals rather than the given concrete subject. Secondly, we already know that systems at each moment of time are in one of their functional states and it depends on external influences. For example, when the system is in quiescence state it is at its lowest level of functional condition, while being at peak load it is at its highest level. What do these tables suggest then? They probably suggest due values for the systems of organism in quiescence state or at their peak load condition. But, after all, the problems of patients are not those associated with their status in quiescence state, and the level of their daily normal (routine) load is not their maximum load. For normal evaluation of the functional condition of the patient's organism it is necessary to use not tabular data of due values, but due curves of functions of the body systems which nowadays are almost not applied. Coincidence or non-coincidence of actual curves of the body systems' functions with due curves would be a criterion of their sufficiency or insufficiency. Hence, application of standard tables is insufficient and does not meet the requirements of adequate diagnostics. Application of due curves is more of informative character (see below). Statistical mathematical models do not provide such accuracy, howsoever exact we measure parameters. They show what values of parameters should be in a certain group of subjects alike in terms of certain properties, for example, males aged 20-30 years, of 165-175 cm height, smokers or non-smokers, married or single, paleface, yellow- or black-skinned, etc. Statistical models are much simpler than those determined, but less exact though, since in relation to the given subject we can only know something with certain degree (e.g. 80%) of probability. Statistical models apply when we do not know all elements of the system and laws of their interaction. Then we hunt for similar systems on the basis of significant features, we somewise measure the results of action of all these systems operating in similar conditions (clinical tests) and calculate mean value of the result of action. Having assumed that the given subject closely approximates the others, because otherwise he/she would not be similar to them, we say: “Once these (people) have such-and-such parameters of the given system in such-and-such conditions and they live without any problems, then he/she should have these same parameters if he/she is in the same conditions”. However, a subject's living conditions do always vary. Change or failure to account even one significant parameter can change considerably the results of statistical researches, and this is a serious drawback of statistical mathematical models. Moreover, statistical models often do not reveal the essence of pathological process at all. The functional residual capacity (FRC) of lungs shows volume of lungs in the end of normal exhalation and is a certain indicator of the number of functional units of ventilation (FUV). Hence, the increase in FRC indicates the increase in the number FUV? But in patients with pulmonary emphysema FRC is considerably oversized. All right then, does this mean that the number of FUV in such patients is increased? It is nonsense, as we know that due to emphysema destruction of FUV occurs! And in patients with insufficiency of pumping function of left ventricle reduction of FRC is observed. Does this mean that the number of FUV is reduced in such patients? It is impossible to give definite answer to these questions without the knowledge of the dynamics of external respiration system function and pulmonary blood circulation. Hence, the major drawback of statistical models consists in that sufficiently reliable results of researches can be obtained only in the event that all significant conditions defining the given group of subjects are strictly observed. Alteration or addition of one or several significant conditions of research, for example, stature/height, sex, weight, the colour of eyes, open window during sleep, place of residence, etc., may alter very much the final result by adding a new group of subjects. As a result, if we wish to know, e.g. vital capacity of lungs in the inhabitants of New York we must conduct research among the inhabitants of New York rather than the inhabitants of Moscow, Paris or Beijing, and these data may not apply, for example, to the inhabitants of Rio de Janeiro. Moreover, standards/norms may differ in the inhabitants of different areas of New York depending on national/ethnic/ identity, environmental pollution in these areas, social level and etc. Surely, one may investigate all conceivable variety of groups of subjects and develop specifications/standards, for example, for males aged from... to..., smokers or non-smokers of cigars (tobacco pipes, cigarettes or cigarettes with cardboard holder) with high (low) concentration of nicotine, aboriginals (emigrants), white, dark- or yellow-skinned, etc. It would require enormous efforts and still would not be justified, since the world is continually changing and one would have to do this work every time again. It's all the more so impossible to develop statistical specifications/standards for infinite number of groups of subjects in the course of dynamic processes, for example, physical activities and at different phases of pathological processes, etc., when the number of values of each separate parameter is quite large. When the system's details are completely uncertain, although the variants of the system's reaction and their probabilistic weighting factors are known, statistical mathematical model of system arises. Inaccuracy of these models is of fundamental character and is stipulated by probabilistic character of functions. In process of studying of the system details of its structure become apparent. As a result an empirical model emerges in the form of a formula. The degree of accuracy of this model is higher than that of statistical, but it is still of probabilistic character. When all details of the system are known and the mechanism of its operation is entirely exposed the deterministic mathematical model appears in the form of the formula. Its accuracy is only stipulated by the accuracy of measurement methods. Application of statistical mathematical models is justified at the first stages of any cognition process when details of phenomenon in question are unknown. At this stage of cognition a “black box” concept is introduced when we know nothing about the structure of this “box”, but we do know its reaction to certain influences. Types of its reactions are revealed by means of statistical models and thereafter, with the help of logic, details of its systems and their interaction are becoming exposed. When all that is revealed, deterministic models come into play and the evaluation of the systems' functions is made not on the basis of tabular data, but on the basis of due curve of the system function. Due curve of a system's function is a due range of values of function of the given concrete system in the given concrete subject, with its load varying from minimum to maximum. Nowadays due curves are scarcely used, instead extreme minimum and maximum due values are applied. For example, due ventilation of lungs in quiescence state and in the state of peak load. For this purpose maximum load is given to individuals in homotypic groups and pulmonary ventilation in quiescence state and in the state of peak load is measured. Following statistical processing due values of pulmonary ventilation for the conditions of rest and peak load are obtained. The drawback of extreme due values consists in that this method is of little use for the patients. Not all patients are able to normally perform a stress test and discontinue it long before due maximum value is achieved. The patient, for example, could have shown due pulmonary ventilation, but he/she just stopped the load test too early. How can the function be estimated then? It can be only done by means of due curve. If the actual curve coincides with the due curve, the function is normal at the site where coincidence occurred. If actual curve is lower than the due one, it is a lagging curve. Inclined straight line consisting of vertical pieces of line is the due curve. Vertical dotted straight line is the boundary of transition of normal or lagging function into the inadequate line (a plateau). The drawback of due curves is that in order to build them it is necessary to use deterministic mathematical models of systems which number is currently very low. They are built on the basis of knowledge of cause-and-effect relationship between the system elements. These models are the most complex, labor-consuming and for the time being are in many cases impracticable. Therefore, these models are scarcely used in the sphere of applied medicine and this is the reason for the absence of analytical medicine. But they are the most accurate and show what parameters should be present in the given concrete subject at any point of time. Only the use of due curve functions allows for evaluating actual curves properly. The difference of the deterministic mathematical models from statistical tables consists in that in the first case due values for the concrete given subject (the individual's due values) are obtained, while in the second case due values for the group of persons alike the given subject are developed. The possibility of building deterministic models depends only on the extent of our knowledge of executive elements of the system and laws of their interaction. Calculation of probability of a thrown stone hitting a designated target can be drawn as an example of statistical standard scale in the mechanic. After a series of throws, having made certain statistical calculations it is possible to predict that the next throw with such degree of probability will hit the mark. If deterministic mathematical model (ballistics) is used for this purpose, then knowing the stone weight, the force and the angle of throw, viscosity of air, speed and direction of wind, etc., it is possible to calculate and predict precisely the place where a stone will fall. “Give me a spot of support and I will up-end the globe”, said Archimedes, having in view that he had deterministic mathematical model of mechanics of movements. Any living organism is a very complex and multi-component system. It's impossible to account all parameters and their interrelations, therefore statistical mathematical models cannot describe adequately the condition of systems of organism. However, joint use of statistical and deterministic models allows, with sufficient degree of accuracy, to evaluate parameters of living system. In the lapse of time in process of accumulation of knowledge statistical models are replaced by deterministic. Engineering/technology is much simpler than biology and medicine because the objects of its knowledge are rather simple systems (machinery/vehicles) constructed by a man. Therefore, its development and process of replacement of statistical mathematical models for deterministic ones has made great strides as compared with medicine. Nevertheless, on the front line of any science including technical, where there is still no clarity about many things and still a lot has to be learnt, statistics stands its ground as it helps to reveal elements of systems and laws of their interaction. What do we examine the subject and conduct estimation of functions of the systems of his organism for? Do we do it in order to know to which extent he/she differs from the homothetic subject? Probably, yes. But, perhaps, the main objective of examination of a patient is to determine whether he/she can normally exist without medical aid and if not, what kind of help might be provided. Pathological process is a process of destruction of some SFU of the organism's systems in which one of the key roles is played by a vicious circle. However, vicious circles start to actuate only if certain degree of load is present. They do not emerge below this level and do not destroy SFU, i.e. no pathological process emerges and no illness occurs below a certain threshold of loading (mechanical, thermal, toxic, etc.). Hence, having defined a threshold of the onset of the existence of vicious circle, we can learn the upper “ceiling” of quality of life of the given patient. If his/her living conditions (tempo of life) allow him/her not to exceed this “ceiling”, it suggests that the given subject will not be in poor health under these conditions. If the tempo of life requires more than the capacity of his/her organism may provide, he/she will be in poor health. In order not to be ill he/she should stint himself/herself in some actions. To limit oneself in actions means to reduce one's living standard, to deprive oneself of the possibility to undertake certain actions which others can do or which he/she did earlier, but which are now inaccessible to the given patient on the grounds of restricted resources of his/her organism because of defects. If these restrictions have to do only with pleasure/delight, such as, for example, playing football, this may be somehow sustained. But if these restrictions have to do with conditions of life of the patient it has to be somehow taken into account. For example, if his/her apartment is located on the ground floor, then to provide for quite normal way of life his/her maximum consumption of Î2 should be, e.g., 1000 ml a minute. But what one should do if he/she lives, e.g., on the third floor and in the house with no elevator, and to be able to get to the third floor on foot he/she should be able to take up 2000 ml/min Î2, while he/she is able to uptake take up only 1000 ml/min Î2,? The patient would then have a problem which can be solved only by means of some kind of health care actions or by changing conditions of life. In clinical practice we almost do not assess the patient's functional condition from the stand point of its correspondence to living conditions. Of course, it is trivial and we guess it, but for the time being there are no objective criteria and corresponding methodology for the evaluation of conformity of the functional reserves of the patient's organism with the conditions of his/her life activity. Ergonomics is impossible without systemic analysis. Major criterion of sufficiency of the organism's functions in the given conditions of life is the absence of the occurrence of vicious circles (see below) at the given level of routine existential loads. If vicious circles arise in the given conditions, it is necessary either to somehow strengthen the function of the organism's systems or the patient will have to change his/her living conditions so that vicious circles do not work, or otherwise he/she will always be in poor health with all the ensuing consequences. So, we need not only to know due minimum or maximum values which we may obtain using statistical mathematical models. We also need to know the patient's everyday due values of the same parameters specific for the given concrete patient so that his/her living conditions do not cause the development of pathological processes and destroy his/her organism. To this effect we need deterministic mathematical models.
Stabilization systems and proportional systems. There exist a great number of types of various systems. But stabilization systems and proportional systems are of special importance for us. In respect of the first one the result of action always remains the same (stable), it does not depend on the force of external influence, but on the command. For example, ðÍ of blood should be always equal to 7.4, blood pressure to 120/80 mm Hg, etc., (homeostasis systems) regardless of external influences. In respect of the second one the result of action depends on the force of external influence under any specific law designated by the command and is proportional to it. For example, the more physical work we perform the more Î2 we should consume and excrete ÑÎ2. Stabilization system uses two receptors, “Õ” and “Y”. The “Õ” receptor is used to start up the system depending on the presence of external influence, while the “Y” receptor is used for the measurement of the result of action. The command (the task specifying the value of the result of action) is entered to the command entry point of the stabilization system's control block. Stabilization system should fulfill this task, i.e. support (stabilize) the result of action at the designated level irrespective of the force of external influence. Stability of the result of action is ensured by that the “database” of the control block contains the ratios/correlations of the number of active SFU and forces of external influence and is sustained according to the NF logic: if the result of action has increased, it is necessary to reduce it, and if it has decreased it's necessary to increase it. For this purpose the control block should contain DPC and NF. Hence, the elementary control block (DPC) is not suitable for stabilization systems. At least simple control block which contains NF as well is necessary. In stabilization system the result of action of the system up to vertical dotted straight line is stable (normal function, the curve goes horizontally). Beyond the dotted straight line the function goes down (increases), stabilization was disturbed (insufficiency of function). With proportional system, its function increases (goes down) until vertical dotted straight line proportionally to the external influence (normal function). Beyond the dotted straight line the function does not vary (it entered the saturation phase, transited to a plateau condition - insufficient function). The measuring element in stabilization system continually measures the result of action of the system and communicates it to the control block which compares it to the preset result. In case of discrepancy of the result of action with the task this block makes decision on those or other actions to be taken and forces the executive elements to operate so that this divergence has disappeared. External influence may vary within various ranges, but the result of action should remain stable and be equal to the preset result. The system spends its resources to do it. If the resources are exhausted, stabilization system ceases to stabilize the result of action and starting from this point the onset of its insufficiency occurs. One of stabilization examples is stellar rotation speed in vacuum. If the radius of the star reduces, its rotational speed will increase and centrifugal forces will amplify, thus scaling up its radius and slowing down its rotational speed. If the radius of the star scales up, the entire process will go in a reverse order. A figure skater regulates the speed of rotational pirouettes he/she performs on the skating-rink based on the same principle. Proportional system should also use both “Õ” and “Y” receptors. One of them measures the incoming influence, while another one measures the result of action of the system. The command (the task as to what the proportion between external influence and the result of action should be) is input to the entry point of the control block. It is for this reason that such systems are called proportional. External influence may change within the varying range. But the control block should adjust the performance of the executive elements so that the “prescribed” (preset by the directive) proportion between external influence and the result of action is maintained. Examples of proportional systems are, for example, amplifiers of electric signals, mechanical levers, sea currents (the more the water in the ocean is warmed up, the more intensive is the flow in the Gulf Stream), atmospheric phenomena, etc. So, the examples of stabilization and proportional systems are found in any medium, but not only in biological systems.
Active and passive systems. Passive systems are those which do not exspend energy for their actions. Active systems are those which do exspend energy for their actions. However, as it was repeatedly underlined, any action of any system requires expenditure of energy. Any action, even the most insignificant, is impossible without expenditure of energy, because, as it has already been mentioned, any action is always the interaction between systems or its elements. Any interaction represents communication between the systems or their elements which requires expenditure of energy for the creation thereof. Therefore any action requires energy consumption. Hence, all systems, including passive, consume energy. The difference between active and passive systems is only in the source of energy. How does the passive system operate then? If the system is in the state of equilibrium with the environment and no influence is exerted upon it the system should not perform any actions. Once it does not perform any actions, it does not consume energy. It is passive until the moment it starts to operate and only then it will start to consume energy. The balanced state of a pencil is stipulated by the balanced pushing (pressure) of springs onto a pencil. The springs are not simply incidental groups of elements (a set of atoms and molecules), but they are passive systems with NF loops and executive elements at molecular level (intermolecular forces in steel springs) which seek to balance forces of intermolecular connections/bonds which is manifested in the form of tension load of the springs. Since in case of the absence of external influence no actions are performed by the system, there is no energy consumption either, and the system passively waits for the onset of external influence. Both types of systems have one and the same goal: to keep a pencil in vertical position. In passive systems this function is carried out by springs (passive SFU, A and B) and air columns encapsulated/encased in rubber cans (passive SFU, D). The SFU store (use) energy during external influence (pushing a pencil with a finger squeezes the springs). In active system (C) the same function is achieved for at the expense of airflows which always collapse. These airflows create motor fans (active SFU) which spend energy earlier reserved, for example, in accumulators. Once these airflows are encapsulated/encased in rubber cylinders they will not collapse any more and will exist irrespective of fans, while carrying out the same function. But now it represents a passive system (D). Now external influence occurs and the pencil has diverged aside. The springs would immediately seek to return a pencil to the former position, i.e. the system starts to operate. Where does it take energy for the actions from? This energy was brought by the external influence in the form of kinetic energy of pushing by a finger which has compressed (stretched) the springs and they have reserved this energy in the form of potential energy of compression (stretching). As soon as external influence (pushing by a finger) has ceased, potential energy of the compressed springs turns to kinetic energy of straightening thereof and it returns a pencil back in the vertical balanced position. External influence enhances internal energy of the system which is used for the performance of the system. The influence causes surplus of internal energy of the system which results in the reciprocal action of the system. In the absence of influence no surplus of the system's internal energy is available which results in the absence of action. External influence brings in the energy in the system which is used to produce reaction to this influence. Functions of springs may be performed by airflows created by fans located on a pencil. In order to “build” airflows surplus of energy of the “fans - pencil” system is used which is also brought in from the outside, but stored for use at the right time (for example, gasoline in the tank or electricity in accumulator). Such system would be active because it will use its internal energy, rather than that of external influence. The difference between airflows and springs consists in that the airflows consist of incidental groups of molecules of air (not systems) moving in one direction. Amongst these elements there are executive elements (SFU, air molecules), but there is no control block which could construct a springs-type system out of them, i.e. provide the existence of airflows as stable, separate and independent bodies (systems). These airflows are continually created by fan propellers and as they have no control block of their own they always collapse by themselves. Suppose that we construct some kind of a system which will ensure prevention of the airflows from collapse, let's say, encase them in rubber cylinders, they then may exist independently of fans. But in this case the system of stabilization of the pencil's vertical position will shift from the active category to the passive. Hence, both active and passive systems consume energy. However, the passive ones consume the external energy brought in by external influence, while the active ones would use their own internal energy. One may argue that internal energy, say, of myocyte is still the external energy brought in to a cell from the outside, e.g. in the form of glucose. It is true, and moreover, any object contains internal energy which at some stage was external. And we probably may even know the source of this energy, which is the energy of the Big Bang. Some kind of energy was spent once and somewhere for the creation of an atom, and this energy may be extracted therefrom somehow or other. Such brought-in internal energy is present in any object of our World and it is impossible to find any other object in it which would contain exclusively its own internal energy which was not brought in by anything or ever from the outside. Energy exchange occurs every time the systems interact. But passive systems do not spend their internal energy in the process of their performance because they “are not able” of doing it, they only use the energy of the external influence, whereas active systems can spend their internal energy. The passive system is the thorax which performs passive exhalation and many other systems of living organism.
Evolution of systems. Complex control block. For the most efficient achievement of the goal the system always should carry out its action in the optimum way and produce the result of action in the right place and time. The system's control block solves both problems: where and when it is necessary to actuate. In order to be able to operate at the right place it should have a notion of space and the corresponding sensors delivering information on the situation in the given space. In turn, the time of delivery of the result of action with simple systems includes two periods: the time spent for decision-making (from the moment of onset of external influence till the moment of SFU activation) and the time spent for the SFU actuation (from the moment of the beginning of SFU activation till the moment the result of action is achieved). The time spent for the decision-making depends on duration of cycles of the system's performance which issue was discussed above. The time spent for the SFU actuation depends on the SFU properties such as, for example, the speed of biochemical reactions in live cells or the speed of reduction of sarcomere in muscular cells which to a considerable degree depends on the speed of power consumption by these SFU and the speed of restoration of energy potential after these SFU have been actuated. These speeds are basically the characteristics inherent in SFU, but are also determined by service systems which serve these SFU. They may also be controlled by control block. Metabolic, hormonal, prostaglandin and vegetative neural regulation in living organism is intended just for this purpose, i.e. to change to some extent the speeds of biochemical reactions in tissue cells and conditions of delivery of energy resources by means of regulation of (service) respiratory and blood circulation systems. But the notion of “at the right time” means not only the time of actuation in response to the external influence. In many cases there is a need for the actuation to start before external influence is exerted. However, the system with simple control block starts to perform only after the onset of external influence. It is a very significant (catastrophic) drawback for living systems, because if the organism is being influenced upon, it may mean that it is already being eaten. It would be better if the system started to perform before the onset of this external influence. If the external situation is threatening by the onset of dangerous influence, the optimal actions of the system may protect it from such influence. For this purpose it is necessary to know the condition of external situation and to be able to see, estimate and know what actions need to be undertaken in certain cases. In other words, it is necessary to exercise control in order to forestall real result of action prior to external influence. In order to perform these actions it should contain special elements which can do it and which it does not have. Simple control block can exercise control only on the basis of mismatch (divergence/discrepancy) of real result of action with the preset one, because the system with simple control block cannot “know” anything about external situation until the moment this situation starts to influence upon the system. The knowledge of external situation is inaccessible to simple control block. Therefore, simple control block always starts to perform with delay. It may be sometimes too late to control. If the system (the living organism) does not know the external situation, it may not be able to make projection as to what the situation is and catch the victim or forestall encounter with a predator. Thus, simple control block cannot make decisions on the time and place of actuation. For this purpose control block needs a special analyzer which can determine and analyze external situation and depending on various external or internal conditions elaborate the decision on its actions. This analyzer should have a notion of time and space in which certain situation is deployed, as well as corresponding informants (sensors with communication lines between them and this special analyzer) which provide information on the external situation. The analyzer-informant has nothing of this kind. When the hunter shoots at a flying duck, it shoots not directly at the bird, but he shoots with anticipation as he knows that before the bullet reaches a duck it (the duck) will move forward. The hunter, being a system intended for shooting a duck, should see the entire situation at a distance, estimate it correctly, make the projection as to whether it makes sense to shoot, and he should act, i.e. shoot at a duck, only on the basis of such analysis. He cannot wait until the duck touches him (until his “X” is actuated) so that he then can shoot at it. In order to do so he should first single out a duck as the object he needs from other unnecessary objects, then measure a distance to a duck, even if it would be “by eye”. He does it by means of special (visual) analyzer which is neither “X” nor “Y” sensor, but is an additional “C” sensor (additional special remote receptors with afferent paths). Such receptors can be any receptors which are able of receiving information at a distance (haemo-, termo-, photoreceptors, etc). The hunter's visual analyzer includes photosensitive rods and cone cells in the eye (photoreceptors), optic nerves and various cerebral structures. He should be able to distinguish all surrounding subjects, classify them and single out a duck against the background of these subjects and locate a duck (situational evaluation). In addition, by means of reciprocal innervation he should position his body in such a way that the gun is directed precisely to the place in front of the duck (forestalling/ anticipation) to achieve the goal, i.e. to hit the duck. He does all this by means of his additional analyzer which is the analyzer-classifier. Simple control block of systems with NF does not contain such additional analyzer-classifier. That is why it is called “simple”. It has only analyzer-informant which feels external influence by means of “X” sensor only when this influence has already begun; it measures the result of action by means of NF (“Y” sensor) only when this result is already evident and analyzes the information received after the result of action is already produced, because it takes time for the NF to activate. In addition, the analyzer-informant contains only “database” in which the table of due values of controllable parameters (data) which need to be compared to the data of measurements of external influence and results of action “is written down” in explicit or implicit form. It elaborates decisions on the basis of these comparisons. Its algorithm of control is based only on the comparison of the given measurements carried out by “X” and “Y” with the “database”. If the mismatch is equal to “M” it is necessary to perform, for example, less action, whereas if it is equal to “N”, then more action should be done. Simple control block cannot change the decision as to the alteration of the level of controllable parameter, time of actuation and the NF intensity, since it does not have appropriate information. To perform these actions it should contain special elements which can provide it with such information. What does it need for this purpose? In order to make a decision the given block should “know” the situation around the system which can cause certain external influence. For this purpose it should first of all “see” it, i.e. have sensors which can receive information at a distance and without direct contact (remote “C” informant). In addition, it should contain a special analyzer-classifier which can classify external environment and single out from it not all the objects and situations, but those only which may affect the implementation of its goals. Besides, it should have notions of space and time. The play of fish and even dolphin shoals in the vicinity of floating combatant ship cannot affect its movement to target destination. But the “game” of the enemy submarine in its vicinity may substantially affect the fulfillment of its task. The combatant ship should be able to “see” all its surroundings and, based on the external situation, single out from all possible situations only those that may create such external influences which can prevent it from the implementation of its objective. For this purpose it should “know” possible situational scenarios which may affect the achievement of the goal of the given system. To this effect it should have “knowledge base” containing the description of all those situations which can affect the implementation of the objective. If its “knowledge base” does not have the description of certain objects or situations it cannot distinguish (classify) an object or a situation and can not make correct decision. The “knowledge base” should store information not on the parameters of external influence which are stored in the “database”, but on the situations around (beyond) the system which may lead to specific external influence. The “knowledge base” may be introduced in the control block at the moment of its “birth” or later together with the command, at that it is being introduced in the given block by the systems external in relation to the given system. If its “knowledge base” does not contain the description of the given situation, it can not distinguish and classify it. The “knowledge base” contains the description of various situations and the significance of these situations for the system. Knowing the importance of real situation for the achievement of the goal the system can make projection and take decision on its actions depending on the projection made. In addition to the “knowledge base” it should have “decision base”- a set of ready/stored/ decisions that are made by the control block depending on the situation and the projection, (authorized decisions, instructions) in which appropriate decisions are stored that need to be made in respective situations. If it does not have ready decisions regarding external situation it cannot perform its objective. Having identified a situation and elaborated the decision, it gives a command to the analyzer-informant which activates a stimulator in an appropriate way. Thus, the control block is being complexificated on account of inclusion in its structure of the “C” informant and the analyzer-classifier containing the “knowledge base” and the “base of decisions”. That is why such control blocks are called “complex”. The more complex the decision-making block is, the more precise decision may be chosen. Consequently, complex control block includes both the analyzer-informant which has “database
and the analyzer-classifier which has the “knowledge base” and the “decision base”. Not any living cell has analyzer - classifier. Animate/organic/ nature is classified under two major groups: flora and fauna. Plants, as well as many other living forms of animate nature, such as corals and bacteria, do not possess remote sensors, although in some cases it may seem that plants, nevertheless, do have such sensors. For example, sunflowers turn their heads towards the sun as if phototaxis is inherent in them. But they actually turn their heads not towards the light, but towards the side wherefrom their bodies get more heated, and heat comes from the side wherefrom the light comes. Heat is felt locally by a sunflower's body. It does not have special infra-red sensors. Photosynthesis process is not a process of phototaxis. Hence, plants are systems with simple control block. In spite of the fact that there are plants with a very complex structure that are even capable to feed on subjects of fauna, their control block is still simple and reacts only to direct contact. For example, a sundew feeds on insects; it can entice them, paste them to its external stomach and even contract its valves. It's a predator and in this sense it is akin to a wolf, a shark or a jellyfish. It can do variety of actions like an animal, but it can only do it after the insect alights on it. A sundew cannot chase its victims because it does not see them (remote sensors are not available). Whatever alights on it, even a small stone, it will do all necessary actions and try to digest it because it does not have analyzer-classifier. This is why a sundew is a plant, but not an animal. Animate cells, including unicellular forms, even such as amoeba or infusoria types, are systems with complex control blocks since they possess at least one of spatial analyzers - chemotaxis. It is the presence of remote sensors that differs a cell of an animal from any objects of flora, in which such sensors controls are not present. Therefore the control block is a determinant of what kind of nature the given living object belongs to. The jellyfish is not an alga, but an animal because it has chemotaxis. Remote analyzer gives an idea about the space in which it has to move. That is why plants stay put, while animals move in space. Simple control block including only the analyzer-informant is a determinant of the world of minerals and plants. We will see below where the difference between the mineral and vegetative worlds/natures lies. Complex control block including the analyzer-classifier is a fauna determinant anyway. An amoeba is the same kind of hunter as a wolf, a shark or a man. It feeds on infusorians. To catch an infusorian it should know where the latter is and should be able to move. It cannot see the victim at a distance, but it can feel it by its chemical sense organs and seek to catch it as it has chemotaxis, possibly the first of the remote sensor mechanisms. But in addition to chemotaxis the amoeba should also have a notion (even primitive) of space in which it exists and in which it should move in a coordinated and task-oriented manner to catch an infusorian. In addition, it should be able to single out an infusorian from other objects which it can encounter on its way. Its analyzer-classifier is much simpler than, for example, that of a wolf or a shark because it does not have organs of sight and hearing and neural structures at all, but it can classify external situation. It has complex control block comprising the “C” informant, and that is why an amoeba is not a plant, but an animal. Since control blocks may be of any degree of complexity, reflexes may be of any degree of complexity, too, from elementary axon reflexes to the reflexes including the cerebral cortex performance (instincts and conditioned reflexes). The number of reflexes of living organism is enormous and there exist specific reflexes for each system of the organism. Moreover, the organism is not only a complex system in itself, but due to its complexity it has a possibility to build additional, temporary/transient/ systems necessary at the given point of time for some specific concrete occasion. For example, lamentation system is a temporary system which the organism builds for a short time interval. The lamentation system's control block is the example of complex control block. The purpose of lamentation is to show one's suffering and be pitied. This system includes, in the capacity of composite executive elements, other systems (subsystems) that are located sufficiently far from each other both in space and in terms of functions (lacrimal glands, respiratory muscles, alveoli and pulmonary bronchial tubes, vocal chords, mimic muscles, etc.). At first the external situation is identified and in case of need lamentation reflex (complex reflex, an instinct) is actuated under the certain program, which includes control of lifting up one's voice up to a certain timbre (control over the respiratory muscles and vocal chords), sobbing (a series of intermittent sighs), lacrimation /excretion of tears/, specific facial expression, etc. All these remote elements are consolidated by the complex control block in a uniform system, i.e. lamentation system, with very concrete and specific purpose to show one's sufferings to the other system. The lamentation reflex can be realized at all levels of nervous system, starting from the higher central cerebral structures, including vegetative neural system, subcortex and up to cerebral cortex. But we are examining only child's weeping which is realized in neural structures not higher than subcortex level (instinctive crying). After the purpose has been achieved (sufferings have been explicitly demonstrated, and whether or not the child was pitied will be found out later) the reflex is brought to a stop, this complex control block disappears and the system disintegrates into the components which now continue functioning as part of other systems of organism. Lamentation system disappears (it is scattered). Whence the control block (at subcortex level) knows that it is necessary to cry now, but it is not necessary to cry at any other moment? For this purpose it identifies a situation (singles it out and classifies). The analyzer-classifier is engaged in it. Its “knowledge base” is laid down in subcortex from birth (the instincts). Simple control block cannot perform such actions. All actions of the systems controlled by elementary and simple control blocks would be automatic. Biological analogues of elementary control block are the axon reflexes working under the “all-or-none” law; those of simple control blocks are unconditional (innate, instinctive) reflexes when certain automatic, but graduated reaction occurs in response to certain external influence. Simple control block would be adapting the system's actions better than the elementary one because it takes account of not only external influence, but the result of action of the system which has occurred in response to this external influence as well. But it cannot identify a situation. Complex control block can perform such actions. It reacts not to external influence, but to certain external situation which can exert certain external influence. Biological analogues of complex control block are complex reflexes or instincts. During pre-natal development the “knowledge” of possible situations “is laid down” into the brain of a fetus (the “knowledge base”). The volume of this knowledge is immense. A chicken can run immediately after it hardly hatches from egg. A crocodile, a shark or a snake become predators right after birth, i.e. they know and are able of doing everything that is required for this purpose. It speaks of the fact that they have sufficient inborn “knowledge base” and “base of decisions” for this purpose. In such cases we say that animal has instincts. Thus, the system with complex control block is the object which can react to certain external situation in which this influence may be exerted. But it can react only to fixed (finite) number of external situations which description is contained in its “knowledge base” and it has a finite number of decisions on these situations which description is contained in its “base of decisions”. In order to identify external situation it has the “C” informant and the analyzer-classifier. In other respects it is similar to the system with simple control block. It can also react to certain external influence and its reaction is stipulated by type and number of its SFU. The result of action of the system is also graduated. The number of gradations is defined by the number of executive SFU in the system. It also has the analyzer-informant with the “database”, DPC (the “X” informant) and NF (the “Y” informant), which control the system through the stimulator (efferent paths). There are no analogues with complex control block in inorganic /abiocoen, inanimate/ nature. Biological analogues of systems with complex control block are all animals, from separate cells to animals with highly developed nervous system including cerebrum and remote sense organs, such as sight, hearing, sense of smell, but in which it is impossible to develop reflexes to new situations, for example, in insects. The analogues of the “C” informant are all “remote” receptors: eyesight (or its photosensitive analogues in inferior animals), hearing and sense of smell. The analogues of analyzer-classifier are, for example, visual, acoustical, gustatory and olfactory analyzers located in the subcortex. Visual, acoustical, gustatory and olfactory analyzers located in the cerebral cortex are anyway referred to analyzers-correlators.
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