The Problem of Defining Life

Scientific theory states that one of the most important tasks of science, and scientists, is the task of definition. Thus it becomes absolutely necessary to define the phenomenon known as life . Very few terms which are used so frequently have been defined in such an unsatisfactory manner. The paradox is that the more we know about life, the more difficult it becomes to define it satisfactorily. There is still no clear definition of the term life which is accepted by all the scientists studying this phenomenon (Cleland and Chyba, 2002). 

Various definitions have been proposed, and, depending on one s scientific standpoint, a suitable one may be available. Several of these definitions will be presented below. A completely satisfactory answer will, however, probably only be found when more detailed results on the origin of life become available. 

Self-reproduction without this process, information would be lost after every generation. 

Mutation without it, information would be invariant—and thus no development of the species would be possible. 

Metabolism without this, a living system would reach an equilibrium state, from which, again, no development would be possible. 

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The calculation of the fire s outcome in the third step includes the distribution of heat, smoke, and toxic gases throughout the building of concern. It allows the introduction of people into that building and monitors their movement in response to the fire. They may escape safely or fail to escape due to heat or the inhalation of toxic smoke. The benefits of changing some component of the defined fire problem is observed in the change in the number of deaths predicted, rather than by direct comparison of the toxic potencies of the different smokes. This mirrors the complexity of real-life fires. 

In all previous subsections the problem of detennining the parameters characteristic of a population of data or of a sample of data has been addressed with the use of a bell shaped distribution or normal distribution. Not always experimental data are effectively distributed in a symmetrical fashion. This, for instance, is the case of fatigue life at stress amplitudes close to fatigue Umit. A more general distribution function was introduced in 1939 by a Swedish engineer and researcher Weibull [7]. His probability density function in its simplest form (two parameters function) is defined as... 

The mathematical model can only be an approximation of real-life processes, which are often extremely complex and often only partially understood. Thus models are themselves neither good nor bad but, as pointed out by Kapur, will either give a good fit or a bad fit to actual process behaviour. Similarly, it is possible to develop several different models for the same process, and these will all differ in some respect in the nature of their predictions. Indeed it is often desirable to try to approach the solution of a given problem from as many different directions as possible, in order to obtain an overall improved description. The purpose of the model also needs to be very clearly defined, since different models of a process, each of which has been developed with a particular purpose in mind, may not satisfy a different aim for which the model was not specifically constructed. 

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