Emergent behaviour

The situation with which we are faced in chemistry...seems to offer the most plausible example of emergent behaviour (17). 

In post-Newtonian research, both analysis and synthesis are thus essential in order to complete a circle of research with any possibility of enhancing our understanding of a complex system. This is illustrated in Fig. 2, which shows the circle of research in the understanding of the emergent behaviour of a complex system such as an aeroplane. We can study in great depth the components of this complex system, revealing vast amounts of information... 

The model of a molecule derived from the circle of research (Fig. 4) must be critically evaluated as to whether it contains the information associated with the emergent behaviour of the molecule. In other words, the question must be asked whether information from the atom level exceeds the logical depth necessary to understand the emergent properties of molecules as they relate to drug research (Kier and Hall, 1992). 

The prototype of complexity and emergent behaviour (within our realm of interest and circles of research) is liquid water. Short-range order and local... 

A dynamic simulation uses the ingredients dissected from a complex system to attempt the construction of a model which exhibits dynamic attributes, i.e. emergent behaviour. Such a simulation is more complicated than the static models from which it is derived. Attempts are made to incorporate into these simulations the transactions and interactions that we know are there but which elude a precise definition. Comparisons are made with observables to ascertain some degree of the quality of a model. 

Damiani, C., Serra, R., Villani, M., Kauffman, S.A., Colacci, A. Cell-cell interaction and diversity of emergent behaviours. lET Syst. Biol. 5(2), 137-144 (2011)... 

The first central issue in functional analysis is then Starting out with a complex requirements definition document (RDD) (i.e. with numerous and interacting requirements on the functionality), how do we select a set of functional elements and their interactions such that the resulting functional system satisfies the RDD We could try to pick a subset from a set of previously used elements and let them interact in a particular fashion. But we are faced with exactly the same problem as we encountered with the bottom-up approach to design in the physical domain, as discussed in Sec. B5.2. It is unlikely that the emergent behaviour of the functional system will meet all the requirements in the RDD. It will require a number of iterations to achieve that, and even then we have no way of knowing and demonstrating that we have found the best solution (the second central issue in functional analysis, to be discussed in the next section). 

The second source results in two different cases of emergent behaviour. One is where the additional inputs were designed into an element, and their activation is a decision by the system designer to exploit their influence on the element behaviour. The second case is where the inputs are unintentional, and their activation in the system environment leads to unintended consequences. An example of this is noise pulses entering into embedded control systems and causing unintended behaviour. 

In many cases faults will only restrict fluid flow, or they may be open i.e. non-sealing. Despite considerable efforts to predict the probability of fault sealing potential, a reliable method to do so has not yet emerged. Fault seal modelling is further complicated by the fact that some faults may leak fluids or pressures at a very small rate, thus effectively acting as seal on a production time scale of only a couple of years. As a result, the simulation of reservoir behaviour in densely faulted fields is difficult and predictions should be regarded as crude approximations only. 

The interactions between colloidal particles (see section C2.6.4) are central to tire understanding of suspension behaviour. Aitlrough most work has had to rely on ratlrer indirect ways to characterize tlrese interactions, novel teclmiques are emerging tlrat access tlrese interactions more directly. 

David Turnbull, in his illuminating Commentary on the Emergence and Evolution of Materials Science (Turnbull 1983), defined materials science broadly as the characterisation, understanding, and control of the structure of matter at the ultramolecular level and the relating of this structure to properties (mechanical, magnetic, electrical, etc.). That is, it is Ultramolecular Science . In professional and educational practice, however, he says that materials science focuses on the more complex features of behaviour, and especially those aspects controlled by crystal... 

Proeess operational quality, whieh has emerged as an essential pre-eondition to inerease profitability by fundamentally improving the design and operation of the proeess, involves two eomplementary steps (1) eontrol within pre-speeified limits and (2) eontinuous improvement of operational performanee (Saraiva and Stephanopoulos, 1992a). The first step deals with the reetifieation of abnormal proeess behaviour (as a result of speeial eauses) through effieient... 

One of the aims of the present research at Leeds University, of which the spectroscopic studies form a major part, has been to gain an understanding of mechanical behaviour. Both the uniaxially oriented and the biaxially oriented materials discussed in this review have also been the subject of studies of mechanical anisotropy and deformation. It is therefore of some interest to indicate the key guidelines which are emerging from these related studies. 

To prove this let us make more precise the short-time behaviour of the orientational relaxation, estimating it in the next order of tfg. The estimate of U given in (2.65b) involves terms of first and second order in Jtfg but the accuracy of the latter was not guaranteed by the simplest perturbation theory. The exact value of I4 presented in Eq. (2.66) involves numerical coefficient which is correct only in the next level of approximation. The latter keeps in Eq. (2.86) the terms quadratic to emerging from the expansion of M(Jf ). Taking into account this correction calculated in Appendix 2, one may readily reproduce the exact... 

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