Extending BPM Environments of Your Choice with Performance Related Decision Support

What-if Simulations have been identified as one solution for business performance related decision support. Such support is especially useful in cases where it can be automatically generated out of Business Process Management (BPM) Environments from the existing business process models and performance parameters monitored from the executed business process instances. Currently, some of the available BPM Environments offer basic-level performance prediction capabilities. However, these functionalities are normally too limited to be generally useful for performance related decision support at business process level. In this paper, an approach is presented which allows the non-intrusive integration of sophisticated tooling for what-if simulations, analytic performance prediction tools process optimizations or a combination Of Such solutions into already existing BPM environments. The approach abstracts from process modelling techniques which enable automatic decision support spanning processes across numerous BPM Environments. For instance, this enables end-to-end decision support for composite processes modelled with the Business Process Modelling Notation (BPMN) on top of existing Enterprise Resource Planning (ERP) processes modelled with proprietary languages.

Scale of production and choice of technique in the engineering industries in developing countries

This article examines the relationship between scale of production, optimal choice of technique and costs for three engineering industries: nuts and bolts, iron founding and machine tools. In all three industries costs of production fell as the scale of output increased. This was associated with switches of technique and the spread of fixed costs over a larger number of units. The capital-output ratio fell and labour productivity increased with increases in scale while, in most cases, the capital-labour ratio increased. The implications of these findings are briefly discussed.

Parasite diversity, patterns of MHC II variation and olfactory based mate choice in diverging three-spined stickleback ecotypes

Ecological speciation has been the subject of intense research in evolutionary biology but the genetic basis of the actual mechanism driving reproductive isolation has rarely been identified. The extreme polymorphism of the major histocompatibility complex (MHC), probably maintained by parasite-mediated selection, has been proposed as a potential driver of population divergence. We performed an integrative field and experimental study using three-spined stickleback river and lake ecotypes. We characterized their parasite load and variation at MHC class II loci. Fish from lakes and rivers harbor contrasting parasite communities and populations possess different MHC allele pools that could be the result of a combined action of genetic drift and parasite-mediated selection. We show that individual MHC class II diversity varies among populations and is lower in river ecotypes. Our results suggest the action of homogenizing selection within habitat type and diverging selection between habitat types. Finally, reproductive isolation was suggested by experimental evidence: in a flow channel design females preferred assortatively the odor of their sympatric male. This demonstrates the role of olfactory cues in maintaining reproductive isolation between diverging fish ecotypes.