Function and Teleology

This is a short overview of the biological functions debate in philosophy. While it was fairly comprehensive when it was written, my short book ​A Critical Overview of Biological Functions has largely supplanted it as a definitive and up-to-date overview of the debate, both because the book takes into account new developments since then, and because the length of the book allowed me to go into substantially more detail about existing views

Learning Hybrid Process Models From Events: Process Discovery Without Faking Confidence

Process discovery techniques return process models that are either formal (precisely describing the possible behaviors) or informal (merely a "picture" not allowing for any form of formal reasoning). Formal models are able to classify traces (i.e., sequences of events) as fitting or non-fitting. Most process mining approaches described in the literature produce such models. This is in stark contrast with the over 25 available commercial process mining tools that only discover informal process models that remain deliberately vague on the precise set of possible traces. There are two main reasons why vendors resort to such models: scalability and simplicity. In this paper, we propose to combine the best of both worlds: discovering hybrid process models that have formal and informal elements. As a proof of concept we present a discovery technique based on hybrid Petri nets. These models allow for formal reasoning, but also reveal information that cannot be captured in mainstream formal models. A novel discovery algorithm returning hybrid Petri nets has been implemented in ProM and has been applied to several real-life event logs. The results clearly demonstrate the advantages of remaining "vague" when there is not enough "evidence" in the data or standard modeling constructs do not "fit". Moreover, the approach is scalable enough to be incorporated in industrial-strength process mining tools.Comment: 25 pages, 12 figure

The Abduction of Disorder in Psychiatry

The evolutionary cornerstone of J. C. Wakefield's (1999) harmful dysfunction thesis is a faulty assumption of comparability between mental and biological processes that overlooks the unique plasticity and openness of the brain?s functioning design. This omission leads Wakefield to an idealized concept of natural mental functions, illusory interpretations of mental disorders as harmful dysfunctions, and exaggerated claims for the validity of his explanatory and stipulative proposals. The authors argue that there are numerous ways in which evolutionarily intact mental and psychological processes, combined with striking discontinuities within and between evolutionary and contemporary social/cultural environments, may cause non-dysfunction variants of many widely accepted major mental disorders. These examples undermine many of Wakefield's arguments for adopting a harmful dysfunction concept of mental disorder

Session 2: Female Orgasms and Evolutionary Theory

Proceedings of the Pittsburgh Workshop in History and Philosophy of Biology, Center for Philosophy of Science, University of Pittsburgh, March 23-24 2001 Session 2: Female Orgasms and Evolutionary Theor

An explanatory and predictive PLS-SEM approach to the relationship between organizational culture,organizational performance and customer loyalty: The case of health clubs

Purpose This study aims to analyze the impact and predictive capacity of organizational culture on both customer loyalty and organizational performance in health clubs using data from managers and customers of health clubs in Spain. Design/methodology/approach A total of 101 managers were asked to measure organizational culture and organizational performance and 2,931 customers were asked to indicate their customer loyalty. The proposed hypotheses were tested and their predictability assessed through PLS-SEM. A composite concept was adopted to analyze the relationships between the different constructs and their indicators. Findings The findings suggest that organizational culture has a positive relationship with both customer loyalty and organizational performance. The four main dimensions of organizational culture that influence this relationship are, in order of significance, organizational presence, formalization, atmosphere and service-equipment. The authors’ model has a very good predictive power for both dependent variables. Originality/value Customer loyalty is an aspect of health clubs that can be improved. This study highlights the importance of creating a strong organizational culture in health clubs, as it enhances and predicts customer loyalty and organizational performance. Its predictability has already been tested with samples of managers and customers, with the analysis being performed from the perspective of the organization’s management and customer perceptions. This study also contributes to the field of sport management, using a predictive PLS-SEM techniqu

Soft computing applications in dynamic model identification of polymer extrusion process

This paper proposes the application of soft computing to deal with the constraints in conventional modelling techniques of the dynamic extrusion process. The proposed technique increases the efficiency in utilising the available information during the model identification. The resultant model can be classified as a ‘grey-box model’ or has been termed as a ‘semi-physical model’ in the context. The extrusion process contains a number of parameters that are sensitive to the operating environment. Fuzzy ruled-based system is introduced into the analytical model of the extrusion by means of sub-models to approximate those operational-sensitive parameters. In drawing the optimal structure for the sub-models, a hybrid algorithm of genetic algorithm with fuzzy system (GA-Fuzzy) has been implemented. The sub-models obtained show advantages such as linguistic interpretability, simpler rule-base and less membership functions. The developed model is adaptive with its learning ability through the steepest decent error back-propagation algorithm. This ability might help to minimise the deviation of the model prediction when the operational-sensitive parameters adapt to the changing operating environment in the real situation. The model is first evaluated through simulations on the consistency of model prediction to the theoretical analysis. Then, the effectiveness of adaptive sub-models in approximating the operational-sensitive parameters during the operation is further investigated