Is Dawkins a modern-day Nicodemus?

This article applies a Wittgensteinian approach to the examination of the intelligibility of religious belief, in the wake of the recent attack on the Judeo-Christian religion by Richard Dawkins's book The God Delusion. The article attempts to show that Dawkins has confused religion with superstition, and that while Dawkins's arguments are decisive in the case of superstition, they do not successfully show religion to be a delusion. Religious belief in God is not like belief in the existence of a planet, and genuine religious faith is not like the belief in something for which there is not yet enough evidence, like belief in dark matter. The Christian doctrines of the resurrection and eternal life are misconstrued if they are understood as factual claims because they are then merely shallow superstitions, and not the great religious riddles they are meant to be.

What once was old is new again: reviving an early-modern form of interdisciplinarity for socio-legal studies

Socio-legal studies are an essentially interdisciplinary enterprise. However, there is currently only one form of interdisciplinarity that most socio-legal scholars (and criminologists) recognise and work with. This form is derived from the idea that 'society itself' - and by this most scholars mean 'civil society' - drives the law. However, another, rival understanding of society, which we term the authoritarian-liberal statist understanding that slipped from view in the late seventeenth century and remained obscure from then until now, may be used to generate another form of interdisciplinarity for sOcio-legal studies (and for criminology). However, this rival understanding of society does not simply allow us to reconfigure our notion of 'society'; it radically changes the role society plays in relation to the law. Two crucial points emerge from this rival account: first, society can no longer be understood as separable from (even though interacting with) the law; and second, society can no longer be understood as driving the law.

Whole-proteome phylogeny of large dsDNA viruses and parvoviruses through a composition vector method related to dynamical language model

Background The vast sequence divergence among different virus groups has presented a great challenge to alignment-based analysis of virus phylogeny. Due to the problems caused by the uncertainty in alignment, existing tools for phylogenetic analysis based on multiple alignment could not be directly applied to the whole-genome comparison and phylogenomic studies of viruses. There has been a growing interest in alignment-free methods for phylogenetic analysis using complete genome data. Among the alignment-free methods, a dynamical language (DL) method proposed by our group has successfully been applied to the phylogenetic analysis of bacteria and chloroplast genomes. Results In this paper, the DL method is used to analyze the whole-proteome phylogeny of 124 large dsDNA viruses and 30 parvoviruses, two data sets with large difference in genome size. The trees from our analyses are in good agreement to the latest classification of large dsDNA viruses and parvoviruses by the International Committee on Taxonomy of Viruses (ICTV). Conclusions The present method provides a new way for recovering the phylogeny of large dsDNA viruses and parvoviruses, and also some insights on the affiliation of a number of unclassified viruses. In comparison, some alignment-free methods such as the CV Tree method can be used for recovering the phylogeny of large dsDNA viruses, but they are not suitable for resolving the phylogeny of parvoviruses with a much smaller genome size.

From Greek temple to bird's nest : mapping, assessing and understanding national integrity systems

In this paper, I would like to outline the approach we have taken to mapping and assessing integrity systems and how this has led us to see integrity systems in a new light. Indeed, it has led us to a new visual metaphor for integrity systems – a bird’s nest rather than a Greek temple. This was the result of a pair of major research projects completed in partnership with Transparency International (TI). One worked on refining and extending the measurement of corruption. This, the second, looked at what was then the emerging institutional means for reducing corruption – ‘national integrity systems’

Semantic modeling method for configurable enterprise information systems

Business practices vary from one company to another and business practices often need to be changed due to changes of business environments. To satisfy different business practices, enterprise systems need to be customized. To keep up with ongoing business practice changes, enterprise systems need to be adapted. Because of rigidity and complexity, the customization and adaption of enterprise systems often takes excessive time with potential failures and budget shortfall. Moreover, enterprise systems often drag business behind because they cannot be rapidly adapted to support business practice changes. Extensive literature has addressed this issue by identifying success or failure factors, implementation approaches, and project management strategies. Those efforts were aimed at learning lessons from post implementation experiences to help future projects. This research looks into this issue from a different angle. It attempts to address this issue by delivering a systematic method for developing flexible enterprise systems which can be easily tailored for different business practices or rapidly adapted when business practices change. First, this research examines the role of system models in the context of enterprise system development; and the relationship of system models with software programs in the contexts of computer aided software engineering (CASE), model driven architecture (MDA) and workflow management system (WfMS). Then, by applying the analogical reasoning method, this research initiates a concept of model driven enterprise systems. The novelty of model driven enterprise systems is that it extracts system models from software programs and makes system models able to stay independent of software programs. In the paradigm of model driven enterprise systems, system models act as instructors to guide and control the behavior of software programs. Software programs function by interpreting instructions in system models. This mechanism exposes the opportunity to tailor such a system by changing system models. To make this true, system models should be represented in a language which can be easily understood by human beings and can also be effectively interpreted by computers. In this research, various semantic representations are investigated to support model driven enterprise systems. The significance of this research is 1) the transplantation of the successful structure for flexibility in modern machines and WfMS to enterprise systems; and 2) the advancement of MDA by extending the role of system models from guiding system development to controlling system behaviors. This research contributes to the area relevant to enterprise systems from three perspectives: 1) a new paradigm of enterprise systems, in which enterprise systems consist of two essential elements: system models and software programs. These two elements are loosely coupled and can exist independently; 2) semantic representations, which can effectively represent business entities, entity relationships, business logic and information processing logic in a semantic manner. Semantic representations are the key enabling techniques of model driven enterprise systems; and 3) a brand new role of system models; traditionally the role of system models is to guide developers to write system source code. This research promotes the role of system models to control the behaviors of enterprise.

Autopoiesis, language, literacy and the brain

When we attempt to speak about the relationship between language, literacy, and the brain, we find ourselves ill equipped to deal with these conceptually and qualitatively different phenomena. Immediately we must straddle different academic traditions that treat each of these as separate “things”. Broadly speaking, the study of language firstly belongs to the domain of biology, then to anthropology, sociology, and linguistics. At its most functional, a study of literacy education is a study of a particular technology, its diffusion techniques, and the abilities and motivations of people to adopt, or adapt themselves to, this technology. The brain is most commonly studied in the field of neurology, which is also a sub-discipline of biology, biochemistry, and medicine.