Strasheela: Design and usage of a music composition environment based on the Oz programming model

Strasheela provides a means for the composer to create a symbolic score by formally describing it in a rule-based way. The environment defines a rich music representation for complex polyphonic scores. Strasheela enables the user to define expressive compositional rules and then to apply them to the score. Compositional rules can restrict many aspects of the music - including the rhythmic structure, the melodic structure and the harmonic structure - by constraining the parameters (e.g. duration or pitch) of musical events according to some numerical or logical relation. Strasheela combines this expressivity with efficient search strategies.

Enantiomeric programming in tripodal transition metal scaffolds

A new route to the isolation of the enantiopure tris- chelate complex (Delta/Lambda)- fac-[Ru( L-1)(3)] 21 (where L-1 is 2,2'-bipyridine-5-carboxylic acid) is demonstrated, where the transition metal centre retains the memory of the chirality present in a simple tripodal tether used to control the metal centred geometry.

A role of cellular prion protein in programming T-cell cytokine responses in disease.

The cellular prion protein (PrPC) is widely expressed in neural and non-neural tissues, but its function is unknown. Elucidation of the part played by PrPC in adaptive immunity has been a particular conundrum: increased expression of cell surface PrPC has been documented during T-cell activation, yet the functional significance of this activation remains unclear, with conflicting data on the effects of Prnp gene knockout on various parameters of T-cell immunity. We show here that Prnp mRNA is highly inducible within 8–24 h of T-cell activation, with surface protein levels rising from 24 h. When measured in parallel with CD69 and CD25, PrPC is a late activation antigen. Consistent with its up-regulation being a late activation event, PrP deletion did not alter T-cell-antigen presenting cell conjugate formation. Most important, activated PrP0/0 T cells demonstrated much reduced induction of several T helper (Th) 1, Th2, and Th17 cytokines, whereas others, such as TNF- and IL-9, were unaffected. These changes were investigated in the context of an autoimmune model and a bacterial challenge model. In experimental autoimmune encephalomyelitis, PrP-knockout mice showed enhanced disease in the face of reduced IL-17 responses. In a streptococcal sepsis model, this constrained cytokine program was associated with poorer local control of infection, although with reduced bacteremia. The findings indicate that PrPC is a potentially important molecule influencing T-cell activation and effector function.

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.

Semi-formal Models to Support Program Development: Autonomic Management within Component Based Parallel and Distributed Programming

Functional and non-functional concerns require different programming effort, different techniques and different methodologies when attempting to program efficient parallel/distributed applications. In this work we present a "programmer oriented" methodology based on formal tools that permits reasoning about parallel/distributed program development and refinement. The proposed methodology is semi-formal in that it does not require the exploitation of highly formal tools and techniques, while providing a palatable and effective support to programmers developing parallel/distributed applications, in particular when handling non-functional concerns.

Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183–317 kg/m³ of cement content, 29–261 kg/m³ of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients.