Dance in Handel's London Operas

In considering Handel's imaginative response to a range of contemporary theatrical dance styles and practices, this study demonstrates that dance was far from peripheral to the genre of opera seria. The importance of London as a leading centre for dance innovation, and the interaction between various theatrical genres regarding the use of dance, is also established.

Marie Sallé, Handel, Rameau and the development of narrative dance music:Bericht vom Internationalen Symposium an der Hochschule fur Musik und Theater Leipzig

Paradigmatic analysis reveals that these two composers developed distinct responses to creating narrative in dance music

Marie Sallé as muse, Handel's music for mime

Considers Handel's musical response to a dancer-choreographer in line with then-current styles of dance

'Handel's unpublished dance music':A perspective on his approach to composition

Provides incipits of the dances not then in modern editions.

Depicting Characters and danced Narratives: Handel, 'The Italian troupe', and Marie Sallé

Handel’s London career afforded opportunities for responding to dancers working in distinct styles of movement—most notably the Italian troupe resident at the King’s Theatre in 1726-27, and Marie Sallé at Covent Garden in 1734-35. By studying the dances from Admeto (1727) and Ariodante (1735), this paper will explore Handel's response to the serious and grotesque styles, as well as to the character and narrative modes.

Efficient FPGA Hardware Development: A Multi-Language Approach

This paper presents a multi-language framework to FPGA hardware development which aims to satisfy the dual requirement of high-level hardware design and efficient hardware implementation. The central idea of this framework is the integration of different hardware languages in a way that harnesses the best features of each language. This is illustrated in this paper by the integration of two hardware languages in the form of HIDE: a structured hardware language which provides more abstract and elegant hardware descriptions and compositions than are possible in traditional hardware description languages such as VHDL or Verilog, and Handel-C: an ANSI C-like hardware language which allows software and hardware engineers alike to target FPGAs from high-level algorithmic descriptions. On the one hand, HIDE has proven to be very successful in the description and generation of highly optimised parameterisable FPGA circuits from geometric descriptions. On the other hand, Handel-C has also proven to be very successful in the rapid design and prototyping of FPGA circuits from algorithmic application descriptions. The proposed integrated framework hence harnesses HIDE for the generation of highly optimised circuits for regular parts of algorithms, while Handel-C is used as a top-level design language from which HIDE functionality is dynamically invoked. The overall message of this paper posits that there need not be an exclusive choice between different hardware design flows. Rather, an integrated framework where different design flows can seamlessly interoperate should be adopted. Although the idea might seem simple prima facie, it could have serious implications on the design of future generations of hardware languages.

Hui and Walter's latent-class model extended to estimate diagnostic test properties from surveillance data: a latent model for latent data

Diagnostic test sensitivity and specificity are probabilistic estimates with far reaching implications for disease control, management and genetic studies. In the absence of 'gold standard' tests, traditional Bayesian latent class models may be used to assess diagnostic test accuracies through the comparison of two or more tests performed on the same groups of individuals. The aim of this study was to extend such models to estimate diagnostic test parameters and true cohort-specific prevalence, using disease surveillance data. The traditional Hui-Walter latent class methodology was extended to allow for features seen in such data, including (i) unrecorded data (i.e. data for a second test available only on a subset of the sampled population) and (ii) cohort-specific sensitivities and specificities. The model was applied with and without the modelling of conditional dependence between tests. The utility of the extended model was demonstrated through application to bovine tuberculosis surveillance data from Northern and the Republic of Ireland. Simulation coupled with re-sampling techniques, demonstrated that the extended model has good predictive power to estimate the diagnostic parameters and true herd-level prevalence from surveillance data. Our methodology can aid in the interpretation of disease surveillance data, and the results can potentially refine disease control strategies.