A Two-Process Model for Control of Legato Articulation Across a Wide Range of Tempos During Piano Performance

Prior reports indicated a non-linear increase in key overlap times (KOTs) as tempo slows for scales/arpeggios performed at internote intervals (INIs) of I00-1000 ms. Simulations illustrate that this function can be explained by a two-process model. An oscillating neural network based on dynamics of the vector-integration-to-endpoint model for central generation of voluntary actions, allows performers to compute an estimate of the time remaining before the oscillator's next cycle onset. At fixed successive threshold values of this estimate they first launch keystroke n+l and then lift keystroke n. As tempo slows, time required to pass between threshold crossings elongates, and KOT increases. If only this process prevailed, performers would produce longer than observed KOTs at the slowest tempo. The full data set is explicable if subjects lift keystroke n whenever they cross the second threshold or receive sensory feedback from stroke n+l, whichever comes earlier.Fulbright grant; Office of Naval Research (N00014-92-J-1309, N0014-95-1-0409

Business cycles in the Netherlands, 1815-1913

This article exploits a unique new dataset containing information on the economy of the Netherlands to date business cycles turning points in the 19th century (1815-1913) using a modern econometric technique. The business cycle in the Netherlands is compared to the international (UK and US) business cycle for the second half of the sample. We conclude that business cycles do exist in the Netherlands in the 19th century – even before 1870. The Netherlands follows the international business cycle before 1870 and after 1890. In the in-between period the Dutch production could not meet both domestic demand and export demand.

On information in static and dynamic factor models

This paper employs concepts from information theory in factor models. We show that in the exact factor model the whole distribution of eigenvalues of the covariance matrix contributes to the information and not only the largest ones. In addition, we derive the condition that the first q say eigenvalues diverge whereas the rest remain bounded in the static model rather than having to assume it. Finally, we calculate information in static and dynamic factor models, which can be used to find the dimensions of the factor space. We illustrate the concepts with simulation experiments.

Consumer demand in the Industrial Revolution: The Netherlands, 1815-1913

The industrial revolution is mostly seen as a supply side phenomenon. Ever since Gilboy stated that factors of demand may have been equally important, scholars have stressed the importance of investments and technological change. This paper re-considers Gilboy?s ideas, using the dataset of the Dutch historical national accounts for the nineteenth century. Using a counterfactual VAR analysis, it is investigated to what extent changes in (determinants of) consumer demand may have affected patterns of industrial development.

Identifying barriers in telesurgery by studying current team practices in robot-assisted surgery

This paper investigates challenges in current practices in robot-assisted surgery. In addition, by using the method of proxy technology assessment, we provide insights into the current barriers to wider application of robot-assisted telesurgery, where the surgeon and console are physically remote from the patient and operating team. Research in this field has focused on the financial and technological constraints that limit such application; less has been done to clarify the complex dynamics of an operating team that traditionally works in close symbiosis. Results suggest that there are implications for working practices in transitioning from traditional robot-assisted surgery to remote robotic surgery that need to be addressed, such as possible communication problems which might have a negative impact on patient outcomes