Multiple pitch estimation using non-homogeneous poisson processes

Novel statistical models are proposed and developed in this paper for automated multiple-pitch estimation problems. Point estimates of the parameters of partial frequencies of a musical note are modeled as realizations from a non-homogeneous Poisson process defined on the frequency axis. When several notes are combined, the processes for the individual notes combine to give a new Poisson process whose likelihood is easy to compute. This model avoids the data-association step of linking the harmonics of each note with the corresponding partials and is ideal for efficient Bayesian inference of unknown multiple fundamental frequencies in a signal. © 2011 IEEE.

Dynamic regulation of ARGONAUTE4 within multiple nuclear bodies in Arabidopsis thaliana.

DNA methylation directed by 24-nucleotide small RNAs involves the small RNA-binding protein ARGONAUTE4 (AGO4), and it was previously shown that AGO4 localizes to nucleolus-adjacent Cajal bodies, sites of snRNP complex maturation. Here we demonstrate that AGO4 also localizes to a second class of nuclear bodies, called AB-bodies, which are found immediately adjacent to condensed 45S ribosomal DNA (rDNA) sequences. AB-bodies also contain other proteins involved in RNA-directed DNA methylation including NRPD1b (a subunit of the RNA Polymerase IV complex, RNA PolIV), NRPD2 (a second subunit of this complex), and the DNA methyltransferase DRM2. These two classes of AGO4 bodies are structurally independent--disruption of one class does not affect the other--suggesting a dynamic regulation of AGO4 within two distinct nuclear compartments in Arabidopsis. Abolishing Cajal body formation in a coilin mutant reduced overall AGO4 protein levels, and coilin dicer-like3 double mutants showed a small decrease in DNA methylation beyond that seen in dicer-like3 single mutants, suggesting that Cajal bodies are required for a fully functioning DNA methylation system in Arabidopsis.

Impedance control is tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make and vary the direction of movements in unstable environments. It has been shown that when a single reaching movement is repeated in unstable dynamics, the central nervous system (CNS) learns an impedance internal model to compensate for the environment instability. However, there is still no explanation for how humans can learn to move in various directions in such environments. In this study, we investigated whether and how humans compensate for instability while learning two different reaching movements simultaneously. Results show that when performing movements in two different directions, separated by a 35° angle, the CNS was able to compensate for the unstable dynamics. After adaptation, the force was found to be similar to the free movement condition, but stiffness increased in the direction of instability, specifically for each direction of movement. Our findings suggest that the CNS either learned an internal model generalizing over different movements, or alternatively that it was able to switch between specific models acquired simultaneously. © 2008 IEEE.