Determination of density and concentration from fluorescent images of a gas flow

A fluorescent image analysis procedure to determine the distribution of species concentration and density in a gas flow is proposed. The fluorescent emission is due to the excitation of atoms/molecules of a gas that is intercepted by an electron blade. The intensity of the fluorescent light is proportional to the local number density of the gas. When the gas flow is a mixture of different species, this proportionality can be exploited to extract the contribution associated to the species from the spectral superposition acquired by a digital camera. This yields a method that simultaneously reveals species concentrations and mass density of the mixture. The procedure is applied to two under-expanded sonic jets discharged into a different gas ambient - Helium into Argon and Argon into Helium - to measure the concentration and density distribution along the jet axis and across it. A comparison with experimental and numerical results obtained by other authors when observing under-expanded jets at different Mach numbers is made with the density distribution along the axis of the jet. This density distribution appears to be self-similar.Comment: New figures in portable .eps forma

Principles of sensorimotor learning.

The exploits of Martina Navratilova and Roger Federer represent the pinnacle of motor learning. However, when considering the range and complexity of the processes that are involved in motor learning, even the mere mortals among us exhibit abilities that are impressive. We exercise these abilities when taking up new activities - whether it is snowboarding or ballroom dancing - but also engage in substantial motor learning on a daily basis as we adapt to changes in our environment, manipulate new objects and refine existing skills. Here we review recent research in human motor learning with an emphasis on the computational mechanisms that are involved

Whole-scalp EEG mapping of somatosensory evoked potentials in macaque monkeys

High-density scalp EEG recordings are widely used to study whole-brain neuronal networks in humans non-invasively. Here, we validate EEG mapping of somatosensory evoked potentials (SSEPs) in macaque monkeys (Macaca fascicularis) for the long-term investigation of large-scale neuronal networks and their reorganisation after lesions requiring a craniotomy. SSEPs were acquired from 33 scalp electrodes in five adult anaesthetized animals after electrical median or tibial nerve stimulation. SSEP scalp potential maps were identified by cluster analysis and identified in individual recordings. A distributed, linear inverse solution was used to estimate the intracortical sources of the scalp potentials. SSEPs were characterised by a sequence of components with unique scalp topographies. Source analysis confirmed that median nerve SSEP component maps were in accordance with the somatotopic organisation of the sensorimotor cortex. Most importantly, SSEP recordings were stable both intra- and interindividually. We aim to apply this method to the study of recovery and reorganisation of large-scale neuronal networks following a focal cortical lesion requiring a craniotomy. As a prerequisite, the present study demonstrated that a 300-mm2 unilateral craniotomy over the sensorimotor cortex necessary to induce a cortical lesion, followed by bone flap repositioning, suture and gap plugging with calcium phosphate cement, did not induce major distortions of the SSEPs. In conclusion, SSEPs can be successfully and reproducibly recorded from high-density EEG caps in macaque monkeys before and after a craniotomy, opening new possibilities for the long-term follow-up of the cortical reorganisation of large-scale networks in macaque monkeys after a cortical lesion