Plasmonic excitations in noble metals: The case of Ag

The delicate interplay between plasmonic excitations and interband transitions in noble metals is described by means of {\it ab initio} calculations and a simple model in which the conduction electron plasmon is coupled to the continuum of electron-hole pairs. Band structure effects, specially the energy at which the excitation of the $d$-like bands takes place, determine the existence of a subthreshold plasmonic mode, which manifests itself in Ag as a sharp resonance at 3.8 eV. However, such a resonance is not observed in the other noble metals. Here, this different behavior is also analyzed and an explanation is provided.Comment: 9 pages, 8 figure

Kinematic Reducibility of Multiple Model Systems

This paper considers the relationship between second order multiple model systems and first order multiple model systems. Such a relationship is important to, among other things, studying path planning for mechanical control systems. This is largely due to the fact that the computational complexity of a path planning problem rapidly increases with the dimension of the state space, implying that being able to reduce a path planning problem from TQ to Q can be helpful. Not surprisingly, the necessary and sufficient condition for such a reduction is that each model constituting a multiple model control system be reducible. We present an extensive example in order to illustrate how these results can provide insight into the control of some specific physical systems

Plasticity of functional connectivity in the adult spinal cord

This paper emphasizes several characteristics of the neural control of locomotion that provide opportunities for developing strategies to maximize the recovery of postural and locomotor functions after a spinal cord injury (SCI). The major points of this paper are: (i) the circuitry that controls standing and stepping is extremely malleable and reflects a continuously varying combination of neurons that are activated when executing stereotypical movements; (ii) the connectivity between neurons is more accurately perceived as a functional rather than as an anatomical phenomenon; (iii) the functional connectivity that controls standing and stepping reflects the physiological state of a given assembly of synapses, where the probability of these synaptic events is not deterministic; (iv) rather, this probability can be modulated by other factors such as pharmacological agents, epidural stimulation and/or motor training; (v) the variability observed in the kinematics of consecutive steps reflects a fundamental feature of the neural control system and (vi) machine-learning theories elucidate the need to accommodate variability in developing strategies designed to enhance motor performance by motor training using robotic devices after an SCI