Metamaterial filter for the near-visible spectrum

We demonstrate metamaterials operating in the near-visible regime based on two-dimensional arrays of gold-coated silicon nanopillars. The nanopillar arrays demonstrate a cutoff response at the metamaterial plasma frequency in accordance with theory and can be utilized for filtering applications. A plasma frequency in the near visible region of λ = 1 μm is calculated numerically for an array with a lattice constant of 300 nm and wire radius of 50 nm, with reflection measurements in agreement with numerical calculations. Such structures can be utilized for achieving negative-index based metamaterials for the visible spectrum. © 2012 American Institute of Physics.

Indirect modulation of a terahertz quantum cascade laser using gate tunable graphene

We bring together two areas of terahertz (THz) technology that have benefited from recent advancements in research, i.e., graphene, a material that has plasmonic resonances in the THz frequency, and quantum cascade lasers (QCLs), a compact electrically driven unipolar source of THz radiation. We demonstrate the use of single-layer large-area graphene to indirectly modulate a THz QCL operating at 2.0 THz. By tuning the Fermi level of the graphene via a capacitively coupled backgate voltage, the optical conductivity and, hence, the THz transmission can be varied. We show that, by changing the pulsing frequency of the backgate, the THz transmission can be altered. We also show that, by varying the pulsing frequency of the backgate from tens of Hz to a few kHz, the amplitude-modulated THz signal can be switched by 15% from a low state to a high state. © 2009-2012 IEEE.

Mismatched shaping schemes for bit-interleaved coded modulation

We consider bit-interleaved coded modulation (BICM) schemes where, instead of the true bit or symbol probabilities and the constellation used at the transmitter, the decoder uses arbitrary probabilities or reference constellations. We study the corresponding low- and high- signal-to-noise-ratio regimes and show that even in the presence of this extra sources of mismatch, BICM has a negligible penalty with respect to coded modulation. © 2012 IEEE.

28 Gb/s unequalized PAM3 modulation of an 850 nm VCSEL for next-generation datacommunication links

An 850 nm vertical-cavity surface-emitting laser is modulated at 28 Gb/s using pulseamplitude modulation with three levels. Unequalized transmission over 100 m of OM3 MMF is demonstrated, with advantages over NRZ and PAM4 modulation. © 2012 OSA.

Mixed source model and its adapted vocal tract filter estimate for voice transformation and synthesis

In current methods for voice transformation and speech synthesis, the vocal tract filter is usually assumed to be excited by a flat amplitude spectrum. In this article, we present a method using a mixed source model defined as a mixture of the Liljencrants-Fant (LF) model and Gaussian noise. Using the LF model, the base approach used in this presented work is therefore close to a vocoder using exogenous input like ARX-based methods or the Glottal Spectral Separation (GSS) method. Such approaches are therefore dedicated to voice processing promising an improved naturalness compared to generic signal models. To estimate the Vocal Tract Filter (VTF), using spectral division like in GSS, we show that a glottal source model can be used with any envelope estimation method conversely to ARX approach where a least square AR solution is used. We therefore derive a VTF estimate which takes into account the amplitude spectra of both deterministic and random components of the glottal source. The proposed mixed source model is controlled by a small set of intuitive and independent parameters. The relevance of this voice production model is evaluated, through listening tests, in the context of resynthesis, HMM-based speech synthesis, breathiness modification and pitch transposition. © 2012 Elsevier B.V. All rights reserved.

Metamaterial filter for the near-visible spectrum

We demonstrate metamaterials operating in the near-visible regime based on two-dimensional arrays of gold-coated silicon nanopillars. The nanopillar arrays demonstrate a cutoff response at the metamaterial plasma frequency in accordance with theory and can be utilized for filtering applications. A plasma frequency in the near visible region of λ = 1 μm is calculated numerically for an array with a lattice constant of 300 nm and wire radius of 50 nm, with reflection measurements in agreement with numerical calculations. Such structures can be utilized for achieving negative-index based metamaterials for the visible spectrum.

Modulation of somatosensory processing by action.

Psychophysical evidence suggests that sensations arising from our own movements are diminished when predicted by motor forward models and that these models may also encode the timing and intensity of movement. Here we report a functional magnetic resonance imaging study in which the effects on sensation of varying the occurrence, timing and force of movements were measured. We observed that tactile-related activity in a region of secondary somatosensory cortex is reduced when sensation is associated with movement and further that this reduction is maximal when movement and sensation occur synchronously. Motor force is not represented in the degree of attenuation but rather in the magnitude of this region's response. These findings provide neurophysiological correlates of previously-observed behavioural forward-model phenomena, and advocate the adopted approach for the study of clinical conditions in which forward-model deficits have been posited to play a crucial role.

Design guidelines for granular particles in a conical centrifugal filter

Essential design criteria for successful drying of granular particles in a conical continuous centrifugal filter are developed in a dimensionless fashion. Four criteria are considered: minimum flow thickness (to ensure sliding bulk flow rather than particulate flow), desaturation position, output dryness and basket failure. The criteria are based on idealised physical models of the machine operation and are written explicitly as functions of the basket size lout, spin velocity Ω and input flow rate of powder Qp. The separation of sucrose crystals from liquid molasses is taken as a case study and the successful regime of potential operating points (lout, Ω) is plotted for a wide range of selected values of flow rate Qp. Analytical expressions are given for minimum and maximum values of the three independent parameters (lout, Ω, Qp) as a function of the slurry and basket properties. The viable operating regime for a conical centrifugal filter is thereby obtained as a function of the slurry and basket properties. © 2012 The Institution of Chemical Engineers.

Modeling natural sounds with modulation cascade processes

Natural sounds are structured on many time-scales. A typical segment of speech, for example, contains features that span four orders of magnitude: Sentences ($\sim1$s); phonemes ($\sim10$−$1$ s); glottal pulses ($\sim 10$−$2$s); and formants ($\sim 10$−$3$s). The auditory system uses information from each of these time-scales to solve complicated tasks such as auditory scene analysis [1]. One route toward understanding how auditory processing accomplishes this analysis is to build neuroscience-inspired algorithms which solve similar tasks and to compare the properties of these algorithms with properties of auditory processing. There is however a discord: Current machine-audition algorithms largely concentrate on the shorter time-scale structures in sounds, and the longer structures are ignored. The reason for this is two-fold. Firstly, it is a difficult technical problem to construct an algorithm that utilises both sorts of information. Secondly, it is computationally demanding to simultaneously process data both at high resolution (to extract short temporal information) and for long duration (to extract long temporal information). The contribution of this work is to develop a new statistical model for natural sounds that captures structure across a wide range of time-scales, and to provide efficient learning and inference algorithms. We demonstrate the success of this approach on a missing data task.

Uncertainty increases pain: evidence for a novel mechanism of pain modulation involving the periaqueductal gray.

Predictions about sensory input exert a dominant effect on what we perceive, and this is particularly true for the experience of pain. However, it remains unclear what component of prediction, from an information-theoretic perspective, controls this effect. We used a vicarious pain observation paradigm to study how the underlying statistics of predictive information modulate experience. Subjects observed judgments that a group of people made to a painful thermal stimulus, before receiving the same stimulus themselves. We show that the mean observed rating exerted a strong assimilative effect on subjective pain. In addition, we show that observed uncertainty had a specific and potent hyperalgesic effect. Using computational functional magnetic resonance imaging, we found that this effect correlated with activity in the periaqueductal gray. Our results provide evidence for a novel form of cognitive hyperalgesia relating to perceptual uncertainty, induced here by vicarious observation, with control mediated by the brainstem pain modulatory system.

Modulation of pain ratings by expectation and uncertainty: Behavioral characteristics and anticipatory neural correlates.

Expectations about the magnitude of impending pain exert a substantial effect on subsequent perception. However, the neural mechanisms that underlie the predictive processes that modulate pain are poorly understood. In a combined behavioral and high-density electrophysiological study we measured anticipatory neural responses to heat stimuli to determine how predictions of pain intensity, and certainty about those predictions, modulate brain activity and subjective pain ratings. Prior to receiving randomized laser heat stimuli at different intensities (low, medium or high) subjects (n=15) viewed cues that either accurately informed them of forthcoming intensity (certain expectation) or not (uncertain expectation). Pain ratings were biased towards prior expectations of either high or low intensity. Anticipatory neural responses increased with expectations of painful vs. non-painful heat intensity, suggesting the presence of neural responses that represent predicted heat stimulus intensity. These anticipatory responses also correlated with the amplitude of the Laser-Evoked Potential (LEP) response to painful stimuli when the intensity was predictable. Source analysis (LORETA) revealed that uncertainty about expected heat intensity involves an anticipatory cortical network commonly associated with attention (left dorsolateral prefrontal, posterior cingulate and bilateral inferior parietal cortices). Relative certainty, however, involves cortical areas previously associated with semantic and prospective memory (left inferior frontal and inferior temporal cortex, and right anterior prefrontal cortex). This suggests that biasing of pain reports and LEPs by expectation involves temporally precise activity in specific cortical networks.

Modulation of pain processing in hyperalgesia by cognitive demand.

The relationship between pain and cognitive function is of theoretical and clinical interest, exemplified by observations that attention-demanding activities reduce pain in chronically afflicted patients. Previous studies have concentrated on phasic pain, which bears little correspondence to clinical pain conditions. Indeed, phasic pain is often associated with differential or opposing effects to tonic pain in behavioral, lesion, and pharmacological studies. To address how cognitive engagement interacts with tonic pain, we assessed the influence of an attention-demanding cognitive task on pain-evoked neural responses in an experimental model of chronic pain, the capsaicin-induced heat hyperalgesia model. Using functional magnetic resonance imaging (fMRI), we show that activity in the orbitofrontal and medial prefrontal cortices, insula, and cerebellum correlates with the intensity of tonic pain. This pain-related activity in medial prefrontal cortex and cerebellum was modulated by the demand level of the cognitive task. Our findings highlight a role for these structures in the integration of motivational and cognitive functions associated with a physiological state of injury. Within the limitations of an experimental model of pain, we suggest that the findings are relevant to understanding both the neurobiology and pathophysiology of chronic pain and its amelioration by cognitive strategies.