Probabilistic amplitude and frequency demodulation

A number of recent scientific and engineering problems require signals to be decomposed into a product of a slowly varying positive envelope and a quickly varying carrier whose instantaneous frequency also varies slowly over time. Although signal processing provides algorithms for so-called amplitude-and frequency-demodulation (AFD), there are well known problems with all of the existing methods. Motivated by the fact that AFD is ill-posed, we approach the problem using probabilistic inference. The new approach, called probabilistic amplitude and frequency demodulation (PAFD), models instantaneous frequency using an auto-regressive generalization of the von Mises distribution, and the envelopes using Gaussian auto-regressive dynamics with a positivity constraint. A novel form of expectation propagation is used for inference. We demonstrate that although PAFD is computationally demanding, it outperforms previous approaches on synthetic and real signals in clean, noisy and missing data settings.

Widening engineering horizons: Addressing the complexity of sustainable development

The complex, fragmented and diverse aspects of a sustainable development perspective are translated into an eight-point framework that defines a problem boundary larger than that traditionally adopted by civil engineers. This leads to practical questions intended to inform engineers who ask 'am I being sustainable?' during project implementation. The value of the questions is tested against a case history of a wastewater treatment project. This demonstrates the relevance of the questions to successive project delivery phases of defining the problem, choosing a solution and implementing that solution through design, construction and operation. The case history highlights that answers to several of the additional questions raised by considering this wider problem space are currently buried within government and clients' policies, regulations and standard practice; these answers may not be accessible to the professional engineer.

Discussion: Widening engineering horizons: Addressing the complexity of sustainable development

The following discussion is from an Institution of Civil Engineers (ICE) prestige lecture based on the original paper and delivered by the authors at the ICE in London on 24 September 2008.1 The event was chaired by Engineering Sustainability editorial panel chair, Professor Chris Rogers from Birmingham University. It was attended by an audience of 130 people as well as being watched by a similar number over a live web-cast. The web-cast can be accessed from the ICE archive for online viewing at http://scenta. interwise.com/etechb/ OnDemand/TH6509.

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.