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The analysis and design of a novel flexible dielectric sensor, which can be integrated into a composite materials manufacturing process to measure the resin frontal flow, is presented in this paper. The proposed sensor consists of two parallel line electrodes and a ground plane covered by a dielectric material. The analytical description and the electrostatic modelling were considered for the design of the sensor and to enhance the understanding of the response of the sensor to the resin impregnation of a carbon fabric during the infusion phase. The optimization of the sensor’s response and the increase of its sensitivity with regards to the geometric characteristics and the materials used were the main objectives of this study. An experimental set-up for the vacuum infusion process which includes the proposed sensor was used to measure the capacitance and validate the derived resin flow against visual measurements. The results indicate that the sensor can provide information on the resin frontal flow within 2% accuracy against visual measurements, which make this technology promising for monitoring the liquid resin infusion processes.

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Expectations can substantially influence perception. Predictive coding is a theory of sensory processing that aims to explain the neural mechanisms underlying the effect of expectations in sensory processing. Its main assumption is that sensory neurons encode prediction error with respect to expected sensory input. Neural populations encoding prediction error have been previously reported in the human auditory cortex (AC); however, most studies focused on the encoding of pure tones and induced expectations by stimulus repetition, potentially confounding prediction error with effects of neural habituation. Here, we systematically studied prediction error to pure tones and fast frequency modulated (FM) sweeps across different auditory cortical fields in humans. We conducted two fMRI experiments, each using one type of stimulus. We measured BOLD responses across the bilateral auditory cortical fields Te1.0, Te1.1, Te1.2, and Te3 while participants listened to sequences of sounds.We induced subjective expectations on the incoming sounds independently of stimulus repetition using abstract rules. Our results indicate that pure tones and FM-sweeps are encoded as prediction error with respect to the participants' expectations across auditory cortical fields. The topographical distribution of neural populations encoding prediction error to pure tones and FM-sweeps was highly correlated in left Te1.1 and Te1.2, and in bilateral Te3, suggesting that predictive coding is the general encoding mechanism in AC.