The impact of oligofructose on stimulation of gut hormones, appetite regulation and adiposity

Objective: To investigate the effect of nutrient stimulation of gut hormones by oligofructose supplementation on appetite, energy intake (EI), body weight (BW) and adiposity in overweight and obese volunteers. Methods: In a parallel, single-blind and placebo-controlled study, 22 healthy overweight and obese volunteers were randomly allocated to receive 30 g day−1 oligofructose or cellulose for 6 weeks following a 2-week run-in. Subjective appetite and side effect scores, breath hydrogen, serum short chain fatty acids (SCFAs), plasma gut hormones, glucose and insulin concentrations, EI, BW and adiposity were quantified at baseline and post-supplementation. Results: Oligofructose increased breath hydrogen (P < 0.0001), late acetate concentrations (P = 0.024), tended to increase total area under the curve (tAUC)420mins peptide YY (PYY) (P = 0.056) and reduced tAUC450mins hunger (P = 0.034) and motivation to eat (P = 0.013) when compared with cellulose. However, there was no significant difference between the groups in other parameters although within group analyses showed an increase in glucagon-like peptide 1 (GLP-1) (P = 0.006) in the cellulose group and a decrease in EI during ad libitum meal in both groups. Conclusions: Oligofructose increased plasma PYY concentrations and suppressed appetite, while cellulose increased GLP-1 concentrations. EI decreased in both groups. However, these positive effects did not translate into changes in BW or adiposity.

On the performance of a blind source separation based I/Q-corrector

I and Q Channel phase and gain mismatches are of great concern in communications receiver design. In this paper we carry out a detailed performance analysis of the Blind-Source Seperation (BSS) based imbalance compensation structure. The results indicate that the BSS structure can offer adequate performance for most communication systems. Since the compensation is carried out before any modulation specific processing, the proposed compensation method works with all standard modulation formats.

On the structure and performance of a novel blind source separation based carrier phase synchronization error compensator

In this paper we carry out a detailed performance analysis of a novel blind-source-seperation (BSS) based DSP algorithm that tackles the carrier phase synchronization error problem. The results indicate that the mismatch can be effectively compensated during the normal operation as well as in the rapidly changing environments. Since the compensation is carried out before any modulation specific processing, the proposed method works with all standard modulation formats and lends itself to efficient real-time custom integrated hardware or software implementations.

Application of fractional delay filters to tune the centre frequency location of single-band sigma-delta modulators

This paper presents a novel technique for the design of narrow-band sigma-delta modulators with an embedded tunable centre frequency mechanism. This method demonstrates that the use of sum filters combined with a fractional delayer provide the flexibility of tuning the noise shaping band for any desired variable centre frequency input signal.

Sensory imagery in individuals who are blind and sighted: examining unimodal and multimodal forms

Introduction: Previous research has suggested that visual images are more easily generated, more vivid and more memorable than other sensory modalities. This research examined whether or not imagery is experienced in similar ways by people with and without sight. Specifically, the imabeability of visual, auditory and tactile cue words was compared. The degree to which images were multimodal or unimodal was also examined. Method: Twelve participants totally blind from early infancy and 12 sighted participants generated images in response to 53 sensory and non sensory words, rating imageability and the sensory modality, and describing images. From these 53 items, 4 subgroups of words, which stimulated images that were predominantly visual, tactile, auditory and low-imagery, respectively, were created. Results: T-tests comparing imageability ratings from blind and sighted participants found no differences for auditory and tactile words (both p>.1). Nevertheless, whilst participants without sight found auditory and tactile images equally imageable, sighted participants found images in response to tactile cue words harder to generate than visual cue words (mean difference: -0.51, p=.025). Participants with sight were also more likely to develop multisensory images than were participants without sight (both U≥15.0, N1=12, N2=12, p≤.008). Discussion: For both the blind and sighted, auditory and tactile images were rich and varied and similar language was used. Sighted participants were more likely to generate multimodal images. This was particularly the case for tactile words. Nevertheless, cue words that resulted in multisensory images were not necessarily rated as more imageable. The discussion considers whether or not multimodal imagery represent a method of compensating for impoverished unimodal imagery. Implications for Practitioners: Imagery is important not only as a mnemonic in memory rehabilitation, but also everyday uses for things such as autobiographical memory. This research emphasises both the importance of not only auditory and tactile sensory imagery, but also spatial imagery for people without sight.

A Single-Frame Super-Resolution Innovative Approach

Super-resolution refers to the process of obtaining a high resolution image from one or more low resolution images. In this work, we present a novel method for the super-resolution problem for the limited case, where only one image of low resolution is given as an input. The proposed method is based on statistical learning for inferring the high frequencies regions which helps to distinguish a high resolution image from a low resolution one. These inferences are obtained from the correlation between regions of low and high resolution that come exclusively from the image to be super-resolved, in term of small neighborhoods. The Markov random fields are used as a model to capture the local statistics of high and low resolution data when they are analyzed at different scales and resolutions. Experimental results show the viability of the method.