Design and Implementation of Novel FPGA Based Time-Interleaved Variable Centre-Frequency Digital Sigma-Delta Modulators

Novel, multi-path, time-interleaved digital sigma-delta modulators that can operate at any arbitrary frequency from DC to Nyquist are designed, analysed and synthesized in this study. Dual- and quadruple-path fourth-order Butterworth, Chebyshev, Inverse Chebyshev and Elliptical based digital sigma-delta modulators, which offer designers the flexibility of specifying the centre-frequency, pass-band/stop-band attenuation as well as the signal bandwidth are presented. These topologies are compared in terms of their signal-to-noise ratios, hardware complexity, stability, tonality and sensitivity to non-idealities. Detailed simulations performed at the behavioural-level in MATLAB are compared with the experimental results of the FPGA implementation of the designed modulators. The signal-to-noise ratios between the simulated and empirical results are shown to be different by not more than 3-5 dBs. Furthermore, this paper presents the mathematical modelling and evaluation of the tones caused by the finite wordlengths of these digital multi-path sigma-delta modulators when excited by sinusoidal input signals

Resonant Plasmonic–Biomolecular Chiral Interactions in the Far-Ultraviolet: Enantiomeric Discrimination of sub-10 nm Amino Acid Films

Resonant plasmonic–molecular chiral interactions are a promising route to enhanced biosensing. However, biomolecular optical activity primarily exists in the far-ultraviolet regime, posing significant challenges for spectral overlap with current nano-optical platforms. We demonstrate experimentally and computationally the enhanced chiral sensing of a resonant plasmonic–biomolecular system operating in the far-UV. We develop a full-wave model of biomolecular films on Al gammadion arrays using experimentally derived chirality parameters. Our calculations show that detectable enhancements in the chiroptical signals from small amounts of biomolecules are possible only when tight spectral overlap exists between the plasmonic and biomolecular chiral responses. We support this conclusion experimentally by using Al gammadion arrays to enantiomerically discriminate ultrathin (\u3c10 nm thick) films of tyrosine. Notably, the chiroptical signals of the bare films were within instrumental noise. Our results demonstrate the importance of using far-UV active metasurfaces for enhancing natural optical activity

L-Cell Expression of Melanocortin-4-Receptor Is Marginal in Most of the Small Intestine in Mice and Humans and Direct Stimulation of Small Intestinal Melanocortin-4-Receptors in Mice and Rats Does Not Affect GLP-1 Secretion.

The molecular sensors underlying nutrient-stimulated GLP-1 secretion are currently being investigated. Peripheral administration of melanocortin-4 receptor (MC4R) agonists have been reported to increase GLP-1 plasma concentrations in mice and humans but it is unknown whether this effect results from a direct effect on the GLP-1 secreting L-cells in the intestine, from other effects in the intestine or from extra-intestinal effects. We investigated L-cell expression of MC4R in mouse and human L-cells by reanalyzing publicly available RNA sequencing databases (mouse and human) and by RT-qPCR (mouse), and assessed whether administration of MC4R agonists to a physiologically relevant gut model, isolated perfused mouse and rat small intestine, would stimulate GLP-1 secretion or potentiate glucose-stimulated secretion. L-cell MC4R expression was low in mouse duodenum and hardly detectable in the ileum and MC4R expression was hardly detectable in human L-cells. In isolated perfused mouse and rat intestine, neither intra-luminal nor intra-arterial administration of NDP-alpha-MSH, a potent MC4R agonist, had any effect on GLP-1 secretion (P ≥0.98, n = 5-6) from the upper or lower-half of the small intestine in mice or in the lower half in rats. Furthermore, HS014-an often used MC4R antagonist, which we found to be a partial agonist-did not affect the glucose-induced GLP-1 response in the rat, P = 0.62, n = 6). Studies on transfected COS7-cells confirmed bioactivity of the used compounds and that concentrations employed were well within in the effective range. Our combined data therefore suggest that MC4R-activated GLP-1 secretion in rodents either exclusively occurs in the colon or involves extra-intestinal signaling

Monitoring of trace metals, biochemical composition and growth of Axillary seabream (Pagellus acarne Risso, 1827) in offshore Copper alloy net cage

The study was conducted to assess trace metal contents, biochemical composition and growth performance of axillary seabream (Pagellus acarne Risso, 1827) cultured in a copper alloy mesh cage. A total of 400 axillary seabream (initial mean weight: 176.0±14.0 g), a new candidate species for the Mediterranean aquaculture, were stocked into a high-density polyethylene frame gravity cage and fed a commercial seabream diet for a period of 6 months. At the end of the feeding trial, fish reached a final weight of 264.8±16.8 g with a weight increase of 88.8 g and a feed conversion rate of 2.51. Overall, relative growth rate, specific growth rate and feed conversion ratio were satisfactory and comparable to the pelagic fishes such as gilthead seabream or European seabass, which are presently the main fish species for the Mediterranean aquaculture industry. Trace elements in fish grown in copper alloy net cages over a 6-month period showed satisfactory results, as the metal concentrations in fish tissues such as liver, skin, muscle and gills were below the reported upper limits for human consumption, indicating that copper alloy net is an acceptable and safe material for finfish cage aquaculture. Furthermore, from the growth performance data obtained in the present study, it can be concluded that axillary seabream showed potential for cage farming, and thus is a promising new candidate for the Mediterranean aquaculture industry

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

<p>Abstract</p> <p>Background</p> <p>The distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations. In order to mute the impact of outliers, one option is to fit models with residuals having a heavy-tailed distribution. Here, a Student's-<it>t </it>model was considered for the distribution of the residuals with the degrees of freedom treated as unknown. Bayesian inference was used to investigate a bivariate Student's-<it>t </it>(BS<it>t</it>) model using Markov chain Monte Carlo methods in a simulation study and analysing field data for gestation length and birth weight permitted to study the practical implications of fitting heavy-tailed distributions for residuals in linear mixed models.</p> <p>Methods</p> <p>In the simulation study, bivariate residuals were generated using Student's-<it>t </it>distribution with 4 or 12 degrees of freedom, or a normal distribution. Sire models with bivariate Student's-<it>t </it>or normal residuals were fitted to each simulated dataset using a hierarchical Bayesian approach. For the field data, consisting of gestation length and birth weight records on 7,883 Italian Piemontese cattle, a sire-maternal grandsire model including fixed effects of sex-age of dam and uncorrelated random herd-year-season effects were fitted using a hierarchical Bayesian approach. Residuals were defined to follow bivariate normal or Student's-<it>t </it>distributions with unknown degrees of freedom.</p> <p>Results</p> <p>Posterior mean estimates of degrees of freedom parameters seemed to be accurate and unbiased in the simulation study. Estimates of sire and herd variances were similar, if not identical, across fitted models. In the field data, there was strong support based on predictive log-likelihood values for the Student's-<it>t </it>error model. Most of the posterior density for degrees of freedom was below 4. Posterior means of direct and maternal heritabilities for birth weight were smaller in the Student's-<it>t </it>model than those in the normal model. Re-rankings of sires were observed between heavy-tailed and normal models.</p> <p>Conclusions</p> <p>Reliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets. The predictive log-likelihood was able to distinguish the correct model among the models fitted to heavy-tailed datasets. There was no disadvantage of fitting a heavy-tailed model when the true model was normal. Predictive log-likelihood values indicated that heavy-tailed models with low degrees of freedom values fitted gestation length and birth weight data better than a model with normally distributed residuals.</p> <p>Heavy-tailed and normal models resulted in different estimates of direct and maternal heritabilities, and different sire rankings. Heavy-tailed models may be more appropriate for reliable estimation of genetic parameters from field data.</p

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy-tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy-tail distributions (multivariate Student’s t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89±0.90 (4.35, 7.86) and 2.04±0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals