Effects of mixture of nanoparticles under different salinity in the clams Ruditapes philippinarum and Ruditapes decussatus

Dissertação de mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidadde do Algarve, 2015

Selection and combination of biomarkers to control and prevent the risk of occupational exposure to the mixture of lead, arsenic and manganese

Tese de doutoramento, Farmácia (Toxicologia), Universidade de Lisboa, Faculdade de Farmácia, 2014

Characterizations of distributions using log odds rate

In this paper, we examine the relationships between log odds rate and various reliability measures such as hazard rate and reversed hazard rate in the context of repairable systems. We also prove characterization theorems for some families of distributions viz. Burr, Pearson and log exponential models. We discuss the properties and applications of log odds rate in weighted models. Further we extend the concept to the bivariate set up and study its properties.

Evaluation of the inclusion of a mixture of organic acids or lactulose into the feed of pigs experimentally challenged with Salmonella Typhimurium

A mixture of organic acids and lactulose for preventing or reducing colonization of the gut by Salmonella Typhimurium was evaluated in pigs. A total of 63 4-week-old commercial piglets were randomly distributed into three different experimental dietary groups: a plain diet without additives (PD) and the same diet supplemented with either 0.4% (w/v) formic acid and 0.4% lactic acid (w/v) (AC) or 1% (w/v) lactulose (LC). After 7 days of adaptation, two-thirds of the pigs (14 from each diet) were challenged with a 2-mL oral dose of 10(8) CFU/mL of Salmonella Typhimurium, leaving the remaining animals unchallenged (UC). After 4 and 10 days post-challenge, pigs were euthanized and the ileum and caecum content were aseptically sampled to (a) quantify lactic, formic, and short-chain fatty acids (SCFA), (b) quantify bacterial populations and Salmonella by fluorescence in situ hybridization and (c) qualitatively analyse bacterial populations through denaturing gradient gel electrophoresis (DGGE). Modification of fermentation products and counts of some of the bacterial groups analysed in the challenged pigs receiving the treatments AC and LC were minimal. Treatments only influenced the bacterial diversity after 10 days post-challenge, with AC generating a lower number of DGGE bands than UC(P < 0.05). Neither the inclusion of a mixture of 0.4% (w/v) formic and 0.4% (w/v) lactic acids nor of 1% (w/v) lactulose in the feed influenced numbers of Salmonella in the ileum and caecum of experimentally challenged pigs. (C) 2009 Elsevier B.V. All rights reserved.

A mixture of experts network structure construction algorithm for modelling and control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.

Neurofuzzy mixture of experts network parallel learning and model construction algorithms

A connection between a fuzzy neural network model with the mixture of experts network (MEN) modelling approach is established. Based on this linkage, two new neuro-fuzzy MEN construction algorithms are proposed to overcome the curse of dimensionality that is inherent in the majority of associative memory networks and/or other rule based systems. The first construction algorithm employs a function selection manager module in an MEN system. The second construction algorithm is based on a new parallel learning algorithm in which each model rule is trained independently, for which the parameter convergence property of the new learning method is established. As with the first approach, an expert selection criterion is utilised in this algorithm. These two construction methods are equivalent in their effectiveness in overcoming the curse of dimensionality by reducing the dimensionality of the regression vector, but the latter has the additional computational advantage of parallel processing. The proposed algorithms are analysed for effectiveness followed by numerical examples to illustrate their efficacy for some difficult data based modelling problems.

Effect of linseed oil and fish oil alone or as an equal mixture of ruminal fatty acid metabolism in growing steers fed maize silage-based diets

Based on the potential benefits to human health there is interest in increasing 18:3n-3, 20:5n-3, 22:6n-6, and cis-9,trans-11 conjugated linoleic acid (CLA) in ruminant foods. Four Aberdeen Angus steers (406 ± 8.2 kg BW) fitted with rumen and duodenal cannulae were used in a 4 x 4 Latin square experiment with 21 d periods to examine the potential of fish oil (FO) and linseed oil (LO) in the diet to increase ruminal outflow of trans-11 18:1 and total n-3 polyunsaturated fatty acids (PUFA) in growing cattle. Treatments consisted of a control diet (60:40; forage:concentrate ratio, on a DM basis, respectively) based on maize silage, or the same basal ration containing 30 g/kg DM of FO, LO or a mixture (1:1, w/w) of FO and LO (LFO). Diets were offered as total mixed rations and fed at a rate of 85 g DM/kg BW0.75/d. Oils had no effect (P = 0.52) on DM intake. Linseed oil had no effect (P > 0.05) on ruminal pH or VFA concentrations, while FO shifted rumen fermentation towards propionate at the expense of acetate. Compared with the control, LO increased (P < 0.05) 18:0, cis 18:1 (Δ9, 12-15), trans 18:1 (Δ4-9, 11-16), trans 18:2, geometric isomers of ∆9,11, ∆11,13, and ∆13,15 CLA, trans-8,cis-10 CLA, trans-10,trans-12 CLA, trans-12,trans-14 CLA, and 18:3n-3 flow at the duodenum. Inclusion of FO in the diet resulted in higher (P < 0.05) flows of cis-9 16:1, trans 16:1 (Δ6-13), cis 18:1 (Δ9, 11, and 13), trans 18:1 (Δ6-15), trans 18:2, 20:5n-3, 22:5n-3, and 22:6n-3, and lowered (P < 0.001) 18:0 at the duodenum relative to the control. For most fatty acids at the duodenum responses to LFO were intermediate of FO and LO. However, LFO resulted in higher (P = 0.04) flows of total trans 18:1 than LO and increased (P < 0.01) trans-6 16:1 and trans-12 18:1 at the duodenum compared with FO or LO. Biohydrogenation of cis-9 18:1 and 18:2n-6 in the rumen was independent of treatment, but both FO and LO increased (P < 0.001) the extent of 18:3n-3 biohydrogenation compared with the control. Ruminal 18:3n-3 biohydrogenation was higher (P < 0.001) for LO and LFO than FO, while biohydrogenation of 20:5n-3 and 22:6n-3 in the rumen was marginally lower (P = 0.05) for LFO than FO. In conclusion, LO and FO at 30 g/kg DM altered the biohydrogenation of unsaturated fatty acids in the rumen causing an increase in the flow of specific intermediates at the duodenum, but the potential of these oils fed alone or as a mixture to increase n-3 PUFA at the duodenum in cattle appears limited.

Keeping the dream of rigorous hypothesis testing alive

This article reviews recent work on hypothesis testing in the American Journal of AGricultural Economics and its predecessor journal, the Journal of Farm Economics

A mixture of trans-galactooligosaccharides reduces markers of metabolic syndrome and modulates the fecal microbiota and immune function of overweight adults

Metabolic syndrome is a set of disorders that increases the risk of developing cardiovascular disease. The gut microbiota is altered toward a less beneficial composition in overweight adults and this change can be accompanied by inflammation. Prebiotics such as galactooligosaccharides can positively modify the gut microbiota and immune system; some may also reduce blood lipids. We assessed the effect of a galactooligosaccharide mixture [Bi2 muno (B-GOS)] on markers of metabolic syndrome, gut microbiota, and immune function in 45 overweight adults with $3 risk factors associated with metabolic syndrome in a double-blind, randomized, placebo (maltodextrin)-controlled, crossover study (with a 4-wk wash-out period between interventions). Whole blood, saliva, feces, and anthropometric measurements were taken at the beginning, wk 6, and end of each 12-wk intervention period. Predominant groups of fecal bacteria were quantified and full blood count, markers of inflammation and lipid metabolism, insulin, and glucose were measured. B-GOS increased the number of fecal bifidobacteria at the expense of less desirable groups of bacteria. Increases in fecal secretory IgA and decreases in fecal calprotectin, plasma C-reactive protein, insulin, total cholesterol (TC), TG, and the TC:HDL cholesterol ratio were also observed. Administration of B-GOS to overweight adults resulted in positive effects on the composition of the gut microbiota, the immune response, and insulin, TC, and TG concentrations. B-GOSmay be a useful candidate for the enhancement of gastrointestinal health, immune function, and the reduction of metabolic syndrome risk factors in overweight adults.

Adaptive nonlinear equalizer using a mixture of gaussians based on-line density estimator

This paper introduces a new adaptive nonlinear equalizer relying on a radial basis function (RBF) model, which is designed based on the minimum bit error rate (MBER) criterion, in the system setting of the intersymbol interference channel plus a co-channel interference. Our proposed algorithm is referred to as the on-line mixture of Gaussians estimator aided MBER (OMG-MBER) equalizer. Specifically, a mixture of Gaussians based probability density function (PDF) estimator is used to model the PDF of the decision variable, for which a novel on-line PDF update algorithm is derived to track the incoming data. With the aid of this novel on-line mixture of Gaussians based sample-by-sample updated PDF estimator, our adaptive nonlinear equalizer is capable of updating its equalizer’s parameters sample by sample to aim directly at minimizing the RBF nonlinear equalizer’s achievable bit error rate (BER). The proposed OMG-MBER equalizer significantly outperforms the existing on-line nonlinear MBER equalizer, known as the least bit error rate equalizer, in terms of both the convergence speed and the achievable BER, as is confirmed in our simulation study