Use of a continuous culture fermentation system to investigate the effect of GanedenBC30 (Bacillus coagulans GBI-30, 6086) supplementation on pathogen survival in the human gut microbiota

Single-stage continuous fermentation systems were employed to examine the effects of GanedenBC30 supplementation on the human gastrointestinal microbiota in relation to pathogen challenge in vitro. Denaturing gradient gel electrophoresis analysis demonstrated that GanedenBC30 supplementation modified the microbial profiles in the fermentation systems compared with controls, with profiles clustering according to treatment. Overall, GanedenBC30 supplementation did not elicit major changes in bacterial population counts in vitro, although notably higher Bcoa191 counts were seen following probiotic supplementation (compared to the controls). Pathogen challenge did not elicit significant modification of the microbial counts in vitro, although notably higher Clit135 counts were seen in the control system post-Clostridium difficile challenge than in the corresponding GanedenBC30-supplemented systems. Sporulation appears to be associated with the anti-microbial activity of GanedenBC30, suggesting that a bi-modal lifecycle of GanedenBC30 in vivo may lead to anti-microbial activity in distal regions of the gastrointestinal tract.

Bacterial, SCFA and gas profiles of a range of food ingredients following in vitro fermentation by human colonic microbiota.

It is now apparent that there is a strong link between health and nutrition and this can be seen clearly when we talk of obesity. The food industry is trying to capitalise on this by adapting high sugar/fat foods to become healthier alternatives. In confectionery food ingredients can be used for a range of purposes including sucrose replacement. Many of these ingredients may also evade digestion in the upper gut and be fermented by the gut microbiota upon entering the colon. This study was designed to screen a range of ingredients and their activities on the gut microbiota. In this study we screened a range of these ingredients in triplicate batch culture fermentations with known prebiotics as controls. Changes in bacteriology were monitored using FISH. SCFA were measured by GC and gas production was assessed during anaerobic batch fermentations. Bacterial enumeration showed significant increases (P ≤ 0.05) in bifidobacteria and lactobacilli with polydextrose and most polyols with no significant increases in Clostridium histolyticum/perfringens. SCFA and gas formation indicated that the substrates added to the fermenters were being utilised by the gut microbiota. It therefore appears these ingredients exert some prebiotic activity in vitro. Further studies, particularly in human volunteers, are necessary.

Simplified recursive identifier for ARMA processes

Symmetrical behaviour of the covariance matrix and the positive-definite criterion are used to simplify identification of single-input/single-output systems using recursive least squares. Simulation results are obtained and these are compared with ordinary recursive least squares. The adaptive nature of the identifier is verified by varying the system parameters on convergence.

Knowledge transfer processes in PFI/PPP: critical success factors

Successful knowledge transfer is an important process which requires continuous improvement in today’s knowledge-intensive economy. However, improving knowledge transfer processes represents a challenge for construction practitioners due to the complexity of knowledge acquisition, codification and sharing. Although knowledge transfer is context based, understanding the critical success factors can lead to improvements in the transfer process. This paper seeks to identify and evaluate the most significant critical factors for improving knowledge transfer processes in Public Private Partnerships/Private Finance Initiatives (PPP/PFI) projects. Drawing upon a questionnaire survey of 52 construction firms located in the UK, data is analysed using Severity Index (SI) and Coefficient of Variation (COV), to examine and identify these factors in PPP/PFI schemes. The findings suggest that a supportive leadership, participation/commitment from the relevant parties, and good communication between the relevant parties are crucial to improving knowledge transfer processes in PFI schemes. Practitioners, managers and researchers can use the findings to efficiently design performance measures for analysing and improving knowledge transfer processes.

Use of Megasphaera elsdenii NCIMB41125 as a probiotic for early-lactation dairy cows: effects on rumen pH and fermentation patterns

Multiparous rumen-fistulated Holstein cows were fed, from d 1 to 28 post-calving, an ad libitum TMR containing (g/kg DM) grass silage (196), corn silage (196), wheat (277), soybean meal (100), and other feeds (231) with CP, NDF, starch and water soluble carbohydrate concentrations of 176, 260, 299 and 39 g/kg DM respectively and ME of 12.2 MJ/kg DM. Treatments consisting of a minimum of 1010 cfu Megasphaera elsdenii NCIMB 41125 in 250 ml solution (MEGA) or 250 ml of autoclaved M. elsdenii (CONT) were administered via the rumen cannula on d 3 and 12 of lactation (n=7 per treatment). Mid-rumen pH was measured every 15 minutes and eating and ruminating behavior was recorded for 24 h on d 2, 4, 6, 8, 11, 13, 15, 17, 22 and 28. Rumen fluid for VFA and lactic acid (LA) analysis was collected at 11 timepoints on each of d 2, 4, 6, 13 and 15. Data were analysed as repeated measures using the Glimmix (LA data) or Mixed (all other data) procedures of SAS with previous 305 d milk yield and d 2 measurements as covariates where appropriate. Milk yield was higher (CONT 43.0 vs MEGA 45.4 ±0.75 kg/d, P=0.051) and fat concentration was lower (CONT 45.6 vs MEGA 40.4 ±1.05 g/kg, P=0.005) in cows that received MEGA. Time spent eating (263 ±15 min/d) and ruminating (571 ±13 min/d), DM intake (18.4 ±0.74 kg/d), proportion of each 24 h period with rumen pH below 5.6 (3.69 ±0.94 h) and LA concentrations (2.00 mM) were similar (P>0.327) across treatments. Ruminal total VFA concentration (104 ±3 mM) was similar (P=0.404) across treatments, but a shift from acetate (CONT 551 vs MEGA 524 ±14 mmol/mol VFA, P=0.161) to propionate production (CONT 249 vs MEGA 275 ±11 mmol/mol VFA, P=0.099) meant that the acetate:propionate ratio (CONT 2.33 vs MEGA 1.94 ±0.15) was reduced (P=0.072) in cows that received MEGA. This study provides evidence that supplementation of early lactation dairy cows with MEGA alters rumen fermentation patterns in favour of propionate, with potential benefits for animal health and productivity.

Neurofuzzy design and model construction of nonlinear dynamical processes from data

A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.

Neurofuzzy control using Kalman filtering state feedback with coloured noise for unknown non-linear processes

This paper presents a controller design scheme for a priori unknown non-linear dynamical processes that are identified via an operating point neurofuzzy system from process data. Based on a neurofuzzy design and model construction algorithm (NeuDec) for a non-linear dynamical process, a neurofuzzy state-space model of controllable form is initially constructed. The control scheme based on closed-loop pole assignment is then utilized to ensure the time invariance and linearization of the state equations so that the system stability can be guaranteed under some mild assumptions, even in the presence of modelling error. The proposed approach requires a known state vector for the application of pole assignment state feedback. For this purpose, a generalized Kalman filtering algorithm with coloured noise is developed on the basis of the neurofuzzy state-space model to obtain an optimal state vector estimation. The derived controller is applied in typical output tracking problems by minimizing the tracking error. Simulation examples are included to demonstrate the operation and effectiveness of the new approach.

Multi-microprocessor control of processes with pure time delay

In 1967 a novel scheme was proposed for controlling processes with large pure time delay (Fellgett et al, 1967) and some of the constituent parts of the scheme were investigated (Swann, 1970; Atkinson et al, 1973). At that time the available computational facilities were inadequate for the scheme to be implemented practically, but with the advent of modern microcomputers the scheme becomes feasible. This paper describes recent work (Mitchell, 1987) in implementing the scheme in a new multi-microprocessor configuration and shows the improved performance it provides compared with conventional three-term controllers.

Genetic algorithms for optimal control of beer fermentation

This paper uses genetic algorithms to optimise the mathematical model of a beer fermentation process that operates in batch mode. The optimisation is based in adjusting the temperature profile of the mixture during a fixed period of time in order to reach the required ethanol levels but considering certain operational and quality restrictions.

Processes governing the predictability of the Atlantic meridional overturning circulation in a coupled GCM

The processes that govern the predictability of decadal variations in the North Atlantic meridional overturning circulation (MOC) are investigated in a long control simulation of the ECHO-G coupled atmosphere–ocean model. We elucidate the roles of local stochastic forcing by the atmosphere, and other potential ocean processes, and use our results to build a predictive regression model. The primary influence on MOC variability is found to come from air–sea heat fluxes over the Eastern Labrador Sea. The maximum correlation between such anomalies and the variations in the MOC occurs at a lead time of 2 years, but we demonstrate that the MOC integrates the heat flux variations over a period of 10 years. The corresponding univariate regression model accounts for 74.5% of the interannual variability in the MOC (after the Ekman component has been removed). Dense anomalies to the south of the Greenland-Scotland ridge are also shown to precede the overturning variations by 4–6 years, and provide a second predictor. With the inclusion of this second predictor the resulting regression model explains 82.8% of the total variance of the MOC. This final bivariate model is also tested during large rapid decadal overturning events. The sign of the rapid change is always well represented by the bivariate model, but the magnitude is usually underestimated, suggesting that other processes are also important for these large rapid decadal changes in the MOC.