Ionic Competition Effects in a Continuous Uranium Biosorptive Recovery Process

Immobilized Rhizopus arrhizus biomass was studied in a continuous sorption and desorption mode in order to identify factors that affect the long term uranium biosorptive uptake capacity performance of the immobilized biomass. Laboratory-scale continuous operation pilot plant experiments were performed using synthetic uranyl nitrate and industrial uranium mine leachate solutions. Analysis of the liquid solutions indicated that the immobilized Rhizopus arrhizus biomass successfully recovered all of the uranium from the dilute (less than 500 mg U dm⁻³) solutions. All uranium can subsequently be eluted, yielding highly concentrated uranium eluates. The immobilized Rhizopus arrhizus biomass maintained its uranium biosorptive uptake capacity over 12 successive sorption–elution cycles when synthetic uranyl nitrate solutions were used. However, when used with mine leachate solutions, an 18% reduction in the uranium biosorptive uptake capacity occurred within the first four adsorption–elution cycles. Spectral analysis indicated that, during continuous use and reuse, the immobilized biomass retained its structural integrity. EDAX, scanning and transmission electron microscopic techniques employed on the microbial biomass suggested that the presence of aluminium interferes with the uranium biosorption process. Spectral analysis also indicated that the presence of silicon enhances the negative effect of the presence of aluminium on the uranium biosorptive uptake capacity of the immobilized Rhizopus arrhizus biomass particles. © 1997 SCI     

Inhibitory effect of organic acid salts on spoilage flora in culture medium and cured cooked meat products under commercial manufacturing conditions

Lactobacillus curvatus, isolated from a spoiled vacuum-packaged 'pariza' type meat product, was used to inoculate modified MRS broth containing sodium lactate, sodium acetate and potassium sorbate in different concentrations, alone or in inter se combinations. Two commercial preparations (MIX 1 and MIX 2) were also used containing combinations of the above antimicrobials. Results from the preservatives addition to the culture medium showed highest antimicrobial activity in the case of the sodium lactate (2%, 3% or 4%), sodium acetate (0.5%) and potassium sorbate (0.15%) combination. Results from the preservatives addition to two types of thermally processed meats showed that sodium lactate and the combination of sodium lactate, sodium acetate and potassium sorbate were the most effective; extending the products shelf life an additional 10 days. Finally, MIX 1 and MIX 2 suppressed the lactic acid bacteria (LAB) growth in the culture medium but not in the final product.     

Estimating the diagnostic accuracy of three culture-dependent methods for the Listeria monocytogenes detection from a Bayesian perspective

The objective of this study was to estimate the test accuracy measures (classification probabilities [CPs], predictive values [PVs], likelihood ratios [LRs] and area under receiving operating characteristic curve [AUC]) of three different culture-dependent methods, commonly used during routine analysis for the detection of the foodborne pathogen Listeria monocytogenes, from a Bayesian perspective. Data from a previous study by Andritsos et al. (2010) were used to define measures of accuracy for the diagnostic tests. Samples of minced pork meat obtained from local markets were tested for L. monocytogenes presence by parallel testing using selective media (PALCAM, ALOA and RAPID'L.mono). Dirichlet distribution, which is the multivariate expression of a Beta distribution, was used to analyze the data. Bayesian analysis determines characteristics of the posterior distribution from available prior information. Results showed that all methods were best at ruling in L. monocytogenes presence than ruling it out. PALCAM seemed to have better performance based on positive PV, positive LR and AUC, but it was not so sensitive as RAPID'L.mono was. Results also showed that none of the media were perfect in detecting L. monocytogenes, i.e. sensitivity and specificity equal to one. Besides, the problem of observing zero counts may be overcome by applying Bayesian analysis, making the determination of a test performance feasible.     

Quantifying Listeria monocytogenes prevalence and concentration in minced pork meat and estimating performance of three culture media from presence/absence microbiological testing using a deterministic and stochastic approach

Listeria monocytogenes poses a serious threat to public health, and the majority of cases of human listeriosis are associated with contaminated food. Reliable microbiological testing is needed for effective pathogen control by food industry and competent authorities. The aims of this work were to estimate the prevalence and concentration of L. monocytogenes in minced pork meat by the application of a Bayesian modeling approach, and also to determine the performance of three culture media commonly used for detecting L. monocytogenes in foods from a deterministic and stochastic perspective. Samples (n = 100) collected from local markets were tested for L. monocytogenes using in parallel the PALCAM, ALOA and RAPID'L.mono selective media according to ISO 11290-1:1996 and 11290-2:1998 methods. Presence of the pathogen was confirmed by conducting biochemical and molecular tests. Independent experiments (n = 10) for model validation purposes were performed. Performance attributes were calculated from the presence–absence microbiological test results by combining the results obtained from the culture media and confirmative tests. Dirichlet distribution, the multivariate expression of a Beta distribution, was used to analyze the performance data from a stochastic perspective. No L. monocytogenes was enumerated by direct-plating (<10 CFU/g), though the pathogen was detected in 22% of the samples. L. monocytogenes concentration was estimated at 14–17 CFU/kg. Validation showed good agreement between observed and predicted prevalence (error = −2.17%). The results showed that all media were best at ruling in L. monocytogenes presence than ruling it out. Sensitivity and specificity varied depending on the culture-dependent method. None of the culture media was perfect in detecting L. monocytogenes in minced pork meat alone. The use of at least two culture media in parallel enhanced the efficiency of L. monocytogenes detection. Bayesian modeling may reduce the time needed to draw conclusions regarding L. monocytogenes presence and the uncertainty of the results obtained. Furthermore, the problem of observing zero counts may be overcome by applying Bayesian analysis, making the determination of a test performance feasible.     

Distributed adaptive fault‐tolerant leader‐following formation control of nonlinear uncertain second‐order multi‐agent systems

This paper presents a distributed integrated fault diagnosis and accommodation scheme for leader‐following formation control of a class of nonlinear uncertain second‐order multi‐agent systems. The fault model under consideration includes both process and actuator faults, which may evolve abruptly or incipiently. The time‐varying leader communicates with a small subset of follower agents, and each follower agent communicates to its directly connected neighbors through a bidirectional network with possibly asymmetric weights. A local fault diagnosis and accommodation component are designed for each agent in the distributed system, which consists of a fault detection and isolation module and a reconfigurable controller module comprised of a baseline controller and two adaptive fault‐tolerant controllers, activated after fault detection and after fault isolation, respectively. By using appropriately the designed Lyapunov functions, the closed‐loop stability and asymptotic convergence properties of the leader‐follower formation are rigorously established under different modes of the fault‐tolerant control system.     

Robust fault isolation for a class of non-linear input?output systems

The design and analysis of fault diagnosis methodologies for non-linear systems has received significant attention recently. This paper presents a robust fault isolation scheme for a class of non-linear systems with unstructured modelling uncertainty and partial state measurement. The proposed fault diagnosis architecture consists of a fault detection and approximation estimator and a bank of isolation estimators. Each isolation estimator corresponds to a particular type of fault in the fault class. A fault isolation decision scheme is presented with guaranteed performance. If at least one component of the output estimation error of a particular fault isolation estimator exceeds the corresponding adaptive threshold at some finite time, then the occurrence of that type of fault can be excluded. Fault isolation is achieved if this is valid for all but one isolation estimator. Based on the class of non-linear systems under consideration, fault isolability conditions are rigorously investigated, characterizing the class of non-linear faults that are isolable by the proposed scheme. Moreover, the non-conservativeness of the fault isolability conditions is illustrated by deriving a subclass of nonlinear systems and faults for which this condition is also necessary for fault isolability. A simulation example of a simple robotic system is used to show the effectiveness of the robust fault isolation methodology.