Strategy for a Scale‐up Correlation in a Dissolved Air Flotation Chamber

Beginning with a laboratory‐scale physical model, a scale‐up correlation for a pilot unit project was determined based on the analysis of dynamic similarity correlations involving the predominant phenomena of a dissolved air flotation (DAF) chamber. The implantation costs of pilot units require special strategies due to the lack of correlations of this type, as novel flotation methods have been considered strictly from an economic standpoint. With the aid of computational fluid dynamics and videos of microbubble and floc flow, inertia and gravity were identified as the predominant phenomena in a DAF chamber. The strategy described herein is simple and reduces the likelihood of future risks in scale‐up investments.     

Dynamic monitoring of the shelf life of Cobia (Rachycentron canadum): a study on the applicability of a smart photochromic indicator

To ensure the marketing of fresh fish‐based products, it is necessary to develop fast methods that assess its freshness in real time. This study therefore evaluated the applicability of a photochromic time–temperature indicator (TTI) to monitor the time and temperature history during the period of validity of the whole fish of the cobia specimen stored in ice. The TTI response was both visibly interpreted as well as adaptable to measurement using suitable equipment. The results showed that the smart indicator activated during 6 s of ultraviolet light showed a similar rate of deterioration of the analysed product visual response, proving to be a dynamic shelf life indicator that can assure consumers the ultimate quality point of the entire cobia easily, cheaply and accurately.     

Characterization and determination of brewer's solid wastes composition

Agro‐industrial wastes are produced in large quantities around the world from the processing and manufacturing of food and beverages. The disposal of these wastes into the environment leads to damage to ecosystems owing to their composition rich in organic matter. In this context it may be noted that the brewing industry, whose production process includes processing steps and fermentation of vegetable raw materials such as barley and/or other grains used as adjuncts and hops, generates various byproducts. The worldwide consumption of these beverages and the current model of breweries, which includes production on a large scale, lead to the generation of large amounts of brewery waste, namely spent grain, hot trub and residual yeast. Owing to its composition, these residues exhibit significant potential for application in bioprocess technologies. In this study the three residues mentioned had their composition determined as a function of moisture, ash, total organic carbon (TOC), total and soluble nitrogen, reducing sugar and soluble free amino nitrogen. Moreover, the residues were characterized for total acidity, pH and chemical oxygen demand (COD) of total and soluble fractions. The three residues evaluated had high moisture content (>80%) and high organic matter content (TOC and COD, ~50% and >1000 mg/g, respectively), which can highlights the significant protein fraction (almost 50% for hot trub and residual yeast), suggesting the possibility of using these wastes for recovery. Copyright © 2015 The Institute of Brewing & Distilling     

Microbiological,immunological, and histological changes in the gut of Salmonella Enteritidis-challenged rats fed goat cheese containing Lactobacillus rhamnosus EM1107

Cheeses are able to serve as suitable matrices for supplying probiotics to consumers, enabling appropriate conditions for bacteria to survive gastric transit and reach the gut, where they are assumed to promote beneficial processes. The present study aimed to evaluate the microbiological, immunological, and histological changes in the gut of Salmonella Enteritidis-challenged rats fed goat cheese supplemented with the probiotic strain Lactobacillus rhamnosus EM1107. Thirty male albino Wistar rats were randomly distributed into 5 experimental groups with 6 animals each: negative (NC) and positive (PtC) control groups, control goat cheese (CCh), goat cheese added with L. rhamnosus EM1107 (LrCh), and L. rhamnosus EM1107 only (EM1107). All animals, except NC group were challenged with Salmonella Enteritidis (10⁹ cfu in 1 mL of saline through oral gavage). Microbial composition was assessed with high-throughput 16S rRNA sequencing by means of Illumina MiSeq (Illumina, San Diego, CA). Nuclear factor kappa B (NF-κB) from the animal cecum tissue was determined by real-time PCR and interleukins (TNF-α, IL-1β, IL-10, and IFN-γ) by means of ELISA. Myeloperoxidase and malondialdehyde levels were determined biochemically. The administration of the L. rhamnosus EM1107 probiotic strain, either as a pure culture or added to a cheese matrix, was able to reduce Salmonella colonization in the intestinal lumen and lessen tissue damage compared with rats from PtC group. In addition, the use of cheese for the probiotic strain delivery (LrCh) was associated with a marked shift in the gut microbiota composition toward the increase of beneficial organisms such as Blautia and Lactobacillus and a reduction in NF-κB expression. These findings support our hypothesis that cheeses might be explored as functional matrices for the efficacious delivery of probiotic strains to consumers.     

A Markovian–Bayesian Network for Risk Analysis of High Speed and Conventional Railway Lines Integrating Human Errors

The article provides a new Markovian–Bayesian network model to evaluate the probability of accident associated with the circulation of trains along a given high speed or conventional railway line with special consideration to human error. This probability increases as trains pass throughout the different elements encountered along the line. A Bayesian network, made up of a sequence of several connected Bayesian subnetworks, is used. A subnetwork is associated with each element in the line that implies a concentrated risk of accident or produces a change in the driver's attention, such as signals, tunnel, or viaduct entries or exits, etc. Bayesian subnetworks are also used to reproduce segments without signals where some elements add continuous risks, such as rolling stock failures, falling materials, slope slides in cuttings and embankments, etc. All subnetworks are connected with the previous one and some of them are multi‐connected because some consequences are dependent on previous errors. Because driver's attention plays a crucial role, its degradation with driving time and the changes due to seeing light signals or receiving acoustic signals is taken into consideration. The model updates the driver's attention level and accumulates the probability of accident associated with the different elements encountered along the line. This permits us to generate a continuously increasing risk graph that includes continuous and sudden changes indicating where the main risks appear and whether or not an action must be taken by the infrastructure manager. Sensitivity analysis allows the relevant and irrelevant parameters to be identified avoiding wastes of time and money by concentrating safety improvement actions only on the relevant ones. Finally, some examples are used to illustrate the model. In particular, the case of the Orense–Santiago de Compostela line, where a terrible accident took place in 2013.     

A multi-criteria decision analysis framework for evaluating point-of-use water treatment alternatives

Despite significant progress on meeting global water targets, the lack of access to safe drinking water remains a significant problem in today’s world. Statistics from health agencies indicate that waterborne diseases are among the leading causes of health-related mortalities, particularly in developing nations. This paper examines the performance and applicability of various point-of-use (POU) water treatment alternatives, namely (i) solar disinfection; (ii) boiling of water; (iii) chlorination; (iv) disinfection–flocculation with a natural coagulant (powdered Moringa seeds); (v) filtration with ceramic pots; and (vi) biosand filtration. We evaluated the efficacy of each alternative using a set of criteria based on environmental sustainability, technological performance, financial viability, and social acceptability. We also integrated several multi-criteria decision analysis (MCDA) approaches to determine the most suitable water treatment method for a given community. The analytic hierarchy process (AHP) was implemented to elicit various preference structures and to generate the weights for the criteria. Subsequent ranking of the POU alternatives was then performed using the technique for order preference by similarity to ideal solutions (TOPSIS) method. Sensitivity analysis and visualization charts were developed to evaluate the impact of changes in preference ratings of each alternative with respect to the criteria. A case study was implemented in a rural area in the Philippines to determine the optimal POU alternatives given variations in AHP and TOPSIS input data. The resulting MCDA framework is flexible and can accommodate the inclusion of other alternatives and criteria, and it can also be generalized for other regions and applications.