Simultaneous sulfide and acetate oxidation under denitrifying conditions using an inverse fluidized bed reactor

BACKGROUND: Simultaneous removal of sulfur, nitrogen and carbon compounds from wastewaters is a commercially important biological process. The objective was to evaluate the influence of the CH₃COO^?/NO₃^? molar ratio on the sulfide oxidation process using an inverse fluidized bed reactor (IFBR). RESULTS: Three molar ratios of CH₃COO^?/NO₃^? (0.85, 0.72 and 0.62) with a constant S^2?/NO₃^? molar ratio of 0.13 were evaluated. At a CH₃COO^?/NO₃^? molar ratio of 0.85, the nitrate, acetate and sulfide removal efficiencies were approximately 100%. The N₂ yield (g N₂ g^?1 NO₃^?‐N consumed) was 0.81. Acetate was mineralized, resulting in a yield of 0.65 g inorganic‐C g^?1 CH₃COO^?‐C consumed. Sulfide was partially oxidized to S⁰, and 71% of the S^2? consumed was recovered as elemental sulfur by a settler installed in the IFBR. At a CH₃COO^?/NO₃^? molar ratio of 0.72, the efficiencies of nitrate, acetate and sulfide consumption were of 100%, with N₂ and inorganic‐C yields of 0.84 and 0.69, respectively. The sulfide was recovered as sulfate instead of S⁰, with a yield of 0.92 g SO₄^2?‐S g^?1 S^2? consumed. CONCLUSIONS: The CH₃COO^?/NO₃^? molar ratio was shown to be an important parameter that can be used to control the fate of sulfide oxidation to either S⁰ or sulfate. In this study, the potential of denitrification for the simultaneous removal of organic matter, sulfide and nitrate from wastewaters was demonstrated, obtaining CO₂, S⁰ and N₂ as the major end products. Copyright © 2008 Society of Chemical Industry     

Biofiltration of toluene in the absence and the presence of ethyl acetate under continuous and intermittent loading

BACKGROUND: Two peat biofilters were used for the removal of toluene from air for one year. One biofilter was fed with pure toluene and the other received 1:1 (by weight) ethyl acetate:toluene mixture. RESULTS: The biofilters were operated under continuous loading: the toluene inlet load (IL) at which 80% removal occurred was 116 g m^?3 h^?1 at 57 s gas residence time. Maximum elimination capacity of 360 g m^?3 h^?1 was obtained at an IL of 745 g m^?3 h^?1. The elimination of toluene was inhibited by the presence of ethyl acetate. Intermittent loading, with pollutants supplied for 16 h/day, 5 days/week, did not significantly affect the removal efficiency (RE). Biomass was fully activated in 2 h after night closures, but 6 h were required to recover RE after weekend closures. Live cell density remained relatively constant over the operational period, while the dead cell fraction increased. Finally, a 15 day starvation period was applied and operation then re‐started. Performance was restored with similar re‐acclimatization period to that after weekend closures, and a reduction in dead cell fraction was observed. CONCLUSION: This study demonstrates the capacity of the system to handle intermittent loading conditions that are common in industrial practices, including long‐term starvation. Copyright © 2008 Society of Chemical Industry     

The effect of probability of coalescence on the evolution of bubble sizes in a turbulent pipeline flow: A numerical study

A population balance method in which continuum and discrete phases are integrated is developed to simulate the evolution of polydisperse population of bubbles in a turbulent pipeline flow. The investigation is focused on the effect of the coalescence efficiency on this evolution. A dilute system of bubbles under microgravity conditions is considered. It is found that if the initial coalescence efficiency is low, a slight increase produces a significant effect on the bubble coalescence rate, and thus on the evolution of the population. If, however, the initial coalescence efficiency is high, its increase results in a marginal effect on the way the population evolves. The results of simulations are validated against experimental data on the population mean.     

Karyotype description of Pomacea patula catemacensis (Caenogastropoda, Ampullariidae), with an assessment of the taxonomic status of Pomacea patula.

Mitotic chromosomes of the freshwater snail Pomacea patula catemacensis (Baker 1922) were analyzed on gill tissue of specimens from the type locality (Lake Catemaco, Mexico). The diploid number of chromosomes is 2n = 26, including nine metacentric and four submetacentric pairs; therefore, the fundamental number is FN = 52, No sex chromosomes could be identified. The same chromosome number and morphology were already reported for P. flagellata, i.e., the other species of the genus living in Mexico. The basic haploid number for family Ampullariidae was reported to be n = 14 in the literature; so, its reduction to n = 13 is probably an apomorphy of the Mexican Pomacea snails. Lanistes bolteni, from Egypt, also shows n = 13, but its karyotype is much more asymmetrical, and seems to have evolved independently from P. flagellata and P. patula catemacensis. The nominotypical subspecies, P. patula patula (Reeve 1856), is a poorly known taxon, whose original locality is unknown. A taxonomical account is presented here, and a Mexican origin postulated as the most parsimonious hypothesis.     

Introducing fuzziness in object models and database interfaces through aspects

Imperfection in information can be considered a crosscutting concern that manifests itself in diverse kinds of imprecision, uncertainty, or inconsistency in the data models of a software system. The extension of existing programming and querying interfaces for the different aspects of information imperfection requires a proper modularization of the different concerns of numerical imprecision handling, so that the extensions do not interfere with existing programming practices and do not obscure the original design. Aspect‐oriented design (AOD) enables such a form of nonintrusive extensions to be added to existing software libraries, clearly separating fuzziness or other imperfections in data as a differentiated concern that can be considered from the early phases of development. In this article, a general framework for aspect‐based extension of data models and fuzzy databases is described, and some design and implementation issues of such AOD‐based extensions on OJB database libraries are described as a case study. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 1199–1216, 2006.     

Beast methodology: An agile testing methodology for multi-agent systems based on behaviour driven development

This paper presents a testing methodology to apply Behaviour Driven Development (BDD) techniques while developing Multi-Agent Systems (MASs), termed BEhavioural Agent Simple Testing (BEAST) Methodology. This methodology is supported by the open source framework (BEAST Tool) which automatically generates test cases skeletons from BDD scenarios specifications. The developed framework allows the testing of MASs based on JADE or JADEX platforms. In addition, this framework offers a set of configurable Mock Agents with the aim of being able to execute tests while the MAS is under development. The BEAST Methodology presents transparent traceability from user requirements to test cases. Thus, the stakeholders can be aware of the project status. The methodology and the associated tool have been validated in the development of a MAS for fault diagnosis in FTTH (Fiber To The Home) networks. The results have been measured in quantifiable way obtaining a reduction of the tests implementation time.     

An internet of things–based personal device for diabetes therapy management in ambient assisted living (AAL)

Diabetes therapy management in AAL environments, such as old people and diabetes patients homes, is a very difficult task since many factors affect a patient’s blood sugar levels. Factors such as illness, treatments, physical and psychological stress, physical activity, drugs, intravenous fluids and change in the meal plan cause unpredictable and potentially dangerous fluctuations in blood sugar levels. Right now, operations related to dosage are based on insulin infusion protocol boards, which are provided by physicians to the patients. These boards are not considering very influential factors such as glycemic index from the diet, consequently patients need to estimate the dosage leading to dose error, which culminates in hyperglycemia and hypoglycemia episode. Therefore, right insulin infusion calculation needs to be supported by the next generation of personal-care devices. For this reason, a personal device has been developed to assist and consider more factors in the insulin therapy dosage calculation. The proposed solution is based on Internet of things in order to, on the one hand, support a patient’s profile management architecture based on personal RFID cards and, on the other hand, provide global connectivity between the developed patient’s personal device based on 6LoWPAN, nurses/physicians desktop application to manage personal health cards, glycemic index information system, and patient’s web portal. This solution has been evaluated by a multidisciplinary group formed by patients, physicians, and nurses.     

Algorithm for Increasing the Speed of Evolutionary Optimization and its Accuracy in Multi-objective Problems

Optimization algorithms are important tools for the solution of combinatorial management problems. Nowadays, many of those problems are addressed by using evolutionary algorithms (EAs) that move toward a near-optimal solution by repetitive simulations. Sometimes, such extensive simulations are not possible or are costly and time-consuming. Thus, in this study a method based on artificial neural networks (ANN) is proposed to reduce the number of simulations required in EAs. Specifically, an ANN simulator is used to reduce the number of simulations by the main simulator. The ANN is trained and updated only for required areas in the decision space. Performance of the proposed method is examined by integrating it with the non-dominated sorting genetic algorithm (NSGAII) in multi-objective problems. In terms of density and optimality of the Pareto front, the hybrid NSGAII-ANN is able to extract the Pareto front with much less simulation time compared to the sole use of the NSGAII algorithm. The proposed NSGAII-ANN methodology was examined using three standard test problems (FON, KUR, and ZDT1) and one real-world problem. The latter addresses the operation of a reservoir with two objectives (meeting demand and flood control). Thus, based on this study, use of the NSGAII-ANN integrative algorithm in problems with time-consuming simulators reduces the required time for optimization up to 50 times. Results of the real-world problem, despite lower computational-time requirements, show a performance similar to that achieved in the aforementioned test problems.     

Acoustic scattering solver based on single level FMM for multi-GPU systems

In this paper, we present a heterogeneous parallel solver of a high frequency single level Fast Multipole Method (FMM) for the Helmholtz equation applied to acoustic scattering. The developed solution uses multiple GPUs to tackle the compute bound steps of the FMM (aggregation, disaggregation, and near interactions) while the CPU handles a memory bound step (translation) using OpenMP. The proposed solver performance is measured on a workstation with two GPUs (NVIDIA GTX 480) and is compared with that of a distributed memory solver run on a cluster of 32 nodes (HP BL465c) with an Infiniband network. Some energy efficiency results are also presented in this work.     

mfERG_LAB: Software for processing multifocal electroretinography signals

The multifocal electroretinography technique consists of performing sectorized light excitation of the retina and capturing the resulting evoked potential. This provides functional localized information about the state of the retinal neurons. Analysis of multifocal electroretinography signals can be used for diagnosing different types of optic neuropathies (glaucomatous, demyelinating and ischemic ethiology). In order to obtain a reliable diagnosis, it is necessary to apply advanced processing algorithms (morphological, frequency and time-frequency analysis, etc.) to the multifocal electroretinography signal. This paper presents a software application developed in MATLAB(?) (MathWorks Inc., MA) designed to perform advanced multifocal electroretinography signal analysis and classification. This intuitive application, mfERG_LAB, is used to plot the signals, apply various algorithms to them and present the data in an appropriate format. The application's computational power and modular structure make it suitable for use in clinical settings as a powerful and innovative diagnostic tool, as well as in research and teaching settings as a means of assessing new algorithms.