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     

Inverted Solution Processable OLEDs Using a Metal Oxide as an Electron Injection Contact.

A new type of bottom‐emission electroluminescent device is described in which a metal oxide is used as the electron‐injecting contact. The preparation of such a device is simple. It consists of the deposition of a thin layer of a metal oxide on top of an indium tin oxide covered glass substrate, followed by the solution processing of the light‐emitting layer and subsequently the deposition of a high‐workfunction (air‐stable) metal anode. This architecture allows for a low‐cost electroluminescent device because no rigorous encapsulation is required. Electroluminescence with a high brightness reaching 5700 cd m^–2 is observed at voltages as low as 8 V, demonstrating the potential of this new approach to organic light‐emitting diode (OLED) devices. Unfortunately the device efficiency is rather low because of the high current density flowing through the device. We show that the device only operates after the insertion of an additional hole‐injection layer in between the light‐emitting polymer (LEP) and the metal anode. A simple model that explains the experimental results and provides avenues for further optimization of these devices is described. It is based on the idea that the barrier for electron injection is lowered by the formation of a space–charge field over the metal‐oxide–LEP interface due to the build up of holes in the LEP layer close to this interface.     

Optimal and self‐tuning fusion Kalman filters for discrete‐time stochastic singular systems

Based on the optimal fusion estimation algorithm weighted by scalars in the linear minimum variance sense, a distributed optimal fusion Kalman filter weighted by scalars is presented for discrete‐time stochastic singular systems with multiple sensors and correlated noises. A cross‐covariance matrix of filtering errors between any two sensors is derived. When the noise statistical information is unknown, a distributed identification approach is presented based on correlation functions and the weighted average method. Further, a distributed self‐tuning fusion filter is given, which includes two stage fusions where the first‐stage fusion is used to identify the noise covariance and the second‐stage fusion is used to obtain the fusion state filter. A simulation verifies the effectiveness of the proposed algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

Note on ‘Construction of Double Sampling s‐Control Charts for Agile Manufacturing’

He and Grigoryan (Quality and Reliability Engineering International 2002; 18 :343–355) formulated the design of a double‐sampling (DS) s control chart as an optimization problem and solved it with a genetic algorithm. They concluded that the DS s control charts can be a more economically preferable alternative in detecting small shifts than traditional s control charts. We explain that, since they only considered the average sample size when the process is in control, their conclusion is questionable. Copyright © 2006 John Wiley & Sons, Ltd.     

A distributed adverse drug reaction detection system using intelligent agents with a fuzzy recognition‐primed decision model

Discovering unknown adverse drug reactions (ADRs) in postmarketing surveillance as early as possible is highly desirable. Nevertheless, current postmarketing surveillance methods largely rely on spontaneous reports that suffer from serious underreporting, latency, and inconsistent reporting. Thus these methods are not ideal for rapidly identifying rare ADRs. The multiagent systems paradigm is an emerging and effective approach to tackling distributed problems, especially when data sources and knowledge are geographically located in different places and coordination and collaboration are necessary for decision making. In this article, we propose an active, multiagent framework for early detection of ADRs by utilizing electronic patient data distributed across many different sources and locations. In this framework, intelligent agents assist a team of experts based on the well‐known human decision‐making model called Recognition‐Primed Decision (RPD). We generalize the RPD model to a fuzzy RPD model and utilize fuzzy logic technology to not only represent, interpret, and compute imprecise and subjective cues that are commonly encountered in the ADR problem but also to retrieve prior experiences by evaluating the extent of matching between the current situation and a past experience. We describe our preliminary multiagent system design and illustrate its potential benefits for assisting expert teams in early detection of previously unknown ADRs. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 827–845, 2007.     

Treatment of low turbidity water by sweep coagulation using bentonite

A novel strategy of sweep coagulation to treat low turbidity water is presented herein. Study findings demonstrated that an Na⁺‐saturated bentonite with medium cation exchange capacity (CEC) resulted in significant turbidity removal at a bentonite dosage of 30 mg dm^?3. Bentonite dispersion with fully delaminated platelets tended to undergo a more porous type of coagulation with intense face‐to‐face interactions of platelets and effectively entrapped TiO₂ particles in band‐type structures. This type of coagulation usually results in a large volume of settled flocs with a fluffy structure and excellent turbidity removal efficiency for sweep coagulation. The sign and magnitude of electrical charge on TiO₂ particles has a minor effect on the efficiency of sweep coagulation. Copyright © 2005 Society of Chemical Industry     

Two‐phase production of cyclohexene and cyclooctene oxides in water as an approach to pollution prevention

Liquid–liquid two‐phase epoxidation from cyclohexene and cyclooctene in aqueous potassium peroxymonosulfate (commercially available as Oxone^®) solution was studied as an application in pollution prevention. To avoid potential emissions of volatile organic compounds an aqueous solution was employed to replace the usual chlorinated solvents used in epoxide production. A droplet column reactor and stirred tank reactor were used to investigate two‐phase synthesis of epoxide. An aqueous Oxone^® solution was used to oxidize a dispersion of alkene droplets and form epoxide. The study of aqueous epoxidation in both reactors showed that the epoxidation of alkenes can be represented as a first order reaction with respect to alkene. The salting out effect of Oxone^® concentration was studied in both reactors and found to be very similar at optimal conditions. In comparing the two reactors, it was found that the droplet column reactor produces larger quantities of product per unit reactor volume for the same reaction time. The objective of this study is to provide an alternative reactor design and synthesis route that can meet pollution prevention goals. Copyright © 2004 Society of Chemical Industry