Heavy Metals Bioremediation from Polluted Water by Glass-Ceramic Materials

The objective of this research was to study the removal of cadmium and lead from an aqueous solution through a biological treatment. For this purpose a glass-ceramic material was manufactured from industrial and urban wastes. Biofilms of microorganisms found in wastewater were developed on its surface, and continuous tests were conducted in the presence and absence of the biofilm to analyze the glass-ceramic's ability to remove the heavy metals from an aqueous environment. The results suggest that this bioremediation process, developed on an industrial scale, could represent an alternative to the chemical processes currently used.     

Comparative study of the colorants monascus and cochineal used in the preparation of gels made with various gelling agents

The possibilities of using monascus to colour gels were studied by comparing it with cochineal. Gels were prepared with four gelling agents—carrageenan, gellan, gelatine and xanthan—and their colour was measured with a Hunter Lab colorimeter. The equations relating L^* and h with the concentrations of sugar [SU] and colorant [COL] were deduced, and it was found that [COL] had more influence on colour than [SU]. In general, for these four gelling agents the colour of monascus gels is orange-red and the colour of cochineal gels is purplish red. The gels made with xanthan were always the lightest, whether they were made with cochineal or with monascus.     

Managing logical channel configurations in complex satellite architectures

As a result of the increased switching complexity of many communications satellites, often transponders are available with a variety of configuration options offering flexibility in power, bandwidth, and coverage. Many of these configurations share resources that prevent them from being simultaneously active, making it a challenge to understand and manage the satellite capacity inventory. In this paper we define the logical channel configuration (LCC) as an unambiguous unit of the inventory and present a novel method of modelling the interdependencies between these LCCs using linear algebra. In particular, a projector matrix is defined which can be used to update the activation state of all LCCs when the state of one or more of these is changed. As a result, a number of valid LCC scenarios can be easily generated and evaluated for optimal use of the satellite resources. Copyright © 2005 John Wiley & Sons, Ltd.     

Optimal management of logistic activities in multi-site environments

The new emerging area of Enterprise Wide Optimization (EWO) has focused the attention in effectively solving the combined production/distribution scheduling problem. The importance of logistic activities performed in multi-site environments comes from the relative magnitude of the associated transportation costs and the good chance of getting large savings on such expenses. This paper first develops an exact MILP mathematical formulation for the multiple vehicle time-window-constrained pickup and delivery (MVPDPTW) problem. The approach is able to account for many-to-many transportation requests, pure pickup and delivery tasks, heterogeneous vehicles and multiple depots. Optimal solutions for a variety of benchmark problems with cluster/random distributions of pickup and delivery locations and limited sizes in terms of customer requests and vehicles have been discovered. However, the computational cost exponentially grows with the number of requests. For large-scale m-PDPTW problems, a local search improvement algorithm steadily providing a better solution through two evolutionary steps is also presented. A neighborhood structure around the starting solution is generated by first allowing multiple request exchanges among nearby trips and then permitting the reordering of nodes on every individual route. If a better set of routes is found, both steps are repeated until no improved solution is discovered. Compact MILP mathematical formulations for both sub-problems have been developed and solved through an efficient branch-and-bound algorithm. A significant number of large-scale m-PDPTW benchmark problems, some of them including up to 100 transportation requests, were successfully solved in reasonable CPU times.     

Optimal design of gating systems by gradient search methods

A numerical optimization technique based on gradient-search is applied to obtain an optimal design of a typical gating system used for the gravity process to produce aluminum parts. This represents a novel application of coupling nonlinear optimization techniques with a foundry process simulator, and it is motivated by the fact that a scientifically guided search for better designs based on techniques that take into account the mathematical structure of the problem is preferred to commonly found trial-and-error approaches. The simulator applies the finite volume method and the VOF algorithm for CFD analysis. The direct gradient optimization algorithm, sequential quadratic programming (SQP), was used to solve both a 2D and a 3D gating system design problems using two design variables. The results clearly show the effectiveness of the proposed approach for finding high quality castings when compared with current industry practices.     

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     

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.     

High performance air pollution modeling for a power plant environment

The aim of this work is to provide a high performance air quality simulation using the STEM-II (Sulphur Transport Eulerian Model 2) program, a large-scale pollution modeling application. First, we optimize the sequential program with the aim of increasing data locality. Then, we parallelized the program using OpenMP directives for shared memory systems, and the MPI library for distributed memory machines. Performance results are presented for a SGI O2000 multiprocessor, a Fujitsu AP3000 multicomputer and a Cluster of PCs. Experimental results show that the parallel versions of the code achieve important reductions in the CPU time needed by each simulation. This will allow us to obtain results with adequate speed and reliability for the industrial environment where it is intended to be applied.