A socioeconomic model for managing water resources in Alicante,southeast Spain

The study analyzes variables that influence the water management model based on a simultaneous relationship between competing demands in the Marina Baja of Alicante, using a methodology that directly links together urban and irrigation demands, making them relevant to each other from a socioeconomic point of view. The paper identifies the relevant variables of this model and the agent behaviour in a closed and joint system. It also aims to demonstrate that by considering water demands for different yet simultaneous uses and regarding clean and reclaimed waters as integrated resources, the system could remain in equilibrium without external water supplies.     

Water network cost optimization in a paper mill based on a new library of mathematical models

The increasing costs associated with water supply and the disposal of wastewater has stimulated industries to seek more efficient water management systems. Mathematical modelling and simulation can be a very valuable tool for the study of the multiple alternatives available whilst assessing optimum solutions for water management in industry. This study introduces a new steady state model library able to reproduce industrial water circuits. It has been implemented in a novel software framework for the representation, simulation and optimization of industrial water networks. A water circuit representing a paper mill has been modelled and simulated showing the capability to reproduce real case studies. Alternative scenarios for the water network have also been tested to assess the capability of the models to optimize water circuits minimizing total cost.     

Use of sesame stalk biomass for the removal of Ni(II) and Zn(II) from aqueous solutions

In this study an agricultural residue, sesame stalk, was evaluated for the removal of Ni(II) and Zn(II) metal ions from aqueous solutions. Biosorption studies were carried out at different pH, biosorbent dosage, initial metal ion concentrations, contact time, and solution temperature to determine the optimum conditions. The experimental data were modeled by Langmuir, Freundlich, Dubinin-Radushkevich (D-R) and Temkin isotherm models. Langmuir model resulted in the best fit of the biosorption data. The pseudo-first-order and pseudo-second-order kinetic models were used to describe the kinetic data and to evaluate rate constants. The best correlation was provided by the second-order kinetic model. The thermodynamic parameters such as ΔG°, ΔH° and ΔS° were calculated for predicting the nature of adsorption. The experimental results showed that sesame stalk can be used as an effective and low-cost biosorbent precursor for the removal of heavy metal ions from aqueous solutions.     

Anaerobic monodigestion of poultry manure: determination of operational parameters for CSTR

In this work the anaerobic monodigestion for the treatment of turkey manure was evaluated, without its codigestion with another substrate. The effect of the organic loading rate (OLR) and the substrate concentration (high total solids (TS) concentration) or product concentration (high volatile fatty acids (VFA) and/or ammonia (NH(3)-N) concentrations) was studied. The results show that for a continuous stirred tank reactor (CSTR) operation, a maximum of 40 g/L of TS and 4.0 g/L of ammonium (NH(4)(+)) was required. In addition, the maximum organic loading rate (OLR) will not exceed 1.5 kg VS/m(3)d. Higher TS and NH(4)(+) concentrations and OLR lead to a reduction on the methane productivity and volatile solids (VS) removal. During the CSTR operation, a high alkalinity concentration (above 10 g/L CaCO(3)) was found; this situation allowed maintaining a constant and appropriate pH (close to 7.8), despite the VFA accumulation. In this sense, the alkalinity ratio (α) is a more appropriate control and monitoring parameter of the reactor operation compared to pH. Additionally, with this parameter a VS removal of 80% with a methane productivity of 0.50 m(3)(CH4)/m(3)(R)d is achieved.     

Kidney injury and cell therapy: Preclinical study

The aim of this study is to show histological and immunofluorescence analysis of renal parenchyma of agoutis affected by gentamicin‐induced renal disease after the infusion of bone marrow mononuclear cells (BMMC) stained with Hoechst®. Nine agouti's males were divided into three groups: Test group (TG): renal disease by gentamicin induced (n = 3), cell therapy group (CTG): renal disease by gentamicin induced and BMMC infusion (n = 3), and control group (CG): nonrenal disease and BMMC infusion (n = 3). TG and CTG were submitted to the protocol of renal disease induction using weekly application of gentamicin sulfate for 4 months. CG and CTG received a 1 × 108 BMMC stained with Hoechst and were euthanized for kidney examination 21 days after BMMC injection and samples were collected for histology and immunofluorescence analysis. Histological analysis demonstrated typical interstitial lesions in kidney similarly to human disease, as tubular necrosis, glomerular destruction, atrophy tubular, fibrotic areas, and collagen deposition. We conclude that histological analysis suggest a positive application of agouti's as a model for a gentamicin inducing of kidney disease, beyond the immunofluorescence analysis suggest a significant migration of BMMC to sites of renal injury in CTG. Microsc. Res. Tech., 2012. © 2011 Wiley Periodicals, Inc.     

Biodegradation of 4-methylaniline in a sequencing batch reactor

The biodegradation of the aromatic amine 4-methylaniline (4MA) using an aerobic sequencing batch reactor was evaluated. The specific degradation rate showed an exponential increase during the acclimation of the microorganisms reaching a maximal value of 34 mg 4MA/VSS/h. After the acclimation, the process showed a stable operation. A high similarity index was observed, indicating a low variation in the population diversity. During this period, the physicochemical parameters demonstrated a stable operation of the reactor.     

Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules

This paper presents a proposal for the extraction of association rules called G3PARM (Grammar-Guided Genetic Programming for Association Rule Mining) that makes the knowledge extracted more expressive and flexible. This algorithm allows a context-free grammar to be adapted and applied to each specific problem or domain and eliminates the problems raised by discretization. This proposal keeps the best individuals (those that exceed a certain threshold of support and confidence) obtained with the passing of generations in an auxiliary population of fixed size n. G3PARM obtains solutions within specified time limits and does not require the large amounts of memory that the exhaustive search algorithms in the field of association rules do. Our approach is compared to exhaustive search (Apriori and FP-Growth) and genetic (QuantMiner and ARMGA) algorithms for mining association rules and performs an analysis of the mined rules. Finally, a series of experiments serve to contrast the scalability of our algorithm. The proposal obtains a small set of rules with high support and confidence, over 90 and 99% respectively. Moreover, the resulting set of rules closely satisfies all the dataset instances. These results illustrate that our proposal is highly promising for the discovery of association rules in different types of datasets.     

Second Life as a support element for learning electronic related subjects: A real case

Looking for more active and motivating methodological alternatives from the students’ perspective, which promote analysis and investigation abilities that make the student a more participative agent and some learning processes are facilitated, a practical study was conducted in the University of La Sabana (Chía, Colombia), in Computing Engineering (INF) and Agroindustrial Production Engineering (IPA) academic programs under the guiding question: Is Second Life an attractive tool for students, does it increment motivation, promote participation and facilitate learning processes in electronic related subjects in Engineering degrees?Second Life (SL) platform was then used as a traditional on-site class complement in electronic related subjects. A follow up was conducted with several groups during a year and a half, some students followed the subject with the traditional on-site methodology and others did it following a mixed methodology that combined traditional on-site lessons with virtual sessions trough SL, making a comparison and applying a quantitative as well as a qualitative methodology for the information analysis and recollection.After the specified study period it was found that using SL as part of the methodology, increments motivation toward electronic related subjects, and promotes participation and investigation, due to the fact that this tool makes learning possible in a funnier, more interactive and deeper way than if it had been taught in a master class. Having real-time access from a virtual classroom to all types of audiovisual information, helps more senses get involved in the learning process, making it more effective; nevertheless a weakness was detected related to the attention and concentration: students tend to get distracted, because their classroom is the computer and from there they have access not only to the many worlds of SL but to all the social networks and the Internet in general.     

A genetic algorithm approach for group formation in collaborative learning considering multiple student characteristics

Considering that group formation is one of the key processes in collaborative learning, the aim of this paper is to propose a method based on a genetic algorithm approach for achieving inter-homogeneous and intra-heterogeneous groups. The main feature of such a method is that it allows for the consideration of as many student characteristics as may be desired, translating the grouping problem into one of multi-objective optimization. In order to validate our approach, an experiment was designed with 135 college freshmen considering three characteristics: an estimate of student knowledge levels, an estimate of student communicative skills, and an estimate of student leadership skills. Results of such an experiment allowed for the validation, not only from the computational point of view by measuring the algorithmic performance, but also from the pedagogical point of view by measuring student outcomes, and comparing them with two traditional group formation strategies: random and self-organized.