Adsorption of anionic dyes on chitosan beads. 1. The influence of the chemical structures of dyes and temperature on the adsorption kinetics

In this work, chitosan beads were synthesized in acidic medium and cross-linked in 1% glutaraldehyde solution. The characterization of the materials using TG/DTG, XRD, and BET surface areas showed that the beads did not modify their characteristics after the cross-linking reaction. The cross-linked beads were utilized as adsorbents for the removal of the yellow-, blue-, and red-anionic reactive dyes from aqueous solutions at pH 2.0. Adsorption of the yellow-dye increased from 25 to 50 degrees C. However, adsorption of the blue-dye decreased from 25 to 50 degrees C. Interestingly, the adsorption of the red-dye decreased from 25 to 35 degrees C and increased from 45 to 50 degrees C. The kinetic data were evaluated using an Avrami kinetic model, where the parameter n was related to the determination of changes in the adsorption mechanisms. Adsorption data of the dyes in relation to the contact time, the chemical structures of the dyes, and temperature were presented and were discussed.     

Multistep adsorption of anionic dyes on silica/chitosan hybrid. 1. Comparative kinetic data from liquid- and solid-phase models

In this work, a hybrid silica/chitosan was synthesized and characterized by nitrogen elemental analysis and thermal analysis (TG, DTG, DTA, and DSC) and BET surface area. The hybrid was used in adsorption studies of two anionic dyes from aqueous solutions. A rise of temperature accelerates mass transfer of dyes into the hybrid. However, the maximum adsorption capacities reach similar values from 25 to 55 degrees C. The kinetic data were first evaluated in relation to the decrease of the time-related residual concentration of the dyes in solution, where the second-order model has presented the best fitting. The solid-phase interaction of dye data presents a rough fitting to the traditional first-order Lagergren kinetic model. However, a modified Avrami kinetic equation was successfully fitted to the kinetic quantities, where from five to seven kinetic regions were found. A pore-diffusion model has also demonstrated that the diffusion is the rate-controlling interaction mechanism. However, the experimental-calculated comparative values are the best way to evaluate a specific aqueous- or solid-phase kinetic model.     

New Factorial Designs to Evaluate Chemisorption of Divalent Metals on Aminated Silicas

Adsorption processes of Cu(II), Co(II), and Hg(II) on two aminated silica gel surfaces with immobilized ethylenediamine and diethylenediamine groups were studied by a new 2(3) full factorial design. Two metal quantity levels, temperatures of 25 and 50 degrees C, and silica amounts of 100 and 200 mg were employed. Our study indicates that higher factorial design levels increase adsorption for all metals evaluated, with the exception of the mass parameter. Adsorption is also significantly affected by important antagonistic and synergistic effects involving all factors. Both functionalized silica gel surfaces present higher interactions and good perspectives in preconcentration studies for mercury. The factorial design results are also discussed in terms of some solvation properties for each of the metals studied. Copyright 2001 Academic Press.     

Bayesian knowledge base tuning

For a knowledge-based system that fails to provide the correct answer, it is important to be able to tune the system while minimizing overall change in the knowledge-base. There are a variety of reasons why the answer is incorrect ranging from incorrect knowledge to information vagueness to incompleteness. Still, in all these situations, it is typically the case that most of the knowledge in the system is likely to be correct as specified by the expert (s) and/or knowledge engineer (s). In this paper, we propose a method to identify the possible changes by understanding the contribution of parameters on the outputs of concern. Our approach is based on Bayesian Knowledge Bases for modeling uncertainties. We start with single parameter changes and then extend to multiple parameters. In order to identify the optimal solution that can minimize the change to the model as specified by the domain experts, we define and evaluate the sensitivity values of the results with respect to the parameters. We discuss the computational complexities of determining the solution and show that the problem of multiple parameters changes can be transformed into Linear Programming problems, and thus, efficiently solvable. Our work can also be applied towards validating the knowledge base such that the updated model can satisfy all test-cases collected from the domain experts.     

Evaluation of the effect of silicon on the carbonization process of Colombian semi-anthracites

The environmental impacts associated with the exploitation and transformation of fossil resources aggravate the planet's situation in terms of climate change. Due to this, this paper studies an alternative use of mineral coal as a precursor to obtaining new materials with different properties to the starting coals. The thermal degradation of two Colombian semi-anthracites is analyzed through the thermogravimetry (TG) technique coupled to a Fourier transform infrared spectroscopy (FTIR) equipment from room temperature (25 °C) to 900 °C, at a heating rate of 10 K min^?1 in an inert atmosphere. The catalytic effect of the addition of silicon to these samples before being subjected to a carbonization process is evaluated during this process. The results indicated that the primary reaction occurs in the temperature range between 400 and 680 °C, where the highest mass loss rate was observed. At the end of the heating process, the TG profile of the samples with silicon addition showed losses between 14.33 and 18.82% in mass, these values being slightly higher compared to the starting and demineralized samples. The release of water, light gases such as CO₂, CH₄, and species such as toluene, phenol and formic acid was identified in most of the samples. The presence of silica seems to favor the release of all these species, being more evident in one of the semi-anthracites studied. According to the results obtained, it is proved that the presence of silicon in samples subjected to carbonization processes has a catalytic effect that improves some characteristics of the new materials obtained, thus contributing to the use of carbon to get new materials.

     

Green Synthesis of Gold and Silver Nanoparticles Using Leaf Extract of Capsicum chinense Plant

So far, several studies have focused on the synthesis of metallic nanoparticles making use of extracts from the fruit of the plants from the genus Capsicum. However, as the fruit is the edible, and highly commercial, part of the plant, in this work we focused on the leaves, a part of the plant that is considered agro-industrial waste. The biological synthesis of gold (AuNPs) and silver (AgNPs) nanoparticles using aqueous extracts of root, stem and leaf of Capsicum chinense was evaluated, obtaining the best results with the leaf extract. Gold and silver nanoparticles synthesized using leaf extract (AuNPs-leaf and AgNPs-leaf, respectively) were characterized by UV-visible spectrophotometry (UV-Vis), Fourier Transform Infrared Spectroscopy with Attenuated Total Reflection (FTIR-ATR), X-ray Photoelectron Spectroscopy (XPS), Ultra Hight Resolution Scanning Electron Microscopy coupled to Energy-Dispersive X-ray spectroscopy (UHR-SEM-EDX) and Transmission Electron Microscopy (TEM), and tested for their antioxidant and antimicrobial activities. In addition, different metabolites involved in the synthesis of nanoparticles were analyzed. We found that by the use of extracts derived from the leaf, we could generate stable and easy to synthesize AuNPs and AgNPs. The AuNPs-leaf were synthesized using microwave radiation, while the AgNPs-leaf were synthesized using UV light radiation. The antioxidant activity of the extract, determined by ABTS, showed a decrease of 44.7% and 60.7% after the synthesis of the AuNPs-leaf and AgNPs-leaf, respectively. After the AgNPs-leaf synthesis, the concentration of polyphenols, reducing sugars and amino acids decreased by 15.4%, 38.7% and 46.8% in the leaf extract, respectively, while after the AuNPs-leaf synthesis only reducing sugars decreased by 67.7%. These results suggest that these groups of molecules are implicated in the reduction/stabilization of the nanoparticles. Although the contribution of these compounds in the synthesis of the AuNPs-leaf and the AgNPs-leaf was different. Finally, the AgNPs-leaf inhibited the growth of S. aureus, E. coli, S. marcescens and E. faecalis. All of them are bacterial strains of clinical importance due to their fast antibiotic resistance development.     

Optimal control of impulsive switched systems with minimum subsystem durations

This paper presents a new computational approach for solving optimal control problems governed by impulsive switched systems. Such systems consist of multiple subsystems operating in succession, with possible instantaneous state jumps occurring when the system switches from one subsystem to another. The control variables are the subsystem durations and a set of system parameters influencing the state jumps. In contrast with most other papers on the control of impulsive switched systems, we do not require every potential subsystem to be active during the time horizon (it may be optimal to delete certain subsystems, especially when the optimal number of switches is unknown). However, any active subsystem must be active for a minimum non-negligible duration of time. This restriction leads to a disjoint feasible region for the subsystem durations. The problem of choosing the subsystem durations and the system parameters to minimize a given cost function is a non-standard optimal control problem that cannot be solved using conventional techniques. By combining a time-scaling transformation and an exact penalty method, we develop a computational algorithm for solving this problem. We then demonstrate the effectiveness of this algorithm by considering a numerical example on the optimization of shrimp harvesting operations.     

Fusing multiple Bayesian knowledge sources

We address the problem of information fusion in uncertain environments. Imagine there are multiple experts building probabilistic models of the same situation and we wish to aggregate the information they provide. There are several problems we may run into by naively merging the information from each. For example, the experts may disagree on the probability of a certain event or they may disagree on the direction of causality between two events (e.g., one thinks A causes B while another thinks B causes A). They may even disagree on the entire structure of dependencies among a set of variables in a probabilistic network. In our proposed solution to this problem, we represent the probabilistic models as Bayesian Knowledge Bases (BKBs) and propose an algorithm called Bayesian knowledge fusion that allows the fusion of multiple BKBs into a single BKB that retains the information from all input sources. This allows for easy aggregation and de-aggregation of information from multiple expert sources and facilitates multi-expert decision making by providing a framework in which all opinions can be preserved and reasoned over.     

An introduction to the k-defect polynomials

The 0-defect polynomial of a graph is just the chromatic polynomial. This polynomial has been widely studied in the literature. Yet little is known about the properties of k-defect polynomials of graphs in general, when 0 < k ≤ |E(G)|. In this survey we give some properties of k-defect polynomials, in particular we highlight the properties of chromatic polynomials which also apply to k-defect polynomials. We discuss further research which can be done on the k-defect polynomials.     

A proteomic strategy for the identification of caspase-associating proteins

We report the efficient in vivo labelling of caspases expressed inside apoptotic HeLa cells using fluoromethyl ketone (fmk)-containing probes; preliminary results indicated that these probes may be used to identify caspase-associating proteins.