A New Bi-Functional Derivative of Polyethylene Glycol as Molecular Carrier for Eugenol and Ibuprofen

Eugenol (EU) and ibuprofene (IBU) were covalently bound to a bi-functionalized PEG, used as molecular carrier of drugs and the release kinetics of the two bioactive molecules was studied in vitro in buffer solution at pH 7.4, in simulated gastric fluid and in mouse plasma. The hydrolysis studies showed a specific cleavage dependent on the pH of the medium and by the presence of proteolytic enzymes in mouse plasma. Studies in vitro on the release of the parent drug from this double prodrug in various media, indicate that the adduct may be sufficiently stable to pass intact the gastrointestinal tract and release into the circulation EU and IBU. Many advantages may be achieved by the synthesis of the prodrug EU-PEG-IBU related to synergistic analgesic and anti-inflammatory effects, to the reduction of the adverse reactions and the improvement of the chemical-physical properties of the parent drugs

Retention of arsenic and selenium compounds present in coal combustion and gasification flue gases using activated carbons

7 pages, 7 figures, 6 tables.-- Printed version published Aug 2007.The emission of potentially toxic compounds of arsenic and selenium present in flue gases from coal combustion and gasification processes has led to the need for gas cleaning systems capable of reducing their content. This work is focused on the capture of these elements in activated carbons which have proven to have good retention capacities for mercury compounds in gas phase. Two commercial activated carbons (Norit RBHG3 and Norit RB3) and a carbon prepared via activation of a pyrolysed coal (CA) were tested in simulated coal combustion and gasification atmospheres in a laboratory scale reactor. Arsenic and selenium compounds were retained to different extents on these carbons, retention efficiency depending mainly on the speciation of the element, which in turn depends on the gas atmosphere. Arsenic retention was similar in both combustion and gasification atmospheres unlike selenium retention. Moreover the retention of arsenic was lower than that of selenium.This work was carried out with the financial support of ECSC (7220-ED/095). We are also grateful to our colleagues in ICB (CSIC) R. Juan and C. Ruiz who prepared the CA activated carbon and Amelia Martínez Alonso of INCAR who assisted us in the textural characterization.Peer reviewe

integrated dynamic energy management for steel production

Abstract The steel industry is an important consumer of electrical energy having a significant impact on the electricity network and accounting to a significant part of production costs. Thus, there is the opportunity of closer cooperation between grid operators and steel industry to improve the power consumption prediction and actively contribute to a secure network operation. This paper aims to describe an overall dynamical approach for electricity demand monitoring and timely reactions to the grid situation, to avoid non flexible equipment disconnection, financial fines when deviating from energy contingent and contributing to the grid stability. Energy management, simulation, decision support procedures and process control tools will be integrated in an agent based system able to predict and manage power consumption

Improving the Stability of the Variable Selection with Small Datasets in Classification and Regression Tasks

Within the design of a machine learning-based solution for classification or regression problems, variable selection techniques are often applied to identify the input variables, which mainly affect the considered target. The selection of such variables provides very interesting advantages, such as lower complexity of themodel and of the learning algorithm, reduction of computational time and improvement of performances. Moreover, variable selection is useful to gain a profound knowledge of the considered problem. High correlation in variables often produces multiple subsets of equally optimal variables, which makes the traditional method of variable selection unstable, leading to instability and reducing the confidence of selected variables. Stability identifies the reproducibility power of the variable selection method. Therefore, having a high stability is as important as the high precision of the developed model. The paper presents an automatic procedure for variable selection in classification (binary and multi-class) and regression tasks, which provides an optimal stability index without requiring any a priori information on data. The proposed approach has been tested on different small datasets, which are unstable by nature, and has achieved satisfactory results

Genetic operators impact on genetic algorithms based variable selection

This paper faces the problem of variables selection through the use of a genetic algorithm based metaheuristic approach. The method is based on the evolution of a population of variables subsets, which is led by the genetic operators determining their selection and improvement through the algorithm generations. The impact of different genetic operators expressly designed for this purpose is assessed through a test campaign. The results show that the use of specific operators can lead to remarkable improvements in terms of selection quality