On the release of metronidazole from natural rubber latex membranes

The controlled release of drugs can be efficient if a suitable encapsulation procedure is developed, which requires biocompatible materials to hold and release the drug. In this study, a natural rubber latex (NRL) membrane is used to deliver metronidazole (MET), a powerful antiprotozoal agent. MET was found to be adsorbed on the NRL membrane, with little or no incorporation into the membrane bulk, according to energy dispersive X-ray spectroscopy. X-ray diffraction and FTIR spectroscopy data indicated that MET retained its structural and spectroscopic properties upon encapsulation in the NRL membrane, with no molecular-level interaction that could alter the antibacterial activity of MET. More importantly, the release time of MET in a NRL membrane in vitro was increased from the typical 6-8 h for oral tablets or injections to ca. 100 h. The kinetics of the drug release could be fitted with a double exponential function, with two characteristic times of 3.6 and 29.9 h. This is a demonstration that the induced angiogenesis known to be provided by NRL membranes can be combined with a controlled release of drugs, whose kinetics can be tailored by modifying experimental conditions of membrane fabrication for specific applications. (C) 2010 Elsevier B.V. All rights reserved.

Elastomeric Composites Based on Ethylene-Propylene-Diene Monomer Rubber and Conducting Polymer-Modified Carbon Black

Thermally stable elastomeric composites based on ethylene-propylene-diene monomer (EPDM) and conducting polymer-modified carbon black (CPMCB) additives were produced by casting and crosslinked by compression molding. CPMCB represent a novel thermally stable conductive compound made via ""in situ"" deposition of intrinsically conducting polymers (ICP) such as polyaniline or polypyrrole on carbon black particles. Thermogravimetric analysis showed that the composites are thermally stable with no appreciable degradation at ca. 300 degrees C. Incorporating CPMCB has been found to be advantageous to the processing of composites, as the presence of ICP lead to a better distribution of the filler within the rubber matrix, as confirmed by morphological analysis. These materials have a percolation threshold range of 5-10 phr depending on the formulation and electrical dc conductivity values in the range of 1 x 10(-3) to 1 x 10(-2) S cm(-1) above the percolation threshold. A less pronounced reinforcing effect was observed in composites produced with ICP-modified additives in relation to those produced only with carbon black. The results obtained in this study show the feasibility of this method for producing stable, electrically conducting composites with elastomeric characteristics. POLYM. COMPOS., 30:897-906, 2009. (C) 2008 Society of Plastics Engineers

The Mobility of Chondroitin Sulfate in Articular and Artificial Cartilage Characterized by (13)C Magic-Angle Spinning NMR Spectroscopy

We have studied the molecular dynamics of one of the major macromolecules in articular cartilage, chondroitin sulfate. Applying (13)C high-resolution magic-angle spinning NMR techniques, the NMR signals of all rigid macromolecules in cartilage can be suppressed, allowing the exclusive detection of the highly mobile chondroitin sulfate. The technique is also used to detect the chondroitin sulfate in artificial tissue-engineered cartilage. The tissue-engineered material that is based on matrix producing chondrocytes cultured in a collagen gel should provide properties as close as possible to those of the natural cartilage. Nuclear relaxation times of the chondroitin sulfate were determined for both tissues. Although T(1) relaxation times are rather similar, the T(2) relaxation in tissue-engineered cartilage is significantly shorter. This suggests that the motions of chondroitin sulfate in data:rat and artificial cartilage different. The nuclear relaxation times of chondroitin sulfate in natural and tissue-engineered cartilage were modeled using a broad distribution function for the motional correlation times. Although the description of the microscopic molecular dynamics of the chondroitin sulfate in natural and artificial cartilage required the identical broad distribution functions for the correlation times of motion, significant differences in the correlation times of motion that are extracted from the model indicate that the artificial tissue does not fully meet the standards of the natural ideal. This could also be confirmed by macroscopic biomechanical elasticity measurements. Nevertheless, these results suggest that NMR is a useful tool for the investigation of the quality of artificially engineered tissue. (C) 2010 Wiley Periodicals, Inc. Biopolymers 93: 520-532, 2010.

Extraction of cellulose whiskers from cassava bagasse and their applications as reinforcing agent in natural rubber

In this work cassava bagasse, a by-product of cassava starch industrialization was investigated as a new raw material to extract cellulose whiskers. This by-product is basically constituted of cellulose fibers (17.5 wt%) and residual starch (82 wt%). Therefore, this residue contains both natural fibers and a considerable quantity of starch and this composition suggests the possibility of using cassava bagasse to prepare both starch nanocrystals and cellulose whiskers. In this way, the preparation of cellulose whiskers was investigated employing conditions of sulfuric acid hydrolysis treatment found in the literature. The ensuing materials were characterized by transmission electron microscopy (TEM) and X-ray diffraction experiments. The results showed that high aspect ratio cellulose whiskers were successfully obtained. The reinforcing capability of cellulose whiskers extracted from cassava bagasse was investigated using natural rubber as matrix. High mechanical properties were observed from dynamic mechanical analysis. (C) 2010 Elsevier B.V. All rights reserved.

Phenolic matrices and sisal fibers modified with hydroxy terminated polybutadiene rubber: Impact strength, water absorption, and morphological aspects of thermosets and composites

The aim of the present work was to investigate the toughening of phenolic thermoset and its composites reinforced with sisal fibers, using hydroxyl-terminated polybutadiene rubber (HTPB) as both impact modifier and coupling agent. Substantial increase in the impact strength of the thermoset was achieved by the addition 10% of HTPB. Scanning electron microscopy (SEM) images of the material with 15% HTPB content revealed the formation of some rubber aggregates that reduced the efficiency of the toughening mechanism. In composites, the toughening effect was observed only when 2.5% of HTPB was added. The rubber aggregates were found located mainly at the matrix-fiber interface suggesting that HTPB could be used as coupling agent between the sisal fibers and the phenolic matrix. A composite reinforced with sisal fibers pre-impregnated with HTPB was then prepared; its SEM images showed the formation of a thin coating of HTPB on the surface of the fibers. The ability of HTBP as coupling agent between sisal fibers and phenolic matrix was then investigated by preparing a composite reinforced with sisal fibers pre-treated with HTPB. As revealed by its SEM images, the HTPB pre-treatment of the fibers resulted on the formation of a thin coating of HTPB on the surface of the fibers, which provided better compatibility between the fibers and the matrix at their interface, resulting in a material with low water absorption capacity and no loss of impact strength. (C) 2009 Elsevier B.V. All rights reserved.

Graphite-silicone rubber composite electrode: Preparation and possibilities of analytical application

Composite electrodes were prepared using graphite powder and silicone rubber in different compositions. The use of such hydrophopic materials interned to diminish the swallowing observed in other cases when the electrodes are used in aqueous solutions for a long time. The composite was characterized for the response reproducibility, ohmic resistance, thermal behavior and active area. The voltammetric response in relation to analytes with known voltammetric behavior was also evaluated, always in comparison with the glassy carbon. The 70% (graphite, w/w) composite electrode was used in the quantitative determination of hydroquinone (HQ) in a DPV procedure in which a detection limit of 5.1 x 10(-8) mol L-1 was observed. HQ was determined in a photographic developer sample with errors lower then 1% in relation to the label value. (c) 2007 Elsevier B.V. All rights reserved.

THE POTENTIALITIES OF USING A GRAPHITE-SILICONE RUBBER COMPOSITE ELECTRODE IN THE DETERMINATION OF PROPRANOLOL

A graphite silicone-rubber composite electrode (GSR) was used for the determination of propranolol in drug formulation. Cyclic voltammetry (CV) at the GSR presented an irreversible oxidation peak at + 0.8V vs. SCE, in Britton Robinson (B-R) buffer pH 7.4. The quantitative determination was carried out using differential pulse voltammetry (DPV). Under optimized parameters a linear dynamic range from 5.0 to 80.6 mu mol L(-1) with a detection limit of 1.1 mu mol L(-1) was observed. A repeatability of 4.5 +/- 0.1 mu A (n = 10) peak current was found after 10 successive DPV voltammograms of propranolol in the same solution after surface renovations. Using the proposed electrode, propranolol was quantified in a pharmaceutical formulation with results that agreed within 95% confidence level (t-test) with those from an official method.

Analytical Potentialities of Carbon Nanotube/Silicone Rubber Composite Electrodes: Determination of Propranolol

A new composite electrode based on multiwall carbon nanotubes (MWCNT) and silicone-rubber (SR) was developed and applied to the determination of propranolol in pharmaceutical formulations. The effect of using MWCNT/graphite mixtures in different proportions was also investigated. Cyclic voltammetry and electrochemical impedance spectroscopy were used for electrochemical characterization of different electrode compositions. Propranolol was determined using MWCNT/SR 70% (m/m) electrodes with linear dynamic ranges up to 7.0 mu molL(-1) by differential pulse and up to 5.4 mu molL(-1) by square wave voltammetry, with LODs of 0.12 and 0.078 mu molL(-1), respectively. Analysis of commercial samples agreed with that obtained by the official spectrophotometric method. The electrode is mechanically robust and presented reproducible results and a long useful life.

Artificial Neural Networks and the Study of the Psychoactivity of Cannabinoid Compounds

Cannabinoid compounds have widely been employed because of its medicinal and psychotropic properties. These compounds are isolated from Cannabis sativa (or marijuana) and are used in several medical treatments, such as glaucoma, nausea associated to chemotherapy, pain and many other situations. More recently, its use as appetite stimulant has been indicated in patients with cachexia or AIDS. In this work, the influence of several molecular descriptors on the psychoactivity of 50 cannabinoid compounds is analyzed aiming one obtain a model able to predict the psychoactivity of new cannabinoids. For this purpose, initially, the selection of descriptors was carried out using the Fisher`s weight, the correlation matrix among the calculated variables and principal component analysis. From these analyses, the following descriptors have been considered more relevant: E(LUMO) (energy of the lowest unoccupied molecular orbital), Log P (logarithm of the partition coefficient), VC4 (volume of the substituent at the C4 position) and LP1 (Lovasz-Pelikan index, a molecular branching index). To follow, two neural network models were used to construct a more adequate model for classifying new cannabinoid compounds. The first model employed was multi-layer perceptrons, with algorithm back-propagation, and the second model used was the Kohonen network. The results obtained from both networks were compared and showed that both techniques presented a high percentage of correctness to discriminate psychoactive and psychoinactive compounds. However, the Kohonen network was superior to multi-layer perceptrons.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

Evolution of artificial defects during shape rolling

Very often defects are present in rolled products. For wire rods, defects are very deleterious since the wire rods are generally used directly in various applications. For this reason, the market nowadays requires wire rods to be completely defect-free. Any wire with defects must be rejected as scrap which is very costly for the production mill. Thus, it is very important to study the formation and evolution of defects during wire rod rolling in order to better understand and minimize the problem, at the same time improving quality of the wire rods and reducing production costs. The present work is focused on the evolution of artificial defects during rolling. Longitudinal surface defects are studied during shape rolling of an AISI M2 high speed steel and a longitudinal central inner defect is studied in an AISI 304L austenitic stainless steel during ultra-high-speed wire rod rolling. Experimental studies are carried out by rolling short rods prepared with arteficial defects. The evolution of the defects is characterised and compared to numerical analyses. The comparison shows that surface defects generally reduce quicker in the experiments than predicted by the simulations whereas a good agreement is generally obtained for the central defect.

Outdoor performance of forest seedlings pre-cultivated under artificial lights : effects of the light spectra used for pre-cultivation on the future establishment and development

Forest nurseries are essential for producing good quality seedlings, thus being a key element in the reforestation process. With increasing climate change awareness, nursery managers are looking for new tools that can help reduce the effects of their operations on the environment. The ZEPHYR project, funded by the European Commission under the Seventh Framework Programme (FP7), has the objective of finding new alternatives for nurseries by developing innovative zero-impact technologies for forest plant production. Due to their direct relationship to the energy consumption of the nurseries, one of the main elements addressed are the grow lights used for the pre-cultivation. New LED luminaires with a light spectrum tailored to the seedlings’ needs are being studied and compared against the traditional fluorescent lamps. Seedlings of Picea abies and Pinus sylvestris were grown under five different light spectra (one fluorescent and 4 LED) during 5 weeks with a photoperiod of 16 hours at 100 μmol∙m-2∙s-1 and 60% humidity. In order to evaluate if these seedlings were able cope with real field stress conditions, a forest field trial was also designed. The terrain chosen was a typical planting site in mid-Sweden after clear-cutting. Two vegetation periods after the outplanting, the seedlings that were pre-cultivated under the LED lamps have performed at least as well as those that were grown under fluorescent lights. These results show that there is a good  potential for lightning substitution in forestry nurseries.