Partículas nanométricas de ferritas de ítrio

Nanoparticles of yttrium iron garnet (YIG) were obtained by coprecipitation. The particles were prepared by hydrolysis in acid medium with addition of ammonia or urea, for homogeneous nucleation, at 90ºC. Different compositions and spherical morphologies were achieved by changing reactants concentrations and precipitation agent. X-ray diffractometry, transmission electron microscopy, differential thermal analysis and electrophoretic mobility were carried out on these particles to investigate the obtained phase, phase transition temperature, morphology, particle size and zeta potential, respectively.

Sistema automático para determinação seqüencial de cianeto livre e total empregando eletrodo tubular íon-seletivo de membrana homogênea

This study presents an automated system for potentiometric determination of free and total cyanide which employs a homogeneous membrane tubular ion-selective electrode. After the electrode is assembled, it is connected to a system composed of 3 three-way solenoid valves, sample line, carrier line, acid stream, and gas diffusion chamber. A Turbo Pascal® computer program, developed specifically for this task, automatically performs all the steps involved in data acquisition and processing. The proposed analytical procedure offers operational simplicity, since detection is performed by a tubular electrode, whose assembly is fast and easy. The system has shown reproducibility (r.s.d. < 0.5%, n=6) and high speed (30 readings/hour); it is efficient for determination of free and total cyanide in waste waters of starch processing plants. The detection limit was 1.2x10-5 and 1.5x10-5 mol L-1, for determination of free and total cyanide, respectively. The linear response range was between 1.2x10-5 and 1.0x10-2 mol L-1 for free cyanide and between 1.5x10-5 and 1.0x10-2 for total cyanide.

Approximation to the theory of affinities to manage the problems of the groupping process

New economic and enterprise needs have increased the interest and utility of the methods of the grouping process based on the theory of uncertainty. A fuzzy grouping (clustering) process is a key phase of knowledge acquisition and reduction complexity regarding different groups of objects. Here, we considered some elements of the theory of affinities and uncertain pretopology that form a significant support tool for a fuzzy clustering process. A Galois lattice is introduced in order to provide a clearer vision of the results. We made an homogeneous grouping process of the economic regions of Russian Federation and Ukraine. The obtained results gave us a large panorama of a regional economic situation of two countries as well as the key guidelines for the decision-making. The mathematical method is very sensible to any changes the regional economy can have. We gave an alternative method of the grouping process under uncertainty.

O uso de sílica gel organofuncionalizada como agente sequestrante para metais

An overview about the homogeneous and heterogeneous methods of synthesizing silylating agents and applications of the organofunctionalized silica-gel samples was explored. The pendant molecules attached covalently to the inorganic surface displayed important properties to act as sequestrating agents for metals in aqueous and non-aqueous solutions. The large variety of basic centres anchored on organic molecules improve the capacity in adsorbing cations. The increase in adsorption is dependent on the number of basic atoms disposed on the pendant molecules on the surface. The combination of acidic and basicity properties favours the selectivity, such is exemplified by the thiol modified silicas towards mercury (II) cations.

Morfologia e cristalinidade de hidroxicarbonato de zinco obtido via precipitação homogênea: influência dos ânions cloreto e nitrato

The effects of chloride and nitrate anions and their respective concentrations, as well as urea presence, on solid phase morphologies were investigated. Zinc hydroxide carbonate was prepared by aging diluted zinc salt solution in presence of urea at 90ºC. Samples were identified by X-ray powder diffractograms showing the characteristic patterns of hydrozincite. The crystallinity was correlated with the concentrations of reagents. Spherulitic-type aggregates and single acicular particles were obtained from diluted chloride and nitrate solutions while porous aggregates of uniform size were formed from solutions with high chloride and urea concentrations.

Nanoparticle Labels in Bioaffinity Assays

Nanoparticles offer adjustable and expandable reactive surface area compared to the more traditional solid phase forms utilized in bioaffinity assays due to the high surface to-volume ratio. The versatility of nanoparticles is further improved by the ability to incorporate various molecular complexes such as luminophores into the core. Nanoparticle labels composed of polystyrene, silica, inorganic crystals doped with high number of luminophores, preferably lanthanide(III) complexes, are employed in bioaffinity assays. Other label species such as semiconductor crystals (quantum dots) or colloidal gold clusters are also utilized. The surface derivatization of such particles with biomolecules is crucial for the applicability to bioaffinity assays. The effectiveness of a coating is reliant on the biomolecule and particle surface characteristics and the selected coupling technique. The most critical aspects of the particle labels in bioaffinity assays are their size-dependent features. For polystyrene, silica and inorganic phosphor particles, these include the kinetics, specific activity and colloidal stability. For quantum dots and gold colloids, the spectral properties are also dependent on particle size. This study reports the utilization of europium(III)-chelate-embedded nanoparticle labels in the development of bioaffinity assays. The experimental covers both the heterogeneous and homogeneous assay formats elucidating the wide applicability of the nanoparticles. It was revealed that the employment of europium(III) nanoparticles in heterogeneous assays for viral antigens, adenovirus hexon and hepatitis B surface antigen (HBsAg), resulted in sensitivity improvement of 10-1000 fold compared to the reference methods. This improvement was attributed to the extreme specific activity and enhanced monovalent affinity of the nanoparticles conjugates. The applicability of europium(III)-chelate-doped nanoparticles to homogeneous assay formats were proved in two completely different experimental settings; assays based on immunological recognition or proteolytic activity. It was shown that in addition to small molecule acceptors, particulate acceptors may also be employed due to the high specific activity of the particles promoting proximity-induced reabsorptive energy transfer in addition to non-radiative energy transfer. The principle of proteolytic activity assay relied on a novel dual-step FRET concept, wherein the streptavidin-derivatized europium(III)-chelate-doped nanoparticles were used as donors for peptide substrates modified with biotin and terminal europium emission compliant primary acceptor and a secondary quencher acceptor. The recorded sensitized emission was proportional to the enzyme activity, and the assay response to various inhibitor doses was in agreement with those found in literature showing the feasibility of the technique. Experiments regarding the impact of donor particle size on the extent of direct donor fluorescence and reabsorptive excitation interference in a FRET-based application was conducted with differently sized europium(III)-chelate-doped nanoparticles. It was shown that the size effect was minimal

Revisió del model inclusiu en l’àmbit de l’educació no formal del futbol base a partir del criteri d’agrupació

Recerca centrada en l’anàlisi de característiques concretes de l’educació inclusiva en un entorn d’educació no formal, com és el futbol base. El criteri que s’ha utilitzat per realitzar l’anàlisi són els agrupaments. Des de l’educació inclusiva es promouen els agrupaments heterogenis, una forma d’agrupar a l’alumnat tenint en compte les seves diferències, per tal d’enriquir-se entre tot l’alumnat i treure profit d’elles. A la vegada aquest agrupament es caracteritza per fomentar la igualtat d’oportunitats en l’aprenentatge dels alumnes. En canvi, al futbol base predominen els agrupaments homogenis, distribuint als jugadors segons el seu nivell en diferents equips. A la recerca es fa una comparació entre l’opinió de diferents membres involucrats en el món del futbol base de dues entitats esportives, un club de futbol, on es fan els grups de forma homogènia, i una escola de futbol, on es fan els agrupaments de forma heterogènia. Els resultats mostren que realitzant agrupaments homogenis no s’assegura que tots els jugadors tinguin les mateixes oportunitats d’aprenentatge i que el nivell competencial dels jugadors en edat de formació pot ser un element que fomenti desigualtats en el seu procés d’aprenentatge esportiu.

Classificação de cerâmicas arqueológicas da Bacia Amazônica

In order to elucidate the traditional classification of archaeological artefacts, a multielemental analytical method for characterisation of its micro and macro chemical constituents. combined with statistical multivariate analysis for classification, were used. Instrumental thermal neutron activation analysis, for elemental chemical determination, and three statistical methods: discriminant, cluster and modified cluster analysis were applied. The statistical results obtained for the samples from Iquiri, Quinari and Xapuri archaeological phases were in good agreement with the conventional archaeological classification. Iaco and Jacuru archaeological phase were not characterised as homogenous groups. Iquiri phase were the most distinct in relation to the other analysed groups. An homogeneous group for 54% collected samples at the Los Angeles site was also found, this could be characterised as a new archaeological phase.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Flash flood evolution in North-Western Mediterranean

The present paper shows an in-depth analysis of the evolution of floods and precipitation in Catalonia for the period 1981-2010. In order to have homogeneous information, and having in mind that not gauge data was available for all the events, neither for all the rivers and stream flows, daily press from a specific newspaper has been systematically analysed for this period. Furthermore a comparison with a longer period starting in 1900 has been done. 219 flood events (mainly flash flood events) have been identified for the period of 30 years (375 starting in 1900), 79 of them were ordinary, 117 of them were extraordinary and 23 of them were catastrophic, being autumn and summer the seasons with the maxima values. 19% of the events caused a total of 110 casualties. 60% of them died when they tried to cross the street or the stream. Factors like the evolution of precipitation, population density and other socio-economical aspects have been considered. The trend analysis shows an increase of 1 flood/decade that probably has been mainly due to inter-annual and intra-annual changes in population density and in land-use and land-cover.

A topical microemulsion for the prevention of allergic rhinitis symptoms: results of a randomized, controlled, double-blind, parallel group, multicentre, multinational clinical trial (Nares study)

Background: Since barrier protection measures to avoid contact with allergens are being increasingly developed, we assessed the clinical efficacy and tolerability of a topical nasal microemulsion made of glycerol esters in patients with allergic rhinitis. Methods: Randomized, controlled, double-blind, parallel group, multicentre, multinational clinical trial in which adult patients with allergic rhinitis or rhinoconjunctivitis due to sensitization to birch, grass or olive tree pollens received treatment with topical microemulsion or placebo during the pollen seasons. Efficacy variables included scores in the mini-RQLQ questionnaire, number and severity of nasal, ocular and lung signs and symptoms, need for symptomatic medications and patients" satisfaction with treatment. Adverse events were also recorded. Results: Demographic characteristics were homogeneous between groups and mini-RQLQ scores did not differ significantly at baseline (visit 1). From symptoms recorded in the diary cards, the ME group showed statistically significant better scores for nasal congestion (0.72 vs. 1.01; p = 0.017) and mean total nasal symptoms (0.7 vs. 0.9; p = 0.045). At visit 2 (pollen season), lower values were observed in the mini-RQLQ in the ME group, although there were no statistically significant differences between groups in both full analysis set (FAS) and patients completing treatment (PPS) populations. The results obtained in the nasal symptoms domain of the mini-RQLQ at visit 2 showed the highest difference (−0.43; 95% CI: -0.88 to 0.02) for the ME group in the FAS population. The topical microemulsion was safe and well tolerated and no major discomforts were observed. Satisfaction rating with the treatment was similar between the groups. Conclusions: The topical application of the microemulsion is a feasible and safe therapy in the prevention of allergic symptoms, particularly nasal congestion.

A Catálise no Brasil nos últimos 25 anos: uma história de sucesso

In the last 25 years the research in catalysis has passed from heterogeneous processes mainly applied to petrochemical industries to homogeneous processes applied to fine chemicals and green chemistry. In this context the Brazilian Chemical Society (SBQ) is playing an important role in the organization of this interdisciplinary area involving researches from different fields of physical sciences.

Design and production of protein nanostructures for biomolecular detection

Particulate nanostructures are increasingly used for analytical purposes. Such particles are often generated by chemical synthesis from non-renewable raw materials. Generation of uniform nanoscale particles is challenging and particle surfaces must be modified to make the particles biocompatible and water-soluble. Usually nanoparticles are functionalized with binding molecules (e.g., antibodies or their fragments) and a label substance (if needed). Overall, producing nanoparticles for use in bioaffinity assays is a multistep process requiring several manufacturing and purification steps. This study describes a biological method of generating functionalized protein-based nanoparticles with specific binding activity on the particle surface and label activity inside the particles. Traditional chemical bioconjugation of the particle and specific binding molecules is replaced with genetic fusion of the binding molecule gene and particle backbone gene. The entity of the particle shell and binding moieties are synthesized from generic raw materials by bacteria, and fermentation is combined with a simple purification method based on inclusion bodies. The label activity is introduced during the purification. The process results in particles that are ready-to-use as reagents in bioaffinity. Apoferritin was used as particle body and the system was demonstrated using three different binding moieties: a small protein, a peptide and a single chain Fv antibody fragment that represents a complex protein including disulfide bridge.If needed, Eu3+ was used as label substance. The results showed that production system resulted in pure protein preparations, and the particles were of homogeneous size when visualized with transmission electron microscopy. Passively introduced label was stably associated with the particles, and binding molecules genetically fused to the particle specifically bound target molecules. Functionality of the particles in bioaffinity assays were successfully demonstrated with two types of assays; as labels and in particle-enhanced agglutination assay. This biological production procedure features many advantages that make the process especially suited for applications that have frequent and recurring requirements for homogeneous functional particles. The production process of ready, functional and watersoluble particles follows principles of “green chemistry”, is upscalable, fast and cost-effective.

New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4

Food Safety Testing: Rapid Molecular Methods for Chemical and Biological Hazards

The central goal of food safety policy in the European Union (EU) is to protect consumer health by guaranteeing a high level of food safety throughout the food chain. This goal can in part be achieved by testing foodstuffs for the presence of various chemical and biological hazards. The aim of this study was to facilitate food safety testing by providing rapid and user-friendly methods for the detection of particular food-related hazards. Heterogeneous competitive time-resolved fluoroimmunoassays were developed for the detection of selected veterinary residues, that is coccidiostat residues, in eggs and chicken liver. After a simplified sample preparation procedure, the immunoassays were performed either in manual format with dissociation-enhanced measurement or in automated format with pre-dried assay reagents and surface measurement. Although the assays were primarily designed for screening purposes providing only qualitative results, they could also be used in a quantitative mode. All the developed assays had good performance characteristics enabling reliable screening of samples at concentration levels required by the authorities. A novel polymerase chain reaction (PCR)-based assay system was developed for the detection of Salmonella spp. in food. The sample preparation included a short non-selective pre-enrichment step, after which the target cells were collected with immunomagnetic beads and applied to PCR reaction vessels containing all the reagents required for the assay in dry form. The homogeneous PCR assay was performed with a novel instrument platform, GenomEra^™, and the qualitative assay results were automatically interpreted based on end-point time-resolved fluorescence measurements and cut-off values. The assay was validated using various food matrices spiked with sub-lethally injured Salmonella cells at levels of 1-10 colony forming units (CFU)/25 g of food. The main advantage of the system was the exceptionally short time to result; the entire process starting from the pre-enrichment and ending with the PCR result could be completed in eight hours. In conclusion, molecular methods using state-of-the-art assay techniques were developed for food safety testing. The combination of time-resolved fluorescence detection and ready-to-use reagents enabled sensitive assays easily amenable to automation. Consequently, together with the simplified sample preparation, these methods could prove to be applicable in routine testing.