Caracterização geoquímica e cerâmica das argilas do Grupo Itacaré / Formação Aquidauana, na faixa aflorante entre os estados de São Paulo e sul de Minas Gerais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Produção e caracterização física e mecânica de compósito plástico-madeira

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise rugosimétrica de duas cerâmicas odontológicas submetidas a diferentes tratamentos de superfície

Pós-graduação em Reabilitação Oral - FOAR

Novel Antimicrobial Peptides Bacterial Cellulose Obtained by Symbioses Culture Between Polyhexanide Biguanide (PHMB) and Green Tea

Bacterial cellulose is a highly hydrated pellicle made up of a random assembly of ribbon shaped fibers less than 5 nm wide. The unique properties provided by the nanometric structure have led to a number of diagnostic biological probes, display devices due to their unique size-dependent medical applications. Bacterial cellulose matrix extracellular is a novel biotechnology and unique medicine indicated for ultimate chronic wound treatment management, drug delivery, tissue engineering, skin cancer and offers an actual and effective solution to a serious medical and social problem and to promote rapid healing in lesions caused by Diabetic burns, ulcers of the lower limbs or any other circumstance in which there's epidermal or dermal loss. In this work, it is reported novel antimicrobial peptides (AMPs) bacterial cellulose/polyhexanide biguanide (PHMB) which are produced by symbioses culture between polyhexanide biguanide and green tea culture medium resulting in the pure 3-D structure consisting of an ultra-fine network of novel biocellulose/PHMB nanofibres matrix (2-8 nm), highly hydrated (99% in weight), and with higher molecular weight, full biocompatibility.

Amostragem da emissão de material particulado em ambientes externos

The concern of the society with regard to the pollution if becomes each bigger and necessary time. This pollution generates damage for who is in contact, as much in economic terms how much in quality of life. The particulate matter is one of the main polluting the air, being the most harmful to human health, fine particles and ultra fine (below 2.5 μm in diameter). With this, this work had as objective to mensurar the pollution of air for material particulado through samplings in an urban center, in a siderurgical industry, a conventional coal bunker and a forest fire. The equipment used for the sampling of particles had been the DataRam4 (model DR 4000) and the Impactador de Andersen, both developed by company THERMO SCIENTIFIC. The first equipment uses a system of nefelometry and the second uses a gravimetrical system of sampling. During the carried through samplings, it can be observed in some cases the difficulty in the breath, badly be and low visibility that this type of pollutant can cause. In most cases the results were disturbing. In industry, conventional coal bunker and in the forest were measured values high concentration for particles smaller diameters. Peak concentrations issued were: 40,000 μg/m³, 182,000 μg/m³ and 400,000 μg/m³ for the industry, conventional coal bunker and forest, respectively. Already in the urban centre were satisfactory results, always staying within the limit allowed by the rules in force so far in the country

Real-time Sampling of Particulate Matter Smaller than 2.5 µm from Amazon Forest Biomass Combustion

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Interactive quadrangulation with reeb atlases and connectivity textures

Creating high-quality quad meshes from triangulated surfaces is a highly nontrivial task that necessitates consideration of various application specific metrics of quality. In our work, we follow the premise that automatic reconstruction techniques may not generate outputs meeting all the subjective quality expectations of the user. Instead, we put the user at the center of the process by providing a flexible, interactive approach to quadrangulation design. By combining scalar field topology and combinatorial connectivity techniques, we present a new framework, following a coarse to fine design philosophy, which allows for explicit control of the subjective quality criteria on the output quad mesh, at interactive rates. Our quadrangulation framework uses the new notion of Reeb atlas editing, to define with a small amount of interactions a coarse quadrangulation of the model, capturing the main features of the shape, with user prescribed extraordinary vertices and alignment. Fine grain tuning is easily achieved with the notion of connectivity texturing, which allows for additional extraordinary vertices specification and explicit feature alignment, to capture the high-frequency geometries. Experiments demonstrate the interactivity and flexibility of our approach, as well as its ability to generate quad meshes of arbitrary resolution with high-quality statistics, while meeting the user's own subjective requirements.

New Aerosol Particle formation in Amazonia

Events of new particle formation (NPF) in tropical boundary layer followed by consecutive growth towards Aitken mode size range are sparse compared to mid- latitudes Kulmala et al. (2004). This is also the case for rainforest environment. More often short episodes of elevated ultrafine and Aitken mode aerosol particle concentrations are observed their origin and the processes governing these episodes do however remain unclear. Based on observations performed in the Amazonian rainforest environment combined with statistical analysis we present a mechanism explaining the erratic appearance of ultra-fine aerosol in tropical boundary layer of the rainforest.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Reactive halogen compounds in the marine boundary layer: method developments and field measurements

Reactive halogen compounds are known to play an important role in a wide variety of atmospheric processes such as atmospheric oxidation capacity and coastal new particle formation. In this work, novel analytical approaches combining diffusion denuder/impinger sampling techniques with gas chromatographic–mass spectrometric (GC–MS) determination are developed to measure activated chlorine compounds (HOCl and Cl2), activated bromine compounds (HOBr, Br2, BrCl, and BrI), activated iodine compounds (HOI and ICl), and molecular iodine (I2). The denuder/GC–MS methods have been used to field measurements in the marine boundary layer (MBL). High mixing ratios (of the order of 100 ppt) of activated halogen compounds and I2 are observed in the coastal MBL in Ireland, which explains the ozone destruction observed. The emission of I2 is found to correlate inversely with tidal height and correlate positively with the levels of O3 in the surrounding air. In addition the release is found to be dominated by algae species compositions and biomass density, which proves the “hot-spot” hypothesis of atmospheric iodine chemistry. The observations of elevated I2 concentrations substantially support the existence of higher concentrations of littoral iodine oxides and thus the connection to the strong ultra-fine particle formation events in the coastal MBL.

Ontologies and Methods for Interoperability of Engineering Analysis Models (EAMS) in an E-Design Environment

ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.

Highly accurate evaluation of GPS synchronization for TDOA localization

Clock synchronization is critical for the operation of a distributed wireless network system. In this paper we investigate on a method able to evaluate in real time the synchronization offset between devices down to nanoseconds (as needed for positioning). The method is inspired by signal processing algorithms and relies on fine-grain time information obtained during the reconstruction of the signal at the receiver. Applying the method to a GPS-synchronized system show that GPS-based synchronization has high accuracy potential but still suffers from short-term clock drift, which limits the achievable localization error.

Methodology for GPS Synchronization Evaluation with High Accuracy

Clock synchronization in the order of nanoseconds is one of the critical factors for time-based localization. Currently used time synchronization methods are developed for the more relaxed needs of network operation. Their usability for positioning should be carefully evaluated. In this paper, we are particularly interested in GPS-based time synchronization. To judge its usability for localization we need a method that can evaluate the achieved time synchronization with nanosecond accuracy. Our method to evaluate the synchronization accuracy is inspired by signal processing algorithms and relies on fine grain time information. The method is able to calculate the clock offset and skew between devices with nanosecond accuracy in real time. It was implemented using software defined radio technology. We demonstrate that GPS-based synchronization suffers from remaining clock offset in the range of a few hundred of nanoseconds but the clock skew is negligible. Finally, we determine a corresponding lower bound on the expected positioning error.

Characterization of the East Houston particulate matter <2.5 atmosphere; a novel method for desorbing organic constituents from airborne particulates

I have developed a novel approach to test for toxic organic substances adsorbed onto ultra fine particulate particles present in the ambient air in Northeast Houston, Texas. These particles are predominantly carbon soot with an aerodynamic diameter (AD) of <2.5 μm. If present in the ambient air, many of the organic substances will be absorbed to the surface of the particles (which act just like a charcoal air filter), and may be adducted into the respiratory system. Once imbedded into the lungs these particles may release the adsorbed toxic organic substances with serious health consequences. I used a Airmetrics portable Minivol air sampler time drawing the ambient air through collection filters samples from 6 separate sites in Northeast Houston, an area known for high ambient PM 2.5 released from chemical plants and other sources (e.g. vehicle emissions).(1) In practice, the mass of the collected particles were much less than the mass of the filters. My technique was designed to release the adsorbed organic substances on the fine carbon particles by heating the filter samples that included the PM 2.5 particles prior to identification by gas chromatography/mass spectrometry (GCMS). The results showed negligible amounts of target chemicals from the collection filters. However, the filters alone released organic substances and GCMS could not distinguish between the organic substances released from the soot particles from those released from the heated filter fabric. However, an efficacy tests of my method using two wax burning candles that released soot revealed high levels of benzene. This suggests that my method has the potential to reveal the organic substances adsorbed onto the PM 2.5 for analysis. In order to achieve this goal, I must refine the particle collection process which would be independent of the filters; the filters upon heating also release organic substances obscuring the contribution from the soot particles. To obtain pure soot particles I will have to filter more air so that the soot particles can be shaken off the filters and then analyzed by my new technique. ^

Continuous condensation particle (CP) observations from 1984 through 2009 at Neumayer Station, Antacrtica

Continuous condensation particle (CP) observations were conducted from 1984 through 2009 at Neumayer Station under stringent contamination control. During this period, the CP concentration (median 258 1/cm**3) showed no significant long term trend but exhibited a pronounced seasonality characterized by a stepwise increase starting in September and reaching its annual maximum of around 10**3/cm**3 in March. Minimum values below 10**2/cm**3 were observed during June/July. Dedicated time series analyses in the time and frequency domain revealed no significant correlations between inter-annual CP concentration variations and atmospheric circulation indices like Southern Annular Mode (SAM) or Southern Ocean Index (SOI). The impact of the Pinatubo volcanic eruption and strong El Niño events did not affect CP concentrations. From thermodenuder experiments we deduced that the portion of volatile (at 125 °C) and semi-volatile (at 250 °C) particles which could be both associated with biogenic sulfur aerosol, was maximum during austral summer, while during winter non-volatile sea salt particles dominated. During September through April we could frequently observe enhanced concentrations of ultrafine particles within the nucleation mode (between 3 nm and 7 nm particle diameter), preferentially in the afternoon.