935 resultados para Extraction and Processing Industry


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A simple method developed for genomic DNA isolation from fungus was tested on the red alga, Gelidium sesquipedale (Clem.) Born et Thur., which is commercially exploited for its high sulfated polysaccharide (agar) content. This method is faster, cheaper, and less toxic than conventional phenol/chloroform methods. Random amplified polymorphic DNA (RAPD) amplifications were performed successfully without the necessity of purifying the DNA. RAPD markers were used to investigate the genetic similarity among three natural populations of G. sesquipedale from southern Portugal. Bulked-genomic DNA samples of 15 different individuals were made in each population. These can be conceived of as a sample of the population DNA. Of the 62 primers screened, 41 produced bands and 22 revealed polymorphisms. Genetic similarities among populations were high. Populations that are further away from each other have the lowest similarity coefficients, whereas the intermediate Ingrina population, located on the south coast, showed higher genetic similarity with the Odeceixe population located on the southwest coast, than with the Sao Rafael southern population. This suggests a higher genetic flow between Odeceixe and Ingrina or the result may be a founder effect in the sense that the species has propagated from the east coast to the south coast of Portugal. We conclude that the use of this isolation method with RAPD analysis is appropriate to characterize the genetic variability of this commercial species along its geographical distribution. Large sample sizes can be screened at a relatively low cost. Finding genetic markers for commercial populations of C. sesquipedale may be of industrial interest.

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Laser speckle contrast imaging (LSCI) has the potential to be a powerful tool in medicine, but more research in the field is required so it can be used properly. To help in the progression of Michigan Tech's research in the field, a graphical user interface (GUI) was designed in Matlab to control the instrumentation of the experiments as well as process the raw speckle images into contrast images while they are being acquired. The design of the system was successful and is currently being used by Michigan Tech's Biomedical Engineering department. This thesis describes the development of the LSCI GUI as well as offering a full introduction into the history, theory and applications of LSCI.

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Event extraction from texts aims to detect structured information such as what has happened, to whom, where and when. Event extraction and visualization are typically considered as two different tasks. In this paper, we propose a novel approach based on probabilistic modelling to jointly extract and visualize events from tweets where both tasks benefit from each other. We model each event as a joint distribution over named entities, a date, a location and event-related keywords. Moreover, both tweets and event instances are associated with coordinates in the visualization space. The manifold assumption that the intrinsic geometry of tweets is a low-rank, non-linear manifold within the high-dimensional space is incorporated into the learning framework using a regularization. Experimental results show that the proposed approach can effectively deal with both event extraction and visualization and performs remarkably better than both the state-of-the-art event extraction method and a pipeline approach for event extraction and visualization.

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Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data.

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We present the extraction and processing of the IUE Low Dispersion spectra within the framework of the ESA “IUE Newly Extracted Spectra” (INES) System. Weak points of SWET, the optimal extraction implementation to produce the NEWSIPS output products (extracted spectra) are discussed, and the procedures implemented in INES to solve these problems are outlined. The more relevant modifications are: 1) the use of a new noise model, 2) a more accurate representation of the spatial profile of the spectrum and 3) a more reliable determination of the background. The INES extraction also includes a correction for the contamination by solar light in long wavelength spectra. Examples showing the improvements obtained in INES with respect to SWET are described. Finally, the linearity and repeatability characteristics of INES data are evaluated and the validity of the errors provided in the extraction is discussed.

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High quality, pure DNA is required for ensuring reliable and reproducible results in molecular diagnosis applications. A number of in-house and commercial methods are available for the extraction and purification of genomic DNA from faecal material, each one offering a specific combination of performance, cost-effectiveness, and easiness of use that should be conveniently evaluated in function of the pathogen of interest. In this comparative study the marketed kits QIAamp DNA stool mini (Qiagen), SpeedTools DNA extraction (Biotools), DNAExtract-VK (Vacunek), PowerFecal DNA isolation (MoBio), and Wizard magnetic DNA purification system (Promega Corporation) were assessed for their efficacy in obtaining DNA of the most relevant enteric protozoan parasites associated to gastrointestinal disease globally. A panel of 113 stool specimens of clinically confirmed patients with cryptosporidiosis (n = 29), giardiasis (n = 47) and amoebiasis by Entamoeba histolytica (n = 3) or E. dispar (n = 10) and apparently healthy subjects (n = 24) were used for this purpose. Stool samples were aliquoted in five sub-samples and individually processed by each extraction method evaluated. Purified DNA samples were subsequently tested in PCR-based assays routinely used in our laboratory. The five compared methods yielded amplifiable amounts of DNA of the pathogens tested, although performance differences were observed among them depending on the parasite and the infection burden. Methods combining chemical, enzymatic and/or mechanical lysis procedures at temperatures of at least 56 °C were proven more efficient for the release of DNA from Cryptosporidium oocysts.

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Résumé : Les ions hydronium (H3O + ) sont formés, à temps courts, dans les grappes ou le long des trajectoires de la radiolyse de l'eau par des rayonnements ionisants à faible transfert d’énergie linéaire (TEL) ou à TEL élevé. Cette formation in situ de H3O + rend la région des grappes/trajectoires du rayonnement temporairement plus acide que le milieu environnant. Bien que des preuves expérimentales de l’acidité d’une grappe aient déjà été signalées, il n'y a que des informations fragmentaires quant à son ampleur et sa dépendance en temps. Dans ce travail, nous déterminons les concentrations en H3O + et les valeurs de pH correspondantes en fonction du temps à partir des rendements de H3O + calculés à l’aide de simulations Monte Carlo de la chimie intervenant dans les trajectoires. Quatre ions incidents de différents TEL ont été sélectionnés et deux modèles de grappe/trajectoire ont été utilisés : 1) un modèle de grappe isolée "sphérique" (faible TEL) et 2) un modèle de trajectoire "cylindrique" (TEL élevé). Dans tous les cas étudiés, un effet de pH acide brusque transitoire, que nous appelons un effet de "pic acide", est observé immédiatement après l’irradiation. Cet effet ne semble pas avoir été exploré dans l'eau ou un milieu cellulaire soumis à un rayonnement ionisant, en particulier à haut TEL. À cet égard, ce travail soulève des questions sur les implications possibles de cet effet en radiobiologie, dont certaines sont évoquées brièvement. Nos calculs ont ensuite été étendus à l’étude de l'influence de la température, de 25 à 350 °C, sur la formation in situ d’ions H3O + et l’effet de pic acide qui intervient à temps courts lors de la radiolyse de l’eau à faible TEL. Les résultats montrent une augmentation marquée de la réponse de pic acide à hautes températures. Comme de nombreux processus intervenant dans le cœur d’un réacteur nucléaire refroidi à l'eau dépendent de façon critique du pH, la question ici est de savoir si ces fortes variations d’acidité, même si elles sont hautement localisées et transitoires, contribuent à la corrosion et l’endommagement des matériaux.

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Varzea forests of the Amazon estuary contain species of importance to riverine communities. For example, the oil extracted from the seeds of crabwood trees is traditionally used to combat various illnesses and as such artisanal extraction processes have been maintained. The objectives of this study were to (1) describe the process involved in artisanal extraction of crabwood oil in the Fazendinha ProtectedArea, in the state ofAmap´a; (2) characterise the processes of knowledge transfer associated with the extraction and use of crabwood oil within a peri-urban riverine community; and (3) discern medicinal uses of the oil.The data were obtained using semistructured interviews with 13 community members involved in crabwood oil extraction and via direct observation.The process of oil extraction is divided into four stages: seed collection; cooking and resting of the seeds; shelling of the seeds and dough preparation; and oil collection. Oil extraction is carried out within the home for personal use, with surplus marketed within the community. More than 90% of the members of the community involved in extraction of crabwood oil highlighted the use of the oil to combat inflammation of the throat. Knowledge transfer occurs via oral transmission and through direct observation.

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Since last century, the rising interest of value-added and advanced functional materials has spurred a ceaseless development in terms of industrial processes and applications. Among the emerging technologies, thanks to their unique features and versatility in terms of supported processes, non-equilibrium plasma discharges appear as a key solvent-free, high-throughput and cost-efficient technique. Nevertheless, applied research studies are needed with the aim of addressing plasma potentialities optimizing devices and processes for future industrial applications. In this framework, the aim of this dissertation is to report on the activities carried out and the results achieved concerning the development and optimization of plasma techniques for nanomaterial synthesis and processing to be applied in the biomedical field. In the first section, the design and investigation of a plasma assisted process for the production of silver (Ag) nanostructured multilayer coatings exhibiting anti-biofilm and anti-clot properties is described. With the aim on enabling in-situ and on-demand deposition of Ag nanoparticles (NPs), the optimization of a continuous in-flight aerosol process for particle synthesis is reported. The stability and promising biological performances of deposited coatings spurred further investigation through in-vitro and in-vivo tests which results are reported and discussed. With the aim of addressing the unanswered questions and tuning NPs functionalities, the second section concerns the study of silver containing droplet conversion in a flow-through plasma reactor. The presented results, obtained combining different analysis techniques, support a formation mechanism based on droplet to particle conversion driven by plasma induced precursor reduction. Finally, the third section deals with the development of a simulative and experimental approach used to investigate the in-situ droplet evaporation inside the plasma discharge addressing the main contributions to liquid evaporation in the perspective of process industrial scale up.

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Neural representations (NR) have emerged in the last few years as a powerful tool to represent signals from several domains, such as images, 3D shapes, or audio. Indeed, deep neural networks have been shown capable of approximating continuous functions that describe a given signal with theoretical infinite resolution. This finding allows obtaining representations whose memory footprint is fixed and decoupled from the resolution at which the underlying signal can be sampled, something that is not possible with traditional discrete representations, e.g., grids of pixels for images or voxels for 3D shapes. During the last two years, many techniques have been proposed to improve the capability of NR to approximate high-frequency details and to make the optimization procedures required to obtain NR less demanding both in terms of time and data requirements, motivating many researchers to deploy NR as the main form of data representation for complex pipelines. Following this line of research, we first show that NR can approximate precisely Unsigned Distance Functions, providing an effective way to represent garments that feature open 3D surfaces and unknown topology. Then, we present a pipeline to obtain in a few minutes a compact Neural Twin® for a given object, by exploiting the recent advances in modeling neural radiance fields. Furthermore, we move a step in the direction of adopting NR as a standalone representation, by considering the possibility of performing downstream tasks by processing directly the NR weights. We first show that deep neural networks can be compressed into compact latent codes. Then, we show how this technique can be exploited to perform deep learning on implicit neural representations (INR) of 3D shapes, by only looking at the weights of the networks.

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The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

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Pós-graduação em Física - IGCE

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Pós-graduação em Ciência Animal - FMVA