Submitted by Marlene Santos (marlene.bc.ufg@gmail.com) on 2014-12-03T17:40:18Z No. of bitstreams: 2 Dissertação - Roberto Vito Rodrigues Filho - 2013.pdf: 5032081 bytes, checksum: 38e74b2094416a7b86dc95fcf2ace961 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2014-12-04T14:50:02Z (GMT) No. of bitstreams: 2 Dissertação - Roberto Vito Rodrigues Filho - 2013.pdf: 5032081 bytes, checksum: 38e74b2094416a7b86dc95fcf2ace961 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) / Made available in DSpace on 2014-12-04T14:50:02Z (GMT). No. of bitstreams: 2 Dissertação - Roberto Vito Rodrigues Filho - 2013.pdf: 5032081 bytes, checksum: 38e74b2094416a7b86dc95fcf2ace961 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2013-08-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Body Sensor Networks (BSN) are a technology used to supply individual’s vital signs to ubiquitous and pervasive systems. This systems applied to the healthcare area uses BSN to monitor patient’s vital signs remotely, that is without them being in a hospital environment. This technology applied as a base to this application assists healthcare professional to remotely monitor patients, which contribute to solve healthcare services problems. One of those problems is the crowded treatments centers. The usage of BSN, by conditioning remote monitoring, can colaborate to reduce the patients’ needs to consistently go to hospitals, thus contributing to reduce the number of patients in those environments. Given this tecnology potential comes the need to develop good quality applications. However, considering an analysis of BSN projects applied to the healthcare field, the usage of inadequated hardware platforms are noticed. Therefore aiming to make the development of this type of applications easier, it is proposed a simulator specific for BSN applied to the healthcare field. Hence, this work’s goal is to show this application simulator through the usage of a simulated hardware platform which takes intoconsiderationhealthcare demands to provide a test environment. / As Redes de Sensores do Corpo Humano (RSCH) são uma tecnologia utilizada para o fornecimento de sinais vitais de um indivíduo para sistemas pervasivos. Esses sistemas aplicados à área da saúde utilizam as RSCH para o monitoramento de sinais vitais de um paciente de forma remota, sem que o mesmo tenha que estar em um ambiente hospitalar. Essa tecnologia usada como base dessas aplicações, auxiliam os profissionais da saúde no monitoramento de pacientes à distância, ajudando a resolver problemas na prestação de serviço de saúde. Um desses problemas é a lotação dos centros de atendimento. A utilização das RSCH, por condicionar o monitoramento remoto, colabora na redução da necessidadeconstantedaidadopacienteaoshospitais,contribuindoassimcomaredução da lotação nesses ambientes. Com o potencial dessa tecnologia surge a necessidade de desenvolver aplicações de qualidade. Entretanto, considerando uma análise dos projetos de RSCH aplicados à área da saúde, nota-se a realização de testes em ambientes e plataformas de hardware inadequados. Dessa forma, visando facilitar o desenvolvimento deaplicaçõesnestaárea,épropostoumsimuladorespecíficoparaRSCHaplicadasàárea dasaúde.Assim,oobjetivodestetrabalhoémostraressesimuladordeaplicaçõesatravés da utilização de uma plataforma simulada de hardware, a qual leva em consideração as demandas da área médica, para prover um ambiente de testes.

Orientador: Jacques Wainer / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-12T05:34:50Z (GMT). No. of bitstreams: 1 Dantas_MarcioPaixao_M.pdf: 4152956 bytes, checksum: f995417b653e9759340129be4c4d2608 (MD5) Previous issue date: 2008 / Resumo: Um guia de conduta médica é um documento formado por um conjunto de recomendações sistematicamente desenvolvidas para auxiliar nas decisões de praticantes e pacientes sobre cuidados de saúde em circunstâncias específicas. Desde que sejam bem elaborados, comprovadamente melhoram a qualidade média do atendimento médico. Frequentemente médicos não estão acostumados com guias práticos escritos em papel e não os aplicam adequadamente. Implementados em sistemas computacionais podem melhorar significativamente a qualidade do atendimento médico diretamente no local da assistência. Este trabalho está ligado ao projeto ST-Guide, uma iniciativa surgida no Instituto de Computação da Universidade Estadual de Campinas (IC-UNICAMP) para resolver o problema de formalização e implementação de guias clínicos práticos. As contribuições realizadas foram: (a) reestruturação do projeto em outras tecnologias; (b) estabelecimento e implementação de uma arquitetura extensível para suportar modelagem e implementação de guias; (c) realização de alterações conceituais para facilitar o processo de modelagem; (d) criação de novo algoritmo para verificação lógica de incompletude e ambiguidade; e (e) criação de um ambiente gráfico de desenvolvimento de guias associado a um verificador lógico que atua em tempo real, isto é, à medida em que ocorre a modelagem. Experimentos baseados em guias clínicos para assistência pré-natal e hipertensão são apresentados e o texto é concluído com uma discussão do que foi realizado e sugestão de trabalhos futuros. / Abstract: Clinical guidelines are systematically developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances. Since well elaborated, they provenly improve medical assistance quality. Oftenly clinicians aren't used to paper written guidelines and don't apply them adequately. Implemented in computer systems guidelines can significantly improve medical care quality directly at the point-of-care. This work is related to ST-Guide project, an initiative arisen at the Institute of Computing of State University of Campinas (IC-UNICAMP) to solve the practice guideline formalization and implementation problems. The contributions done were: (a) project restructuring on other technologies; (b) extensible architecture specification and implementation to support guideline modelling and implementation; (c) conceptual changes to ease modelling; (d) new incompletude and ambiguity logical verification algorithm; and (e) guideline graphical development environment coupled with a real time logical verifier. Experiments based on pre-natal assistence and hypertension clinical guidelines are presented and the text is concluded with a discussion of what was done and future work suggestions. / Mestrado / Mestre em Computação

Quality by Design (QbD) is a systematic approach that has been recommended as suitable for the development of quality pharmaceutical products. The QbD approach commences with the definition of a quality target drug profile and predetermined objectives that are then used to direct the formulation development process with an emphasis on understanding the pharmaceutical science and manufacturing principles that apply to a product. The design space is directly linked to the use of QbD for formulation development and is a multidimensional combination and interaction of input variables and process parameters that have been demonstrated to provide an assurance of quality. The objective of these studies was to apply the principles of QbD as a framework for the optimisation of a sustained release (SR) formulation of salbutamol sulphate (SBS), and for the establishment of a design space using Response Surface Methodology (RSM) and Artificial Neural Networks (ANN). SBS is a short-acting ♭₂ agonist that is used for the management of asthma and chronic obstructive pulmonary disease (COPD). The use of a SR formulation of SBS may provide clinical benefits in the management of these respiratory disorders. Ashtalin®8 ER (Cipla Ltd., Mumbai, Maharashtra, India) was selected as a reference formulation for use in these studies. An Ishikawa or Cause and Effect diagram was used to determine the impact of formulation and process factors that have the potential to affect product quality. Key areas of concern that must be monitored include the raw materials, the manufacturing equipment and processes, and the analytical and assessment methods employed. The conditions in the laboratory and manufacturing processes were carefully monitored and recorded for any deviation from protocol, and equipment for assessment of dosage form performance, including dissolution equipment, balances and hardness testers, underwent regular maintenance. Preliminary studies to assess the potential utility of Methocel® Kl OOM, alone and in combination with other matrix forming polymers, revealed that the combination of this polymer with xanthan gum and Carbopol® has the potential to modulate the release of SBS at a specific rate, for a period of 12 hr. A central composite design using Methocel® KlOOM, xanthan gum, Carbopol® 974P and Surelease® as the granulating fluid was constructed to fully evaluate the impact of these formulation variables on the rate and extent of SBS release from manufactured formulations. The results revealed that although Methocel® KlOOM and xanthan gum had the greatest retardant effect on drug release, interactions between the polymers used in the study were also important determinants of the measureable responses. An ANN model was trained for optimisation using the data generated from a central composite study. The efficiency of the network was optimised by assessing the impact of the number of nodes in the hidden layer using a three layer Multi Layer Perceptron (MLP). The results revealed that a network with nine nodes in the hidden layer had the best predictive ability, suitable for application to formulation optimisation studies. Pharmaceutical optimisation was conducted using both the RSM and the trained ANN models. The results from the two optimisation procedures yielded two different formulation compositions that were subjected to in vitro dissolution testing using USP Apparatus 3. The results revealed that, although the formulation compositions that were derived from the optimisation procedures were different, both solutions gave reproducible results for which the dissolution profiles were indeed similar to that of the reference formulation. RSM and ANN were further investigated as possible means of establishing a design space for formulation compositions that would result in dosage forms that have similar in vitro release test profiles comparable to the reference product. Constraint plots were used to determine the bounds of the formulation variables that would result in the manufacture of dosage forms with the desired release profile. ANN simulations with hypothetical formulations that were generated within a small region of the experimental domain were investigated as a means of understanding the impact of varying the composition of the formulation on resultant dissolution profiles. Although both methods were suitable for the establishment of a design space, the use of ANN may be better suited for this purpose because of the manner in which ANN handles data. As more information about the behaviour of a formulation and its processes is generated during the product Iifecycle, ANN may be used to evaluate the impact of formulation and process variables on measureable responses. It is recommended that ANN may be suitable for the optimisation of pharmaceutical formulations and establishment of a design space in line with ICH Pharmaceutical Development [1], Quality Risk Management [2] and Pharmaceutical Quality Systems [3]

This study was motivated by concerns within the medical education community regarding the psychometric soundness of current assessment methodologies. More specifically, there is reason to seriously question the reliablity and/or validity of these methodologies in assessing the intellectual skills upon which medical competence is based.

No description available.

The relatively new and still growing field of 3D-printing has opened up the possibilities to manufacture patient-specific medical devices with high geometrical accuracy in a precise and quick manner. Additionally, biocompatible materials are a demand for all medical applications while biodegradability is of importance when developing scaffolds for tissue growth for instance. With respect to this, this project consisted of developing biocompatible and bioresorbable polymer blend and composite filaments, for fused deposition modeling (FDM) printing. Poly(lactic acid) (PLA) and polycaprolactone (PCL) were used as supporting polymer matrix while hydroxyapatite (HA), a calcium phosphate with similar chemical composition to the mineral phase of human bone, was added to the composites to enhance the biological activity. PLA and PCL content was varied between 90–70 wt% and 10-30 wt%, respectively, while the HA content was 15 wt% in all composites. All materials were characterized in terms of mechanical properties, thermal stability, chemical composition and morphology. An accelerated degradation study of the materials was also executed in order to investigate the degradation behavior as well as the impact of the degradation on the above mentioned properties. The results showed that all processed materials exhibited higher mechanical properties compared to the human trabecular bone, even after degradation with a mass loss of around 30% for the polymer blends and 60% for the composites. It was also apparent that the mineral accelerated the polymer degradation significantly, which can be advantageous for injuries with faster healing time, requiring only support for a shorter time period.

A prevalent morphology in the microscopic world of artificial microswimmers, bacteria and viruses is that of a helix. The intriguingly different physics at play at the small scale level make it necessary for bacteria to employ swimming strategies different from our everyday experience, such as the rotation of a helical filament. Bio-inspired microswimmers that mimic bacterial locomotion achieve propulsion at the microscale level using magnetically actuated, rotating helical filaments. A promising application of these artificial microswimmers is in non-invasive medicine, for drug delivery to tumours or microsurgery. Two crucial features need to be addressed in the design of microswimmers. First, the ability to selectively control large ensembles and second, the adaptivity to move through complex conduit geometries, such as the constrictions and curves of the tortuous tumour microvasculature. In this dissertation, a mechanics-based selective control mechanism for magnetic microswimmers is proposed, and a model and simulation of an elastic helix passing through a constricted microchannel are developed. Thereafter, a theoretical framework is developed for the propulsion by stiff elastic filaments in viscous fluids. In order to address this fluid-structure problem, a pertubative, asymptotic, elastohydrodynamic approach is used to characterise the deformation that arises from and in turn affects the motion. This framework is applied to the helical filaments of bacteria and magnetically actuated microswimmers. The dissertation then turns to the sub-bacterial scale of bacteriophage viruses, 'phages' for short, that infect bacteria by ejecting their genetic material and replicating inside their host. The valuable insight that phages can offer in our fight against pathogenic bacteria and the possibility of phage therapy as an alternative to antibiotics, are of paramount importance to tackle antibiotics resistance. In contrast to typical phages, flagellotropic phages first attach to bacterial flagella, and have the striking ability to reach the cell body for infection, despite their lack of independent motion. The last part of the dissertation develops the first theoretical model for the nut-and-bolt mechanism (proposed by Berg and Anderson in 1973). A nut being rotated will move along a bolt. Similarly, a phage wraps itself around a flagellum possessing helical grooves, and exploits the rotation of the flagellum in order to passively travel along and towards the cell body, according to this mechanism. The predictions from the model agree with experimental observations with respect to directionality, speed and the requirements for succesful translocation.

Indiana University-Purdue University Indianapolis (IUPUI) / Proteins are the building blocks in a biological system. They interact with other proteins to make unique biological phenomenon. Protein-protein interactions play a valuable role in understanding the molecular mechanisms occurring in any biological system. Protein interaction databases are a rich source on protein interaction related information. They gather large amounts of information from published literature to enrich their data. Expert curators put in most of these efforts manually. The amount of accessible and publicly available literature is growing very rapidly. Manual annotation is a time consuming process. And with the rate at which available information is growing, it cannot be dealt with only manual curation. There need to be tools to process this huge amounts of data to bring out valuable gist than can help curators proceed faster. In case of extracting protein-protein interaction evidences from literature, just a mere mention of a certain protein by look-up approaches cannot help validate the interaction. Supporting protein interaction information with experimental evidence can help this cause. In this study, we are applying machine learning based classification techniques to classify and given protein interaction related document into an interaction detection method. We use biological attributes and experimental factors, different combination of which define any particular interaction detection method. Then using predicted detection methods, proteins identified using named entity recognition techniques and decomposing the parts-of-speech composition we search for sentences with experimental evidence for a protein-protein interaction. We report an accuracy of 75.1% with a F-score of 47.6% on a dataset containing 2035 training documents and 300 test documents.

Indiana University-Purdue University Indianapolis (IUPUI) / Object segmentation, quantification, and shape modeling are important areas inmedical image processing. By combining these techniques, researchers can find valuableways to extract and represent details on user-desired structures, which can functionas the base for subsequent analyses such as feature classification, regression, and prediction. This thesis presents a new framework for building a three-dimensional (3D) hippocampal atlas model with subfield information mapped onto its surface, with which hippocampal surface registration can be done, and the comparison and analysis can be facilitated and easily visualized. This framework combines three powerful tools for automatic subcortical segmentation and 3D surface modeling. Freesurfer and Functional magnetic resonance imaging of the brain's Integrated Registration and Segmentation Tool (FIRST) are employed for hippocampal segmentation and quantification, while SPherical HARMonics (SPHARM) is employed for parametric surface modeling. This pipeline is shown to be effective in creating a hippocampal surface atlas using the Alzheimer's Disease Neuroimaging Initiative Grand Opportunity and phase 2 (ADNI GO/2) dataset. Intra-class Correlation Coefficients (ICCs) are calculated for evaluating the reliability of the extracted hippocampal subfields. The complex folding anatomy of the hippocampus offers many analytical challenges, especially when informative hippocampal subfields are usually ignored in detailed morphometric studies. Thus, current research results are inadequate to accurately characterize hippocampal morphometry and effectively identify hippocampal structural changes related to different conditions. To address this challenge, one contribution of this study is to model the hippocampal surface using a parametric spherical harmonic model, which is a Fourier descriptor for general a 3D surface. The second contribution of this study is to extend hippocampal studies by incorporating valuable hippocampal subfield information. Based on the subfield distributions, a surface atlas is created for both left and right hippocampi. The third contribution is achieved by calculating Fourier coefficients in the parametric space. Based on the coefficient values and user-desired degrees, a pair of averaged hippocampal surface atlas models can be reconstructed. These contributions lay a solid foundation to facilitate a more accurate, subfield-guided morphometric analysis of the hippocampus and have the potential to reveal subtle hippocampal structural damage associated.

A novel, environmentally friendly, fast, and flexible polishing process for Nitinol parts is presented in this study. Nitinol samples with both superelastic and shape memory properties at room temperature were investigated. The chemical contamination and surface roughness of superelastic Nitinol plates were examined before and after plasma electrolytic polishing. The shift in phase transformation temperature and tensile strength before and after the polishing process were analysed using Nitinol wire with shape memory properties. The obtained experimental results were compared to the data obtained on reference samples examined in the as-received condition. It was found that plasma electrolytic polishing, when the right process parameters are applied, is capable of delivering Nitinol parts with extremely high surface quality. Moreover, it was experimentally proven that plasma electrolytic polishing does not have a negative impact on functionality or mechanical properties of polished parts.