Thesis--Oregon State University. / Photocopy of typescript. Ann Arbor, Mich. : Xerox University Microfilms, 1976. -- 21 cm. Bibliography: leaves 126-129.

Thesis (Ph. D.)--Virginia Commonwealth University, 2010. / Prepared for: School of Nursing. Title from title-page of electronic thesis. Bibliography: leaves 80-85.

Thesis (Ph. D.)--University of Wisconsin--Madison, 1981. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 118-137).

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 158-185).

Ultrasound is one of the primary technologies used for clinical purposes. Ultrasound systems have favorable real-time capabilities, are fast and relatively inexpensive, portable and non-invasive. Recent interest in using ultrasound imaging for tongue motion has various applications in linguistic study, speech therapy as well as in foreign language education, where visual-feedback of tongue motion complements conventional audio feedback. Ultrasound images are known to be difficult to recognize. The anatomical structure in them, the rapidity of tongue movements, also missing segments in some frames and the limited frame rate of ultrasound systems have made automatic tongue contour extraction and tracking very challenging and especially hard for real-time applications. Traditional image processing-based approaches have many practical limitations in terms of automation, speed, and accuracy. Recent progress in deep convolutional neural networks has been successfully exploited in a variety of computer vision problems such as detection, classification, and segmentation. In the past few years, deep belief networks for tongue segmentation and convolutional neural networks for the classification of tongue motion have been proposed. However, none of these claim fully-automatic or real-time performance. U-Net is one of the most popular deep learning algorithms for image segmentation, and it is composed of several convolutions and deconvolution layers. In this thesis, we proposed a fully automatic system to extract tongue dorsum from ultrasound videos in real-time using a simplified version of U-Net, which we call sU-Net. Two databases from different machines were collected, and different training schemes were applied for testing the learning capability of the model. Our experiment on ultrasound video data demonstrates that the proposed method is very competitive compared with other methods in terms of performance and accuracy.

Submitted by GUSTAVO MUÇOUÇAH SAMPAIO BRANDÃO null (gubrandao@terra.com.br) on 2016-07-11T20:28:32Z No. of bitstreams: 1 Pentasaccharides para o tratamento da trombose venosa profunda - cópia.pdf: 2647553 bytes, checksum: 21a99ea1c79999dd8932b40302271db0 (MD5) / Rejected by Ana Paula Grisoto (grisotoana@reitoria.unesp.br), reason: Solicitamos que realize uma nova submissão seguindo a orientação abaixo: O arquivo submetido está sem a ficha catalográfica. A versão submetida por você é considerada a versão final da dissertação/tese, portanto não poderá ocorrer qualquer alteração em seu conteúdo após a aprovação. Corrija esta informação e realize uma nova submissão contendo o arquivo correto. Agradecemos a compreensão. on 2016-07-12T19:07:50Z (GMT) / Submitted by GUSTAVO MUÇOUÇAH SAMPAIO BRANDÃO null (gubrandao@terra.com.br) on 2016-07-12T21:33:22Z No. of bitstreams: 2 Pentasaccharides para o tratamento da trombose venosa profunda - cópia.pdf: 2647553 bytes, checksum: 21a99ea1c79999dd8932b40302271db0 (MD5) Pentasaccharides para o tratamento da trombose venosa profunda - com ficha catalográfica.pdf: 2703945 bytes, checksum: d9034b6210add676a4f9b7cbf4c31ad3 (MD5) / Approved for entry into archive by Ana Paula Grisoto (grisotoana@reitoria.unesp.br) on 2016-07-14T16:36:47Z (GMT) No. of bitstreams: 1 brandao_gms_dr_bot.pdf: 2703945 bytes, checksum: d9034b6210add676a4f9b7cbf4c31ad3 (MD5) / Made available in DSpace on 2016-07-14T16:36:47Z (GMT). No. of bitstreams: 1 brandao_gms_dr_bot.pdf: 2703945 bytes, checksum: d9034b6210add676a4f9b7cbf4c31ad3 (MD5) Previous issue date: 2016-05-25 / Pentasaccharides para o tratamento da trombose venosa profunda Questão da revisão: Os novos anticoagulantes da classe dos pentasaccharides podem ser uma alternativa eficaz e segura aos anticoagulantes convencionais utilizados na terapia padrão do tratamento da trombose venosa profunda? Visão geral: Trombose venosa profunda (TVP) é uma doença grave e potencialmente fatal que se caracteriza pela formação aguda de um coágulo de sangue nas veias profundas. Sua incidência aumenta exponencialmente com a idade e estima-se que na população geral, sua incidência seja de 5 casos em 10,000 habitantes. O tratamento padrão se faz por meio de medicamentos anticoagulantes, inicialmente pela administração de medicamentos injetáveis, as heparinas, por 5 a 7 dias e em seguida pelo uso prolongado de medicamentos de uso oral, os antagonistas da vitamina K. Entretanto, o alto risco de sangramento e a necessidade de um rigoroso controle laboratorial, permanecem como importantes limitações à terapia padrão. Os pentasaccharides são anticoagulantes sintéticos que podem apresentar vantagens em relação ao tratamento convencional como um efeito mais previsível, um regime de dosagem mais conveniente, a ausência da necessidade de controle laboratorial, ausência de interações com medicamentos e/ou alimentos, ausência da temida diminuição das plaquetas induzida pela heparina e em muitos casos melhor custo-benefício. Características chaves e resultados: Nossas buscas, realizadas até julho de 2015, identificaram 20 entre 730 registros que representavam 5 estudos elegíveis, compreendendo um total de 6981 pacientes. Os estudos compararam os pentasaccharides fondaparinux, idraparinux e idrabiotaparinux com a terapia padrão (heparina seguida por antagonista da vitamina K). O principal resultado de eficácia foi feito pela avaliação da incidência de qualquer episódio tromboembolismo venoso (novo episódio de TVP ou embolia pulmonar) durante o tratamento. E o principal resultado de danos foi incidência de sangramento. Esta revisão mostrou que os pentasaccharides (fondaparinux, e a dose de 2.5 mg de idraparinux e a dose equivalente de 3.0 mg de idrabiotaparinux) podem ser uma alternativa eficaz e segura a anticoagulação convencional para o tratamento da TVP. Qualidade da evidência: A qualidade da evidência foi considerada moderada a alta. Um único estudo incluído (Persist) poderia ser julgado potencialmente falho devido ao relevante número de pacientes que foram perdidos ou descontinuaram prematuramente o tratamento após a randomização. De forma geral, os estudos incluídos responderam diretamente as perguntas e foram considerados de boa qualidade. Os resultados dos estudos foram consistentes e os efeitos estimados foram precisos. Nós acreditamos que seja improvável que a maioria dos nossos principais resultados de eficácia e danos possam ser modificados por estudos adicionais. Entretanto, estudos futuros com os pentasaccharides de meia vida prolongada (idraparinux e idrabiotaparinux) em baixas doses podem confirmar nossas estimativas com relação a sua não inferioridade em comparação à terapia padrão. / Background: Deep vein thrombosis (DVT) is a severe disorder caused by acute formation of a clot or thrombus in the deep vein system. The incidence of DVT increases with age: from 2 to 3/10,000 in adults aged 30 to 49 years to 20/10,000 in adults aged 70 to 79 years. If left untreated, the clot can travel up to the lungs and cause a potentially life-threatening pulmonary embolism (PE). Standard treatment is based on antithrombotic therapy, initially with parenteral administration of unfractionated heparin or low molecular weight heparins (LMWH) for five to seven days, then subsequent long-term oral vitamin K antagonists (e.g. warfarin) therapy. However, hemorrhagic complications are a major concern associated with warfarin treatment. Indeed, the hemorrhagic risk of warfarin and the required laboratory control remain the Achilles’ heel of vitamin K antagonist management. The pentasaccharides have characteristics that may be favourable over conventional treatment, including a predictable effect, lack of frequent monitoring or re-dosing and few known drug interactions and absence of heparin-induced thrombocytopenia. To date, no systematic review has measured the effectiveness and safety of these drugs in the treatment of DVT. Objectives: To assess the efficacy and harms of pentasaccharides for the treatment of deep venous thrombosis. Search strategy: 1 The Cochrane Peripheral Vascular Diseases Group Trials Search Co-ordinator searched the Specialised Register (last searched July 2015) and the Cochrane Register of Studies (last searched July 2015). We searched clinical trials databases for details of ongoing or unpublished studies and the reference lists of relevant articles retrieved by electronic searches for additional citations. Selection criteria: We included randomised controlled trials in which people with a DVTconfirmed by standard imaging techniques, were allocated to receive a pentasaccharide (fondaparinux, idraparinux or idrabiotaparinux) for the treatment of DVT. Data collection and analysis: Three review authors (GB, DJ and MS) independently extracted the data and assessed the risk of bias in the trials. Any disagreements were resolved by discussion. We performed meta-analyses when we considered heterogeneity low. The two primary outcomes were recurrent VTE and major (and clinically non-major) bleeding. Other outcomes included all-cause mortality, recurrent DVT, PE, thrombocytopenia, heparin-induced thrombocytopenia syndrome and all other adverse effects induced by the treatments . We calculated all outcomes using a relative risk (RR) with a 95% confidence interval (CI). Main results: We included 5 randomised controlled trials of 6981 participants. Two studies tested fondaparinux, while three tested idraparinux (being one tested idrabiotaparinux). We deemed all included studies to be of high methodological quality and generally low risk of bias. The quality of the evidence was generally graded as high as the outcomes were direct and effect estimates were consistent and precise, as reflected in the narrow CIs around the RRs. Meta-analysis of two studies (2658 participants) comparing fondaparinux with standard anticoagulation groups showed no difference in the risk of recurrent VTE (RR 0.88, 95% CI 0.60 to 1.29). The RR of bleeding in the initial period of treatment (RR 0.94, 95% CI 0.73 to 1.22) and three months of follow up (RR 0.61, 95% CI 0.36 to 1.01) were similar comparing both interventions. Two studies comparing idraparinux with standard therapy showed no difference in the risk of recurrent VTE during three months (RR 1.51; 95% CI 0.26, 8.90) and (RR 0.79; 95% CI 0.21; 2.91). The treatment with idraparinux clearly showed a bleeding risk with a pattern dose-response. However, at a dose of 2.5 mg idraparinux, there was no significant difference in the risk of bleeding in patients receiving idrapaparinux in comparison to standard therapy during six months of follow up (RR 0.92, 95% CI 0.69 to 1.22). One study contributed with data for the analysis (n=741 participants) that there was no significant difference in the risk of recurrent VTE during six months follow-up between idrabiotaparinux compared with idraparinux (RR 0.71, 95% CI 0.30 to 1.66). The risk of bleeding was also similar comparing the two interventions (RR 0.71, 95% CI 0.49 to 1.04). Authors' conclusions: The pentasaccharides (fondaparinux, the dose of 2.5 mg idraparinux and equimolar dose of 3.0 mg idrabiotaparinux) may be an effective and safe alternative to conventional anticoagulation treatment for acute DVT.

Submitted by Milena Leite de Oliveira null (milaolive@tupa.unesp.br) on 2017-01-05T10:58:25Z No. of bitstreams: 1 TESE Milena Leite de Oliveira.pdf: 83084301 bytes, checksum: 403f45f944124e6f1f0686e2b91f36a4 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2017-01-09T16:28:44Z (GMT) No. of bitstreams: 1 oliveira_ml_dr_bot.pdf: 83084301 bytes, checksum: 403f45f944124e6f1f0686e2b91f36a4 (MD5) / Made available in DSpace on 2017-01-09T16:28:44Z (GMT). No. of bitstreams: 1 oliveira_ml_dr_bot.pdf: 83084301 bytes, checksum: 403f45f944124e6f1f0686e2b91f36a4 (MD5) Previous issue date: 2016-11-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A alface pode ser infectada por diferentes tipos de vírus. O Lettuce mosaic virus- LMV foi por muitos anos considerado um dos mais frequentes e amplamente distribuídos mundialmente, podendo ocorrer em infecções simples e/ou mistas com Lettuce mottle virus, LeMoV, um provável sequivirus. A falta de informações a respeito dos aspectos biológicos e moleculares relacionados à classificação taxonômica e à transmissão do LeMoV, motivou a testar sua transmissão com afídeos e por sementes, avançar no sequenciamento do genoma viral e avaliar a incidência do vírus em importantes áreas produtoras de alface no estado de São Paulo. Em 2014, dentre um total de 118 plantas sintomáticas analisadas, 63 (53%) foram positivas para a presença de tospovírus, 11 (9%) foram positivas para LMV e, apenas 6 amostras (5%) foram positivas para LeMoV. Em 2015, 40 plantas (80%) estavam infectadas com tospovírus, e o LMV e LeMoV não foram detectados, indicando que o LeMoV não está limitando a produção de alface, pelo menos não durante o ano de 2014 e 2015. A transmissão desse vírus por sementes não foi verificada nas 832 sementes provenientes de plantas de alface infectadas com LeMoV, o que indica que este vírus provavelmente não seja transmitido por semente. Myzus persicae e Aphis gossypii não foram capazes de transmitir o LeMoV de uma planta de alface para outra. Quase toda a sequencia completa do genoma do LeMoV foi obtida e a presença de domínios conservados verificados na região da capa proteica (CP), da helicase (HEL) e da RNA- dependente de RNA polimerase (RdRp), indicando que o LeMoV é membro da família Secoviridae e está estreitamente relacionado com membros do gênero Sequivirus. Durante o período do doutorado sanduíche na Universidade do Hawaii em Manoa, plantas de jasmim estrelado, coletadas no Hawaii, exibindo sintomas foliares característicos aos provocados pelos vírus, foram analisadas por sequenciamento de nova geração (SNG), a fim de identificar os patógenos relacionados com a doença. Sequencias relacionadas aos vírus da família Tombusviridae como o Rosa rugosa leaf distortion virus, Pelargonium ringspot virus, Pelargonium chlorotic ring pattern virus e Elderberry latent virus foram identificados nas plantas de jasmim estrelado, indicando infecção mista por diferentes vírus.

Robust Speaker Recognition (SR) has been a focus of attention for researchers since long. The advancement in speech-aided technologies especially biometrics highlights the necessity of foolproof SR systems. However, the performance of a SR system critically depends on the quality of speech features used to represent the speaker-specific information. This research aims at extracting the speaker-specific information from Mel-frequency Cepstral Coefficients (MFCCs) using deep learning. Speech is a mixture of various information components that include linguistic, speaker-specific and speaker’s emotional state information. Feature extraction for each information component is inevitable in different speech-related tasks for robust performance. However, almost all forms of speech representation carry all the information as a whole, which is responsible for the compromised performances by SR systems. Motivated by the complex problem solving ability of deep architectures by learning high-level task-specific information in the data, we propose a novel Deep Neural Architecture (DNA) to extract speaker-specific information (SI) from MFCCs, a popular frequency domain speech signal representation. A two-stage learning strategy is adopted, which is based on unsupervised training for network initialisation followed by regularised contrastive learning. To train our network in the 2nd stage, we devise a contrastive loss function to discriminate the speakers on the basis of their intrinsic statistical patterns, distributed in the representations yielded by our deep network. This is achieved in the contrastive pair-wise comparison of these representations for similar or dissimilar speakers. To improve the generalisation and reduce the interference of environmental effects with the speaker-specific representation, we regulate the contrastive loss with the data reconstruction loss in a multi-objective optimisation. A detailed study has been done to analyse the parametric space in training the proposed deep architecture for optimum performance. Finally we compare the performance of our learned speaker-specific representations with several state-of-the-art techniques in speaker verification and speaker segmentation tasks. It is evident that the representations acquired through learned DNA are invariant and comparatively less sensitive to the text, language and environmental variability.

Analyzing large volumes of video data is a challenging and time-consuming task. Automating this process would very valuable, especially in ecological research where massive amounts of video can be used to unlock new avenues of ecological research into the behaviour of animals in their environments. Deep Neural Networks, particularly Deep Convolutional Neural Networks, are a powerful class of models for computer vision. When combined with Recurrent Neural Networks, Deep Convolutional models can be applied to video for frame level video classification. This research studies two datasets: penguins and seals. The purpose of the research is to compare the performance of image-only CNNs, which treat each frame of a video independently, against a combined CNN-RNN approach; and to assess whether incorporating the motion information in the temporal aspect of video improves the accuracy of classifications in these two datasets. Video and image-only models offer similar out-of-sample performance on the simpler seals dataset but the video model led to moderate performance improvements on the more complex penguin action recognition dataset.