Caracterização de isolados de Corynespora cassiicola e avaliação da sensibilidade in vitro a fungicidas

Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Biológicas, Departamento de Fitopatologia, Programa de Pós-Graduação em Fitopatologia, 2015.

Germinação in vitro e desenvolvimento pós-seminal de plântulas de Pilosocereus aurisetus (Werderm.) Byles & G.D. Rowley (Cactaceae)

Pilosocereus aurisetus é uma espécie de cactos de importância econômica e ambiental que se encontra em risco de extinção. A propagação em áreas naturais ocorre, principalmente, de forma sexuada; entretanto, não há registro da germinação e viabilidade de sementes e morfologia pós-seminal de plântulas dessa espécie. Assim, objetivou-se avaliar a germinação de sementes e descrever a morfologia do desenvolvimento pós-seminal de plântulas de P. aurisetus. Para isso, sementes, armazenadas em condições ambientais por 19 meses, foram submetidas aos tratamentos: embebição em água por 24 horas; pré-resfriamento; imersão em solução de giberelina, nas concentrações de 250 mg L-1 e 500 mg L-1; e um tratamento controle. As sementes foram colocadas para germinar em meio de cultura MS, por 30 dias, quando se avaliou a percentagem de germinação. O delineamento estatístico foi o inteiramente casualizado, com cinco tratamentos e quatro repetições, sendo dispostas 25 sementes por parcela. A caracterização pós-seminal foi realizada por um período de 60 dias, utilizando-se microscópio binocular, com base nas Regras para Análise de Sementes. Maior percentagem da germinação de sementes ocorreu no controle, ou quando embebidas por 24 horas, sendo observados 90% e 83%, respectivamente. A morfologia do desenvolvimento pós-seminal indicou que a germinação é do tipo epígea, com hipocótilo de reserva; suas plântulas sofrem modificações na região do colo, para a emissão de raízes, e apresentam cerdas no ápice caulinar, mesmo na fase inicial da expansão cotiledonar. A diferenciação e início da formação das costelas iniciam-se aos 60 dias após a germinação, com o desenvolvimento do epicótilo.

Tourists’ perceptions of world heritage destinations: the case of Guimarães

Guimarães is a world heritage site (UNESCO) since December 2001, and is hosting the European Capital of Culture (ECOC) in 2012. This paper examines the profile, destination image and motivations of tourists’ visiting Guimarães before the cultural event. Based on survey responses from 276 tourists, this study found that tourists arrived to Guimarães came from the two most important cities in the northern part of Portugal (Porto and Braga). They are relatively young and well educated compared with the average tourists that visited Portugal. The results suggest that many tourists are aware of the city status as a world heritage site encompassing a historic centre, monuments, and architectural buildings. Further, these perceptions shape the image of Guimarães, as the factor analysis indicates that “historical background and functionality” is the most reliable and valid factor behind the choice of visiting the city. Finally, the main tourists’ motivation to choose Guimarães as theirs destination is educational, rather than recreational as they want to live a learning experience.

Real-time 3D interactive segmentation of echocardiographic data through user-based deformation of B-spline explicit active surfaces

Image segmentation is an ubiquitous task in medical image analysis, which is required to estimate morphological or functional properties of given anatomical targets. While automatic processing is highly desirable, image segmentation remains to date a supervised process in daily clinical practice. Indeed, challenging data often requires user interaction to capture the required level of anatomical detail. To optimize the analysis of 3D images, the user should be able to efficiently interact with the result of any segmentation algorithm to correct any possible disagreement. Building on a previously developed real-time 3D segmentation algorithm, we propose in the present work an extension towards an interactive application where user information can be used online to steer the segmentation result. This enables a synergistic collaboration between the operator and the underlying segmentation algorithm, thus contributing to higher segmentation accuracy, while keeping total analysis time competitive. To this end, we formalize the user interaction paradigm using a geometrical approach, where the user input is mapped to a non-cartesian space while this information is used to drive the boundary towards the position provided by the user. Additionally, we propose a shape regularization term which improves the interaction with the segmented surface, thereby making the interactive segmentation process less cumbersome. The resulting algorithm offers competitive performance both in terms of segmentation accuracy, as well as in terms of total analysis time. This contributes to a more efficient use of the existing segmentation tools in daily clinical practice. Furthermore, it compares favorably to state-of-the-art interactive segmentation software based on a 3D livewire-based algorithm.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.