O objetivo deste trabalho é criar uma metodologia capaz de reconhecer gestos de mãos, a partir de imagens dinâmicas, para interagir com sistemas. Após a captação da imagem, a segmentação ocorre nos pixels pertencentes às mãos que são separados do fundo pela segmentação pela subtração do fundo e filtragem de cor de pele. O algoritmo de reconhecimento é baseado somente em contornos, possibilitando velocidade para se trabalhar em tempo real. A maior área da imagem segmentada é considerada como região da mão. As regiões detectadas são analisadas para determinar a posição e a orientação da mão. A posição e outros atributos das mãos são rastreados quadro a quadro para distinguir um movimento da mão em relação ao fundo e de outros objetos em movimento, e para extrair a informação do movimento para o reconhecimento de gestos. Baseado na posição coletada, movimento e indícios de postura são calculados para reconhecimento um gesto significativo. / The purpose of this paper is to develop a methodology able to recognize hand gestures from dynamic images to interact with systems. After the image capture segmentation takes place where pixels belonging to the hands are separated from the background based on skin-color segmentation and background extraction. The image preprocessing can be applied before the edge detection. The recognition algorithm uses edges only; therefore it is quick enough for real time. The largest blob from the segmented image will be considered as the hand region. The detected regions are analyzed to determine position and orientation of the hand for each frame. The position and other attributes of the hands are tracked per frame to distinguish a movement from the hand in relation to the background and from other objects in movement, and to extract the information of the movement for the recognition of dynamic gestures. Based in the collected position, movement and indications of position are calculated to recognize a significant gesture.

Urinary bladder cancer is a heterogeneous disease appearing in different forms, e.g. non-muscle invasive and muscle invasive. For all variants, the expression of proteins is interesting to analyze for diagnostic, predictive, prognostic and drug targeting purposes, since it reflects the altered gene expression causing the cancer. Since urothelial cells of the bladder are in direct contact with urine it is likely that this body fluid contains cancer-related proteins. In Paper I, unbiased analysis of proteins in urine from urinary bladder cancer patients and controls, using label-free quantification by mass spectrometry, was applied and four interesting proteins APOE, FGB, LRG and SERPINA1 were selected and further analyzed with western and dot blot. In Paper II, two more proteins, POLR1E and TOP2A, were validated as relevant proteins in bladder cancer urine. In Paper III and IV, the proteins GAL1 and STMN1 were investigated for their prognostic and therapeutic target potential in bladder cancer. In Paper II, III and IV, the expression of seven of the proteins were analyzed on tissue microarrays representing tumour tissue from 360 patients with different tumour stages. For the proteins identified by the urine screening approach, their protein expressions were confirmed in bladder cancer tissue. The expression level in tissue of five of the proteins, APOE, FGB, POLR1E (Paper II), GAL1 (Paper III) and STMN1 (Paper IV), increased with tumour stage, showing diagnostic relevance and three of the proteins, SERPINA1 (Paper II), STMN1 (Paper IV) and GAL1 (Paper III) had prognostic potential in urinary bladder cancer. In addition, GAL1 and STMN1 were demonstrated to be highly expressed in metastatic disease and inhibition of STMN1 reduced cell growth (Paper III and IV), indicating that these proteins are promising drug targets in urinary bladder cancer. In conclusion, the approach of this thesis has generated several candidate protein biomarkers in urine and tissue, validated with independent methods, which have the potential to improve the care for bladder cancer patients.

[pt] A pesquisa trata da interação mediada por ferramentas de comunicação e colaboração em ambientes virtuais de aprendizagem, dentro do contexto da educação a distância (EAD), dentro do olhar da usabilidade pedagógica e do design de interação. O estudo parte da premissa de que existem problemas ligados à interação mediada por ambientes virtuais de aprendizagem que dificultam a implementação de estratégias de ensino da EAD baseadas em colaboração e comunicação. Foi, portanto, definido como objetivo localizar necessidades e questões que podem influenciar o uso de ambientes virtuais de aprendizagem para o planejamento e a implementação de estratégias pedagógicas colaborativas, a partir de relatos de docentes. Além de trazer contribuições para o projeto de uma EAD baseada em colaboração e comunicação, a pesquisa contribui metodologicamente para a área do design de interação com a proposição da técnica da entrevista baseada em cenários. A partir de entrevistas não-diretivas com profissionais da EAD, foram desenvolvidos cenários que têm como tema interações entre pessoas em ambientes virtuais de aprendizagem utilizados para EAD. Esses cenários serviram de base para entrevistas semiestruturadas, com docentes tutores. As entrevistas trazem descrições detalhadas sobre como esses profissionais colocam em práticas estratégias pedagógicas baseadas em comunicação e colaboração e mostram o crescimento do papel da tutoria em EAD nos modelos pedagógicos que utilizam essas estratégias, expondo situações que indicam a necessidade de sistemas que apoiem as tarefas do tutor dentro dos ambientes virtuais de aprendizagem. / [en] This research deals with interaction mediated by communication and collaboration tools in virtual learning environments, within the context of distance education, and from the standpoint of pedagogical usability and interaction design. It is assumed that there are problems related to interaction mediated by virtual learning environments that hinder the implementation of teaching strategies of DE-based collaboration and communication. Thus, the study, based on teachers reports, aims to find requirements and issues that may influence the use of virtual learning environments for planning and implementation of collaborative teaching strategies. In addition to bringing contributions to the design of a distance education based on collaboration and communication, research contributes methodologically to the area of interaction design with the proposition of the use of scenario-based interview technique. Unstructured interviews were conducted with professionals of distance education, to support the development of scenarios that served as subjects for the interview technique based on scenarios with teachers directly involved in interactions with students during courses. The interviews include detailed descriptions of how these professionals put into practice pedagogical strategies based on communication and collaboration and expose the growing role of tutoring in distance education pedagogical models that propose collaborative teaching strategies, resulting in the need for systems that support tutor tasks within virtual learning environments.

<p dir="ltr">Generative Image-to-Image Translation (I2IT) involves transforming an input image from one domain to another. Typically, this transformation retains the content in the input image while adjusting the domain-dependent style elements. Generative I2IT finds utility in a wide range of applications, yet its effectiveness hinges on adaptations to the unique characteristics of the data at hand. This dissertation pushes the boundaries of I2IT by applying it to stain-related problems in computational pathology. Particularly, the main contributions span two major applications of stain translation: H&E-to-H&E and H&E-to-IHC, each with its unique requirements and challenges. More specifically, the first contribution addresses the generalization challenge posed by the high variability in H&E stain appearances to any task-specific machine learning models. To this end, the Generative Stain Augmentation Network (G-SAN) is introduced to augment the training images in any downstream task with random and diverse H&E stain appearances. Experimental results demonstrate G-SAN’s ability to enhance model generalization across stain variations in downstream tasks. The second key contribution in this dissertation focuses on H&E-to-IHC stain translation. The major challenge in learning accurate H&E-to-IHC stain translation is the frequent and sometimes severe inconsistencies in the groundtruth H&E-IHC image pairs. To make training more robust to these inconsistencies, a novel contrastive learning based loss, named the Adaptive Supervised PatchNCE (ASP) loss is presented. Experimental results suggest that the proposed ASP-based framework outperforms the state-of-the-art in H&E-to-IHC stain translation by significant margins. Additionally, a new dataset for H&E-to-IHC translation – the Multi-IHC Stain Translation (MIST) dataset, is released to the public, featuring paired images from H&E to four different IHC stains. For future directions of generative I2IT in stain translation problems, a proof-of-concept study of applying the latest diffusion model based I2IT methods to the problem of virtual H&E staining is presented.</p>

Idiopathic Pulmonary Fibrosis (IPF) is a debilitating respiratory disorder that is characterized by a progressive decline in lung function. Originating through unknown etiology, it is essentially an unchecked wound healing response that causes the build-up of excessive scar tissue in the lung interstitial tissue with a heavy toll on the patient’s respiratory capacity. Pro-fibrotic alternatively activated macrophages (M2) have been linked as an important contributor to the fibrotic remodeling of the lung. Previous Ask research indicates that targeting M2 macrophages is possible through the use of the Dectin-1 receptor, a transmembrane cell surface receptor found in high abundance on M2 macrophages. Activating the Dectin-1 receptor through the use of beta-glucan, a ligand the receptor has a high affinity for, initiates a pro-inflammatory response within the naturally immunosuppressive macrophage and can alter its activity to be less fibrogenic. Our data suggest that M2 polarization of naïve macrophages can be inhibited in vitro by beta-glucan microparticles. Additionally, we have found that polarized M2 macrophages adopt M1-like characteristics when treated with beta-glucan microparticles, in a process that is largely Dectin-1 dependent. M2 cell surface marker CD206, increased levels of which are associated with rapidly progressing IPF, shows significantly decreased frequency of expression in M2 macrophages treated with beta-glucan microparticles. Our assessment for cell-specific uptake of beta-glucan microparticles suggests an important role of the Dectin-1 receptor for significantly increased uptake in murine wild-type M2 macrophages relative to their Dectin-1 knockout counterpart. The use of beta-glucan microparticles as a potential anti-fibrotic therapeutic was assessed in the bleomycin model of fibrotic lung disease. Mice given bleomycin and treated with beta-glucan displayed decreased soluble collagen content and TGFB expression within lung homogenate relative to fibrotic bleomycin control mice. Overall, these results provide insight into the use of beta-glucan as a potential activity modulator of macrophage function in IPF and the possibility of its use as a therapeutic. / Thesis / Master of Science (MSc)

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No description available.

[pt] Realidade Virtual é uma tecnologia capaz de alterar a percepção do usuário e o transportar para um ambiente mediado por tecnologia, criado pelo designer daquela experiência. Esta dissertação analisa o design de experiências imersivas de Realidade Virtual que tem como objetivo informar ou educar participantes sobre informações complexas. Para tal, fez-se uso de taxonomias de UX e educacionais como base de categorização das experiências. A seleção de trabalhos para análise foi feita a partir de uma base massiva de trabalhos publicados sobre realidade virtual. Utilizou-se uma metodologia original, criada para a presente pesquisa e detalhada ao longo da mesma, baseada em técnicas computacionais de ciência de dados para classificação dos resultados, facilitando a seleção e minimizando vieses de escolha. Ao fim desse processo iterativo, os trabalhos escolhidos foram analisados em termos de aprendizado, engajamento e suas características específicas de UX e educacionais. Tal análise da amostragem de trabalhos selecionada indica que o potencial educacional de Realidade Virtual é significativo e aplicável em diversas áreas, e que é possível estimular o engajamento dos participantes com relativa facilidade. Entretanto, a efetividade educacional da experiência é mais complexa de se alcançar. Sugere-se algumas maneiras com potencial de ajudar a alcançar esse resultado, como: maior foco no design instrucional; maior colaboratividade; mais participação de instrutores; mais interações que permitam atividades criativas, bem como modos mais criativos de apresentação das informações. Essas sugestões e recomendações podem ajudar os designers de experiências em Realidade Virtual (ou de outros tipos de realidades mediadas por tecnologia) a proporcionarem ou explorarem o potencial de experiências que podem se mostrar mais efetivas em alcançar os objetivos de educar ou informar sobre temas complexos. / [en] Virtual Reality is a technology that can alter a user s perception and transport them into a technology-mediated environment created by the designer of that virtual experience. This research examines the design of immersive Virtual Reality experiences that aim to inform or educate participants about complex topics. To do so, we use UX and educational taxonomies as a basis for categorizing the experiences. The selection of publications for analysis was made from a massive base of published works on virtual reality. An original methodology was used, created for this research and detailed throughout, based on computational data science techniques to classify the results, facilitating the selection and minimizing biases. At the end of this iterative process, the chosen works were analyzed in terms of learning, engagement, and their specific UX and educational characteristics. Such analysis indicates that the educational potential of Virtual Reality is significant and applicable in a variety of areas, and that it is possible to create engaging experiences with relative ease. However, the educational effectiveness of the experience is more complex to achieve. We explore suggestions that may have the potential to achieve this outcome, such as: more focus on instructional design; more collaboration; more instructor participation; more interactions that allow for creative activities, as well as more creative ways of presenting information. These suggestions and recommendations can help designers of Virtual Reality experiences (or other types of technology-mediated realities) to provide or explore the potential for experiences that may prove more effective in achieving the goals of educating or informing about complex topics.

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with worsening respiratory symptoms and physiological impairment. Pulmonary fibrosis is a chronic lung disease characterized by forming scar tissue (fibrosis) in the lungs. Alternatively activated macrophages (M2) known as pro-fibrotic are known to contribute to the fibrotic remodeling of the lung. In addition to the polarization of slices from naïve to pro-fibrotic, the addition of anti-fibrotic therapeutics reprogram slices back to a naïve condition. To polarize the slices, naïve slices are incubated with a previously investigated method in the lab known as the polarization cocktail. The polarization cocktail can be achieved by adding of IL-4, IL-6 and IL-13 to naïve(M0) slices in the Precision Cut lung slice (PCLS) model. For the therapeutic model, slices are incubated with the polarization cocktail and subsequently with the therapeutic. Our results have shown that the precision cut lung slice model can mimic previously investigated in-vivo experiments with the polarization cocktail. Secondly, the addition of therapeutics result in the slices exhibiting lower amounts of M2 markers and arginase activity concluding the model is suitable for the polarization and reprogramming of macrophages. / Thesis / Master of Science in Medical Sciences (MSMS)

No description available.