Contexte: La microscopie joue un rôle important en biologie depuis plusieurs siècles, mais sa résolution a longtemps été limitée à environ 250 nm, de sorte que nombre de structures biologiques (virus, vésicules, pores nucléaires, synapses) ne pouvaient être résolues. Au cours de la dernière décennie, plusieurs méthodes de super-résolution ont été développées pour dépasser cette limite. Parmi ces techniques, les plus puissantes et les plus utilisées reposent sur la localisation de molécules uniques (microscopie à localisation de molécule unique, ou SMLM), comme PALM et STORM. En localisant précisément les positions de molécules fluorescentes isolées dans des milliers d'images de basse résolution acquises de manière séquentielle, la SMLM peut atteindre des résolutions de 20 à 50 nm voire mieux. Cependant, cette technique est intrinsèquement lente car elle nécessite l’accumulation d’un très grand nombre d’images et de localisations pour obtenir un échantillonnage super-résolutif des structures fluorescentes. Cette lenteur (typiquement ~ 30 minutes par image super-résolutive) rend difficile l'utilisation de la SMLM pour l'imagerie cellulaire à haut débit ou en cellules vivantes. De nombreuses méthodes ont été proposées pour pallier à ce problème, principalement en améliorant les algorithmes de localisation pour localiser des molécules proches, mais la plupart de ces méthodes compromettent la résolution spatiale et entraînent l’apparition d’artefacts. Méthodes et résultats: Nous avons adopté une stratégie de transformation d’image en image basée sur l'apprentissage profond dans le but de restaurer des images SMLM parcimonieuses et par là d’améliorer la vitesse d’acquisition et la qualité des images super-résolutives. Notre méthode, ANNA-PALM, s’appuie sur des développements récents en apprentissage profond, notamment l’architecture U-net et les modèles génératifs antagonistes (GANs). Nous montrons des validations de la méthode sur des images simulées et des images expérimentales de différentes structures cellulaires (microtubules, pores nucléaires et mitochondries). Ces résultats montrent qu’après un apprentissage sur moins de 10 images de haute qualité, ANNA-PALM permet de réduire le temps d’acquisition d’images SMLM, à qualité comparable, d’un facteur 10 à 100. Nous avons également montré que ANNA-PALM est robuste à des altérations de la structure biologique, ainsi qu’à des changements de paramètres de microscopie. Nous démontrons le potentiel applicatif d’ANNA-PALM pour la microscopie à haut débit en imageant ~ 1000 cellules à haute résolution en environ 3 heures. Enfin, nous avons conçu un outil pour estimer et réduire les artefacts de reconstruction en mesurant la cohérence entre l’image reconstruite et l’image en épi-fluorescence. Notre méthode permet une microscopie super-résolutive plus rapide et plus douce, compatible avec l’imagerie haut débit, et ouvre une nouvelle voie vers l'imagerie super-résolutive des cellules vivantes. La performance des méthodes d'apprentissage profond augmente avec la quantité des données d’entraînement. Le partage d’images au sein de la communauté de microscopie offre en principe un moyen peu coûteux d’augmenter ces données. Cependant, il est souvent difficile d'échanger ou de partager des données de SMLM, car les tables de localisation seules ont souvent une taille de plusieurs gigaoctets et il n'existe pas de plate-forme de visualisation dédiée aux données SMLM. Nous avons développé un format de fichier pour compresser sans perte des tables de localisation, ainsi qu’une plateforme web (https://shareloc.xyz) qui permet de visualiser et de partager facilement des données SMLM 2D ou 3D. A l’avenir, cette plate-forme pourrait grandement améliorer les performances des modèles d'apprentissage en profondeur, accélérer le développement des outils, faciliter la réanalyse des données et promouvoir la recherche reproductible et la science ouverte. / Background: Microscopy plays an important role in biology since several centuries, but its resolution has long been limited to ~250nm due to diffraction, leaving many important biological structures (e.g. viruses, vesicles, nuclear pores, synapses) unresolved. Over the last decade, several super-resolution methods have been developed that break this limit. Among the most powerful and popular super-resolution techniques are those based on single molecular localization (single molecule localization microscopy, or SMLM) such as PALM and STORM. By precisely localizing positions of isolated fluorescent molecules in thousands or more sequentially acquired diffraction limited images, SMLM can achieve resolutions of 20-50 nm or better. However, SMLM is inherently slow due to the necessity to accumulate enough localizations to achieve high resolution sampling of the fluorescent structures. The drawback in acquisition speed (typically ~30 minutes per super-resolution image) makes it difficult to use SMLM in high-throughput and live cell imaging. Many methods have been proposed to address this issue, mostly by improving the localization algorithms to localize overlapping spots, but most of them compromise spatial resolution and cause artifacts.Methods and results: In this work, we applied deep learning based image-to-image translation framework for improving imaging speed and quality by restoring information from rapidly acquired low quality SMLM images. By utilizing recent advances in deep learning including the U-net and Generative Adversarial Networks, we developed our method Artificial Neural Network Accelerated PALM (ANNA-PALM) which is capable of learning structural information from training images and using the trained model to accelerate SMLM imaging by tens to hundreds folds. With experimentally acquired images of different cellular structures (microtubules, nuclear pores and mitochondria), we demonstrated that deep learning can efficiently capture the structural information from less than 10 training samples and reconstruct high quality super-resolution images from sparse, noisy SMLM images obtained with much shorter acquisitions than usual for SMLM. We also showed that ANNA-PALM is robust to possible variations between training and testing conditions, due either to changes in the biological structure or to changes in imaging parameters. Furthermore, we take advantage of the acceleration provided by ANNA-PALM to perform high throughput experiments, showing acquisition of ~1000 cells at high resolution in ~3 hours. Additionally, we designed a tool to estimate and reduce possible artifacts is designed by measuring the consistency between the reconstructed image and the experimental wide-field image. Our method enables faster and gentler imaging which can be applied to high-throughput, and provides a novel avenue towards live cell high resolution imaging. Deep learning methods rely on training data and their performance can be improved even further with more training data. One cheap way to obtain more training data is through data sharing within the microscopy community. However, it often difficult to exchange or share localization microscopy data, because localization tables alone are typically several gigabytes in size, and there is no dedicated platform for localization microscopy data which provide features such as rendering, visualization and filtering. To address these issues, we developed a file format that can losslessly compress localization tables into smaller files, alongside with a web platform called ShareLoc (https://shareloc.xyz) that allows to easily visualize and share 2D or 3D SMLM data. We believe that this platform can greatly improve the performance of deep learning models, accelerate tool development, facilitate data re-analysis and further promote reproducible research and open science.

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This item was digitized as part of the Million Books Project led by Carnegie Mellon University and supported by grants from the National Science Foundation (NSF). Cornell University coordinated the participation of land-grant and agricultural libraries in providing historical agricultural information for the digitization project; the University of Arizona Libraries, the College of Agriculture and Life Sciences, and the Office of Arid Lands Studies collaborated in the selection and provision of material for the digitization project.

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Palms are ecologically important and charismatic trees of the tropics. They are important to the livelihood of local communities and are key resources for the frugivore community in tropical forests. These frugivores are in turn hunted by humans for food. This ecological connection between human, palms, and frugivores provides a unique setting to study how cultural and ecological components within this multitrophic interaction influences palm populations. In chapter 1, I explored the traditional and ecological knowledge behind the cultivation of palm-weevil larvae for food. I found the Joti people, cultivated two species of weevil-larvae differently, which also determined whether palms were logged before or after reproductive maturity. The cultivation of each weevil-larvae species therefore had a differential impact on palm populations. In chapter 2, I investigated how frugivores mediate interactions between two dominant and co-occuring palms in the Peruvian Amazonia-- Attalea phalerata and Astrocaryum murumuru. I found frugivores codispersed seeds of the two palm species, which contributed to aggregated spatial patterns of their juveniles. Spatial patterns suggested associations between heterospecific palms experienced lower density-dependent mortality than associations between conspecifics and this likely contributes to the coexistence of the two palm species in their early life-history. These findings highlight the importance of dispersers to species coexistence and suggest over-hunting can lead to shifts away from species codominance. In chapter 3, I examined the contribution of dispersal, distance-and density-dependent to spatial ecology of Attalea phalerata. Using microsatellite-based parentage analysis, I found high levels of seed movement mediated by frugivore dispersers. Despite this, I found dispersal limitation remains strong enough to cause spatial aggregation between offspring and parents. As individuals grew towards maturity, distance and density dependent mortality contributed to increasingly disaggregated patterns between older offspring cohorts of parents, non-parent adults, and siblings. These results provide a foundation for assessing the impacts of hunting on the spatial ecology of palm populations. In chapter 4, we characterized 14 microsatellite loci for A. phalerata that were used in the parentage analysis of chapter 3. These loci amplified reliably and were sufficiently polymorphic and will be useful for future studies addressing population-level questions for this species. / text

From 1985 to 2015, local politicians like Kenneth G. Spillias, Jan Winters, and Nancy M. Graham reshaped downtown West Palm Beach. They promised to eliminate urban blight, and turned a crime-ridden area of the city into an upper-middle class entertainment zone frequented by wealthy pleasure-seekers from throughout Palm Beach County. However, much of this transformation was an illusion. These politicians eliminated local taxpayers from the decision-making process by circumventing their votes, but subsequently taxed them to pay for the improvements. Furthermore, blight was not eliminated downtown, merely relocated to areas surrounding the entertainment zone. This resulted in ongoing tension between the mostly white patrons and business owners in the redeveloped area, and the primarily black residents in the dilapidated neighborhoods surrounding this development. / Includes bibliography. / Thesis (M.A.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

At foot of title page: Joint Coconut Research Scheme, Yandina, British Solomon Islands Includes bibliographical references. (p. 111-119)

In the autumn of 1886 the editor in chief of the Swedish social democratic newspaper Social-Demokraten August Palm resigns and Hjalmar Branting takes over as editor in chief. This will lead toa shift how the newspaper writes about culture and general education (bildning in Swedish, after theGerman term Bildung which lacks an English equivalent). August Palm’s resignation and the shift inthe content of the newspaper is in many ways the culmination of an internal struggle within the earlysocial democratic labour movement where one side claims that culture and general education shouldbe made available to all, including workers, and that doing so will lead to the eventual transformationof society. The other side claims that the working class should indeed be granted access to culture andgeneral education, but first an economic transformation must occur. The dispute is over causality, thetwo sides in the conflict have different opinions as to whether the economic transformation of societywill happen before or after culture and general education is made available to the working masses. Inthis study I have shown how these two positions were not as clearly defined or as clearly opposed toeach other as they have sometimes been portrayed in earlier research. As I have shown, there was infact agreement on the basic goal that culture and general education ought to be something thateveryone can enjoy despite there being differing opinions as to how society might get there.