Towards Accurate Reconstruction of Phylogenetic Networks

Since Darwin proposed that all species on the earth have evolved from a common ancestor, evolution has played an important role in understanding biology. While the evolutionary relationships/histories of genes are represented using trees, the genomic evolutionary history may not be adequately captured by a tree, as some evolutionary events, such as horizontal gene transfer (HGT), do not fit within the branches of a tree. In this case, phylogenetic networks are more appropriate for modeling evolutionary histories. In this dissertation, we present computational algorithms to reconstruct phylogenetic networks from different types of data. Under the assumption that species have single copies of genes, and HGT and speciation are the only events through the course of evolution, gene sequences can be sampled one copy per species for HGT detection. Given the alignments of the sequences, we propose systematic methods that estimate the significance of detected HGT events under maximum parsimony (MP) and maximum likelihood (ML). The estimated significance aims at addressing the issue of overestimation of both optimization criteria in the search for phylogenetic networks and helps the search identify networks with the ``right" number of HGT edges. We study their performance on both synthetic and biological data sets. While the studies show very promising results in identifying HGT edges, they also highlight the issues that are challenging for each criterion. We also develop algorithms that estimate the amount of HGT events and reconstruct phylogenetic networks by utilizing the pairwise Subtree-Prune-Regraft (SPR) operation from a collection of trees. The methods produce good results in general in terms of quickly estimating the minimum number of HGT events required to reconcile a set of trees. Further, we identify conditions under which the methods do not work well in order to help in the development of new methods in this area. Finally, we extend the assumption for the genetic evolutionary process and allow for duplication and loss. Under this assumption, we analyze gene family trees of proteobacterial strains using a parsimony-based approach to detect evolutionary events. Also we discuss the current issues of parsimony-based approaches in the biological data analysis and propose a way to retrieve significant estimates. The evolutionary history of species is complex with various evolutionary events. As HGT contributes largely to this complexity, accurately identifying HGT will help untangle evolutionary histories and solve important questions. As our algorithms identify significant HGT events in the data and reconstruct accurate phylogenetic networks from them, they can be used to address questions arising in large-scale biological data analyses

Few-shot Font Generation with Localized Style Representations and Factorization

Automatic few-shot font generation is a practical and widely studied problem because manual designs are expensive and sensitive to the expertise of designers. Existing few-shot font generation methods aim to learn to disentangle the style and content element from a few reference glyphs, and mainly focus on a universal style representation for each font style. However, such approach limits the model in representing diverse local styles, and thus makes it unsuitable to the most complicated letter system, e.g., Chinese, whose characters consist of a varying number of components (often called "radical") with a highly complex structure. In this paper, we propose a novel font generation method by learning localized styles, namely component-wise style representations, instead of universal styles. The proposed style representations enable us to synthesize complex local details in text designs. However, learning component-wise styles solely from reference glyphs is infeasible in the few-shot font generation scenario, when a target script has a large number of components, e.g., over 200 for Chinese. To reduce the number of reference glyphs, we simplify component-wise styles by a product of component factor and style factor, inspired by low-rank matrix factorization. Thanks to the combination of strong representation and a compact factorization strategy, our method shows remarkably better few-shot font generation results (with only 8 reference glyph images) than other state-of-the-arts, without utilizing strong locality supervision, e.g., location of each component, skeleton, or strokes. The source code is available at https://github.com/clovaai/lffont.Comment: Accepted at AAAI 2021, 12 pages, 11 figures, the first two authors contributed equall

Effect of Rare Earth Elements (Er, Ho) on Semi-Metallic Materials (ScN) in an Applied Electric Field

The development of materials and fabrication technology for field-controlled spectrally active optics is essential for applications such as membrane optics, filters for LIDARs, windows for sensors, telescopes, spectroscopes, cameras and flat-panel displays. The dopants of rare earth elements, in a host of optical systems, create a number of absorption and emission band structures and can easily be incorporated into many high quality crystalline and amorphous hosts. In wide band-gap semiconductors like ScN, the existing deep levels can capture or emit the mobile charges, and can be ionized with the loss or capture of the carriers which are the fundamental basis of concept for smart optic materials. The band gap shrinkage or splitting with dopants supports the possibility of this concept. In the present work, a semi-metallic material (ScN) was doped with rare earth elements (Er, Ho) and tested under an applied electric field to characterize spectral and refractive index shifts by either Stark or Zeeman Effect. These effects can be verified using the UV-Vis spectroscopy, the Hall Effect measurement and the ellipsometric spectroscopy. The optical band gaps of ScN doped with Er and doped with Ho were experimentally estimated as 2.33eV and 2.24eV ( 0.2eV) respectively. This is less than that of undoped ScN (2.5 0.2eV). The red-shifted absorption onset is a direct evidence for the decrease of band gap energy (Eg), and the broadening of valence band states is attributable to the doping cases. A decrease in refractive index with an applied field was observed as a small shift in absorption coefficient using a variable angle spectroscopic ellipsometer. In the presence of an electric field, mobile carriers are redistributed within the space charge region (SCR) to produce this electro-refractive effect. The shift in refractive index is also affected by the density and location of deep potential wells within the SCR. In addition, the microstructure change was observed by a TEM analysis. These results give an insight for future applications for the field-controlled spectrally active material systems

Tuning photoluminescence of organic rubrene nanoparticles through a hydrothermal process

Light-emitting 5,6,11,12-tetraphenylnaphthacene (rubrene) nanoparticles (NPs) prepared by a reprecipitation method were treated hydrothermally. The diameters of hydrothermally treated rubrene NPs were changed from 100 nm to 2 μm, depending on hydrothermal temperature. Photoluminescence (PL) characteristics of rubrene NPs varied with hydrothermal temperatures. Luminescence of pristine rubrene NPs was yellow-orange, and it changed to blue as the hydrothermal temperature increased to 180°C. The light-emitting color distribution of the NPs was confirmed using confocal laser spectrum microscope. As the hydrothermal temperature increased from 110°C to 160°C, the blue light emission at 464 to approximately 516 nm from filtered-down NPs was enhanced by H-type aggregation. Filtered-up rubrene NPs treated at 170°C and 180°C exhibited blue luminescence due to the decrease of intermolecular excimer densities with the rapid increase in size. Variations in PL of hydrothermally treated rubrene NPs resulted from different size distributions of the NPs