A piece of popular music is usually defined as a combination of vocal melody and instrumental accompaniment. People often start with the melody part when they are trying to compose or reproduce a piece of popular music. However, creating appropriate instrumental accompaniment part for a melody line can be a difficult task for non-musicians. Automation of accompaniment generation for vocal melodies thus can be very useful for those who are interested in singing for fun. Therefore, a computer software system which is capable of generating harmonic accompaniment for a given vocal melody input has been presented in this thesis. This automatic accompaniment system uses a Hidden Markov Model to assign chord to a given part of melody based on the knowledge learnt from a bank of vocal tracks of popular music. Comparing with other similar systems, our system features a high resolution key estimation algorithm which is helpful to adjust the generated accompaniment to the input vocal. Moreover, we designed a structure analysis subsystem to extract the repetition and structure boundaries from the melody. These boundaries are passed to the chord assignment and style player subsystems in order to generate more dynamic and organized accompaniment. Finally, prototype applications are discussed and the entire system is evaluated.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第18340号 / 農博第2065号 / 新制||農||1024(附属図書館) / 学位論文||H26||N4847(農学部図書室) / 31198 / 京都大学大学院農学研究科森林科学専攻 / (主査)教授 木村 恒久, 教授 西尾 嘉之, 教授 髙野 俊幸 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

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<p dir="ltr">Dietary fibers have been observed to modulate the gut microbiome in ways that prevent and moderate human diseases and confer health benefits onto their human host. How dietary fibers do this is through their structure; gut microbes are equipped with a variety of differ- ent carbohydrate-active enzymes (CAZymes) that allow some to hydrolyze glycosidic bonds, thereby utilizing the dietary fiber. The more complex the dietary fiber, the more diverse the maintained gut microbiota may be, as specialist species may be required for complete hydrol- ysis. Therefore, increasing structural complexity of dietary fibers may increase gut microbial diversity and help prevent diseases. To understand if structural features impact the gut mi- crobiome, a set of resistant glucans varying in structures, including mixed-linkage -glucans, resistant maltodextrins (similar to type IV resistant starch) and polydextroses, which are comprised entirely of glucose, were used as substrates in an in vitro sequential batch fermen- tation using fecal microbiota form three healthy donors as inocula. I measured metabolic outputs, growth curves, and community structures by 16S rRNA amplicon sequencing, which I analyzed for through alpha and beta diversity differences and taxa that overrepresented and increased in each treatment. My results show that, depending on the donor and the resistant glucan, structure does significantly impact the concentrations of short-chain fatty acids (SCFAs) and other metabolites that are produced. Resistant glucan structure also impacts alpha and beta diversity to a degree and linear discriminant analysis (by LEfSe) results also support that specific species have preference towards substrates as well. Next, resistant glucans were supplemented into a high-fat diet, and compared these diets to a low- fat diet (LFD), high-fat diet with cellulose (HFD), and high-fat without cellulose (HWC) in a mouse study using C57BL/6J mice over 4 weeks. Increasing microbial diversity will not only increase diversity in the gut microbiome, but it will also provide protective effects in behavior such as helping to prevent anxiety. I measured weight, metabolic outputs, 16S community structure, changes in alpha and beta diversity, and differential abundances of OTUs and taxa by discriminant analysis Effect Size (LEfSe) and Metastats, and anxiety behaviors using open field and light/dark box tests. Microbial community structure was significantly different in treatment groups from controls. Anxiety for mice in tapioca dextrin 01 (TD01), tapioca dextrin 03 (TD03), and resistant maltodextrin (RMF) treatment groups were gen- erally increased, suggesting that the chemical structure of these resistant dextrins may alter the gut microbiome in ways that may influence behavior.</p><p dir="ltr">My overall results support the hypothesis that the fine structural features of dietary fibers do significantly impact the gut microbiome by selecting for specific microbiota, and may even impact cognition and behavior.</p>

京都大学 / 新制・課程博士 / 博士(理学) / 甲第25128号 / 理博第5035号 / 新制||理||1718(附属図書館) / 京都大学大学院理学研究科化学専攻 / (主査)准教授 板東 俊和, 教授 深井 周也, 教授 秋山 芳展 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

Novel diorganoantimony(III) fluorides containing ligands with pendant arms, R2SbF (5), (R)PhSbF (6) [R = 2-(2′,6′-iPr2C6H3N[double bond, length as m-dash]CH)C6H4], R′′2SbF (7) and (R′′)PhSbF (8) [R′′ = 2-(Me2NCH2)C6H4], were prepared via the ionic derivatives [R2Sb]+[PF6]− (1), [(R)PhSb]+[PF6]− (2), [R′′2Sb]+[SbF6]− (4) and [(R′′)PhSb]+[SbF6]− (obtained in situ) by treatment with [Bu4N]F·3H2O. The ionic species used as starting materials as well as [R′2Sb]+[PF6]− (3) [R′ = 2-(2′,4′,6′-Me3C6H2N[double bond, length as m-dash]CH)C6H4] were obtained from the corresponding bromides or chlorides and Tl[PF6] or Ag[SbF6]. The compounds were investigated by multinuclear NMR spectroscopy in solution, MS and IR spectroscopy in the solid state. The molecular structures of the ionic species 1·2CH2Cl2 and 3·2CHCl3 as well as of the fluorides 5–8 were determined by single-crystal X-ray diffraction. / Dieser Beitrag ist aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Scene understanding attempts to produce a textual description of visible and latent concepts in an image to describe the real meaning of the scene. Concepts are either objects, events or relations depicted in an image. To recognize concepts, the decision of object detection algorithm must be further enhanced from visual similarity to semantical compatibility. Semantically relevant concepts convey the most consistent meaning of the scene. Object detectors analyze visual properties (e.g., pixel intensities, texture, color gradient) of sub-regions of an image to identify objects. The initially assigned objects names must be further examined to ensure they are compatible with each other and the scene. By enforcing inter-object dependencies (e.g., co-occurrence, spatial and semantical priors) and object to scene constraints as background information, a concept classifier predicts the most semantically consistent set of names for discovered objects. The additional background information that describes concepts is called context. In this dissertation, a framework for building context-based concept detection is presented that uses a combination of multiple contextual relationships to refine the result of underlying feature-based object detectors to produce most semantically compatible concepts. In addition to the lack of ability to capture semantical dependencies, object detectors suffer from high dimensionality of feature space that impairs them. Variances in the image (i.e., quality, pose, articulation, illumination, and occlusion) can also result in low-quality visual features that impact the accuracy of detected concepts. The object detectors used to build context-based framework experiments in this study are based on the state-of-the-art generative and discriminative graphical models. The relationships between model variables can be easily described using graphical models and the dependencies and precisely characterized using these representations. The generative context-based implementations are extensions of Latent Dirichlet Allocation, a leading topic modeling approach that is very effective in reduction of the dimensionality of the data. The discriminative contextbased approach extends Conditional Random Fields which allows efficient and precise construction of model by specifying and including only cases that are related and influence it. The dataset used for training and evaluation is MIT SUN397. The result of the experiments shows overall 15% increase in accuracy in annotation and 31% improvement in semantical saliency of the annotated concepts. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

Na Dissertação de Mestrado foi realizado um estudo sobre o comportamento de vigas mistas de aço e concreto biapoiadas sob iteração completa, compostas por perfis classificados como compactos em situação de incêndio. Apesar de ditas biapoiadas, a ideia principal da Dissertação é considerar, na análise em situação de incêndio, a reserva de capacidade existente nas extremidades dessas vigas, usualmente desprezada no dimensionamento à temperatura ambiente, provinda da continuidade da armadura longitudinal negativa presente na laje de concreto, sendo possível dispensar o revestimento contra fogo nesses elementos. Serão abordados, de início, os métodos de dimensionamento ao Estado-Limite Último de vigas mistas à temperatura ambiente, a fim de explicar o comportamento estrutural desse tipo de elemento, dando base para a posterior análise térmica. A análise térmica foi realizada, em uma primeira etapa, por métodos simplificados segundo normas vigentes e tomando hipóteses simplificadoras em que se desprezam esforços indiretos provocados pela dilatação térmica e gradiente térmico, sendo possível aplicar os conceitos no dia a dia de projeto. Numa segunda etapa foi realizada análise termestrutural com modelos numéricos para estudar o comportamento e colapso da viga, sendo os resultados suficientes para validar os valores de TRF encontrados por análise simplificada seguindo métodos normativos. Como conclusão, o ganho de capacidade estrutural da viga, proporcionado pela adoção da ligação mista no apoio, foi suficiente para situações de TRRFs entre 15 min e 21 min, no caso de perfis mais leves, com geometria própria para serem utilizados como vigas de piso de edifícios. Análises mostraram que não é possível justificar a ausência de revestimento contra incêndio para TRRFs de 30 min ou superiores. Tempos inferiores podem ser adotados de acordo com o denominado método do tempo equivalente, limitado a 15 min e são mais usuais para edificações de pequeno porte. / A study will be carried out on the behavior of simply supported, full interaction composite steel and concrete beams composed by compact profiles in fire situation. Despite being designed as simply supported, the main idea is to consider, in the fire situation analysis, the moment resistance capacity reserve on the beam supports, usually neglected during room temperature design, due to the upper longitudinal reinforcement present in the concrete slab, being possible to dispense fireproof coating in these elements. First, room temperature design procedures of composite beams will be approached in order to explain the structural behavior of this type of elements, providing a basis for subsequent thermal analysis. The thermal analysis will be carried out, in a first stage, by simplified methods according to design procedures and adopting simplifying hypotheses in which indirect stresses caused by thermal expansion and thermal gradient are neglected, being possible to apply those concepts in structural design offices. In a second step, thermal stress analyses were performed with aid of numerical models to study the structural behavior and collapse time of the beam. The results were sufficient to validate the fire resistance time values found by the simplified analysis following design methods. As a conclusion, the structural capacity increase of the beam, provided by the adoption of the composite connection at the support in case of lighter steel profiles usually chosen to be used as buildings floor beams, was sufficient for situations of standard fire resistance requirements between 15 min and 21 min. Analyzes have shown that it is not possible to justify the absence of fire resistant coating for standard fire resistance requirements of 30 min or higher. Lower times can be adopted according to the so-called equivalent time method, limited to 15 min, which are more common for small buildings.

In this thesis a computational complement to experimental observables will be presented. Computational tools such as molecular dynamics and quantum chemical tools will be used to aid in the interpretation of experimentally (NMR) obtained structural data. The techniques are applied to study the dynamical features of biologically important carbohydrates and their interaction with proteins. When evaluating conformations, molecular mechanical methods are commonly used. Paper I, highlights some important considerations and focuses on the force field parameters pertaining to carbohydrate moieties. Testing of the new parameters on a trisaccharide showed promising results. In Paper II, a conformational analysis of a part of the repeating unit of a Shigella flexneri bacterium lipopolysaccharide using the modified force field revealed two major conformational states. The results showed good agreement with experimental data. In Paper III, a trisaccharide using Langevin dynamics was investigated. The approach used in the population analysis included a least-square fit technique to match T1 elaxation parameters. The results showed good agreement with experimental T-ROE build-up curves, and three states were concluded to be involved. In Paper IV, carbohydrate moieties were used in the development of prodrug candidates, to “hide” peptide opioid receptor agonists. Langevin dynamics and quantum chemical methods were employed to elucidate the structural preference of the compound. The results showed a chemical shift difference between hydrogens across the ring for the two isomers as well as a difference in the coupling constant, when taking the dynamics into account. In Paper V, the interaction of the Salmonella enteritidis bacteriophage P22 with its host bacterium, involves an initial hydrolysis of the O-antigenic polysaccharide (O-PS). Docking calculations were used to examine the binding between the Phage P22 tail-spike protein and the O-PS repeating unit. Results indicated a possible active site in conjunction with NMR measurements.

How do we find patterns and anomalies, on graphs with billions of nodes and edges, which do not fit in memory? How to use parallelism for such Tera- or Peta-scale graphs? In this thesis, we propose PEGASUS, a large scale graph mining system implemented on the top of the HADOOP platform, the open source version of MAPREDUCE. PEGASUS includes algorithms which help us spot patterns and anomalous behaviors in large graphs. PEGASUS enables the structure analysis on large graphs. We unify many different structure analysis algorithms, including the analysis on connected components, PageRank, and radius/diameter, into a general primitive called GIM-V. GIM-V is highly optimized, achieving good scale-up on the number of edges and available machines. We discover surprising patterns using GIM-V, including the 7-degrees of separation in one of the largest publicly available Web graphs, with 7 billion edges. PEGASUS also enables the inference and the spectral analysis on large graphs. We design an efficient distributed belief propagation algorithm which infer the states of unlabeled nodes given a set of labeled nodes. We also develop an eigensolver for computing top k eigenvalues and eigenvectors of the adjacency matrices of very large graphs. We use the eigensolver to discover anomalous adult advertisers in the who-follows-whom Twitter graph with 3 billion edges. In addition, we develop an efficient tensor decomposition algorithm and use it to analyze a large knowledge base tensor. Finally, PEGASUS allows the management of large graphs. We propose efficient graph storage and indexing methods to answer graph mining queries quickly. We also develop an edge layout algorithm for better compressing graphs.