京都大学 / 新制・課程博士 / 博士(薬学) / 甲第24563号 / 薬博第861号 / 新制||薬||243(附属図書館) / 京都大学大学院薬学研究科薬学専攻 / (主査)教授 髙倉 喜信, 教授 山下 富義, 教授 小野 正博 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(薬学) / 甲第23845号 / 薬博第852号 / 新制||薬||242(附属図書館) / 京都大学大学院薬学研究科薬学専攻 / (主査)教授 髙倉 喜信, 教授 山下 富義, 教授 小野 正博 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

A Clinic for the study of Sleep Disorders The proposal for a clinic for sleep disorders sited on the edge of Dupont Circle within the District of Columbia. This thesis is a reference to time and movement as it relates to our individual perception. We each experience our environments differently and architecture should be prescribed to the fit the needs of the individual. It is the study of design evolution along a time-line. The science of effect. As we move along a line how does our environment and influence shape the final outcome? In architecture, process is the task of understanding. The following documentation is my personal time-line along that undefined path. / Master of Architecture

Yes / The northern and western isles of Scotland have proved fertile ground for archaeological investigation over the last 100 years. However, the nature of the landscape with its rugged coastlines and irregular topography, together with rapid peat growth rates, make for challenging surveying. Commonly, an archaeological monument or series of monuments is identified but little is known about the surrounding areas and, in particular, the palaeo-landscapes within which the monuments are located. This situation is exemplified by the standing stones of Calanais in Lewis. Here, surrounding peat bogs have buried a significant portion of the landscape around which the stones were first erected. This project identifies remote sensing geophysical techniques that are effective in mapping the buried (lost) landscape and thus aid better contextualisation of the stone monuments within it. Further, the project demonstrates the most appropriate techniques for prospecting across these buried landscapes for as yet unidentified stone features associated with the lives of the people who constructed the monuments. / Scottish Enterprise / Research Development Fund Publication Prize Award winner, December 2019.

English language textbooks in Swedish upper secondary education play a significant role in students' perception of culture. The cultural representation within these textbooks is vital to analyze due to the Swedish National Agency for Education (2022a, 2022b)guidelines regarding students' exposure to the English-speaking world. The study aimed to analyze how two Swedish ELT (English Language Teaching) textbooks present cultural representations in accordance with Kachru’s (1992) Concentric Three-Circle Model. The study also aimed to investigate Swedish students’ multicultural exposure to English-speaking countries through ELT textbooks. The study primarily implements a qualitative research methodology through document analysis of two Swedish ELTtextbooks for upper secondary school; however, the study also contains a quantitative aspect to clarify the cultural representations found in the textbooks per Kachru’s (1992)framework. Moreover, the study employs Critical Discourse Analysis (CDA) to analyze power relations embedded in the language and cultural representations found in two textbooks. The textbooks include examples from all circles of Kachru’s (1992)model but focus heavily on Inner Circle countries. Both textbooks provide insight into multicultural understanding and provide cultural norms, some of which are being challenged and problematized. The study's findings indicate a cultural bias and power imbalance in the cultural representations of the ELT textbooks, as the Inner Circle countries are presented as superior and normative. In contrast, the Outer- and Expanding Circle countries are marginalized despite being represented with a degree of critical cultural reflection. Further research could explore students' attitudes when working with other aspects, such as gender representation.

Online gaming has over the years become very popular and during the global pandemic of 2019, gained an even larger amount of people indulging in the activity. All this online activity has led to a decline in in-person social interactions which have been researched to have negative effects on young adults. This thesis aims to find ways to promote more in-person social interaction with the help of games. An artifact in the form of a video game was created with active video game principles and pervasive game characteristics in mind, with the goal of achieving social interaction between players and spectators. Nintendo Joy-Con controllers are the main controller used and an external microphone to capture sounds is used to fulfill the prerequisites of pervasive games. A collection of five different minigames was created, all with different ways that noise can affect the gameplay. The results of the experiments showed that the artifact promotes in-person social interactions between players and spectators by making the spectators able to interact with the games.

South African learners continue to perform poorly in high school Circle Geometry. Lack of learner confidence and motivation in Mathematics may be the contributing factors to the low success rate in Circle Geometry. These factors, coupled with Conventional Teaching Instructions (CTI), may have contributed to the significant reduction in the number of learners enrolled for Mathematics, and provided a rationale for the study that explored a possible alternative teaching pedagogy to motivate and eventually improve learner performance in Circle Geometry. The study aimed to investigate the comparative effects of Computer Assisted Instruction (CAI) and CTI on the performance and motivation of Grade 11 learners in the topic of Circle Geometry. The population of the study consisted of Grade 11 Mathematics learners from 65 secondary schools in the Ekurhuleni North District of Gauteng province in South Africa. Using convenience sampling techniques two schools with n=136 Grade 11 Mathematics learners and two teachers participated in the study. One school formed the experimental group (n=71) and the other school formed the control group (n=65). The study followed a quasi-experimental design with a non-equivalent control group approach consisting of pre-and post-test measures. Intact classes participated in the study as it was not possible to randomly select participants for the study. Both groups wrote a standardised achievement pre-test to ascertain their performance status at the beginning of the study. CAI was implemented in the experimental school while CTI was implemented in the control school. A similar post-test was administered on both groups to measure the comparative effects of each teaching method on the performance of learners. A questionnaire was also administered to both groups to measure the motivation of learners. A purposive sample (n=12) was selected from both groups to participate in semi-structured interviews to account for the results of the test and the questionnaire. A socio-constructivist theory framed the study. Analysis of Covariance (ANCOVA) was used to analyse data. The results of this investigation indicated that the use of the computer software, GeoGebra, in the teaching and learning of Circle Geometry improved the performance and motivation of Grade 11 learners. / Mathematics Education / M. Ed. (Mathematics Education)

Made available in DSpace on 2017-07-21T14:19:37Z (GMT). No. of bitstreams: 1 CLAUDIO KAPP JUNIOR.pdf: 1815678 bytes, checksum: d0a947fefc0e6b1b5a0242eb975f3cb7 (MD5) Previous issue date: 2013-03-18 / No-till systems with diversified crop rotations have stood out of the most effective strategies to improve the sustainability of farming in tropical and subtropical regions. Wheat (Triticum aestivum L.) is one of the most important crops used in this rotation during the autumn-winter season. Nitrogen (N) is uptake in larger amounts by plants, it is essential for the structure and functions in the cell, for all enzymatic reactions and is part of the chlorophyll molecules. Nitrogen fertilizers represent a significant part of the costs of production and due to the dynamics of N in soil, losses of N occur and cause economic and environmental damages. In the same agricultural area may exist changing demands for this nutrient. The attributes of the plant commonly used as indicators of N are NO3- content in stem, leaf chlorophyll content, the intensity of the green color and the N foliar content, dry biomass, and the extraction of N by plants. Lower levels of N can cause chlorophyll deficiency that is recognized by whitish or pale foliar coloration, and this changing in plant color can be identified using remote sensing techniques. This study aimed to evaluate the correlations between spectral reflectance data obtained by commercial ground sensors (Clorofilog 1030, GreenSeeker, and Crop Circle ACS-470) and attributes of wheat crop in response to N rates in top dressing under a no-till system. The efficiency of the sensors was evaluated in two ways: (i) by classical statistical methods, and (ii) through the application of Artificial Neural Networks, a machine learning technique. For the use of Artificial Neural Networks, this study compared the performance of the algorithms Resilient Propagation and Backpropagation. Because wheat plants exhibited adequate nutritional status, even without N application in top dressing, Clorofilog 1030 readings were not sensitive to variations of N rates. Thus, this sensor also did not correlate significantly with the N foliar content, dry biomass, and the extraction of N by wheat plants. The indices obtained by reflectance sensors Crop Circle and GreenSeeker had close correlation with the rates of N in top dressing, dry biomass, and the extraction of N by wheat plants. The Crop Circle and GreenSeeker sensors showed weaker correlation with the N content in leaves, and especially with the wheat grain yield. In this way, it was evident that grain yield has not followed the dry biomass production when high wheat grain yields were obtained. The correlation coefficients obtained by the Resilient Propagation and Backpropagation algorithms were similar to those found by statistical analysis. The Artificial Neural Networks technique had satisfactory behavior similar to classical statistical methods. / O sistema plantio direto com rotação diversificada de culturas tem sido apontado como uma das melhores estratégias para aumentar a sustentabilidade da agricultura em regiões tropicais e subtropicais. Uma das culturas de maior importância nessa rotação durante a estação de outono–inverno é o trigo (Triticum aestivum L.). O nitrogênio (N) é um dos nutrientes extraídos em maior quantidade pelas plantas, sendo essencial para a estrutura e funções nas células, para todas as reações enzimáticas e faz parte das moléculas de clorofila. Os fertilizantes nitrogenados representam parte significativa dos custos da produção agrícola e, em razão da dinâmica do N no solo, perdas consideráveis de N podem ocorrer e causar prejuízos econômicos e ambientais. Em uma mesma área agrícola podem existir demandas variáveis por este nutriente. Os atributos da planta mais utilizados como indicadores de N são o teor de NO3- no colmo, o teor de clorofila, a intensidade da cor verde e o teor de N na folha bandeira, a produção de matéria seca da parte aérea e a extração de N pelas plantas. Níveis baixos de N podem ocasionar deficiência de clorofila que é reconhecida pela coloração pálida ou mesmo esbranquiçada da folha, e esta variação de coloração da planta pode ser identificada por meio de técnicas de sensoriamento remoto. Este trabalho teve o objetivo de estudar as correlações entre dados de refletância espectral obtidos por sensores terrestres comerciais (Clorofilog 1030, GreenSeeker e Crop Circle ACS-470) e atributos de desempenho da cultura do trigo em resposta à doses de N aplicadas em cobertura no sistema plantio direto. A eficiência dos sensores foi avaliada de duas maneiras: (i) por meio de métodos estatísticos clássicos e (ii) por meio da aplicação de Redes Neurais Artificiais com uso da técnica de aprendizado de máquina, software MatLab. Para a utilização de Redes Neurais Artificiais, este trabalho comparou o desempenho dos algoritmos Backpropagation e Resilient Propagation. Os resultados mostraram que as leituras do Clorofilog 1030 não foram sensíveis às variações das doses de N aplicadas em cobertura na cultura do trigo, pois as plantas de trigo apresentaram bom estado nutricional, mesmo sem aplicação de N em cobertura. Logo, este sensor também não teve correlação significativa com o teor de N na folha bandeira, a produção de matéria seca da parte aérea e a extração de N pelas plantas de trigo. Os índices obtidos pelos sensores de refletância Crop Circle e GreenSeeker tiveram estreita correlação com as doses de N aplicadas em cobertura, a produção de matéria seca da parte aérea e a extração de N pelas plantas de trigo. Os sensores Crop Circle e GreenSeeker apresentaram correlação mais fraca com o teor de N no tecido foliar e, principalmente, com a produtividade de grãos de trigo. Isso aconteceu porque ficou bem evidenciado que a produtividade de grãos não acompanhou os ganhos de matéria seca da parte aérea do trigo, quando os rendimentos de grãos de trigo foram elevados. Os coeficientes de correlação obtidos pelos algoritmos Backpropagation e Resilient Propagation foram semelhantes aos encontrados pelas análises estatísticas. A técnica de Redes Neurais Artificiais teve comportamento satisfatório e similar aos métodos estatísticos clássicos.

Made available in DSpace on 2017-07-24T19:38:08Z (GMT). No. of bitstreams: 1 CLAUDIO KAPP JUNIOR.pdf: 1815678 bytes, checksum: d0a947fefc0e6b1b5a0242eb975f3cb7 (MD5) Previous issue date: 2013-03-08 / No-till systems with diversified crop rotations have stood out of the most effective strategies to improve the sustainability of farming in tropical and subtropical regions. Wheat (Triticum aestivum L.) is one of the most important crops used in this rotation during the autumn-winter season. Nitrogen (N) is uptake in larger amounts by plants, it is essential for the structure and functions in the cell, for all enzymatic reactions and is part of the chlorophyll molecules. Nitrogen fertilizers represent a significant part of the costs of production and due to the dynamics of N in soil, losses of N occur and cause economic and environmental damages. In the same agricultural area may exist changing demands for this nutrient. The attributes of the plant commonly used as indicators of N are NO3- content in stem, leaf chlorophyll content, the intensity of the green color and the N foliar content, dry biomass, and the extraction of N by plants. Lower levels of N can cause chlorophyll deficiency that is recognized by whitish or pale foliar coloration, and this changing in plant color can be identified using remote sensing techniques. This study aimed to evaluate the correlations between spectral reflectance data obtained by commercial ground sensors (Clorofilog 1030, GreenSeeker, and Crop Circle ACS-470) and attributes of wheat crop in response to N rates in top dressing under a no-till system. The efficiency of the sensors was evaluated in two ways: (i) by classical statistical methods, and (ii) through the application of Artificial Neural Networks, a machine learning technique. For the use of Artificial Neural Networks, this study compared the performance of the algorithms Resilient Propagation and Backpropagation. Because wheat plants exhibited adequate nutritional status, even without N application in top dressing, Clorofilog 1030 readings were not sensitive to variations of N rates. Thus, this sensor also did not correlate significantly with the N foliar content, dry biomass, and the extraction of N by wheat plants. The indices obtained by reflectance sensors Crop Circle and GreenSeeker had close correlation with the rates of N in top dressing, dry biomass, and the extraction of N by wheat plants. The Crop Circle and GreenSeeker sensors showed weaker correlation with the N content in leaves, and especially with the wheat grain yield. In this way, it was evident that grain yield has not followed the dry biomass production when high wheat grain yields were obtained. The correlation coefficients obtained by the Resilient Propagation and Backpropagation algorithms were similar to those found by statistical analysis. The Artificial Neural Networks technique had satisfactory behavior similar to classical statistical methods. / O sistema plantio direto com rotação diversificada de culturas tem sido apontado como uma das melhores estratégias para aumentar a sustentabilidade da agricultura em regiões tropicais e subtropicais. Uma das culturas de maior importância nessa rotação durante a estação de outono–inverno é o trigo (Triticum aestivum L.). O nitrogênio (N) é um dos nutrientes extraídos em maior quantidade pelas plantas, sendo essencial para a estrutura e funções nas células, para todas as reações enzimáticas e faz parte das moléculas de clorofila. Os fertilizantes nitrogenados representam parte significativa dos custos da produção agrícola e, em razão da dinâmica do N no solo, perdas consideráveis de N podem ocorrer e causar prejuízos econômicos e ambientais. Em uma mesma área agrícola podem existir demandas variáveis por este nutriente. Os atributos da planta mais utilizados como indicadores de N são o teor de NO3- no colmo, o teor de clorofila, a intensidade da cor verde e o teor de N na folha bandeira, a produção de matéria seca da parte aérea e a extração de N pelas plantas. Níveis baixos de N podem ocasionar deficiência de clorofila que é reconhecida pela coloração pálida ou mesmo esbranquiçada da folha, e esta variação de coloração da planta pode ser identificada por meio de técnicas de sensoriamento remoto. Este trabalho teve o objetivo de estudar as correlações entre dados de refletância espectral obtidos por sensores terrestres comerciais (Clorofilog 1030, GreenSeeker e Crop Circle ACS-470) e atributos de desempenho da cultura do trigo em resposta à doses de N aplicadas em cobertura no sistema plantio direto. A eficiência dos sensores foi avaliada de duas maneiras: (i) por meio de métodos estatísticos clássicos e (ii) por meio da aplicação de Redes Neurais Artificiais com uso da técnica de aprendizado de máquina, software MatLab. Para a utilização de Redes Neurais Artificiais, este trabalho comparou o desempenho dos algoritmos Backpropagation e Resilient Propagation. Os resultados mostraram que as leituras do Clorofilog 1030 não foram sensíveis às variações das doses de N aplicadas em cobertura na cultura do trigo, pois as plantas de trigo apresentaram bom estado nutricional, mesmo sem aplicação de N em cobertura. Logo, este sensor também não teve correlação significativa com o teor de N na folha bandeira, a produção de matéria seca da parte aérea e a extração de N pelas plantas de trigo. Os índices obtidos pelos sensores de refletância Crop Circle e GreenSeeker tiveram estreita correlação com as doses de N aplicadas em cobertura, a produção de matéria seca da parte aérea e a extração de N pelas plantas de trigo. Os sensores Crop Circle e GreenSeeker apresentaram correlação mais fraca com o teor de N no tecido foliar e, principalmente, com a produtividade de grãos de trigo. Isso aconteceu porque ficou bem evidenciado que a produtividade de grãos não acompanhou os ganhos de matéria seca da parte aérea do trigo, quando os rendimentos de grãos de trigo foram elevados. Os coeficientes de correlação obtidos pelos algoritmos Backpropagation e Resilient Propagation foram semelhantes aos encontrados pelas análises estatísticas. A técnica de Redes Neurais Artificiais teve comportamento satisfatório e similar aos métodos estatísticos clássicos.

South African learners continue to perform poorly in high school Circle Geometry. Lack of learner confidence and motivation in Mathematics may be the contributing factors to the low success rate in Circle Geometry. These factors, coupled with Conventional Teaching Instructions (CTI), may have contributed to the significant reduction in the number of learners enrolled for Mathematics, and provided a rationale for the study that explored a possible alternative teaching pedagogy to motivate and eventually improve learner performance in Circle Geometry. The study aimed to investigate the comparative effects of Computer Assisted Instruction (CAI) and CTI on the performance and motivation of Grade 11 learners in the topic of Circle Geometry. The population of the study consisted of Grade 11 Mathematics learners from 65 secondary schools in the Ekurhuleni North District of Gauteng province in South Africa. Using convenience sampling techniques two schools with n=136 Grade 11 Mathematics learners and two teachers participated in the study. One school formed the experimental group (n=71) and the other school formed the control group (n=65). The study followed a quasi-experimental design with a non-equivalent control group approach consisting of pre-and post-test measures. Intact classes participated in the study as it was not possible to randomly select participants for the study. Both groups wrote a standardised achievement pre-test to ascertain their performance status at the beginning of the study. CAI was implemented in the experimental school while CTI was implemented in the control school. A similar post-test was administered on both groups to measure the comparative effects of each teaching method on the performance of learners. A questionnaire was also administered to both groups to measure the motivation of learners. A purposive sample (n=12) was selected from both groups to participate in semi-structured interviews to account for the results of the test and the questionnaire. A socio-constructivist theory framed the study. Analysis of Covariance (ANCOVA) was used to analyse data. The results of this investigation indicated that the use of the computer software, GeoGebra, in the teaching and learning of Circle Geometry improved the performance and motivation of Grade 11 learners. / Mathematics Education / M. Ed. (Mathematics Education)