京都大学 / 新制・課程博士 / 博士(農学) / 甲第23250号 / 農博第2457号 / 新制||農||1084(附属図書館) / 学位論文||R3||N5340(農学部図書室) / 京都大学大学院農学研究科応用生命科学専攻 / (主査)教授 木岡 紀幸, 教授 植田 充美, 教授 矢﨑 一史 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

京都大学 / 新制・課程博士 / 博士(薬科学) / 甲第23134号 / 薬科博第133号 / 新制||薬科||14(附属図書館) / 京都大学大学院薬学研究科薬科学専攻 / (主査)教授 加藤 博章, 教授 松﨑 勝巳, 教授 高須 清誠 / 学位規則第4条第1項該当 / Doctor of Pharmaceutical Sciences / Kyoto University / DFAM

Background: In today's society, the rapid growth of online shopping among consumers has resulted in the widespread adoption of artificial intelligence powered chatbots by businesses. Despite this, previous research has not focused on where customers place their attitudes towards AI-powered chatbots in e-commerce. The ABC model of attitudes, which includes affective, behavioral, and cognitive components was used to examine how attitudes are formed towards AI-powered chatbots. Purpose: The purpose of this study is to explore consumers' attitudes towards AI-powered chatbots utilized in e-commerce. Methodology: Because the study has an exploratory and inductive approach, a qualitative research strategy was selected. It was determined to use a generic purposive sampling in which ten participants were chosen as part of Generation Z. A semi-structured interview was conducted in which questions were posed regarding the ABC model and the characteristics of AI-powered chatbots. To analyze how attitudes are formed and what they are, grounded theory was used to code the interviews to established consumer attitudes categories. Findings: The findings demonstrate that consumers' attitudes towards AI-powered chatbots used in e-commerce varied from being positive, negative, or mixed. This is due to the factors that contributed to the formation of attitudes.

Background: This study explores consumer attitudes towards AI-generated videosusing the ABC model of attitudes, which includes Affective, Behavioral, and Cognitive components. AI-generated videos represent a significant evolution in content creation,incorporating advanced technologies that evoke a range of emotional, behavioural, andcognitive responses from consumers. Understanding these responses is crucial as AIbecomes increasingly integrated into media production. Purpose: The purpose of this study is to explore consumers’ attitudes towardsAI-generated videos. Methodology: Data was collected through semi-structured interviews with participantsfrom diverse backgrounds and professions. A purposive sampling method wasemployed to select participants familiar with generative AI technology, ensuring a richand diverse set of insights. Findings: Findings reveal a spectrum of emotional responses, with negative emotionsoften tied to perceptions of artificiality and lack of authenticity, while positive emotionsare driven by the novelty and potential of AI technology. Behavioural intentions varied,ranging from reluctance due to trust issues to openness influenced by perceived benefitsand professional interests. Cognitive evaluations highlighted knowledge disparities andethical concerns, with deeper understanding correlating with cautious optimism orscepticism. Conclusion: The study contributes to the literature by providing a nuancedunderstanding of how affective, behavioural, and cognitive dimensions interact to shapeoverall consumer attitudes towards AI-generated videos. Practical implications suggestthat companies and marketers should address trust and ethical concerns while enhancingthe authenticity and transparency of AI-generated videos to foster positive consumerengagement.

With modern high-throughput technologies, scientists can now collect high-dimensional data of various forms, including brain images, medical spectrum curves, engineering signals, etc. These data provide a rich source of information on disease development, cell evolvement, engineering systems, and many other scientific phenomena. To achieve a clearer understanding of the underlying mechanism, one needs a fast and reliable analytical approach to extract useful information from the wealth of data. The goal of this dissertation is to develop novel methods that enable scalable estimation, testing, and analysis of complex, high-dimensional data. It contains three parts: parameter estimation based on complex data, powerful testing of functional data, and the analysis of functional data supported on manifolds. The first part focuses on a family of parameter estimation problems in which the relationship between data and the underlying parameters cannot be explicitly specified using a likelihood function. We introduce a wavelet-based approximate Bayesian computation approach that is likelihood-free and computationally scalable. This approach will be applied to two applications: estimating mutation rates of a generalized birth-death process based on fluctuation experimental data and estimating the parameters of targets based on foliage echoes. The second part focuses on functional testing. We consider using multiple testing in basis-space via p-value guided compression. Our theoretical results demonstrate that, under regularity conditions, the Westfall-Young randomization test in basis space achieves strong control of family-wise error rate and asymptotic optimality. Furthermore, appropriate compression in basis space leads to improved power as compared to point-wise testing in data domain or basis-space testing without compression. The effectiveness of the proposed procedure is demonstrated through two applications: the detection of regions of spectral curves associated with pre-cancer using 1-dimensional fluorescence spectroscopy data and the detection of disease-related regions using 3-dimensional Alzheimer's Disease neuroimaging data. The third part focuses on analyzing data measured on the cortical surfaces of monkeys' brains during their early development, and subjects are measured on misaligned time markers. In this analysis, we examine the asymmetric patterns and increase/decrease trend in the monkeys' brains across time. / Doctor of Philosophy / With modern high-throughput technologies, scientists can now collect high-dimensional data of various forms, including brain images, medical spectrum curves, engineering signals, and biological measurements. These data provide a rich source of information on disease development, engineering systems, and many other scientific phenomena. The goal of this dissertation is to develop novel methods that enable scalable estimation, testing, and analysis of complex, high-dimensional data. It contains three parts: parameter estimation based on complex biological and engineering data, powerful testing of high-dimensional functional data, and the analysis of functional data supported on manifolds. The first part focuses on a family of parameter estimation problems in which the relationship between data and the underlying parameters cannot be explicitly specified using a likelihood function. We introduce a computation-based statistical approach that achieves efficient parameter estimation scalable to high-dimensional functional data. The second part focuses on developing a powerful testing method for functional data that can be used to detect important regions. We will show nice properties of our approach. The effectiveness of this testing approach will be demonstrated using two applications: the detection of regions of the spectrum that are related to pre-cancer using fluorescence spectroscopy data and the detection of disease-related regions using brain image data. The third part focuses on analyzing brain cortical thickness data, measured on the cortical surfaces of monkeys’ brains during early development. Subjects are measured on misaligned time-markers. By using functional data estimation and testing approach, we are able to: (1) identify asymmetric regions between their right and left brains across time, and (2) identify spatial regions on the cortical surface that reflect increase or decrease in cortical measurements over time.

Yes / In dealing with big data, we need effective algorithms; effectiveness that depends, among others, on the ability to remove outliers from the data set, especially when dealing with classification problems. To this aim, support vector finder algorithms have been created to save just the most important data in the data pool. Nevertheless, existing classification algorithms, such as Fuzzy C-Means (FCM), suffer from the drawback of setting the initial cluster centers imprecisely. In this paper, we avoid existing shortcomings and aim to find and remove unnecessary data in order to speed up the final classification task without losing vital samples and without harming final accuracy; in this sense, we present a unique approach for finding support vectors, named evolutionary Pentagon Support Vector (PSV) finder method. The originality of the current research lies in using geometrical computations and evolutionary algorithms to make a more effective system, which has the advantage of higher accuracy on some data sets. The proposed method is subsequently tested with seven benchmark data sets and the results are compared to those obtained from performing classification on the original data (classification before and after PSV) under the same conditions. The testing returned promising results.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal. / Le transport des molécules à travers les membranes est un processus cellulaire fondamental. Les transporteurs ABC (pour ATP-binding cassette) sont des protéines transmembranaires médiant le transport actif de substrats variés (peptides, ions, acides aminés, antibiotiques, etc). Le gène ATMI de Saccharomyces cerevisiae code pour un transporteur ABC de 690 acides aminés localisé dans la membrane interne de la mitochondrie. La protéine Atml est une proche homologue de la P-glycoprotéine impliquée dans la résistance aux agents anticancéreux. Il a été démontré qu'Atml est essentielle pour la croissance des cellules, procurant ainsi un phénotype idéal pour l'analyse fonctionnelle de ce transporteur. Nous utilisons une technique, appelée plasmid shuffling', basée sur l'échange de plasmides par contre-sélection d'un plasmide portant le marqueur de sélection URA3 en présence d'acide 5-fluoroorotique (5-F0A) pour étudier Atml. Nous avons construit une souche haploïde de S. cerevisiae dans laquelle la copie chromosomique du gène ATMI est excisée mais qui est viable grâce à la présence d'un plasmide URA3 portant une copie fonctionnelle du gène ATMI. Cette souche a été transformée avec une banque d'allèles mutés d'ATM1 portés par un plasmide LEU2 et criblée pour des mutants thermosensibles (ts) d'Atml après contre-sélection du plasmide URA3 sur 5-F0A. Trois mutants ts d'Atml ont été isolés et les mutations causant le phénotype ts ont été identifiées par séquençage de l'ADN. Des courbes de croissance de ces mutants ont été tracées, démontrant une croissance normale à température permissive mais un arrêt de croissance après quelques divisions à température restrictive. Nous avons produit des anticorps polyclonaux anti-Atml qui nous ont permis d'étudier la protéine de type sauvage et celle des trois mutants ts. Ces études ont révélé l'absence d'Atml seulement dans les mitochondries des mutants ts à température restrictive. D'autre part, des expériences de coimmunoprécipitation ont démontré qu'Atml forme des homodimères et que cette interaction est médiée par la partie C-terminale d'Atml, qui contient le domaine de liaison à l'ATP. Nos expériences ont donc permis d'identifier des acides aminés importants pour la fonction d'Atml ainsi qu'un domaine impliqué dans la structure quaternaire de ce transporteur.

京都大学 / 新制・課程博士 / 博士(薬科学) / 甲第25218号 / 薬科博第180号 / 新制||薬科||20(附属図書館) / 京都大学大学院薬学研究科薬科学専攻 / (主査)教授 高須 清誠, 教授 加藤 博章, 教授 大野 浩章 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

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O nosso objetivo foi de avaliar evolutivamente a perda da força muscular e das habilidades motoras, bem como a progressão da distribuição da fraqueza muscular nos diferentes segmentos dos membros superiores em pacientes com distrofia muscular de Duchenne em corticoterapia. Selecionamos seguintes testes de fácil aplicação: Teste de força Manual Muscular Escala Medical Research Council; Teste ABC provas de coordenação visual-motora e fatigabilidade provas n° 1, 3, 7 e 8; Grau funcional de Brooke; Índice de Barthel. Os testes foram aplicados em 40 pacientes com idades entre 5 e 15 anos, deambulantes e não deambulantes, os quais foram avaliados três vezes, com intervalos de seis meses entre cada avaliação. Os resultados mostraram que a progressão da distribuição da força muscular nos membros superiores ocorreu dos segmentos proximais para os distais em todos os pacientes e foi maior nos pacientes não deambulantes e com maior idade. O ato de escrever (pegada no lápis e/ou caneta) não foi influenciado pela progressão; no entanto, o aumento da fatigabilidade foi um fator limitante contribuindo para a redução do ritmo e da qualidade da escrita. O grau funcional de Brooke confirmou a variação das medidas de força muscular e nas atividades de vida diária o nível de dependência foi maior nos pacientes com maior idade, acontecendo nestes compensações funcionais importantes que lhes permitiram realizar a atividade de forma adaptada. / Our aim was to analyze the progression of the involvement of muscle strength and functional motor hability as well as the progression of the weakness pattern in the upper limbs of children with Duchenne muscular dystrophy who were receiving steroid therapy. We evaluated 40 patients with DMD, aged 5-15 years, by using the following simple tests: MRC score based on the upper limbs muscles; ABC tests number 1, 3, 7 and 8 for assessing visual motor coordination and fatigability; Brooke functional ability scale and modified Barthel index. All boys were evaluated every 6 months along a period of 18 months. The loss of muscular strength showed a proximal to distal progression and was greater in non- ambulant and in older patients. The act of writing (to hold pencil or pen) was not influenced by the progression; however, the fatigability increased and was a limiting factor for the speed and the quality of the hand writing. The Brooke functional ability scale confirmed the changes in the muscular strength. The performance in daily activities showed a greater dependence in the older patients who adopted functional compensations for performing the activities in an adapted way.