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京都大学 / 新制・課程博士 / 博士(理学) / 甲第23712号 / 理博第4802号 / 新制||理||1687(附属図書館) / 京都大学大学院理学研究科地球惑星科学専攻 / (主査)教授 竹見 哲也, 准教授 重 尚一, 教授 榎本 剛 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

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Spatio-temporal data analysis involves modeling a variable observed at different locations over time. A key component of space-time modeling is determining the spatial scale of the data. This dissertation addresses the following three questions: 1) How does spatial aggregation impact the properties of the variable and its model? 2) What spatial scale of the data produces more accurate forecasts of the aggregate variable? 3) What properties lead to the smallest information loss due to spatial aggregation? Answers to these questions involve a thorough examination of two common space-time models: the STARMA and GSTARMA models. These results are helpful to researchers seeking to understand the impact of spatial aggregation on temporal and spatial correlation as well as to modelers interested in determining a spatial scale for the data. Two data examples are included to illustrate the findings, and they concern states' annual labor force totals and monthly burglary counts for police districts in the city of Philadelphia. / Statistics

Combretastatin A4 phosphate (CA4P) is a potent vascular disrupting agent utilized in the treatment of cancer. The observed rapid vascular shutdown post administration as well as its potency at 1/10th of the established maximum tolerated dose (MTD) have made it one of the most prevalent tubulin binding agents. CA4P is currently involved in 19 clinical trials. Unfortunately, as is the case with most forms of chemotherapy, the off target effects associated with its use can be prohibitive for a large percentage of cancer patients. The advantages associated with the liposomal encapsulation of chemotherapeutic agents have been established for over 20 years and are shown to decrease off target effects whilst increasing stability, bioavailability, and circulation time. Liposomes comprised of conventional phospholipids, such as 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), are usually stabilized by the incorporation of cholesterol. However, the addition of cholesterol to liposomal formulations is concerning due to the capability of cholesterol to form oxysterol molecules and exacerbate other preexisting conditions such as hypertension or cardiovascular disease. With this study we aim to enhance the usage of CA4P through liposomal encapsulation in order to reduce some of the associated off target effects and increase bioavailability and overall efficacy. We also aimed to enhance the stability of our lipid vesicles through the incorporation of bipolar tetraether lipids isolated from the thermoacidophilic archaea S. acidocaldarius. The polar lipid fraction E (PLFE) lipids studied here have previously been shown to generate highly stable lipid vesicles. The liposomal formulation studied here included the encapsulation of the anti-cancer drug CA4P in PLFE liposomes. With this work we characterized our liposomes to optimize their drug loading, membrane stability, size, colloidal stability, and membrane surface charge. We also identified a photochemical isomerization reaction occurring in our CA4P samples and then proceeded to characterize the fluorescence and aggregation behavior of our CA4P isoforms. From our studies of CA4P in solution we observed a red shift in the excitation spectra of CA4P with increasing concentrations. This bathochromic shift is characteristic with the formation of j-aggregates. The CA4P concentrations with the most dramatic red shift corresponded exactly with the drug concentrations associated with self-quenching behavior. From these studies we determined the effects of increased CA4P concentration on fluorescence intensity, drug aggregation and how these phenomena can be utilized and exploited to maximize liposomal drug loading and decrease rate constants of drug leakage and cytotoxicity. The end goal of liposomal chemotherapeutic formulations is a stable, controlled release of as much encapsulated drug as possible. With the thorough understanding of our membrane system, drug fluorescence and CA4P aggregation behavior; we can maximize our encapsulated drug loading as well as create a stable liposomal formulation with a predictable CA4P release. / Biomedical Sciences

No / Recently there has been an exponential rise in the use of Wireless Sensor Networks (WSNs) in various applications. While WSNs have been primarily used as independent networks, researchers are now looking into ways of integrating them with other existing networks. One such network is the satellite network which provides a reliable communication backbone to remote areas that lack appropriate terrestrial infrastructure. However, due to the integration of the two networks with different transmission and operational characteristics interoperability and security become major concerns. This paper presents an ns-2 based simulation framework of a WSN-satellite integrated network that is used to evaluate the effects of data aggregation and security mechanisms on overall network performance. The average end-to-end packet delay, overall energy consumption and aggregation efficiency are considered for this analysis. This paper also looks into the effects of implementing hop-by-hop security and end-to-end security and justifies the need for end-to-end security in the WSN-satellite integrated networks.

Surveys and a brief-interval longitudinal design were employed to investigate the relationships between selected proactive leader influence behaviors (PLIBs) and followers' commitment to their leaders. Selected elements of followers' implicit leadership theories (ILTs) were expected to moderate the PLIBs – commitment relationships. Hypotheses were generated and tested in order to determine the extent to which (1) PLIBs constituted group-level phenomena and (2) PLIBs and ILTs were related to follower commitment. Empirical evidence did not support treating PLIBs as group-level variables. While PLIBs were related to commitment, hypotheses specifying ILT dimensions as moderators of the PLIB – commitment relationships were not supported. / Ph. D.

Enabled by the wave of online crowdsourcing activities, extracting the Wisdom of Crowds (WoC) has become an emerging research area, one that is used to aggregate judgments, opinions, or predictions from a large group of individuals for improved decision making. However, existing literature mostly focuses on eliciting the wisdom of crowds in an offline context—without tapping into the vast amount of data available on online crowdsourcing platforms. To extract WoC from participants on online platforms, there exist at least three challenges, including social influence, suboptimal aggregation strategies, and data sparsity. This dissertation aims to answer the research question of how to effectively extract WoC from crowdsourcing platforms for the purpose of making better decisions. In the first study, I designed a new opinions aggregation method, Social Crowd IQ (SCIQ), using a time-based decay function to eliminate the impact of social influence on crowd performance. In the second study, I proposed a statistical learning method, CrowdBoosting, instead of a heuristic-based method, to improve the quality of crowd wisdom. In the third study, I designed a new method, Collective Persuasibility, to solve the challenge of data sparsity in a crowdfunding platform by inferring the backers' preferences and persuasibility. My work shows that people can obtain business benefits from crowd wisdom, and it provides several effective methods to extract wisdom from online crowdsourcing platforms, such as StockTwits, Good Judgment Open, and Kickstarter. / Doctor of Philosophy / Since Web 2.0 and mobile technologies have inspired increasing numbers of people to contribute and interact online, crowdsourcing provides a great opportunity for the businesses to tap into a large group of online users who possess varied capabilities, creativity, and knowledge levels. Howe (2006) first defined crowdsourcing as a method for obtaining necessary ideas, information, or services by asking for contributions from a large group of individuals, especially participants in online communities. Many online platforms have been developed to support various crowdsourcing tasks, including crowdfunding (e.g., Kickstarter and Indiegogo), crowd prediction (e.g., StockTwits, Good Judgment Open, and Estimize), crowd creativity (e.g., Wikipedia), and crowdsolving (e.g., Dell IdeaStorm). The explosive data generated by those platforms give us a good opportunity for business benefits. Specifically, guided by the Wisdom of Crowds (WoC) theory, we can aggregate multiple opinions from a crowd of individuals for improving decision making. In this dissertation, I apply WoC to three crowdsourcing tasks, stock return prediction, event outcome forecast, and crowdfunding project success prediction. Our study shows the effectiveness of WoC and makes both theoretical and practical contributions to the literature of WoC.