Photocatalysis is an advanced oxidation process for the purification and remediation of contaminated waters and wastewaters, and is advantageous over conventional treatment technologies due to its ability to degrade emerging and recalcitrant pollutants. In addition, photocatalytic disinfection is less chemical-intensive than other methods such as chlorination, and can inactivate even highly resistant microorganisms with good efficacy. Process sustainability and cost-effectiveness may be improved by utilizing solar irradiation as the source of necessary photons for photocatalyst excitation. However, solar-induced activity of the traditionally-used titania is poor due to its inefficient visible light absorption, and recombination of photo-excited species is problematic. Additionally, mass transfer limitations and difficulties separating the catalyst from the post-treatment slurry hinder conversions and efficiencies obtainable in practice. In this research, various strategies were explored to address these issues using novel visible light active photocatalysts. Two classes of carbon-enhanced photocatalytic materials were studied: activated carbon adsorbent photocatalyst composites, and carbon-doped TiO2. Adsorbent photocatalyst composites based on activated carbon and plasmonic silver/silver chloride structures were synthesized, characterized, and experimentally investigated for their photocatalytic activity towards the degradation of model organic pollutants (methyl orange dye, phenol) and the inactivation of a model microorganism (Escherichia coli K-12) under visible light. The adsorptive behaviour of the composites towards methyl orange dye was also studied and described according to appropriate models. Photocatalytic bacterial inactivation induced by the prepared composites was investigated, and the inactivation mechanisms and roles of incorporated antimicrobial silver on disinfection were probed and discussed. These composites were extended towards magnetic removal strategies for post-use separation through the incorporation of magnetic nanoparticles to prepare Ag/AgCl-magnetic activated carbon composites, and the effect of nanoparticles addition on the properties and photoactivities of the resulting materials was explored. Another silver/silver halide adsorbent photocatalyst composite based on activated carbon and Ag/AgBr exhibiting visible light absorption due to both localized surface plasmon resonance and optical band gap absorption was synthesized and its photocatalytic activity towards organics degradation and microbial inactivation was studied. Carbon-doped mixed-phase titania was also prepared and experimentally investigated.

Virtual reality (VR) is a medium of human interaction which is becoming more popular by the day in today's technological advancements. The applications are being developed at the same rate as the technology itself and we have only seen the start of the possible benefits it could bring society. As the technology advances it will gain a lot of trust, and the potential use cases of virtual environments will be allowed to become more complex. Already today, they often involve network streaming components which often has very strict optimization requirements in order to be able to run in real-time with minimal delay under normal network conditions. In order to reach the required optimizations it is important to understand how users interact with such virtual environments. To support and facilitate the understanding of this kind of interaction we have developed a method for creating qualitative datasets containing extensive information about the 3D scene as well as the sensor data from the head-mounted display (HMD). We then apply this method to create a sample dataset from a virtual 3D environment and try to analyze the data collected through some simple methods for demonstrational purposes.

京都大学 / 新制・課程博士 / 博士(エネルギー科学) / 甲第23536号 / エネ博第427号 / 新制||エネ||81(附属図書館) / 京都大学大学院エネルギー科学研究科エネルギー社会・環境科学専攻 / (主査)教授 石原 慶一, 教授 佐川 尚, 准教授 奥村 英之 / 学位規則第4条第1項該当 / Doctor of Energy Science / Kyoto University / DFAM

Indiana University-Purdue University Indianapolis (IUPUI) / Externally visible characteristics (EVCs) predicted from an unknown sample of DNA are particularly useful in forensics as they can provide information beyond that of an STR profile. Current EVCs which are highly studied and well-predicted include iris, hair, and skin color. Notably, models predicting iris color, such as IrisPlex, are the most accurate with up to ~95% accuracy; however, some inaccurate predictions occur, as is evidenced by the ~5%. Often, these are due to green or hazel eyes, which are frequently viewed as intermediate. Though, some of the inaccurate predictions are due to true-blue being predicted as brown and vice versa. Previous research has theorized the possibility of two SNPs, rs12913832 and rs1800407, acting as a functional haplotype affecting iris color. rs12913832 is recognized as the most predictive SNP for iris color and highly significant in other pigmentation phenotypes; presently, rs1800407 is the second-ranked SNP in the IrisPlex 6-SNP system. Both SNPs are highly variable in Europe, where the majority of variation in iris color originates. In the present study, we explore the SNP variation present in the genetic regions of OCA2-HERC2 as well as possible haplotypes. Our research centers around the functional haplotype and the addition of SNPs to the functional haplotype. In addition, three different ways of classifying the phenotype are assessed simultaneously. First, using a 4-point categorical phenotype—blue/blue grey, blue/green yellow, hazel/light brown, and dark brown. Second, calculating a continuous scale from a quantitative phenotype in which the percentage of each categorical color has been measured. Third, using the IrisPlex 6-SNP system to predict eye color and identify individuals which have been inaccurately predicted. Exploration of the SNP and haplotype variation resulted in two SNPs for both the categorical and quantitative phenotypes which were significantly correlated with hazel/light brown—rs1448484 and rs61335644, both as independent SNPs and when assessed in a haplotype with rs1800407-rs12913832. SNP rs1448484 has been associated with skin pigmentation previously and is located in a possible transcription factor binding site. SNP rs61335644 is not presently associated with pigmentation but is in complete LD with two SNPs in and around regulatory regions present in HERC2. Finally, the addition of rs1448484 and rs61335644 into the current IrisPlex 6-SNP system slightly improved each of the tested performance metrics for hazel/light brown and dark brown. Within the inaccurately predicted phenotypes, rs1800407 is confirmed to affect both inaccurately predicted groups and is the most significant SNP. Additionally, rs121918166, a missense variant in OCA2, is the second most significant SNP in true blue predicted as brown. Both SNPs were also the two most significant haplotypes with at least one allele being derived. Therefore, the next steps should include the addition of the functional haplotype and rs121918166 into the current IrisPlex model, and further testing of rs1448484 and rs61335644 on a molecular level. Consequently, the current IrisPlex model should also be reassessed on an independent test set using the 4-point categorical scale rather than the present 3-point scale.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第19018号 / 農博第2096号 / 新制||農||1029(附属図書館) / 学位論文||H27||N4900(農学部図書室) / 31969 / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 近藤 直, 教授 飯田 訓久, 准教授 小川 雄一 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20337号 / 工博第4274号 / 新制||工||1662(附属図書館) / 京都大学大学院工学研究科分子工学専攻 / (主査)教授 田中 庸裕, 教授 梶 弘典, 教授 阿部 竜 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

京都大学 / 0048 / 新制・論文博士 / 博士(理学) / 乙第13108号 / 論理博第1556号 / 新制||理||1620(附属図書館) / (主査)准教授 重 尚一, 教授 余田 成男, 教授 石川 裕彦 / 学位規則第4条第2項該当 / Doctor of Science / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21118号 / 工博第4482号 / 新制||工||1696(附属図書館) / 京都大学大学院工学研究科物質エネルギー化学専攻 / (主査)教授 阿部 竜, 教授 安部 武志, 教授 作花 哲夫 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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