SARS-CoV-2 is caused by a pathogenic and highly transmissible beta coronavirus leading to severe infections in immuno-compromised individuals. This study first evaluates the primers used in the Reverse Transcription Polymerase Chain Reaction (RT-PCR) to detect SARS-CoV-2 by understanding how mutations might affect the primer efficiency with the SARS-CoV-2 sequences. Mutations on the Spike protein of SARS-CoV-2 are the most important as the spike protein mediates the viral entry into host cells. This study tracks the course of mutations on the spike protein by focusing on the haplogroups of the sequences across the world. A comprehensive database linking three important, currently available databases is curated as part of this study to fill the gaps caused by sequencing errors. Further, this study exploits the data generated by the Illumina and Oxford Nanopore next generation sequencing methods to study the evolution of mutations in a single Septuagenarian patient over an infection period of 102 days using the gene analysis software Geneious Prime. / Master of Science / A novel corona virus named Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) has taken down the entire world by causing Covid-19 pandemic. Initially detected in Wuhan, China, the virus has now made its way to more than 200 countries with a heavy death toll. Understanding the virus through mutation tracking and improving diagnostics and vaccine design have now become the top priority of researchers. Most of these researchers depend on quality viral sequence datasets to identify and track mutations. One aim of this study is to provide a comprehensive dataset linking the GISAID (Global Initiative on Sharing All Influenza Data), NCBI (National Center for Biological Information) and the SRA (Sequence Read Archive) sequences. The dataset can be used for genome analysis and mutation tracking which can provide important insights for vaccine design and in improving diagnostic assays. In addition, this study provides an analysis of viral mutations in in the genomic regions targeted by commonly used primers in the RT-PCR tests for SARS-CoV-2 that may affect the efficiency of detection. This study also uses the haplogroup information of people across the world to track the D614G mutation on the S gene of SARS-CoV-2 as it may be associated with increased transmissibility. To track the course of mutations in SARS-CoV-2, it is important to analyze the sequencing data provided by the Illumina and Oxford Nanopore next generation sequencing methods. We present a case study to investigate the course of SARS-CoV-2 mutations in a single septuagenarian patient over a period of 102days using the Sequence Read Archive (SRA) data generated by two Next Generation Sequencing methods and compare the advantages that one has over the other.

Yes / With the increasing complexity of problems in the construction industry, researchers are investigating computationally rigorous intelligent systems with the aim of seeking intelligent solutions. The purpose of this paper is therefore to analyse the research published on ‘intelligent systems in the construction industry’ over the past two decades. This is achieved to observe and understand the historical trends and current patterns in the use of different types of intelligent systems and to exhibit potential directions of further research. Thus, to trace the applications of intelligent systems to research in the construction industry, a profiling approach is employed to analyse 514 publications extracted from the Scopus database. The prime value and uniqueness of this paper lies in analysing and compiling the existing published material by examining variables (such as yearly publications, geographic location of each publication, etc.). This has been achieved by synthesising existing publications using 14 keywords2 ‘Intelligent Systems’, ‘Artificial Intelligence’, ‘Expert Systems’, ‘Fuzzy Systems’, ‘Genetic Algorithms’, ‘Knowledge-Based Systems’, ‘Neural Networks’, ‘Context Aware Applications’, ‘Embedded Systems’, ‘Human–Machine Interface’, ‘Sensing and Multiple Sensor Fusion’, ‘Ubiquitous and Physical Computing’, ‘Case-based Reasoning’ and ‘Construction Industry’. The prime contributions of this research are identified by associating (a) yearly publication and geographic location, (b) yearly publication and the type of intelligent systems employed/discussed, (c) geographic location and the type of research methods employed, and (d) geographic location and the types of intelligent systems employed. These contributions provide a comparison between the two decades and offer insights into the trends in using different intelligent systems types in the construction industry. The analysis presented in this paper has identified intelligent systems studies that have contributed to the development and accumulation of intellectual wealth to the intelligent systems area in the construction industry. This research has implications for researchers, journal editors, practitioners, universities and research institutions. Moreover, it is likely to form the basis and motivation for profiling other database resources and specific types of intelligent systems journals in this area.

No / In the pharmaceutical field, current practice in gaining process understanding by data analysis or knowledge discovery has generally focused on dealing with single experimental databases. This limits the level of knowledge extracted in the situation where data from a number of sources, so called fractured data, contain interrelated information. This situation is particularly relevant for complex processes involving a number of operating variables, such as a fluid-bed granulation. This study investigated three data mining strategies to discover and integrate knowledge "hidden" in a number of small experimental databases for a fluid-bed granulation process using neurofuzzy logic technology. Results showed that more comprehensive domain knowledge was discovered from multiple databases via an appropriate data mining strategy. This study also demonstrated that the textual information excluded in individual databases was a critical parameter and often acted as the precondition for integrating knowledge extracted from different databases. Consequently generic knowledge of the domain was discovered, leading to an improved understanding of the granulation process.

Modern FPGAs contain routing resources easily exceeding millions of wires. While mainstream design flows and place-and-route tools make very good use of these routing resources, they do so at the cost of very significant processing time. A well established alternative scheme is to modify or generate configuration bitstreams directly, resulting in more dynamic designs and shorter processing times. This thesis introduces a complete set of alternate wire databases for Xilinx Virtex, Virtex-E, and Virtex-II FPGAs, suitable for standalone use or as an addition to the JBits API. The databases can be used to route or trace through any device in these families, and can generate the necessary bitstream configurations with the help of JBits or an independent bitstream interface. / Master of Science

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Databases are used in modern applications and are employed across a wide range of industries and services. Since there are hundreds of different databases to choose from, there are some critical factors to consider, with two of the most important being query speed and memory usage. Numerous studies have compared various databases and their features, employing different technologies to evaluate performance. This thesis compares the performance between two of the most popular relational databases, PostgreSQL and MySQL (InnoDB engine). It focuses on the speed of the CRUD operations (insert, select, update, remove) and memory allocation, in terms of single-column B-tree indexes, which are employed to accelerate data retrieval operations in database tables. The experiment consists of four different database sizes (104 to 107), where each CRUD operation and space allocation is evaluated both with and without the use of indexes for both databases. The results show that indexed MySQL exhibits the fastest performance for select, update, and remove operations on larger datasets, while indexed PostgreSQL is the fastest for these operations on smaller datasets. The results also indicate that using indexes requires additional memory and increases the time needed for the insertion operation in both databases.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第25155号 / 医博第5041号 / 新制||医||1070(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 今中 雄一, 教授 山本 洋介, 教授 永井 洋士 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

京都大学 / 新制・課程博士 / 博士(社会健康医学) / 甲第25207号 / 社医博第134号 / 新制||社医||13(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 森田 智視, 教授 永井 洋士, 教授 中山 健夫 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM