京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第22425号 / 工博第4686号 / 新制||工||1731(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小池 克明, 教授 立川 康人, 准教授 柏谷 公希 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

The discretization of time-dependent wave propagation is plagued with dispersion in which the wavefield is perceived to travel with an erroneous velocity. To remediate the problem, simulations are run on dense and computationally expensive grids yielding plausible approximate solutions. This work introduces an error analysis tool which can be used to obtain optimal simulation parameters that account for mesh size, orders of spatial and temporal discretizations, angles of propagation, temporal stability conditions (usually referred to as CFL conditions), and time of propagation. The classical criteria of 10-15 nodes per wavelength for second-order finite differences, and 4-5 nodes per wavelength for fourth-order spectral elements are shown to be unrealistic and overly-optimistic simulation parameters for different propagation times. This work analyzes finite differences, spectral elements, optimally-blended spectral elements, and isogeometric analysis.

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Gene regulation lies at the heart of most biological processes and transcription factors are the key molecules that control tissues specific gene expression. In higher eukaryotes transcription factors control gene expression by binding regulatory DNA segments called cis-regulatory modules (CRMs). The increasing number of sequenced genomes of multicellular eukaryotes along with high-throughput methods such as whole genome microarray expression data allows for systematic characterization of the CRMs that control gene expression. A first step towards understanding gene regulation is the identification of the regulatory elements present in the genome. We take advantage of the large database of spatio-temporal patterns of gene expression in D. melanogaster embryogenesis to identify sets of developmentally co-expressed genes. We developed a computational method that identifies DNA binding sites for transcription factors from families of co-regulated genes that are expressed during Drosophila embryo development. This method discovers over-represented motifs in a set of co-regulated genes using the exhaustive motif enumeration technique. Clustering the predicted motifs identifies the CRMs, which assist in translating a combinatorial code of TF inputs into a specific gene expression output. The predicted CRMs were verified experimentally by searching the whole genome for the predicted CRMs and establishing expression pattern of the genes that are associated with these CRMs. It is well know that the gene expression is substantially controlled through CRMs and those key regulatory sequences are conserved in related species. The conservation of CRMs can be studied by comparing the related genomes and alignment methods are widely used computational tools for comparing the sequences. However, in distantly related species the CRM sequences are simply not align able. To identify the similar CRMs in distantly related species we developed a non-alignment based method for discovering similar CRMs in related species. This method is based on word frequencies where the given sequences are compared using Poisson based metric. When starting with a set of CRMs involved in Drosophila early embryo development, we show here that our non-alignment method successfully detects similar CRMs in distantly related species ( D. ananassae, D. pseudoobscura, D. willisoni, D. mojavensis, D. virilis, D. grimshawi ). This method proved efficient in discriminating the functional CRMs from the non-functional ones.

Background: The usage of AI is becoming increasingly necessary in almost every industry, including marketing and branding. AI can help managers, marketers and designers in the marketing and branding sectors to overcome realistic and practical challenges by providing data-driven results. These results could be used in making decisions. Nevertheless, implementing AI systems and the acceptance of it varies widely across different industries, with building brands is still behind.  Purpose: This research aims to develop a deeper understanding of why AI systems are not yet commonly used in the branding industry with emphasis on how it could be useful. As a result, the main opportunities and threats to the usage of AI in branding as seen by branding- and IT specialists are explored and expressed.  Method: To achieve the purpose of this study, a qualitative study was conducted. Semi-structured interviews were used as means to collect primary data and in total 15 interviews with branding and IT specialists were carried out. The data was transcribed and analyzed according to thematic analysis which emerged in four main themes.  Conclusion: The results show that AI is capable of creating brand elements, with limitations to mostly non-visual brand elements due to the lack of creativity and emotions in AI solutions. The findings indicate that the perceived possibilities of implementing AI in branding mostly are cost- and time-related since AI tends to be capable of solving tasks which are cost- and time-consuming. Furthermore, the perceived threats mainly involve i) losing a job or ii) intrude on the roles of branding professionals.

Thesis: Sc. D., Massachusetts Institute of Technology, Department of Nuclear Engineering, 1977 / Includes bibliographical references. / Sc. D. / Sc. D. Massachusetts Institute of Technology, Department of Nuclear Engineering

Thesis. 1980. Ph.D.--Massachusetts Institute of Technology. Dept. of Nuclear Engineering. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Bibliography : leaves 138-146. / Ph.D.

No description available.

No description available.

The rapid development of advanced technologies has led to an increase in demand for critical elements that are essential in the manufacturing of high-tech products. Among these critical elements, manganese (Mn), cobalt (Co), and nickel (Ni) are used in the production of batteries, electronics, and other advanced applications. The demand for these elements has been growing exponentially in recent years, driven by the rise of electric vehicles, renewable energy, and other emerging technologies. However, the United States is heavily dependent on foreign sources of critical minerals and on foreign supply chains, resulting in the potential for strategic vulnerabilities to both economy and military. To address this problem and reduce the Nation's vulnerability to disruptions in the supply of critical minerals, it is important to develop critical minerals recycling technologies. A systematic study was conducted to develop a process for producing high-purity Mn, Co, and Ni products from an acid mine drainage (AMD). As major contaminants, Fe and Al in the solution were sequentially precipitated and eliminated by elevating the pH. After that, a pre-concentrated slurry containing Mn, Co, Ni, and Zn was obtained by collecting the precipitates formed in the pH range of 6.50 to 10.00. The pre-concentrated slurry was redissolved for further purification. Sodium sulfide was added into the redissolved solution to precipitate Co, Ni, and Zn selectively while retaining Mn in the solution. Almost 100% of Co, Ni, and Zn but only around 15% of Mn were precipitated using a sulfur-to-metal molar ratio of 1 at pH 4.00. The sulfide precipitate was calcined and then completely dissolved. The critical elements existing in the dissolved solution were efficiently separated using a two-stage solvent extraction process. Ultimately, Co and Ni products with almost 94% and 100% purity were obtained by sulfide and alkaline precipitation, respectively. AMD also contains rare earth elements (REEs), which can be recovered through selective chemical precipitation. REE removal improved at pH 4.0 after converting ferrous to ferric ions with H2O2. Aluminum species in the solution hindered REE adsorption on ferric precipitates, and ferrous ions reduced REE adsorption on aluminum precipitates at lower pH, but at higher pH, REE removal increased due to ferrous ion precipitation. Various tests and analyses were conducted to understand the partitioning mechanisms of REE during the precipitation process of AMD. Sulfide precipitation is crucial to separate Mn from other elements, but the presence of contaminants like Fe and Al can affect sulfide precipitation efficiency. The effects of Al3+ iii and Fe2+ on the precipitation characteristics of four valuable metals, including Mn2+, Ni2+, Co2+, and Zn2+, were investigated by conducting solution chemistry calculations, sulfide precipitation tests, and mineralogy characterizations. It was found that the ability of the valuable metals to form sulfide precipitates followed an order of Zn2+ > Ni2+ > Co2+ > Mn2+. The sulfide precipitate of Zn2+ was the most stable and did not re-dissolve under the acidic condition (pH 4.00 ± 0.05). In addition, the sulfide precipitation of Zn2+ was barely affected by the contaminant metal ions. However, in the presence of Al3+, the precipitation recoveries of Mn2+, Ni2+, and Co2+ in a solution containing all the valuable metals were noticeably reduced due to simultaneous hydrolysis and competitive adsorption. The precipitation recoveries of Ni2+ and Co2+ in solutions containing individual valuable metals also reduced when Fe2+ was present, primarily due to competitive precipitation. However, the recovery of Mn2+ was enhanced due to the formation of ferrous sulfide precipitate, providing abundant active adsorption sites for Mn species. In the solution containing all the valuable metals, Fe2+ promoted the recoveries of the valuable metals due to the higher concentration of Na2S and the formation of ferrous sulfide precipitate. / Doctor of Philosophy / The rapid development of advanced technologies has increased the demand for critical elements essential in manufacturing high-tech products. In this study, a process was developed for producing high-purity Mn, Co, and Ni products from an acid mine drainage (AMD). A product with around 30 wt.% Mn was produced. Co and Ni products with 94% and 100% purity were also obtained. However, when developing the process, it was found that a portion of the REEs is often lost to the precipitates of the dominant metal contaminant ions (Fe and Al) in the staged precipitation. It was found that the REE removal increase was realized through adsorption onto the surfaces of the ferric precipitates. In sulfide precipitation, the presence of Fe and Al in the solution can significantly influence the separation efficiency of the critical elements. The effect of Al3+ on the sulfide precipitation is due to the simultaneous hydrolysis of aluminum and sulfur ions. The reduction of the recovery of valuable metals caused by the Fe2+ is due to the form of iron sulfides.