abstract: Zero-Valent Metals (ZVM) are highly reactive materials and have been proved to be effective in contaminant reduction in soils and groundwater remediation. In fact, zero-Valent Iron (ZVI) has proven to be very effective in removing, particularly chlorinated organics, heavy metals, and odorous sulfides. Addition of ZVI has also been proved in enhancing the methane gas generation in anaerobic digestion of activated sludge. However, no studies have been conducted regarding the effect of ZVM stimulation to Municipal Solid Waste (MSW) degradation. Therefore, a collaborative study was developed to manipulate microbial activity in the landfill bioreactors to favor methane production by adding ZVMs. This study focuses on evaluating the effects of added ZVM on the leachate generated from replicated lab scale landfill bioreactors. The specific objective was to investigate the effects of ZVMs addition on the organic and inorganic pollutants in leachate. The hypothesis here evaluated was that adding ZVM including ZVI and Zero Valent Manganese (ZVMn) will enhance the removal rates of the organic pollutants present in the leachate, likely by a putative higher rate of microbial metabolism. Test with six (4.23 gallons) bioreactors assembled with MSW collected from the Salt River Landfill and Southwest Regional Landfill showed that under 5 grams /liter of ZVI and 0.625 grams/liter of ZVMn additions, no significant difference was observed in the pH and temperature data of the leachate generated from these reactors. The conductivity data suggested the steady rise across all reactors over the period of time. The removal efficiency of sCOD was highest (27.112 mg/lit/day) for the reactors added with ZVMn at the end of 150 days for bottom layer, however the removal rate was highest (16.955 mg/lit/day) for ZVI after the end of 150 days of the middle layer. Similar trends in the results was observed in TC analysis. HPLC study indicated the dominance of the concentration of heptanoate and isovalerate were leachate generated from the bottom layer across all reactors. Heptanoate continued to dominate in the ZVMn added leachate even after middle layer injection. IC analysis concluded the chloride was dominant in the leachate generated from all the reactors and there was a steady increase in the chloride content over the period of time. Along with chloride, fluoride, bromide, nitrate, nitrite, phosphate and sulfate were also detected in considerable concentrations. In the summary, the addition of the zero valent metals has proved to be efficient in removal of the organics present in the leachate. / Dissertation/Thesis / Masters Thesis Environmental and Resource Management 2019

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第18407号 / 情博第522号 / 新制||情||92(附属図書館) / 31265 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 黒橋 禎夫, 教授 西田 豊明, 教授 河原 達也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

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The goal of this case study was to investigate the behavior of real textile wastewater in DCMD (Direct Contact Membrane Distillation) treatment and subsequently to develop a simple and effective pretreatment for it. To this moment, this work is one of the only studies to make an in-depth analysis of the treatment while considering the complexity of this effluent, which is inherently composed of Volatile Organic Compounds (VOCs) and surfactants. After the application of pretreatment, it became clear that the main concern with textile wastewater treatment using MD is wetting, not fouling. Sedimentation and filtration alone were effective in removing suspended solids, but insufficient in stopping wetting. However, neutralization before sedimentation and filtration was proven to be a fundamental step in reducing wetting rates. This improved performance happens due to the change in pH of the wastewater sample, which increases the rejection rates by the membrane. The best experiments, neutralized to pHs 7.40 and 9.06, achieved up to 99.89% rejection by the membrane, with up to 97% conductivity decrease when compared to an experiment without neutralization, 97% removal of COD, and 98% TOC. Overall, the permeate obtained in this work after pretreatment demonstrated excellent quality, and the recovered effluent can possibly be reused in the textile industry, aiming for Zero Liquid Discharge (ZLD) processes. Thus, scaling up this technology for real industrial use is still necessary, tailoring the treatment to the effluent's characteristics to obtain the best results.

For a graph G we define S(G) to be the set of all real symmetric n by n matrices whose off-diagonal zero/nonzero pattern is described by G. We show how to compute the minimum rank of all matrices in S(G) for a class of graphs called outerplanar graphs. In addition, we obtain results on the possible eigenvalues and possible inertias of matrices in S(G) for certain classes of graph G. We also obtain results concerning the relationship between two graph parameters, the zero forcing number and the path cover number, related to the minimum rank problem.

Zero-Shot Learning (ZSL) for image classification aims to recognize images from novel classes for which we have no training examples. A common approach to tackling such a problem is by transferring knowledge from seen to unseen classes using some auxiliary semantic information of class labels in the form of class embeddings. Most of the existing methods represent image features and class embeddings as point vectors, and such vector representation limits the expressivity in terms of modeling the intra-class variability of the image classes. In this thesis, we propose three novel ZSL methods that represent image features and class labels as distributions and learn their corresponding parameters as distribution embeddings. Therefore, the intra-class variability of image classes is better modeled. The first model is a Triplet model, where image features and class embeddings are projected as Gaussian distributions in a common space, and their associations are learned by metric learning. Next, we have a Triplet-VAE model, where two VAEs are trained with triplet based distributional alignment for ZSL. The third model is a simple Probabilistic Classifier for ZSL, which is inspired by energy-based models. When evaluated on the common benchmark ZSL datasets, the proposed methods result in an improvement over the existing state-of-the-art methods for both traditional ZSL and more challenging Generalized-ZSL (GZSL) settings. / Zero-Shot Learning (ZSL) för bildklassificering syftar till att känna igen bilder från nya klasser som vi inte har några utbildningsexempel för. Ett vanligt tillvägagångssätt för att ta itu med ett sådant problem är att överföra kunskap från sett till osynliga klasser med hjälp av någon semantisk information om klassetiketter i form av klassinbäddningar. De flesta av de befintliga metoderna representerar bildfunktioner och klassinbäddningar som punktvektorer, och sådan vektorrepresentation begränsar uttrycksförmågan när det gäller att modellera bildklassernas variation inom klass. I denna avhandling föreslår vi tre nya ZSL-metoder som representerar bildfunktioner och klassetiketter som distributioner och lär sig deras motsvarande parametrar som distributionsinbäddningar. Därför är bildklassernas variation inom klass bättre modellerad. Den första modellen är en Triplet-modell, där bildfunktioner och klassinbäddningar projiceras som Gaussiska fördelningar i ett gemensamt utrymme, och deras föreningar lärs av metrisk inlärning. Därefter har vi en Triplet-VAE-modell, där två VAEs tränas med tripletbaserad fördelningsinriktning för ZSL. Den tredje modellen är en enkel Probabilistic Classifier för ZSL, som är inspirerad av energibaserade modeller. När de utvärderas på de vanliga ZSLdatauppsättningarna, resulterar de föreslagna metoderna i en förbättring jämfört med befintliga toppmoderna metoder för både traditionella ZSL och mer utmanande Generalized-ZSL (GZSL) -inställningar.

In Part I of the thesis an account is given of the basic algebra of extension fields which is required for the understanding of Galois theory. The fundamental theorem states the relationships of the subgroups of a permutation group of the root field of an equation to the subfields which are left invariant by these subgroups. Extensions of the basic theorem conclude Part I. In part II the solvability of equations by radicals is discussed, for fields of characteristic zero. A discussion of finite fields and primitive roots leads to a criterion for the solvability by radicals of equations over fields of prime characteristic. Finally, a method for determining the Galois group of any equation is discussed. Most of the material in the introductory chapters is taken from Artin's: Galois Theory (cf. p. 120). / Thesis / Master of Arts (MA)