Optimization and Machine Learning Frameworks for Complex Network Analysis

Thesis (Ph.D.)--University of Washington, 2016-06

Postsynthesis stabilization of free-standing mesoporous silica films

Mixed ammonia-water vapor postsynthesis treatment provides a simple and convenient method for stabilizing mesostructured silica films. X-ray diffraction, transmission electron microscopy, nitrogen adsorption/desorption, and solid-state NMR (C-13, Si-29) were applied to study the effects of mixed ammonia-water vapor at 90 degreesC on the mesostructure of the films. An increased cross-linking of the silica network was observed. Subsequent calcination of the silica films was seen to cause a bimodal pore-size distribution, with an accompanying increase in the volume and surface area ratios of the primary (d = 3 nm) to secondary (d = 5-30 nm) pores. Additionally, mixed ammonia-water treatment was observed to cause a narrowing of the primary pore-size distribution. These findings have implications for thin film based applications and devices, such as sensors, membranes, or surfaces for heterogeneous catalysis.

Rheological Properties of Organoclay Suspensions in Epoxy Network Precursors

This paper deals with the evolution of the state of dispersion of organically modified montmorillonites in epoxy or amine precursors. The epoxy prepolymer is a diglycidyl ether of bisphenol A (DGEBA) and the curing agent is an aliphatic diamine with a polyoxypropylene backbone (Jeffamine D2000). The clay dispersion is evaluated at the platelet scale (nanoscopic scale) from X-ray spectrometry [wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS)] and at the aggregates scale (microscopic scale) from rheological analysis. The organoclays used form gels in the monomers above the percolation threshold if no shear is applied and present a mechanical gel/sol transition when shear stress increases. Gel strength and viscosity at high shear rates are linked to the nanometric state of dispersion and reveal the existence of two different organizations depending on organoclay/monomer interactions: (i) When the clay shows good interactions with the monomer, a significant swelling of the clay galleries by the monomer is obtained. These swollen particles lead to formation of weak gels which after shearing give high relative viscosity fluids. (ii) When the clay develops poor interactions with the monomer, the clay tends to reduce its exchange surface with the monomer and leads to a strongly connected gel. Shear breaks down this physical network leading to a very low relative viscosity fluid composed of nonswollen particles keeping a high aspect ratio. (C) 2003 Elsevier B.V All rights reserved.

Large-scale velocity structures in the Horologium-Reticulum supercluster

We present 547 optical redshifts obtained for galaxies in the region of the Horologium-Reticulum supercluster (HRS) using the 6 degrees field (6dF) multifiber spectrograph on the UK Schmidt Telescope at the Anglo-Australian Observatory. The HRS covers an area of more than 12 degrees x 12 degrees on the sky centered at approximately alpha = 03(h)19(m), delta = 50 degrees 02'. Our 6dF observations concentrate on the intercluster regions of the HRS, from which we describe four primary results. First, the HRS spans at least the redshift range from 17,000 to 22,500 km s(-1). Second, the overdensity of galaxies in the intercluster regions of the HRS in this redshift range is estimated to be 2.4, or delta rho/(rho) over bar similar to 1: 4. Third, we find a systematic trend of increasing redshift along a southeast-northwest spatial axis in the HRS, in that the mean redshift of HRS members increases by more than 1500 km s(-1) from southeast to northwest over a 12 degrees region. Fourth, the HRS is bimodal in redshift with a separation of similar to 2500 km s(-1) (35 Mpc) between the higher and lower redshift peaks. This fact is particularly evident if the above spatial-redshift trend is fitted and removed. In short, the HRS appears to consist of two components in redshift space, each one exhibiting a similar systematic spatial-redshift trend along a southeast-northwest axis. Lastly, we compare these results from the HRS with the Shapley supercluster and find similar properties and large-scale features.

A theoretical exploration of catchment-scale sediment delivery

This paper proposes a theoretical explanation of the variations of the sediment delivery ratio (SDR) versus catchment area relationships and the complex patterns in the behavior of sediment transfer processes at catchment scale. Taking into account the effects of erosion source types, deposition, and hydrological controls, we propose a simple conceptual model that consists of two linear stores arranged in series: a hillslope store that addresses transport to the nearest streams and a channel store that addresses sediment routing in the channel network. The model identifies four dimensionless scaling factors, which enable us to analyze a variety of effects on SDR estimation, including (1) interacting processes of erosion sources and deposition, (2) different temporal averaging windows, and (3) catchment runoff response. We show that the interactions between storm duration and hillslope/channel travel times are the major controls of peak-value-based sediment delivery and its spatial variations. The interplay between depositional timescales and the travel/residence times determines the spatial variations of total-volume-based SDR. In practical terms this parsimonious, minimal complexity model could provide a sound physical basis for diagnosing catchment to catchment variability of sediment transport if the proposed scaling factors can be quantified using climatic and catchment properties.

Modeling hybridoma cell metabolism using a generic genome-scale metabolic model of Mus musculus

The reconstructed cellular metabolic network of Mus musculus, based on annotated genomic data, pathway databases, and currently available biochemical and physiological information, is presented. Although incomplete, it represents the first attempt to collect and characterize the metabolic network of a mammalian cell on the basis of genomic data. The reaction network is generic in nature and attempts to capture the carbon, energy, and nitrogen metabolism of the cell. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, including transport reactions between the compartments and the extracellular medium. The reaction list consists of 872 internal metabolites involved in a total of 1220 reactions, whereof 473 relate to known open reading frames. Initial in silico analysis of the reconstructed model is presented.

Time-evolution of highly localized positive-energy states of the free Dirac electron

Highly localized positive-energy states of the free Dirac electron are constructed and shown to evolve in a simple way under the action of Dirac's equation. When the initial uncertainty in position is small on the scale of the Compton wavelength, there is an associated uncertainty in the mean energy that is large compared with the rest mass of the electron. However, this does not lead to any breakdown of the one-particle description, associated with the possibility of pair-production, but rather leads to a rapid expansion of the probability density outwards from the point of localization, at speeds close to the speed of light.

Establishing representative no-take areas in the Great Barrier Reef : Large scale implementation of theory on marine protected areas

The Great Barrier Reef Marine Park, an area almost the size , of Japan, has a new network of no-take areas that significantly improves the protection of biodiversity. The new marine park zoning implements, in a quantitative manner, many of the theoretical design principles discussed in the literature. For example, the new network of no-take areas has at least 20% protection per bioregion, minimum levels of protection for all known habitats and special or unique features, and minimum sizes for no-take areas of at least 10 or 20 kat across at the smallest diameter Overall, more than 33% of the Great Barrier Reef Marine Park is now in no-take areas (previously 4.5%). The steps taken leading to this outcome were to clarify to the interested public why the existing level of protection wets inadequate; detail the conservation objectives of establishing new no-take areas; work with relevant and independent experts to define, and contribute to, the best scientific process to deliver on the objectives; describe the biodiversity (e.g., map bioregions); define operational principles needed to achieve the objectives; invite community input on all of The above; gather and layer the data gathered in round-table discussions; report the degree of achievement of principles for various options of no-take areas; and determine how to address negative impacts. Some of the key success factors in this case have global relevance and include focusing initial communication on the problem to be addressed; applying the precautionary principle; using independent experts; facilitating input to decision making; conducting extensive and participatory consultation; having an existing marine park that encompassed much of the ecosystem; having legislative power under federal law; developing high-level support; ensuring agency Priority and ownership; and being able to address the issue of displaced fishers.

Effect of free ammonia and free nitrous acid concentration on the anabolic and catabolic processes of an enriched Nitrosomonas culture

The effects of free ammonia (FA; NH3) and free nitrous acid (FNA; HNO2) concentrations on the metabolisms of an enriched ammonia oxidizing bacteria (AOB) culture were investigated using a method allowing the decoupling of growth and energy generation processes. A lab-scale sequencing batch reactor (SBR) was operated for the enrichment of an AOB culture. Fluorescent in-situ hybridization (FISH) analysis showed that 82% of the bacterial population in the SBR bound to the NEU probe specifically designed for Nitrosomonas europaea. Batch tests were carried out to measure the oxygen and ammonium consumption rates by the culture at various FA and FNA levels, in the presence or absence of inorganic carbon (CO2, HCO3, and CO32-). It was revealed that FA of up to 16.0 mgNH(3)-N (.) L-1, which was the highest concentration used in this study, did not have any inhibitory effect on either the catabolic or anabolic processes of the Nitrosomonas culture. In contrast, FNA inhibited both the growth and energy production capabilities of the Nitrosomonas culture. The inhibition on growth initiated at approximately 0.10 mgHNO(2)-(NL-1)-L-., and the data suggested that the biosynthesis was completely stopped at an FNA concentration of 0.40 mgHNO(2)-N (.) L-1. The inhibition on energy generation initiated at a slightly lower level but the Nitrosomonas culture was still oxidizing ammonia at half of the maximum rate at an FNA concentration of 0.50-0.63 mgHNO(2)-N (.) L-1. The affinity constant of the Nitrosomonas culture with respect to ammonia was determined to be 0.36 mgNH3-N (.) L-1, independent of the presence or absence of inorganic carbon. (c) 2006 Wiley Periodicals, Inc.

Effect of temperature and free ammonia on nitrification and nitrite accumulation in landfill leachate and analysis of its nitrifying bacterial community by FISH

The cause of seasonal failure of a nitrifying municipal landfill leachate treatment plant utilizing a fixed biofilm was investigated by wastewater analyses and batch respirometric tests at every treatment stage. Nitrification of the leachate treatment plant was severely affected by the seasonal temperature variation. High free ammonia (NH3-N) inhibited not only nitrite oxidizing bacteria (NOB) but also ammonia oxidizing bacteria (AOB). In addition, high pH also increased free ammonia concentration to inhibit nitrifying activity especially when the NH4-N level was high. The effects of temperature and free ammonia of landfill leachate on nitrification and nitrite accumulation were investigated with a semi-pilot scale biofilm airlift reactor. Nitrification rate of landfill leachate increased with temperature when free ammonia in the reactor was below the inhibition level for nitrifiers. Leachate was completely nitrified up to a load of 1.5 kg NH4-N m(-3) d(-1) at 28 degrees C. The activity of NOB was inhibited by NH3-N resulting in accumulation of nitrite. NOB activity decreased more than 50% at 0.7 mg NH3-N L-1. Fluorescence in situ hybridization (FISH) was carried out to analyze the population of AOB and NOB in the nitrite accumulating nitrifying biofilm. NOB were located close to AOB by forming small clusters. A significant fraction of AOB identified by probe Nso1225 specifically also hybridized with the Nitrosonlonas specific probe Nsm156. The main NOB were Nitrobacter and Nitrospira which were present in almost equal amounts in the biofilm as identified by simultaneous hybridization with Nitrobacter specific probe Nit3 and Nitrospira specific probe Ntspa662. (c) 2005 Elsevier Ltd. All rights reserved.

The inhibitory effects of free nitrous acid on the energy generation and growth processes of an enriched Nitrobacter culture

The inhibitory effects of nitrite (NO2-)/free nitrous acid (HNO2-FNA) on the metabolism of Nitrobacter were investigated using a method allowing the decoupling of the growth and energy generation processes. A lab-scale sequencing batch reactor was operated for the enrichment of a Nitrobacter culture. Fluorescent in situ hybridization (FISH) analysis showed that 73% of the bacterial population was Nitrobacter. Batch tests were carried out to assess the oxygen and nitrite consumption rates of the enriched culture at low and high nitrite levels, in the presence or absence of inorganic carbon. It was observed that in the absence of CO2, the Nitrobacter culture was able to oxidize nitrite at a rate that is 76% of that in the presence of CO2, with an oxygen consumption rate that is 85% of that measured in the presence of CO2. This enabled the impacts of nitrite/FNA on the catabolic and anabolic processes of Nitrobacter to be assessed separately. FNA rather than nitrite was likely the actual inhibitor to the Nitrobacter metabolism. It was revealed that FNA of up to 0.05 mg HNO2-N center dot L-1 (3.4 mu M), which was the highest FNA concentration used in this study, did not have any inhibitory effect on the catabolic processes of Nitrobacter. However, FNA initiated its inhibition to the anabolic processes of Nitrobacter at approximately 0.011 mg HNO2-N center dot L-1 (0.8 mu M), and completely stopped biomass synthesis at a concentration of approximately 0.023 mg HNO2-N center dot L-1 (1.6 mu M). The inhibitory effect could be described by an empirical inhibitory model proposed in this paper, but the underlying mechanisms remain to be revealed.

The n-tuple network: coping with sub-optimality

The subject of this thesis is the n-tuple net.work (RAMnet). The major advantage of RAMnets is their speed and the simplicity with which they can be implemented in parallel hardware. On the other hand, this method is not a universal approximator and the training procedure does not involve the minimisation of a cost function. Hence RAMnets are potentially sub-optimal. It is important to understand the source of this sub-optimality and to develop the analytical tools that allow us to quantify the generalisation cost of using this model for any given data. We view RAMnets as classifiers and function approximators and try to determine how critical their lack of' universality and optimality is. In order to understand better the inherent. restrictions of the model, we review RAMnets showing their relationship to a number of well established general models such as: Associative Memories, Kamerva's Sparse Distributed Memory, Radial Basis Functions, General Regression Networks and Bayesian Classifiers. We then benchmark binary RAMnet. model against 23 other algorithms using real-world data from the StatLog Project. This large scale experimental study indicates that RAMnets are often capable of delivering results which are competitive with those obtained by more sophisticated, computationally expensive rnodels. The Frequency Weighted version is also benchmarked and shown to perform worse than the binary RAMnet for large values of the tuple size n. We demonstrate that the main issues in the Frequency Weighted RAMnets is adequate probability estimation and propose Good-Turing estimates in place of the more commonly used :Maximum Likelihood estimates. Having established the viability of the method numerically, we focus on providillg an analytical framework that allows us to quantify the generalisation cost of RAMnets for a given datasetL. For the classification network we provide a semi-quantitative argument which is based on the notion of Tuple distance. It gives a good indication of whether the network will fail for the given data. A rigorous Bayesian framework with Gaussian process prior assumptions is given for the regression n-tuple net. We show how to calculate the generalisation cost of this net and verify the results numerically for one dimensional noisy interpolation problems. We conclude that the n-tuple method of classification based on memorisation of random features can be a powerful alternative to slower cost driven models. The speed of the method is at the expense of its optimality. RAMnets will fail for certain datasets but the cases when they do so are relatively easy to determine with the analytical tools we provide.

An advanced real-time predictive maintenance framework for large scale machine systems

This thesis introduces and develops a novel real-time predictive maintenance system to estimate the machine system parameters using the motion current signature. Recently, motion current signature analysis has been addressed as an alternative to the use of sensors for monitoring internal faults of a motor. A maintenance system based upon the analysis of motion current signature avoids the need for the implementation and maintenance of expensive motion sensing technology. By developing nonlinear dynamical analysis for motion current signature, the research described in this thesis implements a novel real-time predictive maintenance system for current and future manufacturing machine systems. A crucial concept underpinning this project is that the motion current signature contains infor­mation relating to the machine system parameters and that this information can be extracted using nonlinear mapping techniques, such as neural networks. Towards this end, a proof of con­cept procedure is performed, which substantiates this concept. A simulation model, TuneLearn, is developed to simulate the large amount of training data required by the neural network ap­proach. Statistical validation and verification of the model is performed to ascertain confidence in the simulated motion current signature. Validation experiment concludes that, although, the simulation model generates a good macro-dynamical mapping of the motion current signature, it fails to accurately map the micro-dynamical structure due to the lack of knowledge regarding performance of higher order and nonlinear factors, such as backlash and compliance. Failure of the simulation model to determine the micro-dynamical structure suggests the pres­ence of nonlinearity in the motion current signature. This motivated us to perform surrogate data testing for nonlinearity in the motion current signature. Results confirm the presence of nonlinearity in the motion current signature, thereby, motivating the use of nonlinear tech­niques for further analysis. Outcomes of the experiment show that nonlinear noise reduction combined with the linear reverse algorithm offers precise machine system parameter estimation using the motion current signature for the implementation of the real-time predictive maintenance system. Finally, a linear reverse algorithm, BJEST, is developed and applied to the motion current signature to estimate the machine system parameters.

HTHP syngas cleaning concept of two stage biomass gasification for FT synthesis

The EU intends to increase the fraction of fuels from biogenic energy sources from 2% in 2005 to 8% in 2020. This means a minimum of 30 million TOE/a of fuels from biomass. This makes technical-scale generation of syngas from high-grade biomass, e.g. straw, hay, bark, or paper/cardboard waste, and the production of synthetic fuels by Fischer-Tropsch (FT) synthesis highly attractive. The BTL concept (Biomass to Liquids) of the Karlsruhe Research Center, labeled bioliq, focuses on this challenge by locally concentrating the biomass energy content by fast pyrolysis in a coke/oil slurry followed by slurry conversion to syngas in a central entrained flow gasifier at 1200C and pressures above 4MPa. FT synthesis generates intermediate products for synthetic fuels. To prevent the sensitive catalysts from being poisoned the syngas must be free of tar and particulates. Trace concentrations of H2S, COS, CS2, HCl, NH3, and HCN must be on the order of a few ppb. Moreover, maximum conversion efficiency will be achieved by cleaning the gas above the synthesis conditions. (T>350C, P>4MPa). The concept of an innovative dry HTHP syngas cleaning process is presented. Based on HT particle filtration and suitable sorption and catalysis processes for the relevant contaminants, an overall concept will be derived, which leads to a syngas quality required for FT synthesis in only two combined stages. Results of filtration experiments on a pilot scale are presented. The influence of temperature on the separation and conversion, respectively, of particulates and gaseous contaminants is discussed on the basis of experimental results obtained on a laboratory and pilot scale. Extensive studies of this concept are performed in a scientific network comprising the Karlsruhe Research Center and five universities; funding is provided by the Helmholtz Association of National Research Centers in Germany.