Fractal analysis of flocs formed in edible oil -water emulsions by image analysis techniques

Edible oil is an important contaminant in water and wastewater. Oil droplets smaller than 40 μm may remain in effluent as an emulsion and combine with other contaminants in water. Coagulation/flocculation processes are used to remove oil droplets from water and wastewater. By adding a polymer at proper dose, small oil droplets can be flocculated and separated from water. The purpose of this study was to characterize and analyze the morphology of flocs and floc formation in edible oil-water emulsions by using microscopic image analysis techniques. The fractal dimension, concentration of polymer, effect of pH and temperature are investigated and analyzed to develop a fractal model of the flocs. Three types of edible oil (corn, olive, and sunflower oil) at concentrations of 600 ppm (by volume) were used to determine the optimum polymer dosage and effect of pH and temperature. To find the optimum polymer dose, polymer was added to the oil-water emulsions at concentration of 0.5, 1.0, 1.5, 2.0, 3.0 and 3.5 ppm (by volume). The clearest supernatants obtained from flocculation of corn, olive, and sunflower oil were achieved at polymer dosage of 3.0 ppm producing turbidities of 4.52, 12.90, and 13.10 NTU, respectively. This concentration of polymer was subsequently used to study the effect of pH and temperature on flocculation. The effect of pH was studied at pH 5, 7, 9, and 11 at 30°C. Microscopic image analysis was used to investigate the morphology of flocs in terms of fractal dimension, radius of oil droplets trapped in floc, floc size, and histograms of oil droplet distribution. Fractal dimension indicates the density of oil droplets captured in flocs. By comparison of fractal dimensions, pH was found to be one of the most important factors controlling droplet flocculation. Neutral pH or pH 7 showed the highest degree of flocculation, while acidic (pH 5) and basic pH (pH 9 and pH 11) showed low efficiency of flocculation. The fractal dimensions achieved from flocculation of corn, olive, and sunflower oil at pH 7 and temperature 30°C were 1.2763, 1.3592, and 1.4413, respectively. The effect of temperature was explored at temperatures 20°, 30°, and 40°C and pH 7. The results of flocculation of oil at pH 7 and different temperatures revealed that temperature significantly affected flocculation. The fractal dimension of flocs formed in corn, olive and sunflower oil emulsion at pH 7 and temperature 20°, 30°, and 40°C were 1.82, 1.28, 1.29, 1.62, 1.36, 1.42, 1.36, 1.44, and 1.28, respectively. After comparison of fractal dimension, radius of oil droplets captured, and floc length in each oil type, the optimal flocculation temperature was determined to be 30°C. ^

Predicting success or failure of tax -base revenue sharing attempts: A comparative analysis

To promote regional or mutual improvement, numerous interjurisdictional efforts to share tax bases have been attempted. Most of these efforts fail to be consummated. Motivations to share revenues include: narrowing fiscal disparities, enhancing regional cooperation and economic development, rationalizing land-use, and minimizing revenue losses caused by competition to attract and keep businesses. Various researchers have developed theories to aid understanding of why interjurisdictional cooperation efforts succeed or fail. Walter Rosenbaum and Gladys Kammerer studied two contemporaneous Florida local-government consolidation attempts. Boyd Messinger subsequently tested their Theory of Successful Consolidation on nine consolidation attempts. Paul Peterson's dual theories on Modern Federalism posit that all governmental levels attempt to further economic development and that politicians act in ways that either further their futures or cement job security. Actions related to the latter theory often interfere with the former. Samuel Nunn and Mark Rosentraub sought to learn how interjurisdictional cooperation evolves. Through multiple case studies they developed a model framing interjurisdictional cooperation in four dimensions. ^ This dissertation investigates the ability of the above theories to help predict success or failure of regional tax-base revenue sharing attempts. A research plan was formed that used five sequenced steps to gather data, analyze it, and conclude if hypotheses concerning the application of these theories were valid. The primary analytical tools were: multiple case studies, cross-case analysis, and pattern matching. Data was gathered from historical records, questionnaires, and interviews. ^ The results of this research indicate that Rosenbaum-Kammerer theory can be a predictor of success or failure in implementing tax-base revenue sharing if it is amended as suggested by Messinger and further modified by a recommendation in this dissertation. Peterson's Functional and Legislative theories considered together were able to predict revenue sharing proposal outcomes. Many of the indicators of interjurisdictional cooperation forwarded in the Nunn-Rosentraub model appeared in the cases studied, but the model was not a reliable forecasting instrument. ^

An Exergy Based Engineering and Economic Analysis of Sustainable Building

To achieve the goal of sustainable development, the building energy system was evaluated from both the first and second law of thermodynamics point of view. The relationship between exergy destruction and sustainable development were discussed at first, followed by the description of the resource abundance model, the life cycle analysis model and the economic investment effectiveness model. By combining the forgoing models, a new sustainable index was proposed. Several green building case studies in U.S. and China were presented. The influences of building function, geographic location, climate pattern, the regional energy structure, and the technology improvement potential of renewable energy in the future were discussed. The building’s envelope, HVAC system, on-site renewable energy system life cycle analysis from energy, exergy, environmental and economic perspective were compared. It was found that climate pattern had a dramatic influence on the life cycle investment effectiveness of the building envelope. The building HVAC system energy performance was much better than its exergy performance. To further increase the exergy efficiency, renewable energy rather than fossil fuel should be used as the primary energy. A building life cycle cost and exergy consumption regression model was set up. The optimal building insulation level could be affected by either cost minimization or exergy consumption minimization approach. The exergy approach would cause better insulation than cost approach. The influence of energy price on the system selection strategy was discussed. Two photovoltaics (PV) systems – stand alone and grid tied system were compared by the life cycle assessment method. The superiority of the latter one was quite obvious. The analysis also showed that during its life span PV technology was less attractive economically because the electricity price in U.S. and China did not fully reflect the environmental burden associated with it. However if future energy price surges and PV system cost reductions were considered, the technology could be very promising for sustainable buildings in the future.

Maltreatment, Psychiatric Symptoms and Human Immunodeficiency Virus/Sexual Transmitted Infection Risk Behavior Among Youth with Alcohol and Other Drug Use Problems: A Person-Centered Analysis

Multi-problem youth undergoing treatment for substance use problems are at high behavioral risk for exposure to sexually transmitted infections (STIs), including human immunodeficiency virus (HIV). Specific risk factors include childhood adversities such as maltreatment experiences and subsequent forms of psychopathology. The current study used a person-centered analytical approach to examine how childhood maltreatment experiences were related to patterns of psychiatric symptoms and HIV/STI risk behaviors in a sample of adolescents (N = 408) receiving treatment services. Data were collected in face-to-face interviews at two community-based facilities. Descriptive statistics and Latent Profile Analysis (LPA) were used to (a) classify adolescents into groups based on past year psychiatric symptoms, and (b) examine relations between class membership and forms of childhood maltreatment experiences, as well as past year sexual risk behavior (SRB). LPA results indicated significant heterogeneity in psychiatric symptoms among the participants. The three classes generated via the optimal LPA solution included: (a) a low psychiatric symptoms class, (b) a high alcohol symptoms class and (c) a high internalizing symptoms class. Class membership was associated significantly with adolescents’ self-reported scores for childhood sexual abuse and emotional neglect. ANOVAs documented significant differences in mean scores for multiple indices of SRB indices by class membership, demonstrating differential risk for HIV/STI exposure across classes. The two classes characterized by elevated psychiatric symptom profiles and more severe maltreatment histories were at increased behavioral risk for HIV/STI exposure, compared to the low psychiatric symptoms class. The high internalizing symptoms class reported the highest scores for most of the indices of SRB assessed. The heterogeneity of psychiatric symptom patterns documented in the current study has important implications for HIV/STI prevention programs implemented with multi-problem youth. The results highlight complex relations between childhood maltreatment experiences, psychopathology and multiple forms of health risk behavior among adolescents. The results underscore the importance of further integration between substance abuse treatment and HIV/STI risk reduction efforts to improve morbidity and mortality among vulnerable youth.

Analysis of the lateral diffuse metal-oxide semiconductor (LDMOS) power amplifier for cellular base stations

The primary purpose of this thesis was to present a theoretical large-signal analysis to study the power gain and efficiency of a microwave power amplifier for LS-band communications using software simulation. Power gain, efficiency, reliability, and stability are important characteristics in the power amplifier design process. These characteristics affect advance wireless systems, which require low-cost device amplification without sacrificing system performance. Large-signal modeling and input and output matching components are used for this thesis. Motorola's Electro Thermal LDMOS model is a new transistor model that includes self-heating affects and is capable of small-large signal simulations. It allows for most of the design considerations to be on stability, power gain, bandwidth, and DC requirements. The matching technique allows for the gain to be maximized at a specific target frequency. Calculations and simulations for the microwave power amplifier design were performed using Matlab and Microwave Office respectively. Microwave Office is the simulation software used in this thesis. The study demonstrated that Motorola's Electro Thermal LDMOS transistor in microwave power amplifier design process is a viable solution for common-source amplifier applications in high power base stations. The MET-LDMOS met the stability requirements for the specified frequency range without a stability-improvement model. The power gain of the amplifier circuit was improved through proper microwave matching design using input/output-matching techniques. The gain and efficiency of the amplifier improve approximately 4dB and 7.27% respectively. The gain value is roughly .89 dB higher than the maximum gain specified by the MRF21010 data sheet specifications. This work can lead to efficient modeling and development of high power LDMOS transistor implementations in commercial and industry applications.

Active suspension development based on energy analysis

This research focuses on developing active suspension optimal controllers for two linear and non-linear half-car models. A detailed comparison between quarter-car and half-car active suspension approaches is provided for improving two important scenarios in vehicle dynamics, i.e. ride quality and road holding. Having used a half-car vehicle model, heave and pitch motion are analyzed for those scenarios, with cargo mass as a variable. The governing equations of the system are analysed in a multi-energy domain package, i.e., 20-Sim. System equations are presented in the bond-graph language to facilitate calculation of energy usage. The results present optimum set of gains for both ride quality and road holding scenarios are the gains which has derived when maximum allowable cargo mass is considered for the vehicle. The energy implications of substituting passive suspension units with active ones are studied by considering not only the energy used by the actuator, but also the reduction in energy lost through the passive damper. Energy analysis showed less energy was dissipated in shock absorbers when either quarter-car or half-car controllers were used instead of passive suspension. It was seen that more energy could be saved by using half-car active controllers than the quarter-car ones. Results also proved that using active suspension units, whether quarter-car or half-car based, under those realistic limitations is energy-efficient and suggested.

Structural Analysis and Form-Finding of Mycelium-Based Monolithic Domes

As sustainability becomes an integral design driver for current civil structures, new materials and forms are investigated. The aim of this study is to investigate analytically and numerically the mechanical behavior of monolithic domes composed of mycological fungi. The study focuses on hemispherical and elliptical forms, as the most typical solution for domes. The influence of different types of loading, geometrical parameters, material properties and boundary conditions is investigated in this study. For the cases covered by the classical shell theory, a comparison between the analytical and the finite element solution is given. Two case studies regarding the dome of basilica of “San Luca” (Bologna, Italy) and the dome of sanctuary of “Vicoforte” (Vicoforte, Italy) are included. After the linear analysis under loading, buckling is also investigated as a critical type of failure through a parametric study using finite elements model. Since shells rely on their shape, form-found domes are also investigated and a comparison between the behavior of the form-found domes and the hemispherical domes under the linear and buckling analysis is conducted. From the analysis it emerges that form-finding can enhance the structural response of mycelium-based domes, although buckling becomes even more critical for their design. Furthermore, an optimal height to span ratio for the buckling of form-found domes is identified. This study highlights the importance of investigating appropriate forms for the design of novel biomaterial-based structures.

Improved damage detectability in a wind turbine blade by optimal selection of vibration signal correlation coefficients

Piotr Omenzetter and Simon Hoell’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.

A branch and efficiency algorithm for the optimal design of supply chain networks

Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.

Large volume metrology process model:measurability analysis with integration of metrology classification model and feature-based selection model

Aircraft manufacturing industries are looking for solutions in order to increase their productivity. One of the solutions is to apply the metrology systems during the production and assembly processes. Metrology Process Model (MPM) (Maropoulos et al, 2007) has been introduced which emphasises metrology applications with assembly planning, manufacturing processes and product designing. Measurability analysis is part of the MPM and the aim of this analysis is to check the feasibility for measuring the designed large scale components. Measurability Analysis has been integrated in order to provide an efficient matching system. Metrology database is structured by developing the Metrology Classification Model. Furthermore, the feature-based selection model is also explained. By combining two classification models, a novel approach and selection processes for integrated measurability analysis system (MAS) are introduced and such integrated MAS could provide much more meaningful matching results for the operators. © Springer-Verlag Berlin Heidelberg 2010.

Optimal Reporting Systems With Investor Information Acquisition

This paper analyzes a manager's optimal ex-ante reporting system using a Bayesian persuasion approach (Kamenica and Gentzkow (2011)) in a setting where investors affect cash flows through their decision to finance the firm's investment opportunities, possibly assisted by the costly acquisition of additional information (inspection). I examine how the informativeness and the bias of the optimal system are determined by investors' inspection cost, the degree of incentive alignment between the manager and the investor, and the prior belief that the project is profitable. I find that a mis-aligned manager's system is informative

only when the market prior is pessimistic and is always positively biased; this bias decreases as investors' inspection cost decreases. In contrast, a well-aligned manager's system is fully revealing when investors' inspection cost is high, and is counter-cyclical to the market belief when the inspection cost is low: It is positively (negatively) biased when the market belief is pessimistic (optimistic). Furthermore, I explore the extent to which the results generalize to a case with managerial manipulation and discuss the implications for investment efficiency. Overall, the analysis describes the complex interactions among determinants of firm disclosures and governance, and offers explanations for the mixed empirical results in this area.

Optimal Capital Requirements in Financial Networks with Fire Sales

I explore and analyze a problem of finding the socially optimal capital requirements for financial institutions considering two distinct channels of contagion: direct exposures among the institutions, as represented by a network and fire sales externalities, which reflect the negative price impact of massive liquidation of assets.These two channels amplify shocks from individual financial institutions to the financial system as a whole and thus increase the risk of joint defaults amongst the interconnected financial institutions; this is often referred to as systemic risk. In the model, there is a trade-off between reducing systemic risk and raising the capital requirements of the financial institutions. The policymaker considers this trade-off and determines the optimal capital requirements for individual financial institutions. I provide a method for finding and analyzing the optimal capital requirements that can be applied to arbitrary network structures and arbitrary distributions of investment returns.

In particular, I first consider a network model consisting only of direct exposures and show that the optimal capital requirements can be found by solving a stochastic linear programming problem. I then extend the analysis to financial networks with default costs and show the optimal capital requirements can be found by solving a stochastic mixed integer programming problem. The computational complexity of this problem poses a challenge, and I develop an iterative algorithm that can be efficiently executed. I show that the iterative algorithm leads to solutions that are nearly optimal by comparing it with lower bounds based on a dual approach. I also show that the iterative algorithm converges to the optimal solution.

Finally, I incorporate fire sales externalities into the model. In particular, I am able to extend the analysis of systemic risk and the optimal capital requirements with a single illiquid asset to a model with multiple illiquid assets. The model with multiple illiquid assets incorporates liquidation rules used by the banks. I provide an optimization formulation whose solution provides the equilibrium payments for a given liquidation rule.

I further show that the socially optimal capital problem using the ``socially optimal liquidation" and prioritized liquidation rules can be formulated as a convex and convex mixed integer problem, respectively. Finally, I illustrate the results of the methodology on numerical examples and

discuss some implications for capital regulation policy and stress testing.

The quality of financial information in the extractive industries: a value relevance analysis

The extractive industry is characterized by high levels of risk and uncertainty. These attributes create challenges when applying traditional accounting concepts (such as the revenue recognition and matching concepts) to the preparation of financial statements in the industry. The International Accounting Standards Board (2010) states that the objective of general purpose financial statements is to provide useful financial information to assist the capital allocation decisions of existing and potential providers of capital. The usefulness of information is defined as being relevant and faithfully represented so as to best aid in the investment decisions of capital providers. Value relevance research utilizes adaptations of the Ohlson (1995) to assess the attribute of value relevance which is one part of the attributes resulting in useful information. This study firstly examines the value relevance of the financial information disclosed in the financial reports of extractive firms. The findings reveal that the value relevance of information disclosed in the financial reports depends on the circumstances of the firm including sector, size and profitability. Traditional accounting concepts such as the matching concept can be ineffective when applied to small firms who are primarily engaged in nonproduction activities that involve significant levels of uncertainty such as exploration activities or the development of sites. Standard setting bodies such as the International Accounting Standards Board and the Financial Accounting Standards Board have addressed the financial reporting challenges in the extractive industry by allowing a significant amount of accounting flexibility in industryspecific accounting standards, particularly in relation to the accounting treatment of exploration and evaluation expenditure. Therefore, secondly this study examines whether the choice of exploration accounting policy has an effect on the value relevance of information disclosed in the financial reports. The findings show that, in general, the Successful Efforts method produces value relevant information in the financial reports of profitable extractive firms. However, specifically in the oil & gas sector, the Full Cost method produces value relevant asset disclosures if the firm is lossmaking. This indicates that investors in production and non-production orientated firms have different information needs and these needs cannot be simultaneously fulfilled by a single accounting policy. In the mining sector, a preference by large profitable mining companies towards a more conservative policy than either the Full Cost or Successful Efforts methods does not result in more value relevant information being disclosed in the financial reports. This finding supports the fact that the qualitative characteristic of prudence is a form of bias which has a downward effect on asset values. The third aspect of this study is an examination of the effect of corporate governance on the value relevance of disclosures made in the financial reports of extractive firms. The findings show that the key factor influencing the value relevance of financial information is the ability of the directors to select accounting policies which reflect the economic substance of the particular circumstances facing the firms in an effective way. Corporate governance is found to have an effect on value relevance, particularly in the oil & gas sector. However, there is no significant difference between the exploration accounting policy choices made by directors of firms with good systems of corporate governance and those with weak systems of corporate governance.

The Most Complete Photometric Analysis of 548 CALIFA Galaxies

We present an extensive photometric catalog for 548 CALIFA galaxies observed as of the summer of 2015. CALIFA is currently lacking photometry matching the scale and diversity of its spectroscopy; this work is intended to meet all photometric needs for CALIFA galaxies while also identifying best photometric practices for upcoming integral field spectroscopy surveys such as SAMI and MaNGA. This catalog comprises gri surface brightness profiles derived from Sloan Digital Sky Survey (SDSS) imaging, a variety of non-parametric quantities extracted from these pro files, and parametric models fitted to the i-band pro files (1D) and original galaxy images (2D). To compliment our photometric analysis, we contrast the relative performance of our 1D and 2D modelling approaches. The ability of each measurement to characterize the global properties of galaxies is quantitatively assessed, in the context of constructing the tightest scaling relations. Where possible, we compare our photometry with existing photometrically or spectroscopically obtained measurements from the literature. Close agreement is found with Walcher et al. (2014), the current source of basic photometry and classifications of CALIFA galaxies, while comparisons with spectroscopically derived quantities reveals the effect of CALIFA's limited field of view compared to broadband imaging surveys such as the SDSS. The colour-magnitude diagram, star formation main sequence, and Tully-Fisher relation of CALIFA galaxies are studied, to give a small example of the investigations possible with this rich catalog. We conclude with a discussion of points of concern for ongoing integral field spectroscopy surveys and directions for future expansion and exploitation of this work.

RELIBILITY ANALYSIS OF SIMPLE SLOPES AND SOIL-STRUCTURES WITH LINEAR LIMIT STATES

The first objective of this research was to develop closed-form and numerical probabilistic methods of analysis that can be applied to otherwise conventional methods of unreinforced and geosynthetic reinforced slopes and walls. These probabilistic methods explicitly include random variability of soil and reinforcement, spatial variability of the soil, and cross-correlation between soil input parameters on probability of failure. The quantitative impact of simultaneously considering the influence of random and/or spatial variability in soil properties in combination with cross-correlation in soil properties is investigated for the first time in the research literature. Depending on the magnitude of these statistical descriptors, margins of safety based on conventional notions of safety may be very different from margins of safety expressed in terms of probability of failure (or reliability index). The thesis work also shows that intuitive notions of margin of safety using conventional factor of safety and probability of failure can be brought into alignment when cross-correlation between soil properties is considered in a rigorous manner. The second objective of this thesis work was to develop a general closed-form solution to compute the true probability of failure (or reliability index) of a simple linear limit state function with one load term and one resistance term expressed first in general probabilistic terms and then migrated to a LRFD format for the purpose of LRFD calibration. The formulation considers contributions to probability of failure due to model type, uncertainty in bias values, bias dependencies, uncertainty in estimates of nominal values for correlated and uncorrelated load and resistance terms, and average margin of safety expressed as the operational factor of safety (OFS). Bias is defined as the ratio of measured to predicted value. Parametric analyses were carried out to show that ignoring possible correlations between random variables can lead to conservative (safe) values of resistance factor in some cases and in other cases to non-conservative (unsafe) values. Example LRFD calibrations were carried out using different load and resistance models for the pullout internal stability limit state of steel strip and geosynthetic reinforced soil walls together with matching bias data reported in the literature.