873 resultados para behavior and fate


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This study focuses on empirical investigations and seeks implications by utilizing three different methodologies to test various aspects of trader behavior. The first methodology utilizes Prospect Theory to determine trader behavior during periods of extreme wealth contracting periods. Secondly, a threshold model to examine the sentiment variable is formulated and thirdly a study is made of the contagion effect and trader behavior. The connection between consumers' sense of financial well-being or sentiment and stock market performance has been studied at length. However, without data on actual versus experimental performance, implications based on this relationship are meaningless. The empirical agenda included examining a proprietary file of daily trader activities over a five-year period. Overall, during periods of extreme wealth altering conditions, traders "satisfice" rather than choose the "best" alternative. A trader's degree of loss aversion depends on his/her prior investment performance. A model that explains the behavior of traders during periods of turmoil is developed. Prospect Theory and the data file influenced the design of the model. Additional research included testing a model that permitted the data to signal the crisis through a threshold model. The third empirical study sought to investigate the existence of contagion caused by declining global wealth effects using evidence from the mining industry in Canada. Contagion, where a financial crisis begins locally and subsequently spreads elsewhere, has been studied in terms of correlations among similar regions. The results provide support for Prospect Theory in two out of the three empirical studies. The dissertation emphasizes the need for specifying precise, testable models of investors' expectations by providing tools to identify paradoxical behavior patterns. True enhancements in this field must include empirical research utilizing reliable data sources to mitigate data mining problems and allow researchers to distinguish between expectations-based and risk-based explanations of behavior. Through this type of research, it may be possible to systematically exploit "irrational" market behavior.

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The behaviour and fate of spilled oil in harsh marine environments, such as the North Atlantic and the Arctic Ocean are complex due to environmental factors and the composition of the crude. In order to develop appropriate oil spill prevention and management methods, we must first understand how the oil behaves in these harsh environmental conditions. This study focuses on determining the fate of oil in harsh marine environments by first identifying target compounds in the oil that can be used to determine the fate of a spill. This thesis presents the partitioning behaviour of six polycyclic aromatic hydrocarbons (PAHs), which represent different groups, and phenols in cold conditions. The smallest PAH, naphthalene, dominated in terms of concentration in water accommodated fraction (WAF) of oil, while the larger ringed PAHs presented at lower concentrations. The smallest oil-water partition coefficient was recorded by phenol which partitioned into the seawater more quickly than PAHs. The partitioning of larger PAHs was slower and they indicated high partition coefficients. The oil partitioning increased slightly as temperature increased from 4ᴼC to 15ᴼC. The oil loading (0.1 g/L to 10 g/L) also contributed in deciding the concentrations in water. The use of chemical dispersants is a common response to spills. This study identified that chemical dispersants can change the fate of an oil spill by increasing the availability of oil in seawater. The concentration of larger PAHs such as pyrene and chrysene increased significantly with the application of dispersants. The information obtained are used in developing a molecular imprinted polymer (MIP) sensor to identify oil spills in the North Atlantic Ocean.

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Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.

The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.

In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.

I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.

Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.

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In this Rapid Communication we demonstrate the applicability of an augmented Gibbs ensemble Monte Carlo approach for the phase behavior determination of model colloidal systems with short-ranged depletion attraction and long-ranged repulsion. This technique allows for a quantitative determination of the phase boundaries and ground states in such systems. We demonstrate that gelation may occur in systems of this type as the result of arrested microphase separation, even when the equilibrium state of the system is characterized by compact microphase structures.

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Understanding consumer behavior is critical for firms' decision making. How consumers make decisions about what they want and buy directly affect the profits of firms. Therefore, it is important to consider consumer behaviors and incorporate them into the model when studying the optimal strategy of firms and competition between firms. In this dissertation, I study rich and interesting consumer behaviors and their impact on firms' strategy in two essays. The first essay considers consumers' shopping cost which leads to their preference for one-stop shopping. I examine how store visit costs and consumer knowledge about a product affect the strategic store choice of consumers and, in turn, the pricing, customer service and advertising decisions of competing retailers. My analysis offers insights on how specialty stores can compete with big-box retailers. In the second essay, I focus on a well-established psychology phenomenon, cognitive dissonance. I incorporate the idea of cognitive dissonance into a model of spatial competition and examine its implications for selling strategy. I provide new insight on the profitability of advance selling and spot selling as well as the pricing of bundle and its components. Collectively, two essays in this dissertation introduce novel ways to model consumer behaviors and help to understand the impact of consumer behaviors on firm profitability and strategy.

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For the official publication, see: http://dx.doi.org/10.1016/j.lindif.2016.06.021

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Thesis (Master's)--University of Washington, 2016-06

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Two further key aspects of prosociality as a sexual signal are explored here. Firstly, the context in which it is used (in particular relationship length), and, second, also the different types of prosocial behaviors that exist in social interactions. Therefore, this commentary can show why prosocial behaviors are biased towards physically attractive individuals, as they can gain valuable information from them.

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Although very little is known about the transport, fate and toxic effects of medical compounds in aquatic environments, the presence of these compounds in potable water sources can no longer be overlooked. We can argue that trace concentrations of drugs in the water is relatively a minor problem, however, the current and future demands on global potable freshwater supplies will probably lead to greater incidents of indirect and direct water-reuse situations at the local, regional, and cross-border levels. It is important to remark that the solution of this emerging ecological issue does not rely on new and better wastewater treatment technologies, but a new paradigm of responsibility and the understanding of the relations between anthropogenic actions and their ecological effects as well. The objective of this brief communication is to present the state of the art of research conducted in the last decade in Europe and United States concerning the presence of pharmaceuticals products in aquatic environments.

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In the context of greater market liberalization in Latin America, one issue that merits greater attention for empirical investigation is the international expansion of family-owned business. Specifically, the relationship between export behavior, family control and board composition in the Latin American context is absent in the literature. Using a large and unique database from Colombian firms (33,249 firms in the period of 2008 to 2013), we provide insightful information on the determinants of export behavior of family firms in emerging markets. Our empirical test confirms an endogenous relation between boards’ composition (specifically the presence of independent members) and export behavior in family firms. Firms with a higher participation of independent board members are more likely to exhibit higher levels of exports. A "virtuous cycle" was also detected whereby the introduction of independent members on the board can be expected to boost export behavior, which in turn will encourage the increase of independent members on the board of private firms.

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A detailed non-equilibrium state diagram of shape-anisotropic particle fluids is constructed. The effects of particle shape are explored using Naive Mode Coupling Theory (NMCT), and a single particle Non-linear Langevin Equation (NLE) theory. The dynamical behavior of non-ergodic fluids are discussed. We employ a rotationally frozen approach to NMCT in order to determine a transition to center of mass (translational) localization. Both ideal and kinetic glass transitions are found to be highly shape dependent, and uniformly increase with particle dimensionality. The glass transition volume fraction of quasi 1- and 2- dimensional particles fall monotonically with the number of sites (aspect ratio), while 3-dimensional particles display a non-monotonic dependence of glassy vitrification on the number of sites. Introducing interparticle attractions results in a far more complex state diagram. The ideal non-ergodic boundary shows a glass-fluid-gel re-entrance previously predicted for spherical particle fluids. The non-ergodic region of the state diagram presents qualitatively different dynamics in different regimes. They are qualified by the different behaviors of the NLE dynamic free energy. The caging dominated, repulsive glass regime is characterized by long localization lengths and barrier locations, dictated by repulsive hard core interactions, while the bonding dominated gel region has short localization lengths (commensurate with the attraction range), and barrier locations. There exists a small region of the state diagram which is qualified by both glassy and gel localization lengths in the dynamic free energy. A much larger (high volume fraction, and high attraction strength) region of phase space is characterized by short gel-like localization lengths, and long barrier locations. The region is called the attractive glass and represents a 2-step relaxation process whereby a particle first breaks attractive physical bonds, and then escapes its topological cage. The dynamic fragility of fluids are highly particle shape dependent. It increases with particle dimensionality and falls with aspect ratio for quasi 1- and 2- dimentional particles. An ultralocal limit analysis of the NLE theory predicts universalities in the behavior of relaxation times, and elastic moduli. The equlibrium phase diagram of chemically anisotropic Janus spheres and Janus rods are calculated employing a mean field Random Phase Approximation. The calculations for Janus rods are corroborated by the full liquid state Reference Interaction Site Model theory. The Janus particles consist of attractive and repulsive regions. Both rods and spheres display rich phase behavior. The phase diagrams of these systems display fluid, macrophase separated, attraction driven microphase separated, repulsion driven microphase separated and crystalline regimes. Macrophase separation is predicted in highly attractive low volume fraction systems. Attraction driven microphase separation is charaterized by long length scale divergences, where the ordering length scale determines the microphase ordered structures. The ordering length scale of repulsion driven microphase separation is determined by the repulsive range. At the high volume fractions, particles forgo the enthalpic considerations of attractions and repulsions to satisfy hard core constraints and maximize vibrational entropy. This results in site length scale ordering in rods, and the sphere length scale ordering in Janus spheres, i.e., crystallization. A change in the Janus balance of both rods and spheres results in quantitative changes in spinodal temperatures and the position of phase boundaries. However, a change in the block sequence of Janus rods causes qualitative changes in the type of microphase ordered state, and induces prominent features (such as the Lifshitz point) in the phase diagrams of these systems. A detailed study of the number of nearest neighbors in Janus rod systems reflect a deep connection between this local measure of structure, and the structure factor which represents the most global measure of order.

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This study investigates the structure and intensity of the surface pathways connecting to and from the central areas of the large-scale convergence regions of the eastern Pacific Ocean. Surface waters are traced with numerical Lagrangian particles transported in the velocity field of three different ocean models with horizontal resolutions that range from ¼° to 1/32°. The connections resulting from the large-scale convergent Ekman dynamics agree qualitatively but are strongly modulated by eddy variability that introduces meridional asymmetry in the amplitude of transport. Lagrangian forward-in-time integrations are used to analyze the fate of particles originating from the central regions of the convergence zones and highlight specific outflows not yet reported for the southeastern Pacific when using the currents at the highest resolutions (1/12° and 1/32°). The meridional scales of these outflows are comparable to the characteristic width of the fine-scale striation of mean currents.