The three chapters in this dissertation look at different aspects of the labor market and its players. The first chapter estimates the impact of using the internet for job search on job match quality. Using both the semi-parametric Meyer (1990) model and the non-parametric Hausman Woutersen (2014) hazard model, the paper finds that exit rate from employment is at least 28% lower when internet is used as a job search tool. The second chapter looks at the effect of past unemployment on future wages. It is believed that employers may use past unemployment as a signal of low productivity. In this situation workers with a history of unemployment may receive lower wages. The paper uses the Machado Mata (2005) quantile decomposition technique to decompose the wage difference into differences due to characteristics and differences due to rewards. Results indicate that workers with an unemployment spell of more than three months receive at least 12% lower wages and that more than 40% of this wage difference can be attributed to the lower rewards received by the previously unemployed.. The last chapter focuses on human capital formation and looks at some of the reasons behind the low levels of schooling India. Using the Indian Household Development Survey (2005), the paper finds that income continues to be an important factor behind the low level of primary school enrollment. On average, poor students have at least 3% lower enrollment rates, when compared to similar skilled non-poor students.

Plant microbiomes are increasingly appreciated as major drivers of plant health and ecosystem services, and are of ever-greater interest for their potential in human applications. However, plant-associated microorganisms often live in complex associations in nature. Here, I characterize one of these microbial associations: the symbiosis between foliar fungal endophytes and their bacterial endosymbionts (endohyphal bacteria, EHB). EHB influence fungal phenotypes and can shape the outcomes of plant-fungal interactions. EHB are thought to form facultative associations with many foliar fungi in the species-rich Ascomycota, but little is known about how these symbioses are initiated and maintained, or how EHB shape the ecology of their fungal hosts. In this study, I assessed factors mediating the relationships between two foliar fungi (Microdiplodia sp., Dothideomycetes; Pestalotiopsis sp. Sordariomycetes) and their EHB. I first established methods for introducing EHB into axenic mycelia of their fungal hosts, providing an important step forward for understanding the establishment of EHB associations and a critical tool for experimental tests of the effects of EHB on fungal phenotypes. Through experiments in vitro, I found that both the identity of the fungal host and the conditions under which fungi and bacteria are grown influence the establishment of EHB/fungal associations. Moreover, I showed EHB of foliar fungi can be transferred across fungal classes, thus creating experimental strains that could be used for the first time to examine the contribution of each symbiont to important fungal traits. Using these strains I evaluated how EHB influence the capacity of foliar fungi to degrade plant material as saprotrophs. I found that the presence and identity of EHB significantly influenced fungal growth on particular media, cellulase and ligninase activity, and mass loss from senescent tissue of their native host plant species in a partnership-specific manner. Because EHB can be acquired horizontally, they may help shape plant-fungal interactions, resultant ecosystem services, and the functional diversification of plant-associated fungi along the saprotroph-endophyte continuum. By manipulating EHB/fungal interactions in new ways, we can potentially influence fungal phenotypes for diverse human applications.

We consider a scheduling problem where each job requires multiple classes of resources, which we refer to as the multiple resource constrained scheduling problem(MRCSP). Potential applications include team scheduling problems that arise in service industries such as consulting and operating room scheduling. We focus on two general cases of the problem. The first case considers uncertainty of processing times, due dates, and resource availabilities consumption, which we denote as the stochastic MRCSP with uncertain parameters (SMRCSP-U). The second case considers uncertainty in the number of jobs to schedule, which arises in consulting and defense contracting when companies bid on future contracts but may or may not win the bid. We call this problem the stochastic MRCSP with job bidding (SMRCSP-JB).We first provide formulations of each problem under the framework of two-stage stochastic programming with recourse. We then develop solution methodologies for both problems. For the SMRCSP-U, we develop an exact solution method based on the L-shaped method for problems with a moderate number of scenarios. Several algorithmic enhancements are added to improve efficiency. Then, we embed the L-shaped method within a sampling-based solution method for problems with a large number of scenarios. We modify a sequential sampling procedure to allowfor approximate solution of integer programs and prove desired properties. The sampling-based method is applicable to two-stage stochastic integer programs with integer first-stage variables. Finally, we compare the solution methodologies on a set of test problems.For SMRCSP-JB, we utilize the disjunctive decomposition (D2 ) algorithm for stochastic integer programs with mixed-binary subproblems. We develop several enhancements to the D2 algorithm. First, we explore the use of a cut generation problem restricted to a subspace of the variables, which yields significant computational savings. Then, we examine generating alternative disjunctive cuts based on the generalized upper bound (GUB) constraints that appear in the second-stage of the SMRCSP-JB. We establish convergence of all D2 variants and present computational results on a set of instances of SMRCSP-JB.

Mathematical model, which depicts on macroscopic scale the physical phenomena occurring during the decomposition of gas hydrate, was set up and applied to the spherical methane hydrate pellet decomposing into ice. Initially, porous hydrate pellet is at uniform temperature and pressure within hydrate stable region. The pressure starts to decrease at t=0 with a fixed rate down to the final pressure and is kept constant afterwards. The bounding surface of pellet is heated by convection. Governing equations are based on the conservation principles, the phase equilibrium relation, equation of gas state and phase change kinetics. The single-domain approach and volume average formulation are employed to take into account transient change of local pressure, volumetric liberation of latent enthalpy, and convective heat and mass transfer accompanied by the decomposed gas flow through hydrate/ice solid matrix. The algorithm called “enthalpy method” is extended to deal with non-equilibrium phase change and utilized to determine local phase volume fractions. Predicted results suggest that the present numerical implementation is capable of predicting essential features of heat and mass transfer during non-equilibrium decomposition of hydrate pellet.

The dissociation behavior of the CH4+CO2 binary gas hydrate has been investigated using Nuclear Magnetic Resonance (NMR) spectroscopy. This technique allows us to distinguish the hydrate structure present, as well as to quantify phase concentrations. Single-pulse excitation was used in combination with magic-angle spinning (MAS). Time-resolved in situ decomposition experiments were carried out at different compositions in sealed, pressurized samples. The decomposition profiles of the CH4+CO2 binary gas hydrate system obtained at various compositions suggest that the decomposition rate is a strong function of the fractional cage occupancy and temperature. An unexpected CH4 hydrate reformation was observed during our decomposition experiments when the temperature reached the ice melting point. A decrease on the CO2 content in the hydrate phase was found during the decomposition experiment, as the pressure and temperature of the system increases.

This thesis studies methane hydrate crystal formation and decomposition at 1.0, 4.0 and 7.0°C in a new apparatus. Hydrate was formed in the interstitial space of a variable volume bed of silica sand particles with an average diameter equal to 329μm (150 to 630μm range). The initial pressure inside the reactor was 8.0MPa for all the formation experiments. Three bed sizes were employed in order to observe the effects of the silica sand bed size on the rate of methane consumption (formation) and release (decomposition). The temperature at various locations inside the silica sand bed was measured with thermocouples during formation and decomposition experiments. For the decomposition experiments, two different methods were employed to dissociate the hydrate: thermal stimulation and depressurization. It was found that more than 74.0% of water conversion to hydrates was achieved in all hydrate formation experiments at 4.0°C and 1.0°C starting with a pressure of 8.0MPa. The dissociation of hydrate was found to occur in two stages when thermal stimulation was employed whereas three stages were found during depressurization. In both cases, the first stage was strongly affected by the changing bed size whereas it was not found to depend on the bed size afterwards.

In this paper, we study primary decomposition of any proper submodule N of a module M over a noetherian ring R. We start by briefly discussing basic facts about the very well known case where M is a finitely generated module over a Noetherian ring R, then we proceed to discuss the general case where M is any module over a Noetherian ring R. We put a lot of focus on the associated primes that occur with the primary decomposition, essentially studying their uniqueness and their relation to the associated primes of M/N.

The sulphation and sulphate decomposition occurring during the oxidation of nickel concentrates were studied by thermal analysis. Samples of industrial nickel concentrates were heated in inert gas to temperatures between 400°C and 850°C and oxidized isothermally in air or in a 4%O2-96%N2 mixture. During isothermal oxidation of the concentrates, SO2 evolved from the roasting reactions led to partial formation of metal sulphates. Following the oxidation and sulphation of the sample, the decomposition of the formed sulphates was studied. This was completed either by heating the sulphated sample to 950°C to thermally decompose the sulphates, or by lowering the partial pressure of oxygen while holding the sample at the isothermal oxidation temperature. The sulphation of the sample was found to follow the parabolic rate law, implying diffusion as the rate controlling-step. The thermal decomposition of the sulphates occurred at a near constant rate, implying zero-order kinetics.

The sulphation and sulphate decomposition occurring during the oxidation of nickel concentrates were studied by thermal analysis. Samples of industrial nickel concentrates were heated in inert gas to temperatures between 400°C and 850°C and oxidized isothermally in air or in a 4%O2-96%N2 mixture. During isothermal oxidation of the concentrates, SO2 evolved from the roasting reactions led to partial formation of metal sulphates. Following the oxidation and sulphation of the sample, the decomposition of the formed sulphates was studied. This was completed either by heating the sulphated sample to 950°C to thermally decompose the sulphates, or by lowering the partial pressure of oxygen while holding the sample at the isothermal oxidation temperature. The sulphation of the sample was found to follow the parabolic rate law, implying diffusion as the rate controlling-step. The thermal decomposition of the sulphates occurred at a near constant rate, implying zero-order kinetics.

This thesis investigates the use of symbiosis as an evolutionary metaphor for problem decomposition using Genetic Programming. It begins by drawing a connection between lateral problem decomposition, in which peers with similar capabilities coordinate their actions, and vertical problem decomposition, whereby solution subcomponents are organized into increasingly complex units of organization. Furthermore, the two types of problem decomposition are associated respectively with context learning and layered learning. The thesis then proposes the Symbiotic Bid-Based framework modeled after a three-staged process of symbiosis abstracted from biological evolution. As such, it is argued, the approach has the capacity for both types of problem decomposition. Three principles capture the essence of the proposed framework. First, a bid-based approach to context learning is used to separate the issues of `what to do' and `when to do it'. Whereas the former issue refers to the problem-specific actions, e.g., class label predictions, the latter refers to a bidding behaviour that identifies a set of problem conditions. In this work, Genetic Programming is used to evolve the bids casting the method in a non-traditional role as programs no longer represent complete solutions. Second, the proposed framework relies on symbiosis as the primary mechanism of inheritance driving evolution, where this is in contrast to the crossover operator often encountered in Evolutionary Computation. Under this evolutionary metaphor, a set of symbionts, each representing a solution subcomponent in terms of a bid-action pair, is compartmentalized inside a host. Communication between symbionts is realized through their collective bidding behaviour, thus, their cooperation is directly supported by the bid-based approach to context learning. Third, assuming that challenging tasks where problem decomposition is likely to play a key role will often involve large state spaces, the proposed framework includes a dynamic evaluation function that explicitly models the interaction between candidate solutions and training cases. As such, the computational overhead incurred during training under the proposed framework does not depend on the size of the problem state space. An approach to model building, the Symbiotic Bid-Based framework is first evaluated on a set of real-world classification problems which include problems with multi-class labels, unbalanced distributions, and large attribute counts. The evaluation includes a comparison against Support Vector Machines and AdaBoost. Under temporal sequence learning, the proposed framework is evaluated on the truck reversal and Rubik's Cube tasks, and in the former case, it is compared with the Neuroevolution of Augmenting Topologies algorithm. Under both problems, it is demonstrated that the increased capacity for problem decomposition under the proposed approach results in improved performance, with solutions employing vertical problem decomposition under temporal sequence learning proving to be especially effective.