Impact of development of job control and task-related stressors on resigned job attitude.

With more experience in the labor market, some job characteristics increase, some decrease. For example, among young employees who just entered the labor market, job control may initially be low but increase with more routine and experience. Job control is a job resource that is valued in itself and is positively associated with job satisfaction; but job control also helps dealing with stressors at work. There is little research on correlated changes, but the existing evidence suggests a joint development over time. However, even less is known about the relevance of such changes for employees. Usually, research tends to use mean levels to predict mean levels in outcomes but development in job control and stressors may be as relevant for job satisfaction as having a certain level in those job characteristics. Job satisfaction typically is regarded as a positive attitude towards one’s work. What has received less attention is that some employees may lower their expectations if their job situation does not reflect their needs, resulting in a resigned attitude towards one’s job. The present study investigates the development of job control and task-related stressors over ten years and tests the predictive value of changes in job control and task-related stressors for resigned attitude towards one’s job. We used data from a Swiss panel study (N=356) ranging over ten years. Job control, task-related stressors (an index consisting of time pressure, concentration demands, performance constraints, interruptions, and uncertainty about tasks), and resigned attitude towards one’s job were assessed in 1998, 1999, 2001, and 2008. Latent growth modeling revealed that growth rates of job control and task-related stressors were not correlated with one another. We predicted resigned attitude towards one’s job in 2008 a) by initial levels, and b) by changes in job control and stressors, controlling for resigned attitude in 1998. There was some prediction by initial levels (job control: β = -.15, p < .05; task-related stressors: β = .12, p = .06). However, as expected, changes in control and stressors predicted resigned attitude much better, with β = -.37, p < .001, for changes in job control, and β = .31, p < .001, for changes in task-related stressors. Our data confirm the importance of having low levels of task-related stressors and higher levels of job control for job attitudes. However, development in these job characteristics seems even more important than initial levels.

The impact of the position effect on the factorial structure of the Culture Fair Test (CFT)

The Culture Fair Test (CFT) is a psychometric test of fluid intelligence consisting of four subtests; Series, Classification, Matrices, and Topographies. The four subtests are only moderately intercorrelated, doubting the notion that they assess the same construct (i.e., fluid intelligence). As an explanation of these low correlations, we investigated the position effect. This effect is assumed to reflect implicit learning during testing. By applying fixed-links modeling to analyze the CFT data of 206 participants, we identified position effects as latent variables in the subtests; Classification, Matrices, and Topographies. These position effects were disentangled from a second set of latent variables representing fluid intelligence inherent in the four subtests. After this separation of position effect and basic fluid intelligence, the latent variables representing basic fluid intelligence in the subtests Series, Matrices, and Topographies could be combined to one common latent variable which was highly correlated with fluid intelligence derived from the subtest Classification (r=.72). Correlations between the three latent variables representing the position effects in the Classification, Matrices, and Topographies subtests ranged from r=.38 to r=.59. The results indicate that all four CFT subtests measure the same construct (i.e., fluid intelligence) but that the position effect confounds the factorial structure

The Impact of Thermal Coupling on Catalyst Behavior in Wall-Coated Heat-Exchanger Microreactors

This thesis presents a numerical study of reaction and diffusion phenomena in wall-coated heat-exchanger microreactors. Specifically, the interactions between an endothermic and exothermic catalyst layer separated by an impermeable wall is studied to understand the inherent behavior of the system. Two modeling approaches are presented, the first under the assumption of a constant thermal gradient and neglecting heat of reaction and the second considering both catalyst layers and reaction heat. Both studies found that thicker, more thermally insulating catalyst layers increase the effectiveness of the exothermic reaction by allowing for accumulation of reaction heat while thinner catalyst layers for the endothermic catalyst allow for direct access of the reactant to higher wall temperatures.

Impact of a modified dietary plan on the health related quality of life of minority participants in the Women's Healthy Eating and Living (WHEL) Study

Advances in medical technology, in genetics, and in clinical research have led to early detection of cancer, precise diagnosis, and effective treatment modalities. Decline in cancer incidence and mortality due to cancer has led to increased number of long-term survivors. However, the ethnic minority population has not experienced this decline and still continues to carry a disparate proportion of the cancer burden. Majority of the clinical research including survivorship studies have recruited and continue to recruit a convenient sample of middle- to upper-class Caucasian survivors. Thus, minorities are underrepresented in cancer research in terms of both clinical studies and in health related quality of life (HRQOL) studies. ^ Life style and diet have been associated with increased risk of breast cancer. High vegetable low fat diet has been shown to reduce recurrence of breast cancer and early death. The Women's Healthy Eating and Living Study is an ongoing multi-site randomized controlled trial that is evaluating the high-vegetable low fat diet in reducing the recurrence of breast cancer and early death. The purpose of this dissertation was to (1) compare the impact of the modified diet on the HRQOL during the first 12-month period on specific Minorities and matched Caucasians; (2) identify predictors that significantly impact the HRQOL of the study participants; and (3) using the structural equation modeling assess the impact of nutrition on the HRQOL of the intervention group participants. Findings suggest that there are no significant differences in change in HRQOL between Minorities and Caucasians; between Minorities in the intervention group and those in the comparison group; and between women in the intervention group and those in the comparison group. Minority indicator variable and Intervention/Comparison group indicator variable were not found to be good predictors of HRQOL. Although the structural equation models suggested viable representation of the relationship between the antecedent variables, the mediating variables and the two outcome variables, the impact of nutrition was not statistically significant to be included in the model. This dissertation, by analyzing the HRQOL of minorities in the WHEL Study, attempted to add to the knowledge base specific to minority cancer survivors. ^

Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

The Texas driver responsibility program: A preliminary analysis of the impact on impaired driving and trauma system funding

Objective. In 2003, the State of Texas instituted the Driver Responsibility Program (TDRP), a program consisting of a driving infraction point system coupled with a series of graded fines and annual surcharges for specific traffic violations such as driving while intoxicated (DWI). Approximately half of the revenues generated are earmarked to be disbursed to the state's trauma system to cover uncompensated trauma care costs. This study examined initial program implementation, the impact of trauma system funding, and initial impact on impaired driving knowledge, attitudes and behaviors. A model for targeted media campaigns to improve the program's deterrence effects was developed. ^ Methods. Data from two independent driver survey samples (conducted in 1999 and 2005), department of public safety records, state health department data and a state auditor's report were used to evaluate the program's initial implementation, impact and outcome with respect to drivers' impaired driving knowledge, attitudes and behavior (based on constructs of social cognitive theory) and hospital uncompensated trauma care funding. Survey results were used to develop a regression model of high risk drivers who should be targeted to improve program outcome with respect to deterring impaired driving. ^ Results. Low driver compliance with fee payment (28%) and program implementation problems were associated with lower surcharge revenues in the first two years ($59.5 million versus $525 million predicted). Program revenue distribution to trauma hospitals was associated with a 16% increase in designated trauma centers. Survey data demonstrated that only 28% of drivers are aware of the TDRP and that there has been no initial impact on impaired driving behavior. Logistical regression modeling suggested that target media campaigns highlighting the likelihood of DWI detection by law enforcement and the increased surcharges associated with the TDRP are required to deter impaired driving. ^ Conclusions. Although the TDRP raised nearly $60 million in surcharge revenue for the Texas trauma system over the first two years, this study did not find evidence of a change in impaired driving knowledge, attitudes or behaviors from 1999 to 2005. Further research is required to measure whether the program is associated with decreased alcohol-related traffic fatalities. ^

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

The impact of host immunity on oscillating rates of syphilis when gender and race are considered

The rates of syphilis in the United States have increased since the all time low in 2000. In 2003, the rates of syphilis in the United States were 2.5 cases per 100,000. There were 178 reported cases of primary and secondary syphilis (8.9 cases per 100,000) in Houston, Texas, which was a 58.9% increase from 2002. While syphilis can be completely treated now, unlike in times past, it is still a public health concern. The purpose of this study is to examine the possibility of modeling the impact of an immune response in primary and secondary syphilis in 63 major cities across the United States, stratified by gender and racial-ethnic groups. A Fourier analysis will be performed by SAS. Subsequently, this study will compare the results to a similar study of syphilis in 68 US cities, that focused on immune response, however, did not stratified by race and gender. This study will help determine if the oscillating rates of syphilis are due to biological factors of the disease or to behavioral changes in the population. This study will use surveillance data from 63 major cities across the United States. The data will be provided by the Centers of Disease Control. Ultimately, this study will expand the knowledge of the effect of immunity on endemics.^

Modeling the sensitivity of precipitation oxygen isotopes to the Last Glacial Maximum boundary conditions: A study using Community Atmosphere Model (CAM3.0)

To understand the validity of d18O proxy records as indicators of past temperature change, a series of experiments was conducted using an atmospheric general circulation model fitted with water isotope tracers (Community Atmosphere Model version 3.0, IsoCAM). A pre-industrial simulation was performed as the control experiment, as well as a simulation with all the boundary conditions set to Last Glacial Maximum (LGM) values. Results from the pre-industrial and LGM simulations were compared to experiments in which the influence of individual boundary conditions (greenhouse gases, ice sheet albedo and topography, sea surface temperature (SST), and orbital parameters) were changed each at a time to assess their individual impact. The experiments were designed in order to analyze the spatial variations of the oxygen isotopic composition of precipitation (d18Oprecip) in response to individual climate factors. The change in topography (due to the change in land ice cover) played a significant role in reducing the surface temperature and d18Oprecip over North America. Exposed shelf areas and the ice sheet albedo reduced the Northern Hemisphere surface temperature and d18Oprecip further. A global mean cooling of 4.1 °C was simulated with combined LGM boundary conditions compared to the control simulation, which was in agreement with previous experiments using the fully coupled Community Climate System Model (CCSM3). Large reductions in d18Oprecip over the LGM ice sheets were strongly linked to the temperature decrease over them. The SST and ice sheet topography changes were responsible for most of the changes in the climate and hence the d18Oprecip distribution among the simulations.

Collisional Formation and Modeling of Asteroid Families

In the last decade, thanks to the development of sophisticated numerical codes, major breakthroughs have been achieved in our understanding of the formation of asteroid families by catastrophic disruption of large parent bodies. In this review, we describe numerical simulations of asteroid collisions that reproduced the main properties of families, accounting for both the fragmentation of an asteroid at the time of impact and the subsequent gravitational interactions of the generated fragments. The simulations demonstrate that the catastrophic disruption of bodies larger than a few hundred meters in diameter leads to the formation of large aggregates due to gravitational reaccumulation of smaller fragments, which helps explain the presence of large members within asteroid families. Thus, for the first time, numerical simulations successfully reproduced the sizes and ejection velocities of members of representative families. Moreover, the simulations provide constraints on the family dynamical histories and on the possible internal structure of family members and their parent bodies.

The emission reduction effect and economic impact of an energy tax vs. a carbon tax in China : a dynamic CGE model analysis

Chinese government commits to reach its peak carbon emissions before 2030, which requires China to implement new policies. Using a CGE model, this study conducts simulation studies on the functions of an energy tax and a carbon tax and analyzes their effects on macro-economic indices. The Chinese economy is affected at an acceptable level by the two taxes. GDP will lose less than 0.8% with a carbon tax of 100, 50, or 10 RMB/ton CO2 or 5% of the delivery price of an energy tax. Thus, the loss of real disposable personal income is smaller. Compared with implementing a single tax, a combined carbon and energy tax induces more emission reductions with relatively smaller economic costs. With these taxes, the domestic competitiveness of energy intensive industries is improved. Additionally, we found that the sooner such taxes are launched, the smaller the economic costs and the more significant the achieved emission reductions.

Modeling for the world crude oil and natural gas markets

Crude oil and natural gas have been essential energy sources and play a crucial role in the world economy. Changes in energy prices significantly impact economic growth. This study builds an econometric model to illustrate the substitute relation between crude oil and natural gas markets. Additionally, the determination of the oil and natural gas prices are endogenized, assuming imperfect competition to reflect a real market strategy. Our empirical results show that the overall performance of this system is acceptable, and the model can be applied to policy analysis for determining monetary or energy policy by introducing this model to the more comprehensive system.

Impact And Explosive Loads On Concrete Buildings Using Shell And Beam Type Elements

The threat of impact or explosive loads is regrettably a scenario to be taken into account in the design of lifeline or critical civilian buildings. These are often made of concrete and not specifically designed for military threats. Numerical simulation of such cases may be undertaken with the aid of state of the art explicit dynamic codes, however several difficult challenges are inherent to such models: the material modeling for the concrete anisotropic failure, consideration of reinforcement bars and important structural details, adequate modeling of pressure waves from explosions in complex geometries, and efficient solution to models of complete buildings which can realistically assess failure modes. In this work we employ LS-Dyna for calculation, with Lagrangian finite elements and explicit time integration. Reinforced concrete may be represented in a fairly accurate fashion with recent models such as CSCM model [1] and segregated rebars constrained within the continuum mesh. However, such models cannot be realistically employed for complete models of large buildings, due to limitations of time and computer resources. The use of structural beam and shell elements for this purpose would be the obvious solution, with much lower computational cost. However, this modeling requires careful calibration in order to reproduce adequately the highly nonlinear response of structural concrete members, including bending with and without compression, cracking or plastic crushing, plastic deformation of reinforcement, erosion of vanished elements etc. The main objective of this work is to provide a strategy for modeling such scenarios based on structural elements, using available material models for structural elements [2] and techniques to include the reinforcement in a realistic way. These models are calibrated against fully three-dimensional models and shown to be accurate enough. At the same time they provide the basis for realistic simulation of impact and explosion on full-scale buildings

Advances in the modeling, characterization and reliability of concentrator multijunction solar cells

Los sistemas de concentración fotovoltaica (CPV) parecen ser una de las vías más prometedoras para generar electricidad a gran escala a precios competitivos. La investigación actual se centra en aumentar la eficiencia y la concentración de los sistemas para abaratar costes. Al mismo tiempo se investiga sobre la fiabilidad de los diferentes componentes que integran un sistema de concentración, ya que para que los sistemas de concentración sean competitivos es necesario que tengan una fiabilidad al menos similar a los sistemas basados en células de silicio. En la presente tesis doctoral se ha llevado a cabo el estudio de aspectos avanzados de células solares multi-unión diseñadas para trabajar a concentraciones ultra-altas. Para ello, se ha desarrollado un modelo circuital tridimensional distribuido con el que simular el comportamiento de las células solares triple-unión bajo distintas condiciones de funcionamiento, así mismo se ha realizado una caracterización avanzada de este tipo de células para comprender mejor su modo de operación y así poder contribuir a mejorar su eficiencia. Finalmente, se han llevado a cabo ensayos de vida acelerados en células multiunión comerciales para conocer la fiabilidad de este tipo de células solares. Para la simulación de células solares triple-unión se ha desarrollado en la presente tesis doctoral un modelo circuital tridimensinal distribuido el cuál integra una descripción completa de la unión túnel. De este modo, con el modelo desarrollado, hemos podido simular perfiles de luz sobre la célula solar que hacen que la densidad de corriente fotogenerada sea mayor a la densidad de corriente pico de la unión túnel. El modelo desarrollado también contempla la distribución lateral de corriente en las capas semiconductoras que componen y rodean la unión túnel. Por tanto, se ha podido simular y analizar el efecto que tiene sobre el funcionamiento de la célula solar que los concentradores ópticos produzcan perfiles de luz desuniformes, tanto en nivel de irradiancia como en el contenido espectral de la luz (aberración cromática). Con el objetivo de determinar cuáles son los mecanismos de recombinación que están limitando el funcionamiento de cada subcélula que integra una triple-unión, y así intentar reducirlos, se ha llevado a cabo la caracterización eléctrica de células solares monouni ón idénticas a las subcelulas de una triple-unión. También se ha determinado la curva corriente-tensión en oscuridad de las subcélulas de GaInP y GaAs de una célula dobleunión mediante la utilización de un teorema de reciprocidad electro-óptico. Finalmente, se ha analizado el impacto de los diferentes mecanismos de recombinación en el funcionamiento de la célula solar triple-unión en concentración. Por último, para determinar la fiabilidad de este tipo de células, se ha llevado a cabo un ensayo de vida acelerada en temperatura en células solares triple-unión comerciales. En la presente tesis doctoral se describe el diseño del ensayo, el progreso del mismo y los datos obtenidos tras el análisis de los resultados preliminares. Abstract Concentrator photovoltaic systems (CPV) seem to be one of the most promising ways to generate electricity at competitive prices. Nowadays, the research is focused on increasing the efficiency and the concentration of the systems in order to reduce costs. At the same time, another important area of research is the study of the reliability of the different components which make up a CPV system. In fact, in order for a CPV to be cost-effective, it should have a warranty at least similar to that of the systems based on Si solar cells. In the present thesis, we will study in depth the behavior of multijunction solar cells under ultra-high concentration. With this purpose in mind, a three-dimensional circuital distributed model which is able to simulate the behavior of triple-junction solar cells under different working conditions has been developed. Also, an advanced characterization of these solar cells has been carried out in order to better understand their behavior and thus contribute to improving efficiency. Finally, accelerated life tests have been carried out on commercial lattice-matched triple-junction solar cells in order to determine their reliability. In order to simulate triple-junction solar cells, a 3D circuital distributed model which integrates a full description of the tunnel junction has been developed. We have analyzed the behavior of the multijunction solar cell under light profiles which cause the current density photo-generated in the solar cell to be higher than the tunnel junction’s peak current density. The advanced model developed also takes into account the lateral current spreading through the semiconductor layers which constitute and surround the tunnel junction. Therefore, the effects of non-uniform light profiles, in both irradiance and the spectral content produced by the concentrators on the solar cell, have been simulated and analyzed. In order to determine which recombination mechanisms are limiting the behavior of each subcell in a triple-junction stack, and to try to reduce them when possible, an electrical characterization of single-junction solar cells that resemble the subcells in a triplejunction stack has been carried out. Also, the dark I-V curves of the GaInP and GaAs subcells in a dual-junction solar cell have been determined by using an electro-optical reciprocity theorem. Finally, the impact of the different recombination mechanisms on the behavior of the triple-junction solar cell under concentration has been analyzed. In order to determine the reliability of these solar cells, a temperature accelerated life test has been carried out on commercial triple-junction solar cells. In the present thesis, the design and the evolution of the test, as well as the data obtained from the analysis of the preliminary results, are presented.

Atmospheric modelling of tritium forms transport: review of capabilities and R&D needs for the assessment of fusion facilities environmental impact

One of the key scrutiny issues of new coming energy era would be the environmental impact of fusion facilities managing one kg of tritium. The potential change of committed dose regulatory limits together with the implementation of nuclear design principles (As Low as Reasonably achievable - ALARA -, Defense in Depth -D-i-D-) for fusion facilities could strongly impact on the cost of deployment of coming fusion technology. Accurate modeling of environmental tritium transport forms (HT, HTO) for the assessment of fusion facility dosimetric impact in Accidental case appears as of major interest. This paper considers different short-term releases of tritium forms (HT and HTO) to the atmosphere from a potential fusion reactor located in the Mediterranean Basin. This work models in detail the dispersion of tritium forms and dosimetric impact of selected environmental patterns both inland and in-sea using real topography and forecast meteorological data-fields (ECMWF/FLEXPART). We explore specific values of this ratio in different levels and we examine the influence of meteorological conditions in the HTO behavior for 24 hours. For this purpose we have used a tool which consists on a coupled Lagrangian ECMWF/FLEXPART model useful to follow real time releases of tritium at 10, 30 and 60 meters together with hourly observations of wind (and in some cases precipitations) to provide a short-range approximation of tritium cloud behavior. We have assessed inhalation doses. And also HTO/HT ratios in a representative set of cases during winter 2010 and spring 2011 for the 3 air levels.