EPA's Council for Regulatory Environmental Modeling : a case study of science policy implementation

As environmental problems became more complex, policy and regulatory decisions become far more difficult to make. The use of science has become an important practice in the decision making process of many federal agencies. Many different types of scientific information are used to make decisions within the EPA, with computer models becoming especially important. Environmental models are used throughout the EPA in a variety of contexts and their predictive capacity has become highly valued in decision making. The main focus of this research is to examine the EPA’s Council for Regulatory Modeling (CREM) as a case study in addressing science issues, particularly models, in government agencies. Specifically, the goal was to answer the following questions: What is the history of the CREM and how can this information shed light on the process of science policy implementation? What were the goals of implementing the CREM? Were these goals reached and how have they changed? What have been the impediments that the CREM has faced and why did these impediments occur? The three main sources of information for this research came from observations during summer employment with the CREM, document review and supplemental interviews with CREM participants and other members of the modeling community. Examining a history of modeling at the EPA, as well as a history of the CREM, provides insight into the many challenges that are faced when implementing science policy and science policy programs. After examining the many impediments that the CREM has faced in implementing modeling policies, it was clear that the impediments fall into two separate categories, classic and paradoxical. The classic impediments include the more standard impediments to science policy implementation that might be found in any regulatory environment, such as lack of resources and changes in administration. Paradoxical impediments are cyclical in nature, with no clear solution, such as balancing top-down versus bottom-up initiatives and coping with differing perceptions. These impediments, when not properly addressed, severely hinder the ability for organizations to successfully implement science policy.

IDENTIFICATION OF GENES CONTROLLING BIOLOGICAL PROCESSES AND PATHWAYS THROUGH STATISTICAL ANALYSIS AND NETWORK RECONSTRUCTION

The developmental processes and functions of an organism are controlled by the genes and the proteins that are derived from these genes. The identification of key genes and the reconstruction of gene networks can provide a model to help us understand the regulatory mechanisms for the initiation and progression of biological processes or functional abnormalities (e.g. diseases) in living organisms. In this dissertation, I have developed statistical methods to identify the genes and transcription factors (TFs) involved in biological processes, constructed their regulatory networks, and also evaluated some existing association methods to find robust methods for coexpression analyses. Two kinds of data sets were used for this work: genotype data and gene expression microarray data. On the basis of these data sets, this dissertation has two major parts, together forming six chapters. The first part deals with developing association methods for rare variants using genotype data (chapter 4 and 5). The second part deals with developing and/or evaluating statistical methods to identify genes and TFs involved in biological processes, and construction of their regulatory networks using gene expression data (chapter 2, 3, and 6). For the first part, I have developed two methods to find the groupwise association of rare variants with given diseases or traits. The first method is based on kernel machine learning and can be applied to both quantitative as well as qualitative traits. Simulation results showed that the proposed method has improved power over the existing weighted sum method (WS) in most settings. The second method uses multiple phenotypes to select a few top significant genes. It then finds the association of each gene with each phenotype while controlling the population stratification by adjusting the data for ancestry using principal components. This method was applied to GAW 17 data and was able to find several disease risk genes. For the second part, I have worked on three problems. First problem involved evaluation of eight gene association methods. A very comprehensive comparison of these methods with further analysis clearly demonstrates the distinct and common performance of these eight gene association methods. For the second problem, an algorithm named the bottom-up graphical Gaussian model was developed to identify the TFs that regulate pathway genes and reconstruct their hierarchical regulatory networks. This algorithm has produced very significant results and it is the first report to produce such hierarchical networks for these pathways. The third problem dealt with developing another algorithm called the top-down graphical Gaussian model that identifies the network governed by a specific TF. The network produced by the algorithm is proven to be of very high accuracy.

Open top chambers and infrared lamps : a comparison of heating efficacy and CO₂/CH₄ dynamics in a Lake Superior coastal peatland

Experimental warming provides a method to determine how an ecosystem will respond to increased temperatures. Northern peatland ecosystems, sensitive to changing climates, provide an excellent setting for experimental warming. Storing great quantities of carbon, northern peatlands play a critical role in regulating global temperatures. Two of the most common methods of experimental warming include open top chambers (OTCs) and infrared (IR) lamps. These warming systems have been used in many ecosystems throughout the world, yet their efficacy to create a warmer environment is variable and has not been widely studied. To date, there has not been a direct, experimentally controlled comparison of OTCs and IR lamps. As a result, a factorial study was implemented to compare the warming efficacy of OTCs and IR lamps and to examine the resulting carbon dioxide (CO2) and methane (CH4) flux rates in a Lake Superior peatland. IR lamps warmed the ecosystem on average by 1-2 #°C, with the majority of warming occurring during nighttime hours. OTC's did not provide any long-term warming above control plots, which is contrary to similar OTC studies at high latitudes. By investigating diurnal heating patterns and micrometeorological variables, we were able to conclude that OTCs were not achieving strong daytime heating peaks and were often cooler than control plots during nighttime hours. Temperate day-length, cloudy and humid conditions, and latent heat loss were factors that inhibited OTC warming. There were no changes in CO2 flux between warming treatments in lawn plots. Gross ecosystem production was significantly greater in IR lamp-hummock plots, while ecosystem respiration was not affected. CH4 flux was not significantly affected by warming treatment. Minimal daytime heating differences, high ambient temperatures, decay resistant substrate, as well as other factors suppressed significant gas flux responses from warming treatments.

A STUDY ON THE FEASIBILITY OF UNIVERSAL CHIP CONTROL IN MACHINING

A novel solution to the long standing issue of chip entanglement and breakage in metal cutting is presented in this dissertation. Through this work, an attempt is made to achieve universal chip control in machining by using chip guidance and subsequent breakage by backward bending (tensile loading of the chip's rough top surface) to effectively control long continuous chips into small segments. One big limitation of using chip breaker geometries in disposable carbide inserts is that the application range is limited to a narrow band depending on cutting conditions. Even within a recommended operating range, chip breakers do not function effectively as designed due to the inherent variations of the cutting process. Moreover, for a particular process, matching the chip breaker geometry with the right cutting conditions to achieve effective chip control is a very iterative process. The existence of a large variety of proprietary chip breaker designs further exacerbates the problem of easily implementing a robust and comprehensive chip control technique. To address the need for a robust and universal chip control technique, a new method is proposed in this work. By using a single tool top form geometry coupled with a tooling system for inducing chip breaking by backward bending, the proposed method achieves comprehensive chip control over a wide range of cutting conditions. A geometry based model is developed to predict a variable edge inclination angle that guides the chip flow to a predetermined target location. Chip kinematics for the new tool geometry is examined via photographic evidence from experimental cutting trials. Both qualitative and quantitative methods are used to characterize the chip kinematics. Results from the chip characterization studies indicate that the chip flow and final form show a remarkable consistency across multiple levels of workpiece and tool configurations as well as cutting conditions. A new tooling system is then designed to comprehensively break the chip by backward bending. Test results with the new tooling system prove that by utilizing the chip guidance and backward bending mechanism, long continuous chips can be more consistently broken into smaller segments that are generally deemed acceptable or good chips. It is found that the proposed tool can be applied effectively over a wider range of cutting conditions than present chip breakers thus taking possibly the first step towards achieving universal chip control in machining.