Analysis of soil carbon transit times and age distributions using network theories

The long-term soil carbon dynamics may be approximated by networks of linear compartments, permitting theoretical analysis of transit time (i.e., the total time spent by a molecule in the system) and age (the time elapsed since the molecule entered the system) distributions. We compute and compare these distributions for different network. configurations, ranging from the simple individual compartment, to series and parallel linear compartments, feedback systems, and models assuming a continuous distribution of decay constants. We also derive the transit time and age distributions of some complex, widely used soil carbon models (the compartmental models CENTURY and Rothamsted, and the continuous-quality Q-Model), and discuss them in the context of long-term carbon sequestration in soils. We show how complex models including feedback loops and slow compartments have distributions with heavier tails than simpler models. Power law tails emerge when using continuous-quality models, indicating long retention times for an important fraction of soil carbon. The responsiveness of the soil system to changes in decay constants due to altered climatic conditions or plant species composition is found to be stronger when all compartments respond equally to the environmental change, and when the slower compartments are more sensitive than the faster ones or lose more carbon through microbial respiration. Copyright 2009 by the American Geophysical Union.

Sequence and Structural Determinants of Specificity Differences between Paralogous Transcription Factors

Transcription factors (TFs) control the temporal and spatial expression of target genes by interacting with DNA in a sequence-specific manner. Recent advances in high throughput experiments that measure TF-DNA interactions in vitro and in vivo have facilitated the identification of DNA binding sites for thousands of TFs. However, it remains unclear how each individual TF achieves its specificity, especially in the case of paralogous TFs that recognize distinct target genomic sites despite sharing very similar DNA binding motifs. In my work, I used a combination of high throughput in vitro protein-DNA binding assays and machine-learning algorithms to characterize and model the binding specificity of 11 paralogous TFs from 4 distinct structural families. My work proves that even very closely related paralogous TFs, with indistinguishable DNA binding motifs, oftentimes exhibit differential binding specificity for their genomic target sites, especially for sites with moderate binding affinity. Importantly, the differences I identify in vitro and through computational modeling help explain, at least in part, the differential in vivo genomic targeting by paralogous TFs. Future work will focus on in vivo factors that might also be important for specificity differences between paralogous TFs, such as DNA methylation, interactions with protein cofactors, or the chromatin environment. In this larger context, my work emphasizes the importance of intrinsic DNA binding specificity in targeting of paralogous TFs to the genome.

Monte Carlo Analysis and Physics Characterization of a Novel Nanoparticle Detector for Medical and Micro-dosimetry Applications

The outcomes for both (i) radiation therapy and (ii) preclinical small animal radio- biology studies are dependent on the delivery of a known quantity of radiation to a specific and intentional location. Adverse effects can result from these procedures if the dose to the target is too high or low, and can also result from an incorrect spatial distribution in which nearby normal healthy tissue can be undesirably damaged by poor radiation delivery techniques. Thus, in mice and humans alike, the spatial dose distributions from radiation sources should be well characterized in terms of the absolute dose quantity, and with pin-point accuracy. When dealing with the steep spatial dose gradients consequential to either (i) high dose rate (HDR) brachytherapy or (ii) within the small organs and tissue inhomogeneities of mice, obtaining accurate and highly precise dose results can be very challenging, considering commercially available radiation detection tools, such as ion chambers, are often too large for in-vivo use.

In this dissertation two tools are developed and applied for both clinical and preclinical radiation measurement. The first tool is a novel radiation detector for acquiring physical measurements, fabricated from an inorganic nano-crystalline scintillator that has been fixed on an optical fiber terminus. This dosimeter allows for the measurement of point doses to sub-millimeter resolution, and has the ability to be placed in-vivo in humans and small animals. Real-time data is displayed to the user to provide instant quality assurance and dose-rate information. The second tool utilizes an open source Monte Carlo particle transport code, and was applied for small animal dosimetry studies to calculate organ doses and recommend new techniques of dose prescription in mice, as well as to characterize dose to the murine bone marrow compartment with micron-scale resolution.

Hardware design changes were implemented to reduce the overall fiber diameter to <0.9 mm for the nano-crystalline scintillator based fiber optic detector (NanoFOD) system. Lower limits of device sensitivity were found to be approximately 0.05 cGy/s. Herein, this detector was demonstrated to perform quality assurance of clinical 192Ir HDR brachytherapy procedures, providing comparable dose measurements as thermo-luminescent dosimeters and accuracy within 20% of the treatment planning software (TPS) for 27 treatments conducted, with an inter-quartile range ratio to the TPS dose value of (1.02-0.94=0.08). After removing contaminant signals (Cerenkov and diode background), calibration of the detector enabled accurate dose measurements for vaginal applicator brachytherapy procedures. For 192Ir use, energy response changed by a factor of 2.25 over the SDD values of 3 to 9 cm; however a cap made of 0.2 mm thickness silver reduced energy dependence to a factor of 1.25 over the same SDD range, but had the consequence of reducing overall sensitivity by 33%.

For preclinical measurements, dose accuracy of the NanoFOD was within 1.3% of MOSFET measured dose values in a cylindrical mouse phantom at 225 kV for x-ray irradiation at angles of 0, 90, 180, and 270˝. The NanoFOD exhibited small changes in angular sensitivity, with a coefficient of variation (COV) of 3.6% at 120 kV and 1% at 225 kV. When the NanoFOD was placed alongside a MOSFET in the liver of a sacrificed mouse and treatment was delivered at 225 kV with 0.3 mm Cu filter, the dose difference was only 1.09% with use of the 4x4 cm collimator, and -0.03% with no collimation. Additionally, the NanoFOD utilized a scintillator of 11 µm thickness to measure small x-ray fields for microbeam radiation therapy (MRT) applications, and achieved 2.7% dose accuracy of the microbeam peak in comparison to radiochromic film. Modest differences between the full-width at half maximum measured lateral dimension of the MRT system were observed between the NanoFOD (420 µm) and radiochromic film (320 µm), but these differences have been explained mostly as an artifact due to the geometry used and volumetric effects in the scintillator material. Characterization of the energy dependence for the yttrium-oxide based scintillator material was performed in the range of 40-320 kV (2 mm Al filtration), and the maximum device sensitivity was achieved at 100 kV. Tissue maximum ratio data measurements were carried out on a small animal x-ray irradiator system at 320 kV and demonstrated an average difference of 0.9% as compared to a MOSFET dosimeter in the range of 2.5 to 33 cm depth in tissue equivalent plastic blocks. Irradiation of the NanoFOD fiber and scintillator material on a 137Cs gamma irradiator to 1600 Gy did not produce any measurable change in light output, suggesting that the NanoFOD system may be re-used without the need for replacement or recalibration over its lifetime.

For small animal irradiator systems, researchers can deliver a given dose to a target organ by controlling exposure time. Currently, researchers calculate this exposure time by dividing the total dose that they wish to deliver by a single provided dose rate value. This method is independent of the target organ. Studies conducted here used Monte Carlo particle transport codes to justify a new method of dose prescription in mice, that considers organ specific doses. Monte Carlo simulations were performed in the Geant4 Application for Tomographic Emission (GATE) toolkit using a MOBY mouse whole-body phantom. The non-homogeneous phantom was comprised of 256x256x800 voxels of size 0.145x0.145x0.145 mm3. Differences of up to 20-30% in dose to soft-tissue target organs was demonstrated, and methods for alleviating these errors were suggested during whole body radiation of mice by utilizing organ specific and x-ray tube filter specific dose rates for all irradiations.

Monte Carlo analysis was used on 1 µm resolution CT images of a mouse femur and a mouse vertebra to calculate the dose gradients within the bone marrow (BM) compartment of mice based on different radiation beam qualities relevant to x-ray and isotope type irradiators. Results and findings indicated that soft x-ray beams (160 kV at 0.62 mm Cu HVL and 320 kV at 1 mm Cu HVL) lead to substantially higher dose to BM within close proximity to mineral bone (within about 60 µm) as compared to hard x-ray beams (320 kV at 4 mm Cu HVL) and isotope based gamma irradiators (137Cs). The average dose increases to the BM in the vertebra for these four aforementioned radiation beam qualities were found to be 31%, 17%, 8%, and 1%, respectively. Both in-vitro and in-vivo experimental studies confirmed these simulation results, demonstrating that the 320 kV, 1 mm Cu HVL beam caused statistically significant increased killing to the BM cells at 6 Gy dose levels in comparison to both the 320 kV, 4 mm Cu HVL and the 662 keV, 137Cs beams.

Institutional Persistence in Eastern Europe: Economic and Political Legacies of Empires and Communism

This dissertation seeks to advance our understanding of the roles that institutions play in economic development. How do institutions evolve? What mechanisms are responsible for their persistence? What effects do they have on economic development?

I address these questions using historical and contemporary data from Eastern Europe and Russia. This area is relatively understudied by development economists. It also has a very interesting history. For one thing, for several centuries it was divided between different empires. For another, it experienced wars and socialism in the 20th century. I use some of these exogenous shocks as quasi-natural social experiments to study the institutional transformations and its effects on economic development both in the short and long run.

This first chapter explores whether economic, social, and political institutions vary in their resistance to policies designed to remove them. The empirical context for the analysis is Romania from 1690 to the 2000s. Romania represents an excellent laboratory for studying the persistence of different types of historical institutional legacies. In the 18th and 19th centuries, Romania was split between the Habsburg and Ottoman Empires, where political and economic institutions differed. The Habsburgs imposed less extractive institutions relative to the Ottomans: stronger rule of law, a more stable and predictable state, a more developed civil society, and less corruption. In the 20th century, the Romanian Communist regime tried deliberately to homogenize the country along all relevant dimensions. It was only partially successful. Using a regression discontinuity design, I document the persistence of economic outcomes, social capital, and political attitudes. First, I document remarkable convergence in urbanization, education, unemployment, and income between the two former empires. Second, regarding social capital, no significant differences in organizational membership, trust in bureaucracy, and corruption persist today. Finally, even though the Communists tried to change all political attitudes, significant discontinuities exist in current voting behavior at the former Habsburg-Ottoman border. Using data from the parliamentary elections of 1996-2008, I find that former Habsburg rule decreases by around 6 percentage points the vote share of the major post-Communist left party and increases by around 2 and 5 percentage points the vote shares of the main anti-Communist and liberal parties, respectively.

The second chapter investigates the effects of Stalin’s mass deportations on distrust in central authority. Four deported ethnic groups were not rehabilitated after Stalin’s death; they remained in permanent exile until the disintegration of the Soviet Union. This allows one to distinguish between the effects of the groups that returned to their homelands and those of the groups that were not allowed to return. Using regional data from the 1991 referendum on the future of the Soviet Union, I find that deportations have a negative interim effect on trust in central authority in both the regions of destination and those of origin. The effect is stronger for ethnic groups that remained in permanent exile in the destination regions. Using data from the Life in Transition Survey, the chapter also documents a long-term effect of deportations in the destination regions.

The third chapter studies the short-term effect of Russian colonization of Central Asia on economic development. I use data on the regions of origin of Russian settlers and push factors to construct an instrument for Russian migration to Central Asia. This instrument allows me to interpret the outcomes causally. The main finding is that the massive influx of Russians into the region during the 1897-1926 period had a significant positive effect on indigenous literacy. The effect is stronger for men and in rural areas. Evidently, interactions between natives and Russians through the paid labor market was an important mechanism of human capital transmission in the context of colonization.

The findings of these chapters provide additional evidence that history and institutions do matter for economic development. Moreover, the dissertation also illuminates the relative persistence of institutions. In particular, political and social capital legacies of institutions might outlast economic legacies. I find that most economic differences between the former empires in Romania have disappeared. By the same token, there are significant discontinuities in political outcomes. People in former Habsburg Romania provide greater support for liberalization, privatization, and market economy, whereas voters in Ottoman Romania vote more for redistribution and government control over the economy.

In the former Soviet Union, Stalin’s deportations during World War II have a long-term negative effect on social capital. Today’s residents of the destination regions of deportations show significantly lower levels of trust in central authority. This is despite the fact that the Communist regime tried to eliminate any source of opposition and used propaganda to homogenize people’s political and social attitudes towards the authorities. In Central Asia, the influx of Russian settlers had a positive short-term effect on human capital of indigenous population by the 1920s, which also might have persisted over time.

From a development perspective, these findings stress the importance of institutions for future paths of development. Even if past institutional differences are not apparent for a certain period of time, as was the case with the former Communist countries, they can polarize society later on, hampering economic development in the long run. Different institutions in the past, which do not exist anymore, can thus contribute to current political instability and animosity.