Analysis of Synthetic Diamond Wafer Interferograms Using a Parallelized Simulated Annealing Algorithm

Diamonds are known for both their beauty and their durability. Jefferson National Lab in Newport News, VA has found a way to utilize the diamond's strength to view the beauty of the inside of the atomic nucleus with the hopes of finding exotic forms of matter. By firing very fast electrons at a diamond sheet no thicker than a human hair, high energy particles of light known as photons are produced with a high degree of polarization that can illuminate the constituents of the nucleus known as quarks. The University of Connecticut Nuclear Physics group has responsibility for crafting these extremely thin, high quality diamond wafers. These wafers must be cut from larger stones that are about the size of a human finger, and then carefully machined down to the final thickness. The thinning of these diamonds is extremely challenging, as the diamond's greatest strength also becomes its greatest weakness. The Connecticut Nuclear Physics group has developed a novel technique to assist industrial partners in assessing the quality of the final machining steps, using a technique based on laser interferometry. The images of the diamond surface produced by the interferometer encode the thickness and shape of the diamond surface in a complex way that requires detailed analysis to extract. We have developed a novel software application to analyze these images based on the method of simulated annealing. Being able to image the surface of these diamonds without requiring costly X-ray diffraction measurements allows rapid feedback to the industrial partners as they refine their thinning techniques. Thus, by utilizing a material found to be beautiful by many, the beauty of nature can be brought more clearly into view.

Genome-wide algorithm for detecting CNV associations with diseases

SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). The quality of the inferences about copy number can be affected by many factors including batch effects, DNA sample preparation, signal processing, and analytical approach. Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP genotyping data. However, these algorithms lack specificity to detect small CNVs due to the high false positive rate when calling CNVs based on the intensity values. Association tests based on detected CNVs therefore lack power even if the CNVs affecting disease risk are common. In this research, by combining an existing Hidden Markov Model (HMM) and the logistic regression model, a new genome-wide logistic regression algorithm was developed to detect CNV associations with diseases. We showed that the new algorithm is more sensitive and can be more powerful in detecting CNV associations with diseases than an existing popular algorithm, especially when the CNV association signal is weak and a limited number of SNPs are located in the CNV.^

EVALUATION OF THE EFFECTIVENESS OF ANISOTROPIC ANALYTICAL ALGORITHM IN FLATTENED AND FLATTENING-FILTER-FREE BEAMS FOR HIGH ENERGY LUNG DOSE DELIVERY USING THE RADIOLOGICAL PHYSICS CENTER LUNG PHANTOM

The effectiveness of the Anisotropic Analytical Algorithm (AAA) implemented in the Eclipse treatment planning system (TPS) was evaluated using theRadiologicalPhysicsCenteranthropomorphic lung phantom using both flattened and flattening-filter-free high energy beams. Radiation treatment plans were developed following the Radiation Therapy Oncology Group and theRadiologicalPhysicsCenterguidelines for lung treatment using Stereotactic Radiation Body Therapy. The tumor was covered such that at least 95% of Planning Target Volume (PTV) received 100% of the prescribed dose while ensuring that normal tissue constraints were followed as well. Calculated doses were exported from the Eclipse TPS and compared with the experimental data as measured using thermoluminescence detectors (TLD) and radiochromic films that were placed inside the phantom. The results demonstrate that the AAA superposition-convolution algorithm is able to calculate SBRT treatment plans with all clinically used photon beams in the range from 6 MV to 18 MV. The measured dose distribution showed a good agreement with the calculated distribution using clinically acceptable criteria of ±5% dose or 3mm distance to agreement. These results show that in a heterogeneous environment a 3D pencil beam superposition-convolution algorithms with Monte Carlo pre-calculated scatter kernels, such as AAA, are able to reliably calculate dose, accounting for increased lateral scattering due to the loss of electronic equilibrium in low density medium. The data for high energy plans (15 MV and 18 MV) showed very good tumor coverage in contrast to findings by other investigators for less sophisticated dose calculation algorithms, which demonstrated less than expected tumor doses and generally worse tumor coverage for high energy plans compared to 6MV plans. This demonstrates that the modern superposition-convolution AAA algorithm is a significant improvement over previous algorithms and is able to calculate doses accurately for SBRT treatment plans in the highly heterogeneous environment of the thorax for both lower (≤12 MV) and higher (greater than 12 MV) beam energies.

Pathway Semantics: An Algebraic Data Driven Algorithm to Generate Hypotheses about Molecular Patterns Underlying Disease Progression

The overarching goal of the Pathway Semantics Algorithm (PSA) is to improve the in silico identification of clinically useful hypotheses about molecular patterns in disease progression. By framing biomedical questions within a variety of matrix representations, PSA has the flexibility to analyze combined quantitative and qualitative data over a wide range of stratifications. The resulting hypothetical answers can then move to in vitro and in vivo verification, research assay optimization, clinical validation, and commercialization. Herein PSA is shown to generate novel hypotheses about the significant biological pathways in two disease domains: shock / trauma and hemophilia A, and validated experimentally in the latter. The PSA matrix algebra approach identified differential molecular patterns in biological networks over time and outcome that would not be easily found through direct assays, literature or database searches. In this dissertation, Chapter 1 provides a broad overview of the background and motivation for the study, followed by Chapter 2 with a literature review of relevant computational methods. Chapters 3 and 4 describe PSA for node and edge analysis respectively, and apply the method to disease progression in shock / trauma. Chapter 5 demonstrates the application of PSA to hemophilia A and the validation with experimental results. The work is summarized in Chapter 6, followed by extensive references and an Appendix with additional material.

Pencil -beam redefinition algorithm dose calculations for electron therapy treatment planning

The electron pencil-beam redefinition algorithm (PBRA) of Shiu and Hogstrom has been developed for use in radiotherapy treatment planning (RTP). Earlier studies of Boyd and Hogstrom showed that the PBRA lacked an adequate incident beam model, that PBRA might require improved electron physics, and that no data existed which allowed adequate assessment of the PBRA-calculated dose accuracy in a heterogeneous medium such as one presented by patient anatomy. The hypothesis of this research was that by addressing the above issues the PBRA-calculated dose would be accurate to within 4% or 2 mm in regions of high dose gradients. A secondary electron source was added to the PBRA to account for collimation-scattered electrons in the incident beam. Parameters of the dual-source model were determined from a minimal data set to allow ease of beam commissioning. Comparisons with measured data showed 3% or better dose accuracy in water within the field for cases where 4% accuracy was not previously achievable. A measured data set was developed that allowed an evaluation of PBRA in regions distal to localized heterogeneities. Geometries in the data set included irregular surfaces and high- and low-density internal heterogeneities. The data was estimated to have 1% precision and 2% agreement with accurate, benchmarked Monte Carlo (MC) code. PBRA electron transport was enhanced by modeling local pencil beam divergence. This required fundamental changes to the mathematics of electron transport (divPBRA). Evaluation of divPBRA with the measured data set showed marginal improvement in dose accuracy when compared to PBRA; however, 4% or 2mm accuracy was not achieved by either PBRA version for all data points. Finally, PBRA was evaluated clinically by comparing PBRA- and MC-calculated dose distributions using site-specific patient RTP data. Results show PBRA did not agree with MC to within 4% or 2mm in a small fraction (<3%) of the irradiated volume. Although the hypothesis of the research was shown to be false, the minor dose inaccuracies should have little or no impact on RTP decisions or patient outcome. Therefore, given ease of beam commissioning, documentation of accuracy, and calculational speed, the PBRA should be considered a practical tool for clinical use. ^

Zircons, isotope ratios and element analyses from tonalite and oxide gabbro of the mid-ocean ridge from ODP Hole 176-735B

A limiting factor in the accuracy and precision of U/Pb zircon dates is accurate correction for initial disequilibrium in the 238U and 235U decay chains. The longest-lived-and therefore most abundant-intermediate daughter product in the 235U isotopic decay chain is 231Pa (T1/2 = 32.71 ka), and the partitioning behavior of Pa in zircon is not well constrained. Here we report high-precision thermal ionization mass spectrometry (TIMS) U-Pb zircon data from two samples from Ocean Drilling Program (ODP) Hole 735B, which show evidence for incorporation of excess 231Pa during zircon crystallization. The most precise analyses from the two samples have consistent Th-corrected 206Pb/238U dates with weighted means of 11.9325 ± 0.0039 Ma (n = 9) and 11.920 ± 0.011 Ma (n = 4), but distinctly older 207Pb/235U dates that vary from 12.330 ± 0.048 Ma to 12.140 ± 0.044 Ma and 12.03 ± 0.24 to 12.40 ± 0.27 Ma, respectively. If the excess 207Pb is due to variable initial excess 231Pa, calculated initial (231Pa)/(235U) activity ratios for the two samples range from 5.6 ± 1.0 to 9.6 ± 1.1 and 3.5 ± 5.2 to 11.4 ± 5.8. The data from the more precisely dated sample yields estimated DPazircon/DUzircon from 2.2-3.8 and 5.6-9.6, assuming (231Pa)/(235U) of the melt equal to the global average of recently erupted mid-ocean ridge basaltic glasses or secular equilibrium, respectively. High precision ID-TIMS analyses from nine additional samples from Hole 735B and nearby Hole 1105A suggest similar partitioning. The lower range of DPazircon/DUzircon is consistent with ion microprobe measurements of 231Pa in zircons from Holocene and Pleistocene rhyolitic eruptions (Schmitt (2007; doi:10.2138/am.2007.2449) and Schmitt (2011; doi:10.1146/annurev-earth-040610-133330)). The data suggest that 231Pa is preferentially incorporated during zircon crystallization over a range of magmatic compositions, and excess initial 231Pa may be more common in zircons than acknowledged. The degree of initial disequilibrium in the 235U decay chain suggested by the data from this study, and other recent high precision datasets, leads to resolvable discordance in high precision dates of Cenozoic to Mesozoic zircons. Minor discordance in zircons of this age may therefore reflect initial excess 231Pa and does not require either inheritance or Pb loss.

(Table 1) Normalized difference vegetation index in control and warming plots, Abisco Research Station

Extreme winter warming events in the sub-Arctic have caused considerable vegetation damage due to rapid changes in temperature and loss of snow cover. The frequency of extreme weather is expected to increase due to climate change thereby increasing the potential for recurring vegetation damage in Arctic regions. Here we present data on vegetation recovery from one such natural event and multiple experimental simulations in the sub-Arctic using remote sensing, handheld passive proximal sensors and ground surveys. Normalized difference vegetation index (NDVI) recovered fast (2 years), from the 26% decline following one natural extreme winter warming event. Recovery was associated with declines in dead Empetrum nigrum (dominant dwarf shrub) from ground surveys. However, E. nigrum healthy leaf NDVI was also reduced (16%) following this winter warming event in experimental plots (both control and treatments), suggesting that non-obvious plant damage (i.e., physiological stress) had occurred in addition to the dead E. nigrum shoots that was considered responsible for the regional 26% NDVI decline. Plot and leaf level NDVI provided useful additional information that could not be obtained from vegetation surveys and regional remote sensing (MODIS) alone. The major damage of an extreme winter warming event appears to be relatively transitory. However, potential knock-on effects on higher trophic levels (e.g., rodents, reindeer, and bear) could be unpredictable and large. Repeated warming events year after year, which can be expected under winter climate warming, could result in damage that may take much longer to recover.

Magnetic susceptibility and electric conductivity of marine surficial sediments by benthic electromagnetic profiling

Distribution, accumulation and diagenesis of surficial sediments in coastal and continental shelf systems follow complex chains of localized processes and form deposits of great spatial variability. Given the environmental and economic relevance of ocean margins, there is growing need for innovative geophysical exploration methods to characterize seafloor sediments by more than acoustic properties. A newly conceptualized benthic profiling and data processing approach based on controlled source electromagnetic (CSEM) imaging permits to coevally quantify the magnetic susceptibility and the electric conductivity of shallow marine deposits. The two physical properties differ fundamentally insofar as magnetic susceptibility mostly assesses solid particle characteristics such as terrigenous or iron mineral content, redox state and contamination level, while electric conductivity primarily relates to the fluid-filled pore space and detects salinity, porosity and grain-size variations. We develop and validate a layered half-space inversion algorithm for submarine multifrequency CSEM with concentric sensor configuration. Guided by results of modeling, we modified a commercial land CSEM sensor for submarine application, which was mounted into a nonconductive and nonmagnetic bottom-towed sled. This benthic EM profiler Neridis II achieves 25 soundings/second at 3-4 knots over continuous profiles of up to hundred kilometers. Magnetic susceptibility is determined from the 75 Hz in-phase response (90% signal originates from the top 50 cm), while electric conductivity is derived from the 5 kHz out-of-phase (quadrature) component (90% signal from the top 92 cm). Exemplary survey data from the north-west Iberian margin underline the excellent sensitivity, functionality and robustness of the system in littoral (~0-50 m) and neritic (~50-300 m) environments. Susceptibility vs. porosity cross-plots successfully identify known lithofacies units and their transitions. All presently available data indicate an eminent potential of CSEM profiling for assessing the complex distribution of shallow marine surficial sediments and for revealing climatic, hydrodynamic, diagenetic and anthropogenic factors governing their formation.