Computational modelling of Er(3+): Garnet laser materials

The Er(3+) ion has attracted a lot of interest for four reasons: (1) Its (4)I(sub 13/2) yields (4)I(sub 15/2) transition lases in the eyesafe region near 1.5 micron; (2) the (4)I(sub 13/2) transition lases near 2.8 micron, an important wavelength for surgical purposes; (3) it displays surprisingly efficient upconversion with lasing observed at 1.7, 1.2, 0.85, 0.56, 0.55, and 0.47 micron following 1.5 micron pumping; and (4) it has absorption bands at 0.96 and 0.81 micron and thus can be diode pumped. However, properties desirable for upconversion reduce the efficiency of 1.5 and 3 micron laser operation and vice versa. Since all of the processes are influenced by the host via the crystal field induced stark splittings in the Er levels, this project undertook modelling of the host influence on the Er lasinng behavior. While growth and measurement of all ten Er(3+) doped garnets is the surest way of identifying hosts which maximize upconversion (or conversly, 1.5 and 3 micron performance), it is also expensive - costing approximately $10,000/material or approximately$100,000 for the materials computationally investigated here. The calculations were performed using a quantum mechanical point charge model developed by Clyde Morrison at Harry Diamond Laboratories. The programs were used to fit the Er:YAG experimental energy levels so that the crystal field parameters, B(sub nm) could be extracted. From these radial factors, rho (sub n) were determined for Er(3+) in garnets. These, in combination with crystal field components, Anm, available from X-ray data, were used to predict energy levels for Er in the other nine garnet hosts. The levels in Er:YAG were fit with an rms error of 12.2/cm over a 22,000/cm range. Predicted levels for two other garnets for which literature values were available had rms errors of less than 17/cm , showing the calculations to be reliable. Based on resonances between pairs of calculated stark levels, the model predicts GSGG as the best host for 1.5 micron laser operation, GSGG or YSAG as the best host for a 2.8 micron operation, and LuGG as the best host for an upconversion material

An exploratory aerodynamic and structural investigation of all-flexible parawings

Aerodynamic and structural aspects of all-flexible parawing

Advanced Opto-Electronics (LIDAR and Microsensor Development)

Our overall intent in this aspect of the project were to establish a collaborative effort between several departments at Montana State University for developing advanced optoelectronic technology for advancing the state-of-the-art in optical remote sensing of the environment. Our particular focus was on development of small systems that can eventually be used in a wide variety of applications that might include ground-, air-, and space deployments, possibly in sensor networks. Specific objectives were to: 1) Build a field-deployable direct-detection lidar system for use in measurements of clouds, aerosols, fish, and vegetation; 2) Develop a breadboard prototype water vapor differential absorption lidar (DIAL) system based on highly stable, tunable diode laser technology developed previously at MSU. We accomplished both primary objectives of this project, in developing a field-deployable direct-detection lidar and a breadboard prototype of a water vapor DIAL system. Paper summarizes each of these accomplishments

Constraints on coronal turbulence models from source sizes of noise storms at 327 MHz

We seek to reconcile observations of small source sizes in the solar corona at 327 MHz with predictions of scattering models that incorporate refractive index effects, inner scale effects and a spherically diverging wavefront. We use an empirical prescription for the turbulence amplitude $C_{N}^{2}(R)$ based on VLBI observations by Spangler and coworkers of compact radio sources against the solar wind for heliocentric distances $R \approx$ 10--50 $R_{\odot}$. We use the Coles & Harmon model for the inner scale $l_{i}(R)$, that is presumed to arise from cyclotron damping. In view of the prevalent uncertainty in the power law index that characterizes solar wind turbulence at various heliocentric distances, we retain this index as a free parameter. We find that the inclusion of spherical divergence effects suppresses the predicted source size substantially. We also find that inner scale effects significantly reduce the predicted source size. An important general finding for solar sources is that the calculations substantially underpredict the observed source size. Three possible, non-exclusive, interpretations of this general result are proposed. First and simplest, future observations with better angular resolution will detect much smaller sources. Consistent with this, previous observations of small sources in the corona at metric wavelengths are limited by the instrument resolution. Second, the spatially-varying level of turbulence $C_{N}^{2}(R)$ is much larger in the inner corona than predicted by straightforward extrapolation Sunwards of the empirical prescription, which was based on observations between 10--50 $R_{\odot}$. Either the functional form or the constant of proportionality could be different. Third, perhaps the inner scale is smaller than the model, leading to increased scattering.Comment: Accepted for publication in the Journal of Geophysical Research (Space Physics). Figures 5, 8 and 9 revised. Conclusions unchange

Assessing the tilt of the solar magnetic field axis through Faraday rotation observations

Context: Faraday rotation measurements of extragalactic radio sources during coronal occultation allow assessment of both the electron density distribution and the three-dimensional magnetic field topology in the outer solar corona. Aims: We simulate the three-dimensional structure of both the coronal magnetic field and the electron density distribution in order to reproduce the excess Faraday rotation measures (RMs) of the occulted radio sources observed during solar activity minimum. In particular, we infer the tilt of the solar magnetic axis with respect to the rotation axis. Methods: We compare the output of the model with Very Large Array (VLA) radio polarimetric measurements of a sample of extragalactic sources observed in May 1997. Information on the magnetic field geometry can be retrieved by fine-tuning the set of model free parameters that best describe the observations. Results: We find that predicted and observed Faraday rotation measures are in excellent agreement, thus supporting the model. Our best-fitting model yields a tilt angle $\theta_{RB}=3.3^{\circ}$ of the solar magnetic axis with respect to the solar rotation axis around Carrington Rotation 1923. This result is consistent with analogous but independent estimates computed from the expansion coefficients of the photospheric field observed at the Wilcox Solar Observatory (WSO).Comment: 8 pages, 5 figures, accepted for publication in A&

The impact of training strategies on the accuracy of genomic predictors in United States Red Angus cattle

Genomic selection (GS) has become an integral part of genetic evaluation methodology and has been applied to all major livestock species, including beef and dairy cattle, pigs, and chickens. Significant contributions in increased accuracy of selection decisions have been clearly illustrated in dairy cattle after practical application of GS. In the majority of U.S. beef cattle breeds, similar efforts have also been made to increase the accuracy of genetic merit estimates through the inclusion of genomic information into routine genetic evaluations using a variety of methods. However, prediction accuracies can vary relative to panel density, the number of folds used for folds cross-validation, and the choice of dependent variables (e.g., EBV, deregressed EBV, adjusted phenotypes). The aim of this study was to evaluate the accuracy of genomic predictors for Red Angus beef cattle with different strategies used in training and evaluation. The reference population consisted of 9,776 Red Angus animals whose genotypes were imputed to 2 medium-density panels consisting of over 50,000 (50K) and approximately 80,000 (80K) SNP. Using the imputed panels, we determined the influence of marker density, exclusion (deregressed EPD adjusting for parental information [DEPD-PA]) or inclusion (deregressed EPD without adjusting for parental information [DEPD]) of parental information in the deregressed EPD used as the dependent variable, and the number of clusters used to partition training animals (3, 5, or 10). A BayesC model with π set to 0.99 was used to predict molecular breeding values (MBV) for 13 traits for which EPD existed. The prediction accuracies were measured as genetic correlations between MBV and weighted deregressed EPD. The average accuracies across all traits were 0.540 and 0.552 when using the 50K and 80K SNP panels, respectively, and 0.538, 0.541, and 0.561 when using 3, 5, and 10 folds, respectively, for cross-validation. Using DEPD-PA as the response variable resulted in higher accuracies of MBV than those obtained by DEPD for growth and carcass traits. When DEPD were used as the response variable, accuracies were greater for threshold traits and those that are sex limited, likely due to the fact that these traits suffer from a lack of information content and excluding animals in training with only parental information substantially decreases the training population size. It is recommended that the contribution of parental average to deregressed EPD should be removed in the construction of genomic prediction equations. The difference in terms of prediction accuracies between the 2 SNP panels or the number of folds compared herein was negligible

Bull-half sib steer comparisons: phenotypic correlation and carcass prediction using ultrasound

Records from Angus bulls (n=257) and steers from Angus sires (n=212) over a four-year period were used in this analysis. The bulls and steers shared in common twenty Angus sires. All animals were serially scanned from weaning to slaughter for the following ultrasound traits: 12th-13th rib fat thickness (FTK), ribeye area (REA), rump fat thickness (RF), percentage intramuscular fat (PFAT), and weight at scanning (WT). Phenotypic correlation estimates between bull data adjusted to a year of age and steer data adjusted to average age at slaughter (390 days) were derived by the CORR procedure from SAS and were correlated by sire. Two sets of correlation estimates were derived, no age of dam adjustments in either sex and bull data adjusted using pooled estimates from the American Angus Association (AAA). The more notable estimates are as follows (AAA adjustments) .19, -.41, .19, .42, .40, -.43 for SREA (steer REA) and BREA (bull REA), SREA and BFTK, SFTK and BFTK, SPFAT and BFTK, SPFAT and BPFAT, SREA and BRF, respectively. Prediction models were derived using bull measures adjusted to a year of age and for age of dam (AAA) to explain steer marbling score (MS) and percent retail product (PRP). All explanatory and response variables were averaged by sire. The final prediction model for PRP explained 47.5% of the variation and included BFTK, BRF, BPFAT and the interaction between BFTK and BPFAT. The final prediction model for MS explained 34.2% of the variation and included BRF, BPFAT, the interaction between BRF and BFTK, and the interaction between BPFAT and BFTK

African American men with low-grade prostate cancer have increased disease recurrence after prostatectomy compared with Caucasian men.

PURPOSE: To explore whether disparities in outcomes exist between African American (AA) and Caucasian (CS) men with low-grade prostate cancer and similar cancer of the prostate risk assessment-postsurgery (CAPRA-S) features following prostatectomy (RP). METHODS: The overall cohort consisted of 1,265 men (234 AA and 1,031 CS) who met the National comprehensive cancer network criteria for low- to intermediate-risk prostate cancer and underwent RP between 1990 and 2012. We first evaluated whether clinical factors were associated with adverse pathologic outcomes and freedom from biochemical failure (FFbF) using the entire cohort. Next, we studied a subset of 705 men (112 AA and 593 CS) who had pathologic Gleason score≤6 (low-grade disease). Using this cohort, we determined whether race affected FFbF in men with RP-proven low-grade disease and similar CAPRA-S scores. RESULTS: With a median follow-up time of 27 months, the overall 7-year FFbF rate was 86% vs. 79% in CS and AA men, respectively (P = 0.035). There was no significant difference in one or more adverse pathologic features between CS vs. AA men (27% vs. 31%; P = 0.35) or CAPRA-S score (P = 0.28). In the subset analysis of patients with low-grade disease, AA race was associated with worse FFbF outcomes (P = 0.002). Furthermore, AA race was a significant predictor of FFbF in men with low-grade disease (hazard ratio = 2.01, 95% CI: 1.08-3.72; P = 0.029). CONCLUSIONS: AA race is a predictor of worse FFbF outcomes in men with low-grade disease after RP. These results suggest that a subset of AA men with low-grade disease may benefit from more aggressive treatment