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The objective of this study was to characterize genetic relationships between growth and carcass traits measured in commercial feedlot and purebred cattle that would aid in determining the effectiveness of combined crossbred and purebred selection (CCPS) strategies for sire selection. Data included 2,183 steers and 418 heifers enrolled in the Tri-County Steer Carcass Futurity (TC). Feedlot traits evaluated were initial body weight at time of delivery (IBW) and final BW at time of harvest (FBW) and carcass backfat thickness at the 12th rib (CFAT), marbling score at the 12th rib (CMAR) and ribeye area at the12th rib (CREA). Purebred data from the American Angus Association (AAA) included records of 139,602 bulls, 130,944 heifers and 6,656 steers for weaning weight (WW); 85,702 bulls, 76,603 heifers and 1,908 steers for yearling weight (YW); and 62,752 bulls and 45,958 heifers for ultrasound measures of backfat thickness at the 12th rib (UFAT), intramuscular fat percentage at the 12th rib (UMAR) and ribeye area at the 12th rib (UREA). The genetic correlations between IBW and WW, FBW and YW, CFAT and UFAT, CMAR and UMAR, and CREA and UREA were 0.01 ° 0.21, 0.43 ° 0.22, 0.66 ° 0.19, 0.65 ° 0.17, and 0.92 ° 0.12, respectively. Regressions of TC traits on corresponding sire EPD resulted in coefficients of 0.23 ° 0.19, 0.57 ° 0.16, 0.67 ° 0.19, 93.3 ° 12.3, and 1.08 ° 0.17 for IBW, FBW, CFAT, CMAR, and CREA, respectively. Three selection indices were evaluated on the basis of relative efficiency of genetic progress toward TC goal traits. The index including AAA records on an individual sire with TC records on his progeny was most effective, thus indicating the benefit of CCPS. / Master of Science

Breeding objectives were developed for Targhee sheep at different levels of prolificacy and triplet survival. Economic weights (EW) were derived for estimated breeding values (BV) from National Sheep Improvement Program genetic evaluations for 120 d weaning weight (WW), maternal milk (MM), yearling weight (YW), fleece weight (FW), fiber diameter (FD), staple length (SL), and prolificacy (PLC; lambs born/100 ewes lambing). A commercial flock was simulated, accounting for nonlinear relationships between performance and profit. Ewes were assumed mated to sires of specified BV and profit was derived from lifetime performance of lambs and replacement females from that lamb crop. Economic weights were determined as change in profit from use of sires with BV that were one additive standard deviation above the mean for each trait [1.98 kg for WW, 1.62 kg for MM, 2.90 kg for YW, 0..36 kg for FW, 0.99 microns for FD, 0.74 cm for SL, and 17.58 lambs/100 ewes for LC], while holding all other BV at breed average. Separate breeding objectives were derived for different ways of meeting increased nutrient needs (P = purchase hay, R = rent pasture, and L= limited flock size) and for different market lamb values (D = discounting lamb value for heavy weights, ND = no discount for heavy lambs). Based on replicated simulations, relative EW did not vary with prolificacy or triplet survival (P > 0.15) but were affected by feed costs and lamb market values (P < 0.01). Selection indexes were derived within and across simulated scenarios, and correlation (r) among indexes of > 0.90 indicated that an index could be used across multiple scenarios with little loss of selection efficiency. Indexes derived within feed cost scenarios (P, R, and L) and lamb value scenarios (D, ND) were strongly intercorrelated (r > 0.97). Correlations among average indexes for feed cost scenarios (0.97 for R and P, 0.70 for R and L; 0.85 for P and L) indicated that two feed cost scenarios could be used depending on whether winter forage was limited (L) or not (NL). The correlation between average indexes for these two scenarios was 0.78. Indexes were presented for combinations of feed cost and lamb value scenarios. Two indexes were suggested, representing the scenarios that apply to a large portion of Targhee producers. These indexes were for discounting heavy lambs with limited winter forage (D-L: 1.0 WW + 0.14 MM __ 0.76 YW + 1.22 FW __ 0.36 FD - 0.09 SL + 0.25 LC) and discounting heavy lambs with additional available forage (D-NL: 1.0 WW + 0.24 MM __ 0.34 YW + 1.65 FW __ 0.41 FD - 0.14 SL + 0.33 LC). For a standardized selection differential of one for the index, the expected changes in mean index value were $2.17 and $1.92 per ewe per generation for D-L and D-NL, respectively. / Master of Science

Attrition, employee turnover, self-selection, and withdrawal all refer to an employee’s exit from an organization, or from an organization’s recruitment or selection process. When individuals with the desired knowledge, skills, abilities, and other qualities (KSAOs) attrit, it represents lost productivity to an organization (Barrick & Zimmerman, 2009). Therefore, organizations should seek a selection program that screens out unwanted characteristics while minimizing the voluntary withdrawal, or quitting, of those who would be a good organizational fit. A military selection context amplifies these two aims because of the limited number of qualified individuals relative to the organization’s personnel needs, and because of the high potential cost of a bad hire. However, there are few studies of attrition during a selection process, and even fewer in a military context that combines physical, cognitive, and personality components as relevant performance dimensions. The purpose of the study was to model attrition from a military special operations selection through training program to determine what combination of physical abilities, cognitive abilities, and personality scales best predicts success. The study examined archival data from 748 candidate records spanning eight different classes during 2019. Secondary purposes of the study included comparing differences in attrition from the first week of the program to the remaining seven weeks, and comparing the predictive validity of a personality trait profile model to a model using personality scales T-scores. In conducting the analysis and modeling, exploratory factor analysis was conducted on the sample Jackson Personality Inventory-Revised (JPI-R) personality scales, finding both similarities and differences with previous study samples (Detwiler & Ramanaiah, 1996; Paunonen & Jackson, 1996). The result of the study was a logit prediction model with a ROC AUC of .784, and an F1 score of .69, that incorporated three physical predictors, performance IQ, and three personality variables: JPI-R T-score for sociability, and two composites created from the factor analysis—a Conscientiousness Composite and an Openness Composite (negative relationship with candidate success). Models for week 1 attrition and attrition from weeks 2-8 differed from the 8-week attrition model, and from each other in the significance and the importance of the personality variables and of cognitive abilities. Physical predictors: run score, pushups score, and sit-ups score, were significant and strong predictors of success for each of the time periods. Verbal IQ was not significant for any time period, while performance IQ was significant in predicting 8-week success, and for success during the week 2-8 time period. Personality predictors varied the most by timeframe, although some component of Conscientiousness predicted strongly for each timeframe. Whereas Openness-related facets predicted for 8-week success and success from week 1 with a negative relationship, Openness factors were non-significant in weeks 2-8. In contrast, Anxiety, a related sub-facet of Neuroticism, predicted moderately (negative relationship) for success from weeks 2-8, but was non-significant for week 1 and for the 8-week program. Unexpected findings included the sample’s different factor structure on the JPI-R, the dominance of the physical predictors in all models, and the strength of personality predictors relative to cognitive abilities. Implications for military and similar types of selection contexts, where selection through training includes a significant physical component, are discussed. / M.S. / The study analyzed attrition from a military special operations selection program to determine what combination of individual differences measured before the program best predicted attrition during the program. The individual differences measured prior to the program were physical abilities, cognitive abilities, and personality. Archival data from 748 candidate records spanning eight different classes during 2019 was analyzed. Attrition is the departure of an individual from an organization, or from a hiring process. This study dealt with attrition from a hiring, or personnel selection process, which is less commonly studied than attrition from within an organization. Secondary purposes of the study included how attrition from the first week of the program differed from the remaining seven weeks, and determining if a specific broad personality profile best predicted attrition. The study found additional results that were not anticipated, specifically, that the military sample differed meaningfully on important dimensions of the Jackson Personality Inventory-Revised (JPI-R) personality scales, in comparison with previous study samples (Detwiler & Ramanaiah, 1996; Paunonen & Jackson, 1996). The practical result of the study was a mathematical prediction model that incorporated a candidate’s scores on pushups, sit-ups, 2-mile run, performance IQ, and three personality variables, and calculates a candidates’ probability of success. The three personality variables that predicted success were scores for sociability, and two composites—a Conscientiousness Composite and an Openness Composite. Mathematical models for week 1 attrition and attrition from weeks 2-8 differed from the 8-week attrition model, and from each other, suggesting that attrition during different timeframes is due to different reasons. Physical predictors: 2 mile run score, pushups score, and sit-ups score, were strong predictors of success for each of the time periods. Verbal IQ did not predict for any time period, while performance IQ predicted 8-week success, and success during the week 2-8 time period. Personality predictors varied the most by timeframe, although a component of Conscientiousness predicted strongly for each timeframe. Openness-related personality facets predicted for 8-week success and success from week 1 with a negative relationship. In contrast, Anxiety, a related sub-facet of Neuroticism, predicted moderately (negative relationship) for success only from weeks 2-8. Unexpected findings included the military sample’s different factor structure on the JPI-R, the dominance of the physical predictors in all models, and the strength of personality predictors relative to cognitive abilities. Implications for military and similar types of selection contexts, where selection through training includes a significant physical component, such as police or firefighters, are discussed.

The recent addition of autonomous formation flying spacecraft to the world's satellite fleet provides new motivation to study feedback control techniques. In this thesis, we develop nonlinear orbit control laws for use in spacecraft orbital maneuvers, and spacecraft formation flying. We apply these new control laws to a number of sample maneuvers, including formation stablishment and formation keeping maneuvers for NASA-Goddard's Leonardo-BRDF formation, and coupled orbit, and attitude maneuvers for HokieSat, a spacecraft designed, and built by students at Virginia Tech to fly in the Ionospheric Observation Nanosatellite Formation (ION-F). To provide target orbit states for feedback control, we develop and apply an algorithm to calculate a formation master orbit representing the geometric center of the formation. We also define a new technique for choosing orbital element feedback gains which appropriately scales the gains for orbit maintenance, and provides an excellent starting point for gain optimization. The orbital element feedback control law, augmented by mean motion control, and applied with appropriate gains, forces asymptotic convergence to a spacecraft target orbit, for a large variety of spacecraft maneuvers. / Master of Science

In the presence of selection and mutation, the genealogy of a given sample configuration can be described by two classes of ancestral processes, namely the coalescent-in-a-random-background model of Kaplan et al. (1988) and the dual process with typed lines of Etheridge and Griffiths (2009). These two processes are based on the same forwards population genetics model. However, in the former model, selection is reflected in the ancestral frequencies in the population, while in the latter model, there are branching events that generate virtual ancestral lines. We simulate the dual processes with typed lines and derive the limits of the two ancestral processes under strong selection and under selection-mutation balance to address the question of to what extent the genealogy is distorted. The two ancestral processes generate the same limiting genealogy. In a two-allele population under strong selection, the disfavoured individuals in the sample are instantaneously converted to a random number of favoured individuals, and the limiting genealogy is governed by the usual Kingman’s coalescent. Under selection-mutation balance, all disfavoured individuals in the sample are instantaneously converted to the favoured type, and the limiting genealogy is determined by a time-changed Kingman’s coalescent. The proofs of these limiting processes are based on the convergence result of Mohle (1998, Lemma 1). The studies of selection-mutation balance are then extended to an additive selection model, where each individual is composed of L diallelic loci. In the corresponding dual process with typed lines, the evolution of the virtual lines on a faster timescale can be approximated by a deterministic process, while the evolution of the real lines is independent of the virtual lines. The structure in the limiting genealogy collapses to Kingman’s coalescent. We also let L tend to infinity, and obtain a full description of the limiting genealogy in the background selection model.

Lam Yuen Yan Sharon. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 65-71). / Abstracts in English and Chinese. / List of Tables --- p.vii / List of Figures --- p.viii / List of Appendices --- p.ix / Chapter Chapter 1: --- Introduction --- p.1 / Chapter Chapter 2: --- Method --- p.18 / Chapter Chapter 3: --- Results --- p.26 / Chapter Chapter 4: --- Discussion --- p.46 / References --- p.65