Public agricultural research has been conducted in Africa for decades and has generated numerous crop technologies, while little is understood on how agricultural research affects the poor and vulnerable groups such as children, and how farmers' perceptions affect their adoption decisions. This dissertation helps fill this gap with three essays on adoption and impacts of improved maize varieties in rural Ethiopia. The first essay estimates poverty impacts. Field-level treatment effects on yield and cost changes with adoption are estimated using instrumental variable techniques, with treatment effect heterogeneity fully accounted for in marginal treatment effect estimation. A backward derivation procedure is then developed within an economic surplus framework to identify the counterfactual income distribution without improved maize varieties. Poverty impacts are estimated by exploiting the differences between the observed and counterfactual income distributions. Improved maize varieties have led to 0.8-1.3 percentage drop in poverty headcount ratio and relative reductions in poverty depth and severity. However, poor producers benefit the least from adoption due to their small land holdings. The second paper assesses the impacts on child nutrition outcomes. The conceptual linkage between maize adoption and child nutrition is first established using an agricultural household model. Instrumental variable (IV) estimation suggests the overall impacts to be positive and significant. Quantile IV regressions further reveal that such impacts are largest among the most severely malnourished. By combining a decomposition procedure with estimates from a system of equations, it is found that the increase in own-produced maize consumption is the major channel such impacts occur. The third paper explores how farmers' perceptions of crop traits affects their willingness to adopt improved maize varieties. Under a random utility framework, a mixed logit procedure is implemented to model farmer's adoption intention, where perceptions of key varietal traits are first identified, and then instrumented using a control function approach to account for potential endogeneity. Perceived yield is found to be the most important trait affecting farmers' adoption intention. Further, yield perceptions among previous adopters appear to be affected by within-village peer effects rather than the real crop performance. / Ph. D.

New agricultural technologies can improve productivity to meet the increased demand for food that places pressure on agricultural production systems in developing countries. Because technological innovation is one of major factors shaping agriculture in both developing and developed countries, it is important to identify factors that help or that hinder the adoption process. Adoption analysis can assist policy makers in making informed decisions about dissemination of technologies that are under consideration. It is also important to estimate the impact of a technology. This dissertation contains three essays that estimate factors affecting integrated pest management (IPM) adoption and the impact of IPM on sweet gourd farming in Bangladesh. The first essay estimates factors that affect the timing of IPM adoption in Bangladesh. It employs duration models, fully parametric and semiparametric, and (i) compares results from different estimation methods to provide the best model for the data, and (ii) identifies factors that affect the length of time before Bangladeshi farmers adopt an agricultural technology. The paper provides two conclusions: 1) even though the non-parametric estimate of the hazard function indicated a non-monotone model such as log-normal or log-logistic, no differences are found in the sign and significance of the estimated coefficients between the non-monotone and monotone models. 2) economic factors do not directly influence the adoption decision but rather factors related to information diffusion and farmer's non-economic characteristics such as age and education. Particularly, farmer's age and education, membership in an association, training, distance of the farmer's house from local and town markets, and farmer's perception about the use of IPM affect the length of time to adoption. Farm size is the only variable closely related to economic factors that is found to be significant and it decreases the length of time to adoption. The second paper measures Bangladeshi farmers' attitudes toward risk and ambiguity using experimental data. In different sessions, the experiment allows farmers to make decisions alone and communicate with peers in groups of 3 and 6 to see how social exchanges among peers affect attitudes toward uncertainty. Combining the measured attributes to household survey data, the paper investigates the factors affecting those attributes as well as the role of risk aversion and ambiguity aversion in technology choice by farmers who: face uncertainty alone, in a group of 3, or in a group of 6. It finds that Bangladeshi farmers in the sample are mostly risk and ambiguity averse. Their risk and ambiguity aversion, moreover, differ when they face the uncertain prospects alone from when they can communicate with other peer farmers before making decisions. In addition, farmer's demographic characteristics affect both risk and ambiguity aversion. Finally, findings suggest that the roles of risk and ambiguity aversion in technology adoption depend on which measure of uncertainty behavior is incorporated in the adoption model. While risk aversion increases the likelihood of technology adoption when farmers face uncertainty alone, only ambiguity aversion matters and it reduces the likelihood of technology adoption when farmers face uncertainty in groups of three. Neither risk aversion nor ambiguity aversion matter when farmers face uncertainty in groups of six. The third paper presents an impact assessment of integrated pest management on sweet gourd in Bangladesh. It employs an instrumental variable and marginal treatment effects approach to estimate the impact of IPM on yield and cost of sweet gourd in Bangladesh. The estimation methods consider both homogeneous and heterogeneous treatment effects. The paper finds that IPM adoption has a 7% - 34% yield advantage over traditional pest management practices. Results regarding the effect of IPM adoption on cost are mixed. IPM adoption alters production costs from -1.2% cost to +42%, depending on the estimation method employed. However, most of the cost changes are not statistically significant. Therefore, while we confidently argue that the IPM adoption provides a yield advantage over non-adoption, we do not find a robust effect regarding a cost advantage of adoption. / Ph. D.

Pre-disaster damage predictions and post-disaster damage assessments are challenging because they result from complicated interactions between multiple drivers, including exposure to various hazards as well as differing levels of community resiliency. Certain societal characteristics, in particular, can greatly magnify the impact of a natural hazard, however they are frequently ignored in disaster management because they are difficult to incorporate into quantitative analyses. In order to more accurately identify areas of greatest need in the wake of a disaster, both the hazards and the vulnerabilities need to be carefully assessed since they have been shown to be positively correlated with damage patterns. This study evaluated the contribution of eight drivers of structural damage from Hurricane Mar'ia in Puerto Rico, leveraging machine learning algorithms to determine the role that societal factors played. Random Forest and Stochastic Gradient Boosting Trees algorithms analyzed a diverse set of data including wind, flooding, landslide, and vulnerability measures. These data trained models to predict the structural damage caused by Hurricane Mar'ia in Puerto Rico and the importance of each predictive feature was calculated. Results indicate that vulnerability measures are the leading predictors of damage in this case study, followed by wind, flood, and landslide measures. Each predictive variable exhibits unique, often nonlinear, relationships with damage. These results demonstrate that societal-driven vulnerabilities play critical roles in damage pattern analysis and that targeted, pre-disaster mitigation efforts should be enacted to reinforce household resiliency in socioeconomically vulnerable areas. Recovery programs may need to be reworked to focus on the highly impacted vulnerable populations to avoid the persistence, or potential enhancement, of preexisting social inequalities in the wake of a disaster. / Master of Science / Disasters are not entirely natural phenomena. Rather, they occur when natural hazards interact with the man-made environment and negatively impact society. Most risk and impact assessment studies focus on natural hazards (processes beyond human control) and do not incorporate the role of societal circumstances (within human agency). However, it has been shown that certain socioeconomic, demographic, and structural characteristics increase the severity of disaster impacts. These characteristics define the the susceptibility of a community to negative disaster impacts, known as vulnerability. This study quantifies the role of vulnerability via a case study of Hurricane Mar'ia. A variety of statistical modeling, known as machine learning, analyzed flood, wind, and landslide hazards along with the aforementioned vulnerabilities. These variables were correlated with a damage assessment database and the model calculated the strength of each variable's relationship with damage. Results indicate that vulnerability measures exhibit the strongest predictive correlations with the damage caused by Hurricane Mar'ia, followed by wind, flood, and landslide measures, respectively, suggesting that efforts to improve societal equality and improvements to infrastructure in vulnerable areas can mitigate the impacts of future hazardous events. In addition, societal information is critical to include in future risk and impact assessment efforts in order to prioritize areas of greatest need and allocate resources to those who would benefit from them most.

Impact tests are performed on two circular circumferential frame segments using a drop tower apparatus. These frames have a nominal radius of 120 inches, a forty-eight - degree included angle, a thin-walled cross section in the shape of the letter J, and are typical of the transverse fuselage frames found in a large transport aircraft. The material is a 2D triaxial braided composite of carbon fiber yarns. Impact speeds of the 91.6 lb drop mass are 23.7 ft/s or less. This speed range is the order of the vertical speed considered in a survivable crash on a runway. Transient response characteristics and failure sequence are compared to nominally identical frames tested quasi-statically in a previous study. The peak load at the first major failure event and the corresponding displacement are larger in impact tests than in the quasi-static tests. However, the fracture sequence in the vicinity of the impact location is similar to what was observed in the static tests. Preliminary transient simulations of the frame impact tests using the LSDyna software were also performed. Using the available composite material failure criteria in the software, reasonable correlation was achieved between the simulation and the tests on the load-displacement plot. The computed strains distributions did not compare as well to the measured strains at the first major failure event. / Master of Science

No / Immediate reporting, commonly referred to as a ‘hot reporting’, has been advocated as a method of effectively supporting clinical decision making. However, its implementation nationally has been limited with poor understanding of its value in practice. A cross sectional attitudinal survey was distributed to emergency department clinicians (medical and nursing staff) and radiographers to explore perceptions of an immediate reporting service in terms of its influence on professional role and autonomy, patient care and service quality. A total of 87 (n = 87/155; 56.1%) completed questionnaires were returned. The findings suggest that significant support for immediate reporting exists. Immediate reporting is believed to improve service quality, reduce clinical errors and provide opportunity for image interpretation skills development. However, responses were not consistent across clinical professions and staff grades. The immediate reporting of emergency department images is perceived to benefit patient, emergency department clinicians and hospital organisation.

Yes / Consultant posts were developed to strengthen strategic leadership whilst maintaining front line service responsibilities and clinical expertise. The nursing profession has attempted to develop tools to enable individuals to evaluate their own practice and consider relevant measurable outcomes. This study evaluated the feasibility of transferring such a nursing ‘toolkit’ to another health profession. Method: This evaluation was structured around a one-day workshop where a nurse consultant impact toolkit was appraised and tested within the context of consultant radiographic practice. The adapted toolkit was subsequently validated using a larger sample at a national meeting of consultant radiographers. Results: There was broad agreement that the tools could be adopted for use by radiographers although several themes emerged in relation to perceived gaps within the nursing template, confirming the initial exercise. This resulted in amendments to the original scope and a proposed new evaluation tool. Conclusion: The impact toolkit could help assess individual and collaborat ive role impact at a local and national level. The framework provides consultant radiographers with an opportunity to understand and highlight the contribution their roles have on patients, staff, their organisation and the wider profession.

Many gas turbine engines operate in harsh environments where the engine can ingest solid particles. Particles can accelerate the deterioration of an engine and reduce the engine’s service life. Understanding particle interactions with the materials used in gas turbines, at representative engine conditions, can improve the design and development of turbomachinery operating in particle laden environments. Coefficient of Restitution (COR) is a measure of the particle/wall interactions and is used to study erosion and deposition. This study presents data taken using the Virginia Tech Aerothermal Rig. Arizona Road Dust (ARD) of 20-40 μm is injected into a flow field to measure the effects of temperature and velocity on particle rebound from a polished high temperature material coupon. The high temperature coupon was tested at different temperatures of ambient (300K), 873K, 1073K, 1173 K, 1223 K, 1273 K, and 1323 K while the velocity of the flow field was held constant at 28 m/s or 70 m/s. The impingement angle of the coupon was varied from 30° to 80° for each temperature tested. The results show an increase in deposition as the temperature approaches the melting temperature of sand. The results have also been compared to previously published literature. / Master of Science

The purpose of this study was to develop injury risk functions for dynamic bending of the human femur in the lateral-to-medial and posterior-to-anterior loading directions. A total of 45 experiments were performed on human cadaver femurs using a dynamic three-point drop test setup. All 45 tests resulted in mid-shaft femur fractures with comminuted wedge and oblique fractures as the most common fracture patterns. The reaction loads were used to develop the injury criteria given that they represent the inertially compensated bending strength of the femur that is more appropriate for dummy load cell application. In the lateral-to-medial bending tests the peak reaction bending moments were 352 ± 83 Nm. In the posterior-to-anterior bending tests the peak reaction bending moments were 348 ± 96 Nm. Regression analysis was used to identify significant parameters, and parametric survival analysis was used to estimate risk functions. Femur cross-sectional area, area moment of inertia (I), maximum distance to the neutral axis (c), I/c, occupant gender, and occupant mass are shown to be significant predictors of fracture tolerance, while no significant difference is shown for loading direction, bone mineral density, leg aspect and age. Risk functions are presented for femur cross-sectional area, I/c, and a combined occupant gender and mass. The risk function that utilizes the most highly correlated (R2 = 0.77) and significant (p = 0.0001) variable, cross-sectional area, predicts a 50 percent risk of femur fracture of 240 Nm, 395 Nm, and 562 Nm for equivalent cross-sectional area of the 5th percentile female, 50th percentile male, and 95th percentile male respectively. / Master of Science

We study axisymmetric deformations of depleted uranium (DU) and tungsten heavy alloy (WHA) rods impacting at normal incidence both a rigid, planar target and a thick, deformable steel target. Each deformable material is modeled as elastic thermoviscoplastic; the flow stress increases with an increase in the effective plastic strain and effective plastic strain-rate but decreases with a rise in the temperature. An objective of this work is to ascertain when and where a shear band, defined as a narrow region of rapid, intense plastic deformation, forms in each material subject to impact loading. The Taylor impact simulations show that shear bands form earlier in WHA than in DU for the material parameters used. In the penetration simulations, shear bands form continuously in the ejecta of the DU penetrator while only one shear band occurs in the WHA ejecta followed by more uniform deformations. Note: In order to view the computer animations referenced in this thesis, one must have a QuickTime movie player and download the files named Ujce.mov Uz2e.mov Uz3e.mov Wjce.mov Wz2e.mov and Wz3e.mov from the same directory the "pdf" file resides in. / Master of Science

The United States Department of the Interior, Bureau of Land Management (BLM) National Operations Center obtained American Recovery and Reinvestment Act of 2009 funding to conduct an ethnographic overview of select proposed solar energy zones (SEZs) to augment the research that had been conducted for the Programmatic Environmental Impact Statement for Solar Development in Six Southwestern States (Draft Solar PEIS). The objective of this project was to solicit tribal identification of traditional cultural properties and sacred landscapes, religious and traditional use sites, significant ethnobotanical resources, other sensitive or significant resources (including visual), and tribal perspectives on the direct and indirect effects of solar energy development through oral interviews and on-site visits to proposed SEZs in Arizona, California, Nevada, and Utah. SWCA Environmental Consultants (SWCA) was selected to perform this work, assisted by the University of Arizona’s Bureau of Applied Research in Anthropology (BARA). As the project progressed, the list of participating tribes was modified to accommodate changing tribal needs and requests. When the tribe that had requested to participate in an ethnographic study for three of the California SEZs (Imperial East, Iron Mountain, and Riverside East) was unable to participate, the scope of the project was modified. In the Draft Solar PEIS, the high cost of conducting Class I archaeological records searches for the four California SEZs had precluded that research; the current project was modified from ethnographic interviews to a Class I records search for all four California SEZs (Imperial East, Iron Mountain, Pisgah, and Riverside East) by SWCA. BARA conducted ethnographic studies for Amargosa Valley, Delamar Valley, Dry Lake, East Mormon Mountain, Gold Point, and Millers in Nevada (inclement weather prevented visits to Dry Lake Valley North), and for Escalante Valley, Milford Flats South, and Wah Wah Valley in Utah.