yaImpute: An R Package for kNN Imputation

This article introduces yaImpute, an R package for nearest neighbor search and imputation. Although nearest neighbor imputation is used in a host of disciplines, the methods implemented in the yaImpute package are tailored to imputation-based forest attribute estimation and mapping. The impetus to writing the yaImpute is a growing interest in nearest neighbor imputation methods for spatially explicit forest inventory, and a need within this research community for software that facilitates comparison among different nearest neighbor search algorithms and subsequent imputation techniques. yaImpute provides directives for defining the search space, subsequent distance calculation, and imputation rules for a given number of nearest neighbors. Further, the package offers a suite of diagnostics for comparison among results generated from different imputation analyses and a set of functions for mapping imputation results.

Reliability of wood plastic composites and improving lower percentile estimation via induced percentile censoring

Wood plastic composites (WPC) are a combination of wood fiber and thermoplastics to form a water resistant substitute for wood in construction. As a manufactured product, practitioners are interested in understanding the reliability of WPC. This thesis explores the reliability of WPC by analyzing data from a WPC manufacturer, and explores a new application of induced percentile right censoring via simulation to improve lower percentile estimation. The research demonstrates significant improvements in the mean squared errors and bias from this percentile right censoring. Estimates of the reliability of WPC are studied for two industrial extrusion lines at the same facility. A parametric analysis of the extrusion lines reveals only small differences in averages. However, a non-parametric method is presented that reveals differences between Kaplan-Meier survival curves for the modulus of elasticity (MOE) and modulus of rupture (MOR) strength metrics of the WPC industrial data.Although the differences between the two extrusion lines are most prevalent in the middle of the distributions, the consistency between the two lines for the smaller left tail percentiles holds greater interest for safety and liability. Bootstrapping is performed to estimate confidence intervals on the differences between the two lines for the first, fifth, and tenth percentiles of the MOE and the MOR. A statistical difference is found for the MOR at the tenth percentile. In many applications, one aging behavior is not sufficient for understanding the entire life time. A simulation is conducted to generate data with a bathtub hazard function. The simulation uses induced right censoring to improve the estimates of the lower tail percentiles. A wide range of possible percentile right censoring yields significant improvements. The smallest mean squared error and bias are achieved when the percentile censoring approaches the point at which aging behavior first shifts.Techniques for finding this optimal point are discussed. Application of the induced percentile right censoring and the methods used to analyze the WPC data may benefit statisticians, wood scientists, and practitioners by improving the statistical tools for understanding product quality and variability

yaImpute: An R Package for kNN Imputation

This article introduces yaImpute, an R package for nearest neighbor search and imputation. Although nearest neighbor imputation is used in a host of disciplines, the methods implemented in the yaImpute package are tailored to imputation-based forest attribute estimation and mapping. The impetus to writing the yaImpute is a growing interest in nearest neighbor imputation methods for spatially explicit forest inventory, and a need within this research community for software that facilitates comparison among different nearest neighbor search algorithms and subsequent imputation techniques. yaImpute provides directives for defining the search space, subsequent distance calculation, and imputation rules for a given number of nearest neighbors. Further, the package offers a suite of diagnostics for comparison among results generated from different imputation analyses and a set of functions for mapping imputation results

The impact of islet mass, number of transplants, and time between transplants on graft function in a national islet transplant program

The UK islet allotransplant program is nationally funded to deliver one or two transplants over 12 months to individuals with type 1 diabetes and recurrent severe hypoglycemia. Analyses were undertaken 10 years after program inception to evaluate associations between transplanted mass; single versus two transplants; time between two transplants and graft survival (stimulated C-peptide >50 pmol/L) and function. In total, 84 islet transplant recipients were studied. Uninterrupted graft survival over 12 months was attained in 23 (68%) single and 47 (94%) (p =.002) two transplant recipients (separated by [median (IQR)] 6 (3–8) months). 64% recipients of one or two transplants with uninterrupted function at 12 months sustained graft function at 6 years. Total transplanted mass was associated with Mixed Meal Tolerance Test stimulated C-peptide at 12 months (p <.01). Despite 1.9-fold greater transplanted mass in recipients of two versus one islet infusion (12 218 [9291–15 417] vs. 6442 [5156–7639] IEQ/kg; p <.0001), stimulated C-peptide was not significantly higher. Shorter time between transplants was associated with greater insulin dose reduction at 12 months (beta −0.35; p =.02). Graft survival over the first 12 months was greater in recipients of two versus one islet transplant in the UK program, although function at 1 and 6 years was comparable. Minimizing the interval between 2 islet infusions may maximize cumulative impact on graft function

Characterization of pre-transplant psychosocial burden in an integrated national islet transplant programme

The psychological burden experienced by people with diabetes prior to islet transplantation is recognized but has not been studied comprehensively, especially in relation to glycemia. Therefore, we conducted a rigorous pre-operative psychosocial profile of UK islet transplant recipients, and compared groups with higher/lower HbA1 c to test the null hypothesis that pre-transplant hypoglycemia awareness and psychosocial burden would not be related to baseline HbA1 c in this high-risk cohort. Pre-transplant, recipients (n = 44) completed validated hypoglycemia awareness questionnaires and generic/diabetes-specific measures of psychological traits and states. Scores were compared in groups, dichotomized by HbA1 c (≤8% versus >8%). Participants were aged (mean±SD) 53 ± 10 years; 64% were women; with HbA1 c 8.3 ± 1.7%. Median rate of severe hypoglycemia over the preceding 12 months was 13 events/person-year and 90% had impaired awareness of hypoglycemia (Gold/Clarke score ≥4). Participants had elevated fear of hypoglycemia (HFS-II Worry), impaired diabetes-specific quality of life (DQoL) and low generic health status (SF-36; EQ-5D). One quarter reported scores indicating likely anxiety/depression (HAD). Dispositional optimism (LOT-R) and generalized self-efficacy (GSE) were within published ‘norms.’ Despite negative perceptions of diabetes (including low personal control), participants were confident that islet transplantation would help (BIPQ). Hypoglycemia awareness and psychosocial profile were comparable in lower (n = 24) and higher (n = 20) HbA1 c groups. Islet transplant candidates report sub-optimal generic psychological states (anxiety/depressive symptoms), health status and diabetes-specific psychological states (fear of hypoglycemia, diabetes-specific quality of life). While their generic psychological traits (optimism, self-efficacy) are comparable with the general population, they are highly optimistic about forthcoming transplant. HbA1 c is not a proxy measure of psychosocial burden, which requires the use of validated questionnaires to systematically identify those who may benefit most from psychological assessment and support

Agronomic and Economic Performance Characteristics of Conventional and Low-External-Input Cropping Systems in the Central Corn Belt

We conducted a 9-ha field experiment near Boone, IA, to test the hypothesis that yield, weed suppression, and profit characteristics of low-external-input (LEI) cropping systems can match or exceed those of conventional systems. Over a 4-yr period, we compared a conventionally managed 2-yr rotation system {corn (Zea mays L.)/soybean [Glycine max (L.) Merr.]} with two LEI systems: a 3-yr corn/soybean/small grain + red clover (Trifolium pratense L.) rotation, and a 4-yr corn/soybean/small grain + alfalfa (Medicago sativa L.)/alfalfa rotation. Synthetic N fertilizer use was 59 and 74% lower in the 3- and 4-yr systems, respectively, than in the 2-yr system; similarly, herbicide use was reduced 76 and 82% in the 3- and 4-yr systems. Corn and soybean yields were as high or higher in the LEI systems as in the conventional system, and weed biomass in corn and soybean was low (≤4.2 g m−2) in all systems. Experimentally supplemented giant foxtail (Setaria faberi Herrm.) seed densities in the surface 20 cm of soil declined in all systems; supplemented velvetleaf (Abutilon theophrasti Medik.) seed densities declined in the 2- and 4-yr systems and remained unchanged in the 3-yr system. Without subsidy payments, net returns were highest for the 4-yr system ($540 ha−1 yr−1), lowest for the 3-yr system ($475 ha−1 yr−1), and intermediate for the 2-yr system ($504 ha−1 yr−1). With subsidies, differences among systems in net returns were smaller, as subsidies favored the 2-yr system, but rank order of the systems was maintained

The Impact of Community Colleges on Rural Economies and Populations

Economic activity in the United States continues to be spatially compressed into urban and suburban agglomeration economies. As a result of this spatial compression, rural economies across the United States are experiencing distance-based frictions that put them at a competitive disadvantage with their urban and suburban counterparts. This competitive disadvantage has led to a number of problems in rural communities, such as high unemployment, high poverty, and population loss. Policymakers, researchers, and other stakeholders in rural communities are exploring numerous measures to promote economic development in rural communities. There are many vital components to economic development. Scholars generally agree that adequate levels of local human capital must be in place before regional economic development can occur. Although human capital is widely believed to be a necessary component of economic development, there has been little research that has explored whether or not investments in higher education benefit rural economies and populations. Education in the rural setting is a complex issue. On the one hand, educational investments have the potential improve rural economies by increasing local human capital stock, which in turn leads to greater workforce productivity. On the other hand, without local employment opportunities, education is seen by many to funnel. This research uses two-stage least squares regression (2SLS) and fixed-effects with key slope dummy interaction terms measure whether rural counties with comprehensive community colleges experienced a comparative advantage in job growth, population growth, and poverty compared to counties without. Community colleges are unique as institutions of higher education because they generally provide open-door access to the general population and are designed to meet the needs of local economies. As such, their impact on rural economies should be an issue of public interest. This research finds that rural counties with community colleges have not experienced a discernible benefit in terms of employment growth or population growth in recent time panels and are associated with higher levels of poverty. The implications of these findings raise important questions about the state of rural economies and the ability of community colleges to catalyze economic development and population growth in rural communities