While assessing emotions, behaviors or performance of preschoolers and young children, scores from adults such as parent psychiatrist and teacher ratings are used rather scores from children themselves. Data from parent ratings or from parents and teachers are often nested such as students are within teachers and a child is within their parents. This popular nested feature of data in educational, social and behavioral sciences makes measurement invariance (MI) testing across informants of children methodologically challenging. There was lack of studies that take into account the nested structure of data in MI testing for multiple adult informants, especially no simulation study that examines the performance of different models used to test MI across different raters. This dissertation focused on two specific nesting data types in testing MI between adult raters of children: paired and partial nesting. For the paired data, the independence assumption of regular MI testing is often violated because the two informants (e.g., father and mother) rate the same child and their scores are anticipated to be related or dependent. The partial nesting data refers to the research situation where teacher and parent ratings are compared. In this scenario, it is common that each parent has only one child to rate while each teacher has multiple children in their classroom. Thus, in case of teacher and parent ratings of the same children, data are repeated measures and also partially nested. Because of these unique features of data, MI testing between adult informants of children requires statistical models that take into account different types of data dependency. I proposed and evaluated the performance of the two statistical models that can handle repeated measures and partial nesting with several simulated research scenarios in addition to one commonly used and one potentially appropriate statistical models across several research scenario. Results of the two simulation studies in this dissertation showed that for the paired data, both multiple-group confirmatory factor analysis (CFA) and repeated measure CFA models were able to detect scalar invariance most of the time using Δχ2 test and ΔCFI. Although the multiple-group CFA (Model 2) was able to detect scalar invariance better than the repeated measure CFA model (Model 1), the detection rates of Model 1 were still at the high level (88% - 91% using Δχ2 test and 84% - 100% using ΔCFI or ΔRMSEA). For configural invariance and metric invariance conditions for the paired data, Model 1 had higher detection rate than Model 2 in almost examined research scenario in this dissertation. Particularly while Model 1 could detect noninvariance (either in intercepts only or in both intercepts and factor loadings) than Model 2 for paired data most of the time, Model 2 could rarely catch it if using suggested cut-off of 0.01 for RMSEA differences. For the paired data, although both Models 1 and 2 could be a good choice to test measurement invariance, Model 1 might be favored if researchers are more interested in detecting noninvariance due to its overall high detection rates for all three levels (i.e. configural, metric, and scalar) of measurement invariance. For scalar invariance with partially nested data, both multilevel repeated measure CFA and design-based multilevel CFA could detect invariance most of the time (from 81% to 100% of examined cases) with slightly higher detection rate for the former model than the later. Multiple-group CFA model hardly detect scalar invariance except when ICC was small. The detection rates for configural invariance using Δχ2 test or Satorra-Bentler LRT were also highest for Model 3 (82% to 100% except only two conditions with detection rates of 61%), following by Model 5 and lowest Model 4. Models 4 and 5 could reach these rates only with the largest sample sizes (i.e., large number of cluster or large cluster size or large in both factors) when the magnitude of noninvariance was small. Unlike scalar and configural invariance, the ability to detect metric invariance was highest for Model 4, following by Model 5 and lowest for Model 3 across many conditions using all of the three performance criteria. As higher detection rates for all configural and scalar invariance, and moderate detection rates for many metric invariance conditions (except cases of small number of clusters combined with large ICC), Model 3 could be a good candidate to test measurement invariance with partially nested data when having sufficient number of clusters or if having small number of clusters with small ICC. Model 5 might be also a reasonable option for this type of data if both the number of clusters and cluster size were large (i.e., 80 and 20, respectively), or either one of these two factors was large coupled with small ICC. If ICC is not small, it is recommended to have a large number of clusters or combination of large number of clusters and large cluster size to ensure high detection rates of measurement invariance for partially nested data. As multiple group CFA had better and reasonable detection rates than the design-based and multilevel repeated measure CFA models cross configural, metric and scalar invariance with the conditions of small cluster size (10) and small ICC (0.13), researchers can consider using this model to test measurement invariance when they can only collect 10 participants within a cluster (e.g. students within a classroom) and there is small degree of data dependency (e.g. small variance between clusters) in the data.

Wideband beamforming have been widely used in modern radar systems. One of the powerful wideband beamforming techniques that is capable of achieving a high selectivity over a wide bandwidth is the nested array (NA) beamformer. Such a beamformer consists of nested antenna arrays, 2-D spatio-temporal filters, and multirate filterbanks. Speed of operation is bounded by the speed of the hardware implementation. This dissertation presents the use of a systematic methodology for design space exploration of the NA beamformer basic building blocks. The efficient systolic array design in terms of the highest possible clock speed of each block was selected for hardware implementation. The proposed systolic array designs and the conventional designs were implemented in FPGA hardware to verify their functionality and compare their erformance. The implementations results confirm that the proposed systolic array implementations are faster and requires less hardware resources than the published designs. The overall beamformer FPGA implementation is constructed based on the analysis of efficient systolic arrays designs of the beamformer building blocks. The implemented overall structure is then validated to ensure its proper operation. Further, the implementation performance is evaluated in terms of accuracy and error analysis in comparison to the MATLAB simulations. The new methodology is based on the systematic methodology to close the gap between the modern wideband radar I/O rates and the silicon operating speed. This new metodology is applied to the interpolator block as an example. The proposed methodology is simulated and tested using MATLAB object oriented programming (OOP) to ensure the proper operation. / Graduate / 2020-11-17

<p>Converting a nutrient management plan from commercial fertilizers to poultry litter helps effectively utilize waste from the nearly 10 billion broiler birds across the United States. Nine field scale watersheds from the USDA ARS Grassland, Soil and Water Research Laboratory near Riesel, TX were evaluated for P inputs and P outputs to determine phosphorus budgets for 15 years of annual application of poultry litter ranging from 75 – 219 kg P ha^-1 yr^-1 on cultivated and pasture/grazed fields. The cumulative net P continued to increase regardless of the application rate and had a positive relationship with soil level P (Mehlich-3 P) and flow weighted mean concentration (FWMC) for dissolved reactive P for both cultivated and pasture managed fields. We assessed hydrological connectivity within two nested watersheds by using the before-after-control-impact (BACI) design. Results showed hydrological connectivity during high rainfall years whereas low rainfall years had minimal connectivity compared to the controls. These results suggest the P contributions from upstream fields receiving poultry litter, even at high application rates, did not exhibit a treatment effect during the low rainfall years at downslope monitoring stations. </p><p><br></p> <p>As nutrient source variability increases in nutrient management plans, improving our ability to differentiate P sources and their fate in soils is critical. We evaluated soils with unique P inputs: inorganic P, poultry litter, and cattle grazing for isotopic signatures by forming silver phosphate and determining the δ¹⁸O_P. Isotopic signatures of the oxygen molecules which are strongly bound to P, provided signatures of 17.09‰, 18.00‰, and 17.20‰ for fields receiving commercial fertilizer, poultry manure, and cattle grazed, respectively. Significant effort was made to determine critical steps in the method to successfully precipitate Ag₃PO₄for analysis. Results show adding a cation removal step as well as monitoring and adjusting pH throughout the method increases probability of successful Ag₃PO₄precipitation. Findings from this study provide a valuable framework for future analysis to confirm unique δ¹⁸O_P signatures which can be used to differentiate the fate of different phosphorus sources in agricultural systems.</p>

Bayesian inference is particularly challenging on hierarchical statistical models as computational complexity becomes a significant issue. Sampling-based methods like the popular Markov Chain Monte Carlo (MCMC) can provide accurate solutions, but they likely suffer a high computational burden. An attractive alternative is the Integrated Nested Laplace Approximations (INLA) approach, which is faster when applied to the broad class of Latent Gaussian Models (LGMs). The method computes fast and empirically accurate deterministic posterior marginal approximations of the model's unknown parameters. In the first part of this thesis, we discuss how to extend the software's applicability to a joint posterior inference by constructing a new class of joint posterior approximations, which also add marginal corrections for location and skewness. As these approximations result from a combination of a Gaussian Copula and internally pre-computed accurate Gaussian Approximations, we name this class Skew Gaussian Copula (SGC). By computing moments and correlation structure of a mixture representation of these distributions, we achieve new fast and accurate deterministic approximations for linear combinations in a subset of the model's latent field. The same mixture approximates a full joint posterior density through a Monte Carlo sampling on the hyperparameter set. We set highly skewed examples based on Poisson and Binomial hierarchical models and verify these new approximations using INLA and MCMC. The new skewness correction from the Skew Gaussian Copula is more consistent with the outcomes provided by the default INLA strategies. In the last part, we propose an extension of the parametric fit employed by the Simplified Laplace Approximation strategy in INLA when approximating posterior marginals. By default, the strategy matches log derivatives from a third-order Taylor expansion of each Laplace Approximation marginal with those derived from Skew Normal distributions. We consider a fourth-order term and adapt an Extended Skew Normal distribution to produce a more accurate approximation fit when skewness is large. We set similarly skewed data simulations with Poisson and Binomial likelihoods and show that the posterior marginal results from the new extended strategy are more accurate and coherent with the MCMC ones than its original version.

Since the start of the COVID-19 pandemic in December 2019, much research has been done to develop the spatial-temporal methods to track it and to predict the spread of the virus. In this thesis, a COVID-19 dataset containing the number of biweekly infected cases registered in Ontario since the start of the pandemic to the end of June 2021 is analysed using Bayesian Spatial-temporal models and Area-to-area (Area-to-point) Poisson Kriging models. With the Bayesian models, spatial-temporal effects on infected risk will be checked and ATP Poisson Kriging models will show how the virus spreads over the space and the spatial clustering feature. According to these models, a Shinyapp website https://mujingrui.shinyapps.io/covid19 is developed to present the results.

No description available.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24478号 / 医博第4920号 / 新制||医||1062(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 山本 洋介, 教授 近藤 尚己, 教授 柳田 素子 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

Understanding the mechanisms that generate shared morphologies across closely related taxa is important when identifying distinct evolutionary lineages using morphological characters. Desmognathus salamanders are an ideal group for testing hypotheses concerning the correlation between morphological similarity and genetic exchange within and among nominal species due to a pattern of high discordance between the two. Phylogeographic hypotheses are tested for populations of the D. quadramaculatus species complex throughout southern Appalachia by combining phylogenetic and population genetic methods with geographical information. Phylogenetic and phylogeographic inferences are then assessed in conjunction with morphological characteristics that have traditionally diagnosed taxonomic entities to understand the genetic basis of shared morphology in this complex, and to assess species boundaries. A history of fragmentation followed by range expansion is suggested as a recurrent pattern that has shaped the current population structure within this complex. The current taxonomy is found to unite populations that share similar morphologies due to parallel evolution rather than ancestry. We suggest revisions in taxonomy that will better reflect the evolutionary history of these lineages. Appreciation of the hidden genetic variation and homoplasious morphological variation often present in and among salamander species can foster the implementation of more appropriate methods for detecting and recognizing the complex history of these organisms.

Whether active or passive, dispersal accompanied by gene flow shapes the population genetics and evolutionary divergence of species. Indirect methods which use genetic markers have the ability to assess effective dispersal—that which resulted in gene flow. My objective was to see if an aquatic insect and an obligate aquatic invertebrate show similar phylogeographic patterns and genetic uniqueness. Hyalella azteca and Callibaetis americanus were collected from 4-5 springs in each of six basins in the Great Basin of western North America. No dispersal or genetic studies of C. americanus have been conducted to date. However, several studies focusing on mtDNA diversity of H. azteca have revealed a tremendous degree of cryptic diversity in the desert springs of the Great Basin. Nested clade phylogeographical analysis (NCPA), FST values, AMOVA, and Mantel tests were used to examine geographical associations. I also used traditional phylogenetic approaches including maximum parsimony (MP) and likelihood (ML) analyses using cytochrome c oxidase subunit I (COI), 28S, and 16S as genetic markers. The mitochondrial COI sequence divergences in C. americanus were higher than H. azteca COI divergences within springs but lower among springs. FST values were very high in H. azteca reaching near fixation for certain alleles. C. americanus FST values were lower suggesting greater gene flow and, consequently, greater dispersal rates. Even though Mantel tests did not detect significant isolation by distance when evaluating all haplotypes together, nested clade analysis was able to examine smaller networks of related haplotypes and detect significant isolation by distance. Whereas the genetic structure in C. americanus was dominated by restricted gene flow with isolation by distance, H. azteca was characterized more by gradual range expansion followed by fragmentation. Mayflies likely showed more gene flow than amphipods because of their flight capabilities, but movement was still restricted by long distances between isolated springs.

The aim of this study was to develop a framework to model travel choice behavior in order to estimate intercity travel demand at nation-level in the United States. Nested and mixed logit models were developed to study national-level intercity transportation in the United States. A separate General Aviation airport choice model to estimates General Aviation person-trips and number of aircraft operations though more than 3000 airports was also developed. The combination of the General Aviation model and the logit models gives the capability to estimate a full spectrum of intercity travel demand in the United States. The logit models were calibrated using a nationwide revealed preference survey (1995 American Travel Survey). Separate models were developed for business and non-business trip purposes. An airport choice model is integrated into the mode choice model to estimate both the market share between any origin-destination pair and other modes of transportation, and the market share split between airports associated with the origin-destination pairs. The explanatory variables used in the utility functions of the models are travel time, travel cost, and traveler's household income. The logit models are used to estimate the market share of automobile and commercial air transportation between 3091 counties and 443 commercial service airports in the United States. The model was also used to estimate market share for on-demand air taxi services. Given an input county-to-county trip demand table, the models were used to estimate county-to-county travel demand by automobile and commercial airline between all counties and commercial service airports in the United States. The model has been integrated into a computer software framework called the Transportation Systems Analysis Model (TSAM) that estimates nationwide intercity travel demand in the United States. / Ph. D.