In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. Reference: O. J. Mengshoel, S. Poll, and T. Kurtoglu. "Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft." Proc. of the IJCAI-09 Workshop on Self-* and Autonomous Systems (SAS): Reasoning and Integration Challenges, 2009 BibTex Reference: @inproceedings{mengshoel09developing, title = {Developing Large-Scale {Bayesian} Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft}, author = {Mengshoel, O. J. and Poll, S. and Kurtoglu, T.}, booktitle = {Proc. of the IJCAI-09 Workshop on Self-$\star$ and Autonomous Systems (SAS): Reasoning and Integration Challenges}, year={2009} }

Mortality rates were calculated as defined in the text.Summary statistics for White cervical cancer mortality rates in 13 U.S. states from 1975 to 2010.

The files submitted here contains data collected for the thesis titled "Relative preference for pecking blocks and its association with keel status and eggshell quality in laying hens housed in enriched cages." The purpose of this research was to determine pecking block preferences of White and Brown feathered laying hens strains, and if there is a time of day effect on pecking block use. We then investigated the association between pecking block preference, pecking block use, keel status, and eggshell quality. We also investigated if laying hens are consistent in their pecking block preference over time. Data on weekly pecking block disappearance, number of hens using pecking blocks across the day, eggshell quality and keel status in focal birds were also assessed. Data was analyzed using SAS Proc GLIMMIX, and consistency data was analyzed using SAS Proc Freq.

Applications of latent transition analysis (LTA) have emerged since the early 1990s, with numerous scientific findings being published in many areas, including social and behavioral sciences, education, and public health. Although LTA is effective as a statistical analytic tool for a person-centered model using longitudinal data, model building in LTA has often been subjective and confusing for applied researchers. To fill this gap in the literature, we review the components of LTA, recommend a framework of fitting LTA, and summarize what acceptable model evaluation tools should be used in practice. The proposed framework of fitting LTA consists of six steps depicted in Figure 1 from step 0 (exploring data) to step 5 (fitting distal variables). We also illustrate the framework of fitting LTA with data on concerns about school bullying from a sample of 1,180 students ranging from 5th to 9th grade (mean age = 12.2 years, SD = 1.29 years at Time 1) over three semesters. We identified four groups of students with distinct patterns of bullying concerns, and found that their concerns about bullying decreased and narrowed to specific concerns about rumors, gossip, and social exclusion over time. The data and command (syntax) files needed for reproducing the results using SAS PROC LCA and PROC LTA (Version 1.3.2) (2015) and Mplus 7.4 (Muthén and Muthén, 1998–2015) are provided as online supplementary materials.

Arterial hypertension is influenced by the intestinal microbiota and its metabolites, which play a crucial role in host health. Dietary peptides are multifunctional molecules with therapeutic potential for managing hypertension. This study aimed to evaluate the impact of incorporating enzymatically hydrolyzed poultry byproduct meal (EHPM-c) into extruded dry diets on the fecal microbiota and blood pressure parameters of elderly obese cats. Eighteen owners of neutered, clinically healthy male and female cats of various breeds were randomly assigned to two groups: control (30.8%, conventional poultry byproduct meal—CPM-c) and test (17.07%, CPM-c + 12.0% EHPM-c). Clinical values of systolic blood pressure, serum aldosterone concentrations, angiotensin-converting enzyme I activity, and fecal microbiota using 16S rRNA were measured. Data were processed using SAS software (PROC MIXED, PROC GLIMMIX, and PROC CORR; p 

We collected black spruce needle from several sites located near Fairbanks Ak, and Delta, Ak in August 1999 (Sites designated here as S1, S2, and S3) were located in Fairbanks (64o40?N, 148o15?W), Alaska (S1: 64o52.164? N, 147o51.462? W; S2: 64o52.058? N, 147o51.378? W; S3: 64o51.603? N, 147o52.789? W) with 2 additional sites (S4, S5) in Delta, Alaska (64010? N, 145030? W). In each stand, 30 trees were randomly selected for sampling. Within each tree, five shoots were collected from the southern aspect of the mid-canopy height from each of the following age classes: 0-, 1-, 4-, 9-, and 19-years old. In two of the Fairbanks stands (S2, S3), 19-year old needles were not present. A total of 690 samples over the five stands include 150 samples per stand in three stands (S1, S4, S5) and 120 samples per stand in the other two stands (S2, S3). Needles were returned to the lab and nitrogen content was determined. We used a three-factor nested analysis of variance (ANOVA) to evaluate differences in needle N concentration among the ages of needles on a tree, among trees nested within a stand, and among stands. Ages and stands were treated as fixed factors and tree was treated as a random factor. The ANOVA and means testing for these differences used Proc GLM in the SAS statistical package with needle N content as the dependent variable and needle age, tree, and stand as independent variables. The GLM procedure handled the problem of missing treatment combinations within the ANOVA. Type III sum of squares was used to test the effects of factors without interactions

Arterial hypertension is influenced by the intestinal microbiota and its metabolites, which play a crucial role in host health. Dietary peptides are multifunctional molecules with therapeutic potential for managing hypertension. This study aimed to evaluate the impact of incorporating enzymatically hydrolyzed poultry byproduct meal (EHPM-c) into extruded dry diets on the fecal microbiota and blood pressure parameters of elderly obese cats. Eighteen owners of neutered, clinically healthy male and female cats of various breeds were randomly assigned to two groups: control (30.8%, conventional poultry byproduct meal—CPM-c) and test (17.07%, CPM-c + 12.0% EHPM-c). Clinical values of systolic blood pressure, serum aldosterone concentrations, angiotensin-converting enzyme I activity, and fecal microbiota using 16S rRNA were measured. Data were processed using SAS software (PROC MIXED, PROC GLIMMIX, and PROC CORR; p 

Note: For each categorical variable, one category was chosen as a reference category (RC, e.g., RC = Social Sciences for the categorical variable discipline). For categorical variables, effect for each predictor variable (a dummy variable representing one of the categories) is a regression coefficient (Coeff) that should be interpreted in relation to its standard error (SE) and the effect of the reference category. Variance components for level 1 are derived from the data, but variance components at level 2 and level 3 indicate the amount of variance that can be explained by differences between studies (level 3) and differences between single reliability coefficients nested within studies (level 2). The loglikelihood test provided by SAS/proc mixed (−2LL) can be used to compare different models, as can also the Bayes Information Criteria (BIC). The smaller the BIC, the better the model is.*p