Wear studies made of slip rings and gas bearing components

Neutron activation analysis techniques were employed for the study of the wear and performance characteristics of slip ring and rotor assemblies and of the problems arising from environmental conditions with special reference to surface contamination. Results showed that the techniques could be successfully applied to measurement of wear parameters

Analysis of solid-rocket effluents for aluminum, silicon, and other trace elements by neutron activation analysis

The sensitivity and reliability of neutron activation analysis in detecting trace elements in solid rocket effluents are discussed. Special attention was given to Al and Si contaminants. The construction and performance of a thermal column irradiation unit was reported

Bayesian comparison of latent variable models: Conditional vs marginal likelihoods

Typical Bayesian methods for models with latent variables (or random effects) involve directly sampling the latent variables along with the model parameters. In high-level software code for model definitions (using, e.g., BUGS, JAGS, Stan), the likelihood is therefore specified as conditional on the latent variables. This can lead researchers to perform model comparisons via conditional likelihoods, where the latent variables are considered model parameters. In other settings, however, typical model comparisons involve marginal likelihoods where the latent variables are integrated out. This distinction is often overlooked despite the fact that it can have a large impact on the comparisons of interest. In this paper, we clarify and illustrate these issues, focusing on the comparison of conditional and marginal Deviance Information Criteria (DICs) and Watanabe-Akaike Information Criteria (WAICs) in psychometric modeling. The conditional/marginal distinction corresponds to whether the model should be predictive for the clusters that are in the data or for new clusters (where "clusters" typically correspond to higher-level units like people or schools). Correspondingly, we show that marginal WAIC corresponds to leave-one-cluster out (LOcO) cross-validation, whereas conditional WAIC corresponds to leave-one-unit out (LOuO). These results lead to recommendations on the general application of the criteria to models with latent variables.Comment: Manuscript in press at Psychometrika; 31 pages, 8 figure

Infrared detection of concrete deterioration

Infrared detection of concrete deterioratio

Regional astrocyte IFN signaling restricts pathogenesis during neurotropic viral infection

Type I IFNs promote cellular responses to viruses, and IFN receptor (IFNAR) signaling regulates the responses of endothelial cells of the blood-brain barrier (BBB) during neurotropic viral infection. However, the role of astrocytes in innate immune responses of the BBB during viral infection of the CNS remains to be fully elucidated. Here, we have demonstrated that type I IFNAR signaling in astrocytes regulates BBB permeability and protects the cerebellum from infection and immunopathology. Mice with astrocyte-specific loss of IFNAR signaling showed decreased survival after West Nile virus infection. Accelerated mortality was not due to expanded viral tropism or increased replication. Rather, viral entry increased specifically in the hindbrain of IFNAR-deficient mice, suggesting that IFNAR signaling critically regulates BBB permeability in this brain region. Pattern recognition receptors and IFN-stimulated genes had higher basal and IFN-induced expression in human and mouse cerebellar astrocytes than did cerebral cortical astrocytes, suggesting that IFNAR signaling has brain region–specific roles in CNS immune responses. Taken together, our data identify cerebellar astrocytes as key responders to viral infection and highlight the existence of distinct innate immune programs in astrocytes from evolutionarily disparate regions of the CNS

Polymorphic Type Inference for the JNI

We present a multi-lingual type inference system for checking type safety of programs that use the Java Native Interface (JNI). The JNI uses specially-formatted strings to represent class and field names as well as method signatures, and so our type system tracks the flow of string constants through the program. Our system embeds string variables in types, and as those variables are resolved to string constants during inference they are replaced with the structured types the constants represent. This restricted form of dependent types allows us to directly assign type signatures to each of the more than 200 functions in the JNI. Moreover, it allows us to infer types for user-defined functions that are parameterized by Java type strings, which we have found to be common practice. Our inference system allows such functions to be treated polymorphically by using instantiation constraints, solved with semi-unification, at function calls. Finally, we have implemented our system and applied it to a small set of benchmarks. Although semi-unification is undecidable, we found our system to be scalable and effective in practice. We discovered 155 errors 36 cases of suspicious programming practices in our benchmarks

Economic Growth and Recession Time Periods: Their Effect Upon Pleasure Travelers Visiting Florida Theme Parks

Two tourism-oriented travel samples were drawn from recent time periods that represented economic growth (expansion) and recession cycles in the O: S. economy. Analysis suggests that during the recession period, a greater percentage of theme park visitors chose to travel by air. Second, theme park travelers were more likely to visit friends or fami4 during the recession period. Third, recession theme park travelers were 10 years older, on the average, than their rapid growth counterparts. The average age difference of theme park visitors was found to be significantly different during cyclical economic periods. Research findings support the need for additional studies that segment using generational market

Predicting a Behavioral Profile for Pleasure Travelers on the Basis of Internet Use Segmentation

In an attempt to create a behavioral profile of pleasure travelers segmented based on Internet use, 5,319 pleasure travelers were interviewed. Initially, the respondents were classified as an Internet user or Internet nonuser based on whether or not they would use the Internet to seek travel related information. Using discriminant analysis, chi square, and analysis of variance statistical techniques, a profile of demographic and behavioral characteristics was created. The results of this study suggest that people who use the Internet to search for travel-related information are likely to be people who are (a) college-educated owners of computers, (b) less than 45 years of age, (c) stay more often in commercial lodging establishments, and (d) spend more money each day while traveling. Implications for marketing managers and future research are discussed

Using the Internet as a Pleasure Travel Planning Tool: An Examination of the Sociodemographic and Behavioral Characteristics among Internet Users and Nonusers

A critical prerequisite for the formulation of effective travel marketing strategies in the next decade must include an understanding of the influence exerted through the Internet. The increasing presence of the Internet as an instrument for advertising travel destinations and travel-related services highlights its importance as a factor in travelers’ decision-making processes. This exploratory investigation examined travelers who requested on-line information about a potential vacation destination using the Internet. Results of this investigation suggest that Internet “users, when compared with “nonusers,” are more educated, have higher household incomes, use commercial lodging accommodations while traveling, tend to travel by air, and spend more money on travel-related expenses on a per diem basis. Implications for target marketing strategies designed for travel destination areas, services, and facilities are discussed