Search

Processing of light tight oils (LTOs) and their blends is challenged with their high fouling propensity. In this study, their fouling potential was attributed to fractions from centrifuge-accelerated settling. A small solid fraction comprising lower than 0.5% of the volume was found to bear a majority of the fouling potential of a set of LTOs. The chemical analysis of these centrifuge-separated solids from an LTO blend resembled that of the field deposits from the crude unit furnace tubes processing the same blend, further validating their impact in crude unit fouling. The liquid fraction of the LTOs affected the fouling potential in two aspects. First, the same solid fraction separated form an LTO presented varying fouling potency when mixed with different liquid fractions from different crude oils. Second, paraffin crystals led to a flocculated structure and impaired solid settling. Time-of-Flight Secondary Ion Mass Spectrometry analysis of lab-generated thin fouling films unmasked the complex and intertwined fouling mechanisms of different LTO blends, which explained the unsatisfactory prediction quality of crude oil fouling potential based on solid volume fraction alone and emphasized the importance to evolve from the conventional fouling management approach focusing solely or heavily on asphaltene stability. Finally, a nonlinear model considering the two-class solids loading input and the Fourier transform infrared fingerprint of the crude oil was developed to predict the fouling potential of crude oils. The predictive power of the model was corroborated in the field at various refinery sites processing crudes with fouling potentials ranging from low to severe. As an integral component of our field-deployable predictive modeling platform, the fouling potential model helped refineries quickly and reliably predict crude oil instability and fouling severity, the associated processing issues, the likely locations where they may be manifested, and the recommended actions for mitigation. Hence, feed-forward optimization and reliability improvement of the crude fractionation unit process were made possible.

Sensory phenomena (SP) are uncomfortable feelings, including bodily sensations, “just-right” perceptions and feelings of incompleteness, which have been shown to be predictors of symptom severity in individuals with obsessive–compulsive disorder (OCD). These sensory phenomena have also been related to obsessive compulsive (OC) traits within the general population. This meta-analysis aimed to quantify a possible relationship between sensory phenomena (incompleteness and Not Just in Right Experiences; NJRE), with OC symptoms in clinical and non-clinical samples. Methods: A systematic search was conducted for studies in children and adult populations of patients with OCD and in general populations displaying symptoms of OCD. Results: Effect sizes of incompleteness and NJRE were correlated to OCD symptoms. The effects sizes in the clinical and non-clinical groups did not differ significantly. Discussion: Robust effect sizes of incompleteness and NJRE in relation to OC symptomatology confirm sensory phenomena as marker of OC symptoms in both groups. The findings suggest that sensory phenomena could be targeted as an intervention in those showing both clinical and sub-clinical levels of OC traits.

Circular plates of variable thickness and elastically restrained against rotation along the edge resting on a WinklerPasternak medium are addressed. Free and forced vibrations are studied using a very simple polynomial coordinate function and the Ritz method. In the case of simply supported and clamped plates of uniform thickness subjected to static loading the results are in very good agreement with values available in the open literature. The entire algorithmic procedure can be efficiently handled using a microcomputer.

Several letters to the editor are presented in response to articles in previous issues including one on shiitake mushrooms by Anita B. Stone in the November/December 2013 issue, another one on methods of food preservation by Shirley Benson and the article "Rabbits Make Great Pets," by Blair Bryant in the November/December 2013 issue.

Stata is general‐purpose statistical software. Currently in version 11, Stata is known for its wide range of statistical routines, ease of data management, and publication‐quality graphics. Stata is available on virtually all computing platforms, including Windows, Macintosh, and most varieties of Unix/Linux. It is designed to run on both 32‐bit and 64‐bit architectures and operating systems. Stata possesses both a command‐line interface and a point‐and‐click menu interface, with a one‐to‐one correspondence between the two. Stata appeals to researchers from a wide range of fields, with concentrations in the health sciences and in economics. Statistically, Stata strengths are in the areas of panel/longitudinal data, survival analysis, and the analysis of data from complex surveys. Users can program their own routines using a mixture of Stata's own interpretive language and the compiled matrix‐programming language Mata, included with all Stata installations. Stata is offered in three flavors: Stata/IC, a standard version adequate for most purposes; Stata/SE, an expanded version for use with larger (wider) datasets; and Stata/MP, a version with specialized code designed to make use of multiple cores/processors and run faster on systems that have them. Copyright © 2010 John Wiley & Sons, Inc.

In the past decade, many statistical methods have been proposed for the analysis of case–control genetic data with an emphasis on haplotype-based disease association studies. Most of the methodology has concentrated on the estimation of genetic (haplotype) main effects. Most methods accounted for environmental and gene–environment interaction effects by using prospective-type analyses that may lead to biased estimates when used with case–control data. Several recent publications addressed the issue of retrospective sampling in the analysis of case–control genetic data in the presence of environmental factors by developing efficient semiparametric statistical methods. This article describes the new Stata command haplologit, which implements efficient profile-likelihood semiparametric methods for fitting gene–environment models in the very important special cases of a rare disease, a single candidate gene in Hardy–Weinberg equilibrium, and independence of genetic and environmental factors.

Abstract.Local polynomial regression is a generalization of local mean smoothing as described by Nadaraya (1964) and Watson (1964). Instead of fitting a local mean, one instead fits a local pth-order polynomial. Calculations for local polynomial regression are naturally more complex than those for local means, but local polynomial smooths have better statistical properties. The computational complexity may, however, be alleviated by using a Stata plugin. In this article, we describe the locpoly command for performing local polynomial regression. The calculations involved are implemented in both ado-code and with a plugin, allowing the user to assess the speed improvement obtained from using the plugin. Source code for the plugin is also provided as part of the package for this program.

Abstract.Local polynomial regression is a generalization of local mean smoothing as described by Nadaraya (1964) and Watson (1964). Instead of fitting a local mean, one instead fits a local pth-order polynomial. Calculations for local polynomial regression are naturally more complex than those for local means, but local polynomial smooths have better statistical properties. The computational complexity may, however, be alleviated by using a Stata plugin. In this article, we describe the locpoly command for performing local polynomial regression. The calculations involved are implemented in both ado-code and with a plugin, allowing the user to assess the speed improvement obtained from using the plugin. Source code for the plugin is also provided as part of the package for this program.

With the release of Stata 7, the glm command for fitting generalized linear models underwent a substantial overhaul. Stata 7 glm contains an expanded array of variance estimators, regression diagnostics, and other enhancements. The overhaul took place to coincide with the release of Hardin and Hilbe (2001). With the new glm came a modular design that enables users to program customized link functions, variance functions, and weight functions to be used if Newey–West covariance estimates are desired. Because cases requiring customized link functions are the more prevalent in the literature, only those are considered here. We give two examples where a nonstandard link function is required: the relative survival model of Hakulinen and Tenkanen (1987)and a logistic model that accounts for natural response as described in Collett (2003). The relative ease (over previous versions of Stata) with which these alternate links can be programmed into glm is demonstrated.

Frailty models are the survival data analog to regression models, which account for heterogeneity and random effects. A frailty is a latent multiplicative effect on the hazard function and is assumed to have unit mean and variance θ, which is estimated along with the other model parameters. A frailty model is an heterogeneity model where the frailties are assumed to be individual- or spell-specific. A shared frailty model is a random effects model where the frailties are common (or shared) among groups of individuals or spells and are randomly distributed across groups. Parametric frailty models were made available in Stata with the release of Stata 7, while parametric shared frailty models were made available in a recent series of updates. This article serves as a primer to those fitting parametric frailty models in Stata via the streg command. Frailty models are compared to shared frailty models, and both are shown to be equivalent in certain situations. The user-specified form of the distribution of the frailties (whether gamma or inverse Gaussian) is shown to subtly affect the interpretation of the results. Methods for obtaining predictions that are either conditional or unconditional on the frailty are discussed. An example that analyzes the time to recurrence of infection after catheter insertion in kidney patients is studied.

Circular plates of variable thickness and elastically restrained against rotation along the edge resting on a Winkler‐Pasternak medium are addressed. Free and forced vibrations are studied using a very simple polynomial coordinate function and the Ritz method. In the case of simply supported and clamped plates of uniform thickness subjected to static loading the results are in very good agreement with values available in the open literature. The entire algorithmic procedure can be efficiently handled using a microcomputer.

The present paper deals with the solution of the title problem applying Lord Rayleigh’s optimization concept when solving integral equations by means of the Ritz method. Polynomial expressions containing a power‐law term with an undetermined exponent ‘‘γ’’ are used. Since the calculated eigenvalue constitutes an upper bound, by minimizing it with respect to γ, one is able to improve the value of the frequency coefficient. A lower bound is then determined using the method of traces. It is shown that both sets of results, upper and lower bounds, are quite close and are also in agreement with the numerical results obtained by means of a finite element algorithm.