Analyses of debonding along interfaces and of the kinking of interface cracks into a fiber have been used to define the role of debonding in fiber‐reinforced, brittle matrix composites. The results reveal that, for fibers aligned with the tensile stress axis, debonding requires an interface fracture energy, Γ i , less than about one‐fourth that for the fiber, Γ f . Further‐more, once this condition is satisfied, it is shown that fiber failure does not normally occur by deflection of the debond through the fiber. Instead, fiber failure is governed by weakest‐link statistics. The debonding of fibers inclined to the stress axis occurs more readily, such that debonds at acutely inclined fibers can deflect into the fiber, whereupon the failure of fibers is dominated by their toughness.
Delamination is considered for thin elastic films that are bonded to cylindrical substrates and subject to an equi-biaxial compressive pre-stress. Results for both positive and negative curvatures are obtained. The film buckles or deflects (depending on the sign of the curvature) away from the substrate inducing mixed mode stress intensities at the edge of the delamination. The energy release rate and combination of modal stress intensities at the delamination edges are determined. Steady-state propagation of delamination blisters is analyzed for both axial and circumferential propagation directions. The results depend strongly on the substrate curvature. Circumferential propagation is suppressed when the curvature is negative, but is favored when the curvature is positive. Axial propagation can occur for both positive and negative curvature substrates.
Recent clinical studies have shown an association between temporomandibular disorders (TMD) and facial pain. The aim of this epidemiological study was to investigate the prevalence of facial pain and TMD, their relation to each other, and also their relation to previous traumas, occlusal factors and pain in other areas of the body. The study is a part of the Well-Being and Health Research of the Northern Finland Birth Cohort 1966 using questionnaires where data on facial pain, TMD symptoms, occlusal divergencies, traumas in the face and other pain areas of the body were registered. Data were obtained from 5696 subjects born in the year 1966 in northern Finland. Twelve percent of the men and 18% of the women had suffered from facial pain during the last year. The most often reported symptom of TMD was clicking of the temporomandibular joints (TMJs) (21% in men, 28% in women), while prevalence of more severe symptoms was 13% or under. Facial pain was related to symptoms of TMD, as well as to traumas in the face or TMJs, distal occlusion and other pain areas (neck, shoulders, arms, lower back, jaws, tooth). The results suggest that facial pain is a usual symptom in adult population, and has an association with TMD, as well as with other musculoskeletal pain symptoms. Traumas to face and TMJs, certain occlusal factors and dental pathology may have a remarkable role in the etiology.
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTConformational Isomerism in 1-Substituted Derivatives of 3,3-DimethylbutaneGeorge M. Whitesides, John P. Sevenair, and Rudolph W. GoetzCite this: J. Am. Chem. Soc. 1967, 89, 5, 1135–1144Publication Date (Print):March 1, 1967Publication History Published online1 May 2002Published inissue 1 March 1967https://doi.org/10.1021/ja00981a019RIGHTS & PERMISSIONSArticle Views171Altmetric-Citations57LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (1 MB) Get e-Alerts Get e-Alerts
Sakkinen et al. (1) derived multiple factors of insulin resistance syndrome through factor analysis of 21 metabolic and hemostatic variables. They used orthogonal transformation (varimax rotation in SAS computer software) to rotate the factors in order to achieve clearer interpretability. Thus, the derived factors including body mass, insulin/ glucose, lipids, blood pressure, and so on are “uncorrelated.” While their approach is statistically sound, the logic is not consistent with the theory of insulin resistance syndrome, which postulates a common underlying biologic process for the close interrelation among obesity, hyperinsulinemia, glucose intolerance, dyslipidemia, and other metabolic disorders (2). There are substantial data that these components are all intercorrelated, both statistically and biologically. Thus, the “uncorrelated” factors identified from this study and several previous analyses may merely reflect a statistical artifact rather than a biologic reality. To test the clustering of the components as well as a unified mechanism that underlies various metabolic abnormalities, an alternative rotation method, an oblique rotation (promax rotation in SAS computer software), can be used to produce correlated factors (3). Then second-order factor(s) can be derived by factor analyzing the correlation matrix of the common factors obtained from the first step. This can also be achieved by confirmatory factor analysis (4), which is a theory-testing method as opposed to a datadriven method like explanatory factor analysis. This modelfitting procedure allows one to test the ability of the hypothesized factor structure to account for the observed covariance by examining the overall fit of the model. The analyses can be carried out using SAS PROC CALIS (5) or specialized computer programs, such as LISREL 8 (6). In addition, the confirmatory factor analysis procedure allows for a test of the equality of factor structure between different groups (e.g., male and female) by comparing the model fit of competing models with and without certain constraints on factor loadings (6).
