312 research outputs found

    Fan Performance Scaling With Inlet Distortions

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    Applications such as boundary-layer-ingesting fans, and compressors in turboprop engines require continuous operation with distorted inflow. A low-speed axial fan with incompressible flow is studied in this paper. The objectives are to (1) identify the physical mechanisms which govern the fan response to inflow distortions and (2) determine how fan performance scales as the type and severity of inlet distortion varies at the design flow coefficient. A distributed source term approach to modeling the rotor and stator blade rows is used in numerical simulations in this paper. The model does not include viscous losses so that changes in diffusion factor are the primary focus. Distortions in stagnation pressure and temperature as well as swirl are considered. The key findings are that unless sharp pitchwise gradients in the diffusion response, strong radial flows, or very large distortion magnitudes are present, the response of the blade rows for strong distortions can be predicted by scaling up the response to a weaker distortion. In addition, the response to distortions which are composed of non-uniformities in several inlet quantities can be predicted by summing up the responses to the constituent distortions

    Assessment of Composite Restorations and Their Unique Features in Forensic Identification of Unidentified Human Beings

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    Background: Dental identification mainly involves the comparison of antemortem and postmortem records. Keiser-Nielson (1980) recommended restored tooth surfaces as the smallest unit to consider in the comparison of dental restorations for identification purposes. Unique appearance of radiographic images of amalgam has led to their application in dental forensic. The present study aimed to investigate the value of composite restorations and their features in forensic identification.Methods: The antemortem sample included 40 periapical radiographs of anterior teeth with class III composite restorations which had been taken at least one year before the study. Ten randomly selected recent radiographs of the same subjects along with two radiographs from other patients were regarded as postmortem samples. Afterward, 12 dentally trained examiners were asked to match the 12 radiographs of group 2 with those of group 1 and to determine which features of the teeth (e.g. shape, contour, and surface) had helped them.Results: Ten examiners were able to correctly match all of the 12 images. According to kappa coefficient, the inter-rater agreement was high (0.8-1.0). The shape of the restoration was the most useful feature in identification.Conclusion: A composite restoration has a unique radiographic morphology that can be used for human identification. Therefore, if the antemortem radiograph of a single composite restoration is available, its comparison with a postmortem radiograph can help identify unidentified human beings

    A multi-stage machine learning model on diagnosis of esophageal manometry

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    High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its interpretation and classification includes an initial evaluation of swallow-level outcomes and then derivation of a study-level diagnosis based on Chicago Classification (CC), using a tree-like algorithm. This diagnostic approach on motility disordered using HRM was mirrored using a multi-stage modeling framework developed using a combination of various machine learning approaches. Specifically, the framework includes deep-learning models at the swallow-level stage and feature-based machine learning models at the study-level stage. In the swallow-level stage, three models based on convolutional neural networks (CNNs) were developed to predict swallow type, swallow pressurization, and integrated relaxation pressure (IRP). At the study-level stage, model selection from families of the expert-knowledge-based rule models, xgboost models and artificial neural network(ANN) models were conducted, with the latter two model designed and augmented with motivation from the export knowledge. A simple model-agnostic strategy of model balancing motivated by Bayesian principles was utilized, which gave rise to model averaging weighted by precision scores. The averaged (blended) models and individual models were compared and evaluated, of which the best performance on test dataset is 0.81 in top-1 prediction, 0.92 in top-2 predictions. This is the first artificial-intelligence-style model to automatically predict CC diagnosis of HRM study from raw multi-swallow data. Moreover, the proposed modeling framework could be easily extended to multi-modal tasks, such as diagnosis of esophageal patients based on clinical data from both HRM and functional luminal imaging probe panometry (FLIP)

    Preozonation and Prechlorination Effects on TOC Removal by Nanofiltration in Water Treatment

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    ABSTRACT: In this study, NF membrane was used for surface water treatment. The rejection of organic material, measured as Total organic carbon (TOC), by Nanofiltration was examined. The effects of application of pre-ozonation and pre-chlorination on TOC removal are discussed and their performances are compared with the performances of Nanofiltraion system without pretreatment process. In NF, natural organic rejection is high and no pre-treatment are required. Coagulation targets large hydrophobic organics which foul NF membranes by precipitation and gel layer formation. The results showed that TOC removal in Preozonation-coagulation was higher than prechlorinationCoagulation. In addition pretreatment increases Nanofiltration efficiency

    Heart Disease Is Associated With Anthropometric Indices and Change in Body Size Perception Over the Life Course. The Golestan Cohort Study

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    Background: Cardiovascular disease and obesity are now becoming leading causes of morbidity and mortality in low- and middle-income countries. Objectives: We investigated the relationship between prevalent heart disease (HD) and current anthropometric indices and body size perception over time from adolescence to adulthood in Iran. Methods: We present a cross-sectional analysis of baseline data from a prospective study of adults in Golestan Province, Iran. Demographics, cardiac history, and current anthropometric indices-body mass index, waist circumference, and waist to hip ratio-were recorded. Body size perception for ages 15 years, 30 years, and at the time of interview was assessed via pictograms. Associations of these factors and temporal change in perceived body size with HD were evaluated using multivariable logistic regression models. Results: Complete data were available for 50,044 participants; 6.1% of which reported having HD. Higher body mass index, waist circumference, and waist to hip ratio were associated with HD (p < 0.001). Men had a U-shaped relationship between HD and body size perception at younger ages. For change in body size perception, men and women demonstrated a U-shaped relationship with prevalent HD from adolescence to early adulthood, but a J-shaped pattern from early to late adulthood. Conclusions: HD was associated with anthropometric indices and change in body size perception over time for men and women in Iran. Due to the increasing prevalence of overweight and obesity in low- and middle-income countries, interventions focused on decreasing the cumulative burden of risk factors throughout the life course may be an important component of cardiovascular risk reduction. © 2015 World Heart Federation (Geneva)

    Association between co-authorship network and scientific productivity and impact indicators in academic medical research centers: A case study in Iran

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    <p>Abstract</p> <p>Background</p> <p>We aimed to examine the co-authorship networks in three successful Iranian academic research centers, in order to find the association between the scientific productivity and impact indicators with network features in a case study.</p> <p>Methods</p> <p>We searched for English articles of the three research centers. We drew co-authorship maps of each center and calculated social network measures.</p> <p>Results</p> <p>The collaboration networks in centers shared many structural features, including a "star-like" pattern of relations. Centers with more successful scientific profile showed denser and more cooperative networks. Key figures in each center were interviewed for their understandings of the reasons for the emergence of these patterns.</p> <p>Conclusion</p> <p>Star shape network structure and dependency on a single big member is a common feature observed in our case study. Scientific output measures correlate with the network structure of research centers. Network analysis seems a useful method to explore the subtle scientific contexts in research organizations.</p

    Verbal Autopsy: Reliability and Validity Estimates for Causes of Death in the Golestan Cohort Study in Iran

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    BACKGROUND: Verbal autopsy (VA) is one method to obtain valid estimates of causes of death in the absence of valid medical records. We tested the reliability and validity of a VA questionnaire developed for a cohort study in Golestan Province in northeastern Iran. METHOD: A modified version of the WHO adult verbal autopsy was used to assess the cause of death in the first 219 Golestan Cohort Study (GCS) subjects who died. The GCS cause of death was determined by two internists who independently reviewed all available medical records. Two other internists ("reviewers") independently reviewed only the VA answers and classified the cause of death into one of nine general categories; they repeated this evaluation one month later. The reliability of the VA was measured by calculating intra-reviewer and inter-reviewer kappa statistics. The validity of the VA was measured using the GCS cause of death as the gold standard. RESULTS: VA showed both good validity (sensitivity, specificity, PPV, and NPV all above 0.81) and reliability (kappa>0.75) in determining the general cause of death independent of sex and place of residence. The overall multi-rater agreement across four reviews was 0.84 (95%CI: 0.78-0.89). The results for identifying specific cancer deaths were also promising, especially for upper GI cancers (kappa = 0.95). The multi-rater agreement in cancer subgroup was 0.93 (95%CI: 0.85-0.99). CONCLUSIONS: VA seems to have good reliability and validity for determining the cause of death in a large-scale adult follow up study in a predominantly rural area of a middle-income country
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