7 research outputs found

    Development and Evaluation of a Portable Device for Measuring Curling and Warping in Concrete Pavements

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    Portland cement concrete (PCC) pavement undergoes repeated environmental load-related deflection resulting from temperature and moisture variations across pavement depth. This has been recognized as resulting in PCC pavement curling and warping since the mid-1920s. Slab curvature can be further magnified under repeated traffic loads and may ultimately lead to fatigue failures, including top-down and bottom-up transverse, longitudinal, and corner cracking. It is therefore significant to measure the “true” degree of curling and warping in PCC pavements, not only for quality control (QC) and quality assurance (QA) purposes, but also for better understanding of its relationship to long-term pavement performance. Although several approaches and devices—including linear variable differential transducers (LVDTs), digital indicators, and some profilers—have been proposed for measuring curling and warping, their application in the field is subject to cost, inconvenience, and complexity of operation. This research therefore explores developing an economical and simple device for measuring curling and warping in concrete pavements with accuracy comparable to or better than existing methodologies. Technical requirements were identified to establish assessment criteria for development, and field tests were conducted to modify the device to further enhancement. The finalized device is about 12 inches in height and 18 pounds in weight, and its manufacturing cost is just $320. Detailed development procedures and evaluation results for the new curling and warping measuring device are presented and discussed, with a focus on achieving reliable curling and warping measurements in a cost-effective manner.For more information, please visit the Institute for Transportation at http://www.intrans.iastate.edu/ </p

    Construction and Validation of a Ferroptosis-Related Prognostic Model for Gastric Cancer

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    Background. Gastric cancer (GC), an extremely aggressive tumor with a very different prognosis, is the third leading cause of cancer-related mortality. We aimed to construct a ferroptosis-related prognostic model that can be distinguished prognostically. Methods. The gene expression and the clinical data of GC patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). The ferroptosis-related genes were obtained from the FerrDb. Using the “limma” R package and univariate Cox analysis, ferroptosis-related genes with differential expression and prognostic value were identified in the TCGA cohort. Last absolute shrinkage and selection operator (LASSO) Cox regression was applied to shrink ferroptosis-related predictors and construct a prognostic model. Functional enrichment, ESTIMATE algorithm, and single-sample gene set enrichment analysis (ssGSEA) were applied for exploring the potential mechanism. GC patients from the GEO cohort were used for validation. Results. An 8-gene prognostic model was constructed and stratified GC patients from TCGA and meta-GEO cohort into high-risk groups or low-risk groups. GC patients in high-risk groups have significantly poorer OS compared with those in low-risk groups. The risk score was identified as an independent predictor for OS. Functional analysis revealed that the risk score was mainly associated with the biological function of extracellular matrix (ECM) organization and tumor immunity. Conclusion. In conclusion, the ferroptosis-related model can be utilized for the clinical prognostic prediction in GC
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