33 research outputs found

    Assessing Moisture Content on the Surface of Mortar Samples from Hyperspectral Imaging

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    Hyperspectral imaging represents an electromagnetic spectrum for each pixel in the image of a structural surface. The characteristic wavelength of the spectrum at reflectance valleys or absorption peaks can be used as a spectral feature for certain chemical detection. In this study, spectral reflectance characteristics of mortar samples are extracted to assess the reduction of moisture on the surface of mortar samples during the cement hydration process. The test results indicate that the reflectance increases and the absorbance decreases because water is reacted and less light will be absorbed during the hydration process. The average absorbance between 1923 nm and 1983 nm in wavelength gradually decreases with the mortar curing time. This feature parameter can be used to evaluate the mortar hydration process

    Hyperspectral Image Analysis for Mechanical and Chemical Properties of Concrete and Steel Surfaces

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    According to the 2017 ASCE Report Card, 39% and 15% of 614,387 bridges in the U.S. are more than 50 years and 40 to 49 years, respectively. The number of deficient bridges is increasing. One of the most common causes of reinforced concrete deterioration is corrosion of steel reinforcing bars. Currently, most bridges are visually inspected every two years using boom/snooper trucks to get access to various areas to be inspected. The subjective visual inspection often leads to inconsistent results that are less useful in bridge management. Hyperspectral camera, installed on an unmanned aerial vehicle, can potentially supplement visual inspection with quantifiable and reliable imagery from remote and safe operations. It can be used to identify physical characteristics (e.g., concrete cracks)and characterize chemical features (e.g., steel corrosion)

    Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

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    Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

    Hyperspectral Imaging Features for Mortar Classification and Compressive Strength Assessment

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    In this study, hyperspectral imagery with two computational algorithms are proposed to classify the type of mortar and assess the in-situ strength of fresh mortar in near real time. Each scanning on a mortar surface includes 30 spatial pixels selected for analysis, each assigned with a light reflectance spectrum over 400-2500 nm. Three groups of mortar samples with a water-to-cement (W/C) ratio of 0.6, 0.5 and 0.4, respectively, were cast and scanned from Day 1 to 14 of curing. Reflectance data at a wavelength range of 1920 nm to 1980 nm, associated with the O-H chemical bond, were extracted and averaged to classify the different mortar types with K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms and to predict their compressive strength from a regression equation. The results showed that the average reflectance increased with time due to water molecules reaction during curing process. The KNN classification model with K = 5 had a prediction accuracy of 70% to 75%, and the SVM classification model with C = 1000 and σ = 10 showed a prediction accuracy of approximately 90%. Therefore, the SVM classification algorithm is recommended for use in mortar classification. The compressive strength is well correlated with the average reflectance with a coefficient of over 0.98

    Biochar Enhances Soil Resource Availability and Suppresses Microbial Metabolism Genes in the Rhizosphere of Wheat

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    Despite the well-documented role of biochar in promoting soil quality and crop productivity, the underlying biological mechanisms remain poorly understood. Here, we explored the effects of straw biochar on soil microbiome in the rhizosphere from wheat using metagenomic sequencing. Our results showed that straw return decreased the yields of wheat, while the straw biochar return increased the wheat yields. Further, both the richness and community composition confirmed different effects of the straw return and straw biochar return. The straw biochar return also resulted in greater rhizosphere effects from wheat, represented by resource availability, including soil organic carbon, soil total nitrogen, available phosphorus, and available potassium. The rhizosphere effects from wheat, represented by microbial metabolism genes involved in carbon, nitrogen, phosphorus, and potassium cycling, however, were decreased by straw biochar returning. In addition, the rhizosphere effects from nitrogen content and the nitrogen cycling genes showed negative relationships with wheat yields. Together, these results revealed that straw biochar enhanced soil resource availability but suppressed microbial metabolism genes in the rhizosphere from wheat, supporting the idea that straw biochar serves as a nutrient pool for crops
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