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Risk Factors of Mortality from All Asbestos-Related Diseases: A Competing Risk Analysis
Published 2017-01-01Get full text
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Modification of Recycled Industrial Solid Waste Incineration Fly Ash as a Low-cost Catalyst for NOx Removal
Published 2024-01-01“…Abstract Fly ash is solid waste from incinerators that contains complex compounds that have great potential to synthesize valuable materials. …”
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Efektivitas E-booklet Tentang ASI Eksklusif dalam Peningkatan Pengetahuan dan Sikap Ibu Hamil Trimester III
Published 2024-12-01Get full text
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Integration of fly ash and ground granulated blast furnace slag into palm oil fuel ash based geopolymer concrete: a review
Published 2024-09-01“…Palm oil fuel ash (POFA) contains abundant silicates and aluminates, making it well-suited for use as binder in geopolymer concrete. …”
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A case-matched series comparing functional outcomes for robotic-assisted unicompartmental knee arthroplasty versus functionally aligned robotic-assisted total knee arthroplasty
Published 2024-12-01“…Our aim was to compare outcomes from a case-matched series of robotic-assisted UKAs and robotic-assisted TKAs performed using FA. Methods: From a prospectively collected database between April 2015 and December 2019, patients who underwent a robotic-assisted medial UKA (RA-UKA) were case-matched with patients who had undergone a FA robotic-assisted TKA (RA-TKA) during the same time period. …”
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Effect of Fertilization with Ash from Biomass Combustion on the Fatty Acid Composition of Winter Rapeseed Oil
Published 2025-01-01“…The response to this challenge is a three-year field experiment (2018–2021) where the effect of fertilization with ash from forest biomass (approx. 70%) and agricultural biomass (approx. 30%), and soil type (Gleyic Chernozem and Haplic Luvisol), on the fatty acid (FA) profile of winter rape seeds (<i>Brassica napus</i> L. ssp. …”
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Machine learning-driven optimization for predicting compressive strength in fly ash geopolymer concrete
Published 2025-03-01“…Six different ML models—AdaBoost, Decision Tree, Extra Tree, Random Forest, Gradient Boosting, and Extreme Gradient Boosting were used to predict fc′ of fly ash-based geopolymer concrete.The results reveal that the AdaBoost model outperformed the other models, achieving R2 score of 0.80 and RMSE of 6.60. …”
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