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- Khan, Majid, et al.
(författare)
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Forecasting the strength of graphene nanoparticles-reinforced cementitious composites using ensemble learning algorithms
- 2024
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Ingår i: Results in Engineering (RINENG). - : Elsevier B.V.. - 2590-1230. ; 21
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Tidskriftsartikel (refereegranskat)abstract
- Integrating nanomaterials into concrete is a promising solution to improve concrete strength and durability. However, the intricacies of such nanoscale cementitious composites are highly complex. Traditional regression models encounter limitations in capturing these intricate compositions to provide accurate and reliable estimations. This study focuses on developing robust prediction models for the compressive strength (CS) of graphene nanoparticle-reinforced cementitious composites (GrNCC) through machine learning (ML) algorithms. Three ML models, bagging regressor (BR), decision tree (DT), and AdaBoost regressor (AR), were employed to predict CS based on a comprehensive dataset of 172 experimental values. Seven input parameters, including graphite nanoparticle (GrN) diameter, water-to-cement ratio (wc), GrN content (GC), ultrasonication (US), sand content (SC), curing age (CA), and GrN thickness (GT), were considered. The models were trained with 70 % of the data, and the remaining 30 % of the data was used for testing the models. Statistical metrics such as mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (R) were employed to assess the predictive accuracy of the models. The DT and AR models demonstrated exceptional accuracy, yielding high correlation coefficients of 0.983 and 0.979 for training, and 0.873 and 0.822 for testing, respectively. Shapley Additive exPlanation (SHAP) analysis highlighted the influential role of curing age and GrN thickness (GT), positively impacting CS, while an increased water-to-cement ratio (w/c) negatively affected CS. This study showcases the efficacy of ML techniques in accurately predicting CS of graphene nanoparticle-modified concrete, offering a swift and cost-effective approach for assessing nanomaterial impact on concrete strength and reducing reliance on time-consuming and expensive experiments.
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| 2. |
- Visser, Gerard H A, et al.
(författare)
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FIGO opinion paper: Drivers and solutions to the cesarean delivery epidemic with emphasis on the increasing rates in Africa and Southeastern Europe.
- 2023
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Ingår i: International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics. - 1879-3479. ; 163:Suppl 2, s. 5-9
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Tidskriftsartikel (refereegranskat)abstract
- Cesarean delivery rates are rapidly increasing in Southeastern Europe (to more than 60%), North Africa (with a rate as high as 72% in Egypt), and in urban areas in Southern Africa (a rate of over 50% in Lagos, Nigeria). Data on the background to these increases are scarce, but likely to include poor birthing facilities in general hospitals, convenience for the doctor, private medicine, fear of litigation, socioeconomic status, shortage of midwives and nurses, and disappearance of vaginal instrumental deliveries. Options to reverse cesarean delivery trends are discussed. In this context there is a need to be better informed about how women are being counseled regarding vaginal or cesarean delivery. The long-term consequences in subsequent pregnancies for mothers and children may well be largely ignored, while these risks are highest in LMICs where higher birth numbers are desired. FIGO has begun discussions with obstetric and gynecologic societies, healthcare bodies, and governments in several countries discussed in this article, to find ways to lower the cesarean delivery rate. The requests came from the countries themselves, which may prove beneficial in helping advance progress.
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