| Keyword search (4,163 papers available) | ![]() |
"Mixture" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | Trajectories of Alcohol-Related Problems Among First-Year Nursing Students: Nature, Predictors, and Outcomes | Cheyroux P; Morin AJS; O' Connor RM; Colombat P; Vancappel A; Eltanoukhi R; Gillet N; | 41797206 PSYCHOLOGY |
| 2 | Scientists warning: we must change paradigm for a revolution in toxicology and world food supply | Seralini GE; Jungers G; Andersen A; Antoniou M; Aschner M; Bacon MH; Bertrand M; Bohn T; Bonfleur ML; Bücking E; Defarge N; Djemil R; Domingo JL; Douzelet J; Fagan J; Fournier T; Garcia JLY; Gil S; Hervé-Gruyer P; Hilbeck A; Hilty L; Huber D; Joyeux H; Khan I; Kouretas D; Lemarchand F; Loening U; Longo G; Mesnage R; Nikolopoulou DI; Panoff JM; Parente C; Robinson C; Scherber C; Sprangers D; Sultan C; Tsatsakis A; Vandelac L; Wan NF; Wynne B; Zaller JG; Zerrad-Saadi A; Zhang X; | 41551494 CHEMBIOCHEM |
| 3 | Optimizing Mixtures of Metal-Organic Frameworks for Robust and Bespoke Passive Atmospheric Water Harvesting | Harriman C; Ke Q; Vlugt TJH; Howarth AJ; Simon CM; | 41427123 CHEMBIOCHEM |
| 4 | Deep clustering analysis via variational autoencoder with Gamma mixture latent embeddings | Guo J; Fan W; Amayri M; Bouguila N; | 39662201 ENCS |
| 5 | Developmental heterogeneity of school burnout across the transition from upper secondary school to higher education: A 9-year follow-up study | Nadon L; Morin AJS; Gilbert W; Olivier E; Salmela-Aro K; | 39645324 PSYCHOLOGY |
| 6 | Self-consolidating concrete: Dataset on mixture design and key properties | Amine El Mahdi Safhi | 38533116 ENCS |
| 7 | Unsupervised Mixture Models on the Edge for Smart Energy Consumption Segmentation with Feature Saliency | Al-Bazzaz H; Azam M; Amayri M; Bouguila N; | 37837127 ENCS |
| 8 | Entropy-Based Variational Scheme with Component Splitting for the Efficient Learning of Gamma Mixtures | Bourouis S; Pawar Y; Bouguila N; | 35009726 ENCS |
| 9 | Mixtures of rare earth elements show antagonistic interactions in Chlamydomonas reinhardtii | Morel E; Cui L; Zerges W; Wilkinson KJ; | 34175518 BIOLOGY |
| 10 | BioMiCo: a supervised Bayesian model for inference of microbial community structure. | Shafiei M, Dunn KA, Boon E, MacDonald SM, Walsh DA, Gu H, Bielawski JP | 25774293 BIOLOGY |
| Title: | Self-consolidating concrete: Dataset on mixture design and key properties | ||||
| Authors: | Amine El Mahdi Safhi | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/38533116/ | ||||
| DOI: | 10.1016/j.dib.2024.110256 | ||||
| Publication: | Data in brief | ||||
| Keywords: | Experimental data; Mixture design; Rheology; Self-consolidating concrete; Workabily; | ||||
| PMID: | 38533116 | Category: | Date Added: | 2024-03-27 | |
| Dept Affiliation: |
ENCS
1 Concordia University, Gina Cody School of Engineering and Computer Science, Montreal, Canada. |
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Description: |
This manuscript delineates the assembly and structure of an extensive dataset encompassing more than 2500 self-consolidating concrete (SCC) mixtures, meticulously compiled from 176 scholarly sources. The dataset has been subjected to a thorough curation process to eliminate feature redundancy, rectify transcriptional inaccuracies, and excise duplicative entries. This refinement process has culminated in a dataset primed for advanced data-driven inquiries within the SCC research domain, marking a novel contribution to the field. The dataset serves as a robust foundational resource, poised for subsequent augmentations and stringent applications in data-centric studies. It facilitates a detailed characterization of SCC properties, potentially through the implementation of machine learning algorithms, or serves as a comparative benchmark to assess the performance across diverse SCC formulations. In conclusion, the dataset serves as a crucial resource for scholars engaged in studying SCC and similar substances. It offers deep insights into the ecological benefits of substituting conventional Portland concrete with SCC alternatives. This compilation not only advances the understanding of SCC properties but also contributes to the broader conversation about sustainable construction practices. |



