Antibiotic-Resistant Bacteria and Resistance Genes in the Water–Food Nexus of the Agricultural Environment

Hong, Pei‐Ying

doi:10.1016/b978-0-12-801214-7.00016-8

Cited by 3 publications

(1 citation statement)

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“…A dose-response model is a sigmoidal model that has been extensively used in pharmaceutical and clinical industries to measure the cause and effect of drug, illness, death, and diseases [24]. For instance, Park et al [25] studied the treatment of tumor via radiotherapy exposure by using dose-response theory.…”

Section: Dose-response Modelmentioning

confidence: 99%

Fabrication and Model Characterization of the Electrical Conductivity of PVA/PPy/rGO Nanocomposite

et al. 2022

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Owing to the numerous advantages of graphene-based polymer nanocomposite, this study is focused on the fabrication of the hybrid of polyvinyl alcohol (PVA), polypyrrole (PPy), and reduced graphene-oxide. The study primarily carried out the experimentation and the mathematical analysis of the electrical conductivity of PVA/PPy/rGO nanocomposite. The preparation method involves solvent/drying blending method. Scanning electron microscopy was used to observe the morphology of the nanocomposite. The electrical conductivity of the fabricated PVA/PPy/rGO nanocomposite was investigated by varying the content of PPy/rGO on PVA. From the result obtained, it was observed that at about 0.4 (wt%) of the filler content, the nanocomposite experienced continuous conduction. In addition, Ondracek, Dalmas s-shape, dose–response, and Gaussian fitting models were engaged for the analysis of the electrical transport property of the nanocomposite. The models were validated by comparing their predictions with the experimental measurements. The results obtained showed consistency with the experimental data. Moreover, this study confirmed that the electrical conductivity of polymer-composite largely depends on the weight fraction of fillers. By considering the flexibility, simplicity, and versatility of the studied models, this study suggests their deployment for the optimal characterization/simulation tools for the prediction of the electrical conductivity of polymer-composites.

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Section: Dose-response Modelmentioning

confidence: 99%