Recent research suggests that when high concentration gradients (HCG) are present, resulting sharp density differences can cause the dispersive flux relationship to deviate from its classical Fickian form. This paper presents stable, upward, miscible displacement experiments conducted in two different types of porous media for a wide range of concentration differences between resident and displacing fluids. The considered groundwater velocities ranged from advection-dominated transport to velocities where the contribution of molecular diffusion is important, with the corresponding Peclet numbers ranging from 0.2 to 320. In addition to single component displacing fluids, mixtures consisting of multiple solutes were considered. The results of this study provide further evidence that classical Fick's law over-estimates the dispersion coefficient under HCG conditions. The decrease in the apparent dispersion coefficient is shown to be a nonlinear function of both concentration difference and groundwater velocity. This observation is attributed to gravitational effects at the sub-continuum scale which are not directly accounted for in classical variable density advection/dispersion models. Mixture experiments showed that the dispersive behaviors of individual components in a groundwater contaminant mixture are coupled.
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http://dx.doi.org/10.1016/j.jconhyd.2012.10.005 | DOI Listing |
Environ Sci Pollut Res Int
January 2025
Grupo de Investigación Materiales Con Impacto (Mat&Mpac), Facultad de Ciencias Básicas, Universidad de Medellín, Carrera 87 No. 30-65, 050026, Medellín, Colombia.
This study shows the efficiency of WH-C450, an adsorbent obtained from water hyacinth (WH) biomass, in the removal of sulfamethoxazole (SMX) from aqueous solutions. The process involves calcination of WH at 450 °C to produce an optimal adsorbent material capable of removing up to 73% of SMX and maximum SMX adsorption capacity of 132.23 mg/g.
View Article and Find Full Text PDFChempluschem
January 2025
Jiangsu Agri-animal Husbandry Vocational College, Department of Pharmacy, CHINA.
With enrichment of tetracycline (TC) in ecosystems, its accurate detection has become a major concern. Noble-metal nano-particles have attracted great interest as potential materials for sensing applications because of their remarkable electrical properties and adaptability. Herein, a novel electro-chemical detection technique based on carbon nano-tubes (CNTs) as the support material is developed to detect TC with high precision.
View Article and Find Full Text PDFEur J Drug Metab Pharmacokinet
January 2025
Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Ultimo, NSW, 2007, Australia.
Caffeine consumption is regarded as a widespread phenomenon, and its usage has continued to increase. In addition, the growing usage of antidepressants worldwide and increase in mental health disorders were shown in recent statistical analyses conducted by the World Health Organisation. The coadministration of caffeine and antidepressants remains a concern due to potential interactions that can alter a patient's response to therapy.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pharmacy, University of Miyazaki Hospital, 5200 Kihara, Kiyotake-cho, Miyazaki, 889-1692, Japan.
Intra-patient variability in immunosuppressive blood drug concentrations is a potential biomarker in managing organ transplant patients. However, the association between the time in therapeutic range of tacrolimus blood concentrations and its efficacy in preventing graft-versus-host disease remains unknown. In this study, we analyzed the relationship between the time in therapeutic range of tacrolimus blood concentrations and its efficacy in acute graft-versus-host disease prophylaxis in patients undergoing allogeneic hematopoietic stem cell transplantation.
View Article and Find Full Text PDFSci Rep
January 2025
Shenyang Institute of Computing Technology, Chinese Academy of Sciences, Shenyang, 110168, Liaoning, China.
The problem of ground-level ozone (O) pollution has become a global environmental challenge with far-reaching impacts on public health and ecosystems. Effective control of ozone pollution still faces complex challenges from factors such as complex precursor interactions, variable meteorological conditions and atmospheric chemical processes. To address this problem, a convolutional neural network (CNN) model combining the improved particle swarm optimization (IPSO) algorithm and SHAP analysis, called SHAP-IPSO-CNN, is developed in this study, aiming to reveal the key factors affecting ground-level ozone pollution and their interaction mechanisms.
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