ORCID Profile
0000-0002-2521-6508
Current Organisation
Durban University of Technology
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Publisher: MDPI AG
Date: 06-08-2020
DOI: 10.3390/W12082218
Abstract: The Gaza coastal aquifer (GCA) is the only source of water for about two million citizens living in Gaza Strip, Palestine. The groundwater quality in GCA has deteriorated rapidly due to many factors. The most crucial factor is the excess pumping due to the high population density. The objective of this article was to evaluate the influence of excess pumping on GCA’s salinity using 10-year predicted future scenarios based on artificial neural networks (ANNs). The ANN-based model was generated to predict the GCA’s salinity for three future scenarios that were designed based on different pumping rates. The results showed that when the pumping rate remains at the present conditions, salinity will increase rapidly in most GCA areas, and the availability of fresh water will decrease in disquieting rates by 2030. Only about 8% of the overall GCA’s area is expected to stay within 500 mg/L of the chloride concentration. Results also indicate that salinity would be improved slightly if the pumping rate is kept at 50% of the current pumping rates while the improvement rate is much faster if the pumping is stopped completely, which is an unfeasible scenario. The results are considered as an urgent call for developing an integrated water management strategy aiming at improving GCA quality by providing other drinking water resources to secure the increasing water demand.
Publisher: Cambridge University Press (CUP)
Date: 2022
DOI: 10.1017/S0950268822000541
Abstract: Using nested case–control data from the Lifelines COVID-19 cohort, we undertook a validation study of a clinical and genetic model to predict the risk of severe COVID-19 in people with confirmed COVID-19 and in people with confirmed or self-reported COVID-19. The model performed well in terms of discrimination of cases and controls for all ages (area under the receiver operating characteristic curve (AUC) = 0.680 for confirmed COVID-19 and AUC = 0.689 for confirmed and self-reported COVID-19) and in the age group in which the model was developed (50 years and older AUC = 0.658 for confirmed COVID-19 and AUC = 0.651 for confirmed and self-reported COVID-19). There was no evidence of over- or under-dispersion of risk scores but there was evidence of overall over-estimation of risk in all analyses (all P 0.0001). In the light of large numbers of people worldwide remaining unvaccinated and continuing uncertainty regarding vaccine efficacy over time and against variants of concern, identification of people at high risk of severe COVID-19 may encourage the uptake of vaccinations (including boosters) and the use of non-pharmaceutical inventions.
Publisher: EDP Sciences
Date: 2018
DOI: 10.1051/E3SCONF/20183402006
Abstract: Boron and organics maybe in high concentration during production of oil and gas, fertilizers, glass, and detergents. In addition, boron added to these industrial processes may require to be removed by the wastewater treatment plant. The preparation, characterization and application of iron oxide-activated carbon composite for removal of boron and COD was studied. The one variable at a time (OVAT) method was implemented to obtain desirable operating conditions (adsorbent dosage 5 g/L, reaction time 2 h, agitation speed 100 rpm, pH 5 for COD removal and pH 9 for boron removal). It was found that boron and organics present in a s le wastewater may require to be treated separately to remove the contaminants. The study achieved 97 and 70% for boron and COD removal, respectively. Adsorption as an alternative cheap source of treatment and its practicability for small communities is recommended as effective in removal of contaminants from river water.
No related grants have been discovered for Mohammed Seyam.