SACM - Australia
Permanent URI for this collectionhttps://drepo.sdl.edu.sa/handle/20.500.14154/9648
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Item Restricted Sex Differences in ICU Mortality and Prediction of Prolonged ICU Stay: A Study Using the MIMIC-III Critical Care Database(Saudi Digital Library, 2026) Asiri, Mohammed; Perez Concha, OscarBackground: Sex differences in critical illness outcomes remain contested after illness severity adjustment. Separately, early prediction of prolonged ICU stay has direct clinical utility for resource planning and discharge decision-making. Objectives: This study aimed to determine whether biological sex is independently associated with in-hospital mortality after adjusting for SOFA-based illness severity, comorbidity, and ICU case-mix, and to develop predictive models for prolonged ICU stay of five days or more using first-24-hour clinical features. Methods: The study used the MIMIC-III critical care database. Sequential multivariable logistic regression with multiple imputation by chained equations was applied to 31,000 adult first ICU admissions. For prediction of prolonged ICU stay, logistic regression, LASSO, Random Forest, and XGBoost models were evaluated on 26,729 patients using a stratified 70/30 train-test split. Results: Female sex was not independently associated with in-hospital mortality in the fully adjusted model (OR 1.11, 95% CI 0.99–1.25, p = 0.064). For prolonged ICU stay prediction, Random Forest achieved the highest AUROC (0.829) and the lowest Brier score (0.126), while XGBoost achieved the highest AUPRC (0.591). Mean Glasgow Coma Scale was the dominant predictor across models. Conclusion: Biological sex was not independently associated with in-hospital ICU mortality after adjustment for illness severity, comorbidity, and ICU case-mix. First-24-hour neurological status and oxygenation parameters were the strongest early predictors of prolonged ICU stay.8 0Item Restricted Exploring the Properties and Stabilisation of Nanoscale Metal Cluster/Overlayer Architectures(Saudi Digital Library, 2026) Asiri, Mohammed; Ebendorff-Heidepriem, HeikeThe shift from fossil fuels to renewable energy sources is a major focus in the global effort to reduce CO2 emissions, with photocatalytic hydrogen production being a promising approach for harvesting energy from sustainable energy sources. Photocatalysts absorb energy from sunlight to drive the water splitting reaction, producing H2. The deposition of a co-catalyst, such as noble metal clusters, can modify and improve the efficiency of the photocatalyst. Metal clusters, consisting of only a few atoms, have gained attention as co-catalysts due to their unique electronic and catalytic properties. However, maintaining their size and stability is challenging, as they tend to agglomerate into larger particles, losing their unique properties. Another challenge is the occurrence of the back reaction during photocatalysis, when H2 and O2 react to form water on the co-catalyst surface. The back reaction reduces the efficiency of photocatalytic water splitting. Atomic Layer Deposition (ALD) of thin metal oxide overlayers on cluster-modified photocatalysts offers a strategy to stabilise the clusters and suppress the back reaction. The self-limiting nature of ALD allows for deposition of an ultrathin overlayer with a controllable thickness. This thesis investigates how ALD-AlOx overlayers can be used to preserve the integrity of noble metal clusters, particularly Au clusters. It is examined how an ALD-AlOx overlayer grows on the surface of a photocatalyst formed by depositing Au clusters on TiO2 surfaces, as well as the distribution and stability of the clusters on the TiO2 surface before and after the ALD overlayer. The growth of ALD-AlOx overlayers on Au101/TiO2 was investigated as a model photocatalyst system to understand how the overlayer grows on the Au clusters and the TiO2 substrate. The investigation determines the overlayer thickness after applying several ALD cycles on a planar TiO2 substrate. The study demonstrated that the ALD-AlOx resulted in evenly deposited overlayers for the system of Au101/TiO2 with a slight tendency to be thicker on the Au cluster than on the TiO2. The layer thicknesses were found to be 2.0 Å, 3.5 Å, and 5.5 Å for 1, 5, and 10 ALD cycles, respectively. A comprehensive study of the stability of Au9(PPh3)8(NO3)3 deposited onto TiO2 by depositing an ultrathin overlayer of ALD-AlOx at various deposition temperatures, 25 °C, 100 °C, 150 °C, and 200 °C was conducted. It was found that ALD-AlOx stabilised Au9 clusters on the TiO2 surface across various temperatures. Notably, the phosphine ligands desorb during the ALD overcoating process at elevated temperatures, while the Au9 cores remained protected beneath the AlOx overlayer. The ALD-AlOx overlayer on Au metal clusters on TiO2 was studied by a combination of microscopic and spectroscopic techniques. It was revealed that the Au101 clusters were distributed randomly across the entire TiO2 surface. The roughness of the Au101/TiO2 system increases as the Au concentration increases, while ALD overcoating smooths the clusters, as the roughness was found to decrease, indicating a uniform coating on clusters by forming thicker overlayers on interstitial regions between clusters. This work provides an understanding of the role of ALD-AlOx overlayer on the stabilisation of Au metal clusters on TiO2 as a photocatalyst model system, with direct relevance of designing and improving photocatalytic water splitting for green hydrogen production.15 0Item Restricted Identification of groundwater flow patterns and barriers in aquifers(Saudi Digital Library, 2025) Asiri, Mohammed; Shelyag, Sergiy; Miller, TonyThe use of inverse methods has been increasing in hydrology. Numerical methods can help identify groundwater barriers and flow patterns in an aquifer, which can reduce errors when comparing the exact and estimated solutions. This thesis uses the method of characteristics (MOC) to identify transmissivity T in an area of abnormal region. From Darcy’s law for steady-state groundwater flow, we start with a one-dimensional case, which helps us consider what may and may not be in the two-dimensional case. Then we use the 2D case to calculate the stream function and find that the gradient of the stream function is orthogonal to the gradient of the head, and we use this when calculating the stream function everywhere. We use MODFLOW to generate head data for the known distribution T and to estimate T under different inflow examples. MOC gives a stable solution and can help identify the area of low T without requiring smoothness of the T distribution.23 0