King Fahd Security College

Surgery is a well-known trigger of Diabetes Ketoacidosis, DKA. Post-surgical DKA is poorly studied in the current literature. This study investigated post-surgical DKA association with poor glycemic control before surgery. Unmatched case–control study sampling all post-surgical DKA cases admitted to ICU during the period from 1st of March 2019 to 1st of December 2022 in King Saud Medical City, Riyadh, Saudi Arabia. The control group comprises all other adult post-surgical subjects admitted to ICU without DKA during the same period. Poor glycemic control was considered when the glycosylated hemoglobin, HbA1C, was equal to or more than 7%. Details of surgery were collected from patients’ records. Fifty-seven post-surgical DKA cases were included and the control group consists of 114 subjects. Poor glycemic control was more frequent among postoperative DKA cases with a statistically significant difference (OR 48.2 95% CI: 12.1 – 267.4; p value < 0.001). Sensitivity analysis of fifty-four pairs of cases and controls matched for age and sex had odds ratio of 48.6 (95% CI: 12.1 – 267.4, p < 0.001). Multivariable logistic regression was done for independent predictor of postoperative DKA. Intraoperative catecholamine and insulin usage along with prolonged duration of surgery were statistically significant predictors (p values < 0.05). Post-surgical DKA was ascribed to poor glycemic control. The usage of catecholamine during surgery associated with postsurgical DKA and should be considered in future research.

This study evaluates the dynamic changes in the quantity and quality of neutrophil-derived cell-free DNA (cfDNA) in whole blood and plasma samples from severe thermal and traumatically injured patients. Neutrophil-derived cfDNA, a component of neutrophil extracellular traps (NETs), is released during immune responses to injury and infection. Excessive NET formation mediates inflammation, tissue damage, and coagulopathy. Increased cfDNA levels in burn and trauma patients are reported to be associated with poor clinical outcomes, indicating their potential as biomarkers for predicting sepsis and MODS. Blood samples were obtained from two cohorts of burns (n = 96) and trauma (n = 147) patients. Neutrophil-derived cfDNA was quantified in plasma by SYTOX Green fluorescence and the size of extracted DNA was measured by electrophoresis. A microfluidic assay was also performed to capture NET-derived chromatin from burn patients' fresh whole blood samples. Captured NETs were stained with SYTOX green and anti-citrullinated histone antibodies. Stimulated whole blood or isolated neutrophils from healthy controls were used to generate NETs as positive controls. Circulating cfDNA levels were significantly elevated in plasma from both burns (days 1-14 postinjury) and trauma patients (<1-72 hours) compared to healthy controls. Electrophoresis revealed a prominent nucleosome band (~150 base pairs) in both burns and trauma plasma, with nucleosome oligomers detected within ultra-early samples (<1-hour posttrauma). The density of nucleosome bands correlated with cfDNA concentrations. Microfluidic capture of circulating NET-derived chromatin demonstrated increased levels in whole blood from burns, particularly at day 1 postinjury. NET-derived chromatin, cfDNA, and nucleosomes are elevated following severe burns and trauma. The dynamic changes in cDNA support their contribution to inflammation and as a key biomarker.

This study evaluated cephalometric changes in Class II malocclusion patients treated with expansion versus extraction in a Saudi Arabian sample. Data from 90 orthodontic patients meeting strict eligibility criteria were collected from multiple private practices in Saudi Arabia. The sample was divided according to treatment modality: Group 1 consisted of patients treated with four premolar extractions (n = 45), and Group 2 included patients treated with maxillary expansion using a banded rapid palatal expander (RPE) supported by mini-screws (n = 45). Nasolabial angle (NLA) for extraction cases presented a statistically significant difference in post-treatment radiographs (mean difference: -3.07 ± 8.92, P = 0.030) and significant changes in all dental variables (e.g., upper incisor position to A–Pog [UI-APog] pre-treatment mean difference: 4.49 ± 3.89; P < 0.001). In pre-treatment radiographs, only the position of the upper incisor to A-Pog showed a considerable difference (11.27 ± 4.19 vs. 8.83 ± 3.00, P = 0.017). Cases treated with RPE reported significant changes in the lower lip thickness (mean difference: -1.02 ± 2.20, P = 0.028). Cases treated with extraction had a greater influence on the dental component than on the soft tissue. In contrast, expansion cases showed a slight impact dentally but a greater effect on soft tissue parameters. However, neither treatment modality resulted in significant skeletal changes.

Recent exponential growth in Internet connectivity has triggered an equal surge in cyber threats while FTP brute force attacks present an important security threat to networks. Repeated authentication attempts form the basis of these attacks while IDS rule-based systems fail to detect them. The proposed study introduces an advanced machine learning (ML)-based framework which employs CSE-CIC-IDS2018 benchmark dataset to precisely detect FTP brute force attacks. This research study evaluates three machine learning classifiers known as Random Forest and Logistic Regression and Isolation Forest through three feature selection techniques that consist of Chi-Square, Correlation-based Feature Selection (CFS) and Recursive Feature Elimination (RFE). Model generalization received improvement through the implementation of Synthetic Minority Over-sampling Technique (SMOTE due to its ability to reduce class imbalance. Experimental outcomes revealed that Random Forest together with Logistic Regression generated accuracy and precision scores to recall and F1 scores above 99.9% which confirms their suitability for real-time intrusion detection systems. Model inference using Logistic Regression with Chi-Square achieved the fastest speed of 0.09s which establishes it as an optimal trade-off between processing time and performance outcomes. Isolation Forest displays limited effectiveness in regard to precision and recall performance during supervised evaluation. This research developed an optimized machine learning solution that specifically identifies protocol attacks through decision borders while demonstrating the importance of choosing proper features for enhancing IDS performance against FTP brute force threats.

This study investigates the impact of open banking initiatives on e-service quality in Saudi Arabian banks. Using a quantitative approach, we surveyed 513 bank customers to assess changes in perceived e-service quality following the implementation of open banking. The study employs an extended E-S-QUAL model, incorporating dimensions specific to open banking. Results indicate that open banking initiatives significantly enhance e-service quality, particularly in the areas of efficiency, system availability, and innovation. However, challenges remain in privacy and security perceptions. This research contributes to the understanding of technology-driven banking innovations in emerging markets and provides practical implications for banks and regulators in Saudi Arabia and similar contexts. Keywords: open banking, e-service quality, Saudi Arabia, financial technology, E-S-QUAL

Purpose Business and operational excellence models are frequently employed by organisations as self-assessment tools for ensuring continued performance improvement. This paper presents an integrated methodology for excellence self-assessment that is applicable at organisational and functional levels. Design/methodology/approach The self-assessment methodology was sequentially developed, based on a theoretical and practical perspective, and a case study was presented. Findings This study develops: (1) a framework of excellence enablers and results criteria for each of the organisational, functional (core and supportive processes) and operational levels; (2) a framework of the characteristics of maturity levels of excellence according to enablers, results, organisational context, in addition to other assessment components; (3) a framework of the assessment and improvement steps for achieving excellence. Originality/value Although several proposed methodologies are available for the self-assessment of business and operational excellence, these only partially focus on various organisational aspects (such as the organisational and functional level, and organisational context) and are primarily used as business excellence models by non-large organisations. This study aims to fill the research gap in this regard.

Surface enhanced Raman spectroscopy (SERS) is a sensitive analytical technique that has been widely utilised for detection of trace levels of organic species. The detection of trace levels of poor vapour pressure molecules such as explosives is a critical challenging due to the low concentration of adsorbed molecules on the surface sites of the SERS substrate. In this work, gold nanorods were fabricated with analyte samples and provided highly sensitivity of SERS detection along with low limit-of-detection (LOD) for explosives down to pM of 2,4- dinitrotoluene (DNT) and nM of both 2,4,6-trinitrotoluene (TNT) and 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) with highly specificity. The sensitivity of the detection was developed by optimising the adsorption of the molecules on nanorods sites, where nanorods and analyte solution were mixed followed by rigorous stirring. This procedure allowed extra molecules to be adsorbed on the nanorods surface, thus, high SERS enhanced has been observed with high specific identification of target probes. This approach showed a powerful method for rapid detection of explosives based SERS technique especially for illicit samples, where the enhancement factor calculated for analytes was in the range 3.17×108 to 2.69×1011.

Metal-organic frameworks (MOFs), a material known for its multifunctionality, chemical stability, and high surface area, are now commonly utilized as an adsorbent for water treatment. The MOF (MIL-88(Fe)-NH₂) was synthesized and used to remove the commonly used toxic herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) from water. The MIL-88(Fe)-NH₂ MOF was fully characterized using multiple techniques. A systematic investigation was conducted to evaluate the key parameters that impact the adsorption process, which include coexisting anions, adsorbent dosage, and solution pH. The adsorption isotherm was fitted using the Langmuir model, while the kinetics were fitted using pseudo-second-order. The adsorption process was both chemisorption and endothermic. The capacity for adsorption increased with rising temperatures. The MIL-88(Fe)-NH₂ adsorbent has a maximum adsorption capacity of 345.25 mg g^-1 for removing 2,4-D, significantly higher than previous adsorbents used for this purpose. The adsorption mechanism could be ascribed to hydrogen bonding, pore filling, π-π conjugations between the 2,4-D molecules and the MIL-88(Fe)-NH₂ adsorbent, and electrostatic interactions. Furthermore, the adsorption capacity of MIL-88(Fe)-NH₂ adsorbent showed only a slight decrease after five successive recycles, and it could be easily regenerated through solvent washing. When used in environmental water samples, especially those containing electronic wastes, the MIL-88(Fe)-NH₂ adsorbent demonstrated satisfactory adsorption capacity and reusability. The MIL-88(Fe)-NH₂ adsorbent is more practical and reusable and has better adsorption capacity and shorter equilibrium time compared to previously reported adsorbents.